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The role of DNA methylation in early detection and progression of pancreatic cancer

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The role of DNA methylation in early detection and progression of pancreatic cancer

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Content THE ROLE OF DNA METHYLATION IN EARLY DETECTION AND
PROGRESSION OF PANCREATIC CANCER

by

Shirley Oghamian

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOCHEMISTRY & MOLECULAR BIOLOGY)

May 2009

Copyright 2009 Shirley Oghamian
ii
Acknowledgments
Where does one begin in trying to thank all the people that have in one way or
another contributed to the success of this dissertation? First and foremost, I would like to
dedicate this work in its entirety to my mother Nora, father Roben, brother Shara and to
my boyfriend Emin. Thank you for teaching me hard work, sacrifice, patience,
persistence, love, respect, and gratitude. You have always encouraged me to do the best I
can and have told me countless times how proud you are. I think that you need to be very
proud of yourselves. Venturing to a new country more than 7,000 miles away from home
and all that is familiar just so that my brother and I could have the best education and
opportunity this world has to offer is heroic. Even though I was young when we left, I
still remember everything as if it happened yesterday. Because of your struggles in trying
to make ends meet, I grew up understanding sacrifice. You could have very easily stayed
behind and hoped that one day I would become someone that is an asset to society. But
you sold everything you had, packed your entire lives in four suitcases and left your
families behind. After more than two decades, I hope that you finally realize how much
of an impact you have had on my life and how much your strength has helped me get
through though times. I will be eternally grateful and hope that you are very proud of all
that you have accomplished.
To Emin: my best friend and the love of my life. Although you have only been
part of my life for two and a half years, you brought joy to not only me, but also my
family, friends and co-workers. Thank you for staying late at nights with me in the lab
and the occasional backrubs, which were very much needed. Your endless supply of
hugs, kisses, well wishes and friendship has been all that I could have ever asked for in a
iii
partner. I love you with all my heart and hope that we can have a long lasting life
together and admiration for one another.
To Zareh, Sona, and Areg: thank you for all that you have done for me. Thank
you for all the encouragement and accepting me into your family. And last but not least,
thank you for raising such a wonderful man.
To my Grandmother and all my Aunts, Uncles, Cousins, and friends: I would like
to thank you for setting great examples and always encouraging me to keep working
hard. I love each and every one of you and hope that I can one day be as helpful to you as
you have been to me.
Now let’s move to my family away from home. I would first like to thank Peter
and Ite for being great role models, both in the lab and in their personal lives. Although I
have learned a lot from you in the lab, the most valuable lessons came from the way you
raised your beautiful daughters and the solid relationship and friendship that you have
with one another. You are truly inspirational as scientists, parents, and partners in life. I
am thankful that my paths in life lead to you and hope that we can have a long lasting
friendship in the years to come.
To Kwang Ho: my dear colleague and one of my best friends. I never thought that
I could possibly have such a strong connection and a deep friendship with someone that I
work with. I still don’t understand how two people that are so opposite can get along so
well. You took it upon yourself to protect me from harm the past 6 years and defend me
when I needed it the most. You have inspired me to be a better person and have taught
me the essence of friendship. It was also fun when we got into fights with one
another…don’t you think?  I don’t know who is more stubborn. But all jokes aside, I
iv
hope that we have permanently integrated into each other’s life and that we won’t drift
away. We shared a lot of memories, both good and bad. However, it seems that I can only
remember the laughter. I love you, Opa. We definitely had a very special bond!
To my five lab sisters: Nicole, Sahar, Janice, Mel and Suhaida (oldest to
youngest). Wow, what a journey! What would I have done without you girls? You were
my backbone throughout the years and I hope that I can count on you for the rest of my
life. I don’t have a biological sister and I always wondered what it would be like to have
one. Now I understand it when people say that having a sister is one of the greatest things
in life. I loved all the talks we used to have in the office. If only those walls had ears.
To my four lab brothers: Dan, Martin, Toshi and Paul (oldest to youngest). In
continuation from the previous paragraph, it those walls had ears they would be bright
red. There definitely was no filter in anything we said. I know more about you than it is
legal for me to know. We laughed way more than we should have. Comic relief was very
much necessary! 
To my lab moms: Mihaela, Tiffany and Andrea. The most valuable lessons that I
learned came from you three. I learned how blessed I have been to have the life that I
have. I learned how difficult life could be, but somehow one finds the strength within to
pull themself up. You made me realized that not everything is black and white and that
there is a bit of gray in every situation (thanks, Tiffany). You made me realized what a
little bit of patience and selflessness could accomplish (thanks, Mihaela). Finally, the
hardest lessons that I learned in life sadly came from your misfortunes, Andrea. Although
you are no longer a member of the Laird lab, I think about you often and hope that the
best years of your life are in the near future.
v
Lastly, I would like to thank my committee members and all USC faculty who
have been a part of my life the past six years and for all the help and support. I definitely
would not be here if it weren’t for your generosity and inspiration. I will be eternally
grateful to all of you.

Peace, love, happiness and prosperity are everything that I wish for all of you!

Shirley

vi
Table of Contents

Acknowledgments ii
List of Tables ix
List of Figures x
Abstract xii

Chapter 1: Introduction – Pancreatic cancer 1
Introduction to Pancreatic Cancer 1
Introduction 1
Early Detection of Pancreatic Cancer 3
Use of Bodily Fluids for Cancer Detection 6
DNA Methylation and Pancreatic Cancer 7
DNA methylation 7
MethyLight 8
Identification of DNA Methylation Markers in Pancreatic Cancer 9

Chapter 2. Identification of a panel of DNA methylation markers
for the detection of pancreatic adenocarcinoma 12
Introduction 12
Materials and Methods 14
RNA and DNA Isolation from Tissue 14
Plasma and Serum Isolation from Blood 16
DNA Isolation from Plasma and Serum 17
DNA Isolation from White Blood Cells 17
DNA Methylation Analysis 17
M. SssI Treatment 18
Bisulfite Conversion 19
Illumina GoldenGate® 19
MethyLight 20
Digtial MethyLight 20
Statistical Analysis 21

vii

Results 21
Candidate Gene Approach 21
Marker Discovery Scheme 21
Counter Selection Using Controls 23
Validation of Markers on Independent Sample Set 27
Blood Analysis 30
Genome Wide Approach (Illumina® GoldenGate) 34
Marker Discovery Scheme 34
Validation of Illumina® Results and Counter Selection Using
Controls 39
Multiplexing 42
Validation of Markers on Independent Sample Set 44
Blood Analysis 46
Discussion 48

Chapter 3. The effects of in vivo modulation of DNA methylation
on tumorigenesis and progression of pancreatic acinar cell
carcinoma in a mouse model 51
Introduction 51
Materials and Methods 55
Dnmt1 Hypomorphic Mice 55
Apc
Min/+
Mice 55
Trp53
TJ/TJ
Mice 55
Generation of Triple Cross 55
Tail DNA Isolation Procedure 56
Genotyping 56
Beta-Catenin Immunohistochemistry 58
Histological Analysis 61
Statistical Analysis 61
Results 63
Breeding and Chi-Square Calculations 63
Histological Analyses 65
Tumor Multiplicity 67
Discussion 70

viii
Chapter 4. Studying CIMP in a mouse model of B-RAF
V600E

induced tumorigenesis 73
Introduction 73
Materials and Methods 76
Generation of the Transgenic Mouse 76
Tail DNA Isolation Procedure 78
Genotyping 78
RNA and DNA Isolation from Tissues 79
DNase Treatment of RNA Samples 81
Reverse Transcriptase cDNA Synthesis 81
Real-Time RT-PCR 81
M. SssI Treatment 82
Bisulfite Conversion 82
MethyLight 83
DNA Methylation analysis 83
Results 84
DNA Methylation Analysis of Liver Tissue Samples 86
Expression Study – B-RAF
V600E
89
Expression Study – Igfbp7 92
Discussion 95

Chapter 5. Discussion 100
Bibliography 104
Appendix 116
Supplemental Table 1 (Human MethyLight reactions) 116
Supplemental Table 2 (Mouse MethyLight reactions) 118
Supplemental Table 3 (OMA-003 Gene Names) 120
ix
List of Tables
Table 3.1 Primer and Probe Sequence for Genotyping 58
Table 3.2 Chi-Square Table of Progeny Generated from the Triple-Cross 64
Table 4.1 Genotyping Primer Sequence 79

x
List of Figures
Figure 2.1 Flow-Chart for Candidate Gene Approach 25
Figure 2.2 Heatmap of Top 7 Loci Using MethyLight 26
Figure 2.3 Complete Flow-Chart for Identfiication of Top 7 Markers 28
Figure 2.4 Validation of Top 7 Markers Using Independent Test Set 29
Figure 2.5 Digital MethyLight of Multiplexed Top Seven Markers Using Plasma 31
Figure 2.6 Comparison of Plasma versus Serum of PITX2 Using Digital
MethyLight 33
Figure 2.7 Supervised Hierarchical Analysis of Illumina GoldenGate® Data 35
Figure 2.8 Heatmap of Top 50 Loci Ranked Based on Illumina GoldenGate®
Data 38

Figure 2.9 MethyLight Validation of Illumina GoldenGate® Data 41
Figure 2.10 Multiplexing of Top 11 Loci Using M. SssI DNA 43

Figure 2.11 Validation of top 11 Loci Using Independent Sample St 45
Figure 2.12 Digital MethyLight of Top 11 Loci Using Plasma and Serum 47
Figure 3.1 Schematic Representations of the Structure of the Dnmt1 Hypomorphic
Allele 54

Figure 3.2 Schematic Representations of Triple-Cross and Tumor Burden Index 62

Figure 3.3 Histological Analysis Using H&E and Beta-Catenin IHC 66
Figure 3.4 Tumor Multiplicity and Area 69
Figure 4.1 Transgenic Construct for Fabp-BRAF
V600E
77
Figure 4.2 Livers from Transgenic Animal and Wildtype Littermate 85
Figure 4.3 MethyLight Analysis of Mouse Liver Tissue 87
Figure 4.4 Insm2 Methylation Level Using MethyLight 88
Figure 4.5 B-RAF
V600E
Expression in Liver from Line 4 and Line 5 91
xi
List of Figures
Figure 4.6 Igfbp7 Expression in Liver from Line 4 and Line 5 94

xii
Abstract
Cancer is the second leading cause of death in the United States and each year
nearly half a million Americans die of the disease. The high rate of mortality is often not
caused by tumors at the site of origin. In most cases, the spreading of tumor to distant
organs is the cause for multiple organ failure and ultimately death. Therefore, it is
imperative that tumors are detected early enough, where surgical intervention or
administration of chemotherapeutic agents can benefit the patient. Studies have shown
that cancers that are detected at early stage have far better prognosis than ones that are
detected at late stage. For this reason, a lot of attention is devoted to early detection of
cancer. However, some types of cancer, such as pancreatic cancer, arise at poorly
accessible sites and are therefore often diagnosed late with poor outcomes.
The focus of our research is to identify DNA methylation biomarkers that are
specific for pancreatic cancer and to utilize newly developed technology for detecting
these molecules in patient blood. We used both a candidate gene approach and a genome-
wide approach to identify novel differentially methylated loci for pancreatic cancer
detection. These techniques allowed us to identify a panel of markers that are methylated
in malignant pancreatic tumors but are either devoid of or show very low levels of
methylation in normal pancreas or benign pancreatic disease. The panel was then tested
using blood from patients who underwent surgical procedures for pancreatic tumor
resection. Current data demonstrates that detection of our top panel in patient blood is not
established and further experimentation is necessary to understand our limitations.
1
Chapter 1: Introduction - Pancreatic cancer, early detection of pancreatic cancer,
pancreatic cancer and DNA Methylation

Introduction to Pancreatic Cancer
Introduction
The American Cancer Society estimates that the lifetime risk for developing
cancer in men is slightly less than 1 in 2; for women, the risk is slightly higher than 1 in
3. In 2008, nearly 1.5 million Americans were diagnosed with cancer and slightly more
than half million died of the disease [93]. Survival outcomes generally depend on the
type of cancer an individual is being treated for and how early it was detected. Localized
tumors have far better outcome than those spread to distant organs. Therefore, it is
essential to undergo routine testing for early detection. Unfortunately, some cancers, such
as pancreatic cancer, do not have established programs for early detection.
The human pancreas is sometimes referred to as having two organs in one. It is
composed of an exocrine portion and an endocrine portion. Approximately 95% of all
pancreatic cancer cases occur in the exocrine pancreas in the form of pancreatic ductal
adenocarcinoma (PDAC). There are several other less frequent types of cancer of the
exocrine pancreas that include adenosquamous carcinomas, squamous cell carcinomas,
and giant cell carcinoma. Clinical and histopathologic studies have identified three PDAC
precursor lesions: Pancreatic Intraepithelial Neoplasia (PanIN), mucinous cystic
neoplasm (MCN), and intraductal papillary mucinous neoplasm (IPMN). The most
common and extensively studied is the PanIN, which is found in the smaller-caliber
pancreatic ducts. Recent advances have suggested that PanIN lesions are a common
finding in older individuals, occurring in as many as 30% of cases of autopsy studies and
2
surgical resection cases [32]. PanINs are staged from I to III, where stage III is the most
advanced and ultimately transform into PDAC [32]. Less common precursor lesions are
MCNs and IPMNs. MCNs are large mucin-producing epithelial cystic lesions with a
variable degree of epithelial dysplasia and focal regions of invasion [32]. IPMNs
resemble PanINs at the cellular level but grow into larger cystic structures [32].
Currently, population-based early detection for pancreatic cancer is not available.
Pap smears, mammograms, colonoscopy and PSA are great examples of population-
based screening programs that have yielded great success in decreasing mortality rates
and have contributed to the high five-year survival and relatively low mortality rates of
these cancers [93]. There is a strong correlation between the stage of disease at diagnosis
and survival rates for most types of cancer. The better the access to the organ or to its
secretions, the easier the opportunities for detecting early-stage cancer. Although the
pancreas is largely inaccessible, investigators have used aspiration of pancreatic juice as a
source of bodily fluid for the detection of both protein and DNA molecules [24, 45, 77,
112, 121]. However, obtaining pancreatic juice is an invasive procedure, therefore,
individuals who are not “at-risk” for developing pancreatic cancer would be less inclined
to undergo routine testing. A newer approach to cancer detection is to use systemically
available molecular markers that exhibit a cancer-specific change. The goal of this
research is to develop biomarkers that can be detected sensitively and specifically and
non-invasively in bodily fluid, such as blood.

3
Early detection of pancreatic cancer
Imaging studies, such as ultrasound or helical Computed Tomography (CT) and
Magnetic Resonance Imaging (MRI) are used to identify tumors. Endoscopic ultrasound
(EUS), which is approximately 90% sensitive, is another procedure that can aid in
visualization of the tumor and the fine-needle aspiration during the EUS procedure helps
in obtaining tissue for the purpose of biopsies and ultimately diagnosis [85]. Currently,
imaging is the main technology used on symptomatic individuals for the detection of
pancreatic cancer. The caveat with using imaging technology for early detection is that it
is not ideal as a population-based technique. It is very expensive and often not covered by
insurance without medical justification. In some cases, the imaging modalities may
indentify lesions that may never become cancerous, therefore contributing to over-
diagnosis bias.
As mentioned earlier, routine tests for early detection of pancreatic cancer are not
currently employed. In recent years, major efforts have been devoted to understanding the
histological and molecular changes that accompany different cancer types in early and
late stages. In particular, the identification of aberrant changes on the molecular scale has
been very helpful in trying to identify tumor biomarkers. The use of DNA, RNA and/or
protein as molecular indicators of disease has yielded varying success. For example,
DNA-based techniques aim to detect cancer-specific DNA alterations, such as mutations
to genomic DNA or CpG Island abnormal methylation. RNA-based detection methods
have been used to identify over-expressed genes in secondary fluids, such as
carcinoembryonic antigen (CEA) mRNA levels in blood samples from patients with
colorectal cancer, the detection of hTERT subunit of telomerase in pancreatic juice [40,
4
85, 97, 98]. Transcriptome analyses are usually carried out using cDNA and
oligonucleotide microarrays for the identification of over-expressed mRNAs in tumors
that can potentially be used as biomarkers. Lastly, protein based techniques are used to
identify protein deregulations in bodily fluids of cancer patients using two-dimensional
gel electrophoresis or mass spectrometry-based approaches such as MALDI-TOF or
SELDI-TOF.
With numerous pros and cons for each type of analyte, the most common
biomarkers have been proteins with aberrant levels of expression or DNA molecules
harboring known oncogenic mutations or extensive methylation at the promoter region.
To function as molecular markers in a screening test, these molecules must be detectible
in bodily fluids that are relatively easily accessible. If molecular markers that allow
detection of cancer are identified, they will require complementary highly sensitive
imaging methods such as abdominal CT scan to locate the cancer. If imaging
technologies are available, why would molecular markers benefit early detection
strategies? In the early stages, most individuals do not show signs or symptoms of the
disease. Imaging technologies are almost always used when there is a symptom or
discomfort at a defined location. Since full body imaging is not a common practice for
early detection of cancer, molecular markers can aid in routine initial screening
procedures.
About two decades earlier, an antigen referred to as CA19-9 emerged as a
potential biomarker for pancreatic cancer detection [52, 94]. However, CA19-9 is
commonly used to monitor response to therapy or recurrence of the disease. It is not
currently being used for the purposes of early detection because high levels of this protein
5
released into the blood are necessary for detection by methods currently available. When
the biomarker is consistently detectable in blood, the disease in most cases is no longer in
its early stages; therefore, the test is not recommended for routine screening purposes.
CA19-9 is also of limited value because approximately 10% to 15% of individuals who
have pancreatic cancer do not secrete this protein, and in some cases, clinicians observe
elevated levels of CA19-9 in patients with benign pancreatic disease [85]. In dealing with
biomarkers for disease detection, important parameters to consider are specificity and
sensitivity. These are measurements of how well a marker can detect true positive cases
(sensitivity) from true negative cases (specificity). Markers that have high rate of false
positives (low specificity), such as CA19-9, will not serve well for early detection.
Genetic and epigenetic markers have been more extensively investigated in
pancreatic juice than have protein markers [29]. There are several reasons why DNA-
based markers are favored over protein-based markers. Firstly, the levels of protein in
pancreatic juice of control individuals fluctuate markedly; therefore accurate
quantification of the proteins is necessary before normal levels of the protein are
established [29]. Secondly, the mere detection of genetic and epigenetic alterations can
often have diagnostic value. Finally, DNA molecules are easily amplifiable by PCR;
therefore minute amounts of genetically and epigenetically altered DNA can be detected
in ‘remote media’.
Who would benefit most from approaches to detect early pancreatic cancer?
Pancreatic cancer is largely sporadic and it is estimated that only 5-8% of cases are
associated with a familial predisposition [61, 62, 85]. Also, unlike other cancers such as
lung cancer, pancreatic cancer is essentially a disease of unknown etiology. Smoking is a
6
strong factor for the development of the lung cancer, whereas pancreatic cancer does not
strongly target a discrete population. Hence, population-based testing would be most
beneficial in saving lives.

Use of Bodily Fluids for Cancer Detection
Several studies have investigated the utility of bodily fluids for screening
asymptomatic populations to detect early stage cancers of various origins. Sputum,
bronchoalveolar lavage or blood have been used to isolate molecular markers for the
detection of lung carcinoma [81]. Urine has been used for the analysis of bladder cancer,
stool for colon cancer detection, nipple aspirates for the detection of breast malignancy,
pancreatic juice, serum, plasma and brush cytology for the detection of pancreatic cancer
and several others [65, 69, 80, 100]. It is known that fluids that originate directly from the
organ of interest are most abundant in analyte. However, obtaining such fluids is often
not trivial. In the case of pancreatic malignancies, a very small population of
asymptomatic individuals would be inclined to undergo procedures that extract pancreatic
juice. Due to the invasive nature of some of the early detection programs listed above, a
plethora of publications that described the use plasma and/or serum as sources of
circulating DNA molecules have surfaced. In our studies, we will attempt to identify
differentially methylated DNA molecules in patient plasma and serum.
The presence of circulating DNA molecules in blood is by no means indicative of
the presence of malignancy. Individuals with non-cancerous disease or even healthy
individuals have some levels of circulating free DNA in their blood. How these
molecules end up in the blood is a bit controversial but it is known that individuals with
7
metastatic cancer have higher concentrations of free DNA in the blood compared to non-
metastatic cancer patients compared to healthy individuals [57].
Several main mechanisms by which DNA is released into the blood have been
proposed. One such mechanism is simply the shedding of DNA from the tumor cells into
the lymphatic fluid, ultimately ending up in the bloodstream. Necrosis and apoptosis are
two main biological processes that contribute to the release of tumor DNA molecules into
the blood. During necrosis, as the tumor enlarges, the cells located in the inner core of the
tumor are often nutrient and oxygen deprived. The deprivation causes the cells to undergo
necrosis thereby releasing their DNA into the blood stream. The second process,
apoptosis, is a mechanism by which the cell undergoes programmed cell death due to
intrinsic or extrinsic signals. Intrinsic are the signals response to severe cellular stress
such as DNA damage and extrinsic signals arise when pro-apoptotic ligands bind to pro-
apoptotic receptors on the cell surface [1]. Finally, the involvement of blood vessels
originating from angiogenesis aid in the spread of micro-metastases of cancer cells into
the blood stream. It is believed that the infiltrating cells are lysed during the process and
the DNA is released into blood [8].

DNA Methylation and Pancreatic Cancer
DNA Methylation
Since the completion of the Human Genome Project, a considerable amount of
attention has been directed towards epigenetics in trying to understand the underlying
mechanisms of differential gene expression. Specialized enzymes, known as DNA
methyltransferases, are responsible for the modification of DNA by converting cytosine
8
immediately upstream of guanine (CpG dinucleotides) to 5-methylcytosine. This small,
yet powerful, modification is implicated in many important biological processes, such as
embryonic development, genomic imprinting, X-chromosome inactivation and silencing
of parasitic elements in the mammalian genome. Epigenetic DNA modifications take
place on cytosine residues in the context of CpG dinucleotides. In normal cells, most
CpG dinucleotides are methylated in repeat sequences and in CpG-poor regions of the
genome. However, CpG islands, which are clusters of CpG dinucleotides located at the 5’
regions of genes, are usually unmethylated. During the course of tumorigenesis, some of
these CpG islands become methylated and are associated with gene silencing. Aberrant
CpG island hypermethylation has been reported in many types of a malignancies and
benign pre-invasive lesions.

MethyLight
MethyLight is a high-throughput semi-quantitative methylation assay that utilizes
Real-Time TaqMan
®
-based technology, and relies on methylation specific primers and a
fluorescent probe that specifically anneal to methylated DNA sequences. Bisulfite-
converted DNA is used as a substrate in this assay. Treatment of DNA with sodium
bisulfite is utilized to convert unmethylated cytosines to uracil while leaving methylated
cytosines intact. The MethyLight primers and probes are designed assuming that all the
CpG located within the primer and probe set are methylated, and it usually covers 6-10
CpGs [16]. Each forward and reverse primer pair flanks a non-extendable probe. This
probe has a fluorescent dye reporter attached to the 5’ end (such as 6FAM) that is
suppressed by a quencher moiety, such as Black Hole Quencher (BHQ) located on the 3’
9
end of the probe. During PCR amplification, the 5’ to 3’ exonuclease activity of the Taq
DNA polymerase degrades the probe, and thus releases the fluorophore that can emit
light once no longer in close proximity of the quencher. The emitted fluorescence is
proportional to the amount of DNA amplified [16]. Other techniques such as Methylation
Specific Polymerase Chain Reaction (MSP) have been used to study the methylation
status of these loci [31]. However, the major drawback of MSP is that it is qualitative and
an endpoint analysis technique. With MethyLight, we are able to quantitatively assess the
methylation status of particular loci.

Identification of DNA Methylation Markers in Pancreatic Cancer
During pancreatic cancer development, numerous genes undergo abnormal
methylation, resulting in hypermethylation or hypomethylation [20]. The mechanism by
which abnormal methylation patterns are acquired during the course of tumorigenesis is
largely unknown. However, knowledge of the mechanism by which promoters undergo
hypermethylation is not vital for the identification of novel biomarkers.
Until very recently, the essential aspect of marker discovery was technology
limitation in the area of novel biomarker discovery. Technology that was capable of
identifying novel loci using non-candidate gene approach was imperative. Although new
studies were emerging with small numbers of novel genes that are differentially
methylated, the core genes for most studies were some of the best studied loci for
pancreatic cancer such as Cyclin D2, SOCS1, SPARC, ppENK, TSLC1, APC, FOXE1,
p16, RAR-β, RASSF1A, THBS1, CACNA1G, MLH1, CCDN2, HS3ST2, BNIP3, CDH13,
TFPI2, P53 and several others [13, 23, 37, 42, 50, 66, 78, 86, 90, 107, 108]. Many of
10
these genes are heavily methylated in a great portion of pancreatic cancers and therefore
can be applied for early detection using sophisticated technologies. Cyclin D2, FOXE1,
NPTX2, ppENK, p16, and TFPI2 have shown to be methylated in pancreatic juice from
patients that have pancreatic ductal adenocarcinoma using conventional MSP [65]. When
using Q-MSP using fluorescent probes and cut off of 1%, the sensitivity drops markedly
[65]. Since, specificity is very important for cancer detection, a panel of genes that are
capable of distinguishing cancer from normal with great accuracy is absolutely necessary.
Therefore, genome-wide approach, rather than a candidate gene approach needed to be
employed for marker discovery purposes.
Recent emergence of high-throughput technologies has paved the way for
identification of new epigenetic markers. Microarray-based and bead-array technologies
have been able to identify hundreds, or even thousands, of loci that are differentially
methylated [38, 79, 88, 121]. High-throughput and relatively inexpensive technology has
greatly facilitated epigenetic marker discovery. While much of the focus of early
detection efforts is on detecting differential DNA methylation differences in malignant
forms of the cancer, the more ambitious goal is to detect and treat precancerous lesions of
the pancreas and ultimately reduce the incidence of pancreatic cancer.
The identification of precancerous lesions is an important part of the strategy to
help cure individuals with an inherited predisposition or sporadic development of
pancreatic cancer. Currently, the only way to identify such lesions reliably is to surgically
resect the part of the pancreas containing the suspicious lesions and examine them
histopathologically. Differentially methylated loci identified using primary tumors could
be very useful in accurate diagnosis and possibly prognosis [27, 35, 36, 76, 80, 89]. As
11
mentioned earlier, invasive procedures, such as those including surgical steps, would not
be good early detection approaches for the population as a whole. Therefore, ideal
markers are those that are methylated in precancerous lesions but not in non-neoplastic
pancreatic tissue.
Identification of DNA methylation markers that arise during IPMN development
could facilitate differentiation of IPMN from non-neoplastic pancreatic cystic lesions
[35]. As suspected, aberrant DNA methylation increases with histologic grades of IPMN.
It has been demonstrated that low levels of methylation in normal duct cells are more
prevalent in patients with ductal neoplasia than in controls without ductal neoplasms and
may indicate the presence of a field of precancerous alterations [35]. However, because
of their size and their noninvasive nature, microscopic precancerous lesions (PanINs and
IPMNs) are likely to be refractory to detection using serum or plasma markers [29].
Pancreatic juice analysis is being investigated as a source for markers of pancreatic
neoplasia, analogous to other local diagnostic marker strategies such as sputum analysis
for lung neoplasia, cervical smears for cervical neoplasia diagnosis, stool marker analysis
to diagnose colorectal neoplasia, and nipple aspirates to improve the diagnosis of breast
neoplasia [29, 65].

12
Chapter 2: Identification of a panel of DNA methylation markers for the detection
of pancreatic adenocarcinoma

Introduction
Although pancreatic cancer is not very common, it has the highest mortality rate
of all major cancers. By the time of diagnosis, nearly half of the patients would have
detectable disease disseminated to distant organs, while a quarter will have detectable
local spread. The median survival rate of pancreatic cancer is three to six months after
diagnosis. The 5-year survival rate for pancreatic cancer is 5%. This rate measures the
percentage of individuals still alive 5-years after the cancer has been detected. The
etiology of pancreatic cancer is poorly understood. However, age, sex, race, smoking,
obesity, diabetes, chronic pancreatitis and family history are among the top risk factors
for the disease. For reasons that are not currently known, older individuals, males and
African Americans have higher probability of being diagnosed with pancreatic cancer
during their lifetime.
Pancreatic cancer is the fourth leading cause of cancer deaths in the United States
and the American Cancer Society estimates that 37,680 Americans were diagnosed with
pancreatic cancer in 2008, of which an estimated 34,290 died [93]. The lifetime risk of
developing pancreatic cancer is 1 in 76 (1.31%). Although it only affects 1% of the U.S.
population, it has the lowest five-year survival rate of all major cancers. The low survival
rate is attributable to its biologically aggressive behavior, chemotherapeutic resistance
and lack of good early detection technology. Also, due to its location and asymptomatic
nature, pancreatic cancer is often detected at later stages, when the disease has already
13
progressed towards metastasis. Only 10% of newly diagnosed individuals survive one
year after diagnosis. Therefore, early detection for pancreatic cancer is essential for
survival and overall decrease in mortality rate. Imaging studies, such as ultrasound or
abdominal Computed Tomography (CT) may be used to identify tumors. Endoscopic
ultrasound (EUS) is another procedure that can aid in visualization of the tumor and
obtaining tissue for the purpose of biopsies.
In the past several decades, major emphases have been placed on identification of
tumor specific biomarkers for the purpose of detecting cancer, both early and recurring.
Most biomarkers identified to date have been protein based, however, recent advances
have prompted the search for DNA based biomarkers, including aberrant DNA
methylation patterns. Advancements in technology for genome-wide discovery of
aberrant DNA methylation changes has led to a dramatic increase in the identification of
potential biomarkers for early detection of multiple cancers. These early detection
markers could potentially be used to detect cancer in the blood of “at-risk” individuals,
thus allowing physicians time for clinical intervention, if necessary.
There is a growing field of research for the identification of DNA methylation
based biomarkers for the detection of cancer, particularly pancreatic cancer.
Hypermethylation of CpG islands is a common mechanism by which tumor suppressor
genes are inactivated. Therefore, the methylation status of known tumor suppressor genes
was primary target for many analyses [22, 27, 35, 65, 77, 108]. Only in the recent years
has there been an attempt at the genome-wide identification of novel DNA methylation
markers. Methylated CpG island Amplification (MCA), Global expression changes using
demethylating agents coupled with expression Microarray, CpG Island tiling arrays and
14
most recently, bead-arrays [79, 88, 107]. The search for marker discovery has
demonstrated to be very robust, reproducible and the results can be validated using
alternative techniques. However, a big hurdle for the field of marker discovery is the
ability to detect the methylated DNA molecules in patient blood. In our studies, we
attempt to identify differentially methylated loci.
We have approached the marker discovery aspect of our research in two ways.
We first identified markers using a candidate gene approach where the methylation status
of genes that are already known to be differentially methylated in cancer were analyzed.
We also used advanced technologies in a genome-wide approach to identify novel
candidate makers for the detection of pancreatic cancer in blood. Relatively ‘recent’
advanced technology from Illumina® is capable of interrogating the methylation status of
1,505 CpG, which corresponds to approximately 807 genes. Illumina GoldenGate®
technology is a bead-array technology that utilizes both allele-specific and locus-specific
primers to target both methylated and unmethylated cytosine in the context of CpG
dinucleotides.

Materials and Methods
RNA and DNA Isolation from Tissue
Tumor specimens, obtained from USC Department of Surgery at the USC/Norris
Comprehensive Cancer Center in accordance with an approved IRB protocol and patient
consent, were used for the analyses. Approximately 35 mg of tumor was dropped into
1mL of TriZol® (Invitrogen Corporation Cat #15596-018) in a 50 mL falcon tube and
homogenized using an electric homogenizer. The contents were transferred into a 1.5 mL
15
eppendorf tube and spun at maximal speed for 3 minutes at room temperature. The
supernatant was recovered and placed in a clean 1.5 mL eppendorf tube while the pellet
was discarded. Chloroform was added at a volume of 200 µL per milliliter TriZol® used.
The contents were vortexed vigorously and allowed to sit on the bench top for 3 minutes
at room temperature. After the 3-minute period, the tubes were placed in a refrigerated
centrifuge and spun at 12,000g for 15 minutes at 4°C. After centrifugation, the aqueous
layer, which contains the RNA, is removed and placed in a clean 1.5mL eppendorf tube
and the bottom, organic layer, which contains the DNA is kept for later use or frozen if
not processed the same day.
To the aqueous layer, 500µL of isopropanol was added and the tube was inverted
gently several times to ensure proper mixing. The tube was then placed at -20°C for 1-2
hours. After the incubation period, the samples were spun at 12,000g for 10 minutes at
4°C. The supernatant was removed and discarded and the pellet was washed with 1mL of
75% ethanol/mL of TriZol® used. The sample was again spun at maximum speed for 5
minutes at 4°C. The supernatant was removed and discarded. Depending on the sized of
the precipitate, approximately 200µL of RNase free H2O was used to dissolve the pellet.
The sample was then placed in 80°C heat block for 5 minutes to dissolve the RNA and
evaporate residual ethanol contamination.
For DNA isolation, 300µL of 100% ethanol was added to the organic phase and
the tube was inverted several times until the solution was clear. The contents were spun
down at maximum speed for 5 minutes at 4°C. The organic phase (supernatant) was
removed and discarded and the pellet was washed with 1ml of 0.1M Sodium Citrate in
10% Ethanol/mL TriZol® used. The pellet with the sodium citrate buffer was vortexed
16
vigorously and allowed to incubate at room temperature for 30 minutes. After the 30-
minute incubation period, the samples were spun at maximum speed for 3 minutes at
room temperature. The supernatant was removed and the washing process with the
sodium citrate was repeated twice more. To the pellet, 1.5mL of 75% ethanol/mL of
TriZol® used was added to the tube and the tube was incubated at room temperature for
20 minutes with periodic vortexing. The samples were then spun at maximum speed for 5
minutes, supernatant was removed and 200 µL of TE was added to the pellet and placed
in 80°C for 10-15 minutes to allow rapid dissolving and evaporation of ethanol. The
tubes were then removed from the heat block and left at room temperature for 5-10
minutes to cool down. The contents were spun one last time at maximum speed for 5
minutes and the supernatant was transferred into a clean 1.5mL eppendorf tube, taking
care that the debris at the bottom of the tube is not transferred to the new tube. The
contents in the new tube are now ready for spectrophotometric measurements.

Plasma and Serum Isolation from Blood
Blood from individuals was drawn in accordance with approved IRB protocol.
Approximately 20 mL of blood was drawn into vials with and without EDTA for serum
and plasma, respectively. Blood in the vials without EDTA coating for the purpose of
serum isolation was allowed to coagulate at room temperature for 10-15 minutes.
However, blood in the vials with EDTA coating for the purpose of plasma isolation was
placed on ice immediately after draw. The EDTA and non-EDTA tubes were placed in a
centrifuge and spun at 1600 g for 10 minutes at room temperature. Serum from the vials
that did not have EDTA was aspirated and aliquots of 2.0 mL were made and
17
immediately placed in -80° C freezers until further use. Vials containing plasma were
processed further by removing as much plasma as possible without touching or disturbing
the Buffy coat. The plasma was then transferred to clean 2.0 mL screw cap tubes and
spun at 13,000 g for 10 minutes at 4° C. The Buffy Coat was gently removed and placed
in a clean 2.0 mL screw cap tube and frozen at -80° C until further use. After the 10
minutes spin, the plasma was removed from each tube, taking care the pellet was not
touched or disturbed, and placed in clean 2.0 mL screw cap tube and frozen at -80° C
until further use.

DNA Isolation from Plasma and Serum
Frozen serum and plasma tubes from the previous step were placed on ice and
allowed to thaw slowly. Approximately 1.0 mL of serum and plasma were used for the
DNA isolation step using QIAmp UltraSens Virus Kit (Cat No. 53704) from Qiagen per
manufacturer’s instructions. The entire DNA isolated from the samples was used in the
next step. No aliquots were made.

DNA Isolation from White Blood Cells
DNA was isolated using Qiagen, QIAmp DNA Blood Kit (Cat No. 51104).
Manufacturer’s instructions were followed.

DNA Methylation Analysis
Genomic DNA was isolated (see Materials and Methods – RNA and DNA
isolation from tissue) and subjected to bisulfite treatment (see Materials and Methods –
18
Bisulfite Conversion) followed by MethyLight analysis. The list of MethyLight reactions
is provided in Supplemental Table 1. MethyLight data is provided in the form of a ratio
using a standard curve to extrapolate the log value using the threshold C(t) value between
the methylated locus of interest and a methylation-independent normalization reaction. In
our studies, the methylation-independent reaction was ALU. At times the DNA samples
used could harbor chromosomal deletions and/or duplications, therefore single copy
normalization controls may not serve well. Also, due to variation in reaction performance
and other PCR parameters, it is necessary to normalize this ratio to the ratio obtained for
a constant reference sample; in our case M. SssI-treated DNA. The M. SssI-treated
reference sample is also used to generate the standard curve. The values are given as
Percentage Methylated Reference (PMR), which is 100 X (methylated reaction / control
reaction)
sample
/ (methylated reaction / control reaction)
M.SssI reference sample
. The
‘methylated reaction’ refers to the methylation measurement of the locus of interest and
the ‘control reaction’ refers to the methylation-independent measurement of ALU.

M. SssI Treatment
Peripheral blood leukocyte (PBL) DNA (Promega) as used as template for M.
SssI treament. PBL DNA at a concentration of 0.05 µg/µL was incubated with M. SssI
(New England Biolabs) at a concentration of 0.05 U/µL and 0.16 mM S-
adenosylmethionine overnight at 37° C. Two additional boost were added to the mixture
two consecutive days with extra S-adenosylmethionine (to 0.20mM) and M. SssI (to
0.065 U/µL) and allowed to incubate again overnight at 37° C. The mixture was
phenol:Chloroform purified and the incubation steps above were repeated twice more.
19
The final product was denoted 3X M.SssI, indicating the PBL DNA underwent three
rounds of M.SssI treatment to ensure complete methylation of cytosine in the context of
CpG dinucleotides.

Bisulfite Conversion
DNA bisulfite conversion was carried out using EZ DNA Methylation KIT™
from Zymo Research Corporation (Cat# D5002). The reaction was carried out per
manufacturer’s instruction. However, the 16 hour incubation at 50°C was carried out
using cycling in a PCR machine. Contents were incubated for 1 minute at 95°C followed
by 1-hour incubation at 50°C. The process was cycled 16 times. At the end of the
program, the samples are removed from the PCR machine and placed on ice for 10
minutes. The recovery step was performed per manufacturer’s suggestions. For tissue
samples, 1 µg of DNA was used for bisulfite conversion. For plasma and serum, DNA
recovered from 1 mL of plasma and/or serum was used for bisulfite conversion.

Illumina GoldenGate®
Illumina GoldenGate Cancer Panel I and custom panel OMA-003 (see
Supplemental Table 3 for gene names) were used to examine the DNA methylation status
of 16 pancreatic ductal adenocarcinomas, 6 normal pancreas, 5 non-tumor adjacent, 5
benign pancreatic disease, 2 WBC from healthy individuals and 8 WBC from pancreatic
cancer patients. Assay was performed at the USC Epigenome Center as recommended by
Illumina. The data obtained is in the form of β-value, which corresponds to the ratio of
Cy5 fluorescence (representing methylation) divided by total fluorescence (Cy5 + Cy3),
20
where Cy3 fluorescence represents unmethylated DNA. the level of methylation is
reported as a b-value, with 1 being highly methylated and 0 indicating no methylation.

MethyLight
All PCR primer and probe sets used in this chapter are listed in Supplemental
Table 1. MethyLight PCR was performed in a 30 µL reaction volume with 200 µM
dNTPs, 0.3 µM forward and reverse PCR primers, 0.1 µM probe, 3.5 mM MgCl
2
, 0.01%
Tween-20, 0.05% gelatin and 0.1 U of Taq polymerase using the following PCR
conditions: 95° C for 10 minutes, then 50 cycles of 95° C for 15 s followed by 60° C for
1 minute. The samples were analyzed in 96-well plates on the Opticon DNA Engine
Continuous Fluorescence Detector (MJ Research/Bio-Rad). A standard curve for the ALU
repeat control reaction was generated from 1:25 serial dilutions of 3X M. SssI treated,
bisulfite converted DNA [113].

Digital MethyLight
Digital MethyLight is very similar to Classic MethyLight except only one sample
is run on each 96-well plate. The sample is spread over 95-wells to dilute the background
and increase the signal to noise ratio. One well is reserved for positive control using 3X
M. SssI treated DNA. A large mixture of DNA sample, PCR mix, Taq polymerase and
primer and probe set was prepared based on concentrations for the classic MethyLight
and spread over 95-wells, 30 µL per well [115].

21
Statistical Analysis
The Student’s T-test was performed for Digital MethyLight data in the
‘Candidate Gene Approach’ section of this chapter. For ‘Genome-Wide Approach’
section, Linearly Weighted Mean (LWM) was used. This is not a published statistical
analysis. Briefly, LWM is a variation of the mean whereby linear weights are assigned to
each value in the group. For the ‘Genome-wide Approach’, we wanted to identify loci
with the greatest difference between tumor sample and normal sample in terms of β-value
where the greatest weight is assigned to the tumor with lowest β-value and normal with
highest β-value. Particularly, we were seeking loci that are methylated in tumors that
have low levels of methylation. Each locus will have one LWM for the tumors, one for
the normal pancreas and one for the white blood cells. The difference between the tumor
and normal is calculated and ranked based on the greatest difference. We also subtracted
the LWM of the white blood cells from 10 individuals to further eliminate loci that are
methylated in blood. Therefore, we used the summed the LWM of the normals and the
WBC for each loci and subtracted the sum from the tumors (Tumor
LWM
– (Normal
LWM
+
WBC
LWM
).

Results
Candidate Gene Approach
Marker Discovery Scheme
In an effort to develop sensitive and specific molecular markers for
adenocarcinomas of the pancreas, nine pancreatic adenocarcinomas were collected from
USC Department of Surgery at the USC/Norris Comprehensive Cancer Center
22
immediately after surgery and snap frozen with liquid nitrogen. DNA was isolated using
TriZol® (see Materials and Methods – RNA and DNA Isolation from Tissue), RNase
treated and quantitated using a spectrophotometer. Approximately 1 µg was used for
bisulfite conversion (see Materials and Methods – Bisulfite Conversion) and converted
DNA was diluted in a total volume of 100 µL H
2
O. From the dilution, 2 µL was used for
Real-Time PCR quantization using the reaction targeting Alu repeats (see Supplemental
Table 1). If the measurement indicated adequate yield, the DNA was diluted further to a
final volume of 1000 µL. Approximately 10 ng (10 µL) was used for all MethyLight
analyses.
Reactions from our MethyLight database were screened for candidacy based on
their performance in other malignancies and information gathered from literature search.
The final list was composed of 287 loci that underwent the initial filtering steps using
blood from control individuals. The use of blood as a screening step is crucial since
markers that survive all filters will be used in blood. Therefore, it is imperative that false
positive result arising from WBC contamination is minimized. The marker discovery
scheme would also require counter selection using normal tissue from the pancreas to
eliminate markers that do not demonstrate cancer-specific methylation. Markers that pass
all counter selection screening are analyzed for methylation status to evaluate their
performance on both frequency and level of methylation using pancreatic
adenocarcinomas.

23
Counter Selection Using Controls
White Blood Cell DNA from two control individuals was isolated and bisulfite
converted (see Materials and Methods – DNA Isolation from White Blood Cells and
Bisulfite Conversion). Each of the 287 loci was tested using WBC DNA from two
controls. Approximately 50 ng of DNA was used for each analysis to obtain the cycle
threshold. A cutoff C(t) of 37 was used for the first filtering step and any reaction
showing amplification at an earlier cycle was eliminated (Data not shown). Based on the
initial screen, 170 candidate markers were eliminated and 117 retained (Figure 2.1). The
remaining markers underwent a second round of screening using 100 µL equivalent
plasma DNA isolated from blood of 10 healthy controls (see Materials and Methods –
DNA Isolation from Plasma and Serum). For any one reaction to advance, none of the
10-control plasma should show detectable methylation. In other words, the PMR for all
10-control plasma must be zero. The secondary screen eliminated 95 reactions and
retained 22 (Figure 2.1).
Although counter selection of the markers in blood is important, the frequency
and level of methylation in primary pancreatic tumors is also important. To select
markers with the greatest sensitivity and specificity, two rounds of filtration were
performed using the nine pancreatic adenocarcinomas to measure both the frequency and
level of methylation. The remaining 22 reactions were subjected to MethyLight analysis
using DNA from primary tumors. The performance of each reaction was assessed based
on the PMR obtained from the analysis (see Materials and Methods – DNA Methylation
Analysis and MethyLight). Using PMR as a continuous variable, reactions showing
intermediate-high levels of methylation (PMR ≥ 20) in at least 50% of tumors were
24
retained as our top markers (Figure 2.1). The methylation status of seven candidate loci
(NTRK3, IGFBP3, FLT3, CCNA1, FOXE1, HOXA1 and RASGRF1) was examined in a
collection of 9 pancreatic adenocarcinomas and 2 normal pancreas samples from autopsy
specimens (Figure 2.2).

25
Flow-Chart for Candidate Gene Approach

Figure 2.1: Flow-Chart for Candidate Gene Approach
Flow-Chart outlining the steps utilized to systematically filter candidate markers.

26
Heatmap of Top 7 Loci Using MethyLight

Figure 2.2: Heatmap of Top 7 Loci Using MethyLight
Heatmap shows the frequency (number of tumors with PMR ≥ 20) and level of
methylation (PMR ≥ 20) for each marker using the nine pancreatic ductal
adenocarcinomas. The values in the colored cells indicate PMR. The rows represent each
of the nine pancreatic adenocarcinomas and the columns represent the top seven loci.
Blue, no detectable methylation (PMR=0). Green, intermediate-low level of methylation
(0 < PMR ≤ 5). Yellow, intermediate-high level of methylation (5 < PMR ≤ 50). Red,
high level of methylation (PMR > 50).

27
The use of normal pancreas ensures the identification of markers that are
hypermethylated in a cancer-specific manner. The most appropriate control is one that is
matched for age, gender, ethnicity and genetic background. However, since obtaining
normal pancreas is very difficult, we resorted to samples from autopsy specimens. A
statistical difference between cases and controls could not be determined due to the small
sample size. This is the first report of hypermethylation of these seven loci in pancreatic
cancer and for some loci in any cancer. Therefore, the seven loci could be tagged as
potential novel DNA methylation markers specific for the detection of pancreatic cancer.

Validation of Markers on Independent Sample Set
To assess the performance of our markers on independent sample set, we used
eight normal pancreas or non-tumor adjacent samples, three benign pancreatic tumors and
nine pancreatic ductal adenocarcinomas. Using MethyLight, PMR was generated for each
of the 7 loci and results were compared between the groups (Figure 2.3). It was evident
that most of the top 7 loci are able to distinguish the pancreatic malignancies from the
normal pancreas and the benign pancreatic disease (Figure 2.4). Having identified and
validated a set of biomarkers that were cancer-specific with both high level and high
frequency of DNA methylation in pancreatic malignant tumors, we next attempted to
detect methylated tumor DNA in patient blood.

28

Complete Flow-Chart for Identification of Top 7 Markers

Figure 2.3: Complete Flow-Chart for Identification of Top 7 Markers
Flow-Chart outlining the steps utilized to systematically filter candidate markers.

29

Validation of Top 7 Markers Using Independent Test Set

Figure 2.4: Validation of Top 7 Markers Using Independent Test Set
Validation of the top markers using normal pancreas (N), benign pancreatic tumor (BT)
and pancreatic ductal adenocarcinomas (PDAC). The values in each colored cell
represent PMR obtained using MethyLight technology. Blue, no detectable methylation
(PMR=0). Green, intermediate-low level of methylation (0 < PMR ≤ 5). Yellow,
intermediate-high level of methylation (5 < PMR ≤ 50). Red, high level of methylation
(PMR > 50).

30

Blood Analysis
Even though individuals with cancer have higher concentration of free-circulating
DNA in their blood compared to healthy individuals, this amount is still extremely small.
Current technologies were not sufficiently sensitive for detecting such small number of
methylated DNA molecules. To overcome this hurdle, we developed an ultrasensitve
technology that is capable of amplifying a single molecule of DNA. This new technology
is called Digital MethyLight (see Materials and Methods – Digital MethyLight) [115].
For this analysis, we used both plasma and serum. Plasma is the liquid component of
blood and it is estimated that about 55% of the blood is plasma. Serum, however, is
essentially plasma with growth factors. When blood is allowed to clot, the fibrinogens
that were once in the plasma are now converted to fibrin and the remaining fluid is now
called serum instead of plasma.
DNA was isolated from plasma and serum (see Materials and Methods – DNA
Isolation from Plasma and Serum) and bisulfite converted (see Materials and Methods –
Bisulfite Conversion). After testing the top seven reactions in a multiplexed setting and
confirming optimal performance for each (data not shown), Digital MethyLight was
performed using 100 µL equivalent plasma for 11 controls and 12 cases. The plasma
samples from both cases and controls were collected from an independent popullation set.
The median for both the controls and cases was 0 (Figure 2.5). This indicates that the top
seven markers are not capable of distinguishing cases from controls using plasma.
This was not the first attempt in trying to identify methylated DNA molecules in
patient blood. The use of Digital MethyLight for the detection of methylated DNA
molecules were performed previously with better outcome using serum from healthy
31

Digital MethyLight of Multiplexed Top Seven Markers Using Plasma

Figure 2.5: Digital MethyLight of Multiplexed Top Seven Markers Using Plasma
Each square (controls) and triangle (cases) represents the number of methylated DNA
molecules per 1.0 mL of plasma. Only 100 µL equivalent of plasma was used for the
analysis but the data is reported in number of methylated molecules per mL. The median
for both controls and cases is 0.

32

individuals and patients with pancreatic cancer (unpublished data). Since plasma
normally contains less DNA than serum, it would be possible that serum may be a
better medium for detection than plasma. Preliminary results from our lab had identified a
gene that was differentially methylated in pancreatic tumors but not in normal pancreas
and had relatively low levels of methylation in control WBC. This locus is called PITX2,
paired-like homeodomain transcription factor 2, and functions in left-right asymmetry in
development, but has no described function in adult pancreas [3]. Cancer related
methylation is reported for this molecule but functional consequence of the methylation
has not been elucidated [30, 64, 103]. We therefore investigated the relationship between
plasma and serum in terms of their performance potential in blood using Digital
MethyLight (Figure 2.6). Initial data demonstrated that there was significant difference
between cases (Series I) and controls when serum was used. An independent set of serum
samples (Series II) were collected from pancreatic cancer patients and analyzed for
PITX2 methylation status using Digital MethyLight. The result also demonstrated
significant difference compared to control serum. However, plasma from the same
individuals as Series II did not show similar finding. This data suggests that serum maybe
a better medium of choice for detecting methylated DNA molecules in blood. We
discussed earlier that PITX2 was differentially methylated in pancreatic tumor tissue and
showed low levels of methylation in control WBC. However, this marker was not
considered for top ranking because it showed very low level of methylation in control
plasma therefore, the marker was eliminated. The stringent criteria were is to minimize
false positive results associated with contamination of non-cancer DNA.
33

Comparison of Plasma versus Serum of PITX2 Using Digital MethyLight

Figure 2.6: Comparison of Plasma versus Serum of PITX2 Using Digital MethyLight
Comparing the number of methylated PITX2 molecule in plasma and serum from
controls (open squares) and cases (colored circles). Two independent sets of samples
were analyzed for this study, designated as Series I and Series II. Plasma samples from
Series II cases are matched with serum sample from Series II cases. Control plasma and
serum are not matched. Only 100 µL equivalent of plasma was used for the analysis but
the data is reported in number of methylated molecules per mL. Black, horzontal line in
each category represents the median. Asterisk (*), demonstrates statistical significance
using T-test (p < 0.01) compared to control serum.

* *
34
Genome-Wide Approach
Marker Discovery Scheme
We utilized the Illumina GoldenGate® discovery platform to identify novel genes
that are differentially methylated in pancreatic cancer. We used Cancer Panel I (OMA-
002) and (OMA-003), which together interrogate over 3,000 loci. Cancer Panel I consists
of 807 known differentially expressed genes in all types of cancers. OMA-003, however,
is a custom array for glioma studies. The selection for the genes on the custom panel was
based on treatment of glioma cell lines with 5’-aza-deoxycytadine and performing
expression microarrays to identify genes that have regained expression.
For the analysis, 16 pancreatic ductal adenocarcinomas, 10 normal pancreas or
normal adjacent, five benign pancreatic tumors, two WBC DNA from healthy individuals
and eight WBC DNA from pancreatic cancer patients were used on the Illumina platform.
The samples were obtained from USC Department of Surgery and Washington
University, Department of Pathology. Immediately after resection, samples were snap
frozen with liquid nitrogen. DNA was isolated using TriZol® (see Materials and Methods
– RNA and DNA Isolation from Tissue), RNase treated and quantitated using
spectrophotometer. Approximately 2 µg was used for bisulfite conversion (see Materials
and Methods – Bisulfite Conversion). Samples that passed quality control were given to
USC Epigenome Center for analysis per instructions from Illumina® (see Materials and
Methods – Illumina GoldenGate®). Upon obtaining raw data, we performed supervised
hierarchical analysis to determine whether differential methylation changes are present in
our sample set (Figure 2.7).

35
Supervised Hierarchical Cluster Analysis of Illumina GoldenGate® Data

Figure 2.7: Supervised Hierarchical Cluster Analysis of Illumina GoldenGate®
Data
Supervised hierarchical cluster using entire sample set. Yellow, high level of methylation
(β-value close to 1). Blue, low level of methylation (β-value close to 0). Data was sorted
based on four categories; WBC (White Blood Cells), normal pancreas or non-tumor
adjacent (Normal), benign pancreatic disease (Benign) and pancreatic cancer (Cancer)
and clustered by gene using Cluster version 3.0. Cancer specific, gender specific and
tissue specific methylation changes can be observed.

36
As a proof of principle, we were able to identify loci that are tissue-specifically
and cancer-specifically methylated and ones that are involved in X-chromosome
inactivation. Because statistical analysis does necessarily identify loci that show greatest
difference between cancer and normal, we wanted to identify markers that are capable of
identifying tumors with the lowest levels of methylation. We therefore identified our top
loci using Linearly Weighted Mean (see Materials and Methods – Statistical Analysis). In
figure 2.8, we have demonstrated the utility of Linearly Weighted Mean (LWM) for its
capability to identify differentially methylated loci by comparing cancer to normal
pancreas and white blood cells. Once the LWM was calculated based on greatest
difference, the loci were ranked and the top 50 were chosen for further analysis using
MethyLight as a validation technique (Figure 2.9). This technique was able to adequately
identify loci that are methylated in tumors with low levels of methylation in primary
cancerous tissue. Several possibilities may explain the result. First, the tumor sample
analyzed could be of different origin such as neuroendocrine, for example. This was not
the case for any of our four samples that had low levels of methylation. Secondly, there
could be high stromal contamination in our samples. Tumors from the pancreas are
known for having very high stromal content compared to tumor. If this were the case,
then we would see very low levels of methylation of loci that are tissue specifically
methylated in the pancreas. Based on our data from figure 2.7, this does not appear to be
the case, because we see strong methylation signal corresponding to the loci that are
tissue-specifically methylated. This suggests that there is strong representation of
pancreatic cells in our samples. Finally, the last possibility would be that the tumor
concentration in the sample is very low and that most of the sample is in fact normal
37
pancreas. Based on figure 2.7, this seems to be the most likely scenario because we see
comparable levels of pancreas specific methylation in all of these samples.

38
Heatmap of Top 50 Loci, Ranked Based on Illumina GoldenGate® Data

Figure 2.8: Heatmap of Top 50 Loci, Ranked Based on Illumina GoldenGate® Data
The horizontal axis represents the tissue samples and the vertical axis represents the
probes on the Illumina GoldenGate® platform. Left panel, tumors of the pancreas
(Pancreatic Tumors). Middle panel, control pancreatic tissue (Normal Pancreas, Non-
Tumor Adjacent, Benign Pancreatic Disease). Right Panel, white blood cells from two
healthy individuals and eight patients with pancreatic cancer (WBC). Illumina results are
given in the form of β-value ranging from 0 (unmethylated) to 1 (methylated). Yellow,
indicates β-value is close to 1 (methylated). Blue, indicates β-value is close to 0
(unmethylated).

39
Validation of Illumina® Result and Counter Selection Using Controls
Next, we validated the Illumina® result of our top loci using MethyLight. For this
analysis, we picked two tumors that had high levels of methylation (strong tumors), two
tumors that had low methylation levels of cancer specific loci (weak tumors), two normal
pancreas and two benign pancreatic tumors. Based on the ranking of the top 50, an
attempt was made to design reactions for the top 20. Some, however, were not designed
due to various reasons such as low density of CpG dinucleotides, lack of a CpG Island
and/or unanticipated problems with designing in that area. However, already available
reactions for loci in the bottom 30 of the rank were also included in the analysis. In figure
2.9, results were obtained using MethyLight and the values represent PMR, which is a
continuous variable (see Materials and Methods – DNA Methylation Analysis and
MethyLight). The two strong tumors did show high levels of methylation whereas the
two weak tumors did not. This result was consistent with Illumina® data. Also,
methylation levels of normal pancreas and of benign pancreatic tumors are very close to
background levels, and in some cases, not detectable. This is also comparable to results
seen with Illumina®.
The validation step was also accompanied by counter selection using control
blood from reportedly healthy individuals. White Blood Cell DNA from two control
individuals was isolated and bisulfite converted (see Materials and Methods – DNA
Isolation from White Blood Cells and Bisulfite Conversion). Approximately 50 ng of
DNA was used for each analysis to obtain the cycle threshold. A cutoff C(t) of 30 was
used for the first filtering step and any reaction showing amplification at earlier cycle was
eliminated (Data not shown). The remaining markers underwent a second round of
40
screening using 100 µL equivalent plasma DNA isolated from blood of 10 healthy
controls (see Materials and Methods – DNA Isolation from Plasma and Serum). For any
one reaction to advance, none of the 10-control plasma should show detectable
methylation. In other words, the PMR for all 10-control plasma must be zero. Therefore,
we were left with 12 loci (11 genes) that showed high levels of methylation in both strong
tumors and were essentially free of false positive results due to contamination from white
blood cells. The top loci from the Illumina® discovery platform are CCNA1, NTRK3,
SLC6A2, FLT3, TRIM58, GAS7, EYA4, RASGRF1, DLK1, FLT1 and FGF5. Fibroblast
Growth Factor 5 (FGF5) was not actually on the top 50 but was included because it
showed differential methylation in another sort using tumor samples (data not shown).

41
MethyLight Validation of Illumina GoldenGate® Data

Figure 2.9: MethyLight Validation of Illumina GoldenGate® Data
Gene, HUGO gene nomenclature committee abbreviation. ML RXN, MethyLight reaction
ID (Blue, indicates reactions that were already available in the database. White, indicates
reactions that were newly designed). Tissue Samples (T=tumor, NP=normal pancreas,
BT= benign pancreatic tumor). Control BC (BC#6=Buffy Coat DNA from healthy donor
#6, BC#8=Buffy Coat DNA from healthy donor #8). The values for the Buffy Coat are
given as cycle threshold C(t) using PBL DNA from healthy individuals. Control Plasma,
control plasma from 10 healthy donors (P1-P10). Total, the number of positives out of 10
control plasma. All values in the colored cells are given as PMR. The colors within the
cells indicate the level of methylation. Dark blue, no detectable methylation (PMR=0).
Green, intermediate-low level of methylation (0 < PMR ≤ 5). Yellow, intermediate-high
level of methylation (5 < PMR ≤ 50). Red, high level of methylation (PMR > 50).

42
Multiplexing
The top 12 loci (11 genes) were subjected to multiplex analysis using M. SssI
treated DNA. The purpose for the multiplexing is to use all loci simultaneously for
analysis of a given sample. Since all tumors do not have the sample methylation
signature, the use of a panel is imperative for the detection of tumor DNA molecules. We
have determined the cycle threshold for each of the 12 loci in single or multiplexed
environment. The C(t) of each reaction was determined using only the primer and probe
set for that reaction. Then each reaction was tested in multiplex where all the primers
from the other reactions were mixed together and only the probe from the test reaction
was added. This was done because the success of each reaction depends on the
interactions between the primers. Non-specific priming or primer dimmers could
dramatically contribute to the failure of each reaction. The tolerated delta C(t) between
single and multiplex reactions was 2 cycles. Changes to the C(t) greater than two cycles
caused for elimination of the reaction from the panel. In this experiment, all reactions
passed except for TRIM58. Therefore, only 11 loci (10 genes) were used for the final
experimentation of this project (Figure 2.10).

43
Multiplexing of Top 11 Loci Using M. SssI DNA

Figure 2.10: Multiplexing of Top 11 Loci Using M. SssI DNA
X-axis represents the reaction ID of top 11 loci. Y-axis represents the cycle threshold
over which fluorescence is detected. Blue bars, represent the average C(t) for the reaction
based on technical triplicate of M. SssI treated DNA for single primer/probe set. Orange
bars, represent average C(t) for each reaction based on technical triplicate of M. SssI
treated DNA for multiplexed reaction of 11 primer sets and 1 probe. Error bars reprent
standard error.

44
Validation of Markers on an Independent Sample Set
To assess the performance of our markers on an independent sample set, we used
five non-tumor adjacent, one benign pancreatic tumor and eight pancreatic
adenocarcinomas. Using MethyLight, the PMR value was generated for each of the 11
loci and results were compared between the groups (Figure 2.11). Although the non-
tumor adjacent and the benign pancreatic tumor had very low levels of methylation, about
half of the tumors also showed such low levels of methylation. The exact reason for this
unknown however one can speculate that the tumor content for the samples was rather
low. Since the tumors were not microdissected and H&E sections of the tumors are not
available, it is impossible to determine the exact cause of the low methylation. Having
identified and validated a set of biomarkers that were cancer-specific with both high level
and high frequency of DNA methylation in pancreatic malignant tumors, we next
attempted to detect methylated tumor DNA in patient blood.

45
Validation of Top 11 Loci Using an Independent Sample Set

Figure 2.11: Validation of Top 11 Loci Using an Independent Sample Set
Validation of the top markers using normal pancreas (N), benign pancreatic tumor (BT)
and pancreatic adenocarcinomas (T). The values in each colored cell preresent PMR
obtained using MethyLight technology. Blue, no detectable methylation (PMR=0).
Green, intermediate-low level of methylation (0 < PMR ≤ 5). Yellow, intermediate-high
level of methylation (5 < PMR ≤ 50). Red, high level of methylation (PMR > 50).

46
Blood Analysis
Even though individuals with cancer tend to have a higher concentration of freely
circulating DNA in their blood compared to healthy individuals, the amount is still
extremely small. Current technologies were not sufficiently sensitive for detecting such a
small number of methylated DNA molecules. To overcome this hurdle, we developed an
ultra-sensitive technology that is capable of amplifying a single molecule of DNA. This
new technology is called Digital MethyLight (see Materials and Methods – Digital
MethyLight). For this analysis, we used both plasma and serum. Plasma is the liquid
component of blood and it is estimated that about 55% of the blood is plasma. Serum,
however, is essentially plasma with growth factors. When blood is allowed to clot, the
fibrinogens that were once in the plasma are now converted to fibrin and the remaining
fluid is now called serum instead of plasma.
DNA was isolated from plasma and serum (see Materials and Methods – DNA
Isolation from Plasma and Serum) and bisulfite converted (see Materials and Methods –
Bisulfite Conversion). After testing the top seven reactions in a multiplexed setting and
confirming the optimal performance for each (data not shown), Digital MethyLight was
performed using 1000 µL equivalent plasma for 4 cases. No control blood was available
for this analysis. For all samples, the number of methylated DNA molecules was at
background levels (Figure 2.12). Therefore, this indicates that the utility of the top 11 loci
for the detection of pancreatic cancer is far from established.

47
Digital MethyLight of the Top 11 Loci Using Plasma and Serum

Figure 2.12: Digital MethyLight of the Top 11 Loci Using Plasma and Serum
The number of Methylated DNA molecules is determined from the number of hits in a
96-well plate. Top panel, 1000 µL equivalent of plasma from 4 pancreatic cancer patients
(a-d). Bottom panel, 1000 µL equivalent of serum from 4 pancreatic cancer patients (e-h).
Blue curve in each graph located at approximately C(t) 28 is positive control using M.
SssI treated DNA.

48
Discussion
Detection of pancreatic cancer at an early stage is vital for obtaining the desired
prognosis. According to the American Cancer Society, the 5-year survival rate of Stage
IA pancreatic cancer is 40% whereas it is only 1% for Stage IV. Stage IA tumors are
confined to the pancreas and are less than 2 cm in size and there is no spread to nearby
lymph nodes or distant sites. Pancreatic cancer is largely asymptomatic until the disease
has advanced to metastasis, therefore waiting for symptoms to arise could be detrimental
to ones health and ultimately, survival.
Currently, imaging technology is the only modality used to detect pancreatic
cancer but it is usually not used as an initial screen for early detection unless the
individual has a strong predisposition to the disease. Serum markers, such as CA19-9 and
CEA, have also been evaluated for the early detection of pancreatic cancer. However,
these markers are neither cancer-specific nor organ-specific because they can also be
elevated in individuals with benign gastrointestinal disorders. For example, screening of
10,000 asymptomatic individuals with ultrasound and CA19-9 for early detection of
pancreatic cancer resulted in only 0.5% of patients with positive result having pancreatic
cancer [34]. The serum marker CA19-9 is most commonly used to detect disease
recurrence. Since CA19-9 cannot be used for early detection, there is an enormous need
for new noninvasive screening tests to detect early pancreatic neoplasms.
In this study, we set out to identify blood markers for the detection of pancreatic
cancer. We have demonstrated the utility of both candidate gene approach and genome-
wide approach in identifying genes that are differentially methylated in pancreatic cancer
tissue. Although with very little overlap, we and others have identified panels of
49
differentially methylated loci that can accurately distinguish carcinomas from normal
pancreas with great reproducibility [79, 88]. The biggest obstacle in the field of marker
discovery is the ability to detect the makers in patient blood and the need for these
makers to have high levels of sensitivity and specificity. Also, it is essential that these
markers be detected early enough so that surgical intervention is still an option for cure.
To date, no study has been able to demonstrate the utility of DNA methylation
biomarkers for blood based screening of pancreatic cancer. Some argue that there would
not be enough free circulating DNA in the blood for early detection and others argue that
DNA methylation changes may not surface until the disease has progressed towards
metastasis, where early detection technology will not pose any advantage. Studies
performed using pancreatic secretions for the detection of K-ras mutations have
demonstrated that the mutation can be detected with great sensitivity [2, 4]. Berthélemy
et al. demonstrated that 17 out of 22 samples obtained from patients with pancreatic
cancer were positive for K-ras mutation and none of the 53 samples obtained from
patients without pancreatic cancer harbored mutant K-ras. Interestingly, two patients that
did not have pancreatic cancer at the time of K-ras screening developed the disease
several months later. One developed the disease 18 months after K-ras screening and the
other, 40 months. The pancreatic juice for the samples was obtained using ERCP
(Endoscopic Retrograde Pancreatography), which is an invasive procedure. Therefore,
this procedure is not ideal for cancer screening. An important question is how much of
the DNA in the pancreatic juice actually ends up in the blood. Although it is very difficult
to determine how much tumor DNA would be circulating in the blood of pancreatic
cancer patients at an early stage, we do know that individuals with cancer have high
50
concentration of DNA. The exact source of the free circulating DNA is largely unknown
but it is assumed it is shed by the tumor.
To address the second concern of whether DNA methylation changes do occur at
an early stage, Hong et al. identified DNA methylation markers that arise during IPMN
development and these markers can be used to differentiate IPMN from non-neoplastic
pancreatic cystic lesions [35]. They concluded that aberrant DNA methylation increases
with histologic grades of IPMN. Low-level methylation in normal duct cells was more
prevalent in patients with ductal neoplasia than in controls without ductal neoplasms.
Several studies of various cancers have surfaced in the recent years that can detect
tumor DNA in patient blood [8, 21, 28, 75]. Although our result does not demonstrate the
utility of DNA methylation biomarkers for early detection, we need to identify our
limitations before solid conclusions can be made. One possible explanation would be that
the primers and probes used as our top markers are not capable of detecting low
concentration of DNA. In the case where DNA concentration is too high, PCR efficiency
is hindered due to increase in unspecific annealing. However, in the case with low DNA
concentration, PCR efficiency is hindered due of increase in primer-dimer formation. Top
markers can be tested for PCR efficiency by spiking control plasma with very low
concentration of M. SssI treated DNA and run MethyLight. Loci that can perform under
such conditions could potentially be great biomarkers. Another possibility would be that
regions that have nucleosome occupancy might be protected against degradation once the
DNA is released, therefore allowing amplification of those regions. In this case,
designing reactions located in regions protected by the nucleosome would be necessary.

51
Chapter 3: The effects of in vivo modulation of DNA methylation on tumorigenesis
and progression of pancreatic acinar cell carcinoma in a mouse model

Introduction
DNA methylation is implicated in many biological processes such as embryonic
development, transcription regulation, X-Chromosome inactivation, genomic imprinting,
chromosomal instability and repression of retrotransposons [39, 110]. The enzymatic
modification of cytosine in the context of CpG dinucleotides has also been very popular
in cancer studies. In normal cells, most CpG dinucleotides are methylated such as repeat
sequences with the exception of CpG islands, which are densely packed CpG
dinucleotides located at the 5’ region of a gene. About half of the mammalian genes have
these CpG islands at their promoter region. This phenomenon is called CpG island
hypermethylation. The role of DNA methylation in cancer has been studied using both in
vitro and in vivo experiments. In the context of tumorigenesis, DNA hypermethylation is
frequently seen at the promoters of tumor suppressor genes is often associated with
transcriptional repression and thus neoplasia [46, 47].
Modulation of maintenance DNA methyltransferase (Dnmt1) levels has been the
focus of many in vivo studies where either genetics or therapeutics is used [12, 17, 54, 63,
84, 105]. For Example, Eads et al. demonstrated the role of DNA methylation on polyp
formation by crossing the intestine cancer-prone Apc
Min/+
mice with Dnmt1 hypomorphic
mice. They found that reduced levels of Dnmt1 result in suppression of macroscopic
intestinal neoplasia but elevated levels of microadenomas and multifocal liver tumors
[17, 96, 119]. The Min (Multiple Intestinal Neoplasia) model was first described by
52
Moser et al. It consisted of the use of ethylnitrosourea which gave rise to germline
mutation of the Apc locus, which is the locus responsible for the human FAP (Familial
Adenomatous Polyposis) condition. The Min model harbors a T to A transversion
mutation at nucleotide 2549 which coverts codon 850 from leucine (TTG) to a stop codon
(TAG) [96]. The mutation results in the development of adenomas of the small intestine
at approximately 4-6 months of age. Animal heterozygous for the Min allele succumb to
the disease due to obstruction of bowel movement [74]. Similar observations were made
with Mlh1
-/-
mice, where a decrease in Dnmt1 expression results in diminished frequency
of intestinal tumors and an increased frequency of aggressive lymphoid tumors [105].
The use of hypomorphic alleles has allowed for viable down-regulation of Dnmt1
since complete knock-out of the maintenance methyltransferase is embryonic lethal [58].
There are several hypomorphic alleles of Dnmt1 but only the N-allele and the R-allele
have been used for our studies. Generation of the Dnmt1
N
allele was done by insertion of
Neomycin cassette in exon 4 as described by Li et al. in 1992 [58]. This allele only has
10% of the expression of the wildtype allele (Figure 3.1). Generation of Dnmt1
R
allele
was done by insertion of three copies of the lac operator sequence (lacO) from E. coli
located in intron 3, just upstream of the splice acceptor site as described by Eads et al
[17]. The R-allele has about half the expression of a wildtype diploid allele (Figure 3.1).
In this study, we aim to understand the role of DNA methylation in pancreatic
cancer. Previously published work by Clarke et al. demonstrated that compound mutation
of Apc
Min/+
and Trp53
TJ/TJ
results in a shift in phenotype and results in the development of
pancreatic acinar cell adenocarcinomas [10]. We have therefore utilized their model of
pancreatic acinar cell adenocarcinoma to investigate the role of DNA methylation in
53
pancreatic tumorigenesis. As discussed earlier, Apc
Min/+
mice develop adenomas of the
intestine while Trp53
TJ/TJ
predominantly develop sarcomas and lymphomas. Generation
of Trp53
TJ/TJ
was done by deletion of nearly half of the coding capacity of the gene,
which completely eliminates the synthesis of the protein. Homologous recombination
between the p53KO targeting vector and one allele of the endogenous p53 gene results in
the replacement of p53 coding sequence between exons 2 and 7 with the neo gene
expression cassette and the formation of the Trp53
TJ/TJ
mutant allele [41]. Both Apc
Min/+
and Trp53
TJ/TJ
mutations are observed in human pancreatic cancer but they are largely
found in pancreatic ductal adenocarcinomas. Therefore, we have attempted to study the
role of DNA methylation on pancreatic cancer development by generating a cross
between Apc
Min/+
Trp53
TJ/TJ
mice and mice carrying the Dnmt1 hypomorphic alleles.

54
Schematic Representation of the Structure of the Dnmt1 Hypomorphic Alleles

Figure 3.1: Schematic representation of hypomorphic alleles of Dnmt1
The Dnmt1
R
allele has a 320 bp insertion containing three copies of the lac operator (lac
O) sequence in intron 3. The Dnmt1
N
allele contains a neomycin cassette that replaces
part of exon 4. Exons are represented as black boxes and introns are represented as solid
lines.

55
Materials and Methods
Dnmt1 Hypomorphic Mice
Rudolf Jaenisch generously donated the Dnmt1
N
allele. Peter W. Laird generated
the Dnmt1
R
allele in the Jaenisch laboratory at MIT Whitehead Institute. The Dnmt1
R

allele was in the 129Sv/Jae background and the Dnmt1
N
allele was in the C57BL/6
background.

Apc
Min/+
Mice
Apc
Min/+
mice were purchased from Jackson Laboratories (Bar Harbor, Maine) in
C57BL/6 background.

Trp53
TJ/TJ
Mice
Trp53
TJ/+
mice in the 129Sv/Jae background was generously donated by Rudolf
Jaenisch at MIT Whitehead Institute.

Generation of Triple-Cross
The triple cross was generated by mating 129Sv/Jae Apc
+/+
Trp53
TJ/+
Dnmt1
R/+

female with C57BL/6 Apc
Min/+
Trp53
TJ/+
Dnmt1
N/+
male to generate 24 different
genotypes. The probability of obtaining the desired genotype of Apc
Min/+
Trp53
TJ/TJ

Dnmt1
N/R
is 1/32. The cross proceeded slowly since 7/8 were not Apc
Min/+
and/or
Trp53
TJ/TJ
. Apc
Min/+
females could not be used because they are rarely healthy enough to
maintain pregnancy.

56
Tail DNA Isolation Procedure
Approximately 1 cm tail biopsies were obtained from 4-week old mice and
incubated in 500µL lysis buffer (100 mM Tris.HCl pH 8.5, 5 mM EDTA, 0.2% SDS, 200
mM NaCl, 100 µg Proteinase K/mL) overnight at 50°C. The following day, samples were
spun at maximum speed for 10 minutes at room temperature and the supernatant was
transferred into a clean 1.5 mL Eppendorf tube. The pellet which contained debris was
discarded. Approximately 1 volume (750 µL) of isopropanol was added to the
supernatant and gently mixed by inverting the tube about 20 times or until the DNA had
precipitated. The DNA was fished out using pipet tips and dissolved in 150µL of TE
buffer (10 mM Tris.HCl, 0.1 mM EDTA, pH 7.5). The DNA was allowed to dissolve
further overnight at 50°C. After this incubation period, the DNA was ready for analysis
[55].

Genotyping
DNA from tail biopsies was isolated as described previously. The genotype of the
Dnmt1 allele was determined by multiplexing PCR analysis using primers OL106,
OL168, OL173 and OL369. The reaction was carried out in a 30 µL volume with 1X
PCR buffer without MgCl
2
, 1.5 mM MgCl
2
, 0.2 mM dNTPs, 0.344 µM primer mix and
0.5 U Taq polymerase. DNA from the previous step was diluted 1:50 and 5 µL was used
for each reaction.The PCR conditions were as follows. 94° C for 5 minutes, then 35
cycles of 94° C for 50 s followed by 60° C for 50 s and 72° C for 1 minute and 30 s
ending with 72°C for 10 minutes. OL168 and OL173 produced both a 342-bp wildtype
specific band and a 661-bp Dnmt1
R
allele-specific band. OL106 and OL173 produced a
57
430-bp Dnmt
N
allele-specific band. OL173 and OL369 produced a second 211-bp
Dnmt1
R
allele-specific band when resolved on 2% agarose gel. Apc genotyping was
performed in a 30 µL reaction volume with 200 µM dNTPs, 0.3 µM forward and reverse
PCR primers, 0.1 µM probe, 3.5 mM MgCl
2
, 0.01% Tween-20, 0.05% gelatin and 0.1 U
of Taq polymerase using the following PCR conditions: 95° C for 10 minutes, then 50
cycles of 95° C for 15 s followed by 60° C for 1 minute. DNA was diluted 1:100 and 10
µL was added to the mix. The samples were analyzed on the Opticon DNA Engine
Continuous Fluorescence Detector (MJ Research/Bio-Rad). The primer and probe
sequence is listed in Table 3.1. Two different probes are used to distinguish the witldtype
allele from the Min allele. Probe from MD24 is used for amplification of Apc
+
allele and
MD25 is used for the amplification of the Apc
Min
allele. The genotype of the Trp53 allele
is determined by multiplexing PCR analysis using primers OL012, OL013 and OL014
where OL012 and OL013 amplify the Trp53 wildtype allele and OL013 and OL014
amplify the knockout allele. The reaction was carried out in a 30 µL volume with 1X
PCR buffer without MgCl
2
, 1.5 mM MgCl
2
, 0.2 mM dNTPs, 0.3 µM primer mix and 0.35
U Taq polymerase. DNA from the previous step was diluted 1:100 and 5 µL was used for
each reaction.The PCR conditions are as follows. 94° C for 5 minutes, then 40 cycles of
94° C for 45 s followed by 55° C for 45s and 72° C for 1 minute, ending with 72°C for 5
minutes. The bands were resolved on 2% agarose gel where Trp53
+/+
gives a 450-bp
band, Trp53
TJ/+
gives a 600-bp and 450-bp and Trp53
TJ/TJ
gives a 600-bp band. The
sequences of the primers are listed in Table 3.1.

58
Table 3.1: Primer and Probe Sequence for Genotyping

Table 3.1: Primer and Probe Sequence for Gentoyping
List and sequence of primers used for genotyping Apc, Trp53 and Dnmt1 mice.

Beta-Catenin Immunohistochemistry
Pancreas from Apc
Min/+
Trp53
-/-
and Dnmt1 wildtype and hypomorphic mice were
collected and stored in 10% buffered formalin overnight. The following day, the tissue
was removed and stored in 70% ethanol until it was processed for paraffin embedding.
Samples were given to the USC Pathology Core for paraffin embedding and
tissues were sectioned at 4 µm thickness and mounted on charged glass slides. The slides
were dried for 1 hour in a heating oven at 60° C. Once the slides were dried, they were
removed from the oven and deparaffinized by dipping the slides in CitriSolv (Fisher
Scientific Cat No. 22-143-975), 3 times for 30 minutes each, 100% ethanol (2 times for 3
minutes each), 80% ethanol (1 time for 3 minutes), 50% ethanol (1 time for 3 minutes),
and ddH
2
O (1 time for 3 minutes).
The antigen was then retrieved by completely immersing the slides in 10 mM
Citrate Buffer pH=6.7 (Lab Vision Corporation, Cat No. AP-9003-125) and heating in
the microwave for 4 minutes at power 1 and an additional 4 minutes at power 3. The
slides are removed from the citrate buffer and allowed to cool at room temperature for 20
59
minutes. The area around the section was dried completely with a Kimwipe and the
sections were circumscribed with PAP pen to create a hydrophobic barrier and allowed to
dry for 2 minutes at room temperature. Three drops of 3% hydrogen peroxide was added
on top of each section and allowed to incubate for 10 minutes in a hydrated enclosure.
After 10 minutes of incubation, the hydrogen peroxide was poured off and tapping the
edge of each slide onto a paper towel to remove excess solution gently dried the slides.
The sections were then rinsed three times with 1X PBS. Holding the slides horizontally,
Rinse Buffer was gently added to each slide drop-wise to flood the tissue specimen. The
Rinse Buffer is a component of the Chemicon IHC Select® Immunoperoxidase
Secondary Detection System (Cat No. DAB150 – 150 Slide Kit). The Rinse Buffer was
prepared by diluting 20X Rinse Buffer with water to get 1X Rinse Buffer and 1:1000
dilution of Tween-20 was added to the 1X Rinse Buffer. The rinsing step with Rinse
Buffer was repeated 3 times followed by the addition of 4 drops of Rinse Buffer. This
time, the Rinse Buffer was allowed to incubate at room temperature for a minimum of 2
minutes. The Rinse Buffer was then poured off and excess solution was tapped off. One
drop of blocking reagent (from kit) was added to each section and allowed to incubate at
room temperature for 20 minutes. After the blocking step, the sections were washed with
1X Rinse Buffer (3 times for 20 seconds each) and tapped dry to remove excess solution.
Next, the β-Catenin primary antibody was added to each section. No titration of the
primary antibody was necessary because we used a Ready-to-Use antibody β-Catenin
antibody (Thermo Scientific Cat No. RB-1491-R7). The primary antibody was incubated
at room temperature for 30 minutes, followed by washing five times with Rinse Buffer
and incubation with Rinse Buffer for at least 2 minutes. Secondary Antibody from the
60
Chemicon IHC Select® Immunoperoxidase Secondary Detection System (Cat No.
DAB150 – 150 Slide Kit) was added to each section and allowed to incubate at room
temperature for 10 minutes. Again, no titration was necessary since the secondary
antibody was also Ready-to-Use. Secondary antibody was rinsed off from the sections as
done previously. One drop of Streptavidin-HRP from the Chemicon IHC Select®
Immunoperoxidase Secondary Detection System (Cat No. DAB150 – 150 Slide Kit) was
added to each section and allowed to incubate for 10 minutes in a hydrated enclosure at
room temperature followed by washing with Rinse Buffer. Once the slides were tapped
dry, freshly prepared Chromogen Reagent (follow manufacturer’s instructions) was
added to each section and incubated in a dark, enclosed container for 10 minutes. The
sections were washed again with Rinse Buffer and one drop of hematoxylin counter stain
solution was added and incubated for one minute in an enclosed container. The slides
were washed again with Rinse Buffer and place in a container with deionized water and
kept in here until the next step. The mounting media, Permount, used is a xylene-based
substance therefore the tissues needed to be dehydrated with 100% ethanol (2 times, 3
minutes each) followed by CitriSolv (3 times, 3 minutes each). The slides were wiped
with a Kimwipe and one drop of Permount was added to each slide and the sections were
covered with a coverslip and allowed to dry for 24 hours before visualizing under a
microscope.

61
Histological Analyses
β-Catenin stained sections were visualized at 20X magnification (unless
otherwise stated) without knowledge of genotype. The number of foci, adenomas and
carcinomas were counted for each mouse and documented. Cells classified as foci
displayed clusters of immature pancreatic cells and were usually less than 0.030 mm
2
in
area. Adenomas were characterized as circumscribed masses of well differentiated acinar
cells with mild to moderate nuclear crowding and increased nuclear size. On the other
hand, carcinomas lacked defined boundaries, demonstrated loss of acinar architecture,
loss of cellular differentiation and occupied very large areas, often visible to the naked
eye. For tumor burden index calculations, foci were given a score of 1, adenomas were
given a score of 2 and carcinomas were given a score of 3. The results of the tumor
burden index can be seen in figure 3.2.

Statistical Analysis
Student t-test and Chi-Square analysis were used to obtain p-values.

62
Schematic Representation of Triple-Cross and Tumor Burden Index

Figure 3.2: Schematic Representation of Triple-Cross and Tumor Burden Index
Generation of Apc
Min/+
Trp53
TJ/TJ
Dnmt1
+/+
and hypomorphic mice was carried out by
crossing Apc
+/+
Trp53
TJ/+
Dnmt
R/+
females with Apc
Min/+
Trp53
TJ/+
Dnmt
N/+
male to
generate 24 possible genotypes in offspring. The graph represents tumor burden index of
the four important genotypes where the horizontal lines represent the mean and the
whiskers represent standard deviation

63
Results
Breeding and Chi-Square Calculations
A total of 761 mice were bred by mating Apc
+/+
Trp53
TJ/+
Dnmt1
R/+
females
(129SV/Jae) with Apc
Min/+
Trp53
TJ/+
Dnmt1
N/+
males (C57BL/6) to generate 24 possible
genotypes of F1. Out of 761 total mice, only 88 were heterozygous for the Min allele and
homozygous knockout of Trp53. Of the 88 progeny 21 were Apc
Min/+
Trp53
TJ/+
Dnmt1
+/+
,
27 were Apc
Min/+
Trp53
TJ/TJ
Dnmt1
R/+
, 27 were Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/+
and 13 were
Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/R
(Table 3.2).
Chi-Square analysis was performed to determine whether there is a statistically
significant change in the distribution of genotypes of offspring compared to theoretical
values predicted by Mendelian distributions. The Chi-square between observed and
expected number of mice under each genotype (a total of 24 genotypes) is 12.08. The
difference between expected and observed number of mice under each genotype is not
significant with a p-value greater than 0.05. Therefore, the result confirms that the
genotypes are independently segregated and follow a Mendelian distribution.

64
Chi-Square Table for Progeny Generated from the Triple-Cross

Table 3.2: Chi-Square Table for Progeny Generated from the Triple Cross
Genotype of progeny that were generated by crossing Apc
+/+
Trp53
TJ/+
Dnmt1
R/+
females
and Apc
Min/+
Trp53
TJ/+
Dnmt1
N/+
males. The horizontal axis represents possible Dnmt1
genotypes. The left axis represents possible Apc genotypes. The right axis represents
possible Trp53 genotypes. Values not in the parenthesis represent observed values.
Values inside the parenthesis represent expected values. The asterisk indicates rounding
up of decimals to whole numbers for the total number offspring. The Chi-Squre is 12.08,
p-value is 0.67 and degree of freedom is 23.

65
Histological Analyses
For the analyses, pancreas samples from 67 out of a possible 88 were paraffin
embedded, sectioned and stained with β-catenin antibody for detection (see Materials and
Methods –Beta-Catenin Immunohistochemistry). Of the 67, 11 were
Apc
Min/+
Trp53
TJ/TJ
Dnmt1
+/+
, 21 were Apc
Min/+
Trp53
TJ/TJ
Dnmt1
R/+
, 22 were
Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/+
and 11 were Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/R
. Hematoxylin-eosin
(H&E) staining was performed to detect aberrant histological changes compared to
normal adjacent tissue. We also used β-catenin staining to identify Wnt pathway
deregulation caused by loss of wildtype Apc allele. Loss of Heterozygosity (LOH)
analysis performed in Apc
Min/+
mice has demonstrated that loss of wildtype allele (Apc
+
)
occurs in all spontaneously occurring intestinal adenomas [60]. Hence, we wanted to
known whether early lesions (foci) demonstrate Wnt pathway deregulation, evident by β-
catenin accumulation. Microscopic analysis showed that all aberrant histological analysis
observed by H&E staining also demonstrated accumulation of β-catenin nuclear staining.
The number of foci, adenomas and carcinomas were counted for each mouse and
documented. Cells classified as foci displayed clusters of immature pancreatic cells that
were usually less than 0.030 mm
2
in area. Adenomas were characterized as circumscribed
masses of well-differentiated acinar cells with mild to moderate nuclear crowding and
increased nuclear size. On the other hand, carcinomas lacked defined boundaries,
demonstrated loss of acinar architecture, loss of cellular differentiation and grew in very
large areas, often visible to the naked eye. Progression from focus to carcinoma could be
seen in Figure 3.3.

66
Histological Analysis Using H&E and Beta-Catenin IHC

Figure 3.3: Histological Analysis Using H&E and Beta-Catenin IHC
Top panel: H&E stained sections Apc
Min/+
Trp53
TJ/TJ
Dnmt1 hypomorphic alleles (a-d).
Bottom panel: Immunohistochemistry sections of β-catenin stained slides. Normal
Pancreas (a and e), Foci (b and f), Adenoma (c and g) and Carcinoma (d and h).

67
Tumor Multiplicity
Cohorts of Apc
Min/+
Trp53
TJ/TJ
mice with Dnmt1
+/+
, Dnmt1
R/+
, Dnmt1
N/+
and
Dnmt1
N/R
genotypes were aged up to 100 days and analyzed for foci, adenomas and
carcinomas of the pancreas. The number of adenomas identified by β-catenin
immunostaining was significantly decreased in the hypomethylated Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/+
and Apc
Min/+
Trp53
TJ/TJ
Dnmt1
N/R
compared to Apc
Min/+
Trp53
TJ/TJ
Dnmt1
+/+
and
Apc
Min/+
Trp53
TJ/TJ
Dnmt1
R/+
. However the number of carcinomas also showed dramatic
decrease but the difference was not statistically significant. The number of foci,
adenomas and carcinomas per mouse were identified and plotted per β-catenin
immunostaining (Figure 3.4). Previous publication by Yamada et al. identified an
increase in microadenoma formation in mouse intestines when Apc
Min/+
mice were
crossed with Dnmt1 Hypomorphic alleles suggesting that DNA methylation is
responsible for chromosomal instability through a LOH mechanism [119].
Microadenomas are classified as early precursor lesions to polyp formation in the
intestine. However, in the case with our pancreatic acinar cell adenocarcinoma mouse
model, we did not observe increase in number of foci. In fact, we observed a decrease in
number of foci. One possibility would be that formation of foci is not the earliest event in
pancreatic tumorigenesis since microadenomas are believed to be very early event in
intestinal tumorigenesis. Another possibility would be that promotion of early lesions in
the intestine through a LOH mechanism by DNA hypomethylation might be a tissue-
specific phenomenon.
We next investigated whether DNA methylation is necessary for tumor growth.
We calculated the average nuclear area of the foci per mouse, average area of foci per
68
mouse and average area of adenoma per mouse using computer software (Figure 3.4 D-
F). We found that DNA hypomethylation is not associated with lesion size.

69
Tumor Multiplicity and Area

Figure 3.4: Tumor Multiplicity and Area
Number of foci (A) adenoma (B) and carcinoma (C) are plotted where the x-axis
represents the Dnmt1 hypomorphic alleles and the y-axis represents the number of lesions
per mouse. The horizontal bars represent the mean and the error bars represent standard
deviation. Ratio of Adenomas to Foci and Carcinomas to Adenomas (D) and Area of Foci
(E) and Area of Adenoma (F) are represented in similar fashion. The x-axis represents
hypomorphic alleles of Dnmt1. The y-axis represents the average area of foci (E) and
adenoma (F) for each mouse. The horizontal bars represent the mean and the error bars
represent standard deviation (A-C). The horizontal bars represent the median (E-F).
Statistical significance is designated with corresponding with p-value.

p=0.03

p=0.03

p=0.005
A B
C D
E F
70
Discussion
In this study, we have demonstrated the effect of in vivo modulation of DNA
methylation on tumorigenesis and progression of pancreatic acinar cell carcinoma. By
crossing Apc
Min/+
and Trp53 mutant mice, Clarke et al. showed that combined activation
of the Wnt pathway and inactivation of Trp53 results in increased frequency of invasive
pancreatic acinar cell adenocarcinomas [10]. In mice, sole activation of the Wnt pathway
results in benign intestinal neoplasia with rare cases of intestinal adenocarcinomas, where
abnormalities of the pancreas are not observed. Although Trp53 mutations give rise to
many malignancies such as sarcomas and lymphomas [41], the rate of intestinal adenoma
formation or progression to malignancy has remained unchanged in Apc
Min/+
Trp53
TJ/TJ

mice compared to Apc
Min/+
Trp53
+/+
mice [10]. Although a shift in phenotype was
observed, Apc
Min/+
Trp53
TJ/TJ
mice were characterized by sarcoma and lymphoma at
comparable incidence to the Apc
+/+
Trp53
TJ/TJ
mice. Nearly 83% of animals showed
abnormalities of the exocrine pancreas and 22% of these animals had pancreatic acinar
cell carcinoma. Analysis of the pancreatic acinar cell adenocarcinomas showed loss of
wildtype allele of Apc. This observation may indicate that loss Trp53 increases frequency
of mutation at the Apc locus and is therefore crucial to the development of the neoplasia.
Therefore, the presence of this mutation may tissue specifically regulates tumor initiation
and progression since absence of Trp53 does not exacerbate tumorigenesis in the
intestine.
The role of Trp53 in pancreatic acinar cells is different from that of the
gastrointestinal cells since Trp53 null environment enhances tumor initiation and
progression in pancreatic cells but not in the intestine. A possible explanation is that
71
pancreatic cells produce a lot of reactive metabolites and protection against DNA damage
is necessary [10]. In an experiment to determine whether this protection is accomplished
through apoptosis, Clarke et al. subjected the animals to γ-irradiation. They concluded
that the protection of acinar cells is Trp53 dependent but does not rely on apoptosis
because γ-irradiation does not induce apoptosis in acinar cells but is induced in adjacent
endothelium and lymphoid cells.
In humans, the development of pancreatic cancer is rather different from this
mouse model of pancreatic cancer. As mentioned in Chapter 1, 95% of pancreatic cancers
are of exocrine origin in the form of ductal adenocarcinomas. Although both p53 and
APC mutations are observed in human pancreatic cancer, acinar cell carcinoma is very
rare. This may be due to differences in pancreatic development between the two species.
However, the important question for our studies is the role of DNA methylation on
tumorigenesis of the pancreas. Since differential methylation is observed in human
pancreatic cancer, we next studied the effect of DNA hypomethylation on tumorigenesis.
Is DNA methylation important in tumorigenesis?
We generated a triple-cross between Apc
Min/+
Trp53
TJ/TJ
and Dnmt1 hypomorphic
alleles. Previous publications from our lab demonstrated the importance of DNA
methylation in tumorigenesis. Eads et al. demonstrated that modulations of Dnmt1 in
Apc
Min/+
model of intestinal cancer completely diminish macroscopic adenoma formation
[17]. A similar result was observed by Trinh et al. where modulation of Dnmt1 in Mlh1
-/-
model of intestinal cancer protects against tumor development but exacerbates B and T-
cell lymphoma genesis [105].
72
Chi-Square analysis of the 24 possible genotypes generated demonstrated no
association between number of progeny and genotype. We also looked at the tumor
burden index for each of the four Dnmt1 alleles. In our analysis, we observed a decrease
in tumor burden when comparing mice with wildtype Dnmt1 expression and mice that
had the lowest viable level of Dnmt1 expression. This result suggests that Dnmt1
expression is essential for tumorigenesis in the pancreas and that the effect of DNA
methylation on tumorigenesis is not organ specific. This observation is not restricted to
the intestine but can also be seen in the mouse pancreas.
By counting the number of foci, adenomas and carcinomas for each genotype, we
were able to identify whether DNA methylation is necessary for initiation or progression
of acinar cell carcinoma. Based on statistical calculations, DNA methylation is necessary
for the progression, but not initiation of pancreatic acinar cell carcinoma. However, we
also see slight drop in number of foci comparing wildtype Dnmt1 allele to that of the
Dnmt1
N/R
. This result suggests that DNA methylation is involved in the initiation of
tumorigenesis but is not absolutely necessary. Also, area of foci and area adenomas is
independent of genotype.

73
Chapter 4: Studying CIMP in a mouse model of B-RAF
V600E
induced tumorigenesis

Introduction
In 1999, a publication by Jean-Pierre Issa’s group identified a group of colorectal
tumors that demonstrate concordant methylation in a subset of CpG islands [101]. This
distinct group was termed (CpG Island Methylator Phenotype). They demonstrated that
this group of tumors had high incidences of p16 (CDKN2A) and THBS1
(Thrombospondin 1) methylation in a majority of sporadic colorectal tumors with
microsatellite instability (MSI) due to MLH1 methylation. In the study, they looked at 33
loci in 50 primary colorectal cancers and 15 colonic adenomas. The majority of loci
analyzed in these tumors showed methylation in both tumor and normal tissue. They
concluded that the observed hypermethylation of these loci was a consequence of age;
hence, they termed them Type-A markers (age specific). However, a small number of
these loci were differentially methylated in tumor and not in normal tissue. This group of
markers was termed Type-C (cancer specific). A distinct subset of colorectal tumors and
adenomas that had these Type-C markers differentially hypermethylated were considered
to be CIMP+. Since then, CIMP has been identified in other cancers such pancreatic
adenocarcinomas, hepatocellular carcinoma, ovarian carcinoma and gastric cancer [91,
95, 102, 108].
Although not unanimously accepted [120], the influential work by Toyota et al.
elicited a slew of publications confirming the existence of CIMP [19, 87, 101, 104]. A
possible explanation for the phenotype observed is the presence of a defect in a trans-
acting factor. Many investigators, including our laboratory, have observed a strong
74
association between CIMP and MLH1 hypermethylation, and a B-RAF
V600E
mutation [48,
67, 114]. Our laboratory confirmed the existence of CIMP using a large sample set and
highlighted the tight association of the B-RAF
V600E
mutation and CIMP+ tumors [114].
This very tight association between B-RAF
V600E
and CIMP+ tumors sparked interest in
whether B-RAF
V600E
plays a causative role in the development of CIMP. With a plethora
of known B-RAF mutations, the most common is the Valine to Glutamic Acid
substitution, which is found in about 90% of B-RAF mutant tumors. Nearly all CIMP+
colorectal tumors have the B-RAF
V600E
mutation and anywhere from 5-22% of colorectal
cancers have the B-RAF
V600E
mutation [25, 114]. This mutation is a T to A transversion
mutation, which constitutively activates B-RAF.
B-RAF is a component of the mitogen-activated protein kinase (MAP-kinase)
pathway. It is a downstream effector of Ras signaling in response to extracellular signals,
such as growth factors and hormones, and it also behaves as a kinase by phosphorylating
MEK and ultimately ERK1/2. The activation of ERK1/2 allows for the entrance into the
nucleus thereby allowing expression of ERK responsive genes. B-RAF is generally in the
inactive form and becomes activated only when phosphorylated at Thr
599
and Ser
602

residues. In the case of constitutively active mutations of B-RAF, mainly B-RAF
V600E
,
the mutation disrupts the normal hydrophobic interaction between the activation segment
and P-loop that maintains basal B-RAF in an inactive conformation [71, 111]. In the case
of B-RAF
wt
, the phosphorylation at Thr
599
and Ser
602
cause normal disruption of this
conformation, allowing for activation of B-RAF. The constitutive activation of B-RAF by
the Valine to Glutamic Acid mutation at residue 600 has the same effect of stimulating
endogenous MAP-kinase and ultimately ERK1/2 activation. This activation leads to
75
enhanced cellular proliferation and survival [33, 49, 111, 116, 122]. However, B-RAF
activation is not sufficient for tumorigenesis since mutations in B-RAF are observed in
non-malignant transformed tissues such as benign nevi and pre-malignant polyps of the
colon [83, 122]. Therefore, additional hits are necessary for progression into metastases.
In recent years, a phenomenon called Oncogene Induced Senescence (OIS) has
uncovered an alternative mechanism by which oncogenes participate in ‘permanent’
status of cellular arrest [5, 6, 9, 11, 73]. Briefly, once a cell acquires an oncogenic
mutation, it goes through a rapid but short phase of proliferation followed by cellular
arrest. The cell remains in this state unless it acquires additional mutation/inactivation of
p16, p53, pRB and/or PTEN. The inactivation allows the cells to escape senescence and
proceed with a second round of expansion. Following deregulation of hTERT, the cells
are rendered immortalized. However, they still have not obtained metastatic potential.
Elucidation of how the cells finally cross the threshold into malignancy was largely
unknown until early 2008 [72]. Wajapeyee et al. demonstrated using human melanoma
model that one possible mechanism for the progression from cellular senescence to
melanomagenesis was through epigenetic inactivation of IGFBP7 [109].
In this study, we aimed to address the question of whether B-RAF mutation at
residue 600 plays a causative role in the CIMP phenotype. We attempted to study the
effect of the mutation on differential DNA methylation by generating transgenic mice
using human B-RAF
T1799A
cDNA under the control of rat Fabp(l) (Fatty Acid Binding
Protein) promoter [92]. Since CIMP is very well characterized in the colon, we intended
to express the oncogene in the small intestine and colon. However, it is important to
mention that Fabp(l) is a 35 base-pair sequence from the liver fatty acid-binding protein
76
gene, and therefore mutant B-RAF
V600E
expression is also expected in other organs such
as liver, kidney, stomach and spleen [92]. Also, tissue specific expression of the
oncogene is important because ubiquitous over-expression of B-raf
V600E
in mice has been
reported to be embryonic lethal at 7.5 dpc [71, 117].

Materials and Methods
Generation of the Transgenic Mouse
A construct containing the human B-RAF
T1799A
cDNA under the control of the
CMV promoter was purchased from Biomyx Technology (San Diego, CA). The construct
contained two HA-epitope tags located at the 5’ end of the cDNA and a SV40 polyA
sequence. The CMV promoter was excised using XmnI and BamHI and replaced with the
Fabp(l) promoter preceding the rabbit beta-globin intron (Figure 4.1). The construct was
digested with digested with XmnI and NotI and run on 1% low melting agarose gel and
4460bp band was excised from the gel and DNA was purified using Qiagen Gel
Extraction kit followed by Phenol:Chloroform purification. The DNA was then injected
in B6D2F1 hybrid mouse pronucleus. Small tail biopsies were obtained from the pups
and genotyped for the presence of the transgene.

77
Transgenic Construct for Fabp-BRAF
V600E

Figure 4.1: Transgenic Construct for Fabp-BRAF
V600E

Construct used to generate the transgenic animals. The rat Fabp(l) promoter is used to
express human B-RAF
T1799A
cDNA. The rabbit beta-globin intron is used to facilitate
translation of transgene. The cDNA is tagged with two copies of HA-epitope tags to
differentiate the resulting mRNA and protein from endogenous B-raf. Restriction
endonucleases, XmntI and NotI were used to excise a 4460bp fragment for injection into
mouse pronuclei.

78
Tail DNA Isolation Procedure
Approximately 1 cm tail biopsies were obtained from 4-week-old mice and
incubated in 500 µL lysis buffer (100 mM Tris.HCl pH 8.5, 5 mM EDTA, 0.2% SDS,
200 mM NaCl, 100 µg Proteinase K/mL) overnight at 50°C. The following day, samples
were spun at maximum speed for 10 minutes at room temperature and the supernatant
was transferred into a clean 1.5 mL Eppendorf tube. The pellet, which contained debris,
was discarded. Approximately 1.5 volume (750µL) of isopropanol was added to the
supernatant and gently mixed by inverting the tube about 20 times or until the DNA had
precipitated. The DNA was fished out using pipet tips and dissolved in 150 µL of TE
buffer (10 mM Tris.HCl, 0.1 mM EDTA, pH 7.5). The DNA was allowed to dissolve
further overnight at 50°C. After this incubation period, the DNA was ready for analysis
[55].

Genotyping
DNA from the overnight incubation was diluted 1:50 and was used for
genotyping. PCR cocktail mix was prepared with final concentration of 5% DMSO, 1X
PCR buffer, 2.0 mM MgCl
2
, 0.2 mM dNTP, 0.35 mM primer mix, 0.5 U Taq. 20 µL of
the cocktail mix was added to 5 µL of the 1:50 DNA dilution. Diluting the primers to 20
mM from a stock of 200 mM generated the primer mix. Primers specific for endogenous
wildtype Dnmt1 were used as internal control. The list of primers can be found in Table
4.1. The PCR condition were as follows: 94°C for 5 min followed by 35 cycles of 94°C
for 50 s, 56°C for 50 s, 72°C for 1 min 30 s. The PCR was ended at 72°C for 10 minutes
followed by 4°C incubation until ready to run on gel. The PCR products were resolved on
79
a 2% agarose gel. OL-168 and OL-173 produced a 342-bp wild-type specific band for
Dnmt1 and OL-1159 and OL-1161 produce a 710-bp band for the B-RAF
T1799A
transgene.

Genotyping Primer Sequence
Oligo ID Alternate Name Primer Sequence
OL-1159 BRAF-Tg Sense 5' TGGTTATTGTGCTGTCTCATCAT 3'
OL-1161 BRAF-Tg Antisense 5' GAAGATGTAACGGTATCCATTGA 3'
OL-168 Dnmt1 Reverse for +/+ 5' CCAACAAACCAGTATGTCTCGT 3'
OL-173 Dnmt1 forward 5' CCCAGTTTCCAGAAAGCTACC 3'

Table 4.1 Genotyping Primer Sequence: List and sequence of primers used for
genotyping B-RAF
T1799A
and Dnmt1 mice.

RNA and DNA Isolation from Tissue
Approximately 35 mg of tissue specimen was harvested from the animal, dropped
into 1 mL of TriZol® (Invitrogen Corporation Cat #15596-018) in a 50 mL falcon tube
and homogenized using electric homogenizer. The contents were transferred into 1.5 mL
microfuge tube and spun at maximum speed for 3 minutes at room temperature. The
supernatant was recovered and placed in clean 1.5 mL microfuge tube while the pellet
was discarded. Chloroform was added at a volume of 200 µL per mL TriZol® used. The
contents were vortexed vigorously and allowed to incubate on bench top for 3 minutes at
room temperature. After the 3-minute period, the tubes were placed in a refrigerated
centrifuge and spun at 12,000g for 15 minutes at 4°C. After centrifugation, the aqueous
layer, which contains the RNA, was removed and placed in a clean 1.5 mL microfuge
tube and the bottom, organic layer, which contains the DNA is kept for later use or frozen
if not processed the same day.
To the aqueous layer, 500 µL of isopropanol was added and the tube was inverted
gently several times to ensure proper mixing. The tube was then placed at -20°C for 1-2
80
hours. After the incubation period, the samples were spun at 12,000 g for 10 minutes at
4°C. The supernatant was removed and discarded and the pellet was washed with 1 mL
of 75% ethanol/mL of TriZol® used. The sample was again spun at maximum speed for
5 minutes at 4°C. The supernatant was removed and discarded. Depending on the size of
the precipitate, approximately 200 µL of RNase-free H
2
O was used to dissolve the pellet.
The sample was then placed in 80°C heat block for 5 minutes to dissolve RNA and
evaporate residual ethanol contamination.
For DNA isolation, 300 µL of 100% ethanol was added to the organic phase and
inverted several times until the solution was clear. The contents were spun down at
maximum speed for 5 minutes at 4°C. The organic phase (supernatant) was removed and
discarded and the pellet was washed with 1 mL of 0.1 M sodium citrate in 10%
Ethanol/mL TriZol® used. The pellet with the sodium citrate buffer was vortexed
vigorously and allowed to incubate at room temperature for 30 minutes. After the 30-
minute incubation period, the samples were spun at maximum speed for 3 minutes at
room temperature. The supernatant was removed and the washing process with the
sodium citrate was repeated twice more. To the pellet, 1.5 mL of 75% ethanol/mL of
TriZol® used was added and incubated at room temperature for 20 minutes with periodic
vortexing. The samples were then spun at maximum speed for 5 minutes, supernatant was
removed and 200 µL of TE was added to the pellet and placed in 80°C for 10-15 minutes
to allow rapid dissolving and evaporation of ethanol. The tubes were then removed from
the heat block and let sit at room temperture for 5-10 minutes to cool down. The contents
were spun one last time at maximum speed for 5 minutes and the supernatant is
transferred into a clean 1.5 mL microfuge tube, taking care that the debris at the bottom
81
of the tube is not transferred to the new tube. The contents in the new tube were then
ready for spectrophotometric measurements.

DNase Treatment of RNA Samples
RNA extracted from the tissue was diluted to 200 ng/µL and DNase treated using
TURBO DNA-free from Applied Biosystems (Cat No. AM1907). First, 43 µL of 200
ng/µL of total RNA was incubated with 5 uL of 10X TURBO buffer and 1 µL of
TURBO DNase enzyme for 30 minutes at 37 °C. After the 30-minute incubation period,
another 1 µL of TURBO DNase was added for an additional 30 minutes at 37 °C. Total
volume after the treatment was 50 µL and total RNA concentration was 172 ng/µL.

Reverse Transcriptase cDNA Synthesis
Approximately 1.4 µg (8 µL) of DNase-treated RNA (see Materials and Methods
– DNase Treatment of RNA Samples) was used for cDNA synthesis using SuperScript
III First-Strand Synthesis from Invitrogen (Cat No. 18080-400). Synthesis was performed
per manufacturer’s instructions. The final volume after reverse transcriptase was
performed was 20 µL. The cDNA was then diluted 25 fold to a final concentration of
2.75 ng/µL (500 µL).

Real-Time RT-PCR
10 µL of cDNA (see Materials and Methods – Reverse Transcriptase cDNA
Synthesis) was used for each reaction performed. All RT-PCR primer and probe sets used
for this chapter are located in Supplemental Table 2. Real-Time RT-PCR was performed
82
in a 30 µL reaction volume with 200 µM dNTPs, 0.3 µM forward and reverse PCR
primers, 0.1 µM probe, 3.5 mM MgCl
2
, 0.01% Tween-20, 0.05% gelatin and 0.1 U of
Taq polymerase using the following PCR conditions: 95° C for 10 minutes, then 50
cycles of 95° C for 15 s followed by 60° C for 1 minute. The samples in 96-well plate
were analyzed on the Opticon DNA Engine Continuous Fluorescence Detector (MJ
Research/Bio-Rad). A standard curve using the gene of interest was generated.

M. SssI Treatment
Mouse Tail DNA as used as template for M. SssI treament. Tail DNA at a
concentration of 0.05 µg/µL was incubated with M. SssI (New England Biolabs) at a
concentration of 0.05 U/µL and 0.16 mM S-adenosylmethionine overnight at 37° C. A
boost was added to the mixture the following day with extra S-adenosylmethionine (to
0.20mM) and M. SssI (to 0.065 U/µL) and allowed to incubate again overnight at 37° C.
The mixture was phenol:Chloroform purified and aliquots were made for future use.

Bisulfite Conversion
DNA bisulfite conversion was carried out using EZ DNA Methylation KIT™
from Zymo Research Corporation (Cat# D5002). The reaction was carried out per the
manufacturer’s instructions. However, the 16 hour incubation at 50°C was carried out
using cycling in a PCR machine. Contents were incubated for 1 minute at 95°C followed
by a 1-hour incubation at 50°C. The process was cycled 16 times. At the end of the
program, the samples were removed from the PCR machine and placed on ice for 10
minutes. The recovery step was performed per the manufacturer’s instructions.
83
MethyLight
All PCR primer and probe sets used for this chapter are located in Supplemental
Table 2. MethyLight PCR was performed in a 30 µL reaction volume with 200 µM
dNTPs, 0.3 µM forward and reverse PCR primers, 0.1 µM probe, 3.5 mM MgCl
2
, 0.01%
Tween-20, 0.05% gelatin and 0.1 U of Taq polymerase using the following PCR
conditions: 95° C for 10 minutes, then 50 cycles of 95° C for 15 s followed by 60° C for
1 minute. The samples were analyzed in a 96-well plate on the Opticon DNA Engine
Continuous Fluorescence Detector (MJ Research/Bio-Rad). A standard curve for the
Lhx1 control reaction was generated from 1:25 serial dilutions of 3X M. SssI-treated,
bisulfite converted DNA [113].

DNA Methylation Analysis
Genomic DNA was isolated (see Materials and Methods – RNA and DNA
isolation from tissue) and subjected to bisulfite treatment (see Materials and Methods –
Bisulfite Conversion) followed by MethyLight analysis. The list of MethyLight reactions
is provided in Supplemental Table 2. MethyLight data is provided in the form of a ratio
using a standard curve to extrapolate the log value using threshold C(t) value between the
methylated locus of interest and methylation-independent normalization reaction. In our
studies, the methylation-independent reaction was Lhx1. Due to variation in reaction
performance and other PCR parameters, it is necessary to normalize this ratio to the ratio
obtained for a constant reference sample; in our case M. SssI-treated DNA. The M. SssI-
treated reference sample was also used to generate the standard curve. The values are
given as Percentage Methylated Reference (PMR), which is 100 X (methylated reaction /
84
control reaction)
sample
/ (methylated reaction / control reaction)
M.SssI reference sample
. The
‘methylated reaction’ refers to the methylation measurement of the locus of interest and
the ‘control reaction’ refers to the methylation-independent measurement of Lhx1.

Results
Twenty fertilized eggs, which were injected with the Fabp-BRAF
V600E
transgene,
were implanted in pseudo-pregnant females. Sixteen pups were born and survived to
adulthood. Out of the 16 pups, only 5 carried the transgene and germline transmission
was observed in four out of five lines. The founders were then crossed with the wildtype
C57BL/6 strain to maintain the line and to create progeny to use for phenotypic analyses.
Initially, our goal was to monitor tumor development in the intestine of the mice, since
our promoter is active in the intestine. None of the mice to date have shown any signs of
tumorigenesis in the intestine. This conclusion is based on macroscopic and microscopic
analysis. However, two out of the four founders showed large tumors of the liver while
the other two did not. Lines without a phenotype were terminated. Progeny from the
founders with the phenotype (Line 4 and Line 5) were maintained and used for analyses.
Tumors of the liver were found to appear at around 11 months of age for line 5 and at
around 14 months of age for line 4 (Figure 4.2). Animals that harbored tumors of the
liver did not show any signs of morbidity at time of sacrifice. Therefore, they were
allowed to age up to the experimental time point. Histological analysis of these liver
tumors showed regions of clear cell altered focus, liver cell dysplasia and adenoma. No
signs of metastases leading to hepatocellular carcinoma were found. Penetrance of the
phenotype was about 80%.
85
Livers From Wildtype Littermate and Transgenic Animal

Figure 4.2: Livers from Wildtype Littermate and Transgenic Animal
Livers were harvested from the animals at approximately 12 months of age. (a) Entire
liver from wildtype littermate showing no signs of macroscopic lesions. (b) Two livers
from B-RAF
V600E
littermates. Both livers have very large tumors ranging from 0.5 cm to
1.0 cm. The animals did not show any signs of morbidity at time of sacrifice.

86
DNA Methylation Analysis of Liver Tissue Samples
Our goal was to determine whether mutations of B-RAF at amino acid residue
600 can lead to the CIMP phenotype observed in humans. We designed MethyLight
reactions for mouse orthologs of top CIMP+ makers based on human studies. Reactions
that are methylated in mouse models of cancer or development were also used for the
analysis. These markers were used to simply broaden our search for differentially
methylated loci. We used several different types of tissues from our model. We used liver
samples from wildtype littermates, mice that had the transgene but never developed
tumors and tumor samples from those that did. Based on our screen, none of the CIMP+
orthologs showed a differential methylation profile in our model. However, we did see an
increase in DNA methylation levels as we progressed from wildtype liver samples to
tumor for the gene Insm2 (Figure 4.3). Statistical analysis using the Student’s T-test to
compare the three different tissue types showed a significant difference between liver
samples from transgenic mice without tumors and tumor samples from transgenic mice
that showed phenotype (Figure 4.4).

87
MethyLight Analysis of Mouse Liver Tissue

Figure 4.3: MethyLight Analysis of Mouse Liver Tissue
Livers from wildtype mouse, livers from B-RAF
V600E
mice without macroscopic tumors,
and liver tumors from B-RAF
V600E
mice are presented on the vertical axis. The x-axis
represents MethyLight reactions for different loci. PMR values are given in the colored
cells. The colors within the cells indicate the level of methylation. Pink, human orthologs
of CIMP genes. Gray, not data available. Blue, no detectable methylation (PMR=0).
Green, intermediate-low level of methylation (0 < PMR ≤ 5). Yellow, intermediate-high
level of methylation (5 < PMR ≤ 50). Red, high level of methylation (PMR > 50).

Sdc1
Cacna1g
Bcl2
Mlh1
Neurod2
Neurog1
Sfrp2
Bdnf
Gata3
Crab1
Nr3c1
Gata4
Hoxa1
Socs1
Mlh1
Hic1
Sall1
Hras1
Gata5
Cbs
Ahcy
Stk11
Esr1
Apc
Srp19
Snail1
Insm2
Cdh1
Ascl2
Casp8
0 2 0 0 9 0 0 3 0 0 0 0 0 0 0 0 0 0 4 0 0 0 55 0 0 0 6 0 0 0
4 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 3 0 0 0
0 1 0 0 16 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 37 0 0 0 1 0 0 0
0 1 0 0 9 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 70 0 0 0 3 0 0 0
0 0 0 0 10 0 0 1 0 0 0 0 0 0 0 0 0 0 5 0 0 0 21 0 0 0 2 0 0 0
0 0 0 0 3 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 37 0 0 0 1 0 0 0
0 0 0 0 24 0 0 4 0 0 0 1 0 0 0 0 0 0 3 0 0 0 67 0 0 0 15 0 0 0
1 1 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 51 0 0 1 5 0 0 0
6
19
19
0 1 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 99 0 0 0 1 0 0 0
0 2 0 0 4 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 35 0 0 0 4 0 0 0
4 1 0 0 5 0 1 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 30 0 0 0 8 0 0 0
3 1 0 0 8 0 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 21 0 0 0 8 0 0 0
1 1 0 0 3 0 0 1 1 0 0 0 0 0 0 0 4 0 5 0 0 0 120 0 0 0 10 0 0 0
0 2 0 0 5 0 0 1 0 0 0 0 0 0 0 0 3 0 5 0 0 0 41 0 0 0 9 0 0 0
0 0 0 0 24 0 0 2 4 0 0 0 0 0 0 0 0 0 3 0 0 0 38 0 0 0 8 0 0 0
17 0 0 0 23 0 0 1 0 0 0 0 0 0 0 0 0 0 5 0 0 0 37 0 0 0 7 0 0 0
0 1 0 0 38 0 0 1 0 0 0 0 0 0 0 0 3 0 5 0 0 0 37 0 0 0 8 0 0 0
1 2 0 0 5 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 21 0 0 0 5 0 0 0
0 2 0 0 5 0 0 3 0 0 0 3 2 0 0 0 0 0 2 0 0 0 58 0 0 0 5 0 0 0
0 3 0 0 48 0 0 1 0 0 0 0 0 0 0 0 0 0 32 0 0 0 232 0 1 0 51 0 0 0
0 2 0 0 0 0 5 2 2 1 0 0 0 0 0 0 0 0 3 0 0 0 38 0 0 0 72 0 0 0
1 1 0 0 5 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 77 0 0 0 10 0 0 0
0 2 0 0 10 0 0 4 0 0 0 0 0 0 0 0 0 0 2 0 0 0 67 0 0 0 16 0 0 0
30
103
35
59
Wildtype
B-RAF
V600E
/+ B-RAF
V600E
/+ Genotype
Phenotype
Tissue Type
N/A No tumors Tumors
Normal Liver Normal Liver Tumor
88
Insm2 Methylation Level Using MethyLight

Figure 4.4: Insm2 Methylation level Using MethyLight
The plot shows median PMR of Insm2 for three different groups. All values are given as
PMR. N, indicates number of mice analyzed. Horizontal line indicates median. Asterisk
indicate statistical significance using Student’s T-test.

*
89
Expression Study – B-RAF
V600E

The penetrance for the phenotype was approximately 80%. Therefore, we set out
to investigate whether heterogeneity in expression of the transgene was responsible for
the variation in phenotype. One possibility would be that the transgene level is relatively
constant between the mice that did develop tumors and the ones that did not. A second
possibility would be that B-RAF
V600E
is being differentially expressed and tumorigenesis
is only observed in samples with sufficient B-RAF
V600E
expression. We measured the
expression level of the transgene in liver samples from mice that did develop tumors and
mice that carried the transgene but did not develop tumors. We also included wildtype
littermates as negative control. We isolated total RNA from liver samples and performed
Real-Time RT-PCR using a reaction specific for the mutant B-RAF
V600E
and normalized
the values using β-Actin. Figure 4.5 compares the difference in transgene expression
between tumor tissue and non-tumor adjacent liver and it also compares transgene
expression difference between non-tumor adjacent liver and liver from transgenic animals
that never developed tumors. Preliminary results suggest that a high B-RAF
V600E

expression in normal liver contributes significantly to tumorigenesis and that B-RAF
V600E

expression is being regulated by an unknown mechanism in some mice that carry the
transgene but never develop tumors.
Based on the results obtained from figure 4.5, our first conclusion is that high B-
RAF
V600E
expression appears to be necessary for tumorigenesis. We draw this conclusion
because the lower B-RAF
V600E
expression is seen in non-tumor adjacent and in mice that
never develop tumors. Thus, low expression of transgene is not sufficient to cause the
phenotype. If adequate B-RAF
V600E
expression were not required for the phenotype,
90
then we would expect tumorigenesis irrespective of B-RAF
V600E
levels. The second
conclusion is that BRAF
V600E
expression is being affected by an unknown mechanism in
some mice that carry the transgene but never develop tumors. Although not obvious from
figure 4.5, three out of four animals that never developed tumors had 100 fold less B-
RAF
V600E
expression compared to non-tumor adjacent. In fact, B-RAF
V600E
expression
levels in these mice were at background levels, which were very comparable to wildtype
littermates. Mice that carried the transgene but never developed tumors had littermates
that also carried the transgene but did develop tumors. Therefore, this observation was
not unique to a particular cross.

91
B-RAF
V600E
Expression in Liver from Line 4 and Line 5

Figure 4.5: B-RAF
V600E
Expression in Liver from Line 4 and Line 5
Quantitative RT-PCR using RNA prepared from wildtype littermate (n=4), liver from
transgenic animals that never developed tumor (n=4), matched non-tumor adjacent (n=6)
and liver tumors (n=7). Columns, relative expression of B-RAF
V600E
after normalization
to β-Actin. There was no detectable expression in liver tissue from wildtype mice. The
error bars represent the standard error. Asterisk, statistical significance using Student’s t-
test comparing Tumor to Adjacent Non-Tumor Liver (p<0.05)

92
There are several ways in which this observation could be explained. The first
possibility is that the chromosomes that carry the transgene have not segregated
completely. Since we are using a transgenic approach rather than gene targeting
approach, it is possible that the transgene has integrated at more than one chromosomal
location. In the event that the transgene integrations have not segregated completely, we
anticipate having variations within a lineage. The variation within a lineage would cause
transgene expression differences, depending on whether the inherited transgene was
integrated in a heterochromatic or euchromatic region. A second possibility for the
differential expression could be that the transgene is being epigenetically regulated. If in
fact epigenetics is involved in the regulation of the transgene, then further
experimentations would be necessary to determine whether the regulation is a result of a
defense mechanism of the host leading to silencing of the exogenous DNA or whether it
is a B-RAF
V600E
specific phenomenon.

Expression Study – Igfbp7
We next determined whether there is a difference in Igfbp7 expression between
the same samples used in figure 4.5. As mentioned earlier, methylation of IGFBP7 was
demonstrated to play a vital role in melanomagenesis. Wajapeyee et al. demonstrated that
complete suppression of IGFBP7 by DNA methylation results in uncontrolled
proliferation of benign nevi to melanoma [109]. In the study, they demonstrated that
primary cells that express B-RAF
V600E
secrete IGFBP7, which acts to induce senescence
and apoptosis. Therefore, IGFBP7 is necessary to maintain the cells in permanent
cellular arrest in the context of mutant B-RAF positive melanoma cells [109]. In our
93
study, we set out to determine whether Igfbp7 expression is also regulated in our tumor
model. In melanoma cells harboring B-RAF
V600E
mutation, IGFBP7 expression is
severely down regulated. Therefore, loss of IGFBP7 expression is a critical step in
melanoma genesis. Since B-RAF mutation in our mouse model does not induce malignant
tumors of the liver of some mice, we do not expect dramatic down regulation of Igfbp7
expression in tumors compared to non-tumor adjacent and liver from mice that never
developed tumors (Figure 4.6). Results from figure 4.6 demonstrate a subtle decrease in
Igfbp7 expression in tumors, suggesting that our model may behave similar to the human
melanoma model in the context of B-RAF mutation. Further experimentation would be
necessary to determine whether existence of additional, cooperating events is necessary
for tumor development in our model.

94
Igfbp7 Expression in Liver from Line 4 and Line 5

Figure 4.6: Igfbp7 Expression in Liver from Line 4 and Line 5
Quantitative RT-PCR using RNA prepared from wildtype littermates (n=4), liver from
transgenic animals that never developed tumors (n=4), matched non-tumor adjacent (n=6)
and liver tumors (n=7). Columns, relative expression of Igfbp7 after normalization to β-
Actin. The error bars represent the standard error. Asterisk, statistical significance using
the Student’s t-test comparing Tumor to Wildtype (p<0.05)

95
Discussion
A thymine to adenine transversion mutation at location 1799 is the most common
genetic alteration in human B-RAF. In fact, 90% of all B-RAF mutations are the resuling
valine to glutamic acid substitutions at amino acid residue 600. This activating mutation
of B-RAF is detected in 70% of melanomas, 15-22% of colorectal, 40% of papillary
thyroid, 30% of ovarian, and 3% of non-small-cell lung cancers [15]. B-RAF
V600E
has
demonstrated its oncogenic potential in various organs using genetically engineered
mouse models of cancer [14, 44, 51, 99]. We have generated a mouse model of B-
RAF
V600E
that develops adenomas of the liver. This is not the first report of B-RAF
V600E

induced tumorigenesis of the liver. Chemical induction of B-raf and Ha-ras mutations
was also found to induce tumors of the liver [43]. However, the B-RAF mutation at
codon 600 is not seen in human hepatocellular carcinoma but is common in
cholangiocarcinoma. The reason why B-RAF mutations are not detected in human
hepatocellular carcinoma are unknown, but one may speculate that B-RAF mutation is
not tolerated in liver malignancies and that cells that acquire the mutation may undergo
apoptosis before clonal expansion.
Over-expression models of oncogene-induced tumors are particularly difficult
since small differences in oncogene activity could cause proliferation or cell cycle arrest
[118, 123]. Interestingly, RAF oncogenes over-expressed in primary cells have been
shown to induce cellular senescence unless accompanied by mutations in the p19
ARF
/p53
pathway [59, 68, 118]. Tuverson et al. recently demonstrated it that the expression of
lower, more physiological levels of K-ras
G12D
in mice promotes proliferation and partial
transformation in primary cells, without a cooperating event [106]. Based on these
96
findings, Dankort et al. generated B-Raf
V600E
mice with particular attention to levels of
oncogene expression [14]. Although not mentioned previously, B-RAF
V600E
expression in
line 4 was 10-fold greater than in line 5. However, line 4 developed tumors much later
than line 5. Findings by Tuverson et al. may explain this phenomenon in our mouse
model and this system may provide another example for the importance of oncogene
expression levels.
The goal of this project was to identify CIMP in a mouse model of cancer.
Previously, we had designed and analyzed the methylation profile of mouse orthologs for
some of the human CIMP genes (CACNA1G, NEUROG1, SOCS1, CDKN2A and MLH1)
on various mouse models of intestinal cancer, non-tumor adjacent tissue and tissue from
aged mice (data not shown). We did not observe frequent methylation differences of
these loci compared to matched normal mucosal counterparts. We also included several
other loci in this screen that showed differential methylation in mouse models of various
cancers and during development based on literature search. In this study, we concluded
that the human CIMP genes do not show a differential methylation profile in mouse
tumors and normal tissue. Interestingly, however, in the case with Cdkn2a, the
methylation pattern suggested age-associated methylation rather than cancer-associated
methylation in the tissues analyzed. This data suggested that genes used to identify
CIMP in human colorectal cancer could not be used in mouse models of intestinal
cancers. None of the loci screened demonstrated strong cancer-associated methylation
pattern. Based on this result, only loci that did not show age-associated methylation
patten were used for further studies of liver samples from the B-RAF
V600E
mice. One such
locus that did show differential methylation in the liver samples was Insm2. This gene
97
was identified by shotgun sequencing of a bacterial artificial chromosome clone and was
later identified as a novel member of the Snail/Slug SNAG transcriptional repressor
family. These proteins work as transcriptional repressors in several developmental
processes.
Insulinoma Associated Protein 2, Insm2, is an intronless gene located on
chromosome 14 of mouse genome. It bears strong sequence homology to Insm1, which
encodes a Zinc-finger DNA-binding motif that is expressed in embryonic development
and re-expressed in neuroendocrine tumors [82]. Insm2 is a major autoantigen in Type-1
diabetes and studies have shown that this autoantibody can appear years before the
development of Type-1 diabetes [56]. Recent genome-wide data analysis of colorectal
tumors from our lab identified INSM2 as a potential CIMP+ marker and a target for
Polycomb Repressor Complex 2 (unpublished data). However, methylation of Insm2 is
not specific to B-RAF
V600E
induced tumorigenesis. It has been shown that SV40 T-
Antigen-induced tumors of the liver also show methylation of Insm2 [99]. Therefore, the
methylation of this locus may be liver tumor specific. Based on our result, we cannot
conclude that B-RAF
V600E
does not induce CIMP in mice. It may be possible that the loci
analyzed do not undergo methylation in mouse tumors. A genome-wide, mouse DNA
methylation analysis would be necessary to determine the causal role of B-RAF
V600E
on
CIMP. However, our data does suggest that markers used to classify CIMP in human
colorectal tumors cannot be used in our mouse model of B-RAF
V600E
induced liver
tumorigenesis. This finding may be due to both tissue-specific and species-specific
differences between the two models. The use of normal human colonic mucosal cell lines
would provide a better model. As these cells are very difficult to obtain, Hinoue et al.
98
performed stable transfection assay of mutant B-RAF
T1799A
in human colorectal cancer
cell lines that were CIMP- and B-RAF
wt
(manuscript submitted). The finding was that B-
RAF
V600E
could not induce CIMP in human colorectal cancer cell lines. A caveat was that
cell lines used for this study had been in culture for decades and therefore may have
already acquired all the epigenetic alterations necessary for growth and proliferation.
Another likely scenario is that B-RAFV600E simply does not induce differential
methylation.
We also examined the effect of B-RAF
V600E
on Igfbp7 expression. Normal human
melanocytes (B-RAF
wt
) express and secrete low levels of IGFBP7, which inhibits MAP
Kinase signaling through an autocrine/paracrine pathway, thereby suppressing
proliferation [109]. In B-RAF
V600E
positive nevi, constitutive activation of the MAP
Kinase pathway increases expression and secretion of IGFBP7, and the resulting high
levels of IGFBP7 inhibit BRAF-MEK-ERK signaling and activate senescence [109].
However, in a B-RAF
V600E
positive melanoma, IGFBP7 expression is lost, therefore
enabling the cells to escape from senescence which results in uncontrolled proliferation
[109]. Addition of exogenous IGFBP7 to B-RAF
V600E
positive melanoma cells inhibits
MAP Kinase signaling and activates apoptosis[109].
Study by Wajapeyee et al. has extensively described the involvement of IGFBP7
in cellular senescence in B-RAF
V600E
positive melanoma but the events leading to the
inactivation of IGFBP7 by promoter methylation still remain unknown. Reasons for why
genes become hypermethylated are one the most compelling questions in cancer biology.
Some believe this to be a stochastic event where methylation at certain loci confers
selective advantage for the cell to grow and proliferate. Others believe that there may be
99
alterations in trans-acting factors in cancer cells leading to changes in DNA methylation
patterns. The use of our model to study such events would be desirable because the
progression of gene expression alterations can be closely monitored in vivo over time.
Yet another advantage of our mouse model is that the tumors develop much later in life,
therefore allowing enough time for epigenetic alterations to occur.

100
Chapter 5: Discussion
In our study presented in Chapter 2 of this dissertation, we attempted to identify
blood markers for the detection of pancreatic cancer. We have demonstrated the utility of
both a candidate gene approach and a genome-wide approach in identifying genes that
are differentially methylated in pancreatic cancer tissue. Our panel of markers thus far
has been able to identify differential methylation differences in primary tissue samples
only. If these markers were to be used in a non-invasive clinical setting, it would be
imperative that we detect these cancer-specific molecules in blood.
Detection of cancer-specific DNA methylation molecules has been quite
challenging for our studies. A recent publication by Melnikov et al. claims that
differential methylation profiling of plasma DNA can detect ductal adenocarcinomas of
the pancreas with significant accuracy using a technology called MethDet, which utilizes
Restriction Enzyme digestion followed by PCR amplification, Cy3 and Cy5 conjugation
and hybridization [70]. However, their data demonstrates 41% false positive results. The
most important measurement for population-based screening tests is the specificity of the
screen. In other words, it is the rate of false positive results. Inaccurate diagnosis could
decrease quality of patient life and often lead to invasive follow up procedures that have
associated morbidity and mortality. We believe that our technology, Digital MethyLight,
is sensitive enough to detect low concentration of methylated DNA molecules, however,
further analysis will be necessary to determine the exact cause for the inability of
detection in patient blood.
The importance of DNA methylation is not restricted to early detection only. As
mentioned in earlier chapters, it is implicated in many important biological processes
101
such as embryonic development, transcription regulation, X-Chromosome inactivation,
genomic imprinting, chromosomal instability and repression of retrotransposons [39,
110]. In chapter 3, we discussed a mouse model of pancreatic cancer that demonstrates
the role of DNA methylation in cancer progression. The broader implication of our study
was that DNA methylation is necessary for carcinomagenesis. The importance of DNA
methylation on tumorigenesis has been previously demonstrated in mouse models of
cancer [12, 17, 54, 105, 119]. It would be interesting to understand at what stage of
tumorigenesis DNA methylation is most influential. In the Apc
Min/+
model of intestinal
tumors, carcinogenesis occurs in two stages, with the formation of microadenomas
leading to the development of macroscopic polyps. Findings by Yamada et al. support
“the notion of a dual role for DNA hypomethylation in suppressing later stage of
intestinal tumorigenesis, but promoting early lesions in the colon” [119]. It is known that
global DNA hypomethylation promotes chromosomal instability in ES cells and mice,
which results in the development of T cell lymphoma and also accelerates tumor
formation in a mouse sarcoma model [7, 18, 26, 105]. This observation is consistent with
chromosomal instability as the prevailing mechanism for the initiation of these lesions.
Data from our mouse model of pancreatic acinar cell carcinoma suggests that DNA
methylation is necessary for the later stages of tumor progression but not necessary for
the initial stages. Thus, it may be possible that genetic alterations are necessary for
initiation of tumorigenesis but additional hits required for growth and proliferation
require epigenetic alterations. If this is proven to be the case, then the effectiveness of
epigenetic therapeutic agents should be assessed considering on the stage of cancer.
102
Finally, for our final project, we wanted to study whether B-RAF
V600E
can induce
CIMP in mice. CpG Island Methylator Phenotype (CIMP) was identified by Toyota et al.
and is described as a subset of tumors that have concordant methylation in a subset of
CpG islands [101]. Even though the initial publication raised criticism [120], the
influential work by Toyota et al. generated a list of publications confirming the existence
of CIMP [19, 87, 101, 104]. The cause for the phenotype observed is unknown; some
speculate a defect in a trans-acting factor. Strong evidence for the association between
CIMP and MLH1 hypermethylation and a B-RAF
T1799A
mutation has been published [48,
67, 114]. Our laboratory confirmed the existence of CIMP using a large sample set and
highlighted the tight association of B-RAF
V600E
mutation and CIMP+ tumors [114]. This
very tight association between B-RAF
V600E
and CIMP+ tumors sparked interest in
whether B-RAF
V600E
plays a causative role in the development of CIMP. We therefore
created a mouse transgenic line for tissue specific expression of B-RAF
V600E
. The CIMP
phenotype observed in human colorectal cancer was not apparent in our model since none
of the mice developed malignancy of the intestine. As discussed extensively in Chapter 4,
our mouse model developed tumors of the liver and DNA methylation analysis was
performed to assess the methylation status of the CIMP loci. We found that loci used to
assess the CIMP status of human colorectal tumors were not methylated in mouse liver
tumors. This may have several implications. First, it may suggest tissue or species
specific differences in human colorectal cancer versus mouse liver tumors. It may imply
that loci used to identify CIMP in mice are different than those in humans. Finally, it may
imply that B-RAF
V600E
simply does not induce CIMP in mice. One of the ways these
implications could be addressed and tested is with the use of genome-wide methylation
103
studies for mice. However, since such a platform does not exist yet, expression
Microarrays may shed some light on this model and help make solid conclusions about
the role of B-RAF
V600E
in CIMP.

104
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116
Appendix

Supplemental Table 1

Reaction
Number
HUGO
Gene Name Forward Primer Sequence (5' to 3') Reverse Primer Sequence (5' to 3') Probe Oligo Sequence (5' to 3')
a
HB-047 TWIST1 GTAGCGCGGCGAACGT AAACGCAACGAATCATAACCAAC CCAACGCACCCAATCGCTAAACGA
HB-075 CDH13 AATTTCGTTCGTTTTGTGCGT CTACCCGTACCGAACGATCC AACGCAAAACGCGCCCGACA
HB-163 PENK GGTTAATTATAAAGTGGTTTTAGTAGTCGTTAAG CAACGTCTCTACGAAATCACGAAC AACGCCTACCTCGCCGTCCCG
HB-164 ESR1 GGCGTTCGTTTTGGGATTG GCCGACACGCGAACTCTAA CGATAAAACCGAACGACCCGACGA
HB-184 SEZ6L GCGTTAGTAGGGAGAGAAAACGTTC ATACCAACCGCCTCCTCTAACC CCGTCGACCCTACAAAATTTAACGCCA
HB-235 PITX2 AGTTCGGTTGCGCGGTT TACTTCCCTCCCCTACCTCGTT CGACGCTCGCCCGAACGCTA
HB-267 HOXA1 GTTGTTGCGGCGATTGTAAA CGCGCAAAACGCAACTT TACTCTTCTTCGCTCCAACACTCCAAATCG
HB-313 ALU GGTTAGGTATAGTGGTTTATATTTGTAATTTTAGTA ATTAACTAAACTAATCTTAAACTCCTAACCTCA CCTACCTTAACCTCCC
b
HB-316 EYA4 GGAAAGAGTTGCGGGAAAAGT ACCAAAACTCCGAACTACGACAAA AACGCGCCCAACCGCCG
HB-317 EYA4 TGGATAGGATGGAAGTTTTGCG AACTACCGACAACGCGACG CGCTCCGACCGTTCCCGACTT
HB-361 TFPI2 TTGGAGTAGAAAGTCGCGTATTTTT AAAAATCGAACGACCCGCTA ACAAAACGTCCGAAAAAACGCCTAACGAA
HB-417 FOXE1 GGGTTAGTTCGCGACGATTTT CGAACCTAACGTCCCCGA CGAACGCTCGACCCTTCTACGAAAAACT
HB-449 CCNA1 TTCGTTCGGGCGGAGAC CGAATAAACTCGCCGCGA ACCCAACGAACGACGACCCTCCA
HB-516 HOXA9 TTATTAAGAAGGCGCGGGTTTC CAATAAAACGACAATACGATTTAACTACTTTTT TAAAAAACTCCGCTAACCGCACTCGCAC
HB-517 HS3ST2 AGTATTTTTCGGTTTTAGGCGATG CGAACCCGACGCACGTA CGAACCGCCCGACTACCCGAAAC
HB-520 NEFL TGGAGACGTTTCGGGTGTATATTT AAACACCGACGCCGAATAAC AAACGTACGATACTATAACCGCTACGCACGCT
HB-528 NEFL GTACGGATAGCGAGGAAGATATCG TACGTAAAAACGCCCCG AATAC ACGCAACGACTACAACACCGCACG
HB-529 NPY TATTCGTGCGGTTGCGGT AAAACCTCGAACAATCACGCTT CGCCACTTCCCGCCCCTAAATAACG
HB-530 ASCL2 GTTTTATTTCGTTTTAGGTAAGGCGTA CCCGCGACTAAACTAAACGC CTATCCCCTAACGCAACTATATCCCGAACG
HB-539 ADCYAP1 CGAGTTTCGGTAAACGAGTTTCG GAAAAACATCGCCGTCTAACG AAACCGCAAAAACCAACG
b
HB-545 IGFBP3 CGCGTTAGTTCGCGTTATCG CCGATTACAAACGTCATACAACG ACCCACGCTCTAAACCGCTACGCTAACTCT
HB-548 FLT1 CGGGTGGTTGAGCGTAGC CGCTTAAATCCCCAAACCG CGCTCGACGAACGCCCGC
HB-550 NTRK3 GGTTGCGTATTTTAGGTGATTTCG GACGACCGAAATCCTCTCCG CCGAATCGCGCCTCGCCAA
HB-555 RASGRF1 AGGGATTGGCGATTTGCG GCGCTACTAAAACGAACTCTTCG CGTCACATAACTCCGCCTACCCCTCG
HB-556 FLT3 TAGATTTTTACGGACGGTTTAGTATTCG TCCTCTAACTCGAACCGCGAT ACCCGAACTTCGCAAACGACCTCG
HB-597 DLK1 GCGGCGGTGGAGAGC GCGAACGCGCAACGA AAAACCAAAACTACACCGAACTACGCGCT

117
HB-615 HOXA9 GTAAGTTCGGTTTGGGAAAAGGTA GACCCCGAAACAAACCACAT ACCTCCCAAATTCCGAAACTACGAAATCTC
HB-696 FLT1 TTCGCGTTGTTTCGTCGTTT AACGTCAATTCCCCTCAAACG TACCGAAAATCTCCGATACCTTCCTAAACTTCTCG
HB-704 FGF5 CGTATCGGTTAGTGAGTATATAAAGTCGC CTAACACCGAAATATTTATAACGCCAATA TGAGGGGAAGTTTCGTAGGCGTGTACG
HB-705 GAS7 GCGTCGGGAAGTAGAGATTCG CTAAAATCCGCGAACTACCCG CGAAAACGTCGCCGCTCGCTCT
HB-709 KCNB1 GTCGAGAGTACGTTTTGTTGCG CAACGATACCGACGAACATAACG CATAACTCCCGCTCCACCAACTCGCTAC
HB-710 LAMA1 TTTCGTTTTCGTCGTTATTCGG ACCAAAACAACGCGAACTCG AACGTTCCAAACGAACGCGCGACT
HB-711 SLC6A2 GTTTTAGAGTTTGTTAAGGCGTCGTC AAACCTAACCCTATCCCGCG TCAAAACGCACTCACGTATCCGACGA
HB-713 ZNF560 TGGTTTTGAGGAAATAGGCG CAATACCCCAAACGAAAATAACG CGACGCGCCAATTCTCTCTTTTAATCGC
HB-735 GAS7 GAAAGATAGGTTTGAAGTTTGGCG TTCCTCCATTTATCCCCATCG CCAATTCTATCAACTCCGACCCCGTCTTCT
HB-739 TRIM58 TTTGAATTGAAGTTAGCGGATATTATTC CGCCTCCCGAAAAACTACG CCGACCGCCCGCACCGTC
HB-741 NEF3 CGGGATAGTGATAAAGAAAGGGC CTTTCCATTTCTCACCTCCCG CGTTTCGCACCCTTAATACGAATATCGCC
HB-744 C8orf42 GCGGCGTTTGTATTTTAGCG CGCCGAAAAAAATAAATCCC TACCCGACGCCCAAACCCCG
HB-745 ATP8A2 GATTAGTTGGAGGTATTCGTTCGTATT CCTTCCCAACTATAACTCCACCG CGCGAACCGACCGCCTTCTCC
HB-746 ZNF667 TTATATTTACGAGGTTTGGAGTCGG ACACCCCGATAAATTCTAAAAATCG CTACGTAATACGCACGCGCGAATAAACG
a
All probes have 6FAM fluorescence at 5’ end and Black Hole Quencher at 3’end unless otherwise stated
b
Probe has 6FAM fluorescence at 5’ end and MGBNFQ at 3’ end

118
Supplemental Table 2

Reaction
Number
HUGO Gene
Name Forward Primer Sequence (5' to 3') Reverse Primer Sequence (5' to 3') Probe Oligo Sequence (5' to 3')
a
MB-034 Cacna1g CGAAGGTAGCGTTTATTCGGG CCCCTCACTTTATTCCGACTTCT CCTTCGCGCCCAAACTCCGAT
MB-036 Bcl2 TTTTTGAATGAACGGTGACGTA ACGAACGCGAAACGAAAAAC TCTCCGCCGAAACGCCTAATTTCCTAT
MB-040 Mlh1 GGGAGGAGTTCGACGAACG ACCAATAAAAACGAAAATACCCTAACG CCCTACTCGAATAATCTAACGCAAAACCCAAAAAA
MB-042 Neurog1 TGCGCGTCGTATTTAAGGG TCGCCGACGATCAAATCAA AAACACCAAATATAACACACGACCGACCTCAAAA
MB-044 Sfrp2 GTTTACGATGTCGCGGGGTTT CTACGCTTATAAAAAAAATCGAACTAACC CCGAACCCAAACAACAATACGAAACGAAA
MB-046 Bdnf GTGGTTAGCGCGAGGTTTTT CCCTATTTTAAATACTTCCCGAAATTA CCGCAAACTCCAAAAAATAAACTTCGAACG
MB-047 Gata3 CGCGAGTATAGTCGAGGATATGGA CCGTTAAAAACCGCGAAATAATA AACTCACCCAACGCGACTAATCCGCAA
MB-048 Crabp1 GAACGTTAGTTTTTTTGTAACGTAGC TATAACGACGACGCGAAAACA CGATCGTTTCGTAGTAGAGGTGGGTGTTTGT
MB-049 Nr3c1 TTGTTTCGAGAGCGGTTAGGGT GAATTACGCGAAATATATCACTCTAACAA AAACTACGAAATAACACGAAAACGATACCGCA
MB-052 Gata4 GGTTAGTAAGGTATTTCGGGTGATTT ACGCCCTATTCAAAAAACGAA CCTCGCACACTAAACTCATAATCGCCGATA
MB-053 Hoxa1 TTGAAACGGTGATTTATTACGGT ACAAACGAAAAACTCGAAAAAAAAA CGTAACTCTACCAACCAATAACTAAACCGCCT
MB-058 Socs1 GGTTTTAGTTTTCGGCGTGGTTA AACCCGACTCCCGACCGT AATAACTAATCGCCTCGCGACTACCGCCT
MB-067 Mlh1 TTCGGTCGTGTGTATAATGGGAA ACCGAACACGAAAACCGTAAAA ATCGAACACAAAAACCCTACGCGTACCAAA
MB-068 Hic1 GAGGTCGTAGTTTAGTCGTATATAGTTTTCG TAAAACGACCCGAACCGACA GCGACCATAACGCCACCTCGCG
MB-069 Sall1 GGGTTTCGCGTTTATCGTC CGACAAATTAAAATCGAAAAAACATAA AATCAAACGCGCCGAATACAAAAAACG
MB-071 Hras1 TTTTTGACGGATGGGTTGTTTA CAACTCGAAACGACCCGTAAT AACTCCTCCGCACCGCGACCTATTAT
MB-072 Gata5 GTTTGTGTTTAGTTGGAGTGCGC CTCCATACTACCGTACCTACCTTCG ACCGAACTCGCAAACTCCCGCG
MB-075 Cbs GATTTTGTTCGAGCGTGTTTTTTA AATCAATACGACCGAAACTCACCTA TCGAACGCGAAAAAACGACTCGACCTAT
MB-076 Ahcy TTTCGTTTTGGGTTTGTTGTTAGTAT CGATTCTAAAAATCCCGAAACG CGAAACCGCCACCTAAACAAAACGCA
MB-077 Stk11 GGGTTTAAGTGGCGAATATGATTTA AAAACGCTACTTCCGACGAAAA TCGCGACGCGCGAACCG
MB-080 Esr1 CACGCTCTGCCTTGATCACA CAGTAAGACGGAAGGAAGGAATGT ACCGCGCCACTCGATCATTCG
MB-081 Apc GGCGTTCGAGTTTGCGGT CCCGAATAAAAATCGCCGA CCGCACTCACCTACCAAACGCTCG
MB-084 Srp19 GTGCGGTGTTCGGTTTGTT GCGCAAACCATCTCCACG ATCCCGTCAACCGCGCCAACCT
MB-085 Snai1 GATAAAGGGGCGTGATTAATAGTACG CAAAATCGATAATCAACTCCGCT CGAAACCCGACCGCACACTACGAT
MB-086 Insm2 AAGATTTTGTCGTATTCGGGATAGC TATACAAACACCAATACGCGAACC TAACTCAACACCGCTACTCCCGCATCG
MB-087 Cdh1 GGTTTTGTTCGATCGTATTCGAGT GCGAAAAAACTACGACACCGA AACCCGACAAACGCCGAACAAACACTA
MB-089 Ascl2 AGATTTATGTTTATTTCGTTTGGAGTCG CTACTACTAACCTCGATTACTCCAAATCG CGCCGACTACAACGCAACAATTCCG

119
MB-090 Casp8 GTAGTAAATTTTTGTGAGTCGGCGT ATCACAACTCCAACTCGAACGA CCGAACCGACGCTCCCCAAAAC
MR-055 B-Actin TGGCTCCTAGCACCATGAAGA GCCACCGATCCACACAGAGT AAGATCATTGCTCCTCCTGAGCGCAA
RD-002 B-RAFV600E GGCAAAGAATTGTAATACGACTCACT TAATCAGGAACGTCGTAAGGGTATC TCTCCAGGGATCCGTATTCGCCCT

a
All probes have 6FAM fluorescence at 5’ end and Black Hole Quencher at 3’end

120

Supplemental Table 3

Symbol Probe ID Accession Input Sequence
SLC17A5 5243 NM_012434.3 ACCGGAGACCTCATGACGCCTA[CG]TGAGCAGGTGTACTCGCCACCTGGCAGA
MITF 3968 NM_000248.2 TTCCAGCAGTGGAAGGACGGGAAG[CG]GGAGCCATGCAGTCCGAATCGG
USP38 4118 NM_032557.4 TCACGAGTAACCTGACGCAGGCGGAAC[CG]ACGAAGACTAGCCGGCAAGAATCCT
PSRC2 3896 NM_144982.3 CTCGTTTCCCTTCTTTCCTAA[CG]GACTGGGTCGGTGCGGTCTTACCCTACTCG
FLJ33718 80 NM_173660.2 GGGGCAGATGCCAGTCTGGGAAGC[CG]GATTGTTTGAAGACCAACTTTAAAG
NEURL 901 NM_004210.3 CGGGCGGAACCCGCCAAGGACCG[CG]AAGTCCAGAGAAAGGAAGCTGAG
PDZK3 1370 NM_178140.1 ATGGGGGAGGCCCGGCACCCC[CG]AGACCGTGTGTGCCCAGGAAAG
C13orf25 2401 XM_931068.1 GCTCGGGCATGCGTTTTGGTTTACA[CG]CGGCCAGGTTAAGGAAACACATTGCC
SLC7A4 3740 NM_004173.1 GCCCACCTTCTTTCTACTGCAG[CG]GACACCCTTCTTGATCCCTCAC
ATXN1 5786 NM_000332.2 CTGCAGTGAAACAGGTCCTGTACGGCTC[CG]CCACTGTAGTAGAAATGATGTCTGCG
CHRDL2 27 NM_015424.3 AAAGGAGGGAGAGATGGAGAGA[CG]AAGGAAGGTCCAGCAGAAGGGA
STAT6 4186 NM_003153.3 AGCAGTGGCTGCCCCAGCC[CG]CTGTTTCCGGCTTCTCCTTCTACCC
HMGN1 751 NM_004965.6 GGTCCCAGTGGCGCTCCGGCCTCA[CG]GTAGTTTGAAGCCGAGCCGCAAAGT
NDN 2954 NM_002487.2 GGCAGGAGAGAAGTGAGATGGATG[CG]TACTGGAGAAGGGGCCAGTTTA
EFNA5 1967 NM_001962.1 GTGGGAAACTGCAGGAGAAGGG[CG]ACGTGCTGATAGAGGGCTTCG
WNT11 4153 NM_004626.2 GACGCTCAGAGGACAAGGCTGAGAGCCA[CG]GAGACAGAGGGGGAAACCC
LOC340061 2236 NM_198282.1 AAGGCAGCACACACATCACA[CG]ATGATTCCCCGTCTCATATTTTTCTT
ITGB3 3736 NM_000212.2 TGAATTAAAGTGTGAATGAATGAAACT[CG]AGGTAGTGGGTGAATGTGTC
TLR2 1586 NM_003264.3 AGGAGAAGCACGATTCATGAGCCTGAGTT[CG]GGCTTCCATGGATGGAAAA
NFYB 2373 NM_006166.3 GCCGGGAGGAGACGGACATTTCATT[CG]AGCTAAAGTGGAGTCGGTTTAGG
ZNF620 5935 NM_175888.1 GGCCTGAGCTGGCCAGACGTCATGCCC[CG]AAGGAGCTACCAGGTGTGGGC
CCNL1 5180 NM_020307.2 GGCCTCTTCCTTTAGCCTCGG[CG]CGGCTTGCGTTCCGCGTGTACCAAGGG
FLJ12998 5548 NM_022764.1 CGGCCTTGATTGCTCCTCATGTAGGA[CG]CGGTTCCCTCCTCTGAGATCCTGCA
AYTL1 4071 NM_017839.3 AAGGGATTGAAAATCCAGGTCCGTC[CG]ACCCTAAAGCAGGGAACTCTGCCT
HIC1 247 NM_006497.2 GGGAGTGCGTCCAAGTGGACAGTGC[CG]TACAGTAATGTCTACGGGGAGTTCCAG
C21orf121 178 NM_198078.1 GAAGGGACGGAACAGGTCACACCCAGAG[CG]GCACAGAGGTGTGTGAGCTGTTC
CACNB1 4989 NM_000723.3 CCCACTCCTGTTTGGACCAC[CG]GAACTTCCCGGTCCCGGTGATCC
LAMA3 3541 NM_000227.2 TTCCTCTGCTCTCAACCAAATT[CG]TTTACAAGCCTCCTTTACTCTTAGGTCAC
LOC339768 1098 NM_194312.1 AGCCTGTGCATGAGTCGCCACTGAGAGCC[CG]GGCCAGAGGATGGAGAAGCAG
GDF6 674 NM_001001557.1 CCACAGAAAACTGATGAGGAAGACGGC[CG]AGAGCAGGACCCTGGGAGTATCC
PLSCR1 4064 NM_021105.1 GTTAAGGAGAGGAACTGGGACTC[CG]ACACTAACTGGAACTGGAAAGTCATC
ZNF707 1022 NM_173831.2 GTTTGTAAAAGTCTGGGCTACCGGCG[CG]GCGTAGTGGATGCAGCATCCTAGTG
PNMT 2501 NM_002686.2 ACCTCGAATCAGGAAAGAGAAGGGG[CG]GGCTGCTGGGCAAAAGAG
ATG16L2 5708 NM_033388.1 GAGCTGGTGCCGGCCTGTGAGTG[CG]CCCCGGTGCTGAGAGGATG

121
LOC138255 273 NM_001010940.1 CCCTTCATCACCTGTGTAGCC[CG]GTCGCTACCCTCACTGCATTCTGGGAA
STK19 6030 NM_032454.1 CTCCGCAGAGCTATGACGTCATGGCAGGCA[CG]CCAGAGGCCGAAGGATGCAAAAGT
C8orf42 5160 NM_175075.2 GGGCATCCCTCGGGGCCTGGG[CG]CCGGGCATCCGGGACTCATCCC
PCAF 1693 NM_003884.3 CCGAGGAACATGTCCGCAGCCAGGGCG[CG]GAGCAGAGTCCCGGGCAGGAG
OPCML 2898 NM_002545.3 CAGAGCAGTCCTCCAAGGCA[CG]CATTGGCTCCACTCTCCTGAGCGACGG
FLJ36166 5686 NM_182634.2 CCAGCGCCTGCAGACTTCGGTG[CG]CGCAGTTCCTAAGCCCACATGCGCA
TGFB2 1899 NM_003238.1 CACACACGTGTGCGCTTCTCTGCTC[CG]GAGCTGCTGCTGCTCCTGCTCTCAGCGCCG
SGPP2 4265 NM_152386.2 GGGCACACCATGGCCGAGCTGCTG[CG]GAGCCTGCAGGATTCCCAGCTCGTC
ECAT11 5581 NM_019079.2 CTCACTTTGTTCGCTCCTCAGT[CG]TCCAGGCGGATTCCTTTTTCGCC
RILP 2952 NM_031430.1 GGAAAAAGCAGCAAATGTGGTCAAGGCAG[CG]GAGTGTGAAAGCCCAGCCCTGC
DOCK5 3640 NM_024940.4 GTCGCCGCCATGGCCCGCTGGATCC[CG]ACCAAGAGGCAGAAGTACGGGGT
ALG10 6126 NM_032834.2 CTCAGTCTTTGCTATCACAACCAA[CG]CACCCTTCCTACACTCCAAAGTTGA
FLJ23447 3461 NM_024825.2 AGCTCCTGACCAGGTCTGCTGCC[CG]GCACCCACCTCCCCTCTGCTG
ADARB1 2910 NM_001112.2 GGTCGTGAGGGAGGTGCCACAGCTC[CG]GCTGCCCACGACAGACACGGGC
FLJ33790 50 NM_173583.1 TCTCCAGGAAGTAAGCGGGCGCCAGTAG[CG]GCAGGCGCACGTGCTCCAGCAGGC
ASRGL1 2008 NM_025080.2 TTGCTTTTCAATCTGCAATTACAAAAT[CG]TGGCATGCCACTTCACGCTTCTCGC
AP1GBP1 51 NM_007247.3 CTCCCCTCTTTCTCTGGAACT[CG]GTAGCTTCATGTTGGCACCTATCACAGACG
NEFL 4202 NM_006158.1 CGCCGCTTGTAGGAGGTCGAGTAGTA[CG]GCTCGTAGCTGAAGGAACTCATG
C12orf35 969 NM_018169.2 AAGATCGCTGCAGGAGATTTCCGCGT[CG]GGCAGATGAAAGCGCTCTGCAAG
PPARGC1B 5381 NM_133263.2 GGGGCCAGGGGTGCTGAGCTG[CG]GGGGCCGCAGCTGCAGCCGC
IRF7 5058 NM_001572.2 GTAATGGGAGGTGGACGTGCCT[CG]AAAAAGGGGCAGCTGCACCGTT
PEG3 3144 NM_006210.1 GCAGCTGCCCAGACTTCTGCAC[CG]AGGTGCAGCTCGACGCCTCCTTGTCA
ZNF616 1407 NM_178523.3 GGAGAAGTGAGGACTGCAAAGTGCA[CG]TTTAATCCAGGCAGACGGAGCGAAGT
FOXC1 2202 NM_001453.1 TTTGTCTGCTTTCCCCCGTTTG[CG]CCTGGAAGCTGCGCCGCGAGTTCCTGCA
MGC24103 1600 XR_001080.1 CGACAACTGATAGGTCAAATCACTAGGGAG[CG]GCTAAAGAGTTATTAATGGTGACAGG
ATP2A3 256 NM_005173.2 GGAGCACCCGGCTCTGGGCTGCG[CG]TCGCCTCCTCTGGGCTCTCCTGGGCC
PTAFR 1886 NM_000952.3 GGCAGCGGCTTCAGCTGCAGTGAC[CG]TGTGTCTCTGTCTGGGTCCTGGCCCCAGC
HIST1H2BN 6125 NM_003520.3 TCCAGGACTCACCACTGGTTAAA[CG]CACAACTTCATTCTCTACCCCACTT
WDR63 4208 NM_145172.1 TCTTAGCGACAGATGCGTCCTGGCAACAGT[CG]GCAGAGTTGCTGCGGTTTGTG
CYB5R2 2029 NM_016229.2 CTGGCCCCTTCCCTGCACA[CG]CAGAGCTGCCACACTGAGCGCCCCT
SPFH2 4255 NM_001003791.1 GCTGGGCCTAGCTGCCGCTCAGGGT[CG]GGGCTGACCCGTCACTTTCGGGAAC
EIF4E 4061 NM_001968.2 TCTTGACGTTGACTCATTCTCCTTAGG[CG]AGTGACTTAATCGCTCGGCGTCTCAGCTTT
E2F3 889 NM_001949.2 CGAGAGATGAGAAAGGGAATCCAGCC[CG]CTCTGGAGCAGTACCTGGTGACC
SLC25A37 1077 NM_016612.1 GTTGCTTGGAAATGTGCACGGGA[CG]GTGACGTCACACAGGGAGGCG
FBP2 5250 NM_003837.2 CCCAGTCCCTTTGGCCTGA[CG]CCCCTTTTCCATAACGTAGCGGGTC
TSP50 2440 NM_013270.2 CCTGGAGTCCCTCAACTTAATCT[CG]GCCGATTCTCAGACCTCCTCAC
PCDHB7 5894 NM_018940.2 AGAAGAATGGAGGCCAGAGTGGAG[CG]TGCTGTGCAGAAAAGGCAAGTCTTATT
MESP1 5022 NM_018670.1 CAAGGTGCCAGCCCCTTGACTG[CG]CCTGTTTCGCCCCACCTGGGCC
FGL2 31 NM_006682.1 GCGCAGGGCTGGAGCTGCTTTAATAG[CG]GCAGCTGCCTGAGTCAGGCTTTC

122
GAL 1644 NM_015973.2 GACTGAGGAGTCGTCCCTGCC[CG]TCACCCTCTGGGGTCTCCAGTGCTGCG
SEC63 1789 NM_007214.3 CTCTGGATTAATTGCCCTGGTTGATCA[CG]TTTCCTTGGGTTCTGGATCTGCTCCTCC
RALGDS 5629 NM_006266.2 TGTTGCGTAGGGCTGAAATGTGTA[CG]TGCTGATCATGTGTGGGGA
2966 GCATTCCATTACAGTGTCTTTCAG[CG]GAGCCAGAGCTCAGCCAATCCTAAT
ACOT4 1882 NM_152331.2 TTTGCCTCAGACGAGTCCGGAGCGC[CG]GGTTAACCGGTCTGAAGTCCC
C1orf96 3712 NM_145257.2 CTGGTCCCAGCAGACGCTGTCCCAGGCA[CG]CGTCACTCTGCAGGAGTCGTCAGTTAG
CSS3 4270 NM_175856.4 TTCTCTCCGGCTGGCAGCGGTGC[CG]CCTGCGGCTCCTCCTCCGGGCC
BNC1 2896 NM_001717.2 CTCCCCTCCTACCCTGGGG[CG]CCCTCGGGGTCTCACTGCCGCGGAG
RUNX1 1824 NM_001754.3 CTGTGGGTTGGTGATGCTCACCA[CG]CTGCGAAACCCTGTGGTTTG
IBRDC2 4002 NM_182757.2 CTGTCAGCCGCAGAGCACGGAGGAAAGA[CG]GAGAGAATGGAAGAGCTCCTG
ACP5 2990 NM_001611.2 TCTGGGCACACGTGTGCAGCAGCCT[CG]GCCCACACAGCCTCCGGGTGG
POGZ 2741 NM_015100.2 TTCACGGCCTCCCAATTGGT[CG]GAGCGCGCTGCACGTCATGGGCTCATCC
TMEM119 1610 NM_181724.1 GAGGGGCTACTCTCGGGCCACA[CG]CAATCCCACCCTTGCTCACACTC
LOXL4 2164 NM_032211.6 TGTCACAGGGGCCGAATCTCACGAGCT[CG]GTCACTTAGGACAATGTAGACGCCCTT
ZNF695 656 NM_020394.2 CAGGAGGTGCGATCAGACACTGGGC[CG]AATGAAACAAGAGTGACAGGTTTTT
INSM1 1390 NM_002196.2 TGCCAGGCTGAGGAGCTGCGGACG[CG]CTGATTGGCTCCAGGGGAA
COL11A2 1711 NM_080679.1 ACTGCTCCCTCCTCGGTGGCTGC[CG]CTTCTGTGTGTCCCCGGCCACCC
GPR176 210 NM_007223.1 CTGTATCTCGTCAGCAGGGGCTGCCTG[CG]GTGTTAGAATTACACGCCCCTGCCAC
PROK2 1171 NM_021935.2 CCGGAACCGCTTTTGTGGTCTC[CG]AGACACTCATTTGCTGTCCTGGTTTCCAA
NUDT13 4843 NM_015901.4 ATTCCTGAGGACTAGGAAGGTGCCC[CG]AAAAGAATTCAGAGTGAGTACAGTGAA
TRIB1 1360 NM_025195.2 TCACTCACAGTCACTCTCTCTGAG[CG]CGTCTCGCTCGCTCTCATACACGCC
PIGG 4952 NM_017733.2 CCAGCCTAGCGTGTCCACGATG[CG]GCTGGGCTCCGGGACTTTCGCTACCTGTT
CDCP1 657 NM_178181.1 CCCTACTACTCCCCATTGCGG[CG]TTGGAGCGGACTTGTCCCCACCTTT
CRY1 130 NM_004075.2 AACTTGTTGACCCTCGTCCACA[CG]CTGAACTCACTGCCTCTGCCCCTTTC
ZNF542 2882 NM_194319.1 CCTCACGGAGAATGGGCCTAACCTCA[CG]GAGAATGGGGCCATCAGATACACC
NOPE 1164 NM_020962.1 CTGAGTCTTCTGGTCTCTCTGCCTCAG[CG]TCTCTATTTCTTCTCCCTGTTGCTGCCTCG
PAPSS2 4230 NM_004670.3 AGGATCCTGCCAACAAACCTGG[CG]GCTTCAAGCATCCTTGCCCTTAACC
C14orf35 1559 NM_001011713.1 AAATCTTCCTTTCTTTTTCGGT[CG]GCTTCTCTGATTTGCTCCATTTTTAATCGC
SLC16A5 2418 NM_004695.2 CCAGTCCCCTCTAGCGCTGT[CG]CAGACCTCCTGCCAGGGCCCC
LCE1F 2137 NM_178354.1 CCTTCAGCTCCTGAACACC[CG]CCACCGAGATGTCTTGCCAGCAGAGC
ST3GAL5 1944 NM_003896.2 TCTGAGTTTGAAAAAGAAGATCCTAGACAC[CG]AGCCAAATATGTTTGCATAAACCGGG
LAYN 5885 NM_178834.2 TCCTGGCCGGTGGGCACACTGCCTG[CG]TGAGTGTTTGTTCTCTGCATCGACCATTCC
ZNF560 5170 NM_152476.1 GTGGCTCTGAGGAAACAGGCGCCAG[CG]ACCAAAAGAGAGAACTGGCGCGC
DAPK1 2706 NM_004938.1 CGGCAAGGAGCCGAGAGGCTGCTT[CG]GAGTGTGAGGAGGACAGCCG
UNC5C 5345 NM_003728.2 CAATGCCTTCTAACTGACGTCTCC[CG]CGAGCGACTGCTCTGCCCCCACTTGG
RNF186 1595 NM_019062.1 GCACAGGGACCGGTGGGACACTGT[CG]CTCAGCACCTGGGCATTGGCAGAGA
NEBL 3737 NM_213569.1 CCCTCATCCCAGGCTGACTGA[CG]TCCCTGGCACCCAAATGTCGCGG
C10orf10 1679 NM_007021.2 TGTCTTAGGAAAACAGCTTGGTGGG[CG]GGGCCTGGCCCAGCTGCCAGC
KIAA1671 5926 XM_371461.4 GGGTGAGGTCAGCAGAGGGCTGT[CG]TATGGAATCTGGGGCTCAGG

123
NUCB1 2822 NM_006184.3 CCCTGCTAGTTGTACCATGCCC[CG]CCCCTGCGCTCTGTAGCCCTGCCCC
GPX7 2167 NM_015696.2 GCCTGCGCGCAGCAGGAGCAGGACTTCTA[CG]ACTTCAAGGCGGTCAACATCCGG
PIGR 756 NM_002644.2 CTAGGAGCTACTGGCAGGGCACTGGA[CG]CTGCTGCCAAAACTGAAACTCTGC
PRICKLE2 5184 NM_198859.1 AGCAAGTCAGTCACGGCATCTGGA[CG]TCCCATCCTGCTGCCCAGTGCTGAGA
TPTE 4104 NM_013315.2 GCTCGCGGGTTAGAAGGCAGCTGTG[CG]TGCTCAGGAAAAGAAGCCACGCACAAG
REEP1 3066 NM_022912.1 CCCGCCAAAGGAACCCTGCAGCGGCCC[CG]TTTGCAGGGCAGGGACCCGG
HCLS1 743 NM_005335.3 CTTCAGTTCCGTATTCAGGTTTT[CG]TCATTTCCTGCCACCCCATCC
PTPN7 6140 NM_002832.2 CCTCCTTGCTGCCACCCA[CG]CACACCCCAGCTGCATTCTGCCC
C10orf114 4214 NM_001010911.1 ACCCTGGTCCTCAATGGCTCGT[CG]CGAGCTGCGCTAGCTGCTCTCTCGGCAGCG
RDH5 3924 NM_002905.2 CACCCTGTCACACATACACTTAATA[CG]CCTGGCATCCAAGTCCACCCAC
ZNF443 5348 NM_005815.2 CCTCCCGGGTTATATTTGCACTTAAG[CG]GAATTTCCTGCCCGTACTCAATAGGAC
C20orf102 6131 NM_080607.1 GCTGCCGGAGCCGGGCAGCCAGGC[CG]CTCAGGGCAGGGGACAGCTG
PLEKHA7 3349 NM_175058.3 GCACTTGATGAAGAAGACGCGGCCATCC[CG]GCACACCCCGTAGGACCAATGCTCAGG
KIAA1524 42 NM_020890.1 CCTCACTCAGCTGTGCGCTCTGATTT[CG]TGCGCTTCCTCGTCCTTCATGTTGGATGG
PDLIM1 3608 NM_020992.2 TGCCAAGTCAGCCCTCTGAGGT[CG]GCTCCGACTTCCCATTTGCTTTTTGT
DUSP13 74 NM_001007271.1 TCCTATGAAAAGGTTGGGCCAAACTT[CG]TCCACACGGCTGCAAGAAGACTTCCC
GLB1L 5163 NM_024506.3 AGCTCTCCGCATTGGTACTTCATGGGT[CG]TCTGGATTGTGCCGGACCTGTGACCCTGCC
C14orf169 5960 NM_024644.1 ATACGAAAGCAGCTGCGAAGTGTTGTATCC[CG]CATGGCAGCGCTGAGGACGCAGAC
SPAG1 2856 NM_003114.3 GGAAGGTGAACCTGTGGCCGT[CG]GCAGATCTGCAGATCTGCCGGAC
HYAL4 3484 NM_012269.1 CTAGGAGTGAGCAAGGCTCTGTGGG[CG]TGGGACCCACCGAGCCAGGCACG
IVL 263 NM_005547.2 GATGGTAGAACCAGGGTTGGGACT[CG]GGACCTCCAACAGCATACGATGTGG
SLC4A11 4870 NM_032034.1 GGGCTGCCCAGGCGGGCCAGAGG[CG]AGGAGGAGAGACGTTCCAGG
SIAE 1868 NM_170601.3 AAGACCTAGCCTTTTCCCTT[CG]TCTCTCTTATTCTCTCAGCATCCCA
C13orf18 2369 NM_025113.1 CCCAGCACCACGCACCTATG[CG]CGCCTCTGCCGGTCCTCCTAGAAATC
SERINC2 2152 NM_178865.3 CACACGGGCTCAAACCGAGGT[CG]ATTTCCGAACGCTCACTTTGGAGCAG
LOC153222 119 NM_153607.1 AAATATTGAGTCGGTGAATGAATGAA[CG]AACGACAAAAGGCAAGGTTTGTCT
LNK 1320 NM_005475.1 GCTGGCCATTTTCCGAGCC[CG]GGTTTCCTGCCTGAGCCCCGCTCG
EGFL9 1655 NM_023932.2 CAGCCCTGCCTTCGCTTGTC[CG]CCGCTCATCACGCTTCTCATATAGATCTAT
TLR4 2425 NM_003266.2 CTGTTTCTTTAGCCACTGGTCTGCAGG[CG]TTTTCTTCTTCTAACTTCCTCTCCTGTGAC
SLC2A8 3894 NM_014580.3 CAGGGCCCGTGGCGGTTCAGG[CG]CCAGAGCTGGCCGATCGGCGTTGGCC
LOC389517 4260 NM_001032389.1 CCCACATGGCTTCCTAACGGGCTG[CG]GCTCTCCTAGGAGTCTCTCGCTCATGGGA
PLEKHA5 1006 NM_019012.2 CTGGAGTGGATCTCCCTGCCC[CG]GTCCTGGACTTACGGGATCACCAGGG
LOC63929 5550 NM_022098.2 CAAGCTGGTTCCCGCTGTAGCAAA[CG]TCCGCGGCCTCTCAGGTTAGACTCT
LOC497190 2281 NM_001011880.1 GCATGGGTCTGTTGGGCCCGTCAGG[CG]CTCCGTGCACAGCCTGGCTCAGCC
COX17 2361 NM_005694.1 ACAGGTGGGGAATTTAAAAGGAGCG[CG]TGCGCAGAAGAGGCAAAATTCGG
MYLC2PL 2555 NM_138403.3 CCATGCAGACAGGCAGGCTATGGGGCTC[CG]ACCCCACGGCAGTGTCTAGGGG
HMGA2 5047 NM_003483.4 CTGCCCAGGGGTGACCTCGAGAGG[CG]GGTGGAGCTAGGCCCACGG
TBX21 1850 NM_013351.1 AAGCGCTGCGACTCTAGTGACAGCGGCC[CG]CTGGAGAGGAAGCCCGAGAGC
PCSK6 3962 NM_138320.1 CGAAGGCCGCACTCACCTGG[CG]GGGGCCTCAGACGCCTGGCGGCCT

124
HRH1 427 NM_000861.2 ATCCATGTACTGGAGGGGACATATGCA[CG]AGGGCAGGGAAAATTTCTC
TMEM87B 2403 NM_032824.1 CTGCCAGCCCTCCCTTGCA[CG]TTCCGGCTCCTCTTCTATCTTCACG
TNNC2 4909 NM_003279.2 GACCGGGACTCCTCTGTTGCAGGT[CG]CCTCCTTTGCACTCCACCACC
KRT7 41 NM_005556.3 TATGGGAAATGAAGTAGGAAGGAA[CG]CAGCCAGGGAAACTAGCTGGG
HTR1D 5290 NM_000864.3 CTTGACGCATCCTGAGCTACTTAACTT[CG]GTTCCTATCCCACTGATCGTTTTAGA
GSTO2 3299 NM_183239.1 CGCTTGGCCCTAGTGCTTTCCAG[CG]GATTTCCCCTCAGGTGCGGAGCC
ENOSF1 1032 NM_017512.2 CAGTGGCTCAGCTCCCAAGC[CG]AGGCCGCTGGTTGTCGCCAGCGTACC
MFI2 4297 NM_033316.2 CCCGCCTTTGGCTCTCACAG[CG]GGGCCTCACCGGTGCGCAGAGCC
ZNF501 3826 NM_145044.1 GAGCGGTTTCTGCTGTGCCCGGCTGC[CG]CGGGTCGATTCCAGCTCCTCCC
SLC37A2 920 NM_198277.1 GGTAGTGCGGGCAGGCAGGCACGTCACAC[CG]GACAGCGTCGAGATTGCTGCTTT
RGC32 814 NM_014059.1 GGCACGCGGCGGGAAGCAGCAGAGCT[CG]CGCCCAGCAGTCAGCTCTGGTGACGC
ZNF680 649 NM_178558.2 TATGTGCTCAGCGGCTGGGCTGAA[CG]TAGAAAGAGTGAAATCCAAGCTGCAGG
CA6 4848 NM_001215.2 ATGGACTGACCGGATATGAAATTGA[CG]TGGGAGGAGATCAGGCAGGT
ZSWIM3 3515 NM_080752.2 TCCGGCAGATTGCCCTAGTAAC[CG]GAAGTCTCCTGCAGACCCCGGG
RGL2 3063 NM_004761.2 CTACACTCGGGGATTCTGGAGACCA[CG]TCGACCCGCAATGAACTGGAATAA
C21orf58 2143 NM_199071.2 GCCAGCCTGGCAGGGGATTTTAAAAT[CG]GCCAATCACAGCGGGCGCCAGGCC
CDC2 398 NM_001786.2 AGGCTTGGTGTGCAAGTTCAGAGGG[CG]GGCAACATCAGGTTCTGGCAAGG
PRR6 1862 NM_181716.2 CCAGAATCCACTCGCACCTG[CG]AAGGCGCCCCTGCCCTGTGTGAATCC
LAT 4931 NM_014387.3 GGGTCCTGGATATGGAGGCCA[CG]GCTGCCAGCTGGCAGGTGGC
LAMC2 2209 NM_005562.1 CTCTGTGCCACACCCTTGGCC[CG]GGCCAGGTGTGCGCCCTCCTCGCTGC
TCF23 5118 NM_175769.1 GACTCAGGCCAAAGCACGGTTGCTGCCAGG[CG]CTGACAGGAAGAGGAGCCGCCT
ROD1 4098 NM_005156.4 AGAGCAGGGACTGACGGGCTAACCG[CG]AGCAGAGGAAGCAGGCGGCGG
ELL3 234 NM_025165.2 CCGAGAGACCAGAGGATGGCTGACA[CG]AAGGGGCACCCGAGACAGCGCC
KIAA1598 1055 NM_018330.3 CCCAAAGAACCACAGAGGTAGAGCGGGA[CG]CAATGAGCCATGAACGCCTGGGC
LRIG3 5104 NM_153377.3 GGTCAATTCCTTCTTTTACTCC[CG]GCGGCGAAGCCCTTTCATGCCC
PTGS2 890 NM_000963.1 CCGCCAGATGTCTTTTCTTCTT[CG]CAGTCTTTGCCCGAGCGCTTCCGA
SERINC5 4234 NM_178276.2 TCAGCCGCAGCTCACACTTGAA[CG]AAGATCAGCCTCGGCGAAGCGCCT
C20orf85 2738 NM_178456.2 GCCTAGAGGTGGACAAAGGGCCCAGA[CG]TGAGCAAAGGATGGCAGCAAGCCCG
CCDC50 3237 NM_174908.2 GGGTAGTCTCGAGGTTCAGACATGGCACA[CG]TTTGGGAGAGAAGCTCACCTCT
AGGF1 5768 NM_018046.3 CCTCCCTGTCGCTCTTAGGGCTT[CG]GTAGCCACATTGCCACAGCTCTCC
H2AFJ 4022 NM_177925.1 CCCCAAAGACTGAGCCGGCTGGCCT[CG]TTATTTATGTGAGCGGCTATGTAAATG
TBC1D4 1884 NM_014832.1 TTCCTTCCAGGCTGCTTCTTTAAT[CG]GGCTGCTACTCCGCCTCCCGTCC
LATS2 840 NM_014572.1 CCTCCCTGCTGGCCTGCGGTAGCT[CG]CCAGGGCCTCTCGGACCTATTTGACTGGC
PIK3R1 3057 NM_181523.1 CGTGTGTGGAGTGCCACGGTACAATCAGA[CG]ACAGATGGACAGTGTGACAAAAGTGT
GATA6 4165 NM_005257.3 CAGCGCCCAGCTGCTCGCTGAG[CG]CAGTTCCGACCCACAGCCTGGC
PEX12 3370 NM_000286.1 GACCCCAGGCGAGGCGCAAACAACCCACGA[CG]CCACGTTTGAAGGGAGGTCTC
DSCR9 5985 NM_148675.2 CCATGCGGCCCTGGTCATCTGGA[CG]GGCCACTGAACTCCACACATTCAC
IL1RAP 1317 NM_002182.2 GGAAGAAAGGGCAGGGTGGCAC[CG]ATCTCAACTGCGAGAGCACGATCTTG
MST1R 2810 NM_002447.1 CCTGGCTCCTGTACCTTCACCTGG[CG]TCTTGGCGCCTTTTTCTCAGCGGCC

125
ANGPT2 2329 NM_001147.1 CCAGATCCTACAGTGTCAGTATC[CG]AATCAATCACTTTCCTTTCCTTATATGAT
TTC9 3324 XM_027236.6 TCCGCTGGATTTCCTCACTC[CG]GCTATGCCACTTCCTTCTACTTCTTCATGC
PIP5K2C 2298 NM_024779.3 GTCAGCTTACAGGGATCCCGCA[CG]CCAGGTGAGCCCACACACTGAGCGG
TMEM16H 1338 NM_020959.1 ACTCCTCATGCACTCTTCGTC[CG]GTTAACACCGACTCCCTTCAGGATG
SPINT1 3101 NM_181642.2 GGCTGGGAAAGCAGGCCCCGGC[CG]GAAAGGAAGACTGGAGGC
DNAJB6 4106 NM_005494.2 TCTCGGCCTTCTCTGTGCCTTC[CG]CGCGTCTGGGCTCCCCGGTACCGTAG
EDG2 960 NM_001401.3 CTTCCTTCTTTTCTGCTTGTTCCA[CG]TAGCACAAGTCAGCAACACCCG
ZFYVE16 2048 NM_014733.2 GAAGTCAGACACTGACGCGAGTGGCCTCC[CG]ATCCCGCAGTCGAGTGGAGAACC
CNTD 807 NM_173478.1 ACTCTGTTCCCCTGCCCCTATATG[CG]GTCCCCTTGAGTCTACAACACGGAC
MYLK 5817 NM_005965.3 TAGGTCGGGGTCTGATGCTAGCTT[CG]TGAGCGTGCATGAGACACTGGCT
ICAM4 2051 NM_001544.2 GAATCCCTTTTTGCAGTACTCC[CG]GGCCCTCTGTTGGGGCCTCCCCT
GOSR2 2749 NM_054022.2 TAAATAGGAATGGGGGGTAGATAGG[CG]GGAGAGTGAGTAGACAAATGCGA
TBC1D2B 2799 NM_015079.2 GGCCCTGGTAGCTGAAGCAGGCGTCCG[CG]ATGTCCAAGTGGCCGAGGG
C15orf48 2038 NM_197955.1 GGCCCGCAGTTGGCCTGCGGAG[CG]CGGTGGACGGTTTGGCGCCCACCAG
LOC145783 5846 XM_934386.1 GGCAAAGTGAACCGAGCCGCTGGG[CG]GTGCAAGGGGAAGCCCAAGCCC
PCMTD1 1874 NM_052937.1 CAAATAGTAATCTCCACGATCAAT[CG]CTCTGAAGGCTTGCTCCACTCTTTCAGTAC
LOXL3 2803 NM_032603.2 CCTACTCATTCCCTCTGCGGTTAG[CG]TGACTCCCCCTACCTTGGCCGA
STEAP4 4068 NM_024636.1 CTATAAGAAGCCAGAGAAGGGCGGGA[CG]GTCTGCTGGATTTCGCAAGAG
PPIL5 3183 NM_152329.3 ACAGTTCTAAGTGCCTTTCCCTGTAA[CG]CAGAGGCACACCTGCCTTCCCTC
CALB1 5933 NM_004929.2 GCTGTCCTCGGTGCTGCTCAGCTCAG[CG]TTCCTCCAGAGTTCTCTCCCTAC
ZNF283 2420 XM_371174.3 GGTAGGGCACATCCTTGGCTCTATCA[CG]CACATAATATTGCACACACCCCCTACA
FLJ36031 6124 NM_175884.3 GGTGGATCTAGGAGGGCTGCCA[CG]TCTAGAGTAAGAGGGTGGATGT
FLJ22662 3077 NM_024829.4 CCACAGGTGCGTTTTCCTCAG[CG]ATTAGCGTACCCCTCATTCCCA
ME3 5389 NM_006680.2 AATTTAACATCCAGTTCTGCAGTCA[CG]CTAGCCACATTTCCAGTTCAAGAGC
RGS22 87 NM_015668.2 TTAAATAATTCGCGGCCTATAGGAAC[CG]CAAACTTCCCCAACACGTGTGTGCC
PPP4R1L 1756 NM_018498.2 GGCGGGGCCCTGCAGACAGGGG[CG]GGGCCCTGCAGACAGGGGC
CITED4 3191 NM_133467.2 CCGGCCCAGCCCACTACTG[CG]CACCTTGCGGCCGCAGCCTGGGGTC
C15orf27 3804 NM_152335.1 GCTGCAGAGCCGAGCGAATCCCGAGCC[CG]GGCAGCAGGTATGTGTCCTCGCAGC
LOC51136 102 NM_016125.2 AGGAGAGAGGTGCGGAGAGTCTG[CG]TGGGGTGGAAGTAGAAGTTA
C3orf33 5394 NM_173657.1 GTCGTCTGCCCACTGCGAGATC[CG]AGCCACGACGTTGGGCTCCATTCC
FLJ34922 3347 NM_152270.2 CCCTTAGCGTTTCCCTGGAGG[CG]CCCAGGTCGAGTCCTTATATACTAGCGGG
SLC38A4 6085 NM_018018.2 GACAAACACAGGGTGGGTAGAAAGAGTTA[CG]AGTGAAAGGGAAGGTAGAAACA
SDS 2989 NM_006843.2 GGGTCTGAGCAGGAGTCAGAGCCAAGCCAG[CG]AGGGAGGGATCAACTGAGTAG
TNFRSF10D 4232 NM_003840.3 CGTGGTCAGTTGTACTCCCTTCC[CG]CAGTCACTTCCAGGCACTCAGGCTGG
SLC12A7 2304 NM_006598.1 TCGGCGTGAGCCTCCACGGGCACCA[CG]GTGAAGTTGGTGGGCATG
FAM24B 1138 NM_152644.1 CCGGGAGTCGCTCTGCCTGCC[CG]TTTCTGCGCTGCACTGGCCGACACTTAAGC
LIMS3 4901 NM_033514.1 ACGATGGCCTTCTCAGGCCGAG[CG]CGCCCCTGCATTATCCCAGAGAA
MGC35361 3995 NM_147194.1 TGACTTGAGGCGGCACAGTGGCCAAGT[CG]ATTGGCCGTGGCAAGTGACCC
MGC16943 2926 NM_080663.1 GGTAAACTGAATTGAGAAGCGGATC[CG]AGGGAGGTTGAAAGCTGTCA

126
FNDC6 2976 NM_144717.2 GCCCTTTCTGAGCTTCCTGGGC[CG]GCTCTAGAACAATTCAGGCTTCGCTGCGA
LYN 5842 NM_002350.1 GGAAAGGAGACGCGAGAGGTGTAGT[CG]ATGTGCCTGCGAAGCCCAGGCT
TCIRG1 759 NM_006019.2 CCCAAGCCCATGAGCCTG[CG]AATGTTGGGGTCCCATCAGCCAGAG
DBF4B 10 NM_025104.2 AATCGGGAAGAGCTCATGGAGCTCG[CG]AATGTAATACGGAGGCCTCTGAG
MTSS1 4261 NM_014751.2 TGATGCAGAGAAAATCGCCCGCTGACC[CG]GGGCCAGCGCCATTGAAAAACG
TIGD2 5013 NM_145715.1 ACCTTATTTGCACTGTTCACTTCTGTC[CG]GGTCATCTTCTCTTGCGTATGATTTCCACA
ZIK1 5384 NM_001010879.1 CGCGCTGAGAAAAGGGTCGTTTC[CG]CTTTGGGACCAATGGGTCG
HUS1B 2163 NM_148959.2 CAGGCACTCGGGTTCCCGGTTG[CG]GTTGCGGGTTCTGTTGTGGGTTCCGCAGCC
RTN1 2789 NM_021136.2 CCTCCTACTCCACTCGCTGCTGC[CG]CCGCTGCTTCGCTATTCCCAATCCTGT
FLJ14834 5310 NM_032849.2 GATTCGTGAAGGCTTTATGGAAAAG[CG]ATGTGATGATCAGTGGGATTT
LASS5 5911 NM_147190.1 CGGTACCTCTGTCTCCACTCC[CG]GAGGCCAGATCGATCTCTCAGGTCA
FNDC5 3089 NM_153756.1 GACAAGTGCCACCGAGATGCC[CG]TTTGTGCCCCCACCCCTAAGC
KCNK15 2049 NM_022358.2 AAGGAAGGACGGAAGACTGGCA[CG]AGGTCACAACATGAGTTAGTGGCGG
MEIS2 3718 NM_002399.2 AAGTGAGGAGGCAGTCATCTGGGTC[CG]ATGTAGCCAAAGGCGTGTGTGTG
KIAA1922 2630 XM_057040.6 CCTCCTGGACAGCTCGTGATGTC[CG]GGCCAGCTCCCCTCCCAGCTG
ZDHHC21 3690 NM_178566.2 TCCCATGGTACCTTGCTTCAAAG[CG]CGGTCTGCAGCATCAGCATCCTCTGGGA
KCNE3 1270 NM_005472.3 GGCTGTGGGCTCCGACCCTTC[CG]TCCCCTGCAGCGCCTGCTTCCTGG
CD44 2160 NM_000610.3 CCTCACTCCCCACTGTGGGCA[CG]GAGGCACTGCGCCACCCAGGGCA
LRRC16 813 NM_017640.3 GGCCCAAGCCCCGCCGGGGACCAG[CG]AGCCGGGAGGAGGAGCAGG
PTPN21 1227 NM_007039.2 CTGTCTCCAAAAACCCGGCT[CG]CAGACCATTCCCCTGGGCAGAGTC
TM6SF1 2692 NM_023003.1 CTTCCTCCTCTGACACCCT[CG]GATCTGGTTCCACCTTTCCCGGA
ARSI 2208 NM_001012301.1 CTTCTTGCCCTGGATTTCTCC[CG]CCTCCTAATTTCTCTCTCCTCTGCTTTC
CHRM2 1762 NM_000739.2 GGGGATGGAAATGGAGAGAAG[CG]AAAAAGAGCCTGGAGAAACGG
PCDH7 5560 NM_002589.2 CAGCCGTGCCAGGGCACTTC[CG]AGGCCACAACCGACTGACACTTTTT
MAP3K12 3780 NM_006301.2 GCATTGCTCCCCCTATCATAC[CG]ATCTTGCCAGCTCTCCTTCCCTTG
FAM54A 5829 NM_138419.2 TGCAGCCACAGGCGGTAACGATGCCCTCAG[CG]AGGAATAAGAGGTCAACCCGGTG
CTBP1 5140 NM_001328.2 AGGCCCCGGGCCTGGTGTTC[CG]CACGTTCTAAACCGCCTGTCCCC
TRNT1 2305 NM_016000.2 AAGACAGCTGCCAGTTGTCTCAGAT[CG]CACGGGCATGCCGCGCAGATGGGCTTCT
TTC22 4069 NM_017904.1 ATTGTCAAATACGGGGTGCGCAAACCT[CG]GTGCAAGGCAAAAGGCGTGTTT
CES2 4092 NM_003869.4 GGCGCTGGGTCGTGCGAGCCAGTAG[CG]GGCTGAAACGTAGAGGCCAGAA
GNAL 2035 NM_182978.1 CTATTAAAGTAGGGATAAAGAGTGTGCAGA[CG]TGGGTGTAAGATAATGAACAGAAA
COL18A1 895 NM_030582.2 GGGGTCTGACCCGTGCCTGTCC[CG]CGCAGGTGCCCCTGGCCATGGCCGC
MBP 2170 NM_001025090.1 GAGGAGAGTCAGCCCGGCCTGGAGG[CG]AAAGGAGCCGGCAGGTCCTCC
ARL5B 4178 NM_178815.3 TCGGCCTAGCAGTGCCCTCGCTG[CG]CGATCTCAGGCGGGTTCTCCTCGGCT
INPP5D 3777 NM_001017915.1 TGTGCTGAGGCCTGTGCTGCAGAGC[CG]TGACAGGGTTGGACTTCTGC
DNAH11 2256 NM_003777.2 CCTGCGAGGCTACAGCTGTGCGCAGTGG[CG]CGGCTGCTAAGTAGCAGCAGGTGG
C8orf47 5683 NM_173549.1 CTTACTGTGCCATACCCTCCAC[CG]TCTCCCCTCCTGTCTCCTGGGCTC
AP4M1 4099 NM_004722.2 CGTAGACCCGTACCCTTCTCTAG[CG]CGTAGTCCTTCAGTGCCATCGCTGCCG
ICAM1 4033 NM_000201.1 GACTTGAGTTCGGACCCCCT[CG]CAGCCTGGAGTCTCAGTTTACCGCTTTGT

127
SLC2A11 1222 NM_030807.2 GCATAAGTCGGACCTGCCTCTCA[CG]CAATGGATCCCCTGGCGGCAACCC
SYT11 5915 NM_152280.2 GCTTCTTACCCTTCAGTACTTTCT[CG]TTTTGGAACCACAGCGCGTCAGTGGGC
FLJ31196 205 NM_152908.2 TTTTCAGAAGAATTGGTGGCCTGCC[CG]AAGTCACAGAGCAGGTGGTGGCAGA
UBD 1382 NM_006398.2 GAATTCTCGTTCCTTGAATTCC[CG]GCATATCCTTGAACACCCCAATCT
ZNF447 3986 NM_023926.3 GACACGGAAAGGGAGAGACCAGCTCA[CG]GTTAAGAAAGGAGGGAGACCAG
C3orf59 2536 NM_178496.2 AAATCAACAAGCTGCCGGCTC[CG]GTGTTACGGAGCCAGCACCAGCGTCT
AK3 2328 NM_016282.2 CGGCTAGCAGCGCCACTAGCAGG[CG]GCTACTGCGGTTCCCCGGCGTTCC
CNKSR3 1856 NM_173515.2 CGCGCTCGGGTTGCAAAGTTTCAGCTC[CG]GTTGCTGCAAACCGAATAAAAGAG
C17orf67 1647 XM_378687.3 GGATCCTCGTGGCCTTGCCC[CG]CCGGCGGCTTTCCAGAATTTTCTACG
VWCE 3632 NM_152718.1 GGCTTCCTCCCGGTGTAGCCT[CG]GGCTGGTGCCCCCGGCAGCAGGA
ZNF165 3929 NM_003447.2 GAAGTTTCAGTTGCAACCCTGCTG[CG]TGGGCTTCAATTTCACCACCTGAGA
CFTR 3115 NM_000492.2 GTGCGTAGTGGGTGGAGAAAGC[CG]CTAGAGCAAATTTGGGGCCGG
UEV3 5724 NM_018314.2 GCAAGTGACGAGGGCACGGCCAGAAA[CG]CATTGGCGTCAAGGAAACCACGACC
LOC401233 4238 NM_001013680.1 GGTGGCAGAGCAGCGCCGTCACCGAGCAGC[CG]TCGCTGGCCTGATATGCAGCGG
C3orf9 3055 NM_152305.1 GGGGAATCTGCAGTAGGTCTGCCGG[CG]ATGGAGTGGTGGGCTAGCT
PPL 6107 NM_002705.3 GGCCTTCACCTGGTTCTGCGCTAC[CG]CGGAACTCGGCGCTCCTGGTGCTTTGGCGG
HSPA2 3340 NM_021979.2 GGCTGGCCTGTCGGCCTCTGATGCACT[CG]AACTTCCAGCCCTTGGAGCAGACA
HTATIP2 1658 NM_006410.3 CTGAGCCCAGCAGGTGAGGGAAAACG[CG]GGAAGAGGGTCTTGCAGATT
TNFAIP3 5061 NM_006290.2 GGCCGGCTGGACGCACTTCGCAGCC[CG]ACCCAGAGAGTCACGTGACTTTGGA
GATA3 4209 NM_002051.2 CTGCACCGGGACGGAATCGTCCACC[CG]ACCCGAATGAATTGGCAGGAGC
DKFZP434P211 5934 XM_929365.1 CATTGTGGGCACCTGTTCCTCC[CG]CAACCTTTGTGCCCGCCTCTCTCC
ALS2CR19 2733 NM_152526.3 GTCCTCCGAGAGTGGGGGCTG[CG]CCCGCGGGGTCAGACACCTGTT
OR2W3 2180 NM_001001957.2 GATCCTCTTTGTGGTCATCCTGATCG[CG]TACCTCCTGACCCTCGTAGGCAAC
CRIP1 1765 NM_001311.3 AGACATCACAGCGCTGGGCTAGGGGCG[CG]GCTTGAACTCGCCTAAAGAGCTG
SGTB 2081 NM_019072.1 ACGCGAGACGACTGCTGCTGGCCCG[CG]GGGTTCCGTAGGCAGGCCC
C8orf58 742 NM_001013842.1 GGGACTCGGGCCGGGATCCT[CG]GGCGGCTGCATTGGCCGGGGCCGGGG
CLDN5 1985 NM_003277.2 CTGCCCTCCCACCAGTGG[CG]ATGGTGTCCCTGGCACCCCAGCC
C1QDC1 3156 NM_032156.2 CGTGCCCTAATCAGTGGCCCTTG[CG]CACTTACGTATCCGTCTCTCGACCTCC
IRX5 4211 NM_005853.4 GCCCGTGTGTGGCCATGTCCTATC[CG]CAGGGCTACTTGTACCAGCCGTCCGCC
MMP23B 2050 NM_006983.1 CCCACTGCTACCCTTTCCTAAG[CG]GGAGCCCTGGCGCTGCCCTTCCC
MYEF2 2261 NM_016132.2 CTGTCGCTTGGCACCAGTGGAGTCTT[CG]CTTGCAAAGCGGGATTAGACATCAAAG
MBD1 2795 NM_015845.2 CGGAAGTCCGCTGCCTGCCTCT[CG]GGCTCCGCCTCTGGCTAAGCACCTGCG
CCL26 2907 NM_006072.4 CATCCCACAGATTGCCTTTCTA[CG]TCTTACGGTTCTCCCTCCCTCC
SH2D2A 2370 NM_003975.2 GGAAAGCCTTAAGACGATTGTCCCACCCC[CG]GAAGCCACGCAGCTGTAGATAGCGGT
PTGS1 1375 NM_000962.2 TGGGCAGAGGAAGTAAGCGGGCAGC[CG]AGGTGACAGCTGGAGGGAG
GLT8D2 1749 NM_031302.2 ACTCCCCTTTGCTTGCGTTGACTT[CG]GAACGTCTCGGGTTTCTTCCACCT
RNF44 3363 NM_014901.4 GCGCTGACATCATGGCCCGGC[CG]CCCCACTTCTCCTTGTTTATACTACACG
CXCL10 2232 NM_001565.1 GTCTAAGCAATTGAGGAATGTCTCAGAAAA[CG]TGGGGCTAGTGTGCCATATTTATC
TEK 341 NM_000459.1 GTAGGACGATGCTAATGGAAAGTCACAAAC[CG]CTGGGTTTTTGAAAGGATC

128
MLR1 2658 NM_153686.4 TTTCTGCCTTCACTACGGGACTC[CG]ACAGTCCGGAGACTTCACTTCCC
ARTS-1 5214 NM_016442.2 GTTAGGGGCATGCAGGAAAGGGC[CG]GTGCTCAAGTTGGGGACCG
CLDN6 4977 NM_021195.3 AGCGGTGACGTCACTGGACCACCGCCC[CG]GAGGAGGGGCAGAGACCCT
DACT1 2883 NM_016651.4 GGCGACGAGAAAGAGCCAATGAGGAG[CG]AGGGCAAAATCGGGTGCAGTAA
PRICKLE1 4307 NM_153026.1 CACGCGCAGCCAGTGGGGCAGAGCAGCAGG[CG]GATTATGCGCAGGGAGAAAAAA
ALOX12 5511 NM_000697.1 GGGGCCTGGCTCTTCTCCGGGT[CG]TACAACCGCGTGCAGCTTTGGCTGGTCGG
ZNF382 1102 NM_032825.3 TGAACCCAGGTCCCCTGC[CG]TGAGCTCTTCTCGCATCCAGACC
TRAF3IP3 5966 NM_025228.1 AAAAAGAAAGACGGTACCAAGAAGGGA[CG]TGTTAATGGGGCCCAGACCTATG
AK1 5888 NM_000476.1 GTGCCAGAGAGAGGCCAGACCAGGGAG[CG]AGAGGGCTGAGGCATCGACTCA
NOTCH4 174 NM_004557.3 CCTGGACACCCTAGTAATGGGGGG[CG]GAGGAAGAGTGGAGGAACAC
SCARA5 208 NM_173833.3 CAATCGTGGCATTACAGCCC[CG]TGTGGGAACGCCCGCTGGGCCCAG
2748 GCCCAGCACTCATGGAGCC[CG]GAGCCTTCAGTGGTGCCAGACCAGGC
DOK3 5476 NM_024872.1 CAACTCCTGGCTTTCCCACT[CG]GCGTCCTGGTTTGAGCGCCTCACCC
COL4A1 4038 NM_001845.3 TGGCCCGAGAGCACCGACTTGGAG[CG]CCTTGTGCAGGCTAGGGCTGCAC
EYA2 605 NM_005244.3 CACTATTGAGGTCCTCTCCGAGC[CG]TCGTTCCTTTCACAGGGGTCATGCC
NUDT4 1341 NM_019094.3 TCTTTCCATTCACTGGCATGTTTT[CG]GGGCACGGTCATCCCACGCTGGGCT
PPT2 4026 NM_005155.5 CAGTCGTTCTGGTCACTTAGGCGTT[CG]CGTGAGCGCTCAACCCCTTACCGC
LOC645431 1097 XM_934774.1 GCTGTGGCCCGCGGCTCTGCTAGG[CG]GTGGATGCTGCTGCTACGCT
CHP 3858 NM_007236.3 TCGATTCCTGTGAGAAAAGGTAGACTA[CG]CTGCCTGTCGCAGGTTAGTTTGTT
ARHGEF10 122 NM_014629.2 AGCTCTGAGCCGGGAGCAGGCTCTG[CG]GGGAGGATCCAGATGTTG
PILRA 4197 NM_178272.1 TCTCTGAGGACTGAATCTGGGG[CG]CAGAAGGACAGAGATTCAGGCCTGCC
ECGF1 3789 NM_001953.2 CCCCTCGGTCCCGTGTCTGTGT[CG]CCCTCGTCCGTGTCTGCCTCCCG
FLJ31846 3937 NM_144974.1 CGTTGAGGCTCAGGACGAGGGA[CG]GGGCGGCAAATTGTCACAGAGG
MFNG 585 NM_002405.2 CCTCTGGGGCTCCCACAGTTGTT[CG]CTCAGTTCCTGAGGTCTTCACAACAG
CXCL14 6021 NM_004887.3 GAATCGTGTGGTTCTCTCTCTGGCC[CG]GCAGGCCAGCTTTTCCGAGCCG
FBXL13 3448 NM_145032.2 AGCCCTGATCGCCTACAAGTC[CG]AATTTGACTTCACTTTCTCGCATTCTGCC
C18orf56 4185 NM_001012716.1 GTGAGCCAGGGGCTGACCTTGAC[CG]CTCAGATAAATGGAGCGCAGCCTTGA
SP2 5573 NM_003110.4 CCCAGTGACTACCTGCAGCCTGC[CG]CCTCCACCACCCAGGCGAGTA
ZNF143 4857 NM_003442.3 TGGGCCAATGGAAAACCGGAAG[CG]TCCTGTGAGTGATGTAATGACAGCC
MAP3K1 3857 XM_042066.10 GTAGAGTCCAGGGACTAGGAGGACTCACAA[CG]CAGCGATGGGCAGCCAGGCCCTG
RASSF3 958 NM_178169.2 GGCCGGGAGAGCCTGATTGAG[CG]GCGGCCGCAGCTGCATAAGGACT
HCP5 4094 NM_006674.2 AGATTCGGGGAGACATTGAGACAGAG[CG]TTTGATATAAAAGAAGGGGGTA
ZNF229 5050 NM_014518.1 ATGAAACCCTTCCCACACA[CG]TCACACACGTAGGGCCTCTCTCCC
LOC642730 147 XM_931047.1 GCCCTGCTGCCCGTCGGGGAA[CG]GCTCCTGCCGCTGGTCCGCTGGCTGACC
C21orf45 2941 NM_018944.2 CTCTGCTACACCTCAGTGACCGAA[CG]CCTGCCATTACCTACAAATCGCCCG
AQP11 3245 NM_173039.1 CGCAGGGGCGCAAGGGCCGCAGCACG[CG]TGCGCAGTGGGCACCAAGAGCGCT
IL12A 3050 NM_000882.2 GACCCCGTTGCTCCGGCTGAG[CG]TGGGCTCTTTCTCTAGGTCTTTCCTCC
TRIM58 2885 NM_015431.2 GTCGGCGCCTGCTTTCCTGGGG[CG]TGGGCTCCTCCCCCTGTGCAGAC
ZNF563 2787 NM_145276.1 GAAGAAGCGATCACACAGTGCTGAGTCGAG[CG]GGATGAACGAGTTCCAGGCACAG

129
RASGRF1 5157 NM_002891.3 AATCCAGATATACCATTCCC[CG]CTGGAACCTCTTCTCCGCTCCGCA
SLC39A10 2829 NM_020342.1 CGACGTTCGAAAGCCAGGAGAAAAGG[CG]AATGATAAAGGGCGCTCCACGCATG
PLVAP 3318 NM_031310.1 GGGCGGTGCTGATTAAGTGCCACAAAA[CG]TGGGAAATGTGCCAGGCACG
MDS025 3871 NM_021825.3 CAAGCCGCTCACTTTTCGTGAGG[CG]TCACATCCTGCTGCTTCACCCTCTGGT
STAT4 3561 NM_003151.2 CTTGAGTAGCCTTGCCCCTGGTTGCTA[CG]GTGCGTTCTTCTCCCTTTGTGACATCAG
TP73L 1959 NM_003722.3 GTGGCTACTATACGTCAAGGACTCTGAAGC[CG]TGAGAGAGGGGGAAGAACA
TTC17 5383 NM_018259.3 CACCTCTCTTCCCATAGGTGGTT[CG]AAAGCACACCTTTTGTTCCCCA
2257 ACACAGGGAGGTGTTCGAATGATCCC[CG]TTTCACAGAAGACGAAACTGAGGCT
IL24 2291 NM_181339.1 CTTCTGAAATGACTTCCACGGCTGGGA[CG]GGAACCTTCCACCCACAGCTATGC
HOXB2 1577 NM_002145.2 AGGAAAAGATGAGTGAGGATCTCCG[CG]TTGGAGGAAGAGGGAGTC
C9orf156 4317 NM_016481.2 GGGGCTTCGAACCCTATCC[CG]GGCGTGTGCCCCTCCGGGACCC
EGFL8 2027 NM_030652.1 GCCTGCAGCCTGTAGGGTCCAGCGTCAAAG[CG]AATCATGGGGTCCAGGGCTG
NMNAT2 5672 NM_015039.2 CTCTCTTTTCGTTCTGGCTTCCTT[CG]CATCTCTCGCCTGGTGCCCCACC
FLJ46072 5910 NM_198488.1 GGACGCCCACGAGAGGCCCGGCCC[CG]GCATACGGAGCCAGGGCATAGGCG
CTHRC1 5769 NM_138455.2 GCTGCTCCTGCTGCTGCAGCTGCCCG[CG]CCGTCGAGCGCCTCTGAGATCCC
GSTM4 820 NM_000850.3 GGAACTGGCCCAATGCAAAAGGGT[CG]GGAGCATCTGCAACAGAGACTGAGCT
C1orf176 3262 NM_022774.1 CGAAACCAGGTGGAGTCCGAGGTT[CG]GAGGAGTATCAGAGGTTAGGG
GPR158 1700 NM_020752.1 TGGAGAAGGGGGAAGACTCCT[CG]AAAAAGTCTGACTGTTGAGAAAC
C14orf24 1001 NM_173607.2 GAGGTCGAGACGCCAGGCTTCAGGTACA[CG]TACCAGAAATGACGTCACAGGCGGTG
IRX3 5615 NM_024336.1 CGAGGGCTTTTGCTCTCCGGTC[CG]TTCCCTTCACTTCTTCCTTTCTC
GGTL3 5962 NM_178025.1 AAATCCCAGGCTTCCTTTT[CG]GGCCCCAGACCCTTTCACTGAC
TRIM50C 4954 NM_198853.1 GGGGCGCACCAGGCCGAAGGCTCA[CG]CCACAGGGAGGGCAGCTAGGACATG
HIST1H3G 5880 NM_003534.2 AGTAGATGTGTTGTGGGGCCAGATT[CG]GAGGACCACGTTTTGAGAAGTT
ZNF432 1066 NM_014650.2 GAACCCATTATTACCACAAAGG[CG]CGGCATCCCTTCTTAGCGGTTATGATGGCT
SNX16 3381 NM_022133.2 ACTCTCCTTAACCGCAGCTTTT[CG]CCTCCTCCCTCAGCAGCGAGA
FLJ39155 1601 NM_152403.2 CTGTCCCTCTCACTTCCACT[CG]ATTGTAATTTCATCCCCGGGCCGG
CKM 4216 NM_001824.2 TGTGAGCTGGAGGAAGCAGAGGC[CG]GGAGAAGGACCAATTGCAATGG
ARL9 69 NM_206919.1 CCTGGGTAGTAGTCTGGAGACACTCCTAG[CG]GAGTTTACTCGGGAGAGGG
C21orf66 54 NM_058191.2 GGCGACGGCCCCGGGCCCAGCAG[CG]ACTCCCCGCCAGGGGCCCTGT
ZNF641 220 NM_152320.1 GGCACAGAATGTCAGCGGGGCAGACCCC[CG]GGAAAGGCAGCAACCCGGAAG
GPR160 5516 NM_014373.1 GCCTTGCCCGGCTATTTGTTTTC[CG]AGGCCGTTGCGTCCGGGTAGGTTCCT
C10orf116 2999 NM_006829.2 CCCCTGTCCTGGCACCTCTT[CG]GTCCCTGGTTCGGTCTGCCCCTTT
DUSP2 5475 NM_004418.2 ACTAAGGGAAGGGAAGGTGTTACC[CG]GAGTCGGAGGGACTAGCACCCC
FGF18 5618 NM_033649.1 CTCCACTAGAGCGCTGGTGAGTGAGTG[CG]AGTAGCGAATGTGGGCAGGTG
CRKRS 839 NM_016507.1 CGTTGTCTCGCAACTCCACTGC[CG]AGGAACTCTCATTTCTTCCCTCGCT
DPY19L3 3330 NM_207325.1 CCTCATTTCCACAAAGCTC[CG]CGGCGGTTCTGCCCTCCTTGTACCC
ZBTB20 3619 NM_015642.2 CCACATTGGACGCTTCACTC[CG]CGAACCCTCTATCTCTCCCCGCTAT
USP6NL 2185 XM_927409.1 TCCAGCCGGCAGGTCAGAGGATAGCAGAGA[CG]TAGGGAGGTCAGCTGAGTAGGG
PDLIM5 3002 NM_006457.2 TAAGACTACTCCCACCGAAACT[CG]GTAGCGCAGTTGTCTTTCCGCAGCTGCTTC

130
PLXNB1 5750 NM_002673.3 GGAAAGGTCAGCTAGGAAGGAGCCC[CG]TGGCTGGCAGGGCCCAGCCAG
ST6GALNAC2 4204 NM_006456.1 CCGAGAAGTACAGGGCAAAGAGGAGCCC[CG]AGCAGGCAGCCGTGAGCAGGAGCAGC
PLEKHG1 2099 NM_001029884.1 GGCAAAGGTCGTTTGGTGCTTTAAC[CG]AGGTGATTAGGGTAATGACGCC
DCAMKL1 5958 NM_004734.2 GGGCAGATCAGATGGTGGAAGAGAA[CG]TGGACAGGGCTGAGTCTGAG
TCEB3B 5816 NM_016427.2 AGCACAATGCAGACAATCGGGACGGTCCA[CG]CCAGGTGGACTGCTGTGCCCC
STXBP2 4177 NM_006949.1 GAACTCCCATCTGTGAGCGTGTCGT[CG]AGGTGTGCACCTCCAGCGACTTCGTGCTC
SBEM 2094 NM_058173.1 TTACATGTTCAGGAGGGAGGCCATGACT[CG]AAGAATGCACAGCCTGAGTTACACCGG
IHPK2 5078 NM_001005909.1 TGGACAGAAGACTGGATGTGAATAGA[CG]GAAAGAGGGACAAAAGAGTGC
NPPA 2421 NM_006172.1 TCTGGTTCCCCTCTCTTGGCCTA[CG]TCTGTCCCTGTCTCCCAGCTGCCC
FLJ11259 731 NM_018370.1 GCTTGGATTGGTGGGATGTTT[CG]GAATGGGCATTGTCGCCAATTT
1826 GCCCTAGCAGTCTCCGCACTGG[CG]GCCAGTCTGTCCTCCCTCCCTG
ARNTL2 1088 NM_020183.3 TGCCCCGAGGGTCTAACAACTGCAATCTT[CG]GAATGCTGGGACAAAGCTTACT
RHBDD1 2249 NM_032276.2 CACACTCTCCTTACTGCGCTCTGC[CG]CGGTCCTGCCCCGCTGTGCCCTCG
MAPK13 4161 NM_002754.3 GGTCCCGCTGGGCAGCCCCGACCC[CG]TGCCTGGGCCGCACCTGCCG
CDO1 1079 NM_001801.2 CTTCCAAATAGAGAATTGTGAGGAGCCTG[CG]AAAATTGAGGATGGATTCCACTC
ZNF75A 5723 NM_153028.1 GAAAGCGTCACTTCCACTTC[CG]GCCGGCGCTCTGGCTCTGTACCTGGACAG
11-Sep 5452 NM_018243.2 CACCTGATGGAGCAGGGGGTGG[CG]GCCAGCGCACAGGCTGTCGGCATCT
SOX17 4957 NM_022454.2 GGCCCTGGGTACGCTGTAGACCAGACCG[CG]ACAGGCCAGAACACGGGCGGC
RASL11B 3497 NM_023940.2 GCACTAAGCCGGGGAGCAAACACCGCTCC[CG]GCCCGCCCAGAGCAGACGCCCTAGG
SLC1A4 942 NM_003038.2 GGGGCGGCTTCCCAGAACCTG[CG]GAGCACAACTGGCCGACCGACCC
AER61 1955 NM_173654.1 GAGTCCCACCTGGAGCCGGGGCAGC[CG]TGAACTACCGAGGAGGAGGC
HIST1H2AB 5764 NM_003513.2 AGTCTTAGCCTTGGCGCGAGCTTTAC[CG]CCTTGTTTGCCGCGACCAGACATAACTACT
NUPL1 1285 NM_014089.3 ACGCTCTTCTGGGCCCCCTT[CG]GGGCTGGGCGTCGGGCTCGCAACAACTGC
MST150 1990 NM_032947.3 GTGGCAAAGCCTCCGAAGGACCCTACACTT[CG]GACATCGCAAAGCAGGATCTGAGTCC
C19orf25 3111 NM_152482.1 GGGGAACACGGCACTAGGGGACA[CG]CCACCCATGTGGCTGACGGGA
CKB 1269 NM_001823.3 CAGTGCGAGCTGGCCCGGAGC[CG]CCGACCTTCCTCAAGGTGCCCG
TBL1XR1 1255 NM_024665.3 AAAAGCTGTTACTAAGGGAAAGAGCCAAA[CG]GTTCGGAGCAGCCAACGGCTCAGA
MYBPC2 2794 NM_004533.2 GTCAGAGGAGCAGGAGGAGGTCCCC[CG]ACATGCCTGAGGCAAAACCAGGTG
CEP152 4262 NM_014985.1 GCCGACTAGAAGCTCGCCCGGTGGG[CG]GAGCCGTGCCAGCTCAGGGCAGA
ESCO2 1337 NM_001017420.2 GGCGCTCGGCAGGTCCGCAGGCC[CG]AGACCGAAGAAGCCACTGACTCGT
C11orf17 2753 NM_020642.2 GCGCGCAGACGCCAAGGCTGGGA[CG]CAGAAGGCGTGTTTGGCCGCC
HECW2 2739 NM_020760.1 TGCATGCAGCTCACGGCTGCTGCGGC[CG]CTGCCACGGAGCCGAGAGTCTCT
NETO2 1983 NM_018092.3 GCTCGACCCTGGGCAGGGAAGCG[CG]GACATCGGCAGAGGGAGCCCG
COBLL1 2100 NM_014900.3 CAGTAGCTCGCCTGTTCTCCCT[CG]CGGCTTCCTCTCCTACTCTTCCCTT
GIPC2 1191 NM_017655.4 GGGCCAGCGTGTTTGCCTTCTAAGG[CG]TATTGTTCTGTAGCGTCGGCATCCTCAGGC
HPGD 4190 NM_000860.3 GCGATCTTTGCCTTCCGGACT[CG]CAGACCGGCTCAAAGCCTCCC
RFFL 2383 NM_057178.3 AAGACCCGGCTTGGTGACCTTGAG[CG]AGTCCCTCAACACCTCTGAACGCA
PGBD1 1707 NM_032507.2 ACCGGGCCTCTGAGCTCCCT[CG]GGAGCCTTTCACGAGGTCAGCTACGTC
CYP26A1 1938 NM_057157.1 CCCAGATCTGCCTATTGCGCC[CG]ATGCCCCGAGGCTCTCTCTTGGACTC

131
RECQL5 4969 NM_001003716.1 GACCCCGAAGAATGGTCCAGGGTC[CG]GGGTGAGATAGAGCATTAGAGACT
AMZ1 3914 NM_133463.1 GGTGCTGTGACCTGCGGCAGCACAGC[CG]CCTGCGTTGAGCGCCCACGGTGGGCTGG
TGM2 3534 NM_004613.2 GCGGTGGCTCCTTCCACTGGCGG[CG]AGACCCTCCAAGTGCGACCACTGG
RAD51C 6015 NM_002876.2 GGTCAGAAAAGGGGGACGGTCAG[CG]GGAAGAGCCAAGAGACTGCAACTCT
C9orf82 3397 NM_024828.2 ACTGGCGTCGCAGGTTATGCGTCACTTC[CG]GCCGTGGCACAGAACGTGGTG
SLC35E3 844 NM_018656.2 GGCGTTAGGTGACCAAGGGGGT[CG]GGGACCCAGAGGATAGGACCCA
BNC2 1482 NM_017637.4 TGGTTCAGCCGTAGTCGTTCTGGTTC[CG]AACTGCATGGAGTTGTCAGTACAGGA
ZNF294 1334 NM_015565.1 CCCTCAGGTTCCCTTTAGTT[CG]CTGCTTGTTCTTCCCGCCCATGGTC
CYP3A7 3694 NM_000765.2 CCCCCGTGCTCTGCCTGCAGT[CG]GAAGAGGCTTCTCCACCTCGGCAG
ZNF167 2439 NM_025169.1 CGGCTCGGCCATTGTTTTTGGTCTAA[CG]GGCAGTAGAGTGTCCGGCTTCGGTGCCG
PACSIN1 4073 NM_020804.2 GCTCCCAAGTCAGCTCACA[CG]CACGTCTTCAACACACCCACC
SMAD3 2127 NM_005902.3 TGACAGCACTTGGAAAGGAGGCTGCA[CG]CGGATTTGCATGAAACACAGACTGG
UNG2 4944 NM_021147.2 TCACCATGATGCGGCCGGGTGGC[CG]CTTTACTACCTTCAACGCCCGGGCT
TLE4 715 NM_007005.3 AATTGGTCGGAGCTACAGGCGACGCC[CG]GCCCCCACGTGGGTTTCAGCTG
UHRF1 3979 NM_013282.2 CCAACTCGGCCACTTGGCC[CG]GGCCTCCTTTCTCCTCTGGTCGTGGGG
TMPO 1838 NM_003276.1 TTCCAGCTTGGCCGCAGTTGGTT[CG]TAGTTCGGCTCTGGGGTCTTTTGTGTCCGG
CTAGE1 1776 NM_022663.1 TGCTCTGGCGGTTGCTGCAGTAACCT[CG]GCCACAACAAACGCTGGAGAAGACG
ADHFE1 3463 NM_144650.1 CTGGGTGTGACCCGCTCAGATCCTG[CG]CAGTCTTCTCCGCTTACTTTCAAGAATT
RDH10 5073 NM_172037.2 CCACCCTCTCGCAACTTGGGT[CG]AGTTGACAACTCCCGCGGCAGCC
FLJ32363 4312 NM_198566.1 AGAGTGTTTTGGCCAAGATGCCCGCCA[CG]AAACAGGAAAGCGGAGACAGCGCC
ACYP2 1011 NM_138448.2 GAAAATATCACAATCCGTTTAGAATA[CG]AGTTCAGGCTCAATTCCTTCCTGACT
BOK 764 NM_032515.3 CCACTGCTCTGCCTTGCGGGGGC[CG]CTCCGGCCTGGTCGCCTTCTCC
HDGFL1 5361 NM_138574.1 CAGTGGATCTTCTCGGGGCCC[CG]AGCGTTGCCCGCCCATTAGGTGGCG
GATA2 4156 NM_032638.3 ACGCTGGCCTCGCTACCTTCCTGG[CG]CTCACGCTGCCTCTCTCTCCCC
MGC13024 5095 NM_152288.1 ATCATGTGGCTAGCCCCGGCTC[CG]CCTCTGTCCCAGTTCCTGTTTTGGCCT
KNTC1 2205 NM_014708.3 ATGGCACAAAGGCGAGGAGGCCCGG[CG]CGTCGCACAGCTTGCTGGGAGA
PRRX2 5565 NM_016307.3 GCTGGGAGAGACAGCCTTGGGG[CG]GGTGGTGTGCACAGAGCTCTG
ALKBH 6068 NM_006020.1 GCTGCCATCTTCCCCATCT[CG]CGGCCTATACCCTCTGATCCGGAAGCA
FHAD1 3354 XM_057107.7 CCTATCTGTGAAATGGGGCAGGCT[CG]TGGGGCCTGGAGCATTCAGCAG
CLDN3 4044 NM_001306.2 GGAGGAAGGACTTGGCCCTGCG[CG]GCCCACAACGCCGGGGTAGG
PPME1 5854 NM_016147.1 GGGGCAGTCAGAGCGGAGCCAAGATG[CG]AATGGGGTACGTGACCCATACCC
KCNK6 3091 NM_004823.1 GGTTGGGCGTGCCTCAGTTTCC[CG]GAGGCGGGGCATTCCTCCGTCGC
HSF2BP 1331 NM_007031.1 ACCGTTTACAAACAGCCTTC[CG]TCTCTTCCTGGTCAAGTCCTAACCC
PGAM5 979 NM_138575.1 GGGACCAGGAGGAGGGACAGCC[CG]GCCGAACCTGAACGCACTTCAGG
EMP1 4896 NM_001423.1 CCAGCACCTGCCACTCAGAG[CG]CCTCTGTCGCTGGGACCCTTCAGGTAGGA
FRMD6 991 NM_152330.2 GCCCCGAGGGAGTCCAGCCGGAGG[CG]GAGAAGGCCACTCGGCCAGAAG
HHEX 368 NM_002729.2 GCGGGGCACCAGGGCGCCAGTTCCC[CG]GAGCCTGGTAGCAAGCGCGTCCC
NOL8 2661 NM_017948.4 CATCCTCTCTTCCTTCCTACT[CG]ATTTCCAACCCAGCCTCCTAA
MFAP4 2705 NM_002404.1 CAAGTAACCCCACTCTCTGGGA[CG]CTGTGTACCCTCATAGCTTACGAGTTTCAA

132
NEFH 3027 NM_021076.2 CAAGTCCCCTTTCTTATTC[CG]AACACACTCGCAGGCTCTTCCGAC
KIAA0652 3888 NM_014741.2 AAAAGAATAAATAGGGCGTCCGTACTGTAG[CG]AAAGTGCGACTAAGGTTAGGCATCT
TCF19 5025 NM_007109.1 TGGGAAGCGAACTTAAGCCAGCGGTG[CG]TGGCCCAGGAGTGGGAAAG
CLDN7 2352 NM_001307.3 TCCCAACAGGTGCGCCTGGGA[CG]CTGCGGGGCGCCCCTGACAAGCCT
ZNF223 5060 NM_013361.2 CGTCTCAGGGGAAAAGAAGCCTTGG[CG]AAGAGCAGAGGTTTAGAGGTGCG
MGC62100 2252 NM_206894.1 TCTTAGGCTGGAAGTAACCTTGGTCC[CG]ACGGCCCTGGGAAATGTAGT
NOV 815 NM_002514.2 TGCCCCCAAGTTACTTTGCC[CG]CCTTGGTGGCCCCCATTTGGTCACC
ZNF323 4939 NM_030899.2 CAGCAAACGGCTCTGTGGCTCCTGC[CG]CTCCCACACTTACAGCTGTACTCCTTGG
PIWIL4 974 NM_152431.1 GCCCGAGTGAAGGCCAGAGGCATCGCC[CG]CAGCCCCAGTGCCACAGAAGTGGGGC
DYNC1I1 2838 NM_004411.1 GGGCGAGCCCCGCAGACTGAGTGCTC[CG]GGGAGCTGTCAGTGTCAGGCT
TNXB 3624 NM_032470.2 AGCCACAACCGACTGTGGATCTCGGCAG[CG]ACAGTGAGGAGGGAGTCTGCAG
CD3Z 4020 NM_000734.2 TTTCTAGAAGTTCCCTGCCGT[CG]ACACGTCGGCCCTACCTGTAATCGGC
NAV3 2612 NM_014903.3 GGTCAAAGCCTGTGCATACTGCTCTTC[CG]ATACCAAATCTTGGCACTACTGGGTCACAG
FLJ36445 1324 NM_153233.1 CTTTGCCCACGGTTCCTAGGT[CG]CGGAGTCACAGCAGCCCCAAA
FLJ13910 1623 NM_022780.2 TCAGGCTACGGGCAGCTGTGCGAGCG[CG]GCCTGGAGGAGCTCATCGACT
HSPH1 3314 NM_006644.2 TGTCCGGAGAGCATGTTGGGAAT[CG]TAGTCCCGCTGGGAGAAGTGT
ZNF545 1841 NM_133466.1 TGGGATTTGAGACCGTGTGACTC[CG]GAGATTCGGGGAAGCCAGTT
DLGAP4 5524 NM_183006.1 AGGACCTGGTGGCCCCCGGG[CG]GTGGCAGAGCCCCTGTCCCAAGC
THBD 5375 NM_000361.2 GATGGCGACAGCCTCTCCTGTC[CG]TCCCAGCCCAGACACTTCTTGC
DMRT1 1060 NM_021951.2 CCCAGCTTCCTCGGTGCAC[CG]TGCTTTGGCAACCGGGTCTTGGCGCCTC
FST 654 NM_013409.1 AGACCCCCGTCTAGATTTAAAG[CG]CGGCTGCGCCCGGCTTCTGACGTCC
DKFZp564J157 2182 NM_018457.2 GGGTGACTAGGAAGAGCCGAGACTG[CG]AAGGAGAACGCAGCAAGCCCAGGCG
ABHD7 5074 NM_173567.2 TGCCTGCCCCGCCTGATGCTCA[CG]CTCCGGTCCCTGCTCTTCTGGTCC
KIAA0174 989 NM_014761.2 CTTAGAGCCCGTAGAGGGACACGGAGG[CG]CTGGGTGAAGAGTCAGGGATA
CHRNE 1768 NM_000080.2 TGTGTTTCCTGCCCCTGCCC[CG]CCCCAGCCCAGCGTCCTTTGC
HKDC1 4881 NM_025130.2 GCTGAGTGGGCTTGGCAGAGCCC[CG]GCTTGAGAGGGTTGCTTAGCAA
RCBTB2 5251 NM_001268.2 TGTGGATACCCGACCTAGAAGGATAAGG[CG]TGTATGATGCTGAGAGCAACCTTTT
SIRT1 3014 NM_012238.3 GGGGAGCCGCTCCGCAAGAGGCCG[CG]GAGAGATGGTCCCGGCCT
TRPM2 2988 NM_001001188.3 GAACATGTGCAGGCTGATGAAGAGAAC[CG]GATGAGGGCTTCACATGAGGA
ZDHHC13 5899 NM_019028.2 AATAACAGTCTGATCCTGACCCTGGA[CG]CACATCTGGGGCCCGTGGCACCTGGGG
CP110 780 NM_014711.3 CTCTGTCAGTACCATTTGAGCCATT[CG]CTTCCTGACAAGGCCCGTGGCGAGG
TACSTD1 4087 NM_002354.1 CGGGCGGTGACTCATCAACGAGCACCAG[CG]GCCAGAGGTGAGCAGTCCCGG
CHRNA9 1604 NM_017581.2 CCTAACACACCCTGGGTTCC[CG]GCTTCTCAGCCACTGGAGCTGCCAGTC
DUSP26 5268 NM_024025.1 CTCACATTCGGTGGCCCGAGT[CG]CCAGGCAGCGTGGGCTCCCCAGC
LDLRAD1 1739 NM_001010978.2 CATCTGCCATCTGACAGCAACATTG[CG]AGGCTGGAATCCTCATCCCTATTCC
CDH3 1104 NM_001793.3 ATGCGGAGCCTCCGTTTTCAGT[CG]ACTTCAGATGTGTCTCCACTTTTTTCC
ULK2 5874 NM_014683.2 CCAAACTGCCAGCCTTCGGA[CG]CCTCTCGGGGTTTACTCGCTTAGGATCC
PTPRE 3778 NM_130435.2 CTACATCCCCCAGACAGG[CG]CCTTATCCCCTCCTCTTTCCAG
CHRNA3 4334 NM_000743.2 TCAGTTTCTGTCCCAGGTTTC[CG]GGGCGTGTGCAGCTCCCGCAGGGGGTT

133
LOC126520 3440 XM_932164.1 CCGAAATGGCACACATTCAGAA[CG]TCGAGGCTCATACCTCAAGCGCACTGTGG
CELSR1 1688 NM_014246.1 TCCACTTCGAGAGCACTTTGCGAAAGTTTG[CG]AAGTTGGTTTCAAGATGGCTCC
CXCL12 2161 NM_199168.2 GTCGCTGAGGCAGAGCGCGGTCAGCA[CG]AGGACCAGCACGACCACGACCTTGG
TCOF1 5754 NM_000356.2 TCTGGTTCATGGGCACCAAAAACCGTG[CG]AAATGGATAAATGAGCAGGTAATG
SLC6A2 5379 NM_001043.2 GTCTCCAACTCTTGAGTTCCGG[CG]TGCCCCAACCTCTGTTTCCAA
GGTLA4 3031 NM_178311.1 CACCGGCGCCATTAAGTGCTCA[CG]CGCCCACTCCCTCAGGTTTAAAA
NDUFB2 2424 NM_004546.2 GACTGCTGGAGATGGTGGAGTC[CG]TCAGTGAGTGTGGGGCTG
EME1 5719 NM_152463.1 CCTCACCCCGCTCTGACTACTG[CG]TCCCATTACCGGCTGTCCGGGTC
HIST4H4 3450 NM_175054.2 CAGCACCTTCCGGTGGCGCTTGG[CG]CCTCCCTTACCCAGCCCCTTG
CST6 2114 NM_001323.2 CGCTGGCGCTGGGCCTGGCCCTGGT[CG]CATTCTGCCTCCTGGCGCTGCCACGCG
RRN3 4005 NM_018427.2 ATCTTCACGGAGGAAAGGGGATT[CG]AACCCGGCTGACCCAGGAGCCT
MCTP1 2820 NM_024717.3 GCCGCCGAGGCTCTCTGGCCT[CG]GGACTCCGGCGCTGCCTCTTCCTC
ALDH5A1 5371 NM_001080.3 CCGGCCCAGCTCCGCTGCTA[CG]CTGGGCGCCTGGCGGGCCTCTCTGCGGC
MTMR9 5242 NM_015458.3 ATTCCGTAAGGTCACAGTCAC[CG]CCTCCATCCCCTACTTGCCATGTCT
IFIH1 5123 NM_022168.2 GACTCTGCGGTGTGCGCCTGGGGTCC[CG]GACCGGGGCGATCCTGCTGCACACTC
NDST2 917 NM_003635.2 GGGACCACGACTTCGGAGCAGGGG[CG]GGCTCAGGCCTGGGCTCATC
CLDN10 5943 NM_006984.3 CCTGTACTTCCTCAGGCCATC[CG]AGCATGAAACGCTGTCACCTACCCACA
TSC22D2 1002 NM_014779.2 CGAGCTGGACTGACCACGGCTGCC[CG]GAGACGAGAGAGGAAGCAGCCG
ZNF135 3285 NM_003436.2 GTTCCAAGCGGCACTTATCC[CG]CGTTGATGCCCAGGCACCCCGC
NAPRT1 5715 NM_145201.3 GGCTAGGACGAGGCAGCCCAGATGGA[CG]CAAATGTCGCTTGGAAAGAGCTT
LOC285016 3990 NM_001002919.1 TTTCTTTCCCCTTTGGAAGC[CG]CGGGTGCCAGGCAGCTCCCCGGC
PTPRH 778 NM_002842.2 CAGCACCTACTTCCTCAAGAT[CG]AGGTGCAGGCACCCAGCTCCTTCT
BCL6B 3478 NM_181844.2 TCGTCTGCCCAAACCTGCTGTCT[CG]TTGGGCTCCCCCTTTTCTCCC
KSR1 2375 NM_014238.1 GCTTGTGCAAGAGCCCTGAGGCAGAAT[CG]AGCTTGGTGTGGTCAAGGG
TMIE 3913 NM_147196.1 CTGGAACCCTCCATAACACTGC[CG]GCTGGCAGCTCTGACCATACCATCCC
PRKCH 4188 NM_006255.3 TCTACCACGCCTCAGGTGTTTGCT[CG]GGCTGGGCCACGAACCCTTTCCTT
ARL13B 1248 NM_182896.1 TCCTTGGCTAAGAGGGCAGTCGTCG[CG]GACCCACGCGGTTAGCAAGGCTTAGT
WNT10A 1608 NM_025216.2 TCTGCCAGGCACACACACCT[CG]CGGTAACACATATCCCCCACACA
POFUT2 744 NM_015227.3 CCATCCTCTGACCCTGCC[CG]GTCCTGGAACCCCAGCGTTGGCAC
C10orf89 3670 NM_153336.1 TTCACATCTGGGAACCGCAAAGGAGCG[CG]GTGGTCGGACTGTCAGCCTC
SOX7 1151 NM_031439.2 ATACTCCGACTGCCATTCCTTT[CG]AAAATGACCGGGCTTCGGCCACCG
MGC40168 1581 NM_153709.1 GCGAGGAGGCTGCGAGGAACAGA[CG]CCAGAGCTAGGCCTTGGGGCC
CLDN11 6041 NM_005602.4 GAGTGCTCGCAGCAGGGAAGAAGGAG[CG]AGCAGGGAGGAGCTGAGGA
ZNF141 5602 NM_003441.1 GGACTGAGGTCGGCCTGCAGGCTG[CG]GCCCCGAAGGCAGGATTTGT
DNAJC18 5583 NM_152686.2 CCCAGGATCTCAGCCCTTGTG[CG]TCTTCAGGATCCTCATCCCTGATCT
CLDN1 4874 NM_021101.3 CTCAGGGGTGGCAGGTGCAGAAGG[CG]GAGAGTTTGCAGGTGGGCAAC
APOC2 5133 NM_000483.3 TCAGGAGGGTGAGGGCAGGAG[CG]TGGGTGGAGTCAGCAGGTCCC
NPPC 2043 NM_024409.1 GGTGCGCTCTGAGCCCGTGACTCTGCT[CG]CGCCTTTATAATCCAACCTGCCGCTGAT
YBX2 631 NM_015982.1 GAGGGGCGGGAATCTGCAGCCT[CG]GTTCTGGCAGTGAGTAGCACCGCTC

134
FANCA 4151 NM_001018112.1 CTTCCTATTGGCTGCGGCCAGGCG[CG]CACACCCGTTGGCTGGCGGCGGCCA
MAMDC2 3842 NM_153267.3 ATAAAGCTTATTCCACCCAAC[CG]TTTCCAAATTTTCCTCCAGGCTGT
CSMD3 3906 NM_052900.2 CTTTGCTCGGCTTTCCCCTTTG[CG]GATCCCTTTCATATTATTCGCGAGCTC
KIAA0182 4982 NM_014615.1 GTTTGCGGCTGAAACCCGACACCTCC[CG]CTGGCTGAGGTCAGGGAGC
TUSC3 6070 NM_006765.2 CAGGTCTTCTCCCGGTGAAC[CG]GATGCTCTGTCAGTCTCCTCCTCTGCGTC
WFDC2 601 NM_080733.1 GCGCCTAGAGGGGCCGAGCCACGAG[CG]CCAGGATGGAGCCAGGCGGA
LOC642853 887 XM_931116.1 GAATCGTGGACCCAATATTCC[CG]TCTCCCCGAATTCTCTTAACTCAGT
P2RY2 5132 NM_002564.2 GGCGCAAAGGTCCCGCAGTGGGCCA[CG]CAGGCACCGGGCTGACCTGGCA
ZNF335 6062 NM_022095.3 CGAAGCTCACCCGAGGCTTT[CG]TAGCCACGTTCCTCTCTGACTCCG
GLS2 5930 NM_013267.2 CGTGTAGAGAGGAGGGTGCTGCCT[CG]AGAGAGGAGGCTAAGTAAGAGTGA
CANX 3562 NM_001746.3 CCCTTCCTGATGGCCGATCGT[CG]GACTCCTACCCCTTTTGCCGGCTGC
CENTA2 1099 NM_018404.1 GGGTCCCTCTCCACCTGC[CG]GGCGGAGCGCACGGGCCATGGGCTGAGC
BCL7A 4227 NM_020993.3 GGGCAGGTCGGTTCGAGCCGAGA[CG]AGGAGCCGGGCCAAAGATGATA
ZNF625 5678 NM_145233.2 AGGTGTCCTGGCCTCCTCTCCA[CG]GATCCCTCTAACAGTCCAGTCACA
MXRA8 1256 NM_032348.2 CATGGGCCCCTGATACCACGTGAT[CG]TGTCTCACGTCTAGGAGCCTCCCG
POLG 1661 NM_002693.1 GGCCTAATGGATAAGGCGTCTGACTT[CG]GATCAGAAGATTGCAGGTTCGAGT
EDG4 2721 NM_004720.4 TCTTCTTCGTGTCCAATCGGC[CG]CCGAGTTACAAGCCACTCCCTGATC
RAD9B 4133 NM_152442.2 GGCAGCCATGCTGAAGTGCGTGATGAG[CG]GCAGTCAGGTGAAAGGTGGA
BRUNOL6 3868 NM_052840.3 CCCATCACACATCTCTGTCTT[CG]GTGTCTTTAACCACTTTCTTACCCCTGA
BHMT 651 NM_001713.1 GGCAAAAGTGCAAGAGGCAAAAGGGA[CG]CTAGGCAGGTTTGAAATCTGAGCG
RPP25 2110 NM_017793.1 TGCGCGCTTTAGGGTGAGCCAGGCA[CG]ATGCCTTGCCAACGTGGCCGCC
ZNF31 3103 NM_145238.2 AACTGTCCAGTTCTCTCCTGCCTAT[CG]GGCTGGTCACCTCTAGTCATTCTCTCTTCT
C6orf206 2534 NM_152732.2 GGAGCTTCAGGTCTCCATGGAGG[CG]GCTTCTCCTAGCAACTCGACGGGCGTT
ABHD3 1240 NM_138340.3 AGAGGGAGAGCTCCCGGGACAACATC[CG]CAGGTCCATGGCCAGGCGCTGCATG
MGC15875 2230 NM_032921.1 CTAGAATCTAGGCAGGGTGAACCGGA[CG]AGCTGTATCGTCGCTGAGAGAATC
ZNF274 3981 NM_016324.2 CGGCCTGACCCCTGTCCAG[CG]CCTTTCCTTTCTCCAGCTTCTGCTCTGC
RNF125 285 NM_017831.2 ATTGATTGGATGACAGAGTAGCGATAGCAC[CG]TCTTAGGAGACGCCCAATCATAGGTC
HELB 2330 NM_033647.2 AGGAGGATGAAGAGTCCGTGTTCAT[CG]ACGCCGAGGAGCTCTGCAGTGG
CACNA2D3 4287 NM_018398.2 ACGTGGTGCGCTCGGAGCAGCAGATAC[CG]CTCTCCGTGTAAGTGCCGGCTCC
ZNF451 3239 NM_001031623.1 AGAAAGAGGCTCCGGGGAGATAG[CG]GACCAGTGAGGGCTGCCCCT
FLJ40434 2409 NR_002314.1 TAATGGTTCAAACCCCCAAA[CG]AAATGTTTGCAATCCTCTTGAGTTGCCAAA
ABHD4 3927 NM_022060.2 CCGGGTCAGCTGGTGCTGGCGTCAGG[CG]CTGGGCGGGCTCGCCAGGACCTGGCA
ZFP3 3489 NM_153018.1 TCTAGGAAACCCGGAGGACTCAGGT[CG]TCAATGATTCCGGGGCTGAA
FBXO6 5906 NM_018438.4 GAGTCTATGAAGCCTGCGGAGGTCA[CG]CCCTAGGGAAAGAAGGAGCCCACT
SLC16A6 2932 NM_004694.2 GCCGACCATGTGCTGCGAGCGCTGAG[CG]CAGCCAAGGAGGGGGCCTGC
RUNX3 5221 NM_004350.1 CGGCCTTGGCTCATTGGCTGGGCCG[CG]GTCACCTGGGCCGTGATGTCACGGCC
CHI3L2 4173 NM_001025197.1 TGATGAGGAAGGAGATTCAGGGC[CG]AGGGTGATACCAGGAGGCAGA
MGC33926 6130 NM_152390.1 CCAGAGCCGGGATATAAATGCACCAGGAGC[CG]GGGAGCAGAGGAGCAAATGAG
ANKRD43 963 NM_175873.3 GGTGCGCAACTCCGAGCTGCTGAGC[CG]CTTCAAGCCGCTGCTCGATGCCGGC

135
OACT1 5500 XM_371801.4 AGCCTCCGCTGGGTAAACCGGCATT[CG]ATCAGACAGGCAATGACTTTCGGG
ZC3H11A 3730 NM_014827.3 GAAAACTTGTCATCATTTTAGTCATT[CG]GTCAAGGCCCGTCAGATACTGCAAG
CKAP2 4268 NM_018204.2 CGGCAACTGCAGTCCAGGCTC[CG]CCTCCCTACGCCCATTGGCTTATTCA
AMOTL1 3676 NM_130847.1 CCAGCCGAGGGACTGAACTAGCCATGAT[CG]CCTCATGTGGAGGGCAAAGTTG
884 ACCCACACGCAGGATAACTGGCGAGTGACG[CG]GAGTGGCTGCGAGTCCAAGTTAT
DNAJA4 509 NM_018602.2 GGGCGGCAGTCAGAGCTGGAGCTC[CG]GGGAATCAGACGGGCAGCCAA
BSPRY 2916 NM_017688.1 TCACCAAGTATGTGGCGGACGTCCTGC[CG]GGGAAGAATCAAAGAGCAGTGG
RASSF5 2459 NM_031437.1 CCAAAGCTGCCGCCACTAGC[CG]GGCATGGCCATGGCGTCCCCGGC
EIF2AK3 2807 NM_004836.3 GCGTTTGCTCTCTCATTGGCTGCGGC[CG]CTGCCACTCCATGTTCCCAGGCTGG
RGS1 103 NM_002922.3 TTTCTTTCTAATCAAGTGACCTGTTCT[CG]TTTGGTTAAGTTTCAACCACAAGACAC
BFSP1 3741 NM_001195.2 CGCGCTGCTGGGACGTTCCAGAGC[CG]ATCAGCAGTTGGGCGCCACGCTG
ITSN1 5716 NM_003024.2 GCCCCTTCTTCCAATTGGCTGG[CG]GTTTCCCCACCCACTTATGGGC
DERL3 6059 NM_198440.2 GAGGCTGGTGGCCAATGGGCAGG[CG]CCAAGGTTGAGCACGTGGCGG
GPX3 2144 NM_002084.2 GGCTTGGCCGCGGATTGGTCACACC[CG]AGGGCTTGAAAGGTGGCT
FAP 2934 NM_004460.2 TGGGTCACTGGATCTGTGAAAAC[CG]TTGAAAAGGACCAAGTCTGTCTT
C6orf165 4880 NM_178823.2 GACACGGCTCCTGCTGTCGATTC[CG]ATCCAGGTCAGCCTACTCGGGGCTC
SLC1A2 1746 NM_004171.2 CCCTTTAGCGCCTCAACGGG[CG]CAGGAGGCTCCTGCGGGCGCTAATCCG
C12orf28 2413 NM_182530.1 GAGTTAGAAATATGGAACAGAAAGCTGGCC[CG]GCTAAAGCGGCTCAGTAGTTGGA
RNF152 4160 NM_173557.1 CAAGTCACCGTCACTCTGCTTTGG[CG]ATTTCTCTACTCTCTCCAGACCCA
FOXJ1 21 NM_001454.2 TAAGTATGTGGTGCCTGCGAGGACCA[CG]GTGGGAGCTGAGCACTACCCCA
ZNF615 5736 NM_198480.2 GGTGGGCTCCGGCCTCATCTCT[CG]GCCTCCTCAGTGCCTGACGGCGACT
GPR126 2358 NM_198569.1 GGGGACTCGGGTAGGCTGCAAA[CG]CTGGGGAGATGCCACAGGAGC
TAX1BP3 3092 NM_014604.2 GGAACGCTAAGTAGTGTGTCCGGCGC[CG]TGTTCCAGGTAACTGGGCCACCG
TXK 3630 NM_003328.1 TCATAGTTCGCTCAAGATGTTTCTCA[CG]GGCAGAGTTAACCCCACCTATTTTC
PARD6B 614 NM_032521.1 CGCAGGACCAATCGTGCGGTGGTAGG[CG]GGGTTTTGAGGAGGCAGC
KIAA0690 3429 NM_015179.2 TGGCGAGGAATGAGCTTAAATGAC[CG]GCTTCCAGGGACGTAGAAACACGC
PRSS21 3420 NM_144956.1 GAAGTGAAGAGAGCCCAGCGGGAGCC[CG]CAGTGGGGACAGCCTGGGCAG
LSMD1 2995 NM_032356.3 TTACTTGATCCTTATATGCCCCACG[CG]GGACTCATACTACGTTTCCCGTGAACAC
NNAT 3038 NM_005386.2 ATCTCGGCAAACCCTCTTTCT[CG]ACCACCCACCTACCATTCTTGG
COL6A2 1870 NM_001849.2 GACCAGGTGAGCGCCTCCCGGACCC[CG]CACCCTGGAAGCCGCTCGGCCC
C7orf29 2811 NM_138434.2 AGCCACACTCTCTGCCTGTCTC[CG]CCACCCATTGCTTGGGACACTTCCC
BICD1 3487 NM_001714.2 CATTTCTCGTCAGTTTCTCGGG[CG]GTGTAGCTGCCGCTGCCACCAGAGCC
PVR 2986 NM_006505.2 GGGCTCAGGATCTGTCCCATCA[CG]AGTTGGAACCTCAGCTCTGCCACTCGG
FBXW7 5517 NM_033632.2 CCTCTTCCTGGGTCTTTTCAGGCTG[CG]GCTTCTGCCCGTCCAGGGCCACT
ANKFY1 4826 NM_016376.2 CGTAGAGGTCTGCCACGATGGCCAGCAGA[CG]GCTGATGAAGGACTCGCTGC
MIB1 897 NM_020774.2 CAACGGCACAGCTGCCAACTAC[CG]CTGCTCCGGGGCTTACGACCTCCGC
RGMA 62 NM_020211.1 AGGCGGTTACATCCAAGACAAATGCTGTTG[CG]CTCTGCGGAGACGCACCTTTGT
C6orf148 4207 NM_030568.2 GCGGCAGCGGCTGCAGGCCTGGC[CG]ATTGTGAGGAGACAGCGGTACCT
ZNF561 5806 NM_152289.1 GTCCAGAGAAAAAGGTGAGGTTAGAAC[CG]GGCCTCCAGACGGAACTGTG

136
FBN2 915 NM_001999.3 TGCATAACCGGCCTAAAGCCC[CG]AGCGACTCCAGGACCGTCAGCGG
COLEC11 5067 NM_024027.3 AATGAAACTTAAATGCGTAGAGTGAGTTTC[CG]GACTCACGTGTGGCCAGGTCTC
FER1L3 3393 NM_013451.2 CTTTTGACTTTTCGCTGTTACTTCTCA[CG]CCATTGAACACACCCACTCAGTAAC
ISG20L2 3695 NM_030980.1 GGAGAAAAATGAGGTAAGCTCGATCTC[CG]TAGGACTTATGGAAGGAAAGACATC
LOC150356 4248 XM_377720.2 GGGGGCACCAGCAGCTGGCC[CG]GGAGTCAGCAGTCCTGGGCTCCCTC
TTMB 678 NM_001003682.1 TCCGCCCGCAGCGAAGCTGCAGCAGGAG[CG]ACTTGAGCTAGACACCGGGAAGAC
MRC2 4132 NM_006039.2 GCCCTGGCCTCGTCACCTGCTG[CG]CTGCGTCCTGCTCCTCGGGTGCCTGCAC
ECT2 5655 NM_018098.4 GGCGGTATTTGTGAGAGGAGTCGG[CG]TTTGAAGAGGTGGAACTCCTAG
SGNE1 5328 NM_003020.1 GTGTGCTGTAGTGGTGATCTGGCA[CG]TTGTAATTGAGACTGAGGAGGT
FAM29A 28 NM_017645.3 CTCCCTACGGTCAGCCTGAGGT[CG]CGGTGGTCCTTCCATTGCCAACGCC
RAD9A 2868 NM_004584.2 GGCAGCATGAAGTGCCTGGTCACGGG[CG]GCAACGTGAAGGGTGAGTGCA
LOC441208 2827 NM_001013723.1 CCCCTTCCTGCTGGAGCCAG[CG]AGGGGTGCCTGCAGCCGGGACACCTT
ST7OT1 1994 NR_002330.1 GCACTCTTGGGAGTGTATGGATGA[CG]TGTCAGGTCACCAAATGGATTGTCG
PLAGL1 5664 NM_006718.2 AGCGGGGCCTGCTAGCCGAAGTCTC[CG]CCAGGATGGGCCGCCAGAGCCC
OSMR 5801 NM_003999.1 GGTCACTCGGCTTACCTCTGGTTC[CG]CCGGCTGGCCCGTGCGTCCTTGGCC
SESN1 2022 NM_014454.1 TCGCGGGGTCAGTGGATATCCTCA[CG]TTGTGGAGCTGTCAAATCCGTG
PITPNM2 2157 NM_020845.1 GACCCACCTGTATCATGTACAGCTGGG[CG]ATGCGGTACTCCTCCACGGTCATTGGC
TLE1 5823 NM_005077.3 CGACCAGCACTCGGTGTTCTC[CG]CGGTTGCACAAACCCTCCGGGCC
STK31 1671 NM_031414.2 CCCGCTAACACCGGATGATGGCGCAG[CG]CTGTGCACGCAGGCGCAGTGTGG
LOC642452 3150 XM_926229.1 CCCACAGCTGCATCATCCA[CG]CAAAAGTCACCAATACCCACAGCTG
FSTL5 5650 NM_020116.2 CCTTTGCCTTCGCGGGGACTGC[CG]TTTCTGCGCACTCTAAGATCGCTGCGGGCA
TCF15 913 NM_004609.3 GCCGGCGGCCCACCCCGAAGGCCCC[CG]TTCCCGGCTGGCTAGCCCGGCA
STK17A 3398 NM_004760.1 CTTACAGCTCAAATGCCTTTTATTAAC[CG]AAGGTCAGCTTTTGTGACTCTCAGACGCTC
DDAH1 2983 NM_012137.2 CCGGACCTGGCGGTACCTGTGTTCTGT[CG]CAGGTGCACACCTCCCATCGTCC
ZNF559 5131 NM_032497.1 CGGTGGTGTCCCGGTGCAGCCACG[CG]AGAGTAGAAGGGTGGAAAGG
TNFSF15 4065 NM_005118.2 TCCTGGCCTTGGGCCTGCAGCTGC[CG]TGCTCTGGCAGCATTTCCACACTGGCTGTT
RAB37 1009 NM_001006637.1 AGAACGCAGCCGGGTGCTGAGCCTC[CG]GAGTCCGGTAGCTGAATGAAAT
UBR1 6080 NM_174916.1 GAGGGAAACTGACGCCTGCAGTTGC[CG]ACCCCCGGCCAGAGGCAAGCGG
IFIT1 5044 NM_001001887.1 TTTAGTTTCACTTTCCCCTTT[CG]GTTTCCCTAGGTTTCCAACTTGCAA
JMJD2B 1842 NM_015015.1 GCCCAGCTGCCGTCGGGTTGGT[CG]CGGCAGCCTTGGCTGGCGTGCGCCCC
TFCP2L1 4176 NM_014553.1 TGCTGGTTGTAGTGCTCGGGCTG[CG]TGTGCCAGAAGAGCATGGCTGG
EOMES 1046 NM_005442.2 CCTCTCCTTTTCCTTCCT[CG]TACCTCTTGCTCCTCAGGACCCC
ZNF266 265 NM_198058.1 TTATTCTCACCTCCTCCCA[CG]TTCCTAGCACCCTCAAAATGATGCTTC
GOLGB1 3569 NM_004487.1 GGACGGAAGATGGGATTAAGACAC[CG]ACCAATCAGGACTATCGGCAGGACGT
SALL4 5834 NM_020436.2 CTCGACATGGTGCGAGCATCGGGG[CG]CCGGGAGAGCCGCAGTTATTTGC
PHF10 1125 NM_018288.2 GGTGGGACTGGGCCCACGCCC[CG]GCACCCAGGCCCGGGACGG
DCBLD1 5744 NM_173674.1 CCCGCAGGGCTGGGCTGAAAGC[CG]CCCCAATGGGATTCGGTGCG
C20orf58 4259 NM_152864.2 GGCCGGAGCAGGAGCCCATGGTGCC[CG]CCTATACAGGAGGCCCCCGGGTG
SLC22A17 5148 NM_020372.2 CCCGCTCTGCAGCTCTGCAGC[CG]CGGGCGCCTCCTTGGTCTCTGCGATCTC

137
LOC441459 5839 NM_001013728.1 TCGCAGAACCGGGGCTAGATGTCGC[CG]TGGCTGCGGCCAAGCCAGGCG
LOC90342 629 XM_031009.8 CCTTTTCTCCGTTTTCCTCT[CG]CTTGCCCTAGTGTATTCCCGACTCTGTTAG
ECHDC2 2985 NM_018281.1 GGAGGCACAGAACGCGCAGCATCGGGG[CG]CAGGCTGGGAGTGAAGGTG
C15orf42 935 NM_152259.2 AAAAGACTCCTCCTCACC[CG]GCCATGACTCACCATTGGATTCAAAA
PPAPDC1B 1697 NM_032483.2 CCAGTTCCAGCCGAGTAGGT[CG]GCGTACGGTCCATCATCAGCAGCTC
TCEA3 4201 NM_003196.1 GCTTTAACCTGCACTCACTCCAT[CG]TGCACACGGCCTGTGCATGCCACGTGTATC
LOC115749 2798 XM_056680.7 CCCCACCACTGCGTACTCTGTTG[CG]GATCACACCATCCAATACAAACTTT
VPS13C 6004 NM_017684.3 CATCTATGTGGCCGCTCTGCTTTCC[CG]CCGTCACCTGCTGTTGAACTCCGGCCG
FRAT2 1714 NM_012083.2 GGGACTGATTTCCGACCTCC[CG]GGCCCAACGAGCCGTGCTGAAACGT
MCM10 3348 NM_018518.3 GAATGGACATAAGGCTGACAAAGGAACAGT[CG]GTCCCAGAGCGTCAGGAGTTGAG
671 ATTGATTATTAATTTGAGAAACGTGATTTC[CG]AAAGCATTATATTGGGTCAGGTTTCC
ZNF181 2632 NM_001029997.1 AGAGCTCGCCTGGTACAAGGTCTGCCCA[CG]TCCCGGGAGATAAACATTAGTGTGA
COL13A1 4222 NM_005203.3 TGACTGGCCCGGGAGACACGAGG[CG]CCCAGAAGGACTGACAGCGCGGC
COL9A3 697 NM_001853.2 GGCACTGACCGGGCCCTGGTAC[CG]GGGATTCACCCTCCCCGGGGTG
SLC7A5 3295 NM_003486.5 CTGGCGGGCTATTCCCAGGCC[CG]CGTGGTCCTCGAAGGCCCCAGTC
TRIB3 3498 NM_021158.3 GGATGGTGCGATCCCGGGCC[CG]AGGGCATCAGACGGCGGCTGATTAGCTCC
SNX19 2715 NM_014758.1 GGGCGCGTGCTCGCCAAGAGCTGG[CG]CAGATTTCCGAAGTGCCACGAAACAGC
FLJ41603 1564 NM_001001669.1 GTCTGGACAAGCTACTGGACTTTGAG[CG]GGTGGAAGAGAAGCTGCTG
LOC201164 606 NM_178836.2 GCGCCCGGAGCCCGCAGCAGGGCCT[CG]GTACAGGTCACCTGAGACGGGA
FBP1 4928 NM_000507.2 CCTCCACCCGCACTGTGGAG[CG]GGACTCGGGCCATCGGACTCTGCCA
ANGPTL7 2804 NM_021146.2 AATATTTAAGATGCTGACTTGTGGAGCATT[CG]GGCTTGGAAGGAAAGCTATAG
WDR69 2312 NM_178821.1 TCCCGCCTATCCATTTAGGCTG[CG]ACCTCTGGTAGTTCTCCACTTTCTCTAATT
PADI1 3157 NM_013358.1 AGCAGGTGAGTCCTGCTTCGCC[CG]GGGCCCCCAGTTGAAGCTCCC
C15orf33 3936 NM_152647.1 GTGTGGAGCTGTTCGAGGACTCG[CG]GGTGTGCAGGTCTGAGTACCACT
ENO3 682 NM_001976.2 GGACCGAGTGGCTCAGGGATAAATG[CG]CAGCCTGAGAGGGGGTGAG
HSPB7 1039 NM_014424.3 GGCTGGATCCTGTCTCCTTGCCACT[CG]GACCTCGGTGCCTGCCCCAGAAC
SCN4B 4965 NM_174934.1 TCCAGTGGGGCTGGGCTGCTG[CG]GCTGGCACTGCAGGGCCGG
KCNK5 3518 NM_003740.2 AGCCTGAGGAAGGGGGTTAGAA[CG]GGGCTGAAGAAGCTGTAGG
KIF21A 2327 NM_017641.2 CTGCCCCCTCCGGTGGGGA[CG]CGGCCTCCCAGCGGCCAGGCTG
GRIN2C 6048 NM_000835.3 CAAGCTGGGTCGTGACCCCGAGTCC[CG]CAGTGGGGGGACCAAGCCAGCC
DES 4008 NM_001927.3 GGAGATAACCAGGGCTGAAAGAGGCC[CG]CCTGGGGGCTGCAGACATGCT
C8G 5035 NM_000606.1 TGGGTGATGGTTTAAGGAAGATAA[CG]TGTAAAGGGCTAAGGACTGTCG
PSEN1 3503 NM_000021.2 TGGTTGTCAAAGTTGGAGTCCAAGAAT[CG]CGGAGGATGTTTAAAATGCAGTT
TFEB 5534 NM_007162.1 CTCCGGCAACTTGTCGCAAGTT[CG]GGTGCCTGGCCCGCAAGCTGTGCCCG
TTC14 4082 NM_133462.1 CCCTGCATTCTCTAGCCATGGAC[CG]GGACCTTTTGCGGCAGTCGCTAAATTGCC
NEF3 2021 NM_005382.1 GGCGATATTCGCACCAAGGGTGCGAAA[CG]CAATCGGGAGGTGAGAAATG
RNF175 4304 NM_173662.1 GCCATGCAGGGCCCCTGCGA[CG]CAAGCATCTTGCCTTTGCCCCTCTAC
SULT1A1 3975 NM_001055.2 GCCAGCCTCCAGCAGCTACTG[CG]CTGCAGCAGCCGGCACCTGCACCTG
NEIL1 3805 NM_024608.1 CTTTCAGTGACCAATCTCTTTCT[CG]CCTCAGGGCCTTTGTACTGGCGGTTCCTTC

138
C12orf5 233 NM_020375.1 TGCCCCGAACGCAGGCTGCCGGCTAT[CG]AGGGAAGGAATCCTACCGCG
SLC29A2 1041 NM_001532.2 CAGCACTGGTGCGGGGCTCTTCC[CG]CTTCGTCAGCTCCGAGGTGATGCCA
GRAMD2 4902 NM_001012642.1 ATTGTGTCCCCTCTGGACGCTTCTGT[CG]TCCTAGTCTTGCGGCTTGGGTCCCTCTGC
HGS 3171 NM_004712.3 GAGGCAGCGGCACCTTCGAG[CG]TCTCCTAGGTAACGCGTCCCCAC
TTC23 4111 NM_022905.3 CTGTAACTCTCCAATCTCCAACTATGT[CG]TAAAATCCCTTGCCAGTTTACCCA
LCK 3840 NM_005356.2 GGTCTATGGTGGCAGGAAGCTTGG[CG]TGCTAGAGGGTTGTGGTTG
GPR68 1888 NM_003485.3 AGGGGTCCTTCTCCAGCCA[CG]CCCACTCCCGGGTGCCCTGGCTGTC
SC5DL 4009 NM_006918.3 CCTTGAGGGAGAAAACGACCCAGACATT[CG]CGTCAAAGGAAGTGTCGTCTATTT
SLC25A35 5600 NM_201520.1 GGTGATGAAGGCATGGAAGACATTT[CG]GTAGTGCCGCTGGTATGTGCCAG
SPRY2 3965 NM_005842.2 CGGTCCCAGCTCATTGGCTC[CG]CGGGGCTACATTCACTCACACTCCAG
FLJ90166 3711 NM_153360.1 AACCCAGAAGCGCAGTGAAAGTGGCCAACC[CG]GTCGCCTAGAAGCCAGCCCCGGCC
C3orf38 5798 NM_173824.2 GGCCTGGAATACTGGAGGCCCTT[CG]ACGGAGAACAACAAGAAAGGCACTTC
LOC642378 2324 XM_925907.1 TGAGCCCAAACATGGTGGGGTTTA[CG]CTGGACCCCGAGCTTGCAATCTG
LETM2 2939 NM_144652.1 CCTGTTTAATCCAGTCTTCAATCA[CG]GGTTTCCTCGGGCGTTAGCCACTGCC
MGC42367 2406 NM_207362.1 ACCCGGAGGTGGTGGCAAGTCAGTC[CG]GGACTGGCCCAGGGCACCC
LRRC35 3041 NM_152715.2 GGTCAATGCAGGACACTGGGCTCCGG[CG]GCCAGAGTGGGGGACTAGG
WWTR1 1974 NM_015472.3 CTTTGAGTTTACCACGGACTTGGGG[CG]GGATCAAAGGGAAAGTGG
U2AF1 2813 NM_006758.2 CCACAGAGCCGCCTGGGGCT[CG]GTGGGGGGCGCTCAGCTCGACCCC
LXN 623 NM_020169.2 CCGCCCCACTACTGCCTGCAG[CG]GGCTTCCTTACTCCGCCTGCTGGTTCC
RABL3 791 NM_173825.2 AAACCTTGTTCCCTGTTCCTTGTT[CG]GAGTTCCCTGGCCGGGCATTGCATTT
PEAR1 4990 XM_371320.3 TCTGCATGGTCTGTGTCGGGTA[CG]TGTGTATGGGATGTATATGTGAA
PAK6 2215 NM_020168.3 GTGTGGACCCACGTGTGTGTGAGTG[CG]AGAGTGTGTAAGCCAGTGTGTGTG
PPP1R13L 5052 NM_006663.2 GGAGATACAGAAGAGCCGAGACGCCTGCCT[CG]CTGTGGCTGGAGACTGACTC
ZC3H7B 740 NM_017590.4 AGGGGCTGGAAATGAAAGTAAAG[CG]CTCCAGAGCCACATGGACGGAGCTG
UGCGL2 753 NM_020121.2 AGCCTAGTAGCAGCCGCACCA[CG]TTCGTGGCTTTCGCTGGCGCCATGGCAC
ZNF667 430 NM_022103.2 CGTGTGGACACTGAGGCCCTTCCT[CG]AGCTCTTTAACCAAACCCAACCT
ADAMTS9 140 NM_182920.1 GCCGGAGCCTGGTTACCTTGCCT[CG]GGTGCAGCCTGTCCTTGCGCACGGCC
ADAM17 4850 NM_003183.4 CGCCTCCTTTGTCTTGATGCCCA[CG]TCTGGTTAGGACCCCTGCTGTCCATTTT
NTSR1 5333 NM_002531.1 TGGAACCCGTGGCAAGCGCCGAGC[CG]GGAGACAGCCCGAGGAACCACG
SLC23A3 3856 NM_144712.2 GATCGGCTCATGCTGCCTTGCCTTT[CG]CTTTGTCTTGGCTGCCCGGGACCAGAG
LOC440335 5211 XM_498632.2 AGGGGGACACACAGCAGAGTTGATAGAGAG[CG]AGAAAGACGGCACAGGCATGAAGG
BAT1 1111 NM_004640.4 TCCATGCCCCTCATCTCTT[CG]TTTAGGTTTTTGCCACGCAGGTCTTCTC
C17orf41 1312 NM_024857.3 GAAGCTCTGTGGTCCGATCTGCGGTC[CG]CTTGCTTTCCCTGCCCGGTCCC
ST8SIA5 2139 NM_013305.3 AGAGGGCAGGAAGAGGAAACAACAGTTG[CG]GAGCTGGACTTGATGGAA
MGC13379 3019 NM_016499.2 GTCTGGAGAGGGGACATCCGAG[CG]AGGGCCACTTGCGGCCAGGCC
RKHD3 2723 NM_032246.3 TGTCTAATGCGGGACTGGCAGGCT[CG]GGACACTTGGATGTACCTATCAGCC
LCE3D 1799 NM_032563.1 CCTCTCTGCCATCCTCTCTC[CG]GGCTTTTGTTTCAGATCTCTCCATTTC
RTTN 4158 NM_173630.2 AGGGATAGAACCAGCGTTGGCCGCCG[CG]CACGTCGGGAGTTGTAGTTCTG
IL4I1 296 NM_152899.1 ACGATTCTTCGTGCTTGGTTGTTCCTG[CG]CAGTAGCCCACCAGTGCCCCGTA

139
GCC2 5734 NM_181453.2 GATTTTACAGACGTGGAAACCGAGGCC[CG]AGGCCCCAAGGGGTAATCGG
HBS1L 1935 NM_006620.2 GGAATCAGATTTAGCCCAGGC[CG]GTGCGGTGGCTCCTTCCTGTAATCCCA
DBF4 6139 NM_006716.3 CGGCAGTGACCGCGGGAAAACCC[CG]CTTGCTGTGCGACCCAGGGCG
STAT2 2707 NM_005419.2 CGCGCCCTCCAATGGCTCTGGT[CG]CGACTTCCCGTCCCTAGTATGAGCTCG
PTPLAD2 1086 NM_001010915.1 CTGGGCTGCAGCCAGGCGGGCAG[CG]CCAAGGGCCCCATGGGCCGCC
MGC39681 3338 NM_174939.2 GGGCCACCACGTGATCAGTC[CG]CCGACAGATCAAGCACAGCCTCTT
MPHOSPH1 4049 NM_016195.2 ACCTACTCCCAGCGTTCAGTG[CG]GTGCCCTGGCCGCCATTGTTTGAATTT
C6orf128 5893 NM_145316.2 ACCTGTGTGCCCAGCCCCTGA[CG]TTACCGGTCGGCTTCAGCGGCCTGCA
B3GALT4 1950 NM_003782.3 GAGGGGCCGTGAGTGCCGCAGT[CG]GCCAGCCATGGAGCGGAGCTTG
CCDC68 1629 NM_025214.1 AGAGTCGTCTATATACCCCTCAGT[CG]GTGTCTCCTAATGCCTACAGCTTCCATAAC
TMEM2 2732 NM_013390.1 GGCTTGCTAGGGTCGCGCTCAGCCTC[CG]CCGGCCAGACAAGCAGCCCGGCTC
NEK11 3517 NM_024800.2 CTCTGCTTTCTCCGCCTACTTGGGT[CG]GCGAACACTTCCGCCTTGGTGCCGC
IL17D 2461 NM_138284.1 AGCCCTCTCCTCCTCCTG[CG]TGGCGCAGCACAGGCCCTGAGCGC
SYNJ1 5291 NM_203446.1 GTCGGCTCGCCGAGCCAACCAGGTGG[CG]CCTGAAGAGCTGTCCATGGTGTC
NUP210 3625 NM_024923.2 TCCCAGAAGAGGGACCCCGGGCT[CG]CAAAGGGAAGCCACCTGCTGAAGC
LOC646626 2776 XM_933781.1 CACTGCCACCAAGGTCCCT[CG]GATGCAGGGCTCGCCACAGTCCTCC
NOD9 1071 NM_024618.2 GGCTAGGCCATGAATGGGTGTCAGACC[CG]AAGAGCAGGTTGGGGTGCAA
OPLAH 3435 NM_017570.1 CCTGAGGGAGAGACCCACGGGCA[CG]ACTCTGGGAAGAGCCAGAGCCG
LUC7L2 5241 NM_016019.1 GCGGGCGGAGTGATACAGCTGGA[CG]CCAGTTGGTGGAGCCCCCGCG
MGC10701 5653 XM_927995.1 GGCCGCTGCCAGGGCCGCGCAGCCACG[CG]AGTGGAATCAGAGGAGCCTCGA
C17orf28 943 NM_030630.1 TTTTTCTGACCTGTCAAACCCA[CG]TGTTCAGACAGTCCCGCAGGCC
STYK1 5968 NM_018423.1 CGGTTTCCGATGGCACCGGCCCAGT[CG]GAGGGGAAATAATGACAGG
DGKH 6012 NM_152910.3 GGAGAGGATTCGTCTGACAGCGAAG[CG]GAGCAAGAGGGACCCCAGAAACT
MMP11 1063 NM_005940.3 AGGAGAAACTGAGACCCAGAGCGGCA[CG]GGTTGGCCAGGGTCACCCAGCA
GULP1 3500 NM_016315.2 AGGCAAGTCATCGTCGGGTCACAGCGAGG[CG]ACCCAGGAGCGAACTTCCAGGGC
NID2 952 NM_007361.2 CCCTGAGGAGAAGCGAGCCTTTGTA[CG]AAGGCAGAGGGCTGACTCCTAA
ZNF211 1998 NM_006385.2 CGGTCATTTTGGCTGCCCTCC[CG]GAGGTCCGTTCTGTCTGTCAGCCGCTTT
RARRES1 453 NM_002888.2 CGGAGAAAGGGGCAGGCCGCAG[CG]GGCATTGATGGGGCTCCT
RAB17 1761 NM_022449.1 ACTCCATGTGCAGCAAGCACAC[CG]AGGCCACAGGCTGCTGGGCCCACCT
PLEKHG5 3069 NM_020631.2 ACTGGACCTGCTGCCCCCAACT[CG]GCGGCTACCGCTCTTCCTGGCAAAGC
ADAMTS12 581 NM_030955.2 AGATGCAGGGGTGCATGGTCAGGCG[CG]AGAAGGCAGCGACTGCAAAGCTGCC
FLJ35801 3996 NM_153044.1 CTCGGCCACTGTTGTGCTGTGGC[CG]CTGATGATTAAGCATGAGGAACTCAG
MDM4 5117 NM_002393.1 GGAATGGCAGAGGAAGCGTAGTTTTTC[CG]AAGAGCTGAAGGCAGCCTGTGAT
ITPR1 5088 NM_002222.1 CCGCTTCCATCCTAACGGAA[CG]AGCTCCCTCTTCGCGGACATGGGATT
LOC63928 185 NM_022097.1 CTCTCCCGTGCGGATCGCAAAATCT[CG]GAGCTGAAACAGCCCGTTGTTCG
MASTL 2416 NM_032844.1 TGTATGCTGTCCAGCGATGGATCCCACCG[CG]GGAAGCAAGAAGGAGCCTGG
SOX9 4223 NM_000346.2 TGGGAGTTGGAGAGCCGAAAG[CG]GAGCTCGAAACTGACTGGAA
BVES 3930 NM_007073.3 GGAGACTCGGCGGAGAGAGCAGAGA[CG]GAGCTCACCAAGGGGCTTGCC
C10orf58 460 NM_032333.2 AGATTGGAAGGAAGTTGGCCAGCCT[CG]GCTGCAGGACAGGTGCTTCCAGG

140
FLJ44186 4167 NM_198508.1 AGAGCTTCTCACCCACCATA[CG]TCAGTGACCTTCAAGCCCAGATCT
MYBL1 2195 XM_933454.1 TCAAGAGCCGCCGTTTGAATCTG[CG]CACGCGGCCCTGAACCTCATTGGCTGTGG
IQCA 2834 NM_024726.3 ACTTAGCCTGTGGTCCTCCAGGC[CG]TCTTCCCGCTTTCCTGCTGGCCC
HKR1 2394 NM_181786.2 ACCTCTGCACCTTGTTACCTGACTTT[CG]GCTTCAGGATCCGCAGCGTGCACC
TMEM68 5759 NM_152417.1 CGGGCTGCGTACGTCAGAGCTGCCTC[CG]AAGTGGTAAAATGTGCTGCGAG
TDRD6 5179 NM_001010870.1 CCTCTCTGGTCGGTCCTCAC[CG]CAGCCCTGTGTCAGGCCGTCACACG
MAEL 1340 NM_032858.1 TGGCTGGCCCTTTGTACCTGTAAAACG[CG]GAAACACCCGCAGCTCCTCTTTT
DHDDS 67 NM_205861.1 GACCACTGAGGCGTGAAGTACTAGGCGTG[CG]ATAACTGAAGGAGTTAGTAACTGGG
P2RY5 2902 NM_005767.3 GACAGGGGGTGCAGCCCATGGAAGG[CG]AGCCAAAGCAGGGTGGGGCATC
FLJ39599 38 NM_173803.2 GGAGGGGGCAGATGCAGGTGC[CG]GCTGCTGCAGTGCAGTAGCTGCTG
HGFAC 5091 NM_001528.2 GTCAGGTCTAGGACTAGGACCAGTGCAGGC[CG]AGGCCAGAGAGACAGCTGGGCTT
TMEM117 36 NM_032256.1 AGGTTCCTGAGTCCGTCCCT[CG]CCTGCAGCTGCCGCTCTGCAGAGGCGGG
KLB 3375 NM_175737.2 GGCCACCTCCCTCAAATTA[CG]TTGCTCTCTATGACCCATCCTCAGTCT
RAB38 1276 NM_022337.1 GGAGAGGGGAGGAGACAGGAG[CG]AGTCCCGGGACTGGCAGCTG
RAD54B 4041 NM_012415.2 CCTCCCTCGTTGGCCTGCTC[CG]GCGCCACTCCCTGCTTTGTCCC
HSD17B3 861 NM_000197.1 GCTCTCTGTGTATGCCTCCTGGGACCA[CG]CTGCTCTGGAGACCTCCAGATCTTCTTC
ZNF160 315 NM_033288.2 ACGCCATGGTGTGATGCTTGCTCCGCA[CG]ATCCACTTCCGGGTCTGTGGGCAACTGC
MDM2 2903 NM_002392.2 TGCGTACGAGCGCCCAGTGCCCTGGCC[CG]GAGAGTGGAATGATCCCCGA
MYR8 4144 NM_015011.1 AGCCTCTGATCCTTCCAATAAATAA[CG]CTGCTGATCTTCACGCCTCCTCTTCTGTC
RRM2B 5069 NM_015713.3 CGCCTACCTCTGCCAGCCA[CG]CCTCCCCTGCCTCGGGGCTCC
MAL2 403 NM_052886.1 TCACCTGGGCCCACGTGACGGGG[CG]GGGCTCGAGGAGCCCCACG
MGC72104 4067 NM_207350.1 CCTGGTGCTGCTCCAGGTCACATACT[CG]TCCTGAGCCGGCTTCAGCCTGTCC
SYCP3 2831 NM_153694.3 CCTGAAACACACCGCAATGGC[CG]AGGACCAGTTACTGGTCGTCGACAGGCG
AOAH 213 NM_001637.1 CTGGAGGGAGTCTGTGGTGTG[CG]GTTCTGCTGAGGTAAAGACTGC
FLJ25084 2173 NM_152792.1 AAAGGGTAGCACGGGAGGACATCCAGT[CG]TCTACAGAGGACATCTGTGAGTCCAAG
C10orf11 2398 NM_032024.2 AAAGCCAGGCACTTGTGAGATGGAGAC[CG]GGGCGAAACTGCAAGCAGATGC
MIA 2915 NM_006533.1 GCTGGCTGACCGGAAGCTGTGTG[CG]GACCAGGAGTGCAGCCGTAAGAATG
C10orf54 5626 NM_022153.1 CAGCGAGTCAGCTCCACTTGAT[CG]GCAGTTTAAAGCCCGTTCTACCGTC
TCP11 5878 NM_018679.2 GGATGGCCTGGAACTGCTGAGA[CG]AGGCCAGAGCATGCATGGGGCTT
APAF1 2153 NM_181861.1 GTAGCGAGTGGACGTGACTGCTCTATCC[CG]GGCAAAAGGGATAGAACCAGAGG
RFC3 5229 NM_002915.2 GGACGGCTGGACTATCACAAGGAGCAGG[CG]GCCCAGCTGCGGAACCTGGT
KLHL3 1543 NM_017415.1 TCAGGCAGTTCGTCACTAGCC[CG]AGAAATACTGGCCCCTACACCCTCC
F2RL1 2129 NM_005242.3 CCCACCGCTTTCGTGATGTC[CG]CAGTTGCCCACCTGCCTCTACAATAAAA
HIST1H1A 3648 NM_005325.2 GCCTATTTATAGGGTGGGACTGCGC[CG]TGATTGGTGCCCGTCAGTGCCC
PCNX 2871 NM_014982.1 GACTTTTCAACAGTGTCATCAGC[CG]TACCTAACTCTTCCAGGCCTTCAGT
FLJ30834 1759 NM_152399.1 GATTCCTCCCTCCAAATGGA[CG]ACTGAATCTTCTCTCCCCCACGC
CHODL 2254 NM_024944.2 CTTCTGCTTCGCCTCTAGGACATACA[CG]GGACCCCCTAACTTCAGTCCC
F2R 1646 NM_001992.2 AGTGCCCGGCGTATGAAACGCCTAACTT[CG]CGAAATAAAGAGAGACGTATAAAAGTT
KARCA1 5449 NM_152366.3 GAACCCAGGTCTCCTGTCTCT[CG]GGCCAGTGGTCAGTCCACTTTCACTT

141
OXR1 2316 NM_181354.3 CCAGCCCCGCGGCAGCATGGACTACCTGA[CG]ACGTTCACCGAGAAGAGTGGGC
BTD 3582 NM_000060.2 ACCAGACACCTGCTCCTCGCTG[CG]CTCTGCGAAGTTACTGTCCGGCATCTTCC
WDR51B 4198 NM_172240.1 TGCAGGATATTGATATAGTTGCTGGATGTG[CG]TGATGAATGAATGAGTGAATG
SMAD7 4276 NM_005904.2 GGGGGCCGAGTGGACTTCACCC[CG]CATGAGACGTCTGGCAAAATAAGAAG
SNAPC5 2728 NM_006049.1 CATAGCCAACCTCCGGGCTGCTGT[CG]GCCCGGCACTCGGTGATGACGCCAT
HSPA1A 1954 NM_005345.4 GAGACAGTATCTCCATTGTAACGTGGC[CG]GGCGGTGTCAACACAAACGCCCC
ZMYM5 1645 NM_014242.1 GTCAGGTGCGGGCCACACC[CG]CGGCCCTGCAGTTCCACTCCC
SLC1A7 3493 NM_006671.3 GGTGGGTGGGTGCATGTGCTG[CG]GGCCAGGCCTGTGCTGGCT
LAMA1 1265 NM_005559.2 CCTGCCAGGAGCTGGGCGAGAGG[CG]ACCCCTCGGGAAGCCACCCAGGC
ITPK1 971 NM_014216.3 CTCTGATGTTCCCAGCCGGGC[CG]TAACCCCTGGGCGCGCTTGGACCC
GJB7 4157 NM_198568.1 GAGGCAATGCCTCGCCCTGCTT[CG]GCTCTCACATGGTGCGCGCACCCAC
PLXNC1 3125 NM_005761.1 CACCTACACAGTAACCCAAATTA[CG]AGACCTCCCTCCTCCCTATCT
ADPN 215 NM_025225.2 GAAAAATGCTTTCTCTCGAGTCGCTG[CG]GGGAGCTCCCAGGCTGGACCCC
SLC37A3 859 NM_032295.2 GACCTGGCCAGTAATGTTAGCTGCAAAAGA[CG]AGAGGTAGAGAGAAGAAATGATATG
PRRX1 5275 NM_022716.2 TCTTCTGTTTGCCTAACTCCCC[CG]CCCTGCTGGCCTCCGCTTTCCTCTC
HERC2 3283 NM_004667.3 TCCCGCTTATCTTCCTACTTGGAG[CG]CCCTGGCTGCGGCCAAGGCCAACAG
MYO1B 1787 NM_012223.2 AATTGAGACTTACTCCCACTGTTTGC[CG]GAATGTGACCCCAGGCTGGCTTCGAGTT
LOC152078 542 XM_496664.2 CCAGGGTTCTGACAGTGGAGCCAGGA[CG]TCCGGGAGCTGACAATCTAAACG
HBXAP 2017 NM_016578.3 CGCAGATCCCGAAGCAGCGCTGGGAG[CG]TAAGTGCGGGCAGAGCACTGCGCC
FOXA2 2037 NM_021784.3 CAAGGTTACTTTTCAGTCACAAC[CG]AGGTGCCCACAGCATTTCGTAACTAAAA
HECTD2 4271 NM_173497.1 TGCAGGGCTCGACTTGTCTCCC[CG]ACTGCCCGTCCTTAGTCCAGGTTCT
CYP3A5 1596 NM_000777.2 GCTGACAGCCAGGAGAAGCCAGGTTTCCAC[CG]CCAAATTTGGGATGAGGTCCATC
CD2BP2 3495 NM_006110.1 GGTCAGGATGGAGGGGCAAAGTC[CG]AGCAGGGTCAGTGGGTTGCT
L3MBTL2 1987 NM_031488.4 AACGACTCACCCTGCACACATG[CG]AACTACAATTCCCATAACCGCCC
PGAM2 4042 NM_000290.2 ATCCTTGATGGCCTTGGCTCCC[CG]CTTGGCCTCCTCGGTCCCCTTT
RAB11FIP1 2895 NM_025151.3 CCTCATTTCCAGGGTCACAT[CG]CCAGTCGTGGCCTTGCGCGGATTACCTAAC
EPHA4 5739 NM_004438.3 TGGAACCTGTGACAGCGTCGCAAATCC[CG]AAGAGACACGAAAATAGGGCGAA
ZNF502 2016 NM_033210.3 GCTGGAGTTACAGGCTGGGCTTGG[CG]GGAAACAAAGCTGGAGTTACAGG
SLC30A5 3908 NM_022902.2 TGTAGGGACAGGTAAGTGCACAGGGAG[CG]CCACCCGGAGAGGCTGATAGGA
ABCA6 3704 NM_080284.2 TCAACTACAGGGATAAGGGGGAAAA[CG]GTAAACAAGGAAAATGGAACTAGTT
GALR1 1078 NM_001480.2 GCTCGCGCACCGTGACTTCTAAGGGG[CG]CGGATTTCAGCCGAGCTGTTTT
KCR1 4229 NM_001013620.1 CCCGTCTGGCTAGTCCTGTCTAGCG[CG]CCCATTTCGAGCCCAAGTTTCC
BRMS1L 3722 NM_032352.3 GATGAGATGGAGGTGGACTACGC[CG]AAAATGAGGGGAGCAGCTCCG
SMC4L1 6078 NM_001002800.1 CCCGGAGCCGAAACACCGGTAGGAG[CG]GGGAGGTGGGTACTACACAACC
ESAM 4150 NM_138961.1 AACCGCAGCAAGTTGGTCACCAGGGGCCC[CG]GGAGGGAAATCATGGCCCT
TIGD7 3099 NM_033208.2 CTCTAGGCCCTCAAATACTCTTTT[CG]GGTCCTCCTGGTGCTCCCCAAAGC
DUXA 2991 NM_001012729.1 GGAACTTACTGTGTGAATAGGTGTCTT[CG]GCCATGCTGGAAGAGAGTCCTG
SYNC1 5660 NM_030786.1 CACAAACTGTATCCGATCTGGCTC[CG]TGGTTTCCTCCACACACACTGTCTC
LOC51334 2149 NM_016644.1 GGGAGATATCTCGAAGGGCAACGT[CG]AGGGGACTGCAAGCGTCAACCC

142
FLJ90650 5851 NM_173800.3 GGAGCAGGTGTGTTGCTGGTAGCTCAT[CG]CTGGCTTGGAGATAGAGGTG
NIPA1 3923 NM_144599.3 CGCACGATGCCCTTCTTCTGTAGCA[CG]AACGTGGACCCGTTCACCAGGCTC
MGC15523 3105 NM_138570.1 CACCTGAGGGTCTCGCAGCTGTC[CG]GTTCGCCAAGCTGGTCCAGCCGA
TUBD1 5632 NM_016261.2 GCGCTTCTGTCCGGTTCAAACTT[CG]GACCAACCTACTCACCATGCGCATGC
PCDHB2 4872 NM_018936.2 GAGATACGGGGAGATAGAGTTAGCGACAA[CG]TGAGCCAGAGCTGGAGCACGTTTG
CYLD 1953 NM_015247.1 CTCAGGAGCGCAGCTCGGCCTA[CG]ATTGGCTAGCGCGGCGGCTGCCCCC
CPNE8 5508 NM_153634.2 ACCTCTGCACACCCACACT[CG]CCTCCTGGGCCGCGACAGCTTCCT
ZCCHC2 5169 NM_017742.3 AGCAAGCTCCAATACCTCAGGA[CG]GACTTACCGTGGCACCTCACAGAGCTC
SGPL1 3958 NM_003901.2 AGTTGGTGACCGTCGGGATACCACAGC[CG]CCCCAGGACGGCCTGGTTGA
INA 1330 NM_032727.2 CCGGCACCATGAGCTTCGGCT[CG]GAGCACTACCTGTGCTCCTCCTCCTC
C20orf133 1949 NM_080676.4 GCCGTGGCTAGAACACGGAGAGCGG[CG]GGCAGTGCAGCCAATGGGAGG
FLJ39660 992 NM_173646.1 AGAGTTGTTAAAGGAGGCCTCATTAGATG[CG]CTCTCTGACAGGGAAGTTGGCA
PSME3 5237 NM_005789.2 GGACGGCACAGAGGGAGGGAG[CG]AGCGAGCAGTGAGTAAGCCAGCAAGGG
C10orf59 4077 NM_001031709.1 GTCCTCTTTTCCCAGGTTTTGG[CG]TTTAGACAACCCACCTGAGTCCTC
AQP5 5342 NM_001651.1 GAAAAGGAGGAGCTGGACCAAAAGCC[CG]AAGAGAAGAAAAGGGGAAG
ZNF136 4290 NM_003437.2 CAGCTGCAGACGTTCAACCTTCT[CG]CGGGATTTTCATTTCTCGCGTCTGCCG
GTF2I 331 NM_032999.1 CCCCAGTGATCGGATCAAGG[CG]CTGAGCGAGGCCCTGCCTGCGGGGCG
SLC6A4 4004 NM_001045.2 CGGCACACAGGGGTCTGCTCGTGC[CG]CTTTCTCTTGACCTCGGACACCTCC
NMI 3828 NM_004688.1 GATTTTTAAAAAGGGGTGGTTTTG[CG]GAGGAAAGCAGAAGTATACCTGAAGT
FBLN1 1893 NM_001996.2 CTGAGGGCAGAGTCGGGTCCCATCC[CG]GGACACGCCTGGGGTTAGCCA
ZNF671 724 NM_024833.1 GGCCAAGTTGTTTGGGAAAAGTAACC[CG]AGTTTCAAAGGGCTGACAGGACT
SS18L1 4283 NM_015558.3 GGCCGCCCAGCGCAGCCGGAGTATCCACCT[CG]ATGACCACGGGCTGAGCCCCG
KIAA1407 1946 NM_020817.1 AGGGGTCTGAAGACTGAAAGAGT[CG]AATGGTTTGTTGGCAGGTAAGT
RASD1 2797 NM_016084.3 CCCCTGTCCCTCTGCGACTT[CG]GGCAAGGACCCCCATTCCTGC
RPESP 1887 NM_153225.2 AGAGCACTCGATGGGCACCAAA[CG]TGTCTCAGCAGCACTCTGCGCGGGCC
ZNF44 636 NM_016264.2 ATTTCCCGGCTGTGCGGTGTCC[CG]GGTCCTCCCAACTCCCGTAGTC
EGLN3 2158 NM_022073.2 TCGGGGACAAGGGAAAGTTTCT[CG]CAACTCTCGGGAGAAGGGAT
C16orf5 1015 NM_013399.1 GACTGCTGGCACCCAAGGGCCA[CG]GCTGGGCCCTCTGCCTCCCCTC
ULK4 5588 XM_934158.1 CCATGGCAGCACGCAGAACGCTGGAAAAA[CG]CAAAGCGCTGATTGGTTAAGAGTCT
GPR30 1895 NM_001505.1 CCACGCAGGTCTCTGAACCA[CG]CCTCAGGCTGCAGCAGCCGCATTACTC
WDR62 1628 NM_173636.3 AATCTCTTACGGCTCCACCCTA[CG]CCTACATCCGGGCAACCGTTGGGGCG
SYT17 5365 NM_016524.2 GCGCTGGGGTCGCTGCAGTCCC[CG]CAGCTGCCCCGGGCTGCTTGCCCAG
OCLN 5961 XM_936894.1 AAACAGTCCCCTCTGGACCT[CG]TTCGGCCTCTCTCCATCAGACAC
PIK3AP1 5097 NM_152309.2 GGGCACCTGGCCCTGGGTGCTCGG[CG]TTGCCCTTGAGTGCCCTCCTGTGATCTTT
ALKBH6 2430 NM_032878.2 GGGGGCGGCAGCCGTGACAGCCG[CG]GGAAGACATGAGAGGCTGCTAG
POLB 124 NM_002690.1 TCGGCATGGTTCACGCCGGGCTC[CG]GCAGCGCCCTAGTACGTAAGGGGC
FAS 230 NM_000043.3 CTGAAGTGAGCATGCCAGCCACTGCAGGAA[CG]CCCCGGGACAGGAATGCCCATTT
KCTD4 1650 NM_198404.1 CCAGCCTGGTGATGGAATGGAAA[CG]CTGGCAGCATCGCCTGCGCTGTCAG
LECT1 3049 NM_007015.2 TGCACCGGAGGATGTCTTAGAATGTCAG[CG]GGCTCTGCTGTGACAACTGG

143
RNF113B 1883 NM_178861.3 GGGGCTGAGCCACTGTGTCGCCCT[CG]TCCCCGCTGCTGCTGCTCTCTCCGTGCT
CSTL1 2833 NM_138283.1 GGGCGGCAGGTGAGCAAGGAGAA[CG]TGTCTGTAAAGGAAGCACAGGGA
C12orf26 1124 NM_032230.1 TGCTCCGTCTTCCTATCTAGAGCTCTG[CG]AAGCTCACAGCTTTAGCGGGCTCAGGA
COL1A2 5643 NM_000089.3 CAAAGCCTATCCTCCCTGTAGC[CG]GGTGCCAAGCAGCCTCGAGCCTGCTC
XPO6 6002 NM_015171.1 CGCAGACTTGACCAGTCACGGCTA[CG]AACAACTCCTTCCTCCCTACCA
ABCC5 3887 NM_005688.2 GCTCATGGTTCGACCCTGCAGTCTG[CG]CAGATACCGCCTTTCTCACTTTAACAC
CDC23 4119 NM_004661.2 TTATGGACAGGACAGGCGCCACTGCCGC[CG]TCACAGCCACCGGGACCATGGAGG
GPR135 2019 NM_022571.4 TCGGGTTTCCGAGAGTGCCAGGT[CG]ACCTCCTGAGGGACCAATGTCC
KCTD9 4148 NM_017634.2 GGGAAGAGACGCTGAAGGCTAGTAGA[CG]GGAAGGGGCATCAGCCAATCAGA
PRKCDBP 2354 NM_145040.2 TCTCCCTCATGATCCCTGAC[CG]CTCTGCTCCGTCTGCCTGCAACTGCTGGCC
WDR21C 4149 NM_152418.2 TCGCGGTCTTTTGCTCTCCATTT[CG]TTCGGCGGATGTTCTCCCTCCTGAG
YIPF5 5572 NM_030799.6 GTTAGCAGGTTGGGCACCGGTGGG[CG]GGAGGAGGAGACACGAGTATG
AQP7 4072 NM_001170.1 CAGCGCATCTTGATCTTGTTCCTC[CG]TGACTGTCCCTGGCTCAGCTTCCACC
TSPAN14 269 NM_030927.1 GGCCCCGGGCCAGGCCCGGCCTG[CG]CCGCGCACCCACTGGGAGGGC
DYRK3 2044 NM_003582.2 GCGGGCAGCCCTTCTGAGATCG[CG]GGCTAACTGCTACTTTCACCCCTCCTT
PRKAB2 1836 NM_005399.3 CCCAAATGACACTCGGAGGC[CG]CCTCCCTGGGCTCCGGTGCTCGGTGCC
KIAA1914 4885 NM_032550.2 AACCCAATGCCTGGAGGAGGAGAC[CG]AGGTCCAAGCTAGGAGGTTGA
SYNE1 2065 NM_015293.1 TGGCTCCTTTTTCATCAACTTC[CG]AAAGATCCTAAATCGTTTTGGCTGCCAAG
SLC26A10 4180 NM_133489.2 GGCGCCTGCTGCTGGCTCGGCTGCC[CG]CGCTGCACTGGCTGCCCCATTACCGCTGG
TMEM16A 2402 NM_018043.4 GGCGGTCCCAGCGCACAGGCGGCCA[CG]ATGAGGGTCAACGAGAAGTACTCG
PLEKHG6 1333 NM_018173.1 GGCTGGGTGACCCTGGTGTAGC[CG]GGAGTGGGCTTATTTGCAGG
SLC30A6 5468 NM_017964.2 CTTGCCTTGCCCTTAACCTCAA[CG]CTTCAGGTCCCGACCAATCTCT
ZNF547 5988 NM_173631.2 ACTCTGTTTACCAGCTCCCCTGA[CG]GTGCCACTGAGCCTCTATCCGCCAT
SLIT3 1087 NM_003062.1 GAACCAGGGAAGGAAAGGGGCT[CG]GCCAGCAGGGCCCCTGGAAAG
SRPRB 2404 NM_021203.2 TTGTCAGTAGTGGTGGCGGTTCTTG[CG]GTGCTGCTGACGCTAGGTAAAA
CDH1 1588 NM_004360.2 CGGGGCTCACCTGGCTGCAGCCA[CG]CACCCCCTCTCAGTGGCGTCGG
EPHX2 5788 NM_001979.4 GGCCGCACGGAGGAGGCCCTGG[CG]CTGCCCAGGTAAGGGGGCCCA
EID3 3588 NM_001008394.1 TTTTCACGGTCCTTGGCCTTAC[CG]ACGGTTTACAGTCCAGCCAGATTTAG
PARK2 594 NM_004562.1 CAGACCTCCTGCTCACATC[CG]TAAAGCCCACTGATTCTTTTACTACACTTT
PXN 6123 NM_002859.1 TCAAAGTCACTTGCCTGACCCTG[CG]GATGACAAATCCGTCCACAGTCAGC
ATP13A1 2818 NM_020410.1 AGGCTATACGCTGTGATGGCCCCAGGG[CG]GGCACTCTGCAGATATCATCTCCGCTTC
FZD8 4000 NM_031866.1 AGTTGTAGCCGATGCCCTTACACAG[CG]GCACGGTGATCTCTTGGCATGCCAGCTCC
AP1M2 3126 NM_005498.3 CTTGCATTCATTAATCCATCCA[CG]CATCCACTCATTTAGCCATTCATTAA
C8orf53 30 NM_032334.1 ACTGGGTTCCAGACACTAACAAACTA[CG]TGCCCTTCGTGAACGTGCTTAATTTCTTT
LOC441161 3980 XM_496818.1 GCGGCACCATTGGACACTTCCTG[CG]CTGCTTCAATCGCCGGGATTGCCTCTT
DSCR6 3280 NM_018962.1 CGGGTTCCTGGGTCACTTCC[CG]CTGTCTCCAGCCCGAGCTCGTGGCC
PTGIS 3075 NM_000961.3 ACCCTTGGGCTGCAGCCCGGG[CG]GGAGCCGCCCCCTTTGTCTGGCG
CCDC17 1844 NM_152500.1 CTGATTCCTCATTTTTCAGCTGTAGA[CG]AAGATAATCAGCACAGCCCAAGAA
PVRL3 1702 NM_015480.1 AAATCTCTGCTGTGGGAGAAACCC[CG]TTATCAAAGTGGATGAAAAGAATATTT

144
OSTM1 3811 NM_014028.3 GCTCGCCAGCCGGTGACCACGAGCACCCAC[CG]CTTTGGACAATTGCATCTCGGG
ATP9B 3222 NM_198531.3 CCCAGCTTTAGCCACTCGTGA[CG]TCATTGCCCGGACTCCACTGCCTC
GPR162 1190 NM_014449.1 GTCTCCATGGCAGTGCTGGGCGCAGC[CG]GAGAGAGGTAAGACGACCCCTG
ST6GALNAC5 5698 NM_030965.1 CTTTAGGACCCAGCAGGCGGCGGCAGG[CG]GCAGTTGTGTAGATCGCTGAGAGA
RASGRF2 6103 NM_006909.1 CCTTTAAATCGGTCTCCAAGC[CG]ATTACAGCTGAGCTCCCACGTGACGTTT
CD109 1344 NM_133493.1 CCTGGATTTGCGATGTTTGCCACAGCAG[CG]AGAAGCGCCATTGTAATGGGG
BMP1 3947 NM_001199.1 GGGAGACAGGAAGGAGGGAGG[CG]AGCAGAGGGAAGGGGAAG
MARVELD2 1969 NM_144724.1 CCCAGTGTGTGGTCATTGCCGCGA[CG]TGCCGGCTGGTGGCACCGAGCAGCCT
SORL1 4016 NM_003105.3 GCAGGGAGAACAAGGAGGTGTGCC[CG]CCAGGGAAGGGACGCACCCCCAC
C10orf110 2166 NM_018470.1 TTCAGTCCGGGGCTTGGTTGAA[CG]GACTCACCAGGAAACGTGACTTT
C11orf11 3881 NM_006133.1 TCCCGGCCGCCCACGGGACCCCAGC[CG]AGCCTGAGCCAGGCGCCCACCGCC
LOC400890 5260 XM_379036.3 CCTGATGACATGGTTAACGAGGAAGA[CG]ATGTGTTGACCGGCTGCCGT
TMEM30B 944 NM_001017970.1 TTCCTCTCAGTCCAGGTCAT[CG]GACTCCACCTCCTCTCCTAGGTGAG
AGBL2 433 NM_024783.2 GGCCCGTCCCAAGCAGCACGGATGGCTG[CG]GCAGAGAAGCTCCAGCGAGGCAGG
TXNDC10 2755 NM_019022.3 CCCATTACCTGTGGCGCAGAGC[CG]CAGGGCCGTCCAACTCTTCCAC
C3orf14 1267 NM_020685.3 TGACTCTGAGAAGGTGCGGATCTT[CG]ATTCTAAGGGGAGAATGTGAT
CDA08 3305 NM_030790.2 AGTGAGCTGGAAGGTCTTGGAG[CG]AAGAGCTCGGACCAAGCGCTCAGG
PPP1R14A 781 NM_033256.1 GGTCGAGCGGTCACTTGTTCCTT[CG]TTCATTCATTCACTCATCCATCC
ZNFN1A4 2321 NM_022465.2 GCCTCAGCCCTGCTTCCTGTGGA[CG]TCAGGCAGTGATGCTCTTGCCCTCAGGC
TLE3 2708 NM_005078.1 GTTCTCGCAGCGAAATCCCAGAGTCGGG[CG]CCCGCCCCAAGTGGAGACAAAGAGCC
PRODH 1549 NM_016335.2 CTGCATGGTGGGGACCCTCTGC[CG]GCAGGGCTGAGGCCAAGGCC
C6orf155 3931 NM_024882.1 GATGTCGGCGTACAGAGGGCTGTTC[CG]CCCAATCAGGTGTCGGAAAGCCCAG
KRTAP8-1 4189 NM_175857.3 GGAAGACAGCCCCGGGGAAGTTGT[CG]CAGAGCATGGTGTCGGGAGTG
GLOXD1 3160 NM_032756.2 GATGAGTGGGAGCCCAGTGCCTGG[CG]CCGAGTGAAGGCAGCCATTGTGAG
LRRTM2 745 NM_015564.1 ACCATGCTTTGTAACAGCATCGGGGT[CG]TTGCAGGACCCCCTGATTACAATAAA
ZNF585A 1105 NM_199126.1 CACTAACTCCACAGGCAACCT[CG]ACACCCCCTATTACTGGCTCCACA
LOC387921 1753 NM_001012754.2 CGCCCTGGTCTCTGTTCCCTTT[CG]TACTCAAAGCTCGTGCATCCAGGGAG
TRPA1 4251 NM_007332.1 TACAGACCTGTGTTTCCCACCA[CG]TGCACCTTCTTCTGGCGGCCTCTTTGA
PLEKHG4 4183 NM_015432.2 CCTGGGCCATGCAACCTGTAGCTCT[CG]GCCTCTTCTGTCTCCTTTCAGGCTGAGT
WIG1 1024 NM_152240.1 GAGCAGGCCCGGCAGCGGTGGCAG[CG]GTAGCAGTGGCGGCTCCCGCATC
AGMAT 2913 NM_024758.3 CAGGCTGGGGGTGCCCACTGGC[CG]GCACTGTGCCAGGGGTGTCT
MGC39584 2857 XR_000559.1 AGCATCTCCTGGACAGTCAGC[CG]AGTGTTTCCATGATACCAGCCATACCTGA
CD1D 1780 NM_001766.2 GTCAAAAGGTTAGGGTGATGGTGA[CG]GTGGAAATATAGAAAAAGGAATT
C21orf63 3933 NM_058187.3 AAAGCCCAATTATTAGCGCTCGG[CG]GCTGTTTGCGCCGGTGCAGTGTCAGATCC
CLSPN 5858 NM_022111.2 CCACCTAACCTCTCGGTGCC[CG]GCCTTCTAAGCCCCCGTGGGGGG
LOC198437 1823 NM_001007125.1 GTGCCCCTATGTCTGCGGTCCC[CG]ACAGTCAGGGTCTCCCACCAG
CEP27 2054 NM_018097.1 GGAAGGTGCGTCCGAGCCATGGC[CG]CTGCCAACCCGTGGGACCCG
HINT3 5082 NM_138571.3 GCTCCATTATGTCAAACGCTCC[CG]CGCCTCTGTGATGTCACCACGACGCGCT
FLJ43276 162 NM_207382.1 CCAACTGGTGTGTGTGTATTTAGGGG[CG]GGGGGAGGTACAAAACCACC

145
NEXN 1790 NM_144573.1 AGAGAACGGAGGAGGAACGAAAA[CG]CAGAATTGAGCAGGATATGTTAGAAAA
ACTL8 2122 NM_030812.1 TTGCTGGTTGTCAAATTATTGCCTCTC[CG]CTCCACATTCACCCTTCTTGCC
PECAM1 2802 NM_000442.2 AGCTTGGAATGCAGCGGAACTGAGG[CG]AGAGAATAGCAGAGGAAGTAGGGG
P53AIP1 4303 NM_022112.1 CTTCCCACACTCTGCTTCC[CG]CACTCTGTCCTTCCTCAAGGCTGGCAC
DNHD3 4974 NM_020877.2 TGGCCACACAGGAGCAGGGGAATGCCC[CG]GCTGTCAGTGAGCCAGAGCTGCAGG
COMP 2259 NM_000095.2 CCTGGATCCCGGGCCTCTCA[CG]GGTCCTACAGTCCGTTGTGGGGCCGTGG
ZNF297B 6052 NM_014007.2 AGCTGAGGCTACAACAGGCCTGCGCCGG[CG]GCAGAGAGGATATCTTGGGCG
IGF2BP1 885 NM_006546.3 CCTTTCTTTTTAAATCACCAGCT[CG]TGCGACCCTCTCCTGAAGACCC
FAM50B 1262 NM_012135.1 TGCGCAGGTAATGTTCACGAGACGCCACAG[CG]GGGTAGCATCAGAGGCGGGA
NPTX1 3136 NM_002522.2 GGCTGGGTGCCCAAGGACCCAGGT[CG]TCAACACCCGAGTGCCCGGTGGT
CCDC74B 3392 NM_207310.1 TCTGCCTGAGCTGCGGGCTCTG[CG]GCCTCAAGGACTGGACGCCCACAG
HEYL 3697 NM_014571.2 TCGGCTCCTTGGGTCGCTTCATGG[CG]AACGCAGGCTGCCTGGTCTCAGCCC
ZNF665 2331 NM_024733.2 GGTGAACACTGGGAGGCTCCTGCAG[CG]TGGTGCACCCAGGGAGGGCAC
P2RY6 1775 NM_004154.3 AACTGAGGCCAGGGAAAGGTAAAGT[CG]TGAAGGATTCTGGACTGG
ART5 3346 NM_053017.2 AATTCCCTTTCTCAAGGCCTG[CG]GGGTCTTTCTGCGGGACCCTCTTTGGCT
PVRL1 2204 NM_203285.1 GCCGGCTCAGAGGCTCGGCAGATGCC[CG]CCGCAAGTTGCACGAGTCATGCCCCT
AIM1 1093 NM_001624.1 TTGGCTGGTGGTTCTGTAATGTA[CG]TCTAAGGGGAAAAACACCAGATTCT
FLJ30851 1272 NM_198553.1 AGTCAGAAAAGTGTTGCAAATGGGACTC[CG]AGAGGCCAGGCTGAAGCTGCCACACT
PRDM1 1145 NM_001198.2 TCTTAAGCAGGGAGGGGAAGCCAGA[CG]GTTAACACAGACAAAGTGCTGCCGTGA
MSX2P 747 NR_002307.1 GCAGGGAAGGCATGGCTTCTGTTTT[CG]TCCAATGAGAAGGGGCCAGCG
PLCD4 2432 NM_032726.2 CCCTTCTTACTGCTTCCCTC[CG]GCTATAACTTGCCAGTCACAGCAGCCA
C14orf108 5741 NM_018229.2 GCGAAAGAACCGAAAAAAGGCTCGA[CG]CTACCGTGTATGAGGAACTTTGATC
LMBRD2 1740 NM_001007527.1 GGAAAATCCGTCTACAGTCCAG[CG]GCTGACATTTCCCAGTCAGCCGTAG
MYO5C 2277 NM_018728.1 TGGTCCCTCCAAGCTTGGCC[CG]GCTAGTCGGCGCTGCCATTGGCCGGGGC
OAS3 5350 NM_006187.2 GGTTCGTGGCCAGAAGGCTGCAGCCG[CG]GAAGGAGTTCGTAGAGAAGGC
NPY 111 NM_000905.2 CTATCTCTGGCAGGACTAGACGGGG[CG]TGAAGGAAAGAAGGAAAGAAG
MMP19 1653 NM_002429.4 CAGTTCATGGTCCCACCAGA[CG]AGAGCTCCAGAGGCTGTCCGTGCCTCTG
LPIN2 2117 NM_014646.2 TGGAGAAAATGGTGATCCGCTGG[CG]TTAGAAGTGGACAGAGAGGCTCTC
BMP2 3909 NM_001200.1 AATAACTTGCGCACCCCACTTTG[CG]CCGGTGCCTTTGCCCCAGCGGAGC
ZNF365 2717 NM_199451.1 CGGCCCGGCTCAGTCTGATTTA[CG]GCTCTGCTGAAAACCGCTTCGCTCCC
CALML5 2168 NM_017422.3 CATGCCTGCGTCTCCTGCACCT[CG]CGGAGCCTCCGAGCTGCTGCCCAC
KCNJ8 261 NM_004982.2 GGGCTACTTCATGATAACTGGGCTACTT[CG]GACTGAATAAAAGCAGAGAGGTCAGA
AKAP8L 6038 NM_014371.2 GGGCAGGGCTGGGATGCCAACTC[CG]CCACCGAGGTGCTGGGTAGG
FAM112B 3606 NM_144594.1 CCGGGGTGCCTTTCCTTACCT[CG]GTGGACACACACCTTCCTCACAGT
KIAA0240 1689 NM_015349.1 AGACTGTCCCTTCTGCCTTCGGG[CG]TGTCCCTCTTCTGGGCATCTTTTCAG
SERPINB9 925 NM_004155.3 GCGAAGGTCGGGTGACAGCCAAGCTC[CG]TGTTCCAGTGGGAAGGTCCCAT
SOCS4 5973 NM_080867.2 CCGCGTGGAAATTAGCCGGTTGCC[CG]GGCAAATCAGGGAGGAAGG
HSPB8 5188 NM_014365.2 GGTCCCCAGGGGAAAGGCAGGATA[CG]ACACGCTCTAGGGAAGGTATTTCC
CCNF 401 NM_001761.1 AGGGCACGGCCTCGTCTTAGAAG[CG]CCACGTCGAGGCTGTCCCAGGCTGGA

146
PLEK2 4028 NM_016445.1 CAGTCTCTCTGCTCAGCGTCCTT[CG]CCAGGTGCTTCCCGGGCACTTAGCGC
CASC5 4166 NM_170589.2 CGCAAAATTTGTCGAGGAGGTTTGC[CG]CGGCAGGTAAAGAGAATGACTCTT
EPSTI1 5378 NM_001002264.1 CCCGGAGTTCACCACTCTATTG[CG]GGTGTTCATGGTTCACAGCCCGCGGG
MYBPH 2192 NM_004997.2 CGCAGATGGGTGAGATGGGACAT[CG]AGCAGGCCGCGTGCCAGGTGTCAG
TGFBI 1286 NM_000358.1 TGTAGCCTCAAGATCAGTGAGGGAATCTT[CG]GGCCCCCAGCATGCAGGACCGAAG
FALZ 2360 NM_004459.5 CCGGCTTTGGGCTCCAGCCAG[CG]GTCCGCGGAGACTTTGGTCTCCGAA
5330 CATTTGAGTGTCGCCTGAACCC[CG]AGGTCATCTGCACAGCACTATTCCTCTTC
FLJ20273 4074 NM_019027.1 CAGTGAGCTGACCCGCCTCCTAA[CG]CCTCATCCGGGCCTCCCTTTT
HRB2 1182 NM_007043.5 CCGTAGTTTCCTCGTGGCCTCA[CG]GCCTAACCTGGACCATCGGACAGCG
LMO1 2450 NM_002315.1 CCTAGCTCGGTGAGCGTCTTTGCTC[CG]ATCCCAGGGTCGTGGTCTTCAATGATT
B3GNTL1 1392 NM_001009905.1 GGGCTGCTCAGGGCGGAGACCC[CG]TAGGTGAGCCCGAGAGGCGG
CCDC8 3465 NM_032040.1 GCTGGGCCCATTGCTTCCCAG[CG]AAGCGGCAGTGGCCCACGTCAGCA
TNFRSF6B 2136 NM_003823.2 GCTGACTCCTGAACCGTGTGCAGCCTA[CG]ACTTGGTGGGTCCCTCAGTGGCTTCACG
BBS5 1984 NM_152384.2 GGCCCGTTGCCTTGGAGCCAGAGAGA[CG]CAGCTAGGCCTGCACGGCTGTGG
HSPC105 940 NM_145168.1 CCCACGTTCTCTGGCTGTGCGTTC[CG]CCGTGGCGGGAACCCTTTTAGGGTCAC
ABCC6 3453 NM_001171.2 GATGAGAGAACTGAAAGGTGTGCACA[CG]TTAGTAACAAGGAGGCCTGGTGA
LIPG 171 NM_006033.2 GGCCGAGAGAAGGGTCTTACCGGC[CG]GGATTGCTGGAAACACCAAGAG
ABCA5 4947 NM_018672.2 CAGTGGTAAACCTGCCGCCTCTTAG[CG]GGTGACCTTGGCCCACGGCCCTCT
DPYSL2 2964 NM_001386.4 CTAAATTTGCATATCCCAGGATCG[CG]GCCAATCGCTGCTCGTCTCTCTCGAA
C18orf2 1942 NM_031416.1 CTCTGGCATAAACGGGTTAAGGCCTT[CG]ACTGACTGGATAAGGCCACCCATATT
NIN 1795 NM_016350.3 GTCTTCGCGCAGAGGAAGGGCCCC[CG]CCTTCAGCAAGCGGGACTTTAAGG
NPAL3 2584 NM_020448.2 GGGTAGGGGAACAGCAGGAGCAAAGCC[CG]GAAGGTGGCTATGAGGATAAG
RBM24 1685 NM_153020.1 CACCATGGCTGACCGGGCTGCTGC[CG]AAAGGGCCTGCAAGGATCCCAA
GRSF1 799 NM_002092.2 GCAGCTGCTCCAGCAGCGATGGTGGAA[CG]GAAGTGGAATCCAGGGCCG
C9orf157 4010 NM_001012415.1 GTCGCCTCGGTTCCCACTTATG[CG]GTGGTCTCGGTGCCCTTGGGCACTTTGGA
SGOL1 4018 NM_138484.1 TCCTCACATTTCAAGGCTCTT[CG]AAGCTCTCCAGCCACGGCTAGCC
LOC388389 4136 NM_213607.1 GAGGGTGAGAGCTGAGGATGAA[CG]AATCTGATCAGGCGCCTCGGG
MAP3K5 4115 NM_005923.3 GACGGAGCTTCCTTTTCTTGGC[CG]GCTGACAAGTCGGCTCGCAAACCTGCG
LOC389748 1563 XM_372108.3 TCTACACTGGCTGGCTGCAGTCTCCAT[CG]CTGCCACCAACCACAAACATGGCT
ASCC3 3468 NM_006828.2 GGGGTCGCGCCCAGTCACAGGGAAC[CG]CGTGTGAGGACCATCAGTCAGACAGAC
NMT2 6034 NM_004808.1 CCCTACCCTTTGGCGTGCTC[CG]TCTCCTCCTCATTGTCCCCGTC
CSPG2 2788 NM_004385.2 AGTGGGAGGGCAGTGGTTTCCG[CG]AGCAGAGCGATGTTACTGAGTGAGTC
RBP4 4219 NM_006744.3 TGGCAGGAGGCTCGAGTCAACCTGG[CG]GGAAGACCGTGGCCTCACAGAG
SHC4 2436 NM_203349.2 CTTCTGTTCTGCACACAGGAACTTT[CG]AACCTGCTCCCTTCGGCTCTCACA
NAV2 3145 NM_182964.4 TTCCTTGGCTGCTCGCTCTTTCTCT[CG]CCGGCTCAGACCCGTAGCCTCC
SERPINB1 4206 NM_030666.2 GGTGACTGCGTAGGAGTCCGAGCTCC[CG]AGGTCGCCTAAGTGCAAGCAGAAGTG
LOC390205 696 XM_372416.2 CTCAGTGCCAGGCTTGGCCGGGG[CG]GGGAATCTCTCGGCTTGTGCTTGCTCCGCG
FNDC3B 3028 NM_022763.2 TTTTGTCTCCTAGTTCAGGCTATTTC[CG]TGCCTTTGTTCTACCCCTCTTTGGGGC
ST3GAL6 3279 NM_006100.2 GCTGAGCCTTGTGTCACAGTCAGTC[CG]CGGCGCCACAAGCCTCAGTGTTTACTT

147
PLD3 1784 NM_012268.1 GCGGCTAGGAGGGGCCGTCAGG[CG]GGGATACAGCCTGGAAGGTG
SLC29A3 5877 NM_018344.3 GGAGCAGCAACCAAAAGGCCTGATGCGCAG[CG]CACCCATCGCAAGCATGGGCAGTGCGT
CD55 4091 NM_000574.2 TCCCCTTGGCAGCACTCAAG[CG]CGGGGATGCTCCGCTTAGACGAACTCAC
SKIP 5244 NM_030623.1 GGGCCCCAGTCTCAGTTGCT[CG]AGGATCCTGCTCTATCGCTCATTCGTGCC
KIAA0527 4285 XM_171054.4 GGAGAGAGCAAACAAGAGGGGACCT[CG]GGGAAGAGTGAAGAACAAAAG
LOC151194 800 NM_145280.3 CCAGGGGTGAGAGGGAGACCAGG[CG]AGGGGGGTCACAGGGCCT
TMEM67 4997 NM_153704.3 ACGAGCAGTGACTTCCGGTACC[CG]GACTTGGGTTGTCCAATCAGCTCAGCGA
RAD18 2930 NM_020165.2 TCATGACTGCCAGGCCCGGAGGCCAC[CG]AGACTCGGCCAGGGAGTCCATG
C1orf135 4090 NM_024037.1 GCTGTTCCCTTCTCTGTCCC[CG]ACTTCGCTTTCATCATCTCCAGGTGTC
WDR66 3970 NM_144668.3 CGTTTCCTGGCACGTGACCAC[CG]CCCTGCCCTGTCGCTTTAGGGCCTGTCG
FAM33A 1951 NM_182620.1 TTCCTGTTGGGCAAAGGCACAAAACGC[CG]CAGGAGGATTGGCTGCTGTG
OXCT2 206 NM_022120.1 CAAGTGTCCAATGAGCAGGCGC[CG]CTGGGTGACACCGACGCTCATGAACACC
TMEM100 3085 NM_018286.1 TTTCAGGCTACCTCTGTTCCTAAATGA[CG]CTTGTCTTTCCCTCCCTCTCTCTT
SIGIRR 3934 NM_021805.1 CGGCCTCACCTGGTTCCAGA[CG]TTCCACACTCCGGGTCTGTTTCC
MGC4294 5246 XR_001007.1 GGAGACTCCTGCCCTGGTGTGCC[CG]GCTCCTGCCCATCCAGCAGAGC
XLF 4228 NM_024782.1 GCCAGGGTAAGTGGAGGAGAGGC[CG]GGCAGCCGGCTAGTAGAAGGGT
PRP2 619 NM_173490.4 GGCCGGGGCACGGTACCCTGTT[CG]GCCTGGGCCGCAACCACGAAG
HMGA1 5413 NM_145899.1 AGAAGCTCCTTCGTGACTCCTCTG[CG]CGTGCCTTCCCACACCTCCTC
SPINT2 3377 NM_021102.2 TCGGGAGCCGCTTCCAATAGG[CG]TTCGCCATTGGCTCTGGCGACCTCC
DHRS3 1772 NM_004753.4 GAGCTCCCAATTTCAGCC[CG]CGAAAGTCTCCCGACTCATTGCTATTCT
KSP37 3536 NM_031950.2 GATCTGCCCCAGCCCTGTCA[CG]CACAAAGCGCCACACACAGCTTTGG
MSX2 732 NM_002449.3 AATTAGGTCTCGGGCTTTTCAGTTT[CG]GCGTGATTATAACCCTTCAGGGATCGCC
ROBO4 4950 NM_019055.4 CGACCATTTAGCTATAACCCC[CG]ACCCTAACTTCAGCGCTAAGCTTTATCTC
SUSD1 973 NM_022486.3 GGGAGCTGGATGAGGTGACCACAG[CG]CAAGGCCCAGATGAGAGGTCGG
RIPK4 3865 NM_020639.2 GCAGAGCTTCTCACGCTTCTCA[CG]GGTCTCGACGTGCGCATCAGCTGCCC
RBM35B 2311 NM_024939.2 GGAAGTCAAAGGGTCAAGGGGG[CG]GTGAGAGTTGCCGGGTATCACC
TOR1AIP1 2906 NM_015602.2 AAGTTGCCCTGCCATCCTTCTAT[CG]CCCCCACCCCTCCTTTACTTA
C1orf67 5057 XM_932839.1 CATTGTGGCCTCTTCGCCAGGG[CG]CAGGCGTGGCTCTTGGTCAGGCGGTTACGG
SULT1C2 3942 NM_006588.2 TCACAGAGAACGGAAGGGCTGGAA[CG]GGACCCAGCCAGCAGGGTTTGTG
DTX4 33 XM_166213.6 TGCGACTGTGAGTGTGCCAGTGCGTG[CG]CAAGCCCCGAGACAATGCGTGTCTC
MTHFD1L 2890 NM_015440.3 GCAGAGTCTGAGTCCCACTC[CG]CACCCCACCCTCTGTCTGGTACAGC
LOC144501 1876 NM_182507.1 GACCAGTCGGGGGCTGAGGCCC[CG]GGCTGACCAGCAAGAGCCCACGGA
CASP8 70 NM_001228.3 AGGAAGTGAGAAACAAGTGTGTGATAAA[CG]GTGGAGAATGGGAGCACTC
GALNT6 691 NM_007210.2 TCACCAGGGACTTCAGCCA[CG]GCTTCTCTGTGGCCTCCTCTCTGCTGCTCA
FANCM 4037 NM_020937.1 CGTAGCGGTTGAGCTGCTGCTGCTA[CG]GATATCTGACAGAAGCCTTCGGTG
TMEM56 2840 NM_152487.1 CGTGGCTAGCCCAGGTACTGACCGCTG[CG]GGGGCGGGCTCACACAGTTCCCC
FCRLM1 3155 NM_032738.3 CCTAAGGGTGCAGATGATGCTGAAAG[CG]TGTTGGCCAAATCTGAATGATG
MGAT5B 3060 NM_144677.2 GAAGGAGCAGGGACCCCCGCCCGCC[CG]TCCTCGAAGCTGGTCCTCGG
FLJ36748 5329 NM_152406.1 GGCTTAGAAGGTGCTCAAGAAAGACCCG[CG]GCGAATGGAGAAGACAAGCCCAA

148
KIAA0565 5625 XM_930399.1 GACAGGCAGGCTGGGCGCCGCCACCC[CG]AAACCTCCGAGGGAGGACCAG
SLCO6A1 3380 NM_173488.2 CACCCTGGGCGGCTCCTGGCGA[CG]CGGCCCGAGTGCTCTCGGCTGCCC
RSNL2 1913 NM_024692.3 CGGGGGAGGTAACACTGCGACACCC[CG]CAGACGCTGTCAGCCGGGGTC
EDNRB 3045 NM_003991.1 ATACCGAATTAAAGAAAGAAGAGGTTTATT[CG]GCCAGAAGCATCGGCAAGACTCCTG
ZNF597 4823 NM_152457.1 GGAGACACCGGAACTCGAAAGAAAAT[CG]GTAACAAAATGTGGGTTCGGC
TPD52L1 5733 NM_003287.2 ATCTCTGCGTTATGCCCTTATAGCGC[CG]GGAGTGGGTGCCTTCCGCCGGCTGTACAG
CCDC62 5815 NM_032573.3 GCTACACAGGAGCGAGCACGGCCGAGCTCA[CG]GTTATTAGGGGGAAGATGG
B3GALT3 5093 NM_003781.2 CAGCCCTGTGAGCTCGCATGGCG[CG]CCCTCTGGGTCCTCGCGGTCACCT
FABP3 109 NM_004102.3 GGCGCCCTGCTAGCCTGCGTCAG[CG]CCAGTGCCTGGCCCCCGAGTCC
E2F8 3977 NM_024680.2 GATACAAAGCACTATTTACTCCCTGTT[CG]GGTGGCCAGTTCACACCACGGCGTT
EFCBP1 2962 NM_022351.2 CGTCCCTTCTCTCTGTCCGGA[CG]CCCTCCTCCATCCCTGCACTTGG
LOC401097 4217 XM_376281.3 TCAACTAAGGTCACCTTGACGGAG[CG]CTTCCCTGTCCCTCTGGGGCTACCT
LRP1 5518 NM_002332.1 CGGGACCCTCACTCTTGGAC[CG]CTTTCCAGAACTCCGAACCCTGT
SLC22A15 3878 NM_018420.1 TTCCTCTTTCCTCACTTTAAGG[CG]CAGACAGCGGTCCCTCTCAAAACA
SCAMP1 2861 NM_052822.2 GGTGCAGTAGCCTCTCCAGTGCC[CG]CGTCCCACGGTCTAACGGCACTGCTC
POU2F2 3941 NM_002698.1 AAGCAGGCTGGAAGAGCCGACTCCTA[CG]GCTGCGATCCAAGAGGTGCCT
OVOL1 4029 NM_004561.2 GGGCGAGTTTCGTGTCATCACC[CG]CGGAGCGTGCCAGCGCCGGTGCAAAT
TMEM25 2297 NM_032780.2 GCCGCGCTGTGCAACCGCATGCTGGC[CG]ACATGATGGGGCAGCTGCGCC
C9orf103 5879 NM_001001551.1 TTTCCATGGGTGGATGAGGATC[CG]GCCTGCCAGGGTGAGGATC
DDX58 3633 NM_014314.2 ATGCCGGCCTCTGCTTGCAGCTAGCTA[CG]TTCCCCGCAGGCTGTGCCTCACTAG
METT5D1 1241 NM_152636.1 TCCACAGGGGTCGCTGGATTCGTC[CG]GAGCAAAAGAAAAATACGCCCCTGA
GAS7 5546 NM_003644.2 CCGGACATGGCCTTGGCGCC[CG]GGTTCACAGCGCAGCCTGCATTCC
IGFBP1 3001 NM_000596.2 ATTTTGAACACTCAGCTCCTAGCGTG[CG]GCGCTGCCAATCATTAACCTCCTGGTGC
CNIH3 4123 NM_152495.1 AGCCACCCGGGCTGGAGTTGGCC[CG]TTGGGTGGAGCCAGTGCTCG
BTG2 1757 NM_006763.2 AAAAACGCTGCCCGGGGAAAGTC[CG]GGCAGAGCCCGAGCAGCGGCCAG
IGF1R 209 NM_000875.2 CCACTGCGGGAACTTTTCCTC[CG]AGGGGCTGCGCCCTGTTTGCGAAACCC
C1orf59 1989 NM_144584.1 TGGAGTCCCAGTCAGCCTC[CG]CTTTCATCCCAGAGCAGTCCA
CAND2 5322 XM_371617.3 GGGTGTGTGCAATCCGGCGCTG[CG]CTGTCAGCAGGGCAAGGGCTG
STX16 3879 NM_003763.3 CCTGCTGGCAGTGGAGGACCAGGC[CG]TCCAGGAAAGGAAGGGGTCA
SRCRB4D 1599 NM_080744.1 GAGGTGGCCGGCACCAGCTGGAG[CG]GCCCCAGAAAAAGGGCACCCAGG
TP53TG3 2225 NM_015369.1 ACGCTCTGGAAAGAACTCGGGTG[CG]AGTGGGAAAGAAAATCGAGCT
FAM27L 587 NM_203392.1 TTGTGTATGGGCCCTTCCCAGGTAAG[CG]TGATACGTCCTGGCTGTCCTCAGTCCA
BMP4 2485 NM_001202.2 CCCTCCTCCTCTGCCTTCT[CG]CATCTTCCTTCCTCCTCTTTCC
CLIC6 4239 NM_053277.1 GGGTCCCGGTGGGAAGCAGACG[CG]CAATCGGGGAGAAGCTCCAGCAGT
ZFP95 3938 NM_014569.2 CTAGCTAGGCTTACAAGCGTGGGACCCCG[CG]CCTGGCTGAAGAGAGGTATCATTAA
HSPBAP1 1640 NM_024610.3 GGGGTCAGAGTAGGGGCCAAACTC[CG]AGACCCGAAGCTGCACCACAGGAAGG
GALR2 5444 NM_003857.2 CGGTCATCGTGCCCCTGCTCTT[CG]CGCTCATCTTCCTCGTGGGCACCGT
STIM1 2296 NM_003156.2 AGTGGAGCAGCACCAAGGCCCGGAGAT[CG]GGGCAGGGCAGCTGCTGTC
C1QDC2 5114 XM_371208.3 GCGGCCCGAGGAGGACCACGACCG[CG]GCCCAGGCCCAGCGCCGCATGGCT

149
RNPC1 3366 NM_183425.1 TAGTGCCTGCAACCGGCCGGGCCCG[CG]GGGGCAGCCAGGAGAGAAAG
RBM22 3926 NM_018047.1 TGTAGGTGTTGGAACCCAGAGAGGT[CG]CCATCTTGAGAGCGTCCGGAGG
OSBPL3 4017 NM_015550.2 GTCGCACAGGCTAGGAGAACTCGACCTCC[CG]AGAAAGTCAGACTGTGGCAGAGG
SPATA18 4256 NM_145263.1 CTACAAATGAAGAATTAAAGGAATGAAAGG[CG]AAAGAATAAAGGGGCCAAAGAGG
DMRTB1 5633 NM_033067.1 GCAAGGTTCCTGCTGCAGTTCC[CG]GGACACACTGCGAGCCGCTTTGTTACAAG
SF3B1 5784 NM_012433.2 GCCCTGGAGGAAAGTGGATTCTA[CG]AAGGGAGTTAAGAACAGACACTGAGT
FAM60A 2760 NM_021238.1 GCGCAATAATGTCCCCGAGGTG[CG]GAGTGCACGCCAGGCCAGTCCC
POLQ 5710 NM_199420.2 CAACAGCTGCGGACATCTTCC[CG]CCAGTCTTCAAACTCAAACCTCC
ZNF488 3051 NM_153034.2 AAGTTCAGAGCCACGCGCAGTGCTCTTGGC[CG]GGAGGAGGCTGTGCTGCAC
RBP1 3920 NM_002899.2 GCGCAGGTACTCCTCGAAATTCT[CG]TTGACCAACATCTTCCAGTACCC
MCAM 3686 NM_006500.2 GGCCTCTATCGCTTCCCAGAA[CG]ATTGCACCACTGCCGCTGCCGCCG
ADFP 1634 NM_001122.2 GGTTCGCTGGGGCACCCACTGGG[CG]CGCACTCACCGACGGACTGCAGCGA
BAIAP2L1 63 NM_018842.3 TTCGAGGAGCAGAGGAGAAGCGGC[CG]GACGCCGCCAGAGGAAGCTGG
LOC643431 1432 XM_928128.1 GTGGAGGCAGGAGTGGAGGCAGG[CG]GGCCGAACCAGGCAGAGATCCTAG
GFRA1 2698 NM_005264.2 CAGGACACGCAGTGTTCTGCAGC[CG]GCCGCGGGTGCTGCCAGACACACAC
C1QTNF3 5679 NM_181435.4 GACAGCAGAGCTCCAGGAGCGTGGTCTCCT[CG]GGCAGATGCCAGGACTGGAGC
CCPG1 5551 NM_020739.2 CGATTGTGCTGGCTGCCCCAGTGGCGG[CG]GTCACAGCTCGGGCGCCAATGACGC
PAPLN 4278 NM_173462.2 GTGTGTAGGATAGGCATGAAGAGGAG[CG]GATAGGGCAAAGCTAGAAGGCTT
ZNF551 2816 NM_138347.2 TGAGGGACGGGACAGAGAAGTCG[CG]AAAGTGGGCCAGAGGTTCTGC
SHANK3 23 XM_037493.6 AATTGTTTTTCTTTCCCCTTCT[CG]CCCTACCTTGGTCTTCGTGCCCCG
C18orf54 2184 NM_173529.3 TTGGAGATTCGAACTGAAGCCTGTA[CG]GAGGAAATGGTAAGATATATGG
PPCS 96 NM_024664.1 AAAACCCACAAGTCCCACGGGTCAAATGGC[CG]AGAAACGACTCCCAAGGAGTCCAAGT
COL5A2 634 NM_000393.2 CACCAGCTCCAGCACAGTCTG[CG]AAAACTTTTTTCAAGCGATGCAGCTTTAAA
MOBKL2B 2024 NM_024761.3 GTGGGGCGTCGCTTGCCAATCCA[CG]CAAGGGACTCTGCCGCCGGT
MUC1 6016 NM_002456.4 GGGTCCACTGAAGCAGAGCGGGGC[CG]AGAAATAAGAGGGCTGGATAATG
ISYNA1 2768 NM_016368.3 GAGGGGCCCAACGTCTGGAGACC[CG]GTTCGAGGCCCGACAACCCAGAGC
COL9A2 5898 NM_001852.3 ACAGTCCTTCCTGGATCAGC[CG]TCTCATGAATACTCCATCGGCCTCTTC
HES1 4019 NM_005524.2 CGCCAGGGCCTAGGGATCACACAGGATC[CG]GAGCTGGTGCTGATAACAGCGG
PDCD4 3790 NM_014456.3 GGCCCGAGGGGTCAGTACCAGTAGGCG[CG]GCTCACACGCTCGGGAAGACTG
NPAT 56 NM_002519.1 CCGCATCTCCTGGTTCCAGTGG[CG]GCACTGAACTCGCGGCAATTTGTCCC
MYH11 3520 NM_022844.1 GCACCGCACAAGGGCGCACGGAACAGGTG[CG]CACAGGGACGGGAGTCTCAGCCC
PASK 5037 NM_015148.2 CGCAGGTATCTCACCTGGATCAGG[CG]AGGGTCACGCCAAGCCGGCTACAC
SVIL 101 NM_003174.2 TCGGAGGTGGCCCAAGGAAACCG[CG]ATGAATCGGCATAAGCACGTCCTATCT
EDN1 3007 NM_001955.2 GCGCCTCTGCATCTGCGCCAGG[CG]AACGGGTCCTGCGCCTCCTGCAGTC
WDSOF1 3783 NM_015420.4 CGGAAAAGACGGAGGAGATCCAGTT[CG]GGCTGACAGTGAGAGGATGCA
ZIC5 3693 NM_033132.2 TTGCAAGACAACTTGAGTGATTTGGCTC[CG]CGAAACACCAGGTGAAGTCAAAATAAG
C6orf167 2619 NM_198468.1 GGGGTGCCGGTATCCCGCGTACC[CG]GCTGCAGCAAGGACCCGGGG
CRHBP 1908 NM_001882.3 AATGCACTCCCTTATTCTTTGTCTC[CG]CCTCATTCTCCAACACTTTAGTGCACTAA
CLTCL1 5591 NM_001835.1 AGCGGGCCAGTGGTGCTAGTTCTGC[CG]CCAACTCTGGACGGTTGAGTTC

150
EDN2 2843 NM_001956.2 TGCAGGGCCACGAGCAGGGCTAGCGCAA[CG]GAGCACCAGGTGGTAGGCACGG
SCARA3 5054 NM_182826.1 AAAATACCAAGGAAGTTGATCTGGGC[CG]GGGCCCAAGAAGTGACGAGG
ZNF420 5959 NM_144689.3 CGCACCTGCTGGGCTGGCGAACC[CG]AAATTGGGCTTGGAACCCG
TNFSF11 3985 NM_003701.2 AGAGCTGAGAAAGACTTCTGGAGAGG[CG]ACATTTGAGCTGAGAAAGGAAAG
RUNDC1 361 NM_173079.1 GAGGCCCGGCCTGGGGCAACCG[CG]TTTTTAGAAGAGGCGACGGCC
KRT18 3922 NM_000224.2 AGGGCCAACAACACCTGCTGTC[CG]TGTCCATGCCCGGTTGGCCACC
ZP3 5076 NM_007155.4 CGCAGTGCACGTTGTCCAGCAGGATGTGTC[CG]GTGCCATAGCCGAAGAAGGCGTT
SLC33A1 3087 NM_004733.2 AAGTCTTCGTGGGTGTAGGTTTCTT[CG]TTATGCTGACGACAGGCAGTGCCCG
TMEM97 2867 NM_014573.1 CCAACTTTAGTTCGGTGTTTTCCT[CG]GGCTTTGTCTCTATCCCAGCCCCT
C1orf131 300 NM_152379.2 CGTTCCTCAAATCTGTTCTCCA[CG]TGGGCTCCTGGGACCCCGCACTC
ZNF215 5127 NM_013250.1 TGCGCAAGAGTGCGTCGAGGTTGTTC[CG]CGGCAATTTATGAAACTCGGAGCC
UTP11L 4224 NM_016037.2 CGGAAGGCGGCTAAGTCCCGGCAG[CG]GGAACACAGAGAGCGAAGCCAGGTAG
CMTM2 5357 NM_144673.2 CCGGCGCCCTAGCAGATGCA[CG]TGTCTGTCGAATCGCTGCCTCCGAGCC
ACOX1 1718 NM_004035.4 GGAAAGAAGAAATCCGAGGACCGG[CG]ACGCCTAGAACAGGTTGGCTGG
CHRNB1 1931 NM_000747.2 CCTGGCACTGCTCCCAGGGGAT[CG]GGTCTCCACTCCAGCTTTCTCAATT
WDFY3 3207 NM_178583.1 CTGCTCCTCCTACTGAGCCGGC[CG]CAGAAATTGCAGCCGCTCAGCTTCTACC
BCL2L11 1743 NM_006538.2 CTTCTGATGTAAGTTCTGAGTGTGAC[CG]AGAAGGTAGACAATTGCAGCCTGCG
KCNJ12 4235 NM_021012.3 TGGCTTGGGCAAGACCAGAGCACGAT[CG]TGGGTCAATCAGGGTGGAA
KTI12 950 NM_138417.2 CAATGCCTTCTCACGGGCAGAAT[CG]CCGTACACCGCTGGGTCCTCTGCGCC
KIAA1043 2458 XM_929318.1 GTTCTTTTACCTATGTCATGCTGCATC[CG]ACTTTCTTCTTGCTGTCCTATAACTTACCC
SYNGR1 1040 NM_145738.1 CCCACACTTGCTGTGCACGCAC[CG]CCCTCCCCCAAACACTTTGCA
FOXQ1 1777 NM_033260.2 GAACCCCTCCTGGGCTCTTTAA[CG]AGCAGCAGATGCGCATGCTGCTTCTCTCC
ACBD3 4985 NM_022735.3 GACTTCCTGCTGACCTCTGACCTC[CG]CTTACCGACACCGGAACTTCCGCTG
NFATC3 125 NM_004555.2 CGGCGGGGAACATTGGCTAAGC[CG]ACAGTGGAGGCTTAGGCACCGG
H19 4154 NR_002196.1 CCCTGGACAGTTCCAGCACA[CG]TCTCTCTCACCCAGCACCCAT
SDPR 1225 NM_004657.4 GAACTGACTGATGGGTTGCAGAACAC[CG]GGTGTCCTACTGGGAGGCATA
NR4A2 3706 NM_006186.2 GGAGGGAGGGAGCAGGGACAGG[CG]GCCGGCTGGACAGGCAAAAG
SNX10 3290 NM_013322.2 CTGTTCTGCCCGGAGGAGCCGCC[CG]TAAGTGACAAGAGACCCGCTGAGG
MYO15A 3056 NM_016239.2 GAGGACCCCCATGAGGCGGCATGCAGG[CG]GGGAGCAGGCCACAGAACGCAGG
KISS1 3988 NM_002256.2 AGGCGGGACTTTCTCCTTCTTAC[CG]GCTCTTTCCATCCTCCACACC
CRABP2 240 NM_001878.2 CGTGTATGGCTGTCCCCCACC[CG]AGTTCCTCACGTCTCGCCTGTTCC
TBX2 5799 NM_005994.3 CTGGCTCGTTAGCGCAGGGGATC[CG]AGCTGGGCAGGACATGTGAGAT
PLEKHK1 3810 NM_145307.2 CAATAACATTACTCTCAAACACAG[CG]CTCTCTGTTTCCTCTCACCTTTCC
WDR21A 1825 NM_181340.1 CTTGGTCTTTCCGGGTCCTTGCA[CG]CTTCGCTCCAACTCCTGCAGAGCTGA
C10orf118 4976 NM_018017.2 GCCGGGTCTCCTGCCCTTTGGT[CG]GGTTCTTCCTTTCAAGCTCCTCC
HMMR 5725 NM_012484.1 CACTACACCGTCCCCTAAGTGA[CG]CCAAAATGCACTTTCTAACGTCTCCGGA
FLJ10781 4951 NM_018215.2 GGCGCTGCAATTGGACCTAGGGAGC[CG]GGTGCAAGAGTGGCCTGTTCA
MAFF 1343 NM_012323.2 GATGAGATCATTAAGGCAGAAGGTCTAGGT[CG]AAAGAAGAGGGCCAGGACCACTACC
KPTN 6136 NM_007059.1 GGAGGTGGTGGCCACGGCCTCT[CG]CTGTATGCTGTGTGGAAGGTC

151
DHCR24 3846 NM_014762.2 GAAACCTGGCGGTAACCTCTGCAGGT[CG]TGCCACTCGGTGTGCGCAAGGT
EPS8L2 1178 NM_022772.2 CCTGAGGGGTGCACCTGGCCCGG[CG]GAGGCTCTGACCTCCCCAGGGCTGG
GREM1 3893 NM_013372.5 GGGACCAACGCAGGCGATGCCGGG[CG]GCCGACAGGGAAAGCCCAGACCT
MGC87631 4295 NM_001004306.1 CCGTTACACACCAGTGCGCCTG[CG]CACCTTTGACGTCACTGAACCTGTGCCTTC
LOC146429 2356 XM_926271.1 GAGCTGTGCTCAGCGGCATTTCC[CG]GTGAGGCCCTTGACCCTTGACCTCA
PNOC 6060 NM_006228.2 CAGACACTTCCATCTGAGCCT[CG]AGTCTCAGCATTCTCCATTGCACCA
ZFP42 3725 NM_174900.2 GTGGCATTGGAAATAGCAGAGTGCTTCG[CG]GTAACAGGGGTGAGTCTTGTT
SYCP1 2431 NM_003176.2 GCTCCGGGCCGCTCAGGCTGAG[CG]ATTTCCCGCCTTTTCTGAGGTTCT
C13orf21 864 NM_001010897.1 AGAGATTACTTCCGTCCGGGCTG[CG]GCCTCTCTCTGGAGTCGGCTAGCCGGG
ATP8B3 1020 NM_138813.2 GGGACGCACAGCAGTGGGAGCACCCGC[CG]CTCACCGGCGCAGGAGAGGCAGG
LRRC4 154 NM_022143.3 GCGCCTGGGAGAGCCAAGGCCCGG[CG]GGCTATGCAGGTGCATGCCCCCC
ICAM2 3814 NM_000873.2 GGGGCAGGCAATGGGTGCACGCATG[CG]TGTATGAGACGTGTGCACAGGGG
SH2D4A 1680 NM_022071.2 ACACCTAGCAAGGAACCCCGAGCTCTGAAA[CG]TGGAAAGGCCCAGATCTGCAGATT
CYHR1 630 NM_032687.2 CGGCCTCGGCCTGCTCCCTG[CG]TTCCGGGAGGCGTTGTCCTGGGAACC
TDRD9 5021 NM_153046.1 GCCCTAAGGAGAAACACTGGGGGC[CG]TGACTGAGTGGGTGGTCT
FAM84B 5208 NM_174911.3 GAGGCTGGGCAGAGGGCAGCGCAG[CG]GGCAGACTAGGGGCATGTCTTT
MYL9 4057 NM_006097.3 CCACGAAACCAGTGCTTCC[CG]AGTGGTTCCTTCAACCCCGCTCTGG
SECTM1 4215 NM_003004.1 GGGAGGCACCGCACCCGCGGTTCA[CG]CTAAAGGAAGCAGGAAAGCCGCCG
EIF5A2 1319 NM_020390.5 TCTCCTTCTTTCTCTCGGTCAG[CG]CTCAGTTCTGGGCGCCTTCCCC
HORMAD1 2828 NM_032132.2 GAGCCTCAGACACGGGAAGCCTCAGCGCCA[CG]TCTCAGGCAGTGGAAAAGCCAGACAGA
MGC16703 2791 NM_145042.2 CGCCTGAGAGGATAAACTGCACGCGCCA[CG]GGCTATGCACTGGGCTGG
KCNS1 5669 NM_002251.3 GCGCAGTGTCCTTACCTGCCCA[CG]GGTTCCTGATTCCCACCTGCCAA
FOSB 2879 NM_006732.1 GGTAGAACAGGGTAGGTGGGGG[CG]CCAGAGGTGAAGGGGACCT
LY6K 223 NM_017527.2 TGATGAGAGTTTTACAGGATTACTCACGAA[CG]GCCCAGGCAGGGGCCTTACTAGT
LMO2 3533 NM_005574.2 CGGAGCCTTCACCCTTGCAG[CG]AGCTCTCTCACACCAGATGTGCTCTGCGT
ABHD2 3303 NM_007011.4 CTCATTCCTCTGAGCCCAGT[CG]ACAGCTGACCTTACCCAGCCCTCTA
ALDH1A3 2318 NM_000693.1 GGCTCAGCTCCCTGCCGGGT[CG]GGTGTCCCAGCCCTGCGACTTCC
CLK4 1030 NM_020666.2 GGGGCTCGAGCCTCCACACTG[CG]GCTGCGCGGCCCAAGCATTTCCA
GAS8 2892 NM_001481.1 TGAGCACGTGCTGTGTGCTGTTCTAGG[CG]CTGAAGGATAGAAGTGAAGGG
IBRDC3 3987 NM_153341.1 CCCTGCTTGGGACACCCACG[CG]GGGTCCCTGCTGCCCCCAGCC
LOC644433 1080 XM_927576.1 TTATGCAGTGCCCCTCCTCTGTC[CG]CATCCCCAGGACCACCATGGGTG
PLEKHA6 700 NM_014935.2 TTAACTCCATCCACACCAG[CG]ACAAGCTGCTAACCATCCACGCAGC
KCNK3 2222 NM_002246.1 TCCCATTCTCCGTAGTTATCAG[CG]TTTCGCTGTCTAGTTTTCTCTGTCTCTCGG
RRAD 692 NM_004165.1 CCGCCGCTGCTGCTGCAGCCAC[CG]CCTTCTCAGCCCGCACTGGGCTCTGGC
C20orf30 75 NM_014145.4 TTGTCTCTTTACCCAGCTTCC[CG]GGCTAACCCTTACCGAGTGTCACCTGCA
STAR 5504 NM_001007243.1 TCCTGAGCCCCTCAAGCTT[CG]CCTCTGAGTCCCGCAGCTGCAGCCTGG
PYCARD 2651 NM_013258.3 CCAGCATAACATGGCCAACC[CG]ATGGCTCCCGAAACCTTGCCAGATGC
ZNF334 1678 NM_018102.3 GACGCCCGAGTGCTCAGAGCT[CG]CCGCCAGCCCTTCCTATAGGTTGTGG
SMEK2 1766 NM_020463.1 ACCGGGGAAGTACGTAGCCTTGAAC[CG]GAGTAACCAGGGACAGAAAGGAA

152
LRRC34 5257 NM_153353.2 AAGGAGGTGACATCTGGATGGTC[CG]AAGGAGGCTGCCAGAGGACAGA
LOC112703 5009 NM_138411.1 GGTGAGTTACAGACGGAAGGAGGCTG[CG]CAGGGCTGAGAGGGAAGAG
ZNF14 984 NM_021030.2 GGAAGTCACGGTGTCCTCCCTA[CG]GATCTGTCAGTACCTGCAGGTCACGGCGC
USP36 4102 NM_025090.2 TCCGCAGCGCACTAGAGGTGCCGCTACTTC[CG]GGTCGGCCGAGCACACCTGG
FLJ25801 2271 NM_173553.1 GAAATAAGTCCACGCAGACAGAG[CG]GGTCGGCGCTCTGGACTCCTCAAATCC
OVOL2 6099 NM_021220.2 GACTGAGCATGCGCCCTGCAACATAA[CG]GTGTCAACAAGCTCGCTACCTGTCCGA
KCNB1 949 NM_004975.2 GCGAGGCAGAAAGCGAAAGCGGACG[CG]GGTCAGCAAACGGGGAGCTG
TMPRSS2 2853 NM_005656.2 CCCCCGGAGCTGCTACCTCA[CG]AGCTCCTGTAGGCGGCCGGCCCC
FGR 4225 NM_005248.1 GGCCAGCATCCTCCTTGGC[CG]TGGCCACCGGCTCCAATTTCTTGC
LOC161931 3132 NM_139174.2 AGGGCCTAGCGCCTCAGATCTT[CG]TTGGCGGCCATGGCTTCGGCTTCTCAG
FBLN2 1309 NM_001004019.1 GCCTGGCCTCTGGGCAGTTTTGTAGC[CG]GGCCCCTCAGGCCCTCACAATGTG
LOC88523 442 NM_033111.2 GGAAGACTTATGGAGATATTAAAATTGGT[CG]CCTGTAGGTGGTAAGAATATTTTC
ALS2CL 1730 NM_147129.2 CCTTACCTGAGCGCTGTGGTTGCCC[CG]CGCCGGGACTGCCTGTGCGGCTCCTCG
TF 3709 NM_001063.2 GGGCGCCGGAGGCTGCACAGAAG[CG]AGTCCGACTGTGCTCGCTGCTC
PROX1 4145 NM_002763.3 TGCTGCTCTCTCCTCTCCTCC[CG]CTCTTCTCTCTCCTCCTCTCCTGCT
TRIM41 2693 NM_033549.3 CGGCATCGGCTGTGGGGAGTAC[CG]GCTGCAGTCGGCTGTGCCG
ANK1 2162 NM_020475.2 GTTGCCCCGGGGTCGAGAGCAGC[CG]GGGAGAGCTGAGTTCAGAGCC
XPC 5941 NM_004628.3 AAGGGCGCAGGGTTTGAAACATGG[CG]GACGACGTAGACCAGGTAAGTGTATTT
TMEM88 4036 NM_203411.1 CCCGCTGTCACCATGCTGGGCTT[CG]GCTTCCTCTGCCACTCTCAGGTGAGCG
TACSTD2 1804 NM_002353.1 ACAATTTGATTCTAACACAGCAAAT[CG]TTGCTTTTCTTTTCCTGTATCCCACGTAA
MAP7 936 NM_003980.3 CCACTGCGGGCGACCCTATCTTGT[CG]CCAGGACTTCGCATCTGATGAGCCTCAG
FAM111B 5688 NM_198947.1 TGTCAGTTCCCAGGCTCCTGC[CG]CGCACGGGCGAGCCCTTCTAGGCGG
FES 987 NM_002005.2 GCGCGGCAGGCAGGGGCAGAGCAGG[CG]TTCCGAGGGCCAGAGACCCACCCAG
HES2 2347 NM_019089.3 CCGCCTTTGCGTCCTGTCTAC[CG]CGGGGTGGCGGCCCCCAGTTTTC
GJA7 1741 NM_005497.2 CCAGAGTTGTCTTCTGCGCGCTC[CG]CCGAGGCCTTGGTCCATTGTAGCACGGG
HSD17B12 3992 NM_016142.1 CACCGTGGCCTACCTAGCCCTG[CG]TATTTCGTACTCGCTCTTCACGGCCC
TRIP6 2342 NM_003302.1 AGGGGGTGAAGGCCAGAGGCT[CG]GGGCTTCAAGACCGCTGTCTG
CDC42BPG 926 NM_017525.1 CGTAGGGGGCCGCTGCTGAGCT[CG]TGGTGCAGCGCCAGCAGCAGATCTAGG
ZNF570 775 NM_144694.1 ACGCACAAACCTTTTCCCTG[CG]GCCAACCTGCGATTCTCAACTCC
FAM76B 6020 NM_144664.3 AATGACATCCCGGAGCTCTCAG[CG]CGCGAAATCCGCTTTGAACCTGCCC
DKFZp779O175 2308 XM_932926.1 GGGTGATTGTGATATTTGGTTGCG[CG]GGATTATGATGAAATGTGTG
C1QTNF1 5236 NM_198594.1 CACATCTGGCTGGGCTTCGCTCCTTG[CG]CGTCTGTCCCACTTTCTCCCTCTC
TNFRSF10C 3870 NM_003841.2 GGGTATAAATTCAGAGGCGCTGCGCTC[CG]ATTCTGGCAGTGCAGCTGTGGG
GOLGA8A 121 NM_181076.2 CCCTGCCCTGGCTGAGCTGATCAC[CG]CTGCATGTCCCAGCTGCCGGTCTGCCT
PGF 976 NM_002632.4 GGAAGCCTTGCGGAGTCAGGAGCC[CG]TAGGTAAGGCTGTGGCTGG
HSPA8 6082 NM_006597.3 TGGAACTAACCAATGATAGCGGCGCTAGC[CG]GGATCTTGGCCGGCACAGAAC
ZNF541 5510 NM_032255.1 GCTTTTGGGACAGCCCGGCAGGTTC[CG]GAGCCACTGGAAGCTGTGGC
B3GNT5 4012 NM_032047.3 GTGGCTTTAGGGAGAGGTCTAACAACATG[CG]GGAAACAAGAAATCAAGCGCATCCAGG
STK33 2174 NM_030906.2 CCTCCGCTGGGGGGTTACCAGC[CG]GCCGGCAGCGAGATACCCAGAGGC

153
HNRNPG-T 3523 NM_014469.3 TTCAGGAGGCCATTGAAGCCGTTAAGAC[CG]GGTCAGGTGAACAGGAAGTTAA
CCDC18 2862 NM_206886.2 GCGTCAGGTACTGTTGTCTCCGCTC[CG]CGTTTCCTCTCTGGACTCCTCGTGGTTGAC
LGR6 5599 NM_001017403.1 AAGTTTCCTTGACTCCTCCTC[CG]GCTGGGTCTCCCTCCCTTGCCAA
RFWD3 5397 NM_018124.3 GCCGCACTCCGAATGCACCTA[CG]CCAACTGCCACTTCCGGAGCCGCT
ECHDC3 1339 NM_024693.2 AGGCAGAAACTTAAAGTGTGGACCCCCAG[CG]TCTGGATGAGAGGACACAAAGG
LRRIQ2 978 NM_024548.2 CCGATGGTAAAAGTGTCAAATTTCGCAAA[CG]CCTGGACAAGGAAGTGAAATG
ZNF331 1042 NM_018555.4 TTCTCCTGGATCTTATCCCAACTG[CG]CCTGAGACCTTGTTTCACCTCCTGATGTGC
LZIC 5537 NM_032368.3 ACTCTGATCTCTGCACAGTGCCGAC[CG]GTCTCAAATTGCACAAACCTCCAGT
TOM1L1 2265 NM_005486.1 GCTGCCTGCTCCTCCTGCACGGGG[CG]AAAAGCCCACCTGGGATCCGAGC
FABP5 2198 NM_001444.1 GAATACATGAAGGAGCTAGGTGAGGCACC[CG]GCCTGGCAGCGCCTGCAACGTG
EP300 4919 NM_001429.2 CGATGAGAAGGAGGAGGACAGCGC[CG]AGGAGGAAGAGGTTGATG
C6orf204 3482 NM_206921.1 ATCACTCAGAGGTAAGTCGGAACGCAGGT[CG]CTTAACTAGAGAGGCTTTGAGTTCCG
RHOF 5055 NM_019034.2 GTCCCAGGGATACTGCAGCACCGGAAAAA[CG]GGGCTCAGCTGCGAGCAAAGCT
TAS1R1 5853 NM_138697.2 GCTGCTGGGCCTTTGCCTGCCATAGCA[CG]GAGTCTTCTCCTGACTTCACCCTCC
GMPR2 720 NM_001002002.1 CCTGCAAGGGCCACTTCTACTTC[CG]GGTCACTGTCTGGCTCCACCCCC
HRK 2155 NM_003806.1 CGAGGGAAAAAGGCTTGTTTGC[CG]TTTTGGATGAAGCTGATGCTG
LOC57146 4893 NM_020422.3 GCAGGCGGCTCTGGCTCCCTCT[CG]GGACGCTCTTTCCTTCTTCCTCTTGTT
PROSC 758 NM_007198.2 TGGCCGCAGGTGGCCGCTAACCTCT[CG]AAATAGGGATGGCCCGAATTG
SNX5 3677 NM_014426.2 CGCTGCCGTCCATCTTGGAGC[CG]GGCAAAGACGCCACGTGGGGCCTACC
L3MBTL 153 NM_015478.4 GTCTGTGGGGATTGGCTAAGCCT[CG]TAAACCGCAGCCATGGGGCGG
LOC346673 2863 NM_182489.1 GGCGCAAAAAGGGGTGGCCATCC[CG]AGTTGGTATGAATGCAGGGATC
CEP76 6115 NM_024899.2 TCGCCTTGCTTGCCAGGGTCTC[CG]AAAGCGCTGCTGGCCCCTCTTCGCG
CNR1 5366 NM_016083.3 GTACAGGAGGTCAGTGGTGATGGTG[CG]GAAGGTGGTATCTGCAAGGCCA
KIAA1199 1682 NM_018689.1 CGCCCTCACCTGGCTGCTGCGGG[CG]GGACTCTGCGCACCCGGGCTCCG
ELOVL2 480 NM_017770.2 CGCTGCCCAGATCGGCAGCCGCTGCTG[CG]GGGAGAAGCAGTATCGTGCAGG
RAMP1 3833 NM_005855.2 TGTTCACCTGCCGTGCTGTCCC[CG]CCTCTGCCCACCCACTCATCC
ZNF562 5567 NM_017656.1 GCAGCCAGACGGACTGTGCGGCCTCT[CG]GAACTGGCCAGAGGCCGCACCAG
IGFBP5 1389 NM_000599.2 AGGGGCCAGTGGAAGACAGAGTTCTT[CG]GAGCAGGGTGAACACAATGAGG
PDE4C 4993 NM_000923.1 GGGCTCAAGGTGGGGCCGACAC[CG]AGGAGCTGTCGATGCCCAGATG
SLC25A21 4292 NM_030631.1 TCAAGTGAAGTGACCCAGGCCTGGAG[CG]CCAAGTACAAAGCGGGGACGACACTT
CCDC15 110 NM_025004.1 CGGAGGGATTTAGGAAGTCTCGG[CG]TTGGTCCAGGAACGACAGTCCCACC
AGR2 1828 NM_006408.2 TGAAACGTATTGTTAAGAGGTTTTGAAA[CG]ATGGGCAGAGTGCCAAATCCAGGT
KIAA1509 2190 XM_935320.1 GAGAGAAGCCGGTGCACCAACAAAGGGG[CG]GGGAGCCAGGCGCACTCACCCAGG
LRP10 5056 NM_014045.3 GGAAGCTGAAGCTGCAAGTCAAGGGCC[CG]TCTGACAAGTCCGGCAGGGCCG
MVP 4250 NM_017458.2 GGGCTGAACCATCGGGAGGAGG[CG]CCAGCCCACCGAAGGCGAGGGA
AHI1 3 NM_017651.3 TGGGGAGGCTGTCATGGAAGC[CG]CCCAGAATAAGAAAATGAATGAATG
PFTK1 2854 NM_012395.2 CTTTGGCTGCAATGCTGCTGCAGAGCC[CG]GTTACTCTGCCTTCGTGGGAACTCCACA
C7orf31 4279 NM_138811.3 CCCAGCGCTACGGGACTGGCAAGAATG[CG]AAGAGGAACCGAGAGTGAACG
EIF4E3 1326 NM_173359.3 GGGGGCAGAGCCAAGAGGCGCGG[CG]GCAGCAGCGGAGGAGTAGGAGG

154
DKFZp667M2411 3284 NM_207323.1 GTGAAGTGAAATCTGCAAGAGTCCTGCT[CG]TTCAAGGCCTGCATACAGGAAAGAAGC
TP53INP2 2097 NM_021202.1 GGCGGGCGGGCCCCTTTGTGA[CG]TCACAATCAGCTGTTTGAACGTTCCAA
SP5 5670 NM_001003845.1 CCATAAATCTTCCCTCTGACTGGCTGG[CG]GCCCAGCAAAGTCCTTATCAAATT
PPARG 2415 NM_138712.2 CTAAACTTCGGATCCCTCCT[CG]GAAATGGGACCCTCTCTGGGCCGCCT
ARHGEF7 1072 NM_003899.2 AAAAAACCATCTCGGACC[CG]GAGGGCTTTCTGCAGGCGTCGCTGAAGGA
SLC27A2 4060 NM_003645.2 TCCTTTAATATTCCCAACGTC[CG]CTAAGCGCGTCTCATCACCATTTAAAG
EFCAB2 3877 NM_032328.1 ACCGGCTCCGCAGCAAGATGGCGGA[CG]AGAAGGACAGGGAAGGTAAGG
FBF1 5607 XM_932824.1 CGGGTGAATCCACAAATTCAC[CG]GTGTTTATTCCACACCCCAAAGCT
FAM8A1 1110 NM_016255.1 GACGGTCTGGTCCCAGTCAC[CG]ACCAGCCACCGACTACTAGGGCC
CSTF2T 3315 NM_015235.2 TATGGAATGTTCCCCACGAACA[CG]GAACGCAGTGATCGATCCATTGCCGG
C21orf7 2059 NM_020152.2 GCCCTGGTGGTGTGTTCTTGATAT[CG]GTCCATCTAGTGGCGTTGTTTG
EBI2 1250 NM_004951.3 GCTTATGAGAAAGAAACAGGTTTCTGTGG[CG]TGGGGGTGAGTGACAGTCCA
ATP6V0A4 2960 NM_020632.1 CTTCTCAGCCCCACTGGGCTGT[CG]TGCTTTGCAATCCTCCCTGTGCACATTT
ADAMTS14 754 NM_080722.2 GCAGCGGCGGCAGCCAGCCGGTGCTC[CG]ACAGCCCGGGGCGCACCCTAGCC
UBE2B 1590 NM_003337.2 CTTTCCCTGAAATCTCTGGCC[CG]GATGCGTCCCTCTTTCTCCACCC
KCNK4 881 NM_016611.2 GCAGGGAGCACCCTGGAGGGATAGC[CG]GGGAGCAGGTAGAGGGCCAA
JUP 2179 NM_021991.1 CCATTGGCCCCGGGGACTGCCAGT[CG]GCTCTAGGGATGGACTCTAACT
DAZL 4162 NM_001351.2 GACAAGGCTGAGGAGCCCCGAAAGG[CG]GACCGTCAGGCTGAGGAGCG
LOC345630 3072 XM_293903.6 GGGACGGGTGTGATGCAATCG[CG]CCACAGCCGCTGCGTCAAGGGGC
COL12A1 1550 NM_080645.1 AGCCAAGTGGAAAGAGACTCCGCGCCG[CG]GGCTACTTAATAGAGGGCTGTTC
REC8L1 2087 NM_005132.1 TGCGCTCATTGGTCAAGGAAGGGG[CG]CCTGTTACTAGAGGCGAGAACCGG
LRG1 2434 NM_052972.2 GGGTTAGCTGGAATGTCCTGTATCTC[CG]CATGGTCTGGCGTTCAAACCTG
CABYR 5735 NM_012189.2 CCAAATCATGGCCTTTGTCGCTTT[CG]GCTCCCCATTGGCTGCGGCCGCTGTGG
BAALC 5129 NM_024812.2 GGCAATACTCCCTGACCAGTTTTG[CG]GGGTTGCTCCCAGTTCCATTGCTTTT
SFRP1 4325 NM_003012.3 AAAAGAAGGGGAATGGATCACGG[CG]TGGGGTGGAGAGAGACCAG
TSC22D1 3042 NM_006022.2 CATCACTGGCAGCCATGGAGCC[CG]AGCATTTTCCTCCCTCAGGGCA
MGC21881 515 NM_203448.1 GATTTGGGCTTTAATTGGTTGATTT[CG]GACAGGATCTCAGAAAGTGAAGACT
LSR 2363 NM_205835.2 TCTGAAAGCATGCCCTTTGTCCA[CG]TCGTTTACGCTCATTAAAACTTCCAGA
PTGDR 5800 NM_000953.2 GAGCTCTTCACTGGCCTGCTCCG[CG]CTCTTCAATGCCAGCGCCAGGCGC
TEB1 3083 NM_017826.1 CCCAGGCCGGGCTTTGAGGGC[CG]AGGGGACCACCGACCTAGGG
C6orf150 4075 NM_138441.1 CTGGCGGGCACACAAGAGTCTGCGACC[CG]AAGGGGAACCCCAGGCTGG
HYLS1 1109 NM_145014.1 AGTAAAAAAGAATGAGGGCTGAGCAAGA[CG]ATTGGAGCTGACTACCAAGATCACTG
DKFZp434I1020 1219 NM_194295.1 GAGCCCTCTTGGGACCCATGGT[CG]CCCTCAGTCAGCGGGACTGCTCCC
COQ9 4116 NM_020312.1 GGCTGCGCAAGGGACGAGGCAGC[CG]GGGAACGGCAGAAATTCCC
CRAMP1L 1170 NM_020825.2 GGCTCAAGAAGCTGGGCAAGCGGG[CG]GCCGATGAGGAGTCCCTGG
OXTR 1037 NM_000916.3 TCTGCTTGTCTGCGCCCAAGAGC[CG]TTTCTGCCTCCTTGTCGCGCTTCGGA
ACAD11 4247 NM_032169.3 AGCAGGCGGAAGACCTGCAGGGTCC[CG]TTCAGAAAAAGGGCCGTCAGACTG
ATP8A2 3526 NM_016529.3 GCTATAAGAAGGCAGAGGATGAGATGTCC[CG]GGCCACGTCTGTTGGAGACCAG
CDC14A 3030 NM_003672.2 AAGAGTAACTGCTGAAAGGAGGTGG[CG]AAGGAGGATCCGGAGCAGCTG

155
ITGB4 2095 NM_001005619.1 GCCCCGAGGTAGGTCCAGGACGGG[CG]CACAGCAGCAGCCGAGGCTGGCCGG
GRIN2A 2680 NM_000833.2 CAGCGACCCTCTTGTGATCCTGC[CG]CTTCCTCCCTCTTCAGGCCTC
SERINC1 3860 NM_020755.2 TTCCTCTTTCTCAGTCTTTGTC[CG]TCCTAACTCCACTTATTTCCCATTT
AS3MT 3293 NM_020682.2 CCTGGTTGGAAAGCCTGTAGAGCAGCG[CG]GATGACAGTGGAACAGCGGG
ABHD14A 5965 NM_015407.3 TGGGACAGGCCAGACGTTGGTAACACAT[CG]CCAACCAGGGCAGGCGCCATGAGTAGA
KALRN 2951 NM_007064.2 CCACTGCAAACCTCGCGTCTTTG[CG]AAAACCCTTCCTGACTCCCTCC
GOLT1B 5145 NM_016072.2 GGCTCTCGCCTGGGCTGTTTCC[CG]GCTTCATTTCTCCCGACTCAGCTT
CUZD1 66 NM_022034.3 AAACACAAATGTCTTCCCAGGG[CG]GCCTAGGATCCCAAGCTGGCCCA
C10orf88 1229 NM_024942.1 CGTTGCTGAGCTGGTGTGGAA[CG]TCTGTGATCAGGTAGGTGTAGTCTC
CHD6 4908 NM_032221.3 GGTTCCGCAGGGGCCGAGGCCACG[CG]GGCAGATGCAAGGAGAAGCGAG
KPNA4 3043 NM_002268.3 AAAGTAACGTTCTTTTCTCCC[CG]GGCGCGCCCTGTCTTCCTGGGCATTC
DCC1 3752 NM_024094.1 GTCCACATTGTCTCACCTTC[CG]CCAGTGGCGGGCCCTGTGATAACCACTTGG
CDH23 3901 NM_022124.2 GGGGGATTCGTAGAGTTGCCACAGCAGC[CG]GTGCCATGACATCGGCAGAGGG
CGI-09 4876 NM_015939.3 GGAAAGCTGCGGCTGAAGAGAACTG[CG]GACTTGGCAGGAGTCGCCTG
C14orf140 1651 NM_024643.1 GCTGGACCGAGCTGCAGAGTTGGC[CG]GACACTGACTGGGTCAAGTGAC
FLJ46419 559 XM_930581.1 CAGTCTGGCTCTGCAGGGCCC[CG]TTATCCCGGGCTTCTGCTGTCACTCAGG
4863 TTGCTGCAGTGGGGCGCATGCAGCCG[CG]AATCGGCACCTGGGCAGCAAGCG
LRRC51 105 NM_145309.1 ATCTGAGATTTCCCCCAC[CG]ACCCTCATCACCTTTCACAGC
SLC22A5 1203 NM_003060.2 GAGCCCGGGCTACCTCGGT[CG]TCCCCAGCAGGCTTGGCTGGCAGAG
TSPYL6 6035 NM_001003937.1 ACCTCTGTCGCCTTGCTCTTTTCT[CG]GGACCTCTGGCCCTGGTGCGGGTCTTCC
FLJ45248 5997 NM_207505.1 GTTGACTCAGAGGGTGGCCGGG[CG]GCCAGCGTCTGATGTCAGCCTGG
C1orf167 2216 XM_209234.5 GGGAAGGAGCCAAGAGGAGGCA[CG]CCTGGTGGAGGAAGCCCAGAC
ETV4 2187 NM_001986.1 GAAACTTCTCCGACTCACTGGGG[CG]ATGGCGAGGTTTCCGCCTGCCAGGC
RFXAP 951 NM_000538.2 AAAATTAGCATCCTAACACTACAAGT[CG]TGAGACCGCTCAGGAACAATCCTAAT
CRYGD 1885 NM_006891.2 TGGCAAGAACCGCACAAAAGGGGCCCC[CG]GAGGGGAGCAAGGGCATTT
LRRCC1 1980 NM_033402.2 GCGGAAGTGGAAAACGAAGACGG[CG]ACAGCAGCTGCGGGGATGTATGC
DIO3 1047 NM_001362.2 GCGGCAGCGGCTGCCGGAGTCCCC[CG]CCCCCGAGAGCTGGCTGCGG
TRIM39 961 NM_021253.2 GCGGCGGGCATCCCATCTGCA[CG]TCACACCTCTTTCTCACCTGGACAC
ITGA4 2893 NM_000885.4 GTCCCGTGGCAACTGAGTGGGTG[CG]TGAAAAGGGGGGATCATCAA
SEC61A2 172 NM_018144.2 GCAAAATACGATTGGTTCGGTCC[CG]TCCGCTCTCAGCGGCTCAGTCC
CTCFL 2326 NM_080618.2 TTGGCTTGTGGGCTCTGCCTCGTGCAC[CG]CGTGCTGCAGCCCACAGCCGGCC
TNFRSF10A 5981 NM_003844.2 TTCCTCTGTGACCGCCCTTGC[CG]CTCTCAGCTTCTGTTCCTCAACCAC
FBXO22 3919 NM_012170.2 GAAGAAAACAGTTCCGAGCGTATTACGGAA[CG]GAGTACACCTCGGAGTACGGGCT
FOXL2 4134 NM_023067.2 CAGGAGCCTCGCTCTGTTCTGATT[CG]TATGGGCTCCACCGAGTTCCGCTTGC
PPP2R1B 2901 NM_181699.1 AAGACTCAGGCGGACCAAAGAGAGTGCC[CG]AGGCCAGGAGGAAAAAGGCTT
STAG3 4300 NM_012447.2 GACCTTCCCTGAACCCTGCT[CG]GCCAGAAGTCACTCTTCCAGGCTC
KL 4934 NM_004795.2 GCTCCGCTAGGGCCCGGCAGGATCC[CG]CCCCCAAGTCGGGGAAAGTTG
SOX13 1384 NM_005686.2 CAGAGCTCAGCGGTCAGCCT[CG]TAGGCCCTGACTCGGAATCGAGCC
ZNF175 3011 NM_007147.2 GAATGAACCGCGGAATAAAGGTACGC[CG]TTATACGCCATGATAACTGTTGGCGG

156
CHRNA1 186 NM_000079.1 GAGAGGCCAGGGCTCCATGGGCTAC[CG]GAGCTTGTGTGGACCAGGG
ELMOD2 6137 NM_153702.1 ACATGGACTTTCCTCATCTGCCA[CG]TATTGGCCACAGTCAAGTAGCCGGTTC
NRG1 2729 NM_004495.1 GAAAAAGAGCCGGCGAGGAGTTCCC[CG]AAACTTGTTGGAACTCCGG
KLHDC4 3800 NM_017566.2 AGGAAAGAAAACGGCCCGCGCTCTC[CG]CTCGGAAACAGGTGCTCGTG
FAM83F 2062 NM_138435.1 GGCTGAGGGACACGTCCAAGCTGCAGT[CG]GCTCTGTGGTTGTGGACACC
MAL 3096 NM_022438.1 GGTCACCTACGAAGGGAGAAAGGCA[CG]AGGAGCGCCTGACCAAAGTGGT
AQP1 1321 NM_000385.3 CCCTGAGCTTTGCACACAGGGC[CG]AGACACCTGGATTTCTCTGGTTCCCTGA
PAX6 1617 NM_000280.2 CGCTCCTCACTGGCCCATTAG[CG]AAGCCTGACCTCTGTCATCATCCTCC
NFE2L3 6117 NM_004289.5 CGTAGCTGCCCAGTCACTCTC[CG]CCCAGTCTACACATCCTGTCCCTT
BHMT2 5003 NM_017614.3 GGGGAGCCCTGCAGCGGGCAGCTC[CG]CAGCAGGAGGCCCCGCAGCAGCTGCG
SPHK1 1851 NM_021972.2 CGCTTGCCGCTTCCTAGGACC[CG]GGCGGGAACCAGCTCGTGGCCCGG
GPR87 3592 NM_023915.2 TAAGGAGTGGGGGATGAAGTCT[CG]GGTTGGGGCCTACTAACTC
RIBC2 6007 NM_015653.2 GCCTGCGCTACAGCTTCCTTATTTT[CG]TCGCCTGTTCTCCTGATCCTGCGTGTTCT
ANGEL1 1000 NM_015305.2 GCCACCCAGGCGTCCCGAATTAAAATTGAG[CG]CCTCACTGGAGGCCCCATAGTGTTATT
SEMA7A 5176 NM_003612.1 GCGGCAATCAGCCGAGACTGAGCCAGCGCC[CG]GCCGCAGGCAGACCCAAGCGCCAGG
GMPPB 1228 NM_013334.2 GAGGGTGACCAGGGAAGGCTCC[CG]GGCCACGGGATTTTCACAAAGA
2943 ATGGGCATGGTCAGGAAAGTGAAA[CG]AGCTGACACCTGAATGTTGAGAAG
CCDC11 1311 NM_145020.2 CTCCCGCTGTACGGTGCCAAAC[CG]CTGGCTGTACATTTTCGAGTCCCCTTC
CACNB4 5252 NM_000726.2 GGTTCATGAATCAGGACTTGGGGA[CG]GAAGCTGGTGCAGTGTGGC
TSPYL3 1786 XR_000578.1 GCTTTGGGGCAGTTGTAGGACACTCT[CG]GCCTTACAGGGGATAAATTACTCAGG
SYTL3 717 NM_001009991.1 GTAGGATGAGAAGGCATGGCTGGC[CG]TTGCAGCAGGTCGTTTTAGGAGTG
THRSP 3479 NM_003251.2 GCTGACCGTCATGGACCGGTATGCAGC[CG]AGGTGCACAACATGGAGCAGGTGG
KIAA1109 3399 XM_371706.4 GCTGGCACATAGATAGGCATAGAGGGGCAG[CG]TGAATAAGTGAGTTGCTGTTGTG
DLNB14 5285 NM_198489.1 CGCCAGACCTTCTTCTGTGGTCG[CG]GGCACGTTTACAGCCGCAAGCACC
LIMD2 182 NM_030576.2 CCGGCCTGGCTCCGGGATAAC[CG]GGCGGGGCCTGGGCCATTCACTGCCT
XLKD1 3481 NM_006691.2 CACTCACTGCTCCACTTCATAAC[CG]AGACATCCGGATTTCCCTGCTTTC
FMOD 2442 NM_002023.3 GGAGTGAAAGAGTCTACTGAGAGTGTG[CG]TGCCTGTGCCAGACCAGGGTCCC
ZNF552 4851 NM_024762.2 GGGCGCCGTTAAAGAGCTGCAGAGTCA[CG]TCTGTGCAAAGAGAAGAACGACTCT
CRYGC 4301 NM_020989.2 CCATGGCTGGTTGACACGGATGATG[CG]AGTTCAGTGTGATGGGGCCT
ZNF114 620 NM_153608.1 GGGAAATGCAGGAAGCCAGCAAGCGGC[CG]GAGTCTCCGGAGCCCGCAAGG
MORC3 3910 NM_015358.1 CATAGGGCTCCACAGTCGTTC[CG]CCACCTCCCAGTCGGGTTGCGGC
PCDHB15 4046 NM_018935.2 TCTGGCAGGCTGGGAACCCCGT[CG]CTATTCTGTGATGGAGGAAACAG
AP3S1 2322 NM_001284.2 TCGAAGCTGTCGCAGACCTCTGAA[CG]TTAGTAACGCAACATGTGTTTCTCCGCGAC
CEP68 482 NM_015147.1 GGAGCGTCCACGTATTGGTGGAGCCG[CG]GACTTAGAGCTGCGATTCGCTG
MOV10 3963 NM_020963.1 GCCAACTTCCAGCTGCAGCGG[CG]ACTTTCAGTTTCATTTCCACGGAC
SASS6 1462 NM_194292.1 GTTCCGGGTATTAACCTGTGTGGCG[CG]GGGGCTGAGGCAGCCATGTT
HOXB5 648 NM_002147.2 ATGACGATCCGAGAATCGTTAGGGC[CG]ATTCAATGCGAGCCTCCGAGAGAG
PLXDC1 270 NM_020405.3 AGCTCGCCTCGCATGGTGGGTGCC[CG]GACCTGCCCCCGGCCTGCTTGCTGC
ANKRD10 3510 NM_017664.2 CCTGGAGCAGCCGGGTAGGGAG[CG]GAGCCTGGACCAGAGGACGCCA

157
PKDREJ 5982 NM_006071.1 GATGGCTCAGGAGGGCAGTTCAGCCC[CG]TGCAGACCACAGAGCTGACCACGGAGA
DOCK3 718 NM_004947.3 ACCCCCACGGAGGAGGAGAAATACGG[CG]TAGGTAGGTGAGGCTCAGGCCTG
IGF2BP2 152 NM_001007225.1 TCTGGTCGGGGTAGTCCACGAAGG[CG]TAGCCGGACTTCAGCAGGACCTGTCC
ATP6V0E 1277 NM_003945.3 ATCAGAACACTTTGCTGAGCCC[CG]GGTGACCGAATCCCTAGCTCTGGGGTGAGC
CYBA 3539 NM_000101.2 ACGTGCACTCACTCAGGCCGGA[CG]CCAGCGCCTGTTCGTTGGCCCACAT
SERINC4 2039 NM_001033517.1 CTTTGTCCTTAGGGCCTCAACACTG[CG]GCCACTCAGGCTGTTCTCTCCAGATT
PPHLN1 1771 NM_201438.1 GGGGCCCCGCAGGAGAGAAGGC[CG]CAGCTGAGGAGGCGTTTACCTTC
LOC54103 1439 NM_017439.1 TGAGAGGTATCTCAAGTGAGCCTTGTTA[CG]TGTTGGTAATGTTAAATGTTTTG
NPAL2 4066 NM_024759.1 CTCCTCCGGTGCGAGGTGTCCT[CG]GGGAGCCCGGCGGTCTGCGGCCTC
ARHGEF5 5293 NM_001002861.1 CCGGCACTTCCCAGCTCTGA[CG]CGGGAGCTTCTTTCACACCAATGGGGC
GRHL2 1587 NM_024915.1 CTGTAGCTCTTGTTCTGCCATCTCGGG[CG]CTCTCACACACCTTCACCTGCAC
LOC134466 609 XM_930378.1 AGATGGACGTACAAAATAAAGGAGAAAGTG[CG]GAAATGAGAAAGACTAAGGGAC
PDE8B 2320 NM_003719.2 GGACTCGGACGAGTCCAGCTCGCCC[CG]CCAGACCACCAGCGTGTCGCAGGGCCC
MGC57359 3972 NM_001004351.1 GATTGGAAGGACCGGACTCTGT[CG]GCGCCTGGCAGTTCAGGTGAAC
MGC26963 4086 NM_152621.3 TGGCTGTGTTAGTGCTTCGGACCTC[CG]TTAGAAGTAGCAGTTCATGGTGTTGAA
LOC643338 4101 XM_927997.1 GGGCTGTGATCAGAAAGGAAGCCG[CG]TGGTGACACATAAAGCAGGGCTGCC
DMRTA1 3726 NM_022160.1 CCGGGGTCTCTGCCAGGCTCA[CG]GGACAGCTGCACCTCTCAGCGTCTCC
DOCK2 5297 NM_004946.1 AGTCATTTGTCCCCGTCTGGATT[CG]AACCGAGATCTGACACCAAAGCTCA
RNF38 312 NM_022781.3 CGTGCCTCCTACCTACAAAACTC[CG]CAATCAAACAGTAACTGACCTCACGTAGTT
ACTR3B 4125 NM_020445.3 TTACAGGAGGAGAAAGGCGCCAGGCCT[CG]GAAATGGGGTCACGTTCATGT
MGC17330 933 NM_052880.3 CAGGTGATTGAACGACCAGTGTTTAAC[CG]AGGCCCCCTTGGCGGCGGCTCTGC
GJB2 377 NM_004004.3 AGGTTCCTGGCCGGGCAGTC[CG]GGGCCGGCGGGCTCACCTGCGTC
PDE4B 3746 NM_002600.2 CAGTTACAACCTACTACACAGCATCT[CG]TCCGTGCGATACGGTCACATTGTTATTCC
TNRC6B 2350 NM_015088.1 AAATCAAGGAGCCGGCACGTATGGATTC[CG]TTATAGGGCAGTACTGGTTGGAGA
SLC24A3 3039 NM_020689.3 CCGGGGTGGCTTTGCCAACCGG[CG]GAGTTGGCCAGCGGCGGGCCCTCC
VRK2 1051 NM_006296.3 GGCCTGTGTGAGGCTCCGCGGGC[CG]CTGCACTGCGAGGCCGACGCAGCTGGAG
C1orf34 61 XM_934649.1 CGCCGGAATGGGGTCAGAAGCT[CG]GGACCGAGTCAAATGCTGG
C11orf54 4205 NM_014039.2 CGTGATCCCTTCACCCTCT[CG]GACCGACTTCGGAGTCTCGATCCT
ZNF179 3022 NM_007148.2 TCTTTCCCTTCTGTCTCCATGG[CG]ACTCACCACCTCGGCTTGCCTGCAT
ATP11B 805 NM_014616.1 GATGGCCAGACCCACAGACA[CG]ACTTAATCCCACTCCCAGAACG
HCP1 437 NM_080669.2 GTTGGCCAGGAAGACCAGCGGCTCTAC[CG]GGCCCCGGCACAGCACGGCAGCC
C6orf194 5070 NM_001007531.1 GTGAGAAGCAAAATGGTAAAAGCGAAAT[CG]AAAAAGAGAAGTGGGTGTTCCA
BMS1L 3470 NM_014753.2 CAGGCTCTCCCCTGAAAGC[CG]TCCCCATGCCGGTCTCTTTTTTC
ACSL6 4305 NM_015256.2 ACGAATAGCCAGAGGGAGCCCCCCGACA[CG]AGGAAGAAGGTCAGCATGGCG
CSPG4 977 NM_001897.3 CCTCTAGTTCCGCCAGGCTGGGT[CG]GGGTCTCAGGCCCCTCACTCAC
LIMS2 4200 NM_017980.2 CCACCTGCCAGGAGGAAAGCCTGTGCC[CG]TGGACACACTGAGGAGGGCAGA
MDGA1 929 NM_153487.2 CAGCCTCTGTCCAATTTCCT[CG]CCTCCCCCAGGACCAATTAGA
TMEM125 5576 NM_144626.1 TCGGCCCTGCCTTCTCGGAT[CG]GATCCAGCACATCCAGGCTTCTC
LOC400221 113 XM_934745.1 GAAGTCCCTGGAGTAACCCATGTG[CG]CAGCCTGGCACTGTTTTCACTTGCCTTTGG

158
UTP15 1665 NM_032175.2 CACAGTCCGATTAATTGTCCTTGGGT[CG]AGGTGTCTCGTCGGACCCTTTGGGGCTC
ZBTB25 1808 NM_006977.2 GCAGCCCGCGATGGCCCCACGTGACCG[CG]TGTCTGGTAGCAGGGGAAAG
PCK2 5177 NM_004563.2 CCAACCCCCTAACTTCTAGA[CG]TCTGGCCCCTGTAGTCTCCCGCC
DDX43 1861 NM_018665.1 TTTATGGGTCACGGTTGAAAACATTTC[CG]GTGCAGTGGCTGACTGTAATCC
HMGB2 891 NM_002129.2 CATTTAGGTCCTGTCTGTCCCC[CG]CGTCGGCTCAGCCCTGCAGCGTTGGCT
KIAA0831 5790 NM_014924.3 GGTCTGCTGAGGGGCAACAGGTCC[CG]AAGCAGGGGGAGAGTTATATTAGAG
RASEF 2390 NM_152573.2 ATTCTCAATTTTACTGGCTTTCGTTAA[CG]CATTTTTGTGCGTCTAACGTTAAGGTCCCA
SAMD8 4107 NM_144660.1 CTCGGGCCCATCTGGAGCCT[CG]CGTCTTTTCCAGTGTGGGCCCCGC
KCNV2 40 NM_133497.2 GAGAGAGAAGCTGAAGCTGACTCAAAGATC[CG]ACTGGACCTGAACAGTGCCCCAGG
MGC11257 3153 NM_032350.3 TTGATGGAAAGGTCAATGAGAAAAC[CG]AGGTGGCAACCGACATGGAACG
ZNF467 607 NM_207336.1 GGGCAGGTGATGGTCCTAAGGCTC[CG]AGCCTGGAGTAGGTGTGGAA
C3orf41 3734 XM_934351.1 TCTGCTTGCTGAAAAGCTGCAGAGGC[CG]CCAGGAGCCCACGGTGAGCGG
COCH 1307 NM_004086.1 GACGCCTCTGTCCCTGTTTCTTTGT[CG]CTCCCAGCCTGTCTGTCGTCGTTTT
ZNF690 4991 NM_152455.2 CTGATCTCCCCCAGTATCTC[CG]CAGTCCTTCCCGAGGCCTTCTGC
KIAA1875 3841 NM_032529.1 GTTCTGGACTCGGACCTGTATGATG[CG]GATGGCTATGATGTCCCAGACCC
MTAP 3253 NM_002451.3 GCTTGGTTCCCTTAGTCCCGAG[CG]CTCGCCCACTGCAGATTCCTTTC
SPAST 1085 NM_014946.3 GCCGCCGCTGGGAGCCACCAGGCGG[CG]GAGAGGACAGCGACAGGAAGG
ZNFX1 3141 NM_021035.1 CGCGGCCTGGACAACTACTAGAGCGCCT[CG]GGCTGTGCTGCTCGAGACTACA
SLCO2A1 822 NM_005630.1 CGGCAGTGGCCGGAGGAGATTCG[CG]GAGCGGAGACTGAGCCAGCGA
PLA2G7 3574 NM_005084.2 CCTTTCCGCAGACCTGATGC[CG]ATCAGATTTACTCCCTGCTGAATTCACC
TXLNA 4302 NM_175852.3 CTTGGGATCTGCGGCTAGCCCCTG[CG]TAAAGAGGGACGCGTAGTCTTTT

Abstract (if available)

Abstract Cancer is the second leading cause of death in the United States and each year nearly half a million Americans die of the disease. The high rate of mortality is often not caused by tumors at the site of origin. In most cases, the spreading of tumor to distant organs is the cause for multiple organ failure and ultimately death. Therefore, it is imperative that tumors are detected early enough, where surgical intervention or administration of chemotherapeutic agents can benefit the patient. Studies have shown that cancers that are detected at early stage have far better prognosis than ones that are detected at late stage. For this reason, a lot of attention is devoted to early detection of cancer. However, some types of cancer, such as pancreatic cancer, arise at poorly accessible sites and are therefore often diagnosed late with poor outcomes.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Oghamian, Shirley (author)

Core Title The role of DNA methylation in early detection and progression of pancreatic cancer

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Biochemistry and Molecular Biology

Degree Conferral Date 2009-05

Publication Date 05/12/2011

Defense Date 03/17/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag DNA methylation,early detection,OAI-PMH Harvest,pancreatic cancer,progression

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Laird-Offringa, Ite A. (committee member), Shibata, Darryl K. (committee member), Stallcup, Michael R. (committee member)

Creator Email oghamian@usc.edu,virenie21@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2244

Unique identifier UC1185935

Identifier etd-Oghamian-2772 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-242078 (legacy record id),usctheses-m2244 (legacy record id)

Legacy Identifier etd-Oghamian-2772.pdf

Dmrecord 242078

Document Type Dissertation

Rights Oghamian, Shirley

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu