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University of Southern California Dissertations and Theses
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Colorectal cancer: genomic variations in insulin-like growth factor-1 and -2
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Colorectal cancer: genomic variations in insulin-like growth factor-1 and -2
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COLORECTAL CANCER:
GENOMIC VARIATIONS IN INSULIN-LIKE GROWTH FACTOR-1 AND -2
by
Hui-Lee Wong
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
(MOLECULAR EPIDEMIOLOGY)
May 2006
Copyright 2006 Hui-Lee Wong
UMI Number: 3237191
3237191
2007
UMI Microform
Copyright
All rights reserved. This microform edition is protected against
unauthorized copying under Title 17, United States Code.
ProQuest Information and Learning Company
300 North Zeeb Road
P.O. Box 1346
Ann Arbor, MI 48106-1346
by ProQuest Information and Learning Company.
ii
Dedication
WTK
1939-1991
“I wake to sleep, and take my waking slow.”
iii
Acknowledgements
I am thankful to the participants of the Singapore Chinese Health Study,
Singapore and the members (Dr. Jian-Min Yuan, Woon Puay, Canlan and Kazuko).
I am grateful to each member of my dissertation committee who has been
graciously accommodating in combining their diverse expertise. Their concerted
efforts have molded a naïve being to a more knowledgeable person in science, and in
others. As a mentor, Dr. Sue Ingles trained me in epidemiologic and biostatistics
analyses. Sue highly encouraged independence in thought whilst providing a
training environment of calm and flexibility. As a friend, Sue offered wisdom in the
adaptive stages of cultural shock, both professionally and socially. Dr. Peter Laird
provided discussions in the subject matter of DNA methylation and in due course,
more notably, he trained the student in the discipline and rigor of molecular biology.
Dr. Mimi Yu’s weekly discourse on epidemiology in summer 1999, delivered with
her distinct sense of humor, drew me into epidemiology and remains a model of
candor, intergrity and generosity. Dr. Duncan Thomas refused to treat me with
condensending standards by holding me to his expectations on intellectual rigor and
commitment; yet in the growth shifts from familiarity to the unknown, he has
provided constant guidance and unfailing support. Dr. Allen Yang infused the
second stage of this dissertation with his good cheer, enthusiastic adoption of the
latest ideas and technology and has expanded my social English language skill set
with Texan aphorisms. Dr. Darryl Shibata provided discussions on colon
carcinogenesis as well as jokes to buffer against grimness.
iv
I am indebted to other faculty members who were generous with their
guidance. I am humbled by Dr. Malcolm Pike’s (USC) deep sense of honor and
hence, has inspired me to strive for grace in interactions with future students. Dr.
Leslie Bernstein was instrumental in career choices. Dr. Hal Morgenstern (UCLA,
EPI201AB) taught me the foundations in epidemiology. Dr. Sander Greenland
(UCLA, EPI203, 204, 212) volleyed for openness and fidelity in the scientific
process.
I am deeply fortunate to have fellow comrades who are exceptional women
(Jun, Melissa, Wei; Ingles girls). Mihaela (Laird Lab) was unstinting in her
friendship with fellow human beings, despite her professed belief in Cioran’s
pessimisim. My family remains the reason for my ability to be here: Mum, Lucy,
Fang Chi, boy and chai.
v
Table of Contents
Dedication ii
Acknowledgements iii
List of Table viii
List of Figures x
Abstract xii
Chapter 1: Introduction
1.1 Overview 1
1.2 Insulin-like Growth Factor axis in cancer 1
1.3 Colorectal Cancer 5
1.3.1 Cellular: The genetic basis of colorectal cancer 5
1.3.2 Tissue: The pathological basis of colorectal cancer 7
1.3.3 Population: Geographic and Temporal Distribution 9
1.3.4 Population: Risk factors 10
1.3.4.1Physical activity 11
1.3.4.2Diet 11
1.3.4.3Others: Pharmaceutics 13
1.3.4.4 Summary of “western lifestyle” and colorectal cancer 14
1.4 Dissertation Outline 14
Chapter 2: Systematic Review of Insulin-like Growth Factor-1 and
Colorectal Cancer Risk
Abstract 16
2.1 Introduction 16
2.2 Material and Methods 18
2.2.1 Search protocol 18
2.2.2 Data abstraction and coding 18
2.2.3 Statistical analyses 19
2.2.3.1 Effect measurement 20
2.2.3.2 Design of review 20
2.3 Results 21
2.3.1 Studies characteristics 21
2.3.2 Minimally adjusted model 22
2.3.3 Maximally adjusted model 22
2.3.4 Subset Analyses 24
2.4 Discussion 25
2.4.1 Insulin-like Growth Factor-1 25
vi
2.4.2 Insulin-like Growth Factor-2 28
2.4.3 Insulin-like Growth Factor Binding Protein 3 30
2.5 Conclusions 32
Chapter 3: Nested Case-Control Study
Abstract 34
3.1 Introduction 35
3.2 Material and Methods 37
3.2.1 Study population 37
3.2.1.1 Control 38
3.2.1.2 Cases 39
3.2.2 Laboratory Methods 40
3.2.2.1 IGF1 promoter region sequencing 41
3.2.2.2 Genotyping 41
3.2.2.3 Serum Assays 43
3.2.3 Statistical Analyses 44
3.2.3.1 Genotype-colorectal cancer risk association 44
3.2.3.2 Haplotype inference and allelic co-segregation/association 45
3.2.3.3 Genotype-phenotype association 46
3.3 Results 46
3.3.1 Study characteristics 46
3.3.2 IGF1 -969(CA)
n
genotypes 49
3.3.3 IGF1 -533T/C genotypes 51
3.3.4 IGF1 haplotypes 54
3.3.5 IGFBP3 -202 A/C 55
3.3.6 Gene-gene interaction 55
3.3.7 Genotype-phenotype analyses 55
3.3.7.1 IGF1 genotypes and serum IGF1 levels 55
3.3.7.2 IGFBP3 genotype and serum IGFBP3 levels 57
3.4 Discussion 57
3.4.1 IGF1 genotype 58
3.4.2 IGFBP3 genotype 60
3.4.3 Gene-gene interaction 61
3.5 Conclusions 61
Acknowledgements 62
Chapter 4: Nested Case-Control Study
Abstract 63
4.1 Background 64
4.2 Materials and Methods 68
4.3 Results 73
4.4 Discussion 84
Acknowledgements 87
vii
Chapter 5: Epigenetic variation in the Insulin-Like Growth Factor 2
5.1 Introduction 88
5.2 Background 88
5.3 RNA-based LOI assay (gold standard) 95
5.4 DNA-based LOI assay 99
5.4.1 Material and Methods 102
5.4.2 Results 106
5.5 Validation of the new assay with measures of sensitivity and specificity 113
5.6 Conclusions and Future Studies 115
Chapter 6: Conclusions
6.1 IGF1 117
6.2 IGF2 119
Bibliography 122
viii
List of Tables
Table 2.1 Study characteristics for circulating IGF1 and IGFBP3 in
relation to colorectal cancer risk 23
Table 2.2 Study characteristics for circulating IGF2 and colorectal cancer 29
Table 3.1 Selected characteristics of colorectal cancer cases and controls,
the Singapore Chinese Health Study 48
Table 3.2 Distribution of the -969(CA)
n
allele frequencies
in Singapore
Chinese 49
Table 3.3 Odds ratios (ORs) and 95 percent confidence intervals (95%CIs)
for the 969(CA)
n
polymorphisms and colorectal cancer risk,
Singapore Chinese Health Study. 50
Table 3.4 Odds ratios (ORs) and 95 percent confidence intervals (95%CIs)
for the -533 T/C genotype and colorectal cancer risk, Singapore
Chinese Health Study. 53
Table 3.5 Estimated haplotype frequencies for IGF1 -969(CA)
n
and
-533T/C polymorphisms, Singapore Chinese Health Study 54
Table 3.6 Odds ratios (ORs) and 95 percent confidence intervals (95%CIs)
for the -202 IGFBP3 genotype and colorectal cancer risk,
Singapore Chinese Health Study. 56
Table 4.1 Locations of the evolutionarily conserved regions within 10 kilo
base pair upstream of the IGF1 translational start site and primers
for the re-sequencing of these regions in Singapore Chinese 69
Table 4.2 Selected characteristics of colorectal cancer cases and controls
for the IGF1 -2995C/A nested case-control study, the Singapore
Chinese Health Study 74
Table 4.3 Odds ratios (ORs) and 95 percent confidence intervals (95%CIs)
for the IGF1 -2995 C/A genotype and colorectal cancer,
Singapore Chinese Health Study 80
Table 4.4 Odds ratios (ORs) and 95 percent confidence intervals (95%CIs)
for the IGF1 -2995C/A genotype and colorectal cancer by
physical activity, Singapore Chinese Health Study 81
ix
Table 4.5 Genotype combinations of the IGF1 -2995 C/A and -533 C/T
and colorectal cancer risk, Singapore Chinese Health Study. 82
Table 4.6 Genotype combinations of the IGF1 -2995 C/A and -533 C/T
and serum IGF1 levels, Singapore Chinese Health Study 83
Table 5.1 The prevalence of loss of imprinting (measured as RNA-based
allele ratio) of the genes encoding Insulin-like Growth Factor-2
and H19 in the general population, persons at high risk for cancer
and adult cancer. 91
x
List of Figures
Figure 2.1 The schematic of study selection 19
Figure 2.2 A forest plot comparing IGF1 effect on colorectal cancer risk in
six prospective studies, ordered by the year of publication. 25
Figure 2.3 Graphical representation of publication bias in the analysis of
IGF1 and CRC risk (funnel plot). 26
Figure 2.4 Graphical representation of an influence analysis. 27
Figure 2.5 Comparison of the uppermost IGFBP3 category with the
referent group in six prospective studies. 30
Figure 2.6 Graphical representation for publication bias in the analysis of
IGFBP3 and CRC risk (funnel plot). 31
Figure 3.1 Insulin-like Growth Factor1 promoter polymorphisms 51
Figure 3.2 Serum IGFBP3, by IGFBP3 genotypes, Singapore Chinese
Health Study. 57
Figure 4.1 Genomic location of IGF1 regulatory polymorphisms and their
corresponding pairwise |D'| plots. . 67
Figure 4.2 Evolutionary conserved regions (ECR) in the 5’ untranslated
region of the human Insulin-like Growth Factor1 76
Figure 4.3. Predicted binding sites for transcription factors in the IGF1
promoter region 78
Figure 4.4 Serum IGF1, by IGF1 -2995 C/A genotypes 83
Figure 5.1 Comparison of the LOI assays based on mRNA expression
(left panel) and DNA methylation (right panel) 92
Figure 5.2 Regulation of the H19 imprinting center in the expression of
IGF2 and H19 (figure not drawn to scale) 95
Figure 5.3 Amplification plots for the G/G genotype (top panel) and A/A
genotype (bottom panel) of the IGF2 820G>A on the colorectal
cancer cell lines CaCO2 and Colo320 respectively. 97
xi
Figure 5.4 Amplification plots of the paired urothelium margins (left)
and the corresponding bladder tumor tissue (tumor). 99
Figure 5.5 General schema of the epigenetic haplotyping assay 102
Figure 5.6 Graphical representation of the light profile of CpG sites
generated by sequential nucleotide dispensation (Pyrogram
TM
). 107
Figure 5.7 Genomic bisulfite sequencing of 19 CpG sites within and
flanking the H19 imprinting center in the colorectal cancer
cell line, Colo205. 109
Figure 5.8 Test performance of the allele-specific methylation assay. 111
Figure 5.9 Representative pyrograms of normal and loss of imprinting in
tissues of bladder cancer patients. 113
Figure 5.10 Calculations of the test accuracy of the DNA-based LOI assay
as compared to the gold standard (RNA-based assay). 115
Figure 5.11 Position of the single nucleotide polymorphisms present in the
IGF2 mRNA transcripts and in the H19 imprinting center. 116
Figure 6.1 Biological heterogeneity at the level of the organ, cell and allele. 121
xii
Abstract
Insulin-like Growth Factor (IGF)-1 and -2 promote cancer growth.
Upregulation of IGF1 and IGF2 may mediate the effects of “western lifestyle” on
cancer. While IGF1 and IGF2 are genetically determined, known genetic variations
at these loci are not sufficient to account for the observed phenotypic variation. This
dissertation concentrates on the genomic variations in IGF1 (genetic) and IGF2
(epigenetic) that potentially explain cancer incidence rates in a rapidly westernising
population, the Singapore Chinese. The Singapore Chinese population affords a
wide variation of “western lifestyle factors”, including the lower ranges not available
in the occidental populations. The Singapore Chinese Health Study is a population-
based residential cohort study. From this ongoing cohort, a case-cohort sampling of
participants with available biospecimens forms the study population in this
dissertation. The first section of the dissertation is on IGF1 cis-acting genetic
variations. A resequencing survey of the IGF1 upstream regulatory region, based on
a comparative genomics strategy, identified two IGF1 single nucleotide
polymorphisms at positions -533 and -2995 base pair relative to the IGF1
transcriptional start site (+1). In both single marker analyses and in diplotype
analyses, the IGF1-533 C>T and IGF1-2995 G>A were associated with colorectal
cancer risk. These associations are the first reports of IGF1 SNPs and colorectal
cancer risk. Physical inactivity modified the effect of these SNPs. These
observations support the role of IGF1 and western lifestyle factors in colorectal
cancer. The second section of this dissertation is on the epigenetic variation of the
imprinted IGF2 gene. The current measurement of loss of imprinting requires intact
xiii
RNA - unavailable in existing epidemiologic biorepositories. Therefore, we
developed an assay for IGF2 imprinting based on allele-specific DNA methylation in
the H19 imprinting center. The allele-specific methylation assay will facilitate future
case-control studies of IGF2 germline LOI and cancer risk and may represent a new
platform for the development of high-throughput methods to screen for allele-
specific variation that is regulated by epigenetic processes.
1
Chapter 1: Introduction
1.1 Overview
Although colorectal cancer (CRC) is effectively treated if detected
early(Gustin and Brenner 2002), CRC remains a leading cause of cancer-related
death, second only to lung cancer in developed countries(Parkin 2001). Incidence
rates are rapidly accelerating in industrialized Asian (Singapore and Hong Kong),
East European and South American countries, possibly due to the westernizing of
lifestyles(Parkin 2001). While “Western lifestyle” (sedentary lifestyle and high
caloric diet) contributes to more than two-thirds of CRC(Lichtenstein et al. 2000),
the causally relevant mechanisms – vital for strategies that prevent, detect, and treat
CRC – remain obscure. Towards this end, this proposal examines the hypothesis that
genomic (genetic and epigenetic) variations in the insulin-like growth factor1 (IGF1)
signaling pathway mediates and/or modifies the “westernizing effects” on colonic
malignancy(Giovannucci 2002; Kaaks and Lukanova 2001) in the rapidly
westernizing Singapore Chinese population. This chapter introduces the proposed
candidates in colorectal cancer (IGF1 and IGF2), summarizes the known population
factors that impact colorectal cancer, outlines the proposed thesis and concludes with
the rationale for this study.
1.2 Insulin-like growth factor axis in cancer
The IGF axis includes a family of related growth factors (IGF1, IGF2,
insulin) that regulates diverse physiological processes via interaction with designated
receptors. IGF1 and IGF2 regulate normal growth and development via the tyrosine
kinase receptor IGF1-R(Romano 2003), and insulin regulates glucose metabolism
2
via the insulin receptors A and B(Denley et al. 2003). This proposal will focus on
the two ligands, IGF1 and IGF2, primarily driving the growth-related pathways
which are implicated in cancer development.
The central roles of IGF1 and IGF2 in integrating cellular proliferation and
survival responses predict that perturbations in IGF1 and IGF2 levels will predispose
to oncogenesis. In response to nutrient availability, IGF1 regulates cellular
proliferation, differentiation and apoptosis(Longo and Finch 2003). In response to,
among others, developmental cues, IGF2 is essential for embryonic development and
is involved in mitogenic and differentiation processes; much of its exact role in adult
physiology however remains to be elucidated(Clemmons 1989). Deregulation of the
IGF1-R signaling pathway drives colon cancer cell survival(Baserga et al. 2003;
Sekharam et al. 2003). Upon activation by IGF1 and IGF2, the receptor IGF1-R
activates cell growth and survival by crosstalking with other growth and apoptotic
pathways implicated in tumorigenesis i.e., phosphatidyl inositol-3-kinase and
Akt(Yamamoto K. 1992), mitogen-activated protein kinase and RAF(Moelling et al.
2002; Suzuki and Takahashi 2000), cyclooxygenase-2(Di Popolo et al. 2000; Levitt
and Pollak 2002) and steroid hormones(Dupont and Le Roith 2001; Yee and Lee
2000).
While IGF1 and IGF2 promote colonic carcinogenesis in vitro and in vivo,
convincing epidemiologic evidence upon which to base public health measures
remains elusive. Large variations in the levels of circulating IGF1, IGF2 and their
modulating proteins exist in the bloodstream among normal individuals(Pollak et al.
2004). Compared to individuals with lower circulating IGF1 or IGF2, the risk for
3
colorectal cancer is hypothesized to increase for individuals with levels at the higher
ends of the spectrum. The following two paragraphs summarize the epidemiologic
findings for IGF1 and IGF2, respectively, and proposed work to address the gaps in
the literature.
IGF1
A review of the six prospective studies in Caucasian and Asian populations
(Chapter 2) revealed that high levels within the normal range of circulating IGF1
associates with colorectal cancer risk. The assumption underlying these studies is
that variations in circulating IGF1 represent variations in bioactive IGFs in the target
cells and/or variation in IGF1-R signaling. Methodological limitations to the
endocrine measurements are: 1) the paracrine and autocrine effect of these
polypeptides are not accounted for, i.e. invalid exposure measurement and; 2)
serum/plasma IGF1 assays are notoriously imprecise. Age is the strongest predictor
of IGF1(Allen et al. 2003; Baibas et al. 2003; Chang et al. 2002; Holmes et al. 2002;
Lukanova et al. 2001; Probst-Hensch et al. 2003; Signorello et al. 2000; Yu and
Rohan 2000), and explains 40 percent of IGF1 variability(Unden et al. 2002); IGF1
levels progressively decline with advancing age. Lifestyle determinants of IGF1,
including physical activity and caloric intake (Allen et al. 2003; Baibas et al. 2003;
Chang et al. 2002; Holmes et al. 2002; Lukanova et al. 2001; Probst-Hensch et al.
2003; Signorello et al. 2000; Yu and Rohan 2000), contribute less than fifteen
percent(Chang et al. 2002; DeLellis et al. 2004) of the variability in circulating IGF1
levels. In contrast, genetic factors are estimated to account for 38 percent of the
interindividual variability. The extent the natural variation in the gene encoding
4
IGF1 modulates colorectal cancer risk has yet to be determined. Chapter 3 presents
an association study between colorectal cancer risk and the only reported IGF1
polymorphism to date, a microsatellite nearly one kilo basepairs upstream of the
translation start site. Given that the IGF1 microsatellite is unlikely to be causal,
Chapter 4 utilizes comparative genomics strategies in narrowing down genetic
candidates responsible for IGF1 phenotypic variation, and thereby, risk for colorectal
cancer.
IGF2
Only two prospective studies have examined IGF2 and colorectal cancer risk.
Both reported a non-statistically significant two-fold increase in risk. A potential
reason is that IGF2 endocrine levels possibly do not reflect the epigenetic variation
in IGF2 expression in the target colonic cells (detailed in Chapter 5). IGF2
expression in the majority of adult tissues, except for liver and brain, is subjected to
genomic imprinting where only the paternal allele is expressed. A potential
mechanism for IGF2 overexpression is an epigenetic abnormality termed as loss of
genomic imprinting (LOI). The majority of circulating IGF2 is derived from the
liver. Therefore, circulating IGF2 will unlikely reflect the pathologically elevated
levels of IGF2 due to LOI in most adult tissue. Instead, circulating IGF2 represents
the physiologically normal biallelic expression from the liver. Although IGF2 LOI is
a more valid measure of increased IGF2 levels in colonic tissues, an assay for LOI
usable in epidemiologic studies has yet to be developed. Chapter 5 details the
development of such an LOI assay and an outline of a grant proposal to validate its
use as a biomarker.
5
This dissertation assesses the extent to which genomic variations in IGF1 and
IGF2 modify colorectal cancer risk. The rationale for examining genomic variations
are based on observations that the range of IGF1 and IGF2 concentrations among
healthy individuals is considerable(Pollak et al. 2004), and that moderate allelic
differences may significantly contribute to cancer development(Hoogendoorn B.
2003; Yan et al. 2002; Yan et al. 2002). Taken together, although the common
variants of IGF1 and IGF2 are likely to have at most modest effects on cancer risk (<
two-fold), the population impact may be substantial due to the high prevalence of the
risk allele(s) present in the population.
1.3 Colorectal Cancer
1.3.1 Cellular: The genetic basis of colorectal cancer
The transformation of epithelial cells to carcinoma is a chronic process driven
by alterations in genes that regulate cell proliferation, differentiation, apoptosis,
genome stability, angiogenesis, invasion and metastasis(Hanahan and Weinberg
2000). The classical paradigm of colon cancer describes the morphological
transformation from presymptomatic transitional lesion (adenoma) to malignant
mass (carcinoma), paralleled with signature genetic(Fearon and Vogelstein 1990)
and epigenetic(Kondo and Issa 2004) alterations.
The stepwise transformation model(Fearon and Vogelstein 1990), extended
by in vitro and clinical observations, delineates colorectal carcinogenesis, whereby
(1) Mutations in the adenomatous polyposis coli tumor-suppressor gene
(APC) develop early in adenoma (polyp) development (>50% in precancerous
lesions)
6
(2) KRAS mutations arise during the polyp stage (>50% of polyps)
(3) Mutations in the tumor suppressor TP53 (>50% in carcinomas),
transforming growth factor (TGF)- /SMAD and deletions on chromosome 18q (70%
of colorectal cancer) mark the transition to malignancy.
While Fearon and Vogelstein (1990)(Fearon and Vogelstein 1990) have
delineated this classical adenoma-carcinoma multi-mutation pathway, alternatives to
their linear pathway of carcinogenesis have recently been proposed(Smith et al.
2002). The genes and mechanisms that modulate the environment that contribute to
sporadic cancer incidence (>95% of colorectal cancer) remains elusive.
Colorectal cancer is not one but many diseases; molecular subsets (reviewed
in (Lindblom 2001)) potentially are etiologic subgroups that can inform preventive
measures. Genomic instability is present in most intestinal malignancies(Sancho et
al. 2004). Based on molecular and morphological expressions of genomic
instability, two forms are present in colorectal cancer: microstallite instability (MSI
or MIN) and chromosomal instability (CIN), which are mutually exclusive in
colorectal cancer cell lines(Bhattacharyya et al. 1994; Sieber et al. 2002). Each of
these genetic instability phenotypes characterizes a specific hereditary CRC. MSI is
a hallmark of Lynch syndrome and CIN characterizes familial adenomatous
polyposis. In sporadic CRC, CIN tumors, found primarily in the distal colon,
predominate. MSI exists in 10-15 % of sporadic cancer, mainly in the proximal
colon(Perucho 1996). A fraction of sporadic CRC (< 20%) was reported not to
exhibit either MIN or CIN(Tang et al. 2004). MSI tumors are caused by impaired
mismatch repair that manifests as excessive somatic mutations in simple sequence
7
repeats whilst maintaining diploidy. CIN tumors are marked with aneuploidy
(abnormal chromosome content), chromosomal rearrangements and loss of
heterozygosity (LOH) due to an increased rate of gain or loss of either whole or
sections of chromosomes (reviewed in(Rajagopalan et al. 2003)).
CRC tumors can also be typed based on epigenetic aberrations for example
CpG island methylator phenotype (CIMP)(Toyota et al. 1999) that is observed in
~30% sporadic cancer with certain characteristics (proximal cancer, MSI+, family
history of cancer) (Frazier et al. 2003; Hawkins et al. 2002; Samowitz et al. 2005;
van Rijnsoever et al. 2002). CpG islands are stretches of cytosine-guanosine
associated with gene promoters(Bird 1986). CpG islands upstream of certain
expressed genes harbor unmethylated cytosine residues. Methylation on the CpG
island suppresses gene expression by disrupting the binding of transcription factors
and chromatin remodelling(Bestor 1998). A large population-based study (N=864)
has characterized the CIMP phenotype in sporadic colon cancer(Samowitz et al.
2005).
1.3.2 Tissue: The pathological basis of colorectal cancer
Colorectal cancer is mainly an epithelial cancer, carcinoma. Ninety percent
are adenocarcinomas that arise from the normal intestinal mucosa. The mucosa is
differentiated colorectal tissue that functions as a barrier against the external
environment and absorbing nutrients including fats, carbohydrate and fiber
(reviewed in(Sanderson and Naik 2000)). The mucosa achieves a large surface area
through folds of deep cavities termed as crypts. The colon has ~ 10
7
crypts from
which cancer can potentially arise. The two major etiologic hypotheses in CRC,
8
which are not necessarily mutually exclusive, are 1) stem cell hypertrophy; and 2)
secondary bile acids leading to genotoxic insults.
Stem cells
Organized at the bottom of each crypt are one to ten colon stem cells, giving
rise to differentiated colonic cells that rapidly divide and simultaneously migrate
upwards to the colonic lumen to undergo apoptosis and be sloughed off (Bach et al.
2000). The entire colon renews itself completely every 4 to 8 days(Lipkin et al.
1999), one of the most rapidly proliferating human organs. Environmental changes
on the enterocytes are translated to changes in gene expression in pathways
regulating cellular homeostasis. Each cellular division presents an opportunity for
deregulation of pathways in proliferation, apoptosis, differentiation and replication.
Secondary bile acids
Fecal levels of secondary bile acids are implicated epidemiologically in
colorectal carcinogenesis. Bile acids aid in the digestion and intestinal absorption of
lipids and fat-soluble vitamins. Intestinal microflora convert primary bile acids that
escape hepatic reabsorption to secondary
bile acids. Certain secondary bile acids,
particularly deoxycholic acid (DCA)(Martinez et al. 1998), are thought to promote
cancer growth through activating the protein kinase C signaling pathway(Huang et
al. 1999), a key regulator of proliferation, apoptosis and differentiation. Other bile
acids reduce carcinogenesis. For example, proliferation is suppressed by lithocholic
acid (LCA) via Vitamin D receptor signalling(Makishima et al. 2002) and
ursodeoxycholic acid (UDCA) via RAS, cadherin and cyclooxgenase 2
pathways(Khare et al. 2003; Wali et al. 2002).
9
Anatomic Subsite
CRC can be subgrouped into proximal colon (cecum, ascending colon,
transverse colon), distal colon (descending colon, sigmoid colon) and rectum
(rectosigmoid, rectum)(Iacopetta 2002). Colon and rectal cancers differ in genetic
profiles(Frattini et al. 2004) and in distribution by geographic location(Parkin 2001),
gender(Wu et al. 2004), ethnic background(Chattar-Cora et al. 2000; Nelson et al.
1997; Qing et al. 2003; Wu et al. 2004), and other risk factors(Wei et al. 2004).
Incidence of colorectal cancer has been migrating proximally in some populations
(European- and African-American(Cucino et al. 2002; Mostafa et al. 2004),
Australians(Miller et al. 2000), Japanese(Takada et al. 2002), Shanghai Chinese
(colon cancer)(Ji et al. 1998)) but not all (Singapore Chinese(Huang et al. 1999)).
Whether this trend can be attributed to the recent varying environment and screening
procedures remains to be confirmed.
1.3.3 Population: Geographic and Temporal Distribution
Colorectal cancer is the third most common cancer in the world(Parkin
2001). Global incidence of colorectal cancer (measured as age-standardized rates)
varies more than twenty-fold. Colorectal cancer is viewed as a cancer of western
countries. Nearly 50% of the Western population develops the colorectal cancer
precursor (adenoma) by age 70, and the lifetime CRC risk is 5%. Incidence in some
high-risk countries (North America, Western Europe, Australia & New Zealand,
Columbia/ South America) has either stabilized (UK) or actually decreased in the
younger segments in some populations (USA). However, the westernization of
rapidly developing populations is hypothesized to explain the rapidly increasing
10
CRC rates in traditionally low-risk regions (Asia, Africa), specifically populations in
Asia (Singapore Chinese, Japan, Hong Kong and Israel), Eastern Europe (Slovakia)
and Central America (Puerto Rico).
Both environmental and genetic factors underlie colorectal
carcinogenesis(Lichtenstein et al. 2000). Environmental factors contribute to more
than two-thirds of colorectal cancer incidence(Giovannucci et al. 2000; Lichtenstein
et al. 2000). Specifically, “western lifestyle” is implicated epidemiologically and
experimentally. Epidemiological evidence shows that the incidence in traditional
low-risk populations (e.g. Japan) that migrate to high-risk countries (USA) increases
within the first generation of migrants to nearly equal the host population’s
incidence(Le Marchand 1992)
, in
(Le Marchand et al. 1997). Experimentally, a
“Western-style diet” induces precancerous lesions in APC knock-out min mouse
models(Yang et al. 1998). Parallel observations were found in human populations,
specifically in Asians, where the westernization of lifestyles interacts with genetic
components to increase colorectal cancer risk(Le Marchand et al. 1999). The
genetics, “Western lifestyle” components, and their interactions that define cancer
risk remains to be elucidated.
1.3.4 Population: Risk factors
Factors confirmed to increase CRC risk in the general population, i.e. age,
ethnicity, level of education, positive family history of colorectal cancer and a
personal history of polyps, are not modifiable. Epidemiologic research has pursued
causal relations between the constituents of the “western lifestyle”, either in a
specific (nutrient, physical activity)(Giovannucci 2003; Key et al. 2004) or
11
aggregated (obesity, behavioral patterns)(Le Marchand et al. 1997) manner. Obesity
is a major determinant of CRC risk and explains 11% of colorectal cancer
incidence(Bergstrom et al. 2001; Bianchini et al. 2002), possibly through incessant
IGF1 signaling resulting from obesity-related hyperinsulinemia/insulin
resistance(Giovannucci 1995; McKeown-Eyssen 1994). Besides physical inactivity,
specific causative components of lifestyle remain unknown(Key et al. 2004). This
section will summarize components commonly studied in relation to the etiologic
pathways in colorectal carcinogenesis.
1.3.4.1 Physical activity
Physical activity attenuates colon cancer risk via mechanisms that may
include lower IGF1 levels and perturbations in interrelated pathways (decreasing
insulin levels and increasing prostaglandin levels) as well as other mechanisms
(increased gut motility and enhanced free radical scavenger system and immune
system)(Slattery 2004). Physical activity reduces risk of colon cancer, but not of
rectal cancer(Hunt et al. 2002). While the frequency, duration and intensity required
for preventive impact is unconfirmed, 3.5 to 4.0 hours of vigorous activity per week
is thought to lead to an approximate twofold reduction in risk (reviewed in(Slattery
2004)). However, physical activity does not account for the 20-fold variation
between developed and developing countries, implicating dietary components as
major risk factors(Key et al. 2004).
1.3.4.2 Diet
Because national fat consumption was observed to correlate with global
cancer incidence and mortality, dietary fat was identified as a candidate carcinogenic
12
component of the western diet. However, these ecologic correlations were probably
confounded by other components of Western lifestyle, such as positive energy
balance, physical inactivity and correlated dietary components(Willett 2000). In
analytical epidemiologic studies, all(Bostick et al. 1994; Chyou et al. 1996; Flood et
al. 2003; Gaard et al. 1996; Giovannucci et al. 1994; Goldbohm et al. 1994; Jarvinen
et al. 2001; Nagata et al. 2001; Pietinen et al. 1999; Terry et al. 2001; Thun et al.
1992) but one(Willett et al. 1990) large prospective study did not find either total fat
or specific fats (n-3 polyunsaturated fatty acids, n-6 polyunsaturated fatty acids, or
saturated fat) to be a risk factor for colorectal cancer. When gene-environmental
interactions is examined in the Singapore Chinese, Koh and colleagues showed that
persons with a high activity COX- genotype and high intake of its ligand, n-6 PUFA
are at high risk for colon cancer(Koh et al. 2004).
One dietary component, red or processed meat, but not total meat, marginally
increased risk for colorectal cancer in a meta-analysis(Sandhu et al. 2001). Well-
done meat but not processed meat is a risk factor in some (Gaard et al. 1996;
Giovannucci et al. 1994; Goldbohm et al. 1994; Jarvinen et al. 2001; Singh and
Fraser 1998; Willett et al. 1990) but not all(Bostick et al. 1994; Flood et al. 2003;
Pietinen et al. 1999; Sellers et al. 1998; Thun et al. 1992) studies. Well-done meat is
hypothesized to increase colorectal cancer risk through mutagenic heterocyclic
amines and polycyclic aromatic hydrocarbons(Gooderham et al. 1997).
Fruit and vegetable intake is associated with lower CRC risk(Johnson 2004).
The nutrient components associated with reduced risk are calcium (reviewed in(Lin
and White 2004)) and folate intake (reviewed in(Giovannucci 2002; Kim 2003)).
13
Calcium, with the help of Vitamin D, is thought to protect against colorectal cancer
through their anti-mitotic and pro-differentiation actions. Adequate folate levels are
required to prevent DNA hypomethylation and the mis-incorporation of uracil
instead of thymine into DNA(Kim 2004).
While fiber protects against colon carcinogenesis in mouse models(Reddy
1987), the role of fiber remains controversial in epidemiological studies. Fiber did
not lower cancer risk in randomized trials. These findings were predicted by one
large (Nurses Health Study(Fuchs et al. 1999)) and two smaller(Pietinen et al. 1999;
Terry et al. 2001) observational prospective studies. However, these null findings
were later challenged by two other large prospective studies, the European
Prospective Investigation into Cancer and Nutrition (EPIC)(Bingham et al. 2003),
n=1064 adenocarcinomas; and the Prostate, Lung, Colorectal, and Ovarian
(PLCO)(Peters et al. 2003) cancer screening study, n= 3591 adenomas. In contrast
to the previous three negative studies, the EPIC and PLCO studies examined
different populations and the range and type of fiber intake was wide (12 36 g/d).
1.3.4.3 Others: pharmaceutics
In addition to demographic and dietary factors, two common pharmaceutical
modalities in the USA are thought to reduce colon cancer risk: non-steroidal anti-
inflammatory drugs (NSAIDs) and hormone replacement therapy (HRT) in post-
menopausal women(Calle 1997). The low prevalence of NSAIDs usage (< 5%) and
HRT among Singapore Chinese precludes them from being examined in this
dissertation. However, the cross-talk of insulin signaling with NSAIDs(Slattery
14
2004) and sex steroids should be pursued in populations with high prevalence of
NSAIDs usage or hormone replacement therapy (HRT).
1. 3.4.4 Summary of “western lifestyle” and colorectal cancer
Colorectal cancer incidence is attributable to physical inactivity (attributable
fraction: 14-16%)(Slattery 2004) and western style diet (attributable fraction:
12%)(Slattery 2000). The specific dietary components are unknown. Dietary
measurement errors are notorious for masking the etiological factors within the
“western lifestyle”. Less prone to measurement error are variants in genes encoding
the proteins that mediate these “western lifestyle” carcinogenetic effects. Candidate
proteins hypothesized to mediate the obesity- related “western lifestyle” carcinogenic
effects are in the IGF system(Giovannucci 1995; Komninou et al. 2003; McKeown-
Eyssen 1994). Obesity-related metabolic disorders reflective of behavioral patterns
in developed countries, have currently reached a pandemic scale(Haffner and
Taegtmeyer 2003; Seidell 2000). Certain non-Caucasian populations (Asians and
Latinos) may be more genetically susceptible to these metabolic disorders(Chandalia
et al. 2003); westernization of their lifestyles elevates this risk. Identification of the
specific factors will inform prevention and therapeutic strategies.
1.4. Dissertation Sections
The body of the dissertation is comprised of Chapters 2 to 6, each
corresponding to a self-contained manuscript. Chapter 2 presents a literature
review/meta-analysis of epidemiologic studies on the IGF system and colorectal
cancer risk. Chapter 3 examines whether polymorphisms in the IGF1 promoter
region are associated with colorectal cancer risk in a cohort of Singapore Chinese.
15
Chapter 4 uses a comparative genomics strategy to examine the IGF1 allelic
architecture. Chapter 5 outlines the development of a method for epidemiologic
measurement of IGF2 loss of imprinting. Chapter 6 concludes the dissertation with
an evaluation of the results in the light of the current literature and future research
proposals.
16
Chapter 2: Colorectal cancer and insulin-like growth factor-1 signaling
pathway: a systematic review
Abstract
The insulin-like growth factor (IGF)-1 signaling pathway regulates cellular
growth in response to nutrients by activating the receptor, IGF1-R. The ligands for
the receptor (IGF1, IGF2) and the IGF1 major binding protein, IGFBP3, are possibly
involved in colonic malignancy. A systematic review was conducted of prospective
follow-up studies of serum IGF1, IGF2 and IGFBP3 levels with the incidence of
colorectal cancer. Meta-analyses were conducted on IGF1 and IGFBP3. The
scarcity of IGF2 studies did not permit a formal analysis. Six studies with a total of
959 cases and 1955 controls were identified; all were nested within prospective
cohorts. Elevated circulating IGF1 was associated with colorectal cancer risk
(combined odds ratios contrasting the uppermost and referent category: 1.56, 95
percent confidence interval: 1.15 - 2.14). Possible heterogeneity in the results by
assay characteristics and anatomic site was assessed. The IGF1 carcinogenic effect
is possibly specific to colon cancer (1.86, 1.07 – 3.23) but not rectal cancer (0.53,
0.23 – 1.20). The association between IGFBP3 and colorectal cancer risk is
inconsistent, in part, by the type of assay. Prospective studies defining the role of
IGF2 and IGFBP3 in cancer risk have potential impact on early detection and risk
assessment strategies.
2.1 Introduction
IGF1 exerts, through the insulin-like growth factor (IGF)-1R, potent
mitogenic and anti-apoptotic actions on normal and transformed cells(Clemmons
17
1989; Jones and Clemmons 1995), either systemically (endocrine)(Giovannucci
2001; Wu et al. 2002) and/or locally (autocrine/paracrine)(D'Ercole A. 2003).
Although extensive evidence implicates IGf1 as promoting colorectal cancer (CRC)
growth and progression, both in vitro(Fukuda et al. 2002; Guo et al. 1998; Hague et
al. 1997; Koenuma et al. 1989; Lahm et al. 1992; Reinmuth et al. 2002; Remacle-
Bonnet et al. 2000; Sekharam et al. 2003; Tricoli et al. 1986; Whithead et al. 1990)
and in mouse models(Hassan and Howell 2000; Hirose et al. 2004; Wu et al. 2002),
epidemiologic observations has been controversial. Specifically, among prospective
studies where bias of observations due to cancer cachexia depletion of IGF1 levels
are unlikely, two studies found elevated plasma IGF1 associates with increased
colorectal(Ma et al. 1999) or colon cancer risk(Nomura et al. 2003), two found
positive associations of borderline significance(Giovannucci et al. 2000; Palmqvist et
al. 2002) and two studies failed to find an association(Kaaks et al. 2000; Probst-
Hensch et al. 2001). To investigate the heterogeneity besetting the literature, we
quantitatively reviewed existing prospective studies on the IGF1-R ligands, IGF1
and IGF2, and the major modulator for IGF1, IGFBP3. Subgroup analyses
according to potential sources of heterogeneity were undertaken, where not limited
by sparse number of studies. Meta-regression was not performed due to paucity of
studies in the relevant subgroups. Any observed statistical heterogeneity was
examined by performing influence analyses of individual studies.
18
2.2 Material and Methods
2.2.1 Search protocol
Studies published between 1966 and 2004 were identified via a search for all
entries indexed with the keywords “insulin-like growth factor colon cancer risk OR
BMI OR rectum OR colorectal” in the publication database, MEDLINE (National
Library of Medicine, Washington, D.C.). Additional studies were systematically
searched in the reference lists in the identified articles and published reviews.
Eligible studies were limited to English-language-citations and full-text published
studies (i.e., meeting abstracts were excluded). No attempts were made to acquire
unpublished data. Studies were included if the study design was prospective, the
endpoint was frank carcinoma, and if information was available on the following:
effect estimates (odds ratios) or comparison with disease-free group, controlled
variables (held constant in analysis or stratified in design), sex, follow-up period and
anatomic site (colon and rectum). Where possible, methodology conformed to the
proposed consensus criteria for observational studies(Stroup et al. 2000).
2.2.2 Data abstraction and coding
Of the 59 eligible studies, 6 were included in this review (Figure 2.1). The
identified studies investigated either colorectal, colon or rectum cancer. Effect sizes
were extracted from the included studies and calculated, where necessary. Authors
were not contacted for missing data. We extracted information on specific study
characteristics from each study in assessing sources of heterogeneity (Table 2.1) in
sub-group analyses and meta-regressions.
19
Figure 2.1. The schematic of study selection
Publications identified
from electronic searches
n=59
Studies retrieved for
evaluation of inclusion
criteria
n=25
Non-epidemiologic studies
excluded
n=34
Studies excluded based on
inclusion criteria
n=16
Studies assessed for
inclusion in analyses
n=9
Studies eliminated (n=2):
Two populations not
representative of the
general population
(acromegalics).
No studies included from a
review of reference lists
Studies used in analyses
n=7
20
2.2.3 Statistical analyses
2.2.3.1 Effect measurement
All six studies measured total IGF1, IGF2 and IGFBP3 in the serum(Kaaks et
al. 2000; Nomura et al. 2003; Probst-Hensch et al. 2001) or plasma(Giovannucci et
al. 2000; Ma et al. 1999; Palmqvist et al. 2002). All assays were performed blinded
to the case status and provided intra-assay reliability estimates less than 11%.
Absolute differences of IGFs between cases and non-cases are uncomparable
because assay methodologies markly differed among the studies: enzyme-linked
immunosorbent assay (Diagnostic Systems Laboratories, TX)(Giovannucci et al.
2000; Ma et al. 1999; Nomura et al. 2003), immunoradiometric assay (Immunotech,
Marseille)(Kaaks et al. 2000; Palmqvist et al. 2002), and radioimmunoassay (Nichols
Institute, CA)(Probst-Hensch et al. 2001). Therefore, odds ratios (ORs) were
estimated from a random effects model of odds ratios between the uppermost
(quintile, quarter and tertile) and referent category.
2.2.3.2 Design of review
To assess whether IGF1 or IGFBP3 increases the risk of colorectal cancer and,
whether mutual adjustment of IGF1 and IGFBP3 was necessary to observe the effect,
two meta-analyses were performed and compared. None of the studies presented
crude odds ratios (unadjusted for any confounders) and hence, unadjusted odds ratios
were not considered in the meta-analyses. The first analysis is the minimally-
adjusted model (model I) that included all eligible studies suitable for meta-analysis
accounting for the anthropometric measures (age, sex, socio-economic status,
alcohol, body mass index). The second, fully-adjusted model (model II), was
21
restricted to studies that further mutually adjusted for IGF1 and IGFBP3. The
independent effect of IGF1 from IGFBP3 and vice versa was examined by
contrasting model I and II. Since many studies did not present sufficient data to fit
model I, and results between both models were similar, ORs estimated from Model II
were presented in the following subset analyses. Heterogeneity of effect size was
assessed using the methods of Mantel-Haenszel. The combined odds ratios were
estimated from both random(DerSimonian and Laird 1986) and fixed effects models.
The influence of each individual study on the combined estimate was graphically
explored by conducting sensitivity analyses. Publication bias was graphically
examined with the funnel plot and formally tested with Begg’s and Egger’s test.
To investigate whether either the measurement of exposure (IGF1 assay) or
outcome (anatomic site: colon and rectum) explains any observed statistical
heterogeneity, we conducted subgroup analyses. Meta-regression was not performed
due to paucity of studies in the relevant subgroups (<10 studies in the meta-
analyses)(Higgins et al. 2002). All analyses were performed with the module meta
in the Stata Statistical Software, version 8.0 (STATA Corp., College Station, Tex).
2.3 Results
2.3.1 Study characteristics
For IGF1 and IGFBP3, six observational follow-up studies met the priori
inclusion criteria (Table 2.1). All six were case-control designs nested within cohort,
matched at least on age. All studies adjusted, at either the stage of design or
analyses, for anthropometric measures (BMI, height, etc). Smoking was controlled
in all but one(Giovannucci et al. 2000), alcohol intake in all but two(Kaaks et al.
22
2000; Palmqvist et al. 2002). All considered mutual adjustment of IGF1 and
IGFBP3.
For IGF2, two(Hunt et al. 2002) of three(Hunt et al. 2002) prospective studies
reported effect measures. No further formal analyses were performed for IGF2.
Meta-analyses were performed for IGF1 and IGFBP3.
2.3.2 Minimally adjusted model
Two(Giovannucci et al. 2000; Nomura et al. 2003) of the six studies were
not included because either the odds ratios and/or confidence intervals for IGF1 and
IGFBP3 not mutually adjusted were not available. Compared to the lowest category,
persons in the highest category of circulating IGF1 were at a 1.35 times increased
risk of colorectal cancer (combined OR: 1.35; 95 percent confidence interval: 0.94,
1.95).
2.3.3 Maximally adjusted model
All six studies mutually adjusted for IGF1 and IGFBP3. Those in the
uppermost category of circulating IGF1 had a 1.56 times increased colorectal cancer
risk than of those in the referent category (combined ORs: 1.56, 95 percent
confidence interval: 1.15, 2.14).
Table 2.1. Study characteristics for circulating IGF1 and IGFBP3 in relation to colorectal cancer risk
Study (population) Sample size Assay
a
(Intrabatch coefficient)
Controlled variables Subjects(gender)
Follow-up
Nomura, 2003
Japanese-American Cancer
Study
Controls: 282
Colon: 177
Rectal: 105
IGF1: ELISA (<5%)
IGF2: N/A
IGFBP3: ELISA (<7%)
Design: Age, Year of Birth (1 year)
Analysis: BMI, smoking history, alcohol intake
9,345 (M)
8yrs
Hunt, 2002
New York University Women’s
Health Study
Controls:
CRC: 102
IGF1: N/A
IGF2: IRMA (13%)
IGFBP3: N/A
Design: age, date and menopausal status at enrollment into
the cohort, number of blood samples given over time,
and time of the day at which the first sample had been given
Analysis: smoking, BMI, IGFBP1, IGFBP2, IGF-1
Palmqvist, 2002
Northern Sweden Health &
Disease Cohort
Controls: 336
CRC: 168
Colon:110
Rectal: 58
IGF1: IRMA (10.9%)
IGF2: N/A
IGFBP3:IRMA (4.5%)
Design: age (±6 months), sex, subcohort,
and date (±2 months) at blood sampling, and
fasting time (<4 hours, 4–8 hours, or >8 hours).
Analysis: smoking status at the time of blood donation,
BMI, and height
30,300 (M)
31,900 (F)
N/A
Probst, 2001
Shanghai Men Health Study
Controls: 661
CRC: 135
IGF1: RIA (5.4%)
IGF2: IRMA (3.2%)
IGFBP3:IRMA (6.5%)
Design: N/A
Analysis: cigarette smoking(#cig/day),
alcohol intake (g ETOH/day), BMI (actual values) at baseline
18, 244 (M)
12 years
Kaaks, 2000
New York University Women’s
Health Study
Controls: 200
CRC: 102
Colon: 75
Rectal: 26
IGF1: IRMA (5.6%)
IGF2: N/A
IGFBP3:IRMA (2.6%)
Design: age, menopausal status, day of menstrual cycle
(for premenopausal women), and time of last food consumption
Analyses: smoking status, IGFBPs
14, 275 (F)
13 years
Giovannucci, 2000
Nurses Health Study
Controls:158
CRC:79
IGF1: ELISA (2.5%)
IGF2: N/A
IGFBP3: ELISA(3.9%)
Design: N/A
Analysis: age, smoking, BMI, and alcohol intake
32,826 (F)
5 years
Ma, 1999
Physician Health Study
Controls: 318
CRC: 193
IGF1: ELISA(2.9%)
IGF2: ELISA(1.7%)
IGFBP3: ELISA(3.2%)
Design: age, smoking
Analyses: BMI, alcohol intake
22,071 (M)
14 years
a
ELISA: enzyme-linked immunoabsorbent assay, Diagnostic Systems Laboratories (TX, USA); IRMA: double-antibody, immunoradiometric assay;
(Immunotech Marseille, France); RIA: radioimmunoassay, Nichols Institute (CA, USA); N/A: not available; CRC: colorectal; N/A: not applicable
b
design: stratified variable as frequency- or individual-matched; analyses: included in multivariate regression models
23
2.3.4 Subset analyses
For IGF1, only three(Kaaks et al. 2000; Nomura et al. 2003; Palmqvist et al.
2002) studies studied colon and and two(Nomura et al. 2003; Palmqvist et al. 2002),
rectal. The odds ratios comparing the uppermost and baseline category of circulating
IGF1 with colon cancer was 1.86 (95 percent confidence interval: 1.07, 3.23) and for
rectal was 0.53 (0.23, 1.20). Although various IGF1 assays were used to measure
total and fragmented IGF1 species, all six studies observed similar increase in risk
(data not shown).
25
2.4 Discussion
2.4.1 IGF1
Figure 2.2. A forest plot comparing IGF1 effect on colorectal cancer risk in six
prospective studies, ordered by the year of publication. The filled square
corresponds to the odds ratio of the uppermost IGF1 category with the referent
group; the size of the square indicates the weight of the study on the combined
estimate and the horizontal line, 95 percent confidence interval. The diamond
indicates the summary fixed-effects combined estimate of the six studies where the
left and right extremes represent the corresponding confidence intervals.
Giovannucci
2000
Probst
2001
Palmqvist
2002
Nomura
2003
Odds Ratio
.25 .5 2.5
7.5
Combined
Ma 1999
Kaaks
2002
1 5
26
Figure 2.3. Graphical representation for publication bias in the analysis of IGF1
and CRC risk (funnel plot). Each circle represents the OR for CRC contrasting the
highest and lowest category in circulating IGF1 (y axis) against the standard error of
the natural logarithm of each study OR (x axis). The size of the circle parallels the
sample size. The horizontal line represents the fixed effect summary estimate
(inverse-variance weighted); the sloping lines, expected 95 percent confidence
interval given lack of heterogeneity amongst the studies.
Begg's funnel plot with pseudo 95% confidence limits
Odds
Ratio
Standard error of the natural logarithm the odds ratio
0 .2 .4 .6
-.5
0
.5
1
1.5
27
Figure 2.4. Graphical representation of an influence analysis. The meta-analysis
estimate of IGF1 and CRC risk is computed omitting one study at a time.
Elevated levels of circulating IGF1 moderately increased risk for colorectal
cancer (combined ORs: 1.56, 95 percent confidence interval: 1.15, 2.14; Figure 2.2).
Our results are concordant with a previous meta-analysis(Renehan et al. 2004)
estimate of 1.58 (1.11, 2.27). While the funnel-plot asymmetry provided no
evidence for publication bias (Figure 2.3), the possibility of unpublished null results
cannot be excluded. Graphical analysis and formal analysis (Begg’s test: 0.85;
Egger’s test: 0.85) for heterogeneity demonstrated a lack of statistical heterogeneity.
Although our formal analyses may lack the power to detect heterogeneity, we
consider the combined ORs as valid because the estimates from the random and
fixed effects models were essentially the same. None of the included studies
appeared to have a major influence on the combined estimate (Figure 2.4).
1.02
1.56
Summary Odds Ratio
1.15
2.13 2.33
Nomura
2003
Palmqvist
2002
Probst-Hencsh
2001
Kaaks
2002
Giovannucci
2000
Ma
1999
Study ommited
28
Adjustment for IGFBP3 was hypothesized to be necessary to accurately
measure bioactive IGF1(Giovannucci 2001; Yu and Rohan 2000). In contrast to this
assumption and in agreement with a previous meta-analysis(Renehan et al. 2004),
our meta-analyses found that adjustment with IGFBP3 was immaterial.
Our sub-set analyses found that high levels of IGF1 increased the risk of
colon cancer and not rectal cancer. However, in the individual studies, only
one(Nomura et al. 2003) of the four(Kaaks et al. 2000; Ma et al. 1999; Nomura et al.
2003; Probst-Hensch et al. 2001) individual studies that examined sub-site specificity
observed heterogeneity by subsite. Anatomic etiologic distinctions are reflected at
molecular, cellular and population levels. Colon and rectal cancers differ in genetic
profiles(Frattini et al. 2004), embryologic development, distribution of gender(Wu et
al. 2004), ethnic background(Chattar-Cora et al. 2000; Nelson et al. 1997; Qing et al.
2003; Wei et al. 2004), geographic location(Parkin 2001) and risk factors
distribution(Wei et al. 2004). Due to recent varying environment and screening
procedures, colorectal cancer has been migrating proximally in some (European- and
African-American(Cucino et al. 2002; Mostafa et al. 2004), Australians(Miller et al.
2000), Japanese(Takada et al. 2002), Shanghai Chinese(Ji et al. 1998)) but not all
(Singapore Chinese(Mostafa et al. 2004)) populations.
2.4.2 Insulin-like Growth Factor-2
Two studies reported a non-statistically significant two-fold association
between elevated circulating IGF2 and colorectal cancer risk: the New York
Women’s Health Study (OR:2.74;95%:1.67-4.50) and the Shanghai Chinese Men
29
Health Study (OR:2.02; 95%CI: 0.83 – 4.93). In addition, publication bias of
unreported null associations is possible.
Table 2.2 Study characteristics for circulating IGF2 and colorectal cancer
Author, year Sample size
(colorectal
cases)
Subjects(gender)
Follow-up
Controlled variables
Risk factor
Hunt, 2002
New York University
Women’s Health
Study
n=102 14,275 (F)
Follow-up: 6 years
Considered covariates: smoking,
BMI, IGFBP1, IGFBP2, IGF-1
IGF2
Probst 2001
Shanghai Men Health
Study
n=135 18, 244 (M)
Follow-up:12 years
Adj: smoking, BMI, alcohol
IGF1, IGF2, IGFBP3
Ma, 1999
Physician Health
Study
n=193 22,071 (M)
Follow-up: 14 years
Adj: IGFBP-3, age, smoking,
BMI, and alcohol intake
IGF1, IGF2, IGFBP3
Although serum/plasma IGF2 was not associated with colorectal cancer risk,
extensive in vitro evidence(Zarrilli et al. 1994), mouse models(Hassan and Howell
2000) and clinical prevalence studies have implicated IGF2 overexpression in
colonic carcinogenesis. A possible reason is that circulating IGF2 does not reflect a
potential mechanism of IGF2 overexpression termed as loss of imprinting. The
expression of IGF2 is regulated by genomic imprinting. In most adult tissues, except
for the liver, IGF2 is expressed from the copy inherited from the father; the maternal
copy is silenced by biochemical imprints (Giannoukakis et al. 1993; Ohlsson et al.
1993). Loss of genomic IGF2 imprinting leads to IGF2 over-expression and, is a
risk factor for colorectal cancer(Cui et al. 2003). The product of the IGF2 gene
30
regulates cellular growth either at the local tissue sites (autocrine and paracrine) or
systematically via circulating levels in the blood stream (endocrine). The liver is the
source of endocrine IGF2 levels (measured epidemiologically as serum or plasma
IGF2) where alternate promoter usage expresses IGF2 transcripts from both parental
alleles and therefore, not subjected to genomic imprinting. Because hepatic-derived
IGF2 transcripts do not reflect the carcinogenic consequences of loss of imprinting,
we propose that circulating IGF2 is not a valid epidemiologic measurement of
elevated biological levels of IGF2 in the target tissues. Rather, to link IGF2 to
cancer risk, loss of IGF2 imprinting should be measured in future epidemiology
studies.
2.4.3 Insulin-like Growth Factor Binding Protein 3
Figure 2.5. Comparison of the uppermost IGFBP3 category with the referent
group in six prospective studies.
Odds Ratio
.25 .5 1 2.5 5 7.5
Ma
1999
Giovannucci
2000
Kaaks
2002
Probst
2001
Palmqvist
2002
Nomura
2003
31
Figure 2.6. Graphical representation for publication bias in the analysis of IGFBP3
and CRC risk (funnel plot). Each circle represents the OR of CRC contrasting the
highest and lowest category in circulating IGFBP3 (y axis) against the standard error
of the natural logarithm of each study OR (x axis). The size of the circle parallels the
sample size. The horizontal line represents the fixed effect summary estimate
(inverse-variance weighted); the sloping lines, expected 95 percent confidence
interval given lack of heterogeneity amongst the studies.
In contrast to the Nurses Health Study and Physicians’ Health Study which
reported that lower levels of IGF1-adjusted IGFBP3 increases colorectal cancer risk,
the other four studies were either null or found a non-significant increased risk
(Figure 2.5). Thus, a combined effect was not estimated due to heterogeneity among
the studies (p=0.004; Figure 2.6). The two studies with the inverse association
measured IGFBP3 with enzyme-linked immunoabsorbent assay (Diagnostic Systems
Laboratories, TX), as compared to the other four studies that measured with double-
antibody,
immunoradiometric assay(Immunotech Marseille, France). IGFBP3
undergoes post-translational modifications to regulate its physiological functions, in
Begg's funnel plot with pseudo 95% confidence limits
Odds
Ratio
Standard error of the natural logarithm
0 .2 .4 .6
-2
-1
0
1
32
particular proteolysis by other IGFBP-related proteins. Assay differences in species
of intact and proteolysed polypeptides result in measurement of distinct IGFBP3
physiological entities and may contribute to the observed inconsistencies in cancer
risk associations(Diamandi et al. 2000). Apart from measurement differences, the
heterogeneity in the epidemiologic studies may reflect the in vitro and in vivo
literature, with IGFBP3 reported in both growth-promoting (anti-apoptotic, pro-
proliferative)(Kansra et al. 2000) and growth-inhibitory (pro-apoptoptic, anti-
proliferative and pro-differentiation)(Kirman et al. 2004; MacDonald et al. 1999;
Williams et al. 2000) actions on colonic cells.
2.5 Conclusions
Limitations to inferences from the meta-analyses include: the inherent biases in
the observational studies, the small number of studies and the possible bias in the
subset-analyses due to inclusion based on available effect measures. However, to
minimize multiple comparison biases, the subset analyses were constrained to two.
On the methodological question, our meta-analyses concur with a previous meta-
analysis(Renehan et al. 2004) that mutual adjustment of IGF1 and IGFBP3 is not
required to quantify the bioactive polypeptides species. On the etiologic question of
whether colon and rectum cancer arise from differing pathways, our meta-analyses
found that IGF1 appears to contribute to cancer development in the colon.
These analyses do not address the conflicting correlation between the
documented decline in circulating IGF1 and increase in cancer risk with progressing
age(Renehan et al. 2004), nor whether the association observed with IGF1 is an
33
effect, rather than a cause, of epithelial cell proliferation during cancer
development(Rosen and Pollak 1999). However, the systematic review offers two
suggestions for future studies examining the normal variation in the IGF1 signaling
pathway and colorectal cancer risk. Firstly, current epidemiologic measurement of
IGF2 is possibly invalid and the extent to which IGF2 increases colon cancer risk
remains unanswered. The receptor for both IGF1 and IGF2 (IGF1-R) drives colon
cell survival and is expressed in most, if not all, human colon cancers(Singh et al.
1994); only 50% are responsive to IGF1(Singh et al. 1994) and the autocrine role of
IGF2 in colorectal cancer(Zhang et al. 1997) is unaccounted for. Secondly, a
specific assay for physiologically relevant IGFBP3 peptide moieties is needed to
exclude one artefactual source of the conflicting IGFBP3 role in cancer.
34
Chapter 3: A new single nucleotide polymorphism in the Insulin-like Growth
Factor 1 regulatory region associates with colorectal cancer risk in Singapore
Chinese.
Abstract
Elevated levels of plasma insulin-like growth factor 1 (IGF1) are a potential
risk factor for several cancers, including colorectal cancer. Physiologic levels of
plasma IGF1 vary greatly; this variation may be in part genetically determined. We
identified two single nucleotide polymorphisms (SNPs), in perfect linkage
disequilibrium (LD) with each other and in partial LD with a previously studied
cytosine-adenine microsatellite (-969(CA)
n
). We investigated one of the SNPs, -
533T/C, and the -969(CA)
n
in relation to the risk of colorectal cancer in a case-
control study nested within a cohort of Singapore Chinese (cases/controls =
290/873). The (CA)
21
allele, rather than the previously implicated (CA)
19
allele, was
associated with a reduced risk of colorectal cancer (odds ratio for 21/21 versus all
other genotypes =0.48; 95 percent confidence interval= 0.28, 0.84). For the -533C/T
SNP, persons carrying one or more copies of the C allele had a decreased in risk of
colorectal cancer compared to non-carriers (odds ratio for CC/CT versus TT =0.58;
95 percent confidence interval= 0.41, 0.82). This association was specific for colon,
as opposed to rectal cancer and, was modified by age. We also examined a
functional insulin-like growth factor binding protein (IGFBP3) promoter SNP, -202
A/C, previously reported to predict serum IGFBP3 levels. While we were able to
confirm this genotype-phenotype association, the -202A/C IGFBP3 SNP was not
35
significantly associated with colorectal cancer risk. In conclusion, we report a novel
SNP in the IGF1 regulatory region that is associated with colorectal cancer risk.
3.1 Introduction
Insulin-like growth factor 1 (IGF1) is a cellular survival factor implicated in
various neoplasia (reviewed in (Furstenberger and Senn 2002; LeRoith and Roberts
2003; Yu and Rohan 2000)), including colorectal cancer (reviewed in (Bustin and
Jenkins 2001; Sandhu et al. 2002)). IGF1 is strongly mitogenic in colon cancer cell
lines (Lahm et al. 1992; Tricoli et al. 1986; Whithead et al. 1990) as well as anti-
apoptotic in colonic epithelial cells (Hague et al. 1997) and cancer cell lines (Guo et
al. 1998; Remacle-Bonnet et al. 2000). These potential carcinogenic IGF1 effects
may be, in part, exerted through hepatic-derived circulating levels (reviewed in
(Giovannucci 2001)). More than 75% of serum IGF1 circulates as complexes with
its predominant binding protein, IGFBP3 (Holman and Baxter 1996). The
sequestering of IGF1 by IGFBP3 modulates IGF1 bioavailability. In addition, many
in vitro studies indicate that, independent of IGF1, IGFBP3 inhibits replication and
promotes apoptosis (Collard et al. 2003; Holman and Baxter 1996).
Circulating IGF1 promotes colonic carcinogenesis, as evidenced by animal
models and human studies. In mice, circulating levels of IGF1 regulate colon cancer
growth and metastasis (Wu et al. 2002). Among human prospective studies,
although two studies failed to find an association, (Kaaks et al. 2000; Probst-Hensch
et al. 2001), two studies (Ma et al. 1999; Nomura AM 2003) found a clear
association between elevated plasma IGF1 (adjusted for IGFBP3 levels) and
36
increased colorectal or colon cancer risk, and two found positive associations of
borderline significance (Giovannucci et al. 2000; Palmqvist et al. 2002).
Twin studies suggest that circulating IGF1 and IGFBP3 levels are, in part,
genetically determined (Harrela et al. 1996; Kao et al. 1994). The only identified
candidate polymorphism for IGF1 levels is a cytosine-adenine (CA) microsatellite
polymorphism, 969 kilo base pairs upstream from the IGF1 transcription start site
(Rotwein et al. 1986; Weber and May 1989), having 15-23 CA repeats in the
Caucasian population. An initial small study (n=116) reported lower circulating
IGF1 levels among individuals homozygous for the (CA)
19
allele versus individuals
with all other genotypes (129 vs. 154 ng/ml, p=0.03) (Rosen et al. 1998). For
IGFBP3, alleles of an IGFBP3 promoter region SNP (-202A/C) differ in
transcriptional capacities (Deal et al. 2001) and plasma IGFBP3 levels consistently
correlate with genotype in the predicted direction (Deal et al. 2001; Jernstrom et al.
2001; Schernhammer ES et al. 2003).
In this study, we examine polymorphisms in the IGF1 and IGFBP3 genes in
relation to plasma levels of the respective gene products and in relation to colorectal
cancer risk in a case-control study nested within a prospective cohort of 63,257
Singapore Chinese.
37
3.2 Materials and Methods
3.2.1 Study Population
The subjects were participants of the Singapore Chinese Health Study, a
population-based, prospective investigation of diet and cancer risk. Between April
1993 and December 1998, we recruited 63,257 Chinese men and women from two
major dialect groups in Singapore (Hokkien and Cantonese) who originated from
geographically contiguous regions in Southern China: the Hokkiens from the
southern part of Fujian Province and the Cantonese from the central region of
Guangdong. Subjects were between the ages of 45 and 74 years, and resided in
government housing estates. Eighty-six percent of the Singapore population lived in
such facilities. Eighty-five percent of eligible subjects were enrolled. The gender-
dialect breakdown is as follows: 15,617 (25%) Hokkien men, 18,356 (29%) Hokkien
women, 12,342 (19%) Cantonese men, and 16,942 (27%) Cantonese women. Cohort
members were comparable with the general Chinese population in Singapore with
respect to two factors, level of education and smoking status, for which
governmental data were available. According to a 1992 national survey, 31% of
Chinese men aged 45-69 years were current smokers, and they smoked an average of
17 cigarettes per day. The corresponding figures based on male cohort members are
32%, and 16, respectively. The 1990 Singapore Census data show that 74% of
Chinese aged 45-74 years achieved no more than a primary school education. The
corresponding figure from our cohort is 72%.
38
Each subject completed a structured questionnaire administered in-person by
a trained interviewer. Current diet was assessed using a validated 165-item, semi-
quantitative food frequency questionnaire. Personal intakes of 96 nutritive/non-
nutritive dietary components were computed using the Singapore Food Composition
Table (Hankin et al. 2001). Apart from dietary history, the questionnaire also
elicited information on lifetime tobacco use, usual physical activity, medical history,
family history of cancer, and menstrual and reproductive history (women only).
A 3% random sample of study participants and all incident colorectal cancer
cases were contacted for biospecimens (blood or buccal cells and single-void urine
specimens) collection as previously detailed (Sun et al. 2002). Briefly, between
April 1994 and July 1999, of an estimated 1898 cohort participants contacted,
blood (n=908) or buccal cells (n=286) were collected from 1194 subjects,
representing a participation rate of 63%. Additionally, beginning in January 2000,
biospecimen collection was extended to all surviving members of the cohort and is
expected to be complete by May 2004.
3.2.1.1 Controls
Of the 1194 randomly sampled subjects who donated biospecimens (908
blood, 286 buccal samples), thirteen had developed incident colorectal cancer by
April 30, 2002. The 895 (908 minus 13) cohort subjects for whom blood was
drawn and who were free of a history of colorectal cancer on April 30, 2002
comprised the comparison group for this case-control analysis.
39
3.2.1.2 Cases
Incident colorectal cancer cases were identified by record linkage with the
population-based Singapore Cancer Registry(Chia K.S. 2000). The Singapore Cancer
Registry was established in 1968 and since then, has been continuously included in
the “Cancer Incidence in Five Continents” serial publications by the International
Agency for Research on Cancer in Lyon, France. Migration out of Singapore,
especially among housing estate residents, has been negligible since inception of the
cohort (Department of Statistics, Singapore Ministry of Trade and Industry, 2001).
As of April 30, 2002, 592 cases of incident colorectal cancer (ICDO C18-
C20) had developed among cohort members. Blood (n=228) or buccal (n=84)
specimens were available on 53% (312/592) of the colorectal cancer cases. Of the
312 available biospecimens, 50 were collected pre-diagnostically (13 were from
the 3% random sample and 37 were from the expanded biospecimen collection
after January 2000, described above). Of the 262 (312 minus 50) cases that were
collected post-diagnostically, median time from diagnosis to blood draw was 9.5
months.
Participants who donated biospecimens were comparable to non-donors
with respect to body mass index (body mass index expressed as weight in
kilogram divided by height in meters squared), family history of colorectal
cancer, smoking history (never, ex-smoker, current smoker) and physical activity
(moderate activity, hours/week: 0, 0.5-3, >4). Compared with those who had no
40
formal education, a higher proportion of subjects who had primary school or
higher education donated a blood or buccal cell specimen (56% vs. 46%). More
male cases donated specimens (56%) compared to females (49%), and more
Cantonese (57%) donated specimens compared to Hokkiens (50%). The average
age at diagnosis of cancer was comparable between cases with and without
specimens (65 vs. 66 years).
Histological information on each colorectal cancer diagnosis was confirmed
by reviewing the pathology report. The cases included one carcinoid tumour, two
in-situ cases and three with unknown histologies but ascertained by death records
and clinical evidence. Since these cases are unlikely to differ etiologically from
carcinomas and since excluding these cases did not alter the results, these six
cases were retained in our analyses.
The study protocol was approved by the Institutional Review Boards of the
University of Southern California and the National University of Singapore. All
participants gave written, informed consent at the time of recruitment and at
collection of blood (or buccal cells) and urine specimens.
3.2.2 Laboratory methods
DNA was purified from buffy coats of peripheral blood and from buccal
cell samples using standard, published methods (Garcia-Closas et al. 2001). All
three genotype assays described below were performed with case-control status
blinded to the laboratory technician. Six percent of the samples were replicated as
blind duplicates distributed across all genotyping batches. At least three negative
41
controls (water blanks) were included on each PCR plate. Genotyping failure rate
was less than 2% for each of the two IGF1 loci and 6% for the IGFBP3 SNP.
Samples with genotyping failure for one or both of the IGF1 loci were excluded,
leaving 290 cases and 873 controls. In addition, in Table 6 and Figure 2, an
additional 18 cases and 52 controls having missing IGFBP3 genotypes were
excluded.
3.2.2.1 IGF1 promoter region sequencing
To identify additional common polymorphisms in the IGF1 5’ UTR, the one
kilo base region spanning the (CA) repeats and the IGF1 translation start site was
resequenced for 60 Singapore Chinese and 96 non-Hispanic white, black and
Hispanic white subjects (192 total chromosomes) from the Hawaii/Los Angeles
Multiethnic Cohort (DeLellis et al. 2003). Two overlapping segments were
amplified using two sets of primers: 5’AATTGTTTGCCCCCCA3’ & 5’
GAACCCTGTCAC3’ and 5’CCCATCCCCCATATTCCT3’ &
5’GTGCTGCTTTTGTGATTTC3’. Sequencing was carried out using an ABI Prism
3700 DNA Sequencer (PE Biosystems, Foster City CA).
3.2.2.2 Genotyping
IGF1-969(CA)
n
The genomic region containing the CA repeat was PCR amplified using
previously described oligonucleotides (Rosen et al. 1998). The
33
P-labeled PCR
products were separated on 6% denaturing polyacrylamide gels and visualised by
42
autoradiography. Genotypes were scored by comparison to controls that had
genotype confirmed by sequencing. Genotypes were independently scored by two
investigators and samples for which there were discrepant readings were reassayed.
IGF1-533T/C
Alleles for the C->T polymorphism at position -533 upstream of the
transcription start site of the IGF1 gene (Genbank accession number: S85346) were
identified by the fluorogenic 5'-nuclease assay (TaqMan Assay) (Lee et al. 1993)
using the TaqMan PCR Core Reagent Kit (Applied Biosystems, Foster City, CA)
according to manufacturers’ instructions. The oligonucleotide primers for
amplification of the polymorphic region were GC029for (5'-gcccctccataggttctagga-
3') and GC029rev (5'-cgggtgaccccttgtcc-3'). Fluorogenic oligonucleotide probes
used to detect each of the alleles were GC029F (5'-agatcacacccctcacttggcaac-3')
labelled with 6-FAM and GC029C (5'-agatcacacctctcacttggcaac-3') labeled with CY3
(BioSearch Technologies,Novato, CA). PCR amplification was performed in a
thermal cycler (MWG Biotech, High Point, NC) with an initial step of 95C for 10
minutes followed by 50 cycles of 95C/25sec and 63C/1min. The fluorescence
profile of each well was measured in an ABI 7900HT Sequence Detection System
(Applied Biosystems) and the results analyzed with Sequence Detection Software
(Applied Biosystems). Any samples that were outside the parameters defined by the
controls were identified as non-informative.
43
IGFBP3-202A/C
Alleles for the A->C polymorphism at position -202 of the IGFBP3 gene
were identified using direct sequencing of the polymorphic region. The region of the
gene containing the polymorphism was amplified by PCR using primers GC082for
(5’-GAGTTGGCCAGGAGTGACTG-3’) and GC082rev (5’-
GCGTGCAGCTCGAGACTC-3’). PCR reaction mix was prepared using HotStart
Taq Polymerase (Qiagen, Valencia, CA) according to manufacturers’ instructions
using 20ng of genomic DNA, 2mM MgCl
2
and 300uM of each primer. PCR
amplification was performed in a thermal cycler (MWG Biotech, High Point, NC)
using a touchdown protocol with an initial step of 95C for 15 minutes finishing with
35 cycles of 95C/25sec, 57C/1min and 72C/1min. DNA sequencing was performed
using primer GC082S (5’-CCAGGAGTGACTGGGGTGA-3’) using ~10-20ng of
purified PCR product using fluorescently labeled ddNTPs (ABI Dye Terminator
Sequencing Kit, Applied Biosystems) by cycle sequencing for 50 rounds of
95C/15sec & 58C/3.5min. The sequencing reactions were run on an ABI3700
Capillary DNA Analyzer.
3.2.2.3 Serum Assays
Total serum IGF1 and IGFBP3 levels were measured as previously described
(Probst-Hensch et al. 2001). Briefly, measurements of serum IGF1 and IGFBP3
concentrations were
carried out using immunoradiometric assay kits (Diagnostic
Systems
Laboratories, Inc., Webster, TX), following the instructions of the
manufacturer.
44
3.2.3 Statistical Analysis
3.2.3.1 Genotype-colorectal cancer risk association
Although we sampled our controls from the whole cohort, this study is more
case-control than case-cohort in design, because the time period of follow-up was
comparable between the cases and subcohort, with only 13 subjects in the latter
group developing colorectal cancer during the observation period. Nonetheless,
parallel analyses were conducted using standard case-control and case-cohort
methods and did not materially differ. The data presented in this manuscript are
based on case-control analysis.
Specifically, to assess the extent of cancer risk associated with genotypes,
unconditional multiple logistic regression models (Breslow and Day 1980) were
fitted and odds ratio (ORs) and their corresponding 95% confidence intervals
(CIs) were reported. All logistic regression models included age at recruitment
(continuous), year of recruitment, gender and dialect group (Cantonese, Hokkien)
as covariates. Colorectal cancer risk factors which were considered as potential
confounders were BMI, height, education levels, alcohol intake, physical activity,
and smoking history. None were included in the final model because inclusion did
not substantially alter (>5%) the parameter estimates for the exposures
(genotypes).
Colorectal cancer was coded by anatomic subsites per the International
Classification of Disease Oncology (2
nd
ed.): colon (C18.0-C18.9) and rectal
(C19.0-C20.0) cancers. To test for heterogeneity of odds ratios across anatomic
45
subsite as well as age at diagnosis for cases (young cases: <60 years; old cases:
>=60 years), polychotomous logistic regression models were fitted and likelihood
ratio tests were conducted.
To investigate the possible interaction of the IGF1 genotype with gender
and factors associated with serum IGF1 in this population (BMI, calcium intake
and physical activity) (Probst-Hensch et al. 2003), the respective multiplicative
interaction terms were included in the regression models and likelihood ratio tests
were conducted for significance of the interaction parameters.
3.2.3.2 Haplotype inference and allelic co-segregation/association
Allele frequencies were determined by gene counting (Li 1976). The
observed allele frequencies among controls were used to calculate the expected
genotype frequencies under Hardy-Weinberg equilibrium. Departures from
Hardy-Weinberg equilibrium (HWE) was assessed by testing the difference
between the observed (sampled) and expected (under HWE) genotype frequencies
in controls using a 3
2
test (Chiano and Clayton 1998). Linkage disequilibrium
(LD) between IGF1 polymorphisms was assessed by using a 3
2
test of allelic
association (Terwilliger and Ott 1994).
To estimate haplotype frequencies from genotype information within our
population of unrelated individuals, we used the expectation-maximization
algorithm, as implemented in the STATA command hapipf, to resolve phase
uncertainties (Chiano and Clayton 1998; Excoffier and Slatkin 1995; Fallin and
Schork 2000). To estimate odds ratios for haplotype combinations, each
46
individual in the sample was replicated for all possible haplotype configurations
that are compatible with their genotypes and weighted by the estimated haplotype
frequencies in logistic regression models (Zaykin et al. 2002).
3.2.3.3 Genotype-phenotype association
Of the 895 controls in this study, 628 had serum IGF1 and 595 had serum
IGFBP3 measurements available (described previously by Probst-Hensch and
colleagues (Probst-Hensch et al. 2003)). Kruskal-Wallis test statistics were used to
compare distributions of the serum markers by genotype categories. Multiple
regression models were also fitted with age, sex, body mass index, dialect group
and year of recruitment as covariates but were not reported as none of these non-
genetic risk factors acted as confounders. All p-values are two-sided and statistical
analyses were performed using STATA 8.0 (Stata Corp, College Station, TX).
3.3 Results
3.3.1 Study characteristics
The baseline characteristics of the Singapore Chinese Health Study cohort
have been described (Sun et al. 2002). Briefly, the mean age of cohort subjects at
enrollment was 56.5 years. Fifty-six percent of cohort subjects were women and
54% belonged to the Hokkien dialect group. Most were married (83%) at the time of
recruitment. Eighty-eight percent of cohort subjects were born in Singapore or
Malaysia (Singapore and Malaysia are neighboring countries with similar socio-
cultural groups), while virtually all of the remaining 12% were born in China. The
47
cohort was relatively uneducated; 27% of its members had no formal education and
44% received only a primary school education.
The control group for this study was comparable to the whole cohort with
respect to demographic variables and colon cancer risk factors. Table 3.1
summarizes the demographic characteristics among cases and controls. Cases were
heavier than controls, marginally taller, less educated and more likely to be male.
Controls and cases did not differ significantly in terms of physical activity, dietary
calories, fat, fiber or calcium. In addition, they did not differ by dialect group,
family history of colon or rectal cancer, smoking, alcohol consumption, age at
menarche, age at menopause, parity, or age at first birth (data not shown). The age
at diagnosis for cases ranged from 47 to 82 years (median = 66 years).
48
Table 3.1 Selected characteristics of colorectal cancer cases and controls, the
Singapore Chinese Health Study
Characteristics Controls Cases p-value
Total number 873 (100)
a
290 (100)
a
Sex
Female 492 (56.4) 122 (42.0)
Male 381 (43.6) 168 (58.0) p<0.01
Body Mass Index (kg/m
2
)
20 144 (16.4)
a
44 (15.2)
a
20-<24 485 (55.6)
a
143 (49.3)
a
24-<28 200 (23.0)
a
83 (28.6)
a
28+ 44 (5.0)
a
20 (6.9)
a
p=0.04
Height
160 (147,170)
b
160 (147,175)
b
p=0.01
Moderate physical activity (hours/week)
0 653 (74.8) 217 (74.8)
0.5-3 139 (15.9) 42 (14.5)
4+ 81 (9.3) 31 (10.7) p=0.69
Education level
None (formal) 207 (23.7)
a
87 (30)
a
High school
604 (69.2)
a
193 (66.6)
a
Post-high school
41 (4.7)
a
6 (2.0)
a
University 21 (2.4)
a
4 (1.4)
a
p<0.01
Total calcium intake (mg/day)
388.7 (160.1, 865.0)
b
364.8 (149.3, 781.8)
b
p=0.20
Total calories (kcal/day)
1494.5 (835.6, 2480.2)
b
1497.4 (814.4, 2583.0)
b
p=0.91
Total fibre intake (g/day)
12.3 (5.3, 23.7) 11.9 (4.2, 22.7) p=0.54
Total fat (g/day)
41.4 (19.7, 82.3)
b
39.5 (18.3, 77.2)
b
p=0.20
a
Number of subjects (%);
b
Median (5
th
percentile, 95
th
percentile).
49
3.3.2 IGF1 -969(CA)
n
genotypes
Eleven alleles, having 12 to 23 repeats, were observed in the Singapore
Chinese population (Table 3.2). The (CA)
19
allele, at 35.5%, the most frequent
among both cases and controls, is the most common allele in previously reported
Caucasian (62.1 -67.9%, (Allen et al. 2002; Frayling et al. 2002)), Japanese
(40.8%,(Miyao et al. 1998)), Indian-Pakistani (56%) and African-American
(37.8%,(Jernstrom et al. 2001)) populations. Although alleles (CA)
18
and (CA)
19
appeared to be slightly more common among cases and allele (CA)
21
was more
common among controls, there was no overall significant difference in the genotype
distributions between cases and controls (p=0.12).
Table 3.2. Distribution of the -969(CA)
n
allele frequencies
a
in Singapore
Chinese
Cytosine-adenine repeats Controls (%)
a
Cases (%)
12 7 (0.4) 3 (0.5)
14 1 (0.1) 0 (0)
15 2 (0.2) 0 (0)
16 6 (0.3) 0 (0)
17 133 (7.6) 50 (8.6)
18 279 (16.0) 112 (19.3)
19 620 (35.5) 215 (37.1)
20 100 (5.7) 38 (6.6)
21 536 (30.7) 151 (26.0)
22 56 (3.2) 10 (1.7)
23 6 (0.3) 1 (0.2)
Genotype distributions did not deviate from Hardy-Weinberg expectations.
Table 3.3 shows the ORs for allele 19, the allele previously associated with lower
levels of circulating IGF1 (Jernstrom et al. 2001; Rosen et al. 1998), and for the
50
next most common allele, (CA)
21
. There was no decrease in risk among those who
carried one or two copies of the (CA)
19
allele. Given the previously reported lower
levels of circulating IGF1 only among homozygous carriers of the (CA)
19
allele, we
also combined heterozygotes and non-carriers. No decreased risk was observed for
genotype 19/19 versus others. For the second most common allele, (CA)
21,
possession of two copies was associated with approximately half of the risk for
colorectal cancer compared to all other genotypes (Table 3.3).
Table 3.3. Odds ratios (ORs) and 95 percent confidence intervals (95%CIs) for
the -969(CA)
n
polymorphism and colorectal cancer, Singapore Chinese Health Study
Genotype Controls/Cases OR(95%CI)
a
N=873/N=290
Repeat 19
others 374/110 1.00 (referent)
(CA)
19
/others 378/145 1.33 (0.98,1.80)
(CA)
19
/(CA)
19
121/35 1.03 (0.64,1.63)
(CA)
19
/(CA)
19
vs. all other genotypes 0.88 (0.57,1.36)
Repeat 21
others 426/157 1.00 (referent)
b
(CA)
21
/others 358/115 0.90 (0.67,1.23)
b
(CA)
21
/(CA)
21
89/18 0.46 (0.26,0.81)
b
(CA)
21
/(CA)
21
vs. all other genotype 0.48 (0.28,0.84)
a
adjusted for age at recruitment (continuous), sex, dialect group (Cantonese or
Hokkien), and year of recruitment.
b
p for trend= 0.02
51
3.3.3 IGF1 -533T/C genotypes
Resequencing revealed two previously unreported SNPs (-533T/C and -
484T/A) in perfect LD with each other (Figure 3.1). We genotyped one of the
SNPs, -533T/C, for all cases and controls. Genotype frequencies were in
agreement with Hardy-Weinberg equilibrium.
Figure 3.1. Insulin-like Growth Factor1 promoter polymorphisms
Table 3.4 summarizes the effect of the -533T/C genotype on colorectal
cancer risk. An approximate 30% decrease in risk was associated with possession
of one or two copies of the C allele as compared to genotype TT. This association
was confined to risk of colon cancer.
The effect of the C allele appeared to be modified by age, a strong predictor
of circulating IGF1 levels in adulthood (Benbassat et al. 1997; Leifke et al. 2000;
Lissett and Shalet 2003). It was primarily among young participants (below age 60
years) that the protective effect of the C allele was observed. Young carriers of the C
allele had a 54% reduction in risk of colorectal cancer (Table 3.4). In addition, the
effect of the -533T/C genotype on colorectal cancer risk was stronger in overweight
persons, i.e. BMIX24kg/m
2
(TT vs. CT/CC: OR=0.48 (0.29, 0.79)) as contrasted to
(CA)
n
-533 - 484
C
T
T
A
ATG
-969
52
lean persons, i.e. BMI<24kg/m
2
(TT vs. CT/CC: OR=0.83 (0.58, 1.17)) with a nearly
significant formal test for interaction (p=0.08). There was no evidence of interaction
by gender, calcium intake or physical activity.
53
Table 3.4. Odds ratios (ORs) and 95 percent confidence intervals (95%CIs) for
the IGF1 -533T/C genotype and colorectal cancer, Singapore Chinese Health Study.
Genotype Controls (%) Cases (%) OR(95%CI)
a
TT 390(44.7) 156(53.8) 1.00 (referent)
CT 382(43.8) 101(34.8) 0.68 (0.50,0.93)
CC 101(11.5) 33(11.4) 0.71 (0.44,1.13)
CC/CT vs. TT 0.69 (0.52,0.92)
Subsite
Colon
TT 390(44.7) 99(58.9) 1.00 (referent)
CT 382(43.8) 54(32.2) 0.59 (0.40,0.86)
CC 101(11.5) 15(8.9) 0.54 (0.29,0.99)
CC/CT vs. TT 0.58 (0.41,0.82)
Rectal
TT 390(44.7) 57(46.7) 1.00 (referent)
CT 382(43.8) 47(38.5) 0.91 (0.59,1.37)
CC 101(11.5) 18(14.8) 1.08 (0.60,2.00)
CC/CT vs. TT 0.94 (0.63,1.40)
p for heterogeneity = 0.04
b
Age at diagnosis
< 60 years
TT 390(44.7) 45(62.5) 1.00 (referent)
CT 382(43.8) 20(27.8) 0.42 (0.24,0.74)
CC 101(11.5) 7 (9.7 ) 0.61 (0.28,1.43)
CC/CT vs. TT 0.46 (0.28,0.76)
>= 60 years
TT 390(44.7) 111(50.9) 1.00 (referent)
CT 382(43.8) 81(37.2) 0.84 (0.58,1.22)
CC 101(11.5) 26(11.9) 0.74 (0.42,1.29)
CC/CT vs. TT 0.81 (0.57,1.14)
p for heterogeneity = 0.06
c
a
odds ratio from unconditional logistic regression; adjusted for age at recruitment,
gender, dialect groups (Cantonese or Hokkien), and year of recruitment
(continuous).
b
The odds of the cases carrying the IGF1 genotype TT compared to the combined
genotypes of CT/CC were contrasted between colon cancer and rectal cancer cases
c
Test of heterogeneity comparing odds ratio of carriers of TT vs. CT/CC among
younger and older cancer cases
54
3.3.4 IGF1 haplotypes
The -969(CA)
n
and -533T/C loci were not independently distributed
(p<0.001). The frequency of the (CA)
21
- C haplotype was higher than expected
under the hypothesis of no LD (25.1% vs. 17.5%) (Table 3.5). Seventy-five
percent (439/584) of the C alleles were observed to be linked to the (CA)
21
allele.
The T allele, on the other hand, was more often associated with alleles (CA)
17
to
(CA)
19
. Only 8% (97/1162) of T alleles were linked to (CA)
21.
We estimated odds ratios for the (CA)
21
- C haplotype, the haplotype
carrying the two alleles, (CA)
21
and -533 C, that were univariately associated with
lower risk. Compared to those carrying no copies of the (CA)
21
- C haplotype,
odds ratios for those carrying one or two copies were 1.00 (0.74, 1.36) and 0.63
(0.34, 1.15), respectively.
Table 3.5. Estimated haplotype frequencies for IGF1 -969(CA)
n
and -533T/C
polymorphisms, Singapore Chinese Health Study
Haplotype Frequencies (%)
Estimated
a
Expected
b
Haplotype Frequencies (%)
Estimated
a
Expected
b
(CA)
17
– C 8 (0.5)
26 (1.5)
(CA)
17
– T 125 (7.2)
106 (6.1)
(CA)
18
– C 18 (1.0) 64 (3.7) (CA)
18
– T 262 (15.0) 215 (12.3)
(CA)
19
– C 48 (2.7) 123 (7.0) (CA)
19
– T 572 (32.8) 496 (28.4)
(CA)
20
– C 16 (0.9) 24 (1.4) (CA)
20
– T 84 (4.8) 77 (4.4)
(CA)
21
– C 439 (25.1) 306 (17.5) (CA)
21
– T 97 (5.6) 230 (13.2)
(CA)
22
– C 50 (2.9) 35 (2.0) (CA)
22
– T 6(0.3) 22 (1.3)
Other
– C
Total
5 (0.3) 6 (0.3)
584 584
Other
– T
Total
16 (0.9) 16 (0.9)
1162 1162
a
Estimated using the expectation-maximization algorithm to resolve phase
uncertainty.
b
Expected frequencies under the null hypothesis of no linkage
disequilibrium.
55
3.3.5 IGFBP3 -202 A/C
Allele frequencies among control subjects for the -202A/C polymorphism
were 77% (A allele) and 23% (C allele). Genotype frequencies did not deviate
from Hardy-Weinberg expectations. Overall, the genotypes were not associated
with colorectal cancer risk (Table 3.6). However, there was evidence of
heterogeneity by anatomic site (p=0.04). This result appeared to be driven by the
relatively small number of subjects with genotype CC. Compared to persons
carrying at least one copy of the A allele, persons homozygous for the C allele had
a non-statistically significantly increased risk of colon cancer and a non-statistically
significantly decreased risk of rectal cancer. There was no evidence of
heterogeneity by age or interaction with BMI, gender, calcium intake or physical
inactivity.
3.3.6 Gene-gene interaction
There was no evidence that the relationship between IGF1 genotypes (-
969(CA)
19
,-969(CA)
21
and -533T/C)
and colorectal cancer risk was modified by
IGFBP3 genotype (-202A/C) .
3.3.7 Genotype-phenotype analyses
3.3.7.1 IGF1 genotypes and serum IGF1 levels
In the IGF1 gene, the -969(CA)
n
, and in particular the two most common
alleles (CA)
19
and (CA)
21
, did not predict serum IGF1 among the 628 controls with
serum levels available. Median values for (CA)
19/19,
(CA)
19/others,
(CA)
others/others
56
were 125, 132 and 127 ng/ml respectively (p=0.56). Median values for (CA)
21/21,
(CA)
21/others,
(CA)
others/others
were 127, 130 and 127 ng/ml respectively (p=0.87).
Neither did the -533T/C SNP predict serum IGF1 levels. Median values for
the CC, CT and TT genotypes were 130, 133 and 122 ng/ml respectively (p=0.35).
Table 3.6. Odds ratios (ORs) and 95 percent confidence intervals (95%CIs) for
the -202 IGFBP3 and colorectal cancer, Singapore Chinese Health Study
Genotype Controls/Cases OR(95%CI)
a
N=821/N=272
AA 480/166 1.00 (referent)
AC 306/90 0.90 (0.66,1.23)
CC
35/16 1.27 (0.67,2.45)
CC vs. AA/AC 1.32 (0.69,2.52)
Subsite
Colon
AA 480/93 1.00 (referent)
AC 306/51 0.90 (0.61,1.32)
CC
35/13 1.82 (0.89,3.74)
CC vs. AA/AC 1.89 (0.94,3.82)
b
Rectum
AA 480/73 1.00 (referent)
AC 306/39 0.88 (0.57,1.35)
CC
35/3 0.54 (0.56,1.35)
CC vs. AA/AC 0.56 (0.17,1.91)
b
p for heterogeneity=0.04
b
a
adjusted for age at recruitment (continuous), sex, dialect group (Cantonese or
Hokkien), and year of recruitment.
b
The odds of the cases carrying the IGFBP3 genotype CC compared to the
combined genotypes of AA/AC were contrasted between colon cancer and rectal
cancer cases
57
3.3.7.2 IGFBP3 genotype and serum IGFBP3 levels
The -202A/C SNP in the IGFBP3 gene was associated with serum IGFBP3
levels in the predicted direction (Figure 3.2). Median serum IGFBP3 levels were
3994, 3785 and 3307 ng/ml for genotypes AA, AC and CC respectively (p<0.001).
Figure 3.2. Serum IGFBP3, by IGFBP3 genotypes, Singapore Chinese Health
Study.
3.4 Discussion
In this study, we examined polymorphisms in the IGF1 and IGFBP3 genes in
a cohort of Singapore Chinese. We identified two new IGF1 promoter region SNPs,
in LD with a CA microsatellite that, in previous studies, has been inconsistently
associated with cancer risk and other phenotypes. We report here that the new
polymorphisms are associated with risk of colorectal cancer, specifically in the
colon. We also report that IGFBP3 genotype, while not related to risk of colorectal
cancer, is a predictor of serum IGFBP3 levels.
2
4
6
8
A/A A/C C/C
Serum IGFBP3 (ug/mL)
58
3.4.1 IGF1 genotype
Previous studies do not support a direct functional effect of the CA
microsatellite polymorphism. Although lower serum IGF1 levels among men with
the (CA)
19/19
genotype were initially reported in a small study of men with idiopathic
osteoporosis (n=116) (Rosen et al. 1998), three prospective studies, the United
Kingdom component of EPIC (n=660 (Allen et al. 2002)), the Nurses’ Health Study
(n=202 controls (Giovannucci et al. 2002; Missmer et al. 2002)) and the Hawaii/Los
Angeles Multiethnic Cohort (n=230 (DeLellis et al. 2003)), found no association
between CA genotype and serum levels. Two other large studies reported an
association between genotype and serum levels; however, results were in opposing
directions. Reduced circulating IGF1 levels were associated with the absence of the
(CA)
19
(n=900, p=0.003(Vaessen et al. 2001)) in a Dutch population and with the
presence of the (CA)
19
allele (n=640, p
trend
=0.01(Frayling et al. 2002) in a study in
South Wales. While the results of these latter two studies suggest that polymorphism
at this locus influences serum IGF1 levels, the conflicting direction of the results
suggest that it is not the CA microsatellite polymorphism that is responsible
(Frayling et al. 2002) .
To explore the possibility that the CA microsatellite is a marker of a
functional polymorphism, we resequenced the promoter region of the IGF1 gene
from the CA microsatellite to the translation start site. We identified two new SNPs
(-533T/C and -483A/T) that are in partial LD with the -969(CA)
n
. Since the two new
SNPs are in perfect LD, only one of the SNPs, i.e., -533T/C, was examined in the
59
current study. The C allele of the -533T/C SNP was partially linked with the (CA)
21
allele, and both were associated with colorectal cancer risk in this study. In addition,
the (CA)
21
- C haplotype also predicted lower risk but was not more informative than
either of the single markers. Possible scenarios are that either the new SNP is causal
or it is in tighter LD with the putative causal SNP than is the haplotype marker.
Indeed due to the hypermutable nature of microsatellites (Ellegren 2000; Weber and
Wong 1993), the haplotype marker may contain more measurement error.
Although it is possible that the -533T/C SNP is directly responsible for the
observed association, there is currently no evidence that it has a functional effect. In
fact, we found no association between genotype and serum levels. While
measurement of IGF1 serum levels can be problematic due to variable cleavage
products in stored specimens (Nomura et al. 2003), IGF1 serum levels have been
associated with colorectal cancer risk in some previous studies. The reason for the
lack of association between the SNP and IGF1 serum levels in this population
remains unresolved.
The -533T/C SNP was primarily associated with risk of colon but not rectal
cancer. Consistent with our findings, elevated serum IGF1 levels have been
associated with risk of colon but not rectal cancer in a cohort of Hawaiian-Japanese
(Nomura AM 2003). Colon and rectal cancer incidence differ in distribution by
geography, ethnicity, age and gender (DeCosse et al. 1993), suggesting differences in
etiology between the cancers (reviewed in (Iacopetta 2002)). However,
heterogeneity by subsite was not observed in the Physicians’ Health Study (Ma et al.
60
1999), or in the two negative prospective studies, i.e. the Shanghai Chinese Male
Cohort (Probst-Hensch et al. 2001) or the New York Women’s Study (Kaaks et al.
2000).
We observed effect-modification by age. Levels of circulating IGF1 decline
with age (Benbassat et al. 1997; Leifke et al. 2000; Lissett and Shalet 2003) and the
growth hormone (GH) axis is thought to be responsible. Only among younger
persons (< 60 years) was the genotypic effect evident. Among older people, who
have presumably already undergone a significant age-related decline in serum IGF1
levels, no effect of genotype on cancer risk was observed. A similar pattern was
seen for serum IGF1 levels in a Hawaiian-Japanese cohort (Nomura AM 2003).
Furthermore, a previous study reported an interaction between age and the -
961(CA)
n
genotype: the age-related decrease in circulating levels of IGF1 was
stronger among homozygotes for -969(CA)
19
(Rietveld et al. 2003).
3.4.2 IGFBP3 genotype
We confirmed that the IGFBP3 genotype predicts serum IGFBP3 levels.
Consistent with previous studies (Deal et al. 2001; Jernstrom et al. 2001;
Schernhammer ES et al. 2003) and with in vitro assays (Deal et al. 2001), there was a
trend for decreasing serum IGFBP3 levels with increasing copies of the C allele.
While there was no significant association between genotype and cancer risk, there
was evidence of heterogeneity by anatomic site, with a nonsignificantly increased
risk of colon cancer among subjects with genotype CC. Larger sample sizes are
needed to confirm these results.
61
3.4.3 Gene-gene interaction
While a main effect of the IGFBP3 genotype on colorectal cancer risk in our
population was not observed, IGFBP3 genotype might plausibly influence the effect
of IGF1 genotype on cancer risk. IGFBP3 potentially influences the effects of IGF1
on cellular growth and proliferation through stabilizing and increasing IGF1 half-life,
modulating IGF1 transportation and cellular localization, extending metabolic
clearance and regulating IGF1/IGF1-receptor binding. Although we found no
evidence of gene-gene interaction, we had very low power to conduct a formal test of
interaction.
3.5 Conclusions
Our finding of an association between genetic polymorphism in the IGF1
promoter region and colorectal cancer risk is unlikely to be an artifact of population
stratification and admixture (Deng et al. 2001) since the Singapore Chinese Health
Study is a population-based cohort investigation involving subjects drawn from an
ethnically homogeneous southern Chinese population. This population originates
from the contiguous coastal provinces, Fujian and Guangdong, and forms a tight
genetically homogeneous subcluster within the relatively genetically similar
Southern Chinese population ((Cavalli-Sforza 1998) and references therein). Neither
is selection bias likely to explain our results since participation rate was high (85%),
participants appeared to be similar to the general population, and biospecimen
donors and non-donors differed only by dialect group, gender and education, none of
which were related to genotype. Furthermore, the validity of this finding is
62
supported by the observation that a strong predictor of serum IGF1 (age) modifies
the effect of IGF1 genotype on colorectal cancer occurrence.
However, the identity of the polymorphism causally responsible for this
association has not been definitively determined. All three makers, the (CA)
21
- C
haplotype, the -969(CA)
21
allele, and the -533 C allele, predicted lower risk. While
none of these three markers was clearly most informative, the -533 T/C SNP has the
advantages of being less prone to measurement error (compared to a microsatellite
marker), and of producing more stable (less sparse) data. Our finding of an
association between the -533 T/C SNP and colorectal cancer risk supports the utility
of this newly identified IGF1 promoter region SNP for IGF1 association studies.
Acknowledgements
The Singapore Chinese Health Study has been supported by grants R01
CA55069, R35 CA53890, and R01 CA80205 from the National Cancer Institute,
Bethesda, Maryland. We thank Ms. Siew-Hong Low of the National University of
Singapore for supervising the field work of the Singapore Chinese Health Study, and
Ms. Kazuko Arakawa of the University of Southern California for the development
and management of the cohort study database.
63
Chapter 4: Promoter polymorphism in evolutionarily conserved regions in the
Insulin-like Growth Factor 1 regulatory region and colorectal cancer risk.
Abstract
Insulin-like Growth Factor1 (IGF1) promotes colorectal cancer growth and
progression, possibly through obesity-related insulin resistance. IGF1 levels vary
markedly among normal healthy individuals. Genetic factors explain at least half of
the normal IGF1 variation. The relevant IGF1 polymorphisms that underlie the
variation in colorectal cancer rates remain ill-defined. We have previously argued
that an IGF1 polymorphism in the IGF1 promoter region, a cytosine-adenosine
microsatellite (CA
15-22
), is not responsible for variation in IGF1 levels, but rather is
in linkage disequilibrium with functional IGF1 promoter variants. This study
characterizes putative regulatory polymorphisms in the IGF1 promoter region based
on a comparative genomics approach within a cohort of a rapidly westernizing
population, the Singapore Chinese. A common IGF1 single nucleotide
polymorphism (SNP) was identified: -2995 IGF1 C/A, having minor allele frequency
(A allele) = 0.36. We examined whether this -2995 IGF1 C/A SNP predicts
colorectal cancer risk among 300 cases and 1146 controls nested within the
Singapore Chinese Health Study. Compared to persons not carrying a copy of the A
allele (CC genotype), persons carrying at least a copy (CA or AA genotypes) had
approximately 40 percent decreased risk for colorectal cancer (odds ratio, OR, for
CC versus AC/AA: 0.58; 95 percent confidence interval, 95%CI: 0.44, 0.76). This
association was confined to colon cancer (p for heterogeneity=0.02). Among
64
physically active individuals, the effect of the IGF1 SNP on colorectal cancer risk
was approximately two-fold stronger (OR: 0.30; 95%CI: 0.15, 0.60) than among
physically inactive individuals (OR: 0.66; 95%CI: 0.49,0.88) (p for
interaction=0.057).
4.1 Background
Although “Western lifestyle” (sedentary lifestyle and high caloric diet) is
thought to predispose to colorectal cancer (Potter 1999), the mechanistic basis
remains unclear. One candidate proposed to mediate the effects of obesity-related
“western lifestyle” is a potent growth factor, the Insulin-like Growth Factor (IGF)-
1(Giovannucci 1995; Komninou et al. 2003; McKeown-Eyssen 1994). Adoption of
a western diet is associated with significant changes in serum IGF1 levels(Heald et
al. 2005). In response to nutrient availability (Longo and Finch 2003), IGF1
regulates diverse physiological processes including growth, development, aging,
and
longevity (Jones and Clemmons 1995; Stewart and Rotwein 1996). Extensive
evidence, both in vitro and in vivo, suggests that IGF1 promotes colorectal cancer
growth, prevents apoptosis (Fukuda et al. 2002; Guo et al. 1998; Hague et al. 1997;
Koenuma et al. 1989; Lahm et al. 1992; Reinmuth et al. 2002; Remacle-Bonnet et al.
2000; Sekharam et al. 2003; Tricoli et al. 1986; Whithead et al. 1990) (Hassan and
Howell 2000; Hirose et al. 2004; Wu et al. 2002), and increases metastasis
(Bjorndahl et al. 2005). IGF1 effects its multiple roles at the endocrine,
paracrine
and autocrine levels (D'Ercole et al. 1984).
65
At both circulating (endocrine) and local (paracrine and autocrine) levels,
significant heterogeneity in IGF1 levels among normal healthy individuals exists
within and between different ethnic groups (Cruickshank et al. 2001; DeLellis et al.
2003; Girgis et al. 2000; Pastinen and Hudson 2004; Platz et al. 1999). This
population variation in IGF1 levels is hypothesized to underlie the variation in
cancer incidence rates. To examine this hypothesis, six prospective population-
based studies have examined circulating IGF1 (serum or plasma levels measured at
one timepoint during middle-aged) as a proxy for IGF1 mitogenic actions in the
colorectum (Giovannucci et al. 2000; Kaaks et al. 2000; Ma et al. 1999; Nomura et
al. 2003; Palmqvist et al. 2002; Probst-Hensch et al. 2001). Individuals with higher
levels of circulating IGF1 (uppermost 20-25% of the normal range as compared to
the lowermost 20-25%) are at increased risk of developing cancers of the
colorectum, pre-menopausal breast, prostate and lung (meta-analyses of the first five
studies)(Renehan et al. 2004).
While IGF1 variability is, in part, genetically determined, the genetic basis of
IGF1 variation that underlies the population variation in cancer risk remains poorly
defined. Genetic factors contribute to an estimated 50 per cent of the variability in
circulating IGF1 levels among healthy twins (Harrela et al. 1996; Kao et al. 1994).
Furthermore, IGF1 shows considerable variation (Pastinen et al. 2004). Common
polymorphisms in the exons of the IGF1 gene have not been observed in single
strand conformational polymorphism
and heteroduplex formation analyses (Johnston
et al. 1999; Rasmussen et al. 2000). However, a few single nucleotide
66
polymorphisms (SNPs) and microsatellites in the promoter and introns were
reported. Thus, the responsible IGF1 genetic variants probably lie in the regulatory
regions of the gene. Of these, the most studied IGF1 genetic variant resides in the
promoter region: a cytosine-adenosine dinucleotide repeat sequence (CA
15-22
). We
have previously argued that this IGF1 CA
15-22
microsatellite is not responsible for
variation in IGF1 levels, but rather is in linkage disequilibrium with functional
genetic variants in the IGF1 promoter (Wong et al. 2005). The CA
15-22
is localized
to a haplotype block that spans 20 kilobase pairs upstream from the IGF1 translation
start site (Figure 4.1).
To localize candidate regulatory sequences within this haplotype block,
evolutionarily conserved regions were identified within the IGF1 promoter region by
comparison of sequence between a number of vertebrates (human, mouse, rat, dog).
The assumption is that nucleotide sequences involved in regulating gene expression
maintain a higher percent similarity/identity than do non-critical sequences under the
neutral evolution model (Boffelli et al. 2003; Loots et al. 2000; Woolfe et al. 2005).
We then resequenced these conserved regions in a sample of Singapore Chinese
(N=60 controls, Singapore Chinese Health Study). We identified one IGF1 promoter
SNP that lies in a potentially functional element. We found this SNP to be
associated with colorectal cancer risk in Singapore Chinese.
67
Figure 4.1. Genomic location of IGF1 regulatory polymorphisms and
corresponding pairwise |D'| plots. Upper panel: Location of the identified SNPs and
reported (CA)
n
in the Insulin-like Growth Factor1 promoter region. The arrow
indicates the transcriptional direction of the IGF1 gene. Lower panel: Linkage
disequilibrium (LD) blocks surrounding the Insulin-like Growth Factor1 locus in
Han Chinese are indicated as highlighted triangles (HapMap, haplotype block
structure per Gabriel et al 2001). The haplotype blocks are defined as sets of
consecutive sites between which there is little or no evidence of historical
recombination. The diagonal white bar indicates the physical length of the genomic
region 20 KBp upstream and 10 KBp downstream of the IGF gene. Short black lines
plot the position of each SNP to the chromosomal region. Comparisons between
neighbouring SNPs are indicated along the diagonal. Each square plots the level of
LD (measured by |D'|) between a pair of SNPs/sites. Red box: strong LD (|D'|=1;
LOD>2); blue box:weak LD(|D'|=1; LOD<2); Others: inconclusive A haplotype
block is created if 95% of informative (i.e. non-inconclusive) comparisons are
"strong LD". Not drawn to scale.
-969 -533 -484
(CA) n C/T G/A
(Rosen 1998) (Chapter 3)
5’
3’
-2995
G/T
(Chapter 4)
IGF1
68
4.2 Materials and Methods
In Silico Methods
To identify evolutionarily conserved regions (ECRs), we compared the
human sequence (NCBI Build 35 in the UCSC human May 2004 assembly, hg17)
ten kilobase pairs upstream of the IGF1 translation start site (NCBI accession #
AC010202, nucleotide 84199) with mouse, rat and dog (UCSC assembly: mm6, rn3,
canFam1 respectively) sequence. Pairwise alignments were constructed and the
nucleotide level match-mismatch similarity profiles were compared with the blastz
algorithm(Schwartz et al. 2003) incorporated in the ECR Browser portal
(Ovcharenko et al. 2004). Regions with conserved elements were defined as
intervals that exceed the threshold of 200
base pairs with >80% nucleotide identity.
Putative binding sites for transcription factors within the conserved sequences were
predicted with the MatInspector software (http://www.genomatrix.de/). Nucleotide
changes in any single nucleotide polymorphisms discovered in the re-sequencing
process were evaluated for impact/changes in the consensus sequences for the
relevant transcription binding sites. For each allele, the effect on potential
transcription factor binding resulting from the nucleotide exchange (either deleted or
generated) is calculated.
Laboratory Methods
Resequencing
69
To identify common polymorphisms in the IGF1 evolutionarily conserved
regions, the conserved regions were resequenced in sixty individuals from the
Singapore Chinese Health Study (Han Chinese ancestry from southern China,
Guangxi and Fuxian province). Overlapping segments were amplified using the sets
of primers (Table 4.1). Sequencing was carried out using an ABI Prism 3700 DNA
Sequencer (PE Biosystems, Foster City CA).
Table 4.1. Locations of the evolutionarily conserved regions within 10 kilo base
pair upstream of the IGF1 translational start site and primers for the re-sequencing of
these regions in Singapore Chinese.
Evolutionarily
conserved
regions
Genomic position
(NCBI#AC010202)
Length
(basepairs)
Percent
identity
(%) Primers
ECR1
NCBI#S85346
nt:1587-2053 466 >80 described in Chapter 3
ECR2 82871-83140 271 87.1
5’TGATGTGTCAGTCCCCTG3’
5’GGAGTCTGTGTGCCAGAGTG3’
ECR3 81301-81600 256 80.0
5’TGGTGGCATGTTTATTGCTC3’
5’GCTCGGTGCACAGATATAACC3’
ECR4 80831-81100 262 81.7
5’AAGACTGGGAACATGGCTTG3’
5’AGCCCAAGAGGAGTTCAGGT3’
Note: ECR1 was resequenced per Chapter 3. ECRs are labeled per Figure 4.2.
Genotyping
Genomic DNA was isolated from peripheral blood lymphocytes and buccal
cell samples using a QIAamp 96 DNA Blood Kit (Qiagen, Valencia, CA). The
identification and genotyping for the IGF1-533 SNP (rs5742612, dbSNP build 124)
was previously described (Wong et al. 2005). The genotypes for the IGF1 -2995 C/A
(rs12579108, dbSNP build 124) were determined using the fluorogenic 5’-nuclease
assay (Lee et al. 1993). The oligonucleotides primers for amplification of the region
70
surrounding the SNP were 5’AGG AGT GGA TGT TCT TAT GAT AAG CA3’ and
5’ CTG CAA AAA TCT GC AGT GAG ATA TG3’. The fluorogenic allele-specific
oligonucleotide probes (TaqMan MGB Probes, Applied Biosystems Inc, Foster City,
CA) to detect each of the alleles were: a) G allele: VIC labeled 5’ TCC TTG CGG
TTA GCT A 3’; b) 6FAM-labelled 5’ATC CTT GCT GTT AGC TAT 3’. PCR
amplification using ~ 10ng of genomic DNA was performed in a thermal cycler
(MWG Biotech, High Point, NC) with an initial step of 95 C for 10 mins followed by
50 cycles of 95 C for 25sec and 62 C for 60 sec. The fluorescence profile of each
well was measured in an ABI 7900HT Detection System and the results analyzed
with Sequence Detection Software (ABI). Genotype calls for individual samples are
made by plotting the normalized intensity of the reporter dyes in each sample well on
a cartesian plot. A clustering algorithm in the data analysis software assigns
individual sample data to a particular genotype cluster. All analyses were performed
blinded to case or control status. The concordance rate for the 24 pairs of duplicates
was 100%.
Statistical Methods
Although we sampled our controls from the whole cohort, this study is more
case-control than case-cohort in design, because the time period of follow-up was
comparable between the cases and subcohort, with only 13 subjects in the latter
group developing colorectal cancer during the observation period.
Specifically, to assess the extent of cancer risk associated with genotypes,
unconditional multiple logistic regression models (Breslow and Day 1980) were
71
fitted and odds ratio (ORs) and their corresponding 95% confidence intervals
(CIs) were reported. All logistic regression models included age at recruitment
(continuous), year of recruitment, gender and dialect group (Cantonese, Hokkien)
as covariates. Colorectal cancer risk factors which were considered as potential
confounders were body mass index (<20, 20 to <24, 24 to <28, 28+ kgm
-1
),
height, education levels (no formal schooling, primary school, secondary school
and higher), alcohol intake (non-drinker, monthly drinker, weekly drinker, daily
drinker), smoking history (never smoker, ex-smoker, current smoker), physical
activity (no, yes), calcium intake and dietary fats intake. None were included in
the final model because the parameter estimates were similar, i.e. inclusion did
not substantially alter (>5%) the parameter estimates for the exposures
(genotypes).
Colorectal cancer was coded by anatomic subsites per the International
Classification of Disease Oncology (2
nd
ed.): colon (C18.0-C18.9) and rectal
(C19.0-C20.0) cancers. To test for heterogeneity of odds ratios across anatomic
subsite, polychotomous logistic regression models were fitted and likelihood ratio
tests were conducted.
To investigate the possible interaction of the IGF1 genotype with measures
of energy balance (body mass index) as well as gender and factors associated with
serum IGF1 in this population (calcium intake, saturated fats, physical inactivity
and vitamin intake) (Probst-Hensch et al. 2003), the respective multiplicative
72
interaction terms were included in the regression models and likelihood ratio tests
were conducted for significance of the interaction parameters.
Allele frequencies were determined by gene counting (Li 1976). The
observed allele frequencies among controls were used to calculate the expected
genotype frequencies under Hardy-Weinberg equilibrium. Departures from Hardy-
Weinberg equilibrium (HWE) was assessed by testing the difference between the
observed (sampled) and expected (under HWE) genotype frequencies in controls
using a 3
2
test (Chiano and Clayton 1998).
Interaction between the two IGF1 SNPs on cancer risk
To investigate the possibility that the two SNPs may interact with each other,
we stratified individuals according to the genotype of one
IGF1 SNP (i.e. IGF1-2995
C/A) and performed stratum-specific analyses of the other locus (i.e. IGF1 -533
C/T).
IGF1 haplotypes and cancer risk association analyses
Linkage disequilibrium (LD) between IGF1 polymorphisms was assessed by
was assessed by D', a measure of LD that is corrected
for allele frequencies at each of
the two IGF1 SNPs. Individuals were classified into four groups: the three common
genotype combinations and the rare combinations. Odds ratios for each group were
estimated in logistic regression models in comparison to the baseline group (having
two copies of the “protective” allele at each of the two IGF1 loci).
IGF1 genotype and haplotype correlations with the serum IGF1
73
Of the 1146 controls in this study, 628 had serum IGF1 and 595 had serum
IGFBP3 measurements available (described previously by Probst-Hensch and
colleagues (DeLellis et al. 2003)). Of the 628, 12 with no genotype data were treated
as missing data. Kruskal-Wallis test statistics were used to compare distributions of
the serum markers by genotype categories. Analysis of covariance was used to
compare the means of serum IGF1 across the common haplotype groups, adjusting
for age at recruitment (continuous), year of recruitment, gender and dialect group
(Cantonese, Hokkien). Age, sex, body mass index, dialect group and year of
recruitment were also considered as potential confounders but were not reported as
none of these non-genetic risk factors acted as confounders. The mean the IGF1
concentrations within each haplotype group were presented as least squared means.
All p-values are two-sided and statistical analyses were performed using
STATA 8.0 (Stata Corp, College Station, TX).
4.3 Results
Study characteristics
The baseline characteristics of the Singapore Chinese Health Study cohort
have been described in Chapter 3. For case-control study nested within the cohort,
Table 4.2 describes the distributions of demographic and risk factors between cases
and controls.
74
Table 4.2. Selected characteristics of colorectal cancer cases and controls for the
IGF1 -2995C/A nested case-control study, the Singapore Chinese Health Study
Characteristics Controls (n=1146)
a
Cases (n=300)
a
p-value
b
Sex
Males 492 (43.0) 171 (57.0)
Females 654 (57.0) 129 (43.0)
<0.001
Dialect Group
Cantonese 562 (49.0) 133 (44.3)
Hokkien 584 (51.0) 167 (55.7) 0.21
Body Mass Index (kg/m
2
)
20 181 (15.8) 46 (15.3)
20-<24 640 (55.8) 143 (47.7)
24-<28 262 (23.9) 90 (30.0)
28+ 63 (5.5) 21 (7.0)
0.04
Height
160 (147,173)
160 (147,173)
0.02
Physical inactivity
c
Yes 946 (82.5) 249 (83.0)
No 200 (17.5) 51 (17.0) 0.92
Education level
None (formal) 306 (26.7)
95 (31.7)
High school
773 (67.5)
195 (65.0)
Post-high school
44 (3.8)
6 (2.0)
University 23 (2.0)
4 (1.4)
0.003
Cigarette smoking (cigarette and/or water pipe)
Never 833 (72.7) 179 (59.7)
Former 127 (11.1) 49 (16.3)
Current 186 (16.2) 72 (24.0) <0.001
Frequency of alcohol consumption
Nondrinkers 937 (81.8) 237 (79.0)
Monthly 85 (7.4) 19 (6.3)
Weekly 91 (7.9) 27 (9.0)
Daily 33 (2.9) 17 (5.7) 0.09
Total calories (kcal/day)
1484.6 (831.4, 2483.5)
1489.0 (808.9, 2588.6)
0.79
Total calcium intake (mg/day)
373.5 (158.4, 857.1)
360.7 (154.7, 790.1)
0.48
Total fiber intake (g/day)
12.3 (5.0, 23.2) 11.9 (4.3, 22.8) 0.68
Total fat (g/day)
40.6 (19.8, 82.2)
39.5 (18.3, 77.3)
0.51
a
Number of subjects (%) or median (5
th
percentile, 95
th
percentile).
b
Two-sided P-
values derived from Kruskal-Wallis test.
c
Physical inactivity: Yes=No weekly
vigorous or strenuous sports and 9 h of sitting/day; No=All others.
Note: 12 cases and 35 controls were excluded due to missing genotypes. Calcium
intake is missing 2 cases and 1 control.
75
Polymorphisms in the evolutionarily conserved regions within the IGF1 promoter
Based on our previous report (Wong et al. 2005), this report proposes that
the haplotype block spanning the IGF1 promoter harbors functional IGF1
polymorphisms that may impact cancer risk in the population (Figure 4.1). We
delimit borders for distant cis-regulatory elements that regulate IGF1 expression by
defining evolutionarily conserved regions across vertebrates (Figure 4.2). We have
previously resequenced one of the four conserved regions that spans the 5’ UTR
(ECR1, Figure 4.2) and identified 2 SNPs (IGF1 -533C/T and -484G/A). This study
reports the resequencing of the remaining conserved regions within ten kilo base
pairs from the transcription start site (ECR2, ECR3 and ECR4, Figure 4.2).
The resequencing project within 60 Han Chinese residing in Singapore
identified one common SNP (minor allele frequency, MAF=0.35) i.e., IGF1-2995
G/A, numbered
relative to the IGF1 transcription
start site. The IGF1-2995 C/A SNP
is listed in the Perlegen polymorphism database (rs12579108, dbSNP build 124;
MAF=0.42 in 24 Han Chinese, Perlegen panel).
Figure 4.2. Evolutionary conserved regions (ECR) in the 5’ untranslated region of the human Insulin-like Growth
Factor1. Conservation profiles of the human IGF1 upstream regulatory region in reference to the mouse (top panel), rat
(middle panel) and dog (bottom panel). The vertical axis for each panel indicates the percent identity for regions >50%.
The human IGF1 DNA sequence lies linear along the horizontal x-axis. The black arrow indicates the transcriptional
direction. Peaks depict regions of conservation and colored according to location of the regions; blue=IGF1 first exon,
yellow=5’ IGF1 UTR and red=IGF1 upstream regulatory regions. Red bars indicated evolutionarily conserved regions
(exceed at 100 bp/80% identity threshold). Green bars in the last panel indicate regions of repeat sequences. Black boxes
delimit the genomic regions that are resequenced for polymorphisms in 60 Han Chinese.
76
ECR1 ECR2 ECR3 ECR4
Potential transcription factor binding sites are over-represented in the
evolutionarily conserved regions (Figure 4.3). . Based on transcription factor
binding site prediction algorithms, this IGF1-2995 C/A resides in a consensus
domain for a transcription factor: octamer binding factor (Oct1/Oct2). The A allele
destroys the predicted binding site for Oct1/Oct2. Thus, in silico
prediction suggests
that the -2995C allele is more likely than the -2995A allele to
bind octamer binding
factor proteins.
Figure 4.3. Predicted binding sites for transcription factors in the human Insulin-like Growth Factor1 upstream
regulatory regions. Legends per Figure 4.2. Peaks indicate the human IGF1 conservation profile as compared to
homologous mouse sequences. The black letters indicate transcription factors with potential binding sites in the region as
predicted by TRANSFAC.
78
IGF1 genotype-colorectal cancer association study
Genotype distributions for the -2995 C/A SNP did not deviate from Hardy-
Weinberg expectations. Table 4.3 summarizes the effect of the -2995 C/A SNP on
colorectal cancer risk in Singapore Chinese. An approximate 40 per cent decrease in
risk was associated with possession of one or two copies of the A allele (genotypes
AA and CA) as compared to those not carrying a copy (genotype CC). This
association was stronger for colon than for rectal cancer (p for heterogeneity <
0.001).
80
Table 4.3. Odds ratios (ORs) and 95 percent confidence intervals (95%CIs) for
the IGF1 -2995 C/A genotype and colorectal cancer, Singapore Chinese Health
Study
Genotype Controls(%) Cases(%) OR(95%CI)
a
CC 482(42.0) 161(53.7) 1.00 (referent)
CA 535(46.7) 106(35.3) 0.55 (0.41,0.74)
AA 129(11.3) 33(11.0) 0.69 (0.44,1.07)
CA/AA vs. CC 0.58 (0.44,0.76)
Subsite
Colon
b
CC 482(42.0) 99(56.6) 1.00 (referent)
CA 535(46.7) 59(33.7) 0.51 (0.36,0.73)
AA 129(11.3) 17(9.7) 0.59 (0.33,1.04)
CA/AA vs. CC 0.52 (0.38,0.74)
Rectal
b
CC 482(42.0) 63(50.0) 1.00 (referent)
CA 535(46.7) 47(37.3) 0.65 (0.43,0.98)
AA 129(11.3) 16(12.7) 0.88 (0.48,1.61)
CA/AA vs. CC 0.70 (0.48,1.01)
p for heterogeneity < 0.001
c
a
odds ratios from unconditional logistic regression; adjusted for age (year) at
recruitment, gender, dialect groups (Cantonese, Hokkien), and year of recruitment
(continuous).
b
odds ratios from polychotomous logistic regression; adjusted for age at recruitment,
gender, dialect groups (Cantonese or Hokkien), and year of recruitment
(continuous).
c
The odds of the cases carrying the IGF1 -2995 genotype CC compared to the
combined genotypes of CA/AA were contrasted between colon cancer and rectal
cancer cases
Note: missing 35 controls and 12 cases
Interaction with energy balance factors with the IGF1 genotype-colorectal cancer
risk association
Since IGF1 is thought to increase cancer risk by mediating the effects of
obesity-related insulin resistance, we examined whether two measures of energy
balance modify the IGF1 genotype-cancer risk association: 1) physical inactivity (no
81
weekly vigorous or strenuous sports and 9 h of sitting/day); 2) body mass index.
The effect of the IGF1 -2995 C/A was approximately two-fold stronger in physically
active individuals (Table 4.4; p=0.057). No gene-environment interaction was
detected for body mass index. In addition, no gene-environment interaction was
observed for the dietary factors that were previously reported to predict serum IGF1
levels in this population(Probst-Hensch et al. 2003): calcium intake, saturated fats or
vitamin intake (data not shown).
Table 4.4. Odds ratios (ORs) and 95 percent confidence intervals (95%CIs) for
the IGF1 -2995C/A genotype and colorectal cancer by physical activity, Singapore
Chinese Health Study
Genotype Controls(%) Cases(%) OR(95%CI)
a
Physically inactive
(No weekly vigorous or strenous sports and 9 h of sitting/day)
CC 400(42.3) 128(51.4) 1.00 (referent)
CA/AA 546(57.7) 121(48.6) 0.66 (0.49,0.88)
Not Physically inactive
(Others)
CC 82(41.0) 33(64.7) 1.00 (referent)
CA/AA 118(59.0) 18(35.3) 0.30 (0.15,0.60)
p for interaction = 0.057
b
a
odds ratio from unconditional logistic regression; adjusted for age (year) at
recruitment, gender, dialect groups (Cantonese, Hokkien), and year of recruitment
(continuous).
b
departure from multiplicative interaction where the product term = physical activity
(no, yes) and IGF1-2995 C/A genotypes (CC vs. CA/AA), adjusted for age (year) at
recruitment, gender, dialect groups (Cantonese, Hokkien), and year of recruitment
(continuous).
82
Multilocus analysis (IGF1-533C/T and IGF1-2995C/A)
We have previously reported an association between colorectal cancer risk
and a SNP downstream from the -2995 locus, IGF1 -533C/T(Wong et al. 2005).
The new SNP in this report, IGF1 -2995 G/A is in tight linkage disequilibrium with
the IGF1-533C/T (D'=0.97). Thus only three common genotype combinations were
observed (Table 4.5). As compared to those carrying zero risk alleles, individuals
with two risk alleles were at 2.8-fold increased risk, and those with four risk alleles
were at 4.3-fold increased risk of colorectal cancer.
Table 4.5 Genotype combinations of the IGF1 -2995 C/A and -533 C/T and
colorectal cancer risk, Singapore Chinese Health Study.
Diplotype
configuration
Genotype
combinations of
-2995 C/A and
-533 C/T
N #risk
alleles
a
Odds Ratio
(95 %CI)
b
AC/AC AA_CC 123 0 1.0 (reference)
CT/AC
(or CC/AT)
CA_CT 475 2 2.84 (1.92,4.21)
CT/CT CC_TT 536 4 4.35 (3.00,6.30)
Rare haplotypes All others 28 1 or 3 8.52 (3.52, 20.57)
a
Risk alleles are the C allele from -2995 C/A and the T allele from -533 C/T,
assuming additive effects of both loci. The reference group is the combination of the
haplotypes with the known phase -2995A allele and -533C allele.
b
Odds ratio estimated from logistic regression, adjusted for age (year) at
recruitment, gender, dialect groups (Cantonese, Hokkien), and year of recruitment
(continuous) and further adjusted for the other haplotype combinations.
IGF1 genotype-phenotype (serum IGF1) association study
Elevated circulating IGF1 levels associate with increased colon cancer risk.
Hence, the IGF1 genotype-colon cancer association observed in our study might act
through serum level changes. However, in our study, the -2995 C/A SNP did not
predict serum IGF1 levels in controls (Figure 4.4, p=0.17). The median values for
83
the CC, CA and AA genotypes were 129.5 (95%CI: 116.3, 149.7), 132.9 (95%CI:
124.9, 137.7) and 122.3 (112.2, 132.1) ng/ml respectively.
0 100 200 300 400
Serum IGF1 (ng/mL)
AA CA CC
Figure 4.4: Serum IGF1, by IGF1 -2995 C/A genotypes
Neither did the genotype combinations predict serum IGF1 levels (Table 4.6).
Table 4.6 Genotype combinations of the IGF1 -2995 C/A and -533 C/T and
serum IGF1 levels, Singapore Chinese Health Study.
Genotype combinations
-2995 C/A and
-533 C/T
Haplotype
configuration
N # risk
alleles
a
Serum IGF1
Mean (standard
error)
c
AA_CC AC/AC 71 0 137.1 (6.3)
CA_CT CC/AT
CT/AC
273 2 136.6 (3.27)
CC_TT CT/CT 272 4 128.8 (3.22)
a
Risk alleles are the C allele from -2995 C/A and the T allele from -533 C/T.
b
Least squared means (presented as adjusted mean values of serum IGF1 for age
(year) at recruitment, gender, dialect groups (Cantonese, Hokkien), and year of
recruitment (continuous)) estimated from generalized linear models.
Note: N=628 controls with serum IGF1 measurements and 12 missing genotypes.
84
4.4 Discussion
This is the first report of the characterization of the allelic architecture
surrounding the IGF1 promoter region (10 kilo base pairs upstream of the translation
start site) in relation to cancer risk. A putative regulatory IGF1 SNP in the promoter
region is associated with reduced colorectal cancer risk of approximately 40 per cent.
The effect is stronger in colon cancer versus rectum cancer and is more apparent in
physically inactive persons.
The human IGF1 gene spans approximately 90 kb and encodes five exons
(Figure 4.1), two alternative first exons (exon 1 and exon 2) and 4 coding exons.
Two common IGF1 splice mRNA variants arise from two IGF1 promoters. No
common sequence variation (frequency > 0.02) was observed in the coding regions
of the IGF1 gene. Thus, the genetic variants that affect IGF1 levels are probably in
the regulatory regions, i.e., upstream enhancers, promoter, introns or 3’ untranslated
regions.
Little is known about regulatory IGF1 polymorphisms and their impact on
cancer risk. The only studied IGF1 variant lies in the IGF1 promoter region: a
cytosine-adenosine dinucleotide (IGF1(CA)
n
) repeated 15- 22 times approximately
one kilobase pairs upstream of the first transcription start site of the more common
splice variant. This IGF1(CA)
n
microsatellite is associated with colorectal cancer in
the Singapore Chinese (this population) as well as in some Caucasian populations
(Morimoto et al. 2005; Slattery et al. 2005) but not all (Slattery et al. 2004). In those
studies reporting associations, different alleles were associated with risk. We
considered the possibility that these associations with different alleles are due to
85
linkage disequilibrium with another polymorphism(s) that is functional. The
hypermutable nature of the microsatellite may result in these causal variant(s) linked
to various haplotypic backgrounds.
We previously re-sequenced the region between the microsatellite and the
transcription start site and identified two SNPs in partial linkage disequilibrium with
the microsatellite and in perfect linkage disequilibrium with each other. Thus, only
one of the SNPs (IGF1 -533 C/T) was examined in relation to colorectal cancer risk.
The IGF1 -533 C/T SNP is the first IGF1 SNP reported to associate with cancer risk.
This SNP lies within a haplotype block spanning the promoter region. The
functionality of this SNP is unknown. This current report considers
the possibility
that there may be other potentially functional variants within the same haplotype
block.
To dissect the haplotype block for these functional SNPs, we identified and
resequenced regions with a high probability to harbor functional elements (Figure
4.2). The two SNPs in our previous report are in a conserved region that covers the
5’ untranslated region (ECR1, Figure 4.2). Upon resequencing the rest of the
conserved DNA stretches (ECR2-4, Figure 4.2), we identified one SNP, IGF1-2995
C/A. The low abundance of polymorphisms is not surprising; 20-fold fewer SNPs
have been found in conserved regions(Bejerano et al. 2004).
The IGF1 -2995 C/A is associated with colorectal cancer (Table 4.2). The
IGF1-cancer association is unlikely an artifact due to selection bias or population
stratification. This genetic association is probably due to variation in IGF1 gene
itself and not to neighboring genes, which lie in separate haplotype blocks. Further,
86
IGF1 displays heritable allele-specific expression (Pastinen et al. 2004) that argues
for the contribution of cis-acting regulatory polymorphisms. Further studies are
warranted in Asian populations. Based on the Perlegen panels, the minor allele
frequency is lower in Caucasians (p(A)=0.021) and African-Americans (p(A)=0).
The IGF1 -2995 C/A effect on colorectal cancer is more apparent in
physically active persons as compared to physically inactive persons. IGF1 is
thought to mediate the effect of energy balance on cancer. Probst-Hensch and
colleagues previously reported that increased physical activity was associated with
decreased serum IGF1 in this population (Probst-Hensch et al. 2001). The literature
regarding whether exercise reduces IGF1 levels remains mixed; some (Melikoglu et
al. 2005; Ngo et al. 2002) but not all studies (Gapstur et al. 2004; McTiernan et al.
2005; Schmitz et al. 2005) are in agreement with physical inactivity predicting lower
serum IGF1 levels. In agreement with our observations, a case-control study of
predominantly Caucasians (1,346 colon cases and 1,544 controls) observed an 40 %
reduction in colon cancer risk with the IGF1 (CA)
n
(which is in partial LD with the -
2995 SNP) among those with high physical activity (odds ratio: 0.57; 95%
confidence interval: 0.39-0.83; p interaction 0.01) (Slattery et al. 2005). Effect-
modification was not observed for the other measure of energy balance, generalized
obesity (body mass index, BMI) which may not be a sensitive indicator of insulin
sensitivity(Alberti et al. 2005).
Elevated circulating IGF1 levels associate with increased colon cancer risk in
some studies. Hence, the genetic IGF1-colon cancer association observed in our
study might be expected to act through plasma/serum level changes. Further, if the
87
circulating IGF1 levels are considered as intermediate phenotype, the proportion of
variance due to the IGF1 SNP is expected to be larger for the serum IGF1 levels as
compared to cancer incidence rates. In our study, the -2995 C/A SNP did not predict
serum IGF1 levels in 628 controls. Comparisons
of tissue-specific regulation of
IGF-I mRNA in mouse strains suggest that serum
IGF1 concentration does not
necessarily predict local
IGF1 mRNA expression in all tissues (Iida et al. 2005).
While at the fetal stage, the primary source of human IGF1 is at the local level,
circulating IGF1 is thought to augment the local levels via production from the liver
in response to the growth hormone system and nutrition at the adult stage (Ueki et al.
2000). Thus, IGF1 genotypes may be a better marker for colorectal cancer risk.
Acknowledgements
The Singapore Chinese Health Study has been supported by grants R01
CA55069, R35 CA53890, and R01 CA80205 from the National Cancer Institute,
Bethesda, Maryland. We thank Ms. Siew-Hong Low of the National University of
Singapore for supervising the field work of the Singapore Chinese Health Study, and
Ms. Kazuko Arakawa and Dr. Canlan Sun of the University of Minnesota for the
development and management of the cohort study database.
88
Chapter 5: Epigenetic variation in the Insulin-Like Growth Factor 2
5.1 Introduction
To address epigenetic abnormalities in cancer, we developed a novel assay
that uses DNA isolated from peripheral blood to classify persons as to whether they
have a common epigenetic abnormality (i.e., loss of imprinting, LOI) or not (normal
imprinting). Epidemiologic studies currently are not able to measure LOI with the
established methods that require abundant high-quality RNA. Our DNA-based assay
is highly reproducible and quantitative (Section 5.3.2). This chapter contains a
rationale for a LOI measurement in epidemiologic studies and a manuscript detailing
the development of the methodology.
5.2 Background
Genomic imprinting is a normal phenomenon where one of the two parental
alleles is exclusively responsible for the levels of the gene product in the cell.
Normal imprinting is crucial for mammalian development(Ferguson-Smith and
Surani 2001; Reik and Walter 2001). In a mouse model that mimics global
imprinting defects, global loss of imprinting predisposes to cancer(Holm et al. 2005).
In humans, loss of imprinting for genes encoding the Insulin-like Growth Factor 2
(IGF2) is frequent in numerous cancers as well as in tissues of persons with high risk
of cancer (Table 5.1). IGF2 is maternally imprinted and thus, exclusively expressed
from the paternal allele. IGF2 regulates cell growth; dysregulated expression of
IGF2 may predispose to colorectal cancer. In most tissues except fetal, liver and
central nervous system, normal human IGF2 expression is skewed i.e.,
monoexpression that predominates from the paternal allele (maternal imprinting)
89
(Giannoukakis et al. 1993; Ohlsson et al. 1993). The imprinting of the IGF2 gene is
promoter-specific(Ekstrom 1994; Vu and Hoffman 1994), tissue-specific (Wu et al.
1997) and developmentally-regulated (Reik and Walter 2001). Dysruption of IGF2
imprinting (loss of imprinting, LOI) results in the biallelic expression of IGF2
mRNA levels(Ravenel et al. 2001) that increases cell proliferation (Hofmann et al.
2002) and is necessary for adenomas progression to carcinomas(Christofori et al.
1995).
Imprinting is, in part, genetically determined(Cruz-Correa et al. 2004;
Sakatani et al. 2001; Sandovici et al. 2003) but yet, by design, is unstable and
susceptible to environmental insults(Jaenisch and Bird 2003; Thompson et al. 2001).
The consequent functional haploidy enhances susceptibility to cancer, molar (extra-
placenta) pregnancies, neurodevelopmental and neurobehavioural disorders. In
particular for cancer, deregulation of imprinted genes in the growth-related pathways
may increase expression of a potent mitogen and thereby, enhance growth-promoting
signals that predisposes to cancer. A common imprinting abnormality is loss of
imprinting (LOI), defined operationally as loss of preferential parental origin-
specific gene expression that may result in (1) biallelic expression via reactivation of
the normally silent allele (2) epigenetic silencing via silencing of the normally
expressed allele(Feinberg et al. 2002).
Germline loss of imprinting (LOI) is a common epigenetic abnormality that is
heritable(Cruz-Correa et al. 2004; Sandovici et al. 2003), influenced by the
environment(Jaenisch and Bird 2003) and possibly increases with age(Ahuja and
90
Issa 2000). Ten percent of the general population(Cui et al. 1998; Sakatani et al.
2001) is estimated to harbor germline LOI for IGF2 (Table 5.1).
Germline LOI is hypothesized to predict risk of colon cancer and thus may be
useful for early detection. Despite the potential public health impact, much is
unexplored due to a lack of a DNA-based measurement of LOI. To date, an
epidemiologic measurement of germline LOI has yet to be developed. The current
gold standard for measuring LOI requires intact RNA (Figure 5.1), which is not easy
to obtain. For example, Woodson and colleagues reported their inability to examine
germline LOI and colon cancer in their study due to the insufficient RNA quality
obtained from stored
blood samples(Woodson et al. 2004). By contrast, DNA is
stable in archival biospecimens(Patel et al. 2003).
91
Table 5.1. The prevalence of loss of imprinting (measured as RNA-based allele
ratio) of the genes encoding Insulin-like Growth Factor 2 and H19 in the general
population, persons at high risk for cancer and adult cancer.
Population Prevalence of IGF2
LOI (proportion)
ref
Allele ratio
for IGF2 LOI
Presence
of H19 LOI
(proportion)
Source of mRNA
Healthy population
Japanese
a
White
b
Black
b
10% (4/38)
13% (2/15)
12% (2/16)
14% (N/A)
[:\ > 0.5
\:[ < 3:1
\:[ < 3:1
\:[ < 3:1
N/A
N/A
N/A
N/A
peripheral blood
peripheral blood
colon mucosa
colon mucosa
Persons at high risk for cancer
c
Personal history of adenoma
Family history (cancer)
23% (13/56)
41% ( 7/17)
28%(14/50)
38%(3/8)
\:[ < 3:1
qPCR
\:[ < 3:1
qPCR
N/A
N/A
peripheral blood
colon mucosa
peripheral blood
colon mucosa
Cancer
Ectoderm
Brain (glioma)
Mesoderm
Lung
Kidney
Acute myeloid
leukemia
Endoderm
Colorectal
Prostate
Ovarian
Cervical
Breast
57% (8/14)
47% (7/15)
50% (7/14)
56% (9/16)
30% (9/12)
12% (2/17)
56% (5/9)
44% (12/27)
38% (3/8)
83% (10/12)
55% (6/11)
25% (5/20) *
39% (7/18) *
12% (2/17)
5% (2/44)
RFLP
\:[ < 3:1
RFLP
RFLP
RFLP
RFLP
\:[ < 3:1
\:[ < 3:1
AS-PCR
RFLP
RFLP
RFLP
RFLP
RFLP
AS-PCR
No (0/13)
No (0/16)
No (0/9)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Yes (8/13)
Yes (4/17)
Yes (5/14)
No (0/18)
N/A
glioma
adenocarcinoma
renal cell carcinoma
leukemia
peripheral blood
colon mucosa
carcinoma
carcinoma
carcinoma
carcinoma
carcinoma
a
persons with no clinical signs of cancer.
b
controls with colon resections for diseases other than cancer including
diverticulosis, Crohn’s stricture and perforation.
c
family history of cancer or personal history of cancer precursor.
Measurement of IGF2 LOI/ IGF2 mRNA allelic expression ratio: [:\ > 0.5
= RFLP with the ratio of the less abundant allele versus the more abundant allele >
0.5;\:[ < 3:1= modified PCR for the IGF2 Apa1 RFLP with allele ratio of the more
abundant allele versus the less abundant allele arbitrarily chosen threshold of < 3:1;
qPCR=real-time reverse-transcription PCR using the \:[ < 3:1; AS-PCR= exon-
connection and allele-specific PCR for the IGF2 Apa1 restriction fragment length
polymorphism; RFLP= presence or absence of digest fragments of the Apa1
restriction fragment length polymorphism and may overestimate LOI due to genomic
DNA contamination(Yun et al. 1999). * loss of imprinting due to promoter usage
from the imprinted P3 and P4 to the normally biallelic P1. N/A: not described in the
study.
92
Figure 5.1. Comparison of the LOI assays based on mRNA expression (left
panel) and DNA methylation (right panel). Both assays require parent-specific
marks to differentiate between the allele, in this figure, a G/A SNP. The G and A
respectively labels the allele for a SNP on a parental strand that is present in the
cDNA (RNA-based assay, left panel) or is within the methylation measurement
range of the CpGs of interest (DNA-based assay, right panel). The lollipops depict
CpG doublets; open, unmethylated and closed, methylated.
While the mechanism of imprinting is in its infancy, a regulatory region
involves clusters of cytosine-guanine (CpG) dinucleotides methylated on one allele;
the other allele, unmethylated (differentially methylated regions, DMRs). DMRs
regulate the imprinting of genes in two manner: 1) imprinting centers that contain
germ-line imprints initiated in the parental germ cells and maintained throughout
fertilization and embryonic development(Ben-Porath and Cedar 2000; Lewis and
DNA-based LOI assay
Normal IGF2 imprinting
G
A
Loss of IGF2 Imprinting
G
A
RNA-based LOI assay
Loss of IGF2 imprinting
G
A
Normal IGF2 imprinting
G
A
G
G
93
Murrell 2004) gametic imprints within the imprinted gene where the epigenetic
marks are reprogrammed and set up during development.
DNA methylation is the only epigenetic mark retained in genomic DNA
isolated from biospecimens. Allele-specific DNA methylation is a potential
biomarker for germline LOI in prospective studies (Figure 5.1). LOI can be
identified by altered patterns of epigenetic marks, including methyl groups, placed
on the DNA(Reik and Walter 2001). However, the available methodologies are not
quantitative or are labor-intensive. We describe a novel, high-throughput method to
quantitate allele-specific DNA methylation based on bisulfite polymerase chain
reaction (PCR) and pyrosequencing. DNA is first treated with sodium bisulfite,
which converts cytosine but not 5-methylcytosine to uracil. Genes of interest are
subsequently amplified using PCR. Allele-specific methylation can then be
determined by allele-specific pyrosequencing.
This allele-specific methylation methodology can potentially afford
quantitative analyses in the regulation of X chromosome inactivation, allele-specific
expression of genes in the immune system, repetitive elements, and imprinting. As
an example of our new method, we quantitated allele-specific methylation within the
H19 imprinting center in a limited number of human bladder cancer samples.
The H19 imprinting centre controls expression of a growth factor implicated
in twenty cancers, IGF2(Feinberg et al. 2002) and its downstream neighbouring gene
H19. IGF2 is expressed from the paternal allele; H19 from the maternal
allele(Bartolomei and Tilghman 1997). One model of this reciprocal imprinting is
that the IGF2 and H19 promoters compete for the same downstream enhancers
94
where methylation imprints within the H19 imprinting center (H19 IC) determine
which allele will be expressed (Figure 5.2). In normal imprinting, the H19 IC is
methylated on the paternal allele and unmethylated on the maternal allele. The
enhancer competition model for H19 IC predicts that abnormal methylation at core
binding sequences for an insulator protein on the maternal allele (hypermethylation)
will result in expression from both the maternal and paternal IGF2 alleles. Abnormal
H19 IC methylation was observed in colorectal(Nakagawa et al. 2001),
osteosarcoma(Ulaner et al. 2003), Wilms tumours(Cui et al. 2001) and bladder(Takai
et al. 2001) cancer.
We compared our allele-specific methylation assay in the H19 imprinting
center to the current LOI assay based on biallelic mRNA expression. Of the
numerous methods of measuring biallelic expression, we chose the most sensitive
method, real-time RT-PCR (Section 5.3).
95
Figure 5.2. Regulation of the H19 imprinting centre in the expression of IGF2
and H19 (figure not drawn to scale). Filled lollipops represent methylated CpG
doublets in differential methylated regions. The H19 IC harbours binding sites for
the protein CCTCF binding factor (CTCF) that functions as a chromatin
insulator.
CTCF binds to the H19 IC in a methylation-dependent manner. The H19 IC is
normally methylated on the paternal allele and unmethylated on the maternal allele.
The insulator protein CTCF binds to unmethylated CTCF binding sites within the
H19 IC on the maternal allele and prevents the IGF2 promoters from interacting with
the downstream enhancers, leaving only the H19 promoter activated. Hence, the
maternal IGF2 allele is silent and the maternal H19 is expressed. On the paternal
allele, the methylated IC does not bind to CTCF, allowing the IGF2 promoters access
to the shared enhancers. The paternal methylated IC, through unclear mechanisms,
correlates with H19 promoter methylation, and thus the silencing of the H19
promoter. Thereby, the paternal IGF2 is expressed and the paternal H19 is silent
(after Leighton 1995(Leighton et al. 1995), Rand and Cedar, 2003(Rand and Cedar
2003)).
5.3 RNA-based LOI assay (gold standard)
While the gold standard for LOI assay is based on the allelic ratio of
messenger RNA (mRNA), various methodologies in RNA measurement with
inherent limitations exist. We have optimized an RNA-based assay based on the
most sensitive and reliable method to quantitate initial amounts of mRNA, real-time
reverse-transcriptase (RT) polymerase chain reaction (PCR). Our choice of the gold
IGF2 H19
IGF2 H19
CTCF
Enhancers
Enhancers
96
standard assay circumvents the inaccuracy in the more commonly used restriction-
endonuclease (RE) based assay, i.e. partial enzymatic digestion of reverse
transcriptase-polymerase chain reaction (RT-PCR) products and heteroduplex
formation skewing the results of restriction endonuclease digestion of PCR products.
The specificity of this assay was demonstrated in quantitation of allele-
specific IGF2 expression in colorectal cancer cell lines (Figure 5.3). This assay
includes checks for false positives to minimize misclassification of LOI vs. normal
imprinting. To control for co-amplification of contaminating genomic DNA during
the RT-PCR step that can overestimate the frequency of biallelic IGF2 expression,
DNAse digestion of contaminating genomic DNA was performed and a negative
control of RNA preparation that has not been converted to cDNA was included. The
samples were normalized for sample load with housekeeping transcripts PCNA.
97
Figure 5.3. Amplification plots for the G/G genotype (top panel) and A/A
genotype (bottom panel) of the IGF2 820G>A on the colorectal cancer cell lines
CaCO2 and Colo320 respectively. Three different fluorescence probes detect total
IGF2, the G allele and the A allele, respectively. Total IGF2 is used to to normalise
for amount of initial RNA. In the cell line with GG genotype, only the fluorescence
signal for the G allele and the total IGF2 probe are detected (top panel) and similarly
for the AA genotype cell line (bottom panel). Spike: total IGF2; diamond: G probe;
triangular: A probe. Horizontal bar: assay threshold where fluorescence beneath the
bar represents signal drift (detection of fluorescense without amplification of the
template) rather than exponential growth of PCR product during the log-linear phase.
Real-time RT-PCR monitors the first significant increase in amount of PCR product
as compared to baseline (^Rn, difference in recorded fluorescence intensity between
a PCR reaction and a no template control), representing the more reproducible
exponential phase rather than end-point accumulation or PCR products. A higher
initial copy number of the nucleic acid target correlates with an earlier cycle where
the first significant ^Rn is detected (i.e., lower threshold cycle, Ct).
Gold standard: Established LOI assay based on allele ratio of mRNA transcripts
This proposal will use real-time RT-PCR allelic discrimination techniques
based on the Taqman chemistry (PE Applied Biosystem, Foster City CA) modified
from Woodson et al. 2004. The real-time RT-PCR conditions were optimized for a
resolution between the G and A SNP within a reproducible temperature range of
G
A
98
initial exponential amplification (Ct < 40) at a probe concentration of 0.2uM and
annealing temperature of 63 C.
To establish LOI, RNA extracted from biological samples is reversely
transcribed (RT) into complementary DNA (cDNA). On persons heterozygous for a
transcribed polymorphism (present in the cDNA), the cDNA obtained from RT-
polymerase chain reaction (PCR) is the template for assays that reveal if one or two
alleles are expressed. Allelic ratio of the parental alleles was determined by
comparing the two alleles quantitatively using allele-specific real-time RT-PCR to
generate PCR amplication curves specific to each allele. The amplification curves
reflect the initial amount of mRNA in each sample. Therefore the molar amount of
mRNA transcripts for each allele can be compared.
Since previous literature have indicated that the distribution of imprinting
status is bimodal(Ravenel et al. 2001; Sakatani et al. 2001), this proposal will define
IGF2 imprinting status as a dichotomous variable where LOI is biallelic expression
(expression of both parental alleles) and normal imprinting is the expression of only
one allele. The majority of previous reports defined loss of imprinting as the ratio of
the less versus the more abundant allele at an arbitrarily chosen threshold (ratio =
1:3). This specific aim will provide an empirically-derived threshold of allele ratio
to define loss of imprinting. Figure 5.4 depicts a representative amplication plot for
normal imprinting (top panel) and loss of imprinting (bottom panel) as determined
by the RNA-based LOI assay in paired tumor and normal margins of bladder cancer
patients. We propose that the change from normal imprinting (mono-allelic
expression) to LOI (biallelic expression) corresponds to methylation changes within
99
the H19 IC. The following section details the development of allele-specific
methylation assay.
Figure 5.4. Amplification plots of the paired urothelium margins (left) and the
corresponding bladder tumor tissue (tumor). Top panel: Representation of a paired
normal-tumor tissue with normal imprinting with monoallelic expression of the allele
marked by the IGF2 820 A allele. Bottom panel: Representation of a paired normal-
tumor tissue with normal imprinting in the urothelium tissue (representing “normal”
tissue) and loss of imprinting as depicted by biallelic IGF2 expression in the
corresponding tumor tissue.
5.4 DNA-based LOI assay
Rationale
In imprinting, monoallelic expression is dependent on the parental origin of
the chromosome(Ferguson-Smith and Surani 2001). Normal genomic imprinting is
regulated, in part, by methyl groups on cytosines within cytosine-guanine (CpG)
dinucleotides. Since normal genomic imprinting is regulated, in part, by methyl
groups on cytosines within cytosine-guanine (CpG) dinucleotides, normal imprinting
or loss of imprinting(LOI) can be predicted by DNA methylation in regions that are
differentially methylated between parental alleles (differentially methylated regions,
100
DMRs)(Rand and Cedar 2003). As a proxy for parent-specific expression, there are
two current methodologies used to analyze DNA methylation. The first is bisulfite
genomic sequencing(Frommer et al. 1992) of multiple cloned alleles, a process that
is labor-intensive. The second is bisulfite pyrosequencing, a technique that does not
assess allele-specific methylation levels, but instead, averages methylation levels of
both alleles(Dupont 2004). Our new method employs both bisulfite PCR and allele-
specific pyrosequencing to measure DNA methylation of a single allele. To illustrate
our new methodology, we analyzed allele-specific methylation of the H19 gene that
is normally imprinted and expressed only from the maternal allele.
Outline of the allele-specific methylation methodology
To obtain the methylation status of the CpG sites of interest, we adapted a
standard method known as bisulfite genomic sequencing. In brief, this method is
based on the selective deamination of cytosine to uracil by treating DNA with
bisulfite and the sequencing of subsequently generated PCR products. In contrast to
cytosine, 5-methylcytosine does not get converted by bisulfite and remains as
cytosine. This inherent selectivity of bisulfite to induce a primary sequence change
can be used to distinguish DNA methylation status(Frommer et al. 1992).
DNA methylation at a specific CpG dinucleotide can then be quantitated as a ratio of
cytosine to thymine, for which several methods have been developed (Couvert et al.
2003; Dupont 2004; El-Maarii 2002; Gonzalgo and Jones 1997; Herman et al. 1996;
Lo et al. 1999; Shiao 2005; Tost et al. 2003; Xiong and Laird 1997).
In order to measure DNA methylation of each allele individually, we used
Pyrosequencing (Biotage, Uppsala Sweden) with sequencing primers that were
101
directed to a heterozygous single nucleotide polymorphism (SNP) in close proximity
to the CpG site of interest. Thus a pair of sequencing primers is used to measure
methylation of each allele separately. We demonstrate that this methodology
correctly identifies the percentage of allele-specific methylation within a 3 percent
margin of error.
An immediate health application of this allele-specific methylation
methodology is to classify persons as to whether or not they have loss of imprinting
in prospective epidemiologic studies. As a proof of principle, we present the
application of this methodology to study a methylation-dependent imprinting center:
the H19 imprinting center, which regulates the paternally imprinted non-coding RNA
H19(Bell and Felsenfeld 2000; Holmgren et al. 2001; Webber et al. 1998). We can
distinguish the methylation levels of each individual allele by exploiting a SNP in
the
upstream region of the H19 gene (rs2071094; dbSNP build 124) (Figure 5.5). By
doing so, we can quantitate methylation on each allele at a single base resolution for
persons who are heterozygous for the SNP.
102
Figure 5.5. General schema of the epigenetic haplotyping assay. Only samples
heterozygous for a single nucleotide polymorphism (denoted as G/T) in the
differentially methylated regions are utilized in this assay. The methylation
information will be lost during the subsequent polymerase chain reaction
amplification steps. To retain the methylation information, DNA is modified with
sodium bisulfite. Subsequent PCR amplification will convert unmethylated
cytosines on the CpG sites to thymine and methylated cytosines remains detectable
as a cytosine. The percentage of methylation (% C) is quantitated by the ratio of
cytosines versus thymine using the luciferase-based Pyrosequencing platform. Our
epigenetic haplotyping assay quantitates the percentage of methylation on each allele
as marked by a nearby SNP (G allele versus T allele).
5.4.1 Materials and Methods
Cell lines and human tissue samples
The Colo205 colorectal carcinoma cell line was cultured in Dulbecco’s
modified essential medium at 37°C in a humidified atmosphere with 5 percent C0
2
.
Tissue samples were collected through the University of Southern California
Pathology Core Laboratory. Informed written consent was obtained and the
collection was approved by the University of Southern California Institutional
Review Board. The informative samples for the allele-specific methylation assay are
Sodium bisulfite modification
of the CpG sites
G T
G T C C T T
G Primer T Primer C C T T
Allele Specific DNA Methylation Analysis
103
samples heterozygous for a SNP in the H19 imprinting center. Genomic DNA was
extracted from cell lines and tissue samples using standard phenol-chloroform
methodology.
Sodium bisulfite modification of genomic DNA
Sodium bisulfite modification of genomic DNA was performed as described
previously by Frommer et al.(Frommer et al. 1992) with minor modifications. In
brief, DNA (~ 2
`g) suspended in 50 `L distilled water was denatured in 5.5 `L of
0.2 M NaOH at 37°C for 10 min. 30 `L of hydroquinone and 520 `L of sodium
bisulfite (pH 5.0) were added and incubated
at 50°C for 16 hours. The bisulfite
modified DNA was purified with Wizard Plus kits (Promega, Madison IL) according
to manufacturer’s instructions. 5.5 `L of 3M NaOH were added and allowed to
incubate for 5 min at room temperature. The bisulfite-treated DNA was precipitated
with 0.6 volumes of 10 M sodium acetate and
3.0 volumes of ethanol using glycogen
as a carrier. The final precipitate was resuspended in 20 `l of water.
H19 Genotyping Assay
Heterozygosity for the G/A SNP within the H19 imprinting center
(rs2071094, dbSNP build 124; Genbank accession number: AF125183, nucleotide
8008) was determined by Pyrosequencing. A 135 bp region was amplified on human
genomic DNA with the following PCR primers:5’ GGTCTCACCGCCTGGATC 3’
and 5’-BIOTIN GACCCGGGACGTTTCCAC 3’ and genotyped with the
sequencing primer 5’ ACAGCCCGAGCCCGC 3’.
104
Amplification of bisulfite-converted DNA
Bisulfite-modified DNA (2 `L) was amplified in a primary PCR reaction and
followed by a second nested PCR reaction amplifying one `L of the primary PCR
product. PCR reaction was performed in 25 `L volume using 10 pmol of each
primer and the Eppendorf HotMaster Taq DNA kit (Eppendorf, Westbury, NY) at
reagent concentrations per manufacturer’s instructions. The following primers in the
primary PCR reaction were used to amplify the 503 bp fragment from bisulfite-
treated DNA: 5’ GGAGTTGTGTTTTGGGATAGATGT3’ and 5’
AAACAATAAAATATCCCAATTCCA 3’. The primers for the nested PCR that
amplified the 223 bp fragment (nucleotide positions 7876-8102; NCBI accession
AF125183) were: 5’ GTTTTTATGAGTGTTTTATTTTTAGATG 3’ (nucleotide
positions 8102-8075; NCBI accession AF125183, reverse-complement bisulfite-
modified strand); 2) 5’ CCT CCT CAA AAA TCT TTA TAA ATA CAC 3’
coupled with biotin (positions 7903- 7876; NCBI accession AF125183, reverse-
complement bisulfite-modified strand). PCR conditions included one cycle of 94°C
for 3 min, 30 cycles of 94°C, 30 sec; 53°C (primary PCR) or 62°C (nested PCR), 30
sec; 72°C, 30 sec, and followed by one cycle of 72°C for 5 min.
Quantification of allele-specific methylation
The allele-specific methylation was quantitated using Pyrosequencing with
allele-specific sequencing primers and the PyroGold Reagent kit (Biotage, Uppsala
Sweden) on a Pyrosequencing 96HS per manufacturer’s protocol. In brief, 10 `L
PCR products for each sequencing reaction were immobilized onto streptavidin-
coated beads (Streptavidin Sepharose HP, Amersham Biosciences Ltd) in binding
105
buffer (10mM Tris-HCl, pH 7.6, 2 M NaCl, 1 mM EDTA, 0.1% Tween 20) for 10
min. The biotinylated template was purified with the Pyrosequencing vacuum prep
tool (Biotage, Uppsala Sweden) and incubated with 10pmol/reaction individually
with each sequencing primer in annealing buffer (20 mM Tris-acetate, pH 7.6 and 2
mM MgAc
2
). The biotinylated single DNA strand represents the reverse-
complement bisulfite-modified strand (NCBI accession AF125183; nt: 7903- 7876).
The DNA strands were denatured at 80°C for 2 min and reannealed at room
temperature for 10 min. Sequencing was performed according to manufacturer’s
instructions. The allele-specific sequencing primers were 1) G allele: 5’
GAATTTTAGTTG 3’; 2) T allele: 5’ GAATTTTAGTTT 3’. The allele frequency
(% cytosine or % thymidine) was calculated from the peak height analyzed with the
allele quantification module in the PSQ 96 HS software (Biotage). Percentage of
methylation was determined by the percentage of cytosine-to-thymidine conversion
(methylation = % cytosine/(% cytosine + % thymidine)).
Statistical Methods
To assess the extent that allele-specific methylation assay measures
methylation, linear regression analysis was conducted, regressing measured
percentage methylation on predicted (“true”) percentage methylation, with three
replicates at each “true” value (0%, 25%, 50%, 75%, 100%). 95% confidence bands
were calculated around the regression line.
In Silico
To evaluate generalizability to other populations and to prioritize regions for
deep-resequencing of SNPs for future LOI assays, in silico SNP were performed
106
with the public curated databases. Only SNPs validated by a non-computational
method were included. We searched the NCI’s Cancer Genome Anatomy Project
SNP500 Cancer (Packer et al. 2004). (102 pooled samples of African/African-
American, Caucasian, Hispanic and Pacific Rim), Perlegen(Hinds et al. 2005) (24
Han Chinese from Los Angeles, 23 Black and 24 Whites), Centre d'Etude du
Polymorphisme Human (CEPH) pedigrees(Nelson et al. 2004) ( 92 CEPH pooled
Caucasians UTAH), Neogene Brazilian (251 Brazilians), JBIC(Hirakawa et al. 2002)
( 24 Japanese).
5.4.2 Results
DNA methylation of CpG dinucleotides in our assay reflects methylation in the
region that regulates H19 genomic imprinting
The working model of our assay is an imprinting regulatory region that has
been a paradigm for genomic imprinting: the H19 imprinting center (IC). We
quantitated the methylation levels at CpG dinucleotides within the H19 IC in the
colorectal cancer cell line, Colo205 (Figure 5.6), which is heterozygous for a SNP.
The H19 IC is normally methylated on the paternal allele and unmethylated on the
maternal allele at binding sites for the CCTCF binding factor (CTCF) protein. CTCF
functions as a chromatin
insulator and binds to the H19 IC in a methylation-
dependent manner(Takai et al. 2001). In the colorectal cancer cell line Colo205,
which is heterozygous for a G/T SNP in close proximity to the H19 imprinting
center, we quantitated the methylation levels at two CpG dinucleotides within the
H19 IC (Figure 5.6).
107
Figure 5.6. Graphical representation of the light profile of CpG sites generated by
sequential nucleotide dispensation (Pyrogram
TM
). The emitted light pulse is in direct
proportion to the nucleotides present in the sample. The interrogated templates are
the PCR fragments of H19 imprinting region within the colorectal cancer cell line,
Colo205. Shaded areas highlight the two CpG sites of interest. The percentage of
cytosine depicts the percentage of methylation on PCR-amplified bisulfite modified
DNA. The sequence of nucleotides dispensed into the pyrosequencing reactions are
listed below each panel. A=adenosine; C=cytosine; T=thymine; G=guanine. “Exp.
Seq.”, expected sequences of the H19 IC surrounding the two CpG sites of interest.
Inclusion of adenosines (first and eighth nucleotide) and a cytosine (fourth
nucleotide) in the dispensation order function as internal controls for accurate
quantification of nucleotides in the template.
A G C T C G T C A G T G
C:45.0%
T:55.0%
C:59.0%
T:41.0%
Panel A
Both Alleles
(G/T)
A G C T C G T C A G T G
C:80.4%
T:19.6%
C:92.4%
T: 7.6%
A G C TC G TC A G T G
C:0%
T:100%
C:0%
T:100%
Panel B
G Allele
Panel C
T Allele
Exp. Seq. -----GGG-------(C/T)----------GGG---T-(C/T)-------GGG---T----G
108
We observed heavy methylation on the G allele (80.4% and 92.4%,
respectively on the two interrogated CpG sites) but not on the T allele (0% and 0%
on the two CpG sites). Therefore, the G allele must be of paternal origin. This
finding was confirmed by traditional genomic bisulfite sequencing of individual
clones.
This data was confirmed by traditional genomic bisulfite sequencing (Figure
5.7). While genomic bisulfite sequencing provides information on the methylation
status of all CpG dinucleotides
across the chromosomal region of interest, this
methodology is cumbersome and may be susceptible to cloning and selection
bias(Grunau et al. 2001) due to preferential amplification or preferential cloning
of
one of the parental alleles. Further, the two CpG dinucleotides adjacent to the SNP
in our assay predict methylation at the five CpG sites within the H19 IC. Thus, these
two CpG sites are representative of CpG sites in the CTCF binding site. We
interrogated these two CpG sites in our allele-specific methylation assay as a proxy
for methylation status in the H19 IC.
109
Figure 5.7. Genomic bisulfite sequencing of 19 CpG sites within and flanking the
H19 imprinting center in the colorectal cancer cell line, Colo205. Each row
represents a single sequenced molecule/allele. The box indicates the location of the
five CpG sites in the CTCF binding site (CB6, sixth of seven CTCF-binding sites in
the H19 IC). The single nucleotide polymorphism used to differentiate between the
parental alleles in the allele-specific methylation assay is indicated by the notation
IGF2
H19
G/T
G
G
G
110
G/T (rs2071094; the SNP). Methylated CpGs, filled circles; unmethylated CpGs,
empty circles.
The allele-specific methylation assay is highly sensitive, specific and reproducible.
To test if the allele-specific methylation assay can accurately quantitate
allele-specific methylation, we simulated bisulfite-treated DNA populations with
varying proportions of methylated DNA by mixing known plasmid DNAs. The
plasmid DNA contained bisulfite PCR amplified H19 IC which had been previously
sequenced. The plasmid DNA represented the four possible patterns determined by
two states: 1) the allelotype of the SNP adjacent to the CpG site of interest (G/T); 2)
the methylation status (methylated/unmethylated). Combinations of the plasmids
(G-methylated, G-unmethylated, T-methylated and T-unmethylated) were
quantitatively mixed prior to PCR amplification. Specifically, combinations of G-
methylated and G-unmethylated were created to simulate 0%, 25%, 50%, 75% and
100% methylation for the G allele(left panel); likewise for the T allele(right panel).
The average methylation at each CpG site of each parental allele is represented on
the scale of 0 to 100 per cent (Figure 5.8).
Figure 5.8 shows that the allele-specific methylation assay is accurate and
reproducible across the range of possible methylation levels (0-100%). Specifically,
at low percentages of methylation (< 50 per cent), this methodology correctly
identifies the percentage of allele-specific methylation within three per cent. CpG
methylation was only detected by the sequencing primers specific for the allele; no
mispriming of the allele-specific primers was observed (data not shown).
111
Figure 5.8. Test performance of the allele-specific methylation assay. Left panel:
cloned PCR products with known percentage of methylation (0, 25, 50, 75, 100) of G
allele probed with the sequencing primer specific for the G allele. Right panel: T
alleles interrogated with allele-specific primer for the T allele. The concordance of
the measured percentage of methylation and the expected percentage of methylation
is represented as the solid line and the confidence belt, corresponding to 2 standard
errors, as gray lines. Three separate measurements were performed. (Disclosure:
Pyrosequencing data reproduced with permission from Dr. Byun HyangMin, Yang’s
laboratory).
Loss of allele-specific methylation in the H19 imprinting center predicts loss of H19
imprinting
Allele-specific methylation in the H19 IC regulates the parent-specific
expression of the imprinted gene, H19. Using the RNA-based assay described in
Section 5.3, we found a bladder tumor which showed biallelic expression of H19,
and therefore loss of imprinting. Normal urothelium from this same patient showed
mono-allelic expression of H19 and therefore normal imprinting. We analyzed DNA
from this tumor using the allele-specific methylation assay , and were able to
confirm loss of allele specific expression. The allele-specific methylation in the H19
IC is retained in the normal urothelium where the allele marked by the G allele is
heavily methylated (88.6%, 1
st
. CpG site; 2
nd
. 100%, 2
nd
. CpG site) and the allele
0
20
40
60
80
100
0 20 40 60 80 100
Expected % methylation
0
20
40
60
80
100
0 20 40 60 80 100
Expected % methylation
Measured % methylation
Measured %
112
marked by the T allele is unmethylated (0%, 1
st
. CpG site; 2
nd
. 94.0%, 2
nd
. CpG site).
However, in the bladder tumor allele-specific methylation decreased to 46.4% (1
st
.
CpG site) in the G allele, approximately half of the normal bladder tissue. In our
analysis of 41 bladder cancer samples and matched normal urothelium, only four
were heterozygous for both the SNP used in our pyrosequencing assay and the SNP
used in the RNA-based LOI assay. Of these four informative paired samples, only
one pair showed loss of H19 imprinting (Figure 5.9). Larger studies of bladder
cancer will be required to study correlation of LOI and allele-specific methylation.
113
Figure 5.9. Representative pyrograms of normal and loss of imprinting in tissues
of bladder cancer patients. Left panels: Urotheliums bladder tissue that shows
normally imprinted H19 expression. Right panels: Bladder tumor tissue that shows
loss of imprinting (biallelic expression, data not shown). Top panels: Methylation on
the parental allele marked by the G allele of a G/T SNP within the H19 IC. Bottom
panels: Methylation on the parental allele marked by the A allele. The letters below
each pyrogram indicate the dispensed nucleotides (Figure 5.6) injected into the real-
time nucleotide synthesis to interrogate the expected sequence on the PCR-amplified
fragment of H19IC (Figure 5.6). (Disclosure: Pyrosequencing data reproduced with
permission from Dr. Byun HyangMin, Yang’s laboratory).
5.5 Discussion
We have developed a high-throughput method of determining allele-specific
methylation at a single base resolution. Bisulfite genomic sequencing is the only
1300
1400
1500
ES A G C T C G T C A G T G
1250
1300
1350
E S A G C T C G TC A G TG
1300
1400
1500
1600
E S A G C T C G T C A G T G
1400
1600
1800
2000
E S A G C T C G T C A G T G
C:88.6% C:100%
T:11.4% T:0%
C:46.4% C:62.4%
T:53.6% T:37.6%
C:0% C:6.0%
T:100% T:94.0%
C:0% C:2.0%
T:100% T:98.0%
Normal (G allele)
Tumor (G allele)
Normal (T allele) Tumor (T allele)
114
method that quantitates methylation at a similar resolution and represents the gold
standard in the field. However, bisulfite genomic sequencing requires the cloning of
PCR-amplified products and direct sequencing of multiple individual clones that
each represents one parental allele from a single cell. Recently-described high-
throughput and quantitative methylation methodologies determine average
methylation for either a few CpG sites (denaturing high performance liquid
chromatography(Couvert et al. 2003)) or at each individual CpG site
(Pyrosequencing(Dupont 2004; Shiao 2005), matrix-assisted laser desorption
ionization time-of-flight mass spectometry(Schatz 2004; Tost et al. 2003), MSP-
DHPLC(Baumer 2002) and SNuPE-DHPLC(El-Maarii 2002)). None, however,
approaches the allele-specific resolution of our allele-specific methylation
measurement method.
This allele-specific methylation methodology affords a more precise tool to
dissect the complex methylation changes that occur in the loss of imprinting
observed in tumors. To further develop this assay as a biomarker for LOI in
epidemiological studies, population studies to estimate its sensitivity (true positive
rate) and specificity (false positive rate) in discriminating between persons with LOI
from persons with normal imprinting should be conducted. This includes allele-
specific Alu methylation(Sandovici et al. 2005), X chromosome inactivation,
differential promoter and insulator activity, non-coding RNA and monoallelic
expression of cytokine genes(Bayley et al. 2003). We applied the allele-specific
methylation strategy towards developing a marker for loss of imprinting based on
115
DNA methylation. In a limited analysis of bladder samples, we were unable to
correlate DNA methylation changes and H19 imprinting status.
5.6 Conclusions
To further develop this assay as a biomarker for loss of imprinting in
epidemiologic studies, analytical validation to estimate its sensitivity (true positive
rate) and specificity (false positive rate) in discriminating between persons with LOI
from person with normal imprinting should be conducted (Section 5.5). Specifically,
one quantifies the accuracy of the DNA-based assay new DNA based test by
separately assessing the true-positive rate (sensitivity) and the true-negative rate
(specificity) of the new assay relative to the established RNA-based reference
standards (Figure 5.10). Both test characteristics will summarise the two types of
errors: misclassification of LOI
and normal imprinting as defined by the current
(RNA-based) assay. The diagnostic sensitivity is the proportion of persons with LOI
as defined by the gold standard (RNA-based assay) correctly identified; diagnostic
specificity, the proportion of persons with normal imprinting.
Reference
(RNA-based LOI assay)
TP FP Test
(DNA-based LOI assay)
FN TN
Figure 5.10 Calculations of the test accuracy of the DNA-based LOI assay as
compared to the gold standard (RNA-based assay).
Sensitivity=TP/(TP+FN). Specificity=TN/(FP+TN).
Sample size calculations for the validation study is dependent on estimating
the proportion TP/(TP+FN). The denominator of the proportion to be estimated is
116
the number of people with informative genotypes and having LOI. Due to a property
common to both the DNA-based and RNA-based test (allele-specificity), the fraction
of the study population included in this denominator depends on the heterozygosity
of both the two SNPs: the methylation assay (IGF2 8008 C>A, rs2071094) and the
mRNA expression assay (IGF2 820 G>C, rs680, Figure 5.11) in that population.
Ethnicity Heterozygosity Heterozygosity
White
Chinese
Japanese
Korean
0.38
0.42, 0.53, 0.56
0.36
0.47
0.42
0.42
0.42
N/A
Figure 5.11. Position of the single nucleotide polymorphisms present in the IGF2
mRNA transcript and in the H19 imprinting center. The lollipops depict CpG
dinucleotides. The SNP follows the National Cancer Biotechnology Institute
dbSNP(Sherry et al. 1999) accession number (dbSNP build 124). Bases are
numbered per GenBank accession number X07868.
For the validation study, biospecimens must be amenable to reliable isolation
of intact RNA. Thus, the validation study will be performed prospectively.
Sampling will be from these three populations: 1) populations from which freshly
drawn peripheral blood can be obtained (eg. cohorts, registries or screening clinics);
2) frozen solid tumor blocks or frozen lymphocytes (eg. from tissue banks); 3)
existing studies with stored RNA or cDNA.
IGF2 820 G>A
rs680
IGF2 H19 IC H19
IGF2 8008 C>A
rs2071094
117
Chapter 6: Conclusions
6.1 IGF1
The work presented in Chapters 3 and 4 are the first reports of a
comprehensive examination of the role of potential regulatory IGF1 polymorphisms
in cancer susceptibility. By identifying genetic variations in the IGF pathway that
predict colorectal cancer risk, we hope to inform strategies for prevention and future
etiological studies.
In rapidly westernizing countries, such as in industrialized Asia (Singapore
and Hong Kong), Eastern Europe and South America, incidence rates of colorectal
cancer are rapidly accelerating, possibly due to the westernizing of lifestyles(Parkin
2001). To inform preventative studies, a well-defined and relatively genetically
homogeneous cohort such as the Singapore Chinese Health Study is essential.
Studies in Western countries are unlikely to be directly applicable to
other areas of
the world where tumors may have a different molecular
pathogenesis(Chan et al.
2005). While the systematic review of epidemiologic evidence concluded a role for
serum IGF1 in cancer development (Chapter 2), heterogeneity among the
observational serum studies appear substantial. We contend that IGF1 genetic
markers (Chapter 3 and 4) better reflect cancer risk because they capture
autocrine/paracrine effects of IGF1on cancer susceptibility.
Comprehensive identification of regulatory elements to target for
polymorphism screening is currently not feasible. The genetic signatures for
regulatory elements are unknown. Classical experimental studies in cis-acting
regulatory sequences are laborious and generally not comprehensive, e.g. deletion
118
experiments in cell culture, DNAseI hypersensitive studies, promoter and enhancer
trapping studies in mice(Pennacchio and Rubin 2001). In contrast, computational
methods (comparative genomics) have inferred long range regulatory regions in
the
5'UTRs and 3' UTRs of regulatory genes, stable gene deserts, and megabase-sized
regions of moderately conserved noncoding sequences(Bejerano et al. 2005; Siepel
et al. 2005). The comparative genomics approach used in this dissertation can be
extended to localizing regions that function as “master regulators” of genes within
pathways in carcinogenesis, i.e. regulate numerous genes concurrently. The
phenotypic effects of genetic variations are notoriously difficult to predict. One of
the reasons is buffering of genetic variation from perturbations through redundant
pathways or genes. However, one would expect variations in regions of “master
regulators” to be less robust to pertubations. A potential master regulator is the
microRNA group which regulate at least 20% of human genes(Xie et al. 2005).
MicroRNAs are small noncoding RNAs that bind to the 3' untranslated regions of
target genes in humans to regulate post-transcriptional regulation (protein production
of the target transcript)(Bartel and Chen 2004).
Cancer prevention strategies would benefit from the identification of
conserved elements and the nature of their
functions (ENCODE Project Consortium
2004)(ENCODE 2004). Until a comprehensive map exists, we hope candidate
approaches within well-defined cohorts with wide ranges of relevant exposures, such
as in this dissertation will contribute to our understanding of cancer etiology.
119
6.2 IGF2
Although aberrant epigenetics modify cancer development and progression,
the scarcity of research tools has hampered information on the epigenetic basis of
disease. Degradation of epigenetic information varies among individuals.
Deregulated epigenetic information is due to aging, chronic inflammation and
possibly diet and genetic predisposition(Toyota and Issa 2005). The work in Chapter
5 may represent a new platform for the development of high-throughput methods to
measure epigenetic variation in epidemiologic studies.
The assay that we developed aims to measure actual LOI in future
epidemiologic studies. Before the assay can be used as a reliable biomarker of LOI,
further validation studies should be performed. The accuracy of the DNA-based
assay in measuring actual LOI depends on laboratory errors, biological heterogeneity
and random error. Chapter 5 details a study demonstrating minimal laboratory error
within the Pyrosequencing platform.
To assess biological heterogeneity, further validation studies are still needed.
Biological heterogeneity may exist at the level of the allele, cell and organ as
detailed below (Figure 6.1).
i) allelic level: The methylation measured is the average of methylation across the
population of each paternal allele in each cell. To date, it is not known whether the
level of allele-specific methylation regulates imprinting by a threshold effect or
relative ratio of the parental mRNA transcripts. Hence, the effect of the random
noise in the methylation patterns in each paternal allele population on regulation of
normal genomic imprinting is unclear. In addition, loss of imprinting may be due to
120
deregulation in the allele specific alteration in chromatin structure via promoter
usage, non-coding RNA expression, histone modifications, differential methylation
tandem repeats, boundary/insulator elements, chromatin looping and asynchronous
replication. The mechanistic basis of normal imprinting maintenance is unclear.
The gold standard (RNA-based assay) is based on gene expression that is regulated
by other factors not directly related to LOI. If the gold standard is a worse predictor
of actual LOI than the new DNA-based assay, the test performance of the new test
(estimates of sensitivity and specificity) would be compromised.
ii) cellular level: The measured methylation is the average across populations
of blood cells (methylation on DNA isolated from a population of peripheral blood
lymphocytes). However, the populations of lymphocytes may be comprised of
different cell populations due to aging(Ahuja et al. 1998; Issa et al. 1994) that is
linked to methylation. The relative risk of LOI and cancer estimated in the main
epidemiological study should be adjusted for age.
iii) organ: The rationale for the DNA-based LOI assay is based on the
observations that loss of allele-specific DNA methylation in colonic cells is reflected
in the blood cells(Cui et al. 2003). Thus, the hypothesis for the main
epidemiological study is that the measured methylation in DNA isolated from blood
cells can act as a proxy for germline LOI status in the colon crypt. However, loss of
IGF2 imprinting (exposure of interest) in normal hematopoietic (blood) were
observed to strongly correlate with cell proliferation due to inflammation and thus,
not limited to cancer cells.(Hofmann et al. 2002).
121
The LOI assay may represent a new platform for the development of high-
throughput methods to screen for epigenetic variation.
Figure 6.1. Biological heterogeneity at the level of the organ, cell and allele.
Colon
Peripheral
Blood
Organ Cell
Allele
individual
CpG site
122
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Creator
Wong, Hui-Lee
(author)
Core Title
Colorectal cancer: genomic variations in insulin-like growth factor-1 and -2
School
Graduate School
Degree
Doctor of Philosophy
Degree Program
Molecular Epidemiology
Degree Conferral Date
2006-05
Publisher
University of Southern California
(original),
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health sciences, oncology,health sciences, public health,OAI-PMH Harvest
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English
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113518
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Wong, Hui-Lee
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The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...
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health sciences, oncology
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