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Tracking human acute lymphoblastic leukemia cell clones in xenograft mouse models

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Tracking human acute lymphoblastic leukemia cell clones in xenograft mouse models

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Content TRACKING HUMAN ACUTE LYMPHOBLASTIC LEUKEMIA CELL CLONES IN XENOGRAFT
MOUSE MODELs
Jiya Eerdeng
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fufillment of the
MASTER OF SCIENCE
(BIOCHEMISTRY AND MOLECULAR BIOLOGY)
May 2019
i

Acknowledgement
I hereby would like to express my gratitude to my advisor, Dr. Rong Lu, for the offering me the
opportunity to work on this research project and for her guidance during my master study in the
University of Southern California. I enjoyed the research experience in our laboratory, and I have
learnt plenty of skills and new knowledge to fulfill my life.

I ‘d like to thank my committee members, Dr. David Cobrinik and Dr. Jian Xu, for their
guidance and good ideas on this project and for their encouragement and help during my
graduate study.

Moreover, I would love to thank Humberto in my lab for designing and processing the
experiment and for his kindly suggestion and idea during the time at the Lab. I also would like to
thank for my other current and former lab members who gave me support and confidence. They
also provided me with useful suggestions on my study. I really appreciate the help of my friends
and family.
ii

Table of Contents
Acknowledgement ............................................................................................................... i
List of Figures .................................................................................................................... iv
Chapter I. Introduction .........................................................................................................1
Acute Lymphoblastic Leukemia ..............................................................................1
Treatment of Acute Lymphoblastic Leukemia ........................................................3
Relapse of Acute Lymphoblastic Leukemia ............................................................4
Acute Lymphoblastic Leukemia Heterogeneity ......................................................5
Purpose of the project ..............................................................................................6
Chapter II. Materials and Methods ......................................................................................7
Materials ..................................................................................................................7
Reagent ........................................................................................................7
StemSpanTM Serum-Free Expansion Medium II (SFEM II) ..........7
FLT-3 Ligand ...................................................................................7
Recombinant Human Interleukin-3 (IL-3) .......................................8
Stem Cell Factor (SCF) ....................................................................8
Phosphate Buffered Saline ...............................................................8
EDTA ...............................................................................................8
Fetal Bovine Sera .............................................................................9
Phusion PCR master mix .................................................................9
Mice ...........................................................................................................10
iii

NOD.Cg-Prkdc
scid
Il2rg
tm1Wjl
.........................................................10
NOD.Cg-Prkdc
scid
Il2rg
tm1Wjl
Tg ....................................................10
Methods..................................................................................................................12
Leukemia culture and lentiviral transduction. ...............................12
Mice transplantation.......................................................................12
Blood Sample Collection and FACS Analysis. .............................13
DNA Barcode Extraction and Sequencing. ...................................13
PCR Protocol .................................................................................14
Chapter III. Research Strategy ...........................................................................................15
Chapter IV. Results ............................................................................................................19
Naïve ALL cells engraft more polyclonal than relapsed cells ...............................19
ALL clonal diversity is generally consistent among different tissues ...................22
Clones show complex behavior across passages ...................................................25
Reference ...........................................................................................................................30
iv

List of Figures
Figure 1. Single cell tracking technology ..................................................................................... 16
Figure 2. Establishing a human acute lymphoblastic leukemia model in mice ............................ 18
Figure 3. JFK93 samples engraft faster than JFK88 samples ....................................................... 20
Figure 4. JFK93 naive sample engraft more polyclonal than relapsed cells ................................ 21
Figure 5. JFK88 naive cells engraft more polyclonal than relapsed cells. ................................... 21
Figure 6. Clonal composition is more similar between blood and spleen .................................... 22
Figure 7. Clonal compositions are more correlated between blood and spleen............................ 24
Figure 8. Clonal composition with bone marrow is different. ...................................................... 24
Figure 9. Establish a diverse pool of barcoded clonse across passages. ....................................... 25
Figure 10. Clonal diversity decreases along with passages. ......................................................... 26
Figure 11. Clonal evolution with passages ................................................................................... 27
Figure 12. Summary of Clonal Behaiviors ................................................................................... 28
Figure 13. Clones display three major behaviors across passages ................................................ 29
Figure 14. Different behaviors present different distribution across passages. ............................ 29

1

Chapter I.
Introduction
Acute Lymphoblastic Leukemia
Cancer is the disease when cells starts to grow out of control. Leukemias are cancers that start in
cells that would normally develop into different types of blood cells. There are some types of
leukemia, which are divided on the growth rate and cell types. Leukemia which is acute, grow
quickly than that is chronic. Tumors start in myeloid cells or lymphoid cells are called
myeloblastic leukemia and lymphocytic leukemia. Acute lymphocytic leukemia (ALL) is also
called acute lymphoblastic leukemia. “Acute” means that the leukemia can progress quickly, and
if not treated, would probably be fatal within a few months. "Lymphocytic" means it develops
from early (immature) forms of lymphocytes, a type of white blood cell.
ALL starts in the bone marrow (the soft inner part of certain bones, where new blood cells are
made). Most often, the leukemia cells invade the blood fairly quickly. They can also sometimes
spread to other parts of the body, including the lymph nodes, liver, spleen, central nervous
system (brain and spinal cord), and testicles (in males).
Some cancers can also start in these organs and then spread to the bone marrow, but these
cancers are not leukemia.
Other types of cancer that start in lymphocytes are known as lymphomas (either non-Hodgkin
lymphoma or Hodgkin lymphoma). While leukemias like ALL mainly affect the bone marrow
and the blood, lymphomas mainly affect the lymph nodes or other organs (but may also involve
the bone marrow). Sometimes it can be hard to tell if a cancer of lymphocytes is a leukemia or a

2

lymphoma. Usually, if at least 20% of the bone marrow is made up of cancerous lymphocytes
(called lymphoblasts, or just blasts), the disease is considered leukemia(“Acute Lymphocytic
Leukemia (ALL) in Adults,” n.d.; Pui, Gajjar, Kane, Qaddoumi, & Pappo, 2011).

3

Treatment of Acute Lymphoblastic Leukemia
Chemotherapy (chemo) is the use of drugs to treat cancer. Chemo drugs travel through the
bloodstream to reach cancer cells all over the body. Chemo is the main treatment for just about
all people with acute lymphocytic leukemia (ALL). Because of its potential side effects, chemo
might not be recommended for patients in poor health, but advanced age by itself is not a barrier
to getting chemo. Chemo is typically given in cycles, with each period of treatment followed by
a rest period to allow the body time to recover. Chemo for ALL uses a combination of anti-
cancer drugs. The most commonly used chemo drugs include: Vincristine or liposomal
vincristine (Marqibo), Daunorubicin (daunomycin) or doxorubicin (Adriamycin), Cytarabine
(cytosine arabinoside, ara-C), L-asparaginase or PEG-L-asparaginase (pegaspargase or
Oncaspar), 6-mercaptopurine (6-MP), Methotrexate, Cyclophosphamide, Prednisone,
Dexamethasone and Nelarabine (Arranon)(“Acute Lymphocytic Leukemia (ALL) in Adults,”
n.d.).
Radiation therapy uses high-energy radiation to kill cancer cells. It is not usually part of the main
treatment for people with acute lymphocytic leukemia (ALL), but it is used in certain situations:
First, radiation is sometimes used to treat leukemia that has spread to the brain and spinal fluid,
or to the testicles. Second, radiation to the whole body is often an important part of treatment
before a bone marrow or peripheral blood stem cell transplant. Third, radiation is used (rarely) to
help shrink a tumor if it is pressing on the trachea (windpipe) and causing breathing problems.
But chemotherapy is often used instead, as it may work more quickly. Radiation can also be used
to reduce pain in an area of bone invaded by leukemia.

4

Relapse of Acute Lymphoblastic Leukemia
ALL is the most common type of childhood cancer. Almost 4000 cases of ALL are diagnosed
annually in the United States, approximately two thirds of which are children and adolescents
(Pui & Evans, 2006).
Despite the remarkable progress over the past decades in curing ALL resulting from the
refinement of multiagent chemotherapeutic and radiotherapy regiments, relapsed ALL remains a
leading cause of cancer-related deaths in children (Pui & Evans, 1998; Pui, Relling, Campana, &
Evans, 2002).
Current front-line treatment relies on chemotherapy to eradicate ALL cells. About 85% of the
patients achieve a second remission, but the overall cure rate after relapse is only 30–40%.
Patients who relapse within a year or two are particularly resistant to additional chemotherapy
and have a very poor prognosis(Buchanan et al., 2000; Einsiedel et al., 2005; Lawson et al.,
2000).

5

Acute Lymphoblastic Leukemia Heterogeneity
The current cancer treatments attempt to eradicate the entire cancer population in a shotgun
approach. However, this strategy does not remove all cancer cells equally and may fail to
eradicate chemo-resistant cancer cells with unique properties making them responsible for the
relapse in patients(Ding et al., 2012; Greaves & Maley, 2012; Nowell, 1976; Shackleton,
Quintana, Fearon, & Morrison, 2009).
Clinical data strongly suggest that there exists heterogeneity among ALL cells. Some ALL cells
are chemo-resistant and progress quickly while some are chemo-sensitive and progress more
slowly. For example, patients who relapse a few years later have a much better prognosis with
chemotherapy. In fact, many of these patients can be cured with chemotherapy alone(Einsiedel et
al., 2005; Lawson et al., 2000). It remains unclear why late relapse patients remain chemo-
sensitive while early relapse patients are chemo-resistant. In addition, patients with ALL, except
those with mature B-cell ALL, benefit from prolonged maintenance therapy, where low doses of
chemo-treatment are continuously applied for two or more years(Pui & Evans, 1998, 2006).
The reason for the efficacy is poorly understood, and this benefit is not observed in other types of
leukemia. Why low doses of chemotherapy succeed to eradicate leukemia while high doses of
the same drugs fail remain a mystery not explained by the current understanding of leukemia
growth and relapse.

6

Purpose of the project
The research will greatly improve the understanding of cancer relapse in ALL patients providing
a novel clonal level perspective. My findings may ultimately lead to novel therapeutic strategies
that exploit the intratumoral cellular competition. The experimental system and knowledge from
this study can be extrapolated to decipher the role of clonal expansion in all cancer types, not just
in ALL. It will also establish a vital system and capabilities to further study malignant cells
during the progression of oncogenesis. For example, following ALL clones could enable us to
elucidate the metastasis of ALL cells and compare their migration mechanisms with normal
hematopoietic cell

7

Chapter II.
Materials and Methods
Materials
Reagent

StemSpanTM Serum-Free Expansion Medium II (SFEM II)
SSFEM II (Stem Cell Technologies) is a modified version of SFEM. It has been developed for
the in vitro culture and expansion of human hematopoietic cells, when the appropriate growth
factors and supplements are added. Using appropriate supplements, SFEM II may be used to
expand CD34+ cells isolated from human cord blood, mobilized peripheral blood, or bone
marrow samples, or to expand and differentiate lineage-committed progenitor cells to generate
populations of erythroid, myeloid (granulocytes or monocytes), or megakaryocyte progenitor
cells.

FLT-3 Ligand
Fms-Like Tyrosine Kinase 3 Ligand (FLT3 Ligand, FLT3LG) (Gibco by Life Technologies)
is a bioactive protein intended for use in cell culture applications. FLT3 Ligand is a cytokine
involved in hematopoeisis.

8

Recombinant Human Interleukin-3 (IL-3)
IL3 (Gibco by Life Technologies) is a bioactive protein intended for use in cell culture
applications. IL3 provides the cytokine connection between the immune system and the
hematopoietic system. For example, IL3 supports the proliferation and development of almost all
types of hematopoietic progenitor cells and can act as a chemoattractant for eosinophils.

Stem Cell Factor (SCF)
SCF (Gibco by Life Technologies) is the ligand of the c-Kit oncogene and is expressed by
various structural and inflammatory cells in the airways. Binding of SCF by the c-Kit receptor
leads to homodimerization of the receptor and the activation of signalling pathways such as PI-3,
PLC-gamma, Jak/STAT, and MAP kinase pathways. SCF expression leads to the induction of
mast cell survival and the expression and release of histamine, pro-inflammatory cytokines and
chemokines.

Phosphate Buffered Saline
PBS (Thermo Scientific, Waltham, MA) is a balanced salt solution used for a variety of cell
culture applications, such as washing cells before dissociation, transporting cells or tissue,
diluting cells for counting, and preparing reagents. PBS is formulated without calcium and
magnesium for rinsing chelators from the culture before cell dissociation.

EDTA
EDTA (Gibco by Life Technologies) is made from trypsin powder, an irradiated mixture of
proteases derived from porcine pancreas. Due to its digestive strength, trypsin is widely used for

9

cell dissociation, routine cell culture passaging, and primary tissue dissociation. The trypsin
concentration required for dissociation varies with cell type and experimental requirements.

Fetal Bovine Sera
Fetal bovine sera(Gibco by Life Technologies) offer excellent value for basic cell culture,
specialty research, and specific assays, earning the trust of researchers with consistent quality
and award-winning support that helps meet your research needs and budget requirements

Phusion PCR master mix
Thermo Scientific, Waltham, MA. Ready-to-use 2X master mix preserves the fidelity and the
yield in the reaction when using extremely short PCR protocols. The unique master mix
composition permits usage of extremely short cycling protocols with both low and high
complexity DNA templates - 15 seconds per kilobase or less. The master mix utilizes Phusion
Flash II DNA Polymerase, a modified proofreading DNA polymerase derived from Phusion Hot
Start II High-Fidelity DNA Polymerase.

10

Mice

NOD.Cg-Prkdc
scid
Il2rg
tm1Wjl

NSG, JAX stock number 05557. Branded name "NSG™" and theyt are extremely
immunodeficient. The mice carry two mutations on the NOD/ShiLtJ genetic background; severe
combined immune deficiency (scid) and a complete null allele of the IL2 receptor common
gamma chain (IL2rgnull). The scid mutation is in the DNA repair complex protein Prkdc and
renders the mice B and T cell deficient. The IL2rgnull mutation prevents cytokine signaling
through multiple receptors, leading to a deficiency in functional NK cells. The severe
immunodeficiency allows the mice to be humanized by engraftment of human CD34+
hematopoietic stem cells (HSC), peripheral blood mononuclear cells (PBMC), patient derived
xenografts (PDX), or adult stem cells and tissues. The immunodeficient NSG mice enable
research in human immune function, infectious disease, diabetes, oncology, and stem cell
biology.

NOD.Cg-Prkdc
scid
Il2rg
tm1Wjl
Tg
CMV-IL3, CSF2, KITLG 1Eav/MloySzJ NSG-SGM3, JAX stock number 013062
The triple transgenic NSG-SGM3 (NSGS) mice expressing human IL3, GM-CSF and SCF
combine the features of the highly immunodeficient NOD scid gamma (NSG) mouse with
cytokines that support the stable engraftment of myeloid lineages and regulatory T cell
populations. As a result, these NSG-SGM3 mice allow superior engraftment of diverse

11

hematopoietic lineages, primary AML and ALL samples than other models and are useful for
immuno-oncology, immunology and infectious disease studies.

12

Methods

Leukemia culture and lentiviral transduction.
Human B-cell acute lymphoblastic leukemia (B-ALL) cells were sorted for human CD45 and
CD19 from previously cryopreserved samples. These cells were either passaged mouse spleen
cells or primary human bone marrow aspirates. Cells were cultured in StemSpanTM Serum-Free
Expansion Medium II (SFEM II) (Stem Cell Technologies) in the presence of 20 ng/ml human
FLT-3 ligand (Gibco by Life Technologies), 20 ng/ml Human Interleukin-3 (IL-3) (Gibco by
Life Technologies) and 50 ng/ml human Stem Cell Factor (SCF) (Gibco by Life Technologies).
After 24 hours of pre-stimulation, cells were washed and incubated for another 16 hours in the
same medium containing the library of barcoded GFP-encoding lentivirus. We added 8 ng/µl
polybrene into the culture to facilitate viral transduction. B-ALL cells were washed three times
prior to transplantation.

Mice transplantation
NOD.Cg-Prkdcscid Il2rgtm1Wjl (NSG, JAX stock number 05557) and NOD.Cg-
Prkdcscid Il2rgtm1Wjl Tg(CMV-IL3,CSF2,KITLG)1Eav/MloySzJ (NSG-SGM3, JAX stock
number 013062) mice were obtained from the Jackson Laboratory. We transplanted 100,000 to
200,000 B-ALL cells into each recipient via tail vein injection. Irradiation dose of 150 cG was
performed on all recipient mice prior to transplantation. Mice were bred and maintained at the

13

Research Animal Facility of the University of Southern California. Animal procedures were
approved by the Institutional Animal Care and Use Committee.

Blood Sample Collection and FACS Analysis.
Blood samples were collected into PBS containing 10 mM EDTA via a small transverse cut in
the tail vein. To eliminate red blood cells, 2% dextran was added, and the remaining blood cells
were treated with ammonium-chloride-potassium lysis buffer on ice for 5 minutes to remove
residual red blood cells. After a 60 minute antibody incubation at 4° C, samples were suspended
in PBS with 2% FBS and 4,6-Diamidino-2-phenylindole to distinguish dead cells. Cells were
stained by antibodies and sorted using the FACS-Aria I and II cell sorters. Antibodies were
obtained from eBioscience (currently Life Technologies/Thermo Fisher) and BioLegend. Flow
cytometry data were analyzed using FlowJo software version 10.4.2 (Tree Start, Ashland, OR)
and Diva software 8.0.1(BD Biosciences, San Jose, CA).

DNA Barcode Extraction and Sequencing.
Genomic DNA was extracted from sorted leukemia cells and amplified using Phusion PCR
master mix (Thermo Scientific, Waltham, MA). The PCR reactions were halted once they had
progressed halfway through the exponential phase. PCR product was purified and analyzed using
high-throughput sequencing. Sequencing data were analyzed as previously described (Lu, Neff,
Quake, & Weissman, 2011). We combined sequencing data with FACS data to calculate the
clonal abundance for each clone: Clonal abundance =100%*(human cells) % WBCs) * (GFP %
human cells) * (number of reads for each barcode) / (total reads of all barcodes).

14

PCR Protocol
40 ul reaction:
• Template: 16 ul.
• Forward Primer (10um): 2 ul
• Reverse Primer (10um): 2 ul
• Phusion Mix (2X): 20ul
• Eva green dye: 0.4ul

PCR Machine Setting:
• 98 Degree: 30 s
• 22 ~ 28 Cycles, when curve cross the standard:
• 98 Degree: 10s
• 65 Degree: 30s
• 72 Degree: 30s
• 72 Degree: 10 min on PCR machine

15

Chapter III. Research Strategy
Current clonal tracking studies of cancer have relied on naturally occurring genetic mutations
(Ding et al., 2012; Gawad, Koh, & Quake, 2014; Melchor et al., 2014; Paguirigan et al., 2015).
As these mutations are established at different times, the clones carrying them cannot be directly
compared to assess cellular interactions.
To overcome this problem, the proposed experiments will apply a novel in vivo clonal tracking
system developed in our lab (Figure 1). We have demonstrated the efficacy and sensitivity of this
experimental system(Lu et al., 2011; Wu et al., 2014).This technique utilizes synthesized DNA
segments to uniquely label individual cells. The DNA segments are incorporated into the cellular
genome and serve as genetic “barcodes.” They are not expressed, but they are inherited by
progenies along with genomic DNA. Therefore, the abundance of a genetic barcode in a cell
population is proportional to the number of progenies that the original barcoded cell produces.
We have successfully applied this experimental system to quantify the number of cell clones
engrafted in mouse. Using this system, we were able to show that cellular interactions between
normal hematopoietic stem cells significantly alter their proliferation and differentiation. The
system allows for the quantification of cellular proliferation and competition with single-cell
resolution over long periods of time while keeping the whole cancer cell population intact to
maintain interclonal interactions. There is no other system that can simultaneously determine
clonal dynamics at both population and single-cell levels on an intact cancer population.

16

A DNA barcode consists of a common 6-bp library ID at the 5´ end, followed by a random 27-bp
cellular barcode. Different colors illustrate different barcode sequences. A lentiviral vector
delivers barcodes from a large library into a small number of cells at a titer low enough so that
most cells receive a unique barcode. After transplantation, barcodes replicate with host cells in
recipient mice. The progeny of donor cells are harvested, and barcodes are recovered from their
genomic DNA by PCR. Barcodes are identified and quantified using high-throughput sequencing
(Illumina GA II). The 6-bp library ID aids the separation of the barcodes from the sequencing
results. Identical 33-bp barcodes are combined for further analysis.
Figure 1. Single cell tracking technology

17

In order to study cellular competition at a single cell level, we barcoded 500,000 primary human
ALL cells (per mouse), and transplanted half (250,000 cells) into irradiated NSG mice. Then we
extracted the barcodes from the other half (250,000 cells) to estimate the number of labeled ALL
clones. To deliver the unique genetic barcodes into ALL cells, we took leukemia cells and
incubated them overnight in the presence of lentiviral vectors containing a large library of
barcodes. Following transplantation, I monitored ALL progression using luciferase imaging.
Then we harvested ALL cells at early, middle and late stages of cancer progression. I harvested
the ALL cells from the mouse bone marrow and spleen to extract their barcodes. We separated
ALL cells from each limb, left and right to determine if there is heterogeneity in clonal
distribution. We sectioned spleen and livers to study the clonal distribution. We counted the
barcode numbers to analyze the cellular competition during cancer progression. We also
examined the relative abundance of the barcodes to determine whether and when dominant ALL
clones out-compete other ALL cells. The purpose of this setting is that, if we observe
significantly fewer barcodes in high abundance at late stage compared to early stage of cancer
progression, it would imply that those few ALL clones expanded and propagated the disease,
supporting our hypothesis that some ALL clones outcompete other clones and are responsible for
propagating the disease. However, if we observe multiple barcodes with similar representation at
all stages of cancer progression, it would imply that ALL cells in the patient sample are equally
capable of propagating the disease. Additionally, I also compared ALL cells from chemo-
sensitive patients and from chemo-resistant patients to study the relationship between clonal
diversity and chemo-sensitivity.

18

Figure 2. Establishing a human acute lymphoblastic leukemia model in mice

19

Chapter IV. Results
Naïve ALL cells engraft more polyclonal than relapsed cells
Primary ALL cells from patient JFK88 and JFK93 were harvested from both initial diagnosis and
relapsed phage. Both patients took the Chemo treatment and relapsed after the treatment. We
transplanted same amount cells from two group to two sets of NSG mice. Then we compared the
human ALL growth rate and analyzed the clonal composition of them. While both the naïve and
relapsed groups of JFK93 shows a dramatical engraftment rate, leukemia cells from JFK88,
exhibit a relative less aggressive growth pattern. The xenograft mouse model shows a similar
growth pattern as the leukemia relapsed in the patient body.
From the perspective of the clonal composition, both patient samples indicated that the naïve
ALL cells are more polyclonal, compared with the relapsed ALL cell. While the JFK93 clonal
diversity is less than the JFK8 patient, suggests that a possible explanation that one dominant
clone of the relapsed sample from JFK93 rapidly progressed and result an aggressive increase
model.

20

Figure 3. JFK93 samples engraft faster than JFK88 samples

21

Figure 4. JFK93 naive sample engraft more polyclonal than relapsed cells

Figure 5. JFK88 naive cells engraft more polyclonal than relapsed cells.

22

ALL clonal diversity is generally consistent among different tissues
While it is easy to follow the progression of leukemia using blood analysis, but it is also
important to determine whether the clonal composition of blood cells can represent other tissues
and organs. To make this assessment, we compared the clonal composition of ALL cells from
blood, bone marrow from different locations and spleen. In all the patients’ samples, which from
JFK88, JFK93, ALL4 and ALL20, clonal composition from the spleen are more similar with the
one from blood. However, ALL cells form the legs and spine are less similar with the ones from
blood. In addition, clonal abundance from different location of the bone marrow are not
necessarily similar with each other. The cells found in the stomach of JFK93 shows a different
pattern from all other organs that we observed. However, cells found in the liver of JFK88 had
the same clonal composition as the ALL cells found in the blood and spleen.

Figure 6. Clonal composition is more similar between blood and spleen

23

In order to find a statistical conclusion, we took all the organs (or spots) from all the primary
mice from all patients and tested their similarity between each other. Pearson correlation
coefficient was used as the index to measure the similarity. Leukemia cells from spleen show a
high correlation with blood across all the mice. Spine, as part of the bone marrow, show a
relative low similarity with blood. Within the comparison of bone marrow, cells from different
sides of the mice exhibit a pattern where they are less similar with each other. Leukemia cells
form spine are always have a similar composition with one of the two sides.

24

Figure 7. Clonal compositions are more correlated between blood and spleen.

Figure 8. Clonal composition with bone marrow is different.

25

Clones show complex behavior across passages

In order to investigate more on ALL cell behavior, such as clonal dynamics and evolution.
Beyond the routine transplantation from one primary Human ALL to multiple mice, we
established another three to one xenograft mouse model. First, we harvested the cells from three
different primary mice, which were transplanted from same patient sample. Then we took equal
amount cells from these mice and combined them together, transplanted them to the secondary
mice. After leukemia fully engraftment, we combined equal amount cells from two secondary
and transplanted again, to the tertiary mice.

Figure 9. Establish a diverse pool of barcoded clonse across passages.

26

We harvested the spleen cells from each passage and processed sequencing data analysis. We
tracked all the clones from primary mice to tertiary mice. We have observed with more passages,
the diversity of clones dropped quickly.

Figure 10. Clonal diversity decreases along with passages.

27

Figure 11. Clonal evolution with passages

A small portion of clones from two primary mice finally outcompeted and contributed all
leukemia cells at the tertiary mice. In addition, we were interested in quantifying the clonal
behaviors based on their abundance. By stratify three passages’ clonal abundance, we summarize
6 different clusters of behavior, persistent clones, resting clones. Short-term clones, flashing
clones, transient clones and low abundant clones (Kreso A, et al. Science. 2013 Feb
1;339(6119):543-8).

28

Figure 12. Summary of Clonal Behaiviors

We mapped each clone to one of six clusters and found the clones finally outcompeted were not
necessarily present or abundant at the primary stage. Most of the clones from primary mice came
with an end of disappear on either secondary or tertiary stage. There were about one third clonal
abundance coming from the flashing clones, which only presented at the secondary stage. We
also counted the clone numbers of each behavioral clusters across three passages and found there
were a large number of clones belong to low abundant cluster. The clones contributed mostly to
the tertiary mice only came from two primary mice. All the behaviors listed above suggest a
clonal competition and evolution during the transplantations.

29

Figure 13. Clones display three major behaviors across passages

Figure 14. Different behaviors present different distribution across passages.

30

Reference
Acute Lymphocytic Leukemia (ALL) in Adults. (n.d.). Retrieved May 6, 2019, from
https://www.cancer.org/cancer/acute-lymphocytic-leukemia.html
Buchanan, G. R., Rivera, G. K., Pollock, B. H., Boyett, J. M., Chauvenet, A. R., Wagner, H., …
Pinkel, D. (2000). Alternating drug pairs with or without periodic reinduction in children
with acute lymphoblastic leukemia in second bone marrow remission: a Pediatric
Oncology Group Study. Cancer, 88(5), 1166–1174.
Ding, L., Ley, T. J., Larson, D. E., Miller, C. A., Koboldt, D. C., Welch, J. S., … DiPersio, J. F.
(2012). Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome
sequencing. Nature, 481(7382), 506–510. https://doi.org/10.1038/nature10738
Einsiedel, H. G., Von, A. S., Hartmann, R., Fengler, R., Schrappe, M., Janka-Schaub, G., …
Henze, G. (2005). Long-term outcome in children with relapsed ALL by risk-stratified
salvage therapy: results of trial acute lymphoblastic leukemia-relapse study of the Berlin-
Frankfurt-Münster Group 87. Journal of Clinical Oncology : Official Journal of the
American Society of Clinical Oncology, 23(31), 7942–7950.
https://doi.org/10.1200/JCO.2005.01.1031
Gawad, C., Koh, W., & Quake, S. R. (2014). Dissecting the clonal origins of childhood acute
lymphoblastic leukemia by single-cell genomics. Proceedings of the National Academy
of Sciences, 111(50), 17947–17952. https://doi.org/10.1073/pnas.1420822111
Greaves, M., & Maley, C. C. (2012). Clonal evolution in cancer. Nature, 481(7381), 306–313.
https://doi.org/10.1038/nature10762

31

Lawson, S. E., Harrison, G., Richards, S., Oakhill, A., Stevens, R., Eden, O. B., & Darbyshire, P.
J. (2000). The UK experience in treating relapsed childhood acute lymphoblastic
leukaemia: a report on the medical research council UKALLR1 study. British Journal of
Haematology, 108(3), 531–543.
Lu, R., Neff, N. F., Quake, S. R., & Weissman, I. L. (2011). Tracking single hematopoietic stem
cells in vivo using high-throughput sequencing in conjunction with viral genetic
barcoding. Nature Biotechnology, 29(10), 928–933. https://doi.org/10.1038/nbt.1977
Melchor, L., Brioli, A., Wardell, C. P., Murison, A., Potter, N. E., Kaiser, M. F., … Morgan, G.
J. (2014). Single-cell genetic analysis reveals the composition of initiating clones and
phylogenetic patterns of branching and parallel evolution in myeloma. Leukemia, 28(8),
1705–1715. https://doi.org/10.1038/leu.2014.13
Nowell, P. C. (1976). The clonal evolution of tumor cell populations. Science (New York, N.Y.),
194(4260), 23–28.
Paguirigan, A. L., Smith, J., Meshinchi, S., Carroll, M., Maley, C., & Radich, J. P. (2015).
Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia.
Science Translational Medicine, 7(281), 281re2.
https://doi.org/10.1126/scitranslmed.aaa0763
Pui, C.-H., & Evans, W. E. (1998). Acute Lymphoblastic Leukemia. New England Journal of
Medicine, 339(9), 605–615. https://doi.org/10.1056/NEJM199808273390907
Pui, C.-H., & Evans, W. E. (2006). Treatment of Acute Lymphoblastic Leukemia. New England
Journal of Medicine, 354(2), 166–178. https://doi.org/10.1056/NEJMra052603

32

Pui, C.-H., Gajjar, A. J., Kane, J. R., Qaddoumi, I. A., & Pappo, A. S. (2011). Challenging issues
in pediatric oncology. Nature Reviews Clinical Oncology, 8(9), 540–549.
https://doi.org/10.1038/nrclinonc.2011.95
Pui, C.-H., Relling, M. V., Campana, D., & Evans, W. E. (2002). Childhood acute lymphoblastic
leukemia. Rev Clin Exp Hematol, 6, 20.
Shackleton, M., Quintana, E., Fearon, E. R., & Morrison, S. J. (2009). Heterogeneity in cancer:
cancer stem cells versus clonal evolution. Cell, 138(5), 822–829.
https://doi.org/10.1016/j.cell.2009.08.017
Wu, C., Li, B., Lu, R., Koelle, S. J., Yang, Y., Jares, A., … Dunbar, C. E. (2014). Clonal
tracking of rhesus macaque hematopoiesis highlights a distinct lineage origin for natural
killer cells. Cell Stem Cell, 14(4), 486–499. https://doi.org/10.1016/j.stem.2014.01.020

Abstract (if available)

Abstract Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. Clinical data strongly suggest that there exists heterogeneity among ALL cells. Some ALL cells are chemo-resistant and progress quickly while some are chemo-sensitive and progress more slowly. It remains unclear why late relapse patients remain chemo-sensitive while early relapse patients are chemo-resistant. We utilized the DNA barcode technology and genome sequencing technology, improved the understanding of ALL from a novel clonal level perspective. We found naïve ALL cells engraft more polyclonal than relapsed cells. ALL clonal diversity is generally consistent among different tissues while clones show complex behavior across passages.

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Asset Metadata

Creator Eerdeng, Jiya (author)

Core Title Tracking human acute lymphoblastic leukemia cell clones in xenograft mouse models

School Keck School of Medicine

Degree Master of Science

Degree Program Biochemistry and Molecular Biology

Publication Date 11/06/2020

Defense Date 03/21/2019

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

Tag acute lymphoblastic leukemia,DNA barcode technology,OAI-PMH Harvest,xenograft mouse models

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Lu, Rong (committee chair), Cobrinik, David (committee member), Xu, Jian (committee member)

Creator Email eerdeng@usc.edu,jiyaelden@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-168835

Unique identifier UC11660832

Identifier etd-EerdengJiy-7414.pdf (filename),usctheses-c89-168835 (legacy record id)

Legacy Identifier etd-EerdengJiy-7414.pdf

Dmrecord 168835

Document Type Thesis

Format application/pdf (imt)

Rights Eerdeng, Jiya

Type texts

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

Access Conditions 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 a...

Repository Name University of Southern California Digital Library

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