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The role of adipocyte-derived free-fatty acids in acute lymphoblastic leukemia

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The role of adipocyte-derived free-fatty acids in acute lymphoblastic leukemia

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Content i

The Role of Adipocyte-Derived Free-Fatty Acids in Acute Lymphoblastic Leukemia
by
Jonathan Joseph Tucci

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
MEDICAL BIOLOGY

August 2016
i

Table of Contents
List of Figures .................................................................................................................................... iv
Dedication ......................................................................................................................................... v
Acknowledgements........................................................................................................................... vi
Chapter 1: Introduction ...................................................................................................................... 1
1.1 Pediatric Acute Lymphoblastic Leukemia (ALL) ............................................................................... 1
1.2 Obesity and ALL................................................................................................................................ 2
1.3 ALL and Adipocytes .......................................................................................................................... 3
1.4 Lipids and Cancer ............................................................................................................................. 4
1.5 Modeling Obesity and ALL in Mice .................................................................................................. 6
1.6 Dietary and Activity Modulation in Cancer Therapy ........................................................................ 7
Chapter 2: Acute lymphoblastic leukemia uptake of adipocyte-derived
free fatty acids alters their cellular metabolism .................................................................................. 9
2.1 Introduction ..................................................................................................................................... 9
2.2 Results .............................................................................................................................................. 9
2.2.1 ALL cells stimulate adipocyte lipolysis................................................................................. 9
2.2.2 TNFα is partly responsible for ALL-induced adipocyte lipolysis......................................... 10
2.2.3 Translocation of adipocyte-derived FFAs into ALL lipid structures ................................... 11
2.2.4 Lipidomic analysis of adipocyte-derived FFAs in ALL ........................................................ 12
2.2.5 Downregulation of ALL de novo lipogenesis in the presence of adipocytes ..................... 13
2.2.6 ALL utilization of adipocyte-derived FFAs for energy ........................................................ 15
2.3 Discussion ...................................................................................................................................... 16
Chapter 3: Caloric and dietary fat restriction during chemotherapy
improves survival in obese mice with ALL ......................................................................................... 18
3.1 Introduction ................................................................................................................................... 18
3.2 Results ............................................................................................................................................ 18
3.2.1 Calorie and fat restriction improves vincristine efficacy in obese leukemic mice ............. 18
3.2.2 Dietary restriction does not improve efficacy of other chemotherapies .......................... 19
3.2.3 Dietary restriction does not improve chemotherapy efficacy in a humanized murine
model of ALL ...................................................................................................................... 20
3.2.4 Serum restriction improves vincristine efficacy in ALL cell lines........................................ 21
3.3 Discussion ...................................................................................................................................... 22

ii

Chapter 4: Clinical Trial Protocol: Improving Diet and Exercise in
Acute Lymphoblastic Leukemia (IDEAL Weight in ALL Trial) ............................................................... 25
4.1 Introduction ................................................................................................................................... 25
4.2 Goals and Objectives ...................................................................................................................... 26
4.2.1 Hypothesis ......................................................................................................................... 26
4.2.2 Primary Aim ...................................................................................................................... 26
4.2.3 Secondary Aims ................................................................................................................. 26
4.2.4 Exploratory Aims ............................................................................................................... 26
4.3 Background and Significance ......................................................................................................... 27
4.3.1 Fat mass and ALL .............................................................................................................. 27
4.3.2 Dieting, activity and caner ................................................................................................ 27
4.3.3 Diet and activity interventions for obesity ........................................................................ 28
4.3.4 Quality of life during ALL therapy ..................................................................................... 28
4.3.5 Study Significance ............................................................................................................. 29
4.4 Preliminary Data ............................................................................................................................ 29
4.5 Patient Criteria for Eligibility .......................................................................................................... 31
4.5.1 Inclusion criteria ................................................................................................................ 31
4.5.2 Exclusion criteria ............................................................................................................... 31
4.5.3 Concomitant therapy ........................................................................................................ 32
4.5.4 Co-enrollment on research studies ................................................................................... 32
4.6 Study Plan ...................................................................................................................................... 32
4.6.1 Summary of study plan ..................................................................................................... 32
4.6.2 Treatment plan ................................................................................................................. 33
4.6.2.1 Dietary intervention ............................................................................................. 33
4.6.2.2 Physical activity intervention ............................................................................... 33
4.6.2.3 Motivational interviewing (Promotion of adherence to intervention) ................ 34
4.6.2.4 Integration of intervention into ALL therapy ....................................................... 34
4.6.3 Subject renumeration........................................................................................................ 35
4.7 Modifications of Intervention for Toxicity ..................................................................................... 35
4.7.1 Modification of activity intervention ................................................................................ 35
4.7.2 Modification of dietary intervention ................................................................................. 35
4.8 Required Observations .................................................................................................................. 35
4.9 Statistical Considerations and Evaluation Criteria ......................................................................... 37
4.9.1 Sample size and study duration ........................................................................................ 37
4.9.2 Primary endpoint evaluation ............................................................................................ 37
4.9.3 Secondary endpoints evaluation ....................................................................................... 37
4.9.4 Exploratory endpoints evaluation ..................................................................................... 38
Chapter 5: Concluding Remarks and Future Directions ...................................................................... 40
5.1 Summary of Results ....................................................................................................................... 40
5.2 Study Limitation ............................................................................................................................. 41
iii

5.3 Future Research ............................................................................................................................. 42
5.3.1 Lipidomic analysis of ALL cells ........................................................................................... 42
5.3.2 Metabolic flux analysis ..................................................................................................... 42
5.3.3 IDEAL Weight in ALL Trial .................................................................................................. 42
Chapter 6: Materials and Methods ................................................................................................... 43
6.1 Experimental animals and in vivo dietary restriction .................................................................... 43
6.2 Cell culture and adipocyte differentiation ..................................................................................... 43
6.3 Oil Red O staining of neutral lipids ................................................................................................ 44
6.4 Quantification of adipocyte lipids .................................................................................................. 44
6.5 BODIPY-FFA tracing ........................................................................................................................ 45
6.6
13
C-labeling of adipocyte FFAs and ALL cell lipidomics .................................................................. 45
6.7 TOFA inhibition of ALL lipogenesis ................................................................................................. 45
6.8 Gene expression analysis ............................................................................................................... 46
6.9 Western blots ................................................................................................................................. 46
6.10 Statistical analysis .......................................................................................................................... 46
References ....................................................................................................................................... 47

iv

List of Figures
Figure 1.1 De novo lipogenesis and its key enzymes. 5
Figure 2.1 ALL cells and leukemia cell conditioned media induce adipocyte lipolysis
and FFA release.
10
Figure 2.2 Leukemia cell TNFα production is partly responsible for inducing
adipocyte lipolysis.
11
Figure 2.3 Fluorescently-labeled FFAs verify translocation of adipocyte-derived FFAs
to ALL cells.
12
Figure 2.4 Stable-isotope lipidomic identification of adipocyte-derived FFAs in ALL. 13
Figure 2.5 De novo lipogenesis in ALL cells co-cultured with adipocytes 14
Figure 2.6 ALL beta-oxidation in response to FFAs and adipocytes 16
Figure 3.1 Dietary restriction improves obese leukemic mouse survival after
vincristine treatment
19
Figure 3.2 Dietary restriction does not improve survival with other chemotherapies 20
Figure 3.3 Dietary restriction does not improve obese leukemic NSG mouse survival
with triple chemotherapy
21
Figure 3.4 Effect of serum restriction on vincristine efficacy in ALL cell lines 22
Figure 4.1 Experimental design schema 25
Figure 4.2 Body fat percentage measured by DXA 29
Figure 4.3 BMI percentile and MRD positivity 29
Figure 4.4 EFS per BMI during HR-ALL Therapy 30
Figure 5.1 Summary of interaction between ALL and adipocytes. 41

v

Dedication

To my parents who have been with me every step of the way, for their
love and support have made this trek all the more possible.

vi

Acknowledgements

First and foremost, I wish to thank my PI and mentor, Dr. Steve Mittelman. I have come to learn that the
view one has of his Ph.D. years is often dependent on his relationship with his mentor. I can easily say
these four years have been the most rewarding and enjoyable. Steve, with your insight and genuine
nature, you have provided me the perfect role model of a successful physician-scientist, respected
colleague and dedicated family man. For this, I could not be more grateful or fortunate.
I also wish to thank my committee members, Dr. Sebastien Bouret, Dr. Yong-Mi Kim, Dr. Muller Fabbri,
and Dr. Lily Chao. Your selflessness in dedicating your time and knowledge to my studies and this
dissertation are invaluable and will not be forgotten.
I need to thank my parents for dedicating their lives in raising me to value learning and to always keep
me questioning. You were my first mentors and our home was our lab. We created something special
over 27 years and this dissertation is one fruit on our ever-growing tree.
To my original “co-worker”, Rose, your sacrifice in being the girlfriend, fiancée and now wife of a Ph.D.
student is heroic. The long nights, the week-long conferences (especially 2 weeks before our wedding)
and occasionally coming home smelling like mice were far from ideal but you always kept me coming
home to love, support, food and overly-fed cats. With you at my side, I know we will achieve many great
things together.
To all the lab members, past and present, who have provided me support along the way, I could not
have been as successful without your help. Whether maintaining cells or offering advice, your impact on
my training is greatly appreciated.
Lastly, I want to extend my gratitude to my friend, colleague, fellow former graduate student, and
“boss”, Susan Sheng. You made each day in lab fun (and a zoo) by filling it with cats, monkeys, mice and
chicken. We also managed to get some work done too. I hope our careers can again intersect in the
future.

1

Chapter 1
1,2
:
Introduction
1.1 Pediatric Acute Lymphoblastic Leukemia (ALL)
Leukemia is the overarching term given to the uncontrolled proliferation of white blood cells within the
body. Leukemia can be classified according to the lineage, maturation and growth rate of the oncogenic
cell. Acute leukemias are defined by the presence of rapidly proliferating immature leukocytes; whereas,
chronic leukemias are typically slower growing and more mature. These classifications can be each
stratified by the hematopoietic lineage of the blast, namely lymphoid or myeloid. Together, these
comprise the four most prevalent types of leukemia: Acute Lymphoblastic Leukemia (ALL), Acute
Myeloid Leukemia (AML), Chronic Lymphoblastic Leukemia (CLL) and Chronic Myeloid Leukemia (CML).
In the US, ALL is most common in children and adolescents younger than 20 years of age, with 57.2% of
all new ALL diagnoses falling in this age group.(2) Among children, leukemia comprised more than 1 in 4
new cancer diagnoses between 2008 and 2012, with about 70% of those being ALL.(3,4) Additionally, B-
cell ALL makes up 80% of new ALL cases.(5) In all, 3 in every 100,000 children and adolescents in the US
were diagnosed with pre-B ALL during this 4-year span.(4)
B-cell ALL results from the disruption of normal B-cell maturation within the bone marrow, leading to
the overcrowding of the marrow with lymphoblasts and underdevelopment of normal hematopoiesis.
As such, children with B-cell ALL frequently present with fatigue, recurrent infections and/or easy
bruising due to deficiencies in normal red and white blood cell and platelet development, respectively.
Over the years, numerous discoveries have shed light on genetic driver mutations responsible for B-cell
ALL oncogenesis. The TEL-AML1 (ETV6-RUNX1) fusion gene, marked by the t(12;21) translocation, is the
most common genetic alteration in childhood cancer and responsible for pediatric B-ALL.(6,7) TEL-
AML1-positive pediatric patients generally have a good prognosis, with 5-year event-free survival (EFS)
rates around 90%. (8) Another fusion gene, BCR-ABL, resulting from the Philadelphia chromosome (Ph+)
t(9;22) translocation is found in about 5% of pediatric ALL cases(9) and up to 45% of adult cases.(10) The
BCR-ABL fusion gene results in the overexpression of the ABL tyrosine kinase that controls downstream
signaling of cellular division and survival.(11,12) Unlike children with TEL-AML1-positive ALL, pediatric
Ph+ ALL patients have a poorer prognosis and higher risk of relapse with a 4-year EFS around 50% with
standard chemotherapy.(13) The relatively recent addition of tyrosine-kinase inhibitors to Ph+ ALL
chemotherapy has increased the EFS survival to only around 70%.(13,14)
In 1990, Nora Heisterkamp and John Groffen introduced the human BCR-ABL transgene into C57BL/CBA
mice (P190 mice), demonstrating for the first time that this product of the Philadelphia Chromosome
caused leukemia.(15) Further research by this group demonstrated that the p190 isoform of BCR-ABL
drives B-cell ALL oncogenesis while the p210 isoform drives CML.(16) In the following chapters, I will
present results from experiments using the ALL cells (8093 cells) containing the p190 human BCR-ABL

1
This chapter contains direct text from the book chapter entitled, “Mouse Models to Study Obesity Effects on
Hematologic Malignancies”, of which I was first author, published in the book, Murine Models, Energy Balance,
and Cancer (1).

2
This chapter also contains direct text from an IRB-approval clinical trial protocol which I authored. I am a co-
investigator of the clinical trial conducted at CHLA. More information can be found at www.clinicaltrials.gov,
identifier: NCT02708108.
2

transgene originally derived from Dr. Heisterkamp’s mice. A commercially available human ALL cell line
(BV173), derived from a patient with Ph+ CML in blast crisis and contains the p210 BCR-ABL isoform, was
also used in experiments.
In addition to ALL cytogenetics, the National Institutes of Health (NIH) and Children’s Oncology Group
has established other clinical features that determine the risk stratification and prognosis of pediatric
ALL patients. Based on a large retrospective review, patients can fall into the following risk groups with
respective 4-year EFS: Low risk (>95%), Standard risk (90-95%), High risk (88-90%) and Very High risk
(<80%). Children older than 10 years, present with high white blood cell counts or fail to respond to the
first 29 days of chemotherapy (“Induction”) are typically stratified into High or Very High risk groups.
(17,18) Although not a recognized prognostic factor, obesity is associated with EFS levels similar to
High/Very High risk stratifications.(19)
1.2 Obesity and ALL
Obesity is a major cause of morbidity and mortality in the U.S. and worldwide. As of 2012, 34.9% of
American adults were classified as obese (BMI ≥ 30), with non-Hispanic blacks (47.8%) and Hispanics
(42.5%) having the highest rates.(20) More alarmingly, 68.5% of Americans adults are overweight or
obese (BMI ≥ 25), with almost 4 in 5 Hispanics falling in this category. However, this epidemic is not
limited to the adult population. In the same year, 16.9% of American children were classified as obese
(BMI > 95
th
percentile), with the highest rates in 6-11 year old Hispanic males. Moreover, 31.8% of all
children aged 2 to 19 years were classified as overweight or obese (BMI ≥ 85
th
percentile), with Hispanic
6-11 year old males approaching 50%.
Obesity contributes to hypertension, hyperlipidemia, diabetes, heart and cerebrovascular disease, the
leading causes of morbidity and mortality in American adults.(21) The rise in childhood obesity is also
accompanied by increasing incidence in hypertension, hyperlipidemia and diabetes in the pediatric
population.(22) While the effects of increased adiposity on cardiovascular health and diabetes are well
documented, a role for obesity in cancer pathogenesis has been proposed.
Obesity increases the incidence of many cancer types, and obese cancer patients have a higher risk of
mortality from their disease.(23) In 2007, a landmark study in the Children’s Oncology Group (COG) led
by Dr. Butturini from the Children’s Hospital Los Angeles (CHLA) demonstrated in two large cohorts
(4,314 and 1,160 patients) that obesity at the time of diagnosis increases risk of relapse in children with
National Cancer Institute/Rome High-Risk ALL (HR-ALL) by 50% (19), a finding independently confirmed
in a different population of children (24) and in obese adults.(25) In a separate cohort, obese children
were 2.74 times more likely to be minimal residual disease (MRD) positive (26), a finding associated with
increased relapse risk and reduced event-free survival.(27,28)
In a recent study, 36% of children with ALL were overweight or obese at diagnosis.(29) In a cohort of
adolescent and young adults with HR-ALL at Children’s Hospital Los Angeles (CHLA), there is a similar
prevalence of high body fat with 34% who were overweight or obese at diagnosis.(30) Preliminary data
show that individuals then gain a significant amount of adipose tissue after diagnosis during the first
month of treatment (“Induction”) regardless of baseline total body fat, while in another cohort 23% of
children with HR-ALL continued to be obese throughout therapy.(31) The use of glucocorticoids such as
dexamethasone and prednisone during induction therapy likely contribute to this fat gain, as they
stimulate adipogenesis and appetite. Predisposition to inactivity due to intensive leukemia treatment
combined with steroid-induced dietary derangements are therefore likely moderating factors of this
3

marked gain in body fat. As response to leukemia treatment in the first month of therapy is a key
determinant of overall prognosis and risk for relapse, obesity and body fat are substantial risks factors
for relapse. Together, the worsening childhood obesity rates and the recently discovered role of obesity
in pediatric ALL demand further research into molecular mechanisms responsible for this role.
1.3 ALL and Adipocytes
Obesity is the result of excess fat storage within adipocytes. In addition to storing fat, adipocytes
function as an important endocrine and immune tissue, secreting hormones and cytokines that regulate
such processes as feeding and inflammation. These processes are tied ultimately to the health of the
adipocyte. During states of caloric excess, adipocytes are stimulated by insulin to take up excess dietary
metabolites like glucose and free fatty acids (FFAs). Through insulin activation of the phosphoinositide 3’
kinase (PI3K) pathway, these metabolites are then stored as triglycerides, neutral lipids stored within
densely packed lipid droplets within the adipocytes.(32) Activation of lipogenic pathways is concomitant
with repression of lipolysis and fatty-acid oxidation to prevent the immediate breakdown of the new
lipids.(33) In addition to increasing existing adipocyte lipogenesis, insulin stimulates the differentiation
of pre-adipocytes into new adipocytes, further expanding the fat storage capacity of the body.(34)
Despite adipocyte responsiveness to excess caloric intake, adipocyte lipid storage can become untenable,
resulting in adipocyte necrosis and tissue inflammation.
As adipocyte hypertrophy leads to cell stress and necrosis, immune cell infiltration and activation
promotes adipose tissue inflammation. Under normal conditions, adipocytes are key mediators of the
inflammation state of the surrounding microenvironment. Healthy adipocytes secrete adiponectin,
inducing the secretion of anti-inflammatory mediators like IL-10 and IL-1RA by neighboring monocytes
and macrophages.(34) Conversely, inflammatory cytokines like TNFα and IL-6 repress adiponectin
expression, creating a feed-forward loop within adipose tissue once inflammation occurs.(35) Opposing
adiponectin is another adipokine, leptin. Leptin is directly correlated with both fat mass and adipocyte
size and is responsive to insulin levels.(36,37) Unlike adiponectin, leptin stimulates adipose tissue
inflammation by promoting T-cell proliferation and differentiation through IL-1 and TNFα secretion.(38)
The imbalance of leptin to adiponectin in obesity dysregulates adipocyte function and the subsequent
hyper-secretion of inflammatory cytokines into the adipose tissue microenvironment are implicated in
mammary and hepatic carcinogenesis.(39,40)
While the link between adipose tissue inflammation and solid tumor carcinogenesis is evident, the
association between adipocyte dysregulation and blood cancer is less obvious. In B-cell ALL, the bone
marrow is the primary tumor site, as it is home to B-cell development. The bone marrow is comprised of
a heterogeneous mix of both red and white blood cell blasts in close interaction with the surrounding
stroma. This stroma containing osteoblasts, endothelial cells, fibroblasts and adipocytes supports both
normal hematopoiesis and cancer cell proliferation.(41,42) Systemic obesity similarly increases marrow
adiposity in both children and adults.(43,44) Increased marrow adiposity and thus marrow leptin has
been shown to be critical for lymphopoiesis, with pre-B cell numbers doubling in obese mice.(45) More
troubling is the finding that marrow adiposity also increases following induction chemotherapy,
providing any surviving ALL cells a fertile environment for growth and relapse.(46) Outside the bone
marrow niche, adipose tissue depots provide a similar environment for ALL survival.
Our lab has previously shown that adipocyte secretion of the cytokine, stromal-derived factor-1 alpha
(SDF-1α), is responsible for ALL migration into adipose tissue.(47) Once in the adipose
microenvironment, ALL cells reside in nutrient-rich surroundings. Our lab has demonstrated that
4

adipocytes release other metabolites such as asparagine and glutamine, amino acids vital for cancer cell
growth and resistance against the chemotherapy, L-asparaginase.(46) The physical increase in adiposity
in obesity also diminishes chemotherapy efficacy by altering drug pharmacokinetics. One recent
systemic review found that 40% of obese cancer patients are underdosed since a dose proportional to
body weight exceeds toxicity limits.(48) Another study published by our lab demonstrated that there is a
lower concentration of vincristine in the bone marrow and circulation of obese mice than normal weight
mice.(49)
As presented above, the presence of adipocytes, in marrow and adipose tissue, can promote both
carcinogenesis and cancer survival. Yet when assessing adipocyte contribution to ALL cell proliferation
and survival, it is necessary to consider the most abundant resource in adipocytes, lipids.
1.4 Lipids and Cancer
Lipids fulfill three main roles in cell metabolism: membrane synthesis, cellular signaling and energy
production.
Phospholipid membranes form the barriers that compartmentalize cellular processes within organelles
and separate the cell from its environment. Phospholipids are comprised of a polar head region that
largely determines functionality and two non-polar fatty-acid tails that reside within the inner leaflet of
the membrane. Unsaturation (presence of double-bonded carbons) within the fatty-acid tails
contributes to membrane fluidity and cellular pliability.
With the assistance of phospholipases, these fatty-acid tails are removed from the polar head groups
and become active signaling molecules. Fatty acids such as arachidonic acid, when released from
phospholipids, are converted into eicosanoids, necessary for inflammatory responses and vascular
toning. Certain eicosanoids produced by cancer cells promote tumor growth(50), angiogenesis(51) and
immunosuppression(52) within the microenvironment.
Lastly, free fatty acids can be shuttled into the mitochondria by carnitine-palmitoyl transferase 1a
(CPT1a) and used as a substrate for beta-oxidation. Beta-oxidation, in breaking down fatty acids two
carbons at a time, produces acetyl-CoA, NADH and FADH
2
. NADH and FADH
2
are direct co-factors for
complex I and complex II of the electron transport chain, respectively. Between these three products,
one cycle of beta oxidation can produce 14 ATPs and over 100 ATP for complete beta-oxidation of one
fatty acid. Very long chain fatty acids can undergo similar beta-oxidation in peroxisomes instead of
mitochondria. Activation of beta-oxidation provides major sources of energy for solid tumor cancers of
the prostate and pancreas.(53,54) Consequently, inhibition of beta-oxidation can induce apoptosis in
leukemia and glioblastoma.(55,56)
The lipids necessary for these processes can either be synthesized de novo or taken up from the
surrounding environment. De novo lipogenesis is a cytoplasmic process that synthesizes saturated free
fatty acids from acetyl-CoA using NADPH as a co-factor. Acetyl-CoA Carboxylase (ACC) converts acetyl-
CoA into malonyl-CoA, the rate limiting step of lipogenesis. Next, malonyl-CoA and acetyl-CoA are
synthesized by Fatty Acid Synthase (FAS) to form the initial 4-carbon backbone of the new fatty acid.
Each subsequent cycle catalyzed by FAS will add two carbons from a new malonyl-CoA onto the growing
fatty acid, until a 16-carbon fatty acid (palmitate) is synthesized. Palmitate can then be shuttled into the
endoplasmic reticulum for elongation or desaturation into unsaturated FFAs. Most FFA desaturation is
handled by Stearoyl-CoA Desaturase 1 (SCD1), a delta-9 desaturase, creating a double bond at the ninth
carbon from the carboxyl end. SCD1 is responsible for the conversion of stearic acid to oleic acid, the
5

most common FFA in the cell. Other desaturase enzymes are responsible for the synthesis of
polyunsaturated FFAs like arachidonic acid.

Activation of de novo lipogenic pathways accompanies the high proliferative and metabolic rates of
cancer. Akt, constitutively activated in many cancers(57), activates lipogenesis through increased
transcription of the key lipogenesis transcription factor, sterol-regulatory element binding protein
(SREBP).(58) Upregulation of SREBP increases FAS expression and FFA accumulation within the cell.
Studies also suggest that tumor suppressors Rb and p53 associate regulate SREBP expression and
activation and their loss in cancer stimulates a lipogenic phenotype.(59,60) Similarly, FAS is commonly
overexpressed in many cancers, including breast, colon, prostate, stomach and ovarian cancer.(61)
Overexpression of FAS is also associated with increased recurrence and poorer patient survival in breast,
ovarian, lung and endometrial cancers.(62–65) ACC is overexpressed in breast cancer and knockdown of
ACC reduces breast cancer cell viability.(66,67) Additionally, the BRCA1 tumor suppressor interacts with
ACC and mutations in BRCA1 free ACC for lipogenesis.(68,69) Lastly, SCD1 overexpression is present in
colon, esophageal and hepatic cancers.(70) Mice genetically susceptible to liver cancers have greater
hepatic SCD1 expression compared to less susceptible mice.(71) Pharmacological inhibition of SCD1
activates AMPK and reduces ACC activity thereby limiting proliferation of breast and lung cancer
cells.(72) The importance of lipogenesis in cancer is stressed by the independent associations of FAS,
ACC and SCD1 with the proliferation and pathogenesis of numerous cancers.
In addition to lipogenesis, cancer cells are able to derive necessary lipids from their surrounding
microenvironment. Ovarian cancer cells actively home to the omentum where adipocytes provide lipids
to the cancer cells for beta-oxidation and tumor growth.(73) A similar lipid translocation has been noted
between adipocytes and prostate cancer.(74) This translocation results from a crosstalk between cancer
cells and neighboring adipocytes. The ovarian cancer cells stimulate adipocyte lipolysis and release of
FFA into the microenvironment. Macropinocytosis of albumin-bound FFAs and exosomal transfer are
two possible methods for cancer cell FFA uptake.(75,76) A recent study suggests that Ras-transformed
breast and lung cancer cells preferentially bypass de novo lipogenesis for exogenous lipid uptake in
hypoxic states.(77) Alternatively, cancer cells maintain the ability to upregulate de novo lipogenesis in
lipid-poor environments.(78)
In Chapter 2, I will discuss how ALL cells exhibit such flexibility in their lipid metabolism, downregulating
lipogenic pathways in the presence of lipid-rich adipocytes.
1.5 Modeling Obesity and ALL in Mice
Perhaps the most popular mouse model of obesity is the diet-induced obese (DIO) mouse model. This
term generally refers to C57BL/6 mice raised on a high fat diet. While many high fat diets have been

Figure 1.1 - De novo lipogenesis and its key enzymes.
6

used, the most common ones are based on diets originally developed by Surwit (79), and contain either
45% or 60% of calories from fat. Excess fat in these defined ingredient diets comes from lard, and there
are several control diets from which to choose, with variable amounts of sucrose based on the
investigator’s needs. It should be noted that these high fat diets also have higher caloric density than the
control diets or standard mouse chow, and so technically speaking the mice are exposed to a high
fat/high calorie diet. C57BL/6 mice on these diets consume more calories per day and gain weight
rapidly.(80,81) They become glucose intolerant and develop diabetes with age, as well as some of the
cardiovascular complications associated with human obesity.(82,83) Diets high in fructose, sucrose, or
both have been used to induce insulin resistance and hypertriglyceridemia in rodent models; however,
they are less effective in producing obesity in mice than in larger rodents.(84–87)
It is possible to categorize most mouse strains into diet sensitive or diet resistant based on their
response to a high fat diet. C3H/HeJ, A/J, C57L/J and Balb/C mice are relatively resistant to obesity,
while AKR/J, DBA/2J, and C57BL/6 mice are diet sensitive.(80) It is important to keep in mind that a
portion (10-15%) of even sensitive strains of mice will be diet resistant when raised on a high fat diet.
There are several genetic mutations in mice that can cause varying degrees of obesity. Most of these
involve perturbations in the function of leptin. The ob/ob leptin deficient mouse and the db/db mouse
with a nonsignalling leptin receptor were both discovered as spontaneous mutations. These mice exhibit
hyperphagia and develop severe obesity and diabetes, which is exacerbated when they are put on a high
fat diet.(88–90) Similar to the db/db mouse, the s/s mouse carries a STAT3 mutation that disrupts
downstream leptin receptor signaling.(91) Leptin acts primarily on proopiomelanocortin (POMC)-
expressing neurons in the hypothalamus, inducing signaling through αMSH on melanocortin (MC)
receptors, predominantly MC4 and to a lesser extent MC3.(92) Mice with knockout of POMC, MC3, or
MC4 all develop obesity to varying degrees. Similarly, mice which overexpress the MC receptor
antagonists agouti or agouti related protein (AgRP) are characterized by hyperphagia and obesity.(93,94)
The fat mass and obesity associated gene, FTO, was the first obesity susceptibility gene identified by
genome wide association studies.(95) Single nucleotide polymorphisms which are associated with
human obesity have been shown to increase expression of the FTO product.(96) Likewise, increased
copy number of FTO in mice leads to increased food intake and obesity.(97)
Some genetic models seem to uncouple the effects of obesity on adiposity and metabolism. The
adiponectin overexpressing mouse, made on an ob/ob background, exhibits severe adiposity, but is
relatively protected from dyslipidemia, insulin resistance, and deposition of ectopic fat.(98) Likewise, the
aTGL null mouse stores excess lipid in adipose tissue, leading to increased adiposity yet a lean metabolic
phenotype.(99) These models could be used for the study of hematologic malignancy, and other
pathologies, to test for effects of adipose tissue per se without the metabolic derangements generally
observed in obesity.
To improve the relevance of mouse models to human cancer, much recent work has been done
developing xenografts, wherein human cancer cells are engrafted onto an immunodeficient mouse. This
allows the study of human cancer cells in an in vivo environment, albeit one lacking an adaptive immune
system. Most of this work has utilized varieties of Nude, Rag1 null, and severe combined immune
deficiency (SCID) mice.
Nude mice are characterized by their abnormal hair growth and defective thymic development. This
athymia results in a lack of T-cells, as well as a partial B-cell developmental defect.(100) In an attempt to
make obese nude mice, Moiola et al. raised 4 week old Swiss nu/nu mice on a high fat diet for 16 weeks.
7

This diet resulted in a modest elevation in cholesterol level, though only a tendency for increased body
weight.(101) A high fat diet for 6 months in BALB/c nu/nu mice led to a modest increase in body fat, but
no difference in overall body weight compared to control fed mice.(102)
Rag1 null mice lack both B and T cells, due to a deficiency of the recombinant activating gene necessary
for B and T cell maturation. Rag1 mice are considered a “non-leaky” alternative to “leaky” SCID mice
that still develop small levels of B cells and IgM.(103) These mice, which are available on a C57BL/6
background, develop substantial obesity when put on a high fat diet.(104) In fact, they become even
more obese and insulin resistant than C57BL/6 controls, possibly due to absence of specific CD4+ T
cells.(104,105)
SCID mice put onto a high fat diet develop significant obesity, and weighed in one study on average 45%
more than control fed mice.(106) However, Lucas et al. found that C.B-17 SCID mice on a high fat diet
develop increased adiposity, but no increase in overall body weight. Nod/SCID IL2R C -/- (NSG) mice
lack lymphocytes and NK cells, and have been shown to yield better engraftment of human
hematopoietic cells. However, we found that NSG mice were relatively resistant to diet induced obesity
when raised on a 60% fat diet, weighing only about 15% more than control fed mice.(107) To accentuate
this obesity, we reduced litters to 2 mice on day of life #5 as described above, leading to fat fed mice
that were 33% heavier than control fed (non-litter reduced) mice.
These immunodeficient mouse models have all been used to xenograft human hematopoietic
malignancies.(108–117) However, to our knowledge, no studies have been reported in which obese
phenotypes of these mice have been used to evaluate the effects of obesity on human hematopoietic
cancer in vivo. However, recent work from our lab explored the effect of obesity on ALL in a syngeneic
mouse model.
The “P190 mouse” described in section 1.1 created by Drs. Heisterkamp and Groffen develops leukemia
by about 2 months of age, characterized by bcr/abl expressing pre-B ALL cells.(15) Malignant cells
accumulate in the bone marrow and spleen, as in the clinical disease; however, they also form
lymphoma-like tumors, which are not commonly seen in the human disease. Mice become rapidly ill if
not treated, and need to be sacrificed within days of disease becoming clinically apparent (to avoid
death as an endpoint). This model has since been bred onto a C57BL/6 background.
In 2010, we weaned male C57BL/6 P190 mice onto either high fat (60% fat from Research Diets, see
above) or chow diet. Like the background strain, these P190 mice developed diet induced obesity, with
significantly heavier weight within 1 week of weaning. While median lifespan was not different between
obese and control P190 mice (107 vs. 113 days, p=0.2), there was a time dependent effect of obesity to
increase ALL hazard ratio (p<0.05). Thus, obesity accelerated the risk of ALL at older ages.(118)
In Chapter 3, I will discuss how syngeneic and xenograft models of ALL in diet-induced obese mice were
used to assess the effect of caloric and dietary fat restriction on chemotherapy efficacy and overall
survival.
1.6 Dietary and Activity Modulation in Cancer Therapy
The concept of introducing caloric restriction in animal cancer models has been explored throughout the
last century.(119) Recent experiments have focused on the theory of “differential stress resistance,” a
diet restrictive metabolic state that increases normal tissue, but not cancer cell, tolerance to
chemotherapy.(120) During carcinogenesis, cancer cells acquire mutations to various metabolic
oncogenes, such as Akt and Ras, which allow uncontrolled proliferation. During dietary restriction and
8

the subsequent lack of nutrients and growth factors, normal cells down-regulate their metabolic activity
while cancer cells maintain their elevated metabolic state, a condition that promotes greater
chemotherapy specificity toward cancer cells. This was demonstrated in a transgenic mice with human
neuroblastoma fasted for 48 hours prior to etoposide treatment. The fasted mice not only survived
longer than non-fasted mice but also suffered less drug-induced toxicity.(121)
While such a severe starvation diet is not feasible in the clinical setting, altering dietary composition
and/or reducing caloric intake is sufficient to see similar results. In a murine prostate cancer model, mice
fed with either a low-fat or no-carbohydrate diet had significantly reduced tumor growth compared to
mice on a “Western” diet.(122) Similarly, a low carbohydrate, high protein, isocaloric diet limited
squamous cell carcinoma and breast cancer growth in mice.(122) Conversely, restricting total caloric
intake during treatment by 30% reduced breast tumor aggressiveness and tumoral fat content.(123) Our
own preliminary research (described in Chapter 4) has demonstrated a similar effect of caloric and fat
restriction on reducing the weight and improving survival of obese mice with ALL.
Physical activity during therapy has also been shown efficacious to augment cancer sensitivity. Mice that
were allowed to run on a wheel had slower breast tumor growth and improved immune function
compared to non-exercised mice.(124) Furthermore, the amount of running inversely correlated with
the size of the tumor. Similarly, serum from men who exercise for one hour prevented prostate cancer
growth in vitro compared to cells in serum from non-exercising men.(125) Despite this history and the
breadth of research into diet and exercise interventions as adjuvants to chemotherapy, the translation
of these laboratory findings into the clinical setting has remained a barrier.
Diet and exercise have concrete benefits in addition to potentially augmenting chemotherapy efficacy.
Multiple clinical trials conducted in the last ten years have demonstrated the ability of diet and/or
exercise interventions to prevent chemotherapy-associated fat gain, reduce fatigue and improve
emotional well-being in adults with solid tissue and hematological cancers.(126–128) Furthermore, the
American Cancer Society has recommended that proper nutrition and physical activity play a role in all
phases of cancer treatment.(129)
In Chapter 4, I will detail the protocol for a current clinical trial assessing the impact of a personalized
dietary and activity intervention on reducing chemotherapy-induced body fat gain and its effect on ALL
MRD after Induction.
In all, this dissertation will provide an overarching analysis of the effect of fat on acute lymphoblastic
leukemia through various models with a translational approach. Using in vitro models, I will delve into
the interplay between ALL cells and neighboring adipocytes and the mechanisms that govern adipocyte
lipid translocation into ALL cells. Then, I will introduce how a reduction in caloric and fat dietary intake
drastically improves chemotherapy efficacy in a diet-induced obese leukemic mouse model. Lastly, I will
present a new clinical trial that seeks to translate our in vivo findings to pediatric ALL patients with an
aim to prevent treatment-induced weight gain and improve treatment efficacy.

9

Chapter 2:
Acute lymphoblastic leukemia uptake of adipocyte-derived free fatty acids alters
their cellular metabolism
2.1 Introduction
B-cell ALL develops in the bone marrow, a niche rich with osteoblasts, fibroblast, endothelial cells and
adipocytes that support cancer growth and survival.(130,131) Adipocyte secretion of stromal-derived
factor 1 alpha (SDF1α) likely maintains ALL cell residence within the bone marrow niche(132) and
promotes migration of ALL into extramedullary adipose tissue depots.(47) Residence within the adipose
microenvironment limits ALL exposure to or efficacy of chemotherapy.(46,49) In breast cancer
metastases, cancer cell and adipocyte metabolism intertwine to promote tumor progression. Cancer cell
oxidative phosphorylation driving cell proliferation is fueled by changes within the surrounding stroma
and the subsequent release of nutrients.(133) Crosstalk between ovarian cancer cells and stromal
adipocytes stimulate the translocation of adipocyte lipids for cancer cell metabolism.(73)
Lipids, among other roles, are chiefly utilized by cancer cells to meet the requirements for rapid
membrane and energy production. The FFAs needed for these processes can be synthesized de novo or
extracted from the surrounding environment. As an anabolic process, de novo lipogenesis converts base
nutrients and energy into saturated and unsaturated FFAs under the regulation of three key enzymes,
FAS, ACC and SCD1. Upregulation of each of these enzymes is associated with greater cell viability,
recurrence and patient mortality in breast, colon, prostate, stomach, lung and ovarian cancer.(61–72) In
a lipid-poor environment, cancer cells can upregulate this pathway to maintain necessary lipid levels for
growth.(78) However, when lipids are abundant, cancer cells can readily, and sometimes preferentially,
utilize exogenous lipids for cellular processes, sparing vital nutrient for other anabolic processes.(74,77)
In the present study, I report that ALL cells stimulate adipocyte lipolysis and take up released FFAs. In
turn, ALL cells downregulate de novo lipogenesis and upregulate fatty acid oxidation, demonstrating a
preferential utilization of exogenous lipids. These results provide another explanation for the negative
effect of obesity in ALL and bring light to potential targets to reverse this effect.
2.2 Results
2.2.1 ALL cells stimulate adipocyte lipolysis
To investigate the ability of ALL to induce adipocyte lipolysis, murine ALL (8093) or human ALL (BV173)
cells were plated over differentiated 3T3-L1 adipocytes for 72 hours. Similarly, leukemia conditioned
media (LCM), 48 hours post-incubation with either ALL cell line, was added to adipocytes for 72 hours.
Following the 72 hour period, adipocytes lipid content, as determined by Oil Red O lipid staining, was
significantly decreased by BV173 cells and 8093 LCM (BV173: 0.66 ± 0.09 red pixels/adipocyte, p=0.02;
8093 LCM: 0.79 ± 0.08 red pixels/adipocyte, p=0.047).(Fig 2.1A-C) 8093 and BV173 LCM induced similar
declines in adipocyte Oil Red O staining, albeit non-significantly. Neither fibroblasts nor fibroblast
conditioned media induced lipid loss. When measured by FFA release, BV173 LCM significantly
stimulated adipocyte lipolysis, compared to basal levels in complete media or conditioned media from
non-leukemic murine pre-B cells (BV173 LCM over Complete media: 17.5 ± 6.2μM FFA, p=0.047; LCM
over pre-B CM: 20.9 ± 7.2μM FFA, p=0.043).(Fig 2.1D)
10

2.2.2 TNFα is partly responsible for ALL-induced adipocyte lipolysis
Adipocyte lipolysis is a well-defined process, with many cancer-derived cytokines being inducers during
the cachectic state.(134–136) We used a cytokine array to quantify cytokines released by BV173 cells
into LCM. In addition to measuring relatively large levels of RANTES and IL1-RA, we focused our
attention to TNFα since it has the strongest evidence for causing cancer-induced lipolysis. BV173 cells
release nearly 4pg/mL TNFα into media conditioned for 48 hours.(Fig 2.2A) To test whether this is
sufficient to stimulate lipolysis, adipocytes were exposed to increasing doses of TNFα, including 4pg/mL.
TNFα accounts for about 75% of the lipolysis induced by BV173 LCM (4pg/mL TNFα: 20.6 ± 11.7μM FFA;
BV173 LCM: 28.4 ± 10.3μM FFA; n=3 per condition).(Fig 2.2B) The monoclonal antibody to TNFα,
infliximab, is widely used in the clinical setting for inflammatory conditions like rheumatoid arthritis. We
used infliximab to test its ability to prevent TNFα and LCM-induced lipolysis. Infliximab significantly
reduced TNFα-induced adipocyte lipolysis to basal levels.(Fig 2.2C) Phosphorylation of ERK, a
downstream mediator TNFα-induced lipolysis, was also reduced to basal levels by infliximab.(Fig 2.2D)
Conversely, infliximab only partially, and non-significantly, reduces LCM-induced FFA release and ERK
phosphorylation.(Fig 2.2E-F)
Figure 2.1 - ALL cells and leukemia cell
conditioned media induce adipocyte lipolysis and
FFA release. A) Adipocyte lipid content after 72-
hour co-culture with murine (8093) ALL cells,
human (BV173) ALL cells or fibroblasts as control.
B) Adipocyte lipid content after 72-hour
incubation with leukemia or fibroblast
conditioned media. Lipid content measured by Oil
Red O staining was quantified by totaling red
pixels and dividing by number of adipocytes in
each image. Values are normalized to lipid
content of adipocytes in the absence of co-
cultured cells or conditioned media. (20 images
per condition per n; n=3; * = p<0.05) C)
Representative images of adipocytes in the
absence (top) and presence (bottom) of 8093
conditioned media (LCM) after 72-hour incubation
(Red = Oil Red O; Blue = DAPI counterstain). D)
Quantification of colorimetric assay measuring
FFAs released by adipocytes into media after 24
hour incubation with complete media, non-
leukemic pre-B cell conditioned media or BV173
LCM (n=3; * = p<0.05).
11

2.2.3 Translocation of adipocyte-derived FFAs into ALL lipid structures
Knowing ALL cells stimulate adipocyte lipolysis, we then shifted our focus to whether ALL cells take up
the newly released FFAs. A reduction in BV173 LCM FFA content compared to normal media suggests
ALL are capable of utilizing significant amounts of FFAs from their environment (LCM: 11.9 ± 5.7μM FFA;
Complete media: 23.4 ± 3.1μM FFA; n=3; p=0.037).(Fig 2.3A) To verify translocation of FFAs from
adipocytes to ALL cells, we utilized a fluorescently-labeled palmitate analog (BODIPY-FFA) that
incorporates into adipocyte triglyceride and phospholipids.(Fig 2.3E, 3T3-L1) After 48 hours, 8093 and
BV173 cells co-cultured over pre-labeled adipocytes contained 3-6 times more BODIPY-FFA than cells co-
cultured over pre-labeled fibroblasts (8093 over Adipo: 1568.0 ± 365.5 vs. over Fibro: 522.8 ± 10.66,
p=0.011; BV173 over Adipo: 7181.0 ± 939.8 vs. over Fibro: 939.8 ± 27.43, p<0.001).(Fig 2.3B) This
translocation becomes evident in as little as 2 hours.(Fig 2.3C) Closer examination of these cells under
confocal microscopy shows that ALL cells incorporate the adipocyte-derived BODIPY-FFAs within
membranes and dense puncta. Oil Red O staining of stock BV173 cells identifies these puncta as
triglyceride-laden lipid droplets, a phenomenon to our knowledge not known before in ALL.(Fig 2.3D)
Lipid extracts from 8093 and BV173 cells plated over BODIPY-FFA labeled adipocytes were run on a thin-
layer chromatography plate and exposed under UV light to detect the fluorescent FFAs. This confirmed
Figure 2.2 - Leukemia cell TNF α
production is partly responsible for
inducing adipocyte lipolysis. A)
Quantification of human cytokines in
BV173 LCM. Displayed are the 13 of 30
assayed cytokines which were
present. B) Measurement of adipocyte
lipolysis following TNFα dose response
(black line). Doses ranged from
4pg/mL to 40ng/mL TNFα for 24
hours. Level of BV173 LCM induced
lipolysis (red bar; from Fig 2.1D) is
overlain with 4pg/mL TNFα for
comparison (n=3/dose) C,D) Effect of
infliximab on TNFα and LCM induced
adipocyte lipolysis, respectively. Total
FFA in media is quantified
(n=4/condition; *=p<0.05) E,F) Effect
of infliximab on TNFα and LCM-
induction of adipocyte ERK
phosphorylation, respectively, as
measured by Western blot. Ratio of
phospho-ERK to total ERK was
measured by densitometric analysis of
Western blots. Western blot of one
representative n is below the graph.
(n=4/condition; *=p<0.05, **=p<0.01)
12

the storage of adipocyte-derived FFAs within ALL triglyceride-laden lipid droplets (TG arrow) and
phospholipids (PL arrow).(Fig 2.3E) Alkaline hydrolysis of lipid extracts, which cleaves fatty acid tails from
the polar head of the phospholipid, verified the spot at the origin of the lane was indeed phospholipid.

2.2.4 Lipidomic analysis of adipocyte-derived FFAs in ALL
The use of fluorescently-labeled FFAs like BODIPY-FFA allowed for the tracing of lipid movement from
adipocyte to ALL, but it is limited in its ability to identify the types of FFAs being transferred. Saturated
and unsaturated FFAs, despite the difference of only double-bonded carbons, can have very different
fates within the cell. For instance, the saturated FFA palmitate (C16:0) promotes breast cancer apoptosis,
whereas the unsaturated FFA oleate (C18:1) induces cancer cell proliferation.(137) Therefore, to
understand what FFAs are transferred from adipocytes to ALL, we differentiated adipocytes in the
presence of U-
13
C-glucose.
Following differentiation, incorporation of the stable-isotope into adipocyte triglycerides was verified by
desorption electrospray ionizing mass spectrometry (DESI-MS), a technique performed in collaboration
with Dr. Richard Zare and his lab at Stanford University.(Fig 2.4A) Incorporation of the
13
C label shifts the
mass of each lipid by intervals of one, due to the extra neutron in the carbon nucleus. In Figure 2.4A, the
increased amplitude of peaks spaced 1 value apart on the mass to charge (m/z) axis is indicative of
increasing levels
13
C-labeling within triglycerides.
During adipocyte differentiation, FFAs are synthesized from glucose through acetyl-CoA, building the
FFA carbon chain in multiples of 2. Thus, incorporation of
13
C into FFAs shifts the m/z ratio by multiples
of 2. Relative
13
C enrichment in BV173 oleic acid following 24 hour co-culture over
13
C-labeled
adipocytes is significantly increased at m/z=284.26, but not 283.26 or 285.26, confirming the original
Figure 2.3 – Fluorescently-labeled FFAs verify
translocation of adipocyte-derived FFAs to ALL cells.
A) Quantification of FFAs in complete media and
BV173 LCM. (n=3; *=p<0.05) B) Flow cytometry of
8093 (right) and BV173 (left) cells co-cultured for 48
hours over adipocytes (A) or fibroblasts (F) pre-labeled
with BODIPY-FFA. Cells were also co-cultured over no
feeder layer (N). The median value of BODIPY
fluorescence is displayed. (n=4/condition; *=p<0.05,
***=p<0.005) C) Flow cytometry histogram of BV173
cells co-cultured for 0, 1 or 2 hours over adipocytes
pre-labeled with BODIPY-FFA. D) Confocal microscopy
of 8093 (top) and BV173 (middle) cells co-cultured for
48 hours over adipocytes pre-labeled with BODIPY-
FFA. Normally cultured BV173 cells were stained with
Oil Red O (bottom) to detect triglycerides. (Green:
BODIPY-FFA; Red: Oil Red O; Blue: DAPI) E) Ultraviolet
exposure of thin-layer chromatography plate with
BODIPY-labeled lipids in 3T3-L1 adipocyte, BV173 and
8093 cells.* = Alkaline hydrolyzed lipid extracts from
each cell. PL = Phospholipid; TG = Triglyceride.
13

synthesis of ALL oleic acid from
13
C-glucose within adipocytes.(Fig 2.4B, left) On the other hand, the
glycerol backbone of the phospholipid head is derived from a 3-carbon glucose intermediate, meaning
13
C-labeling of the phospholipid will also shift the m/z ratio by 3. Relative
13
C enrichment in ALL
phosphatidylcholine(18:0/16:1) is significantly increased at both m/z=784.57 and 785.586, confirming
13
C-labeling in both the glycerol backbone and the FFA tails.(Fig 2.4B, right).
Next, BV173 cells co-cultured over
13
C-labeled adipocytes were harvested after 6, 24 and 48 hours to
determine the uptake rate of the 2 major saturated (Palmitate [C16:0] and Stearate [C18:0]) and
unsaturated FFAs (Palmitoleic [C16:1] and Oleic [C18:1]).
13
C enrichment in these 4 FFAs in BV173 cells
increased with longer adipocyte incubation, confirming the FFA translocation measured by BODIPY-FFA.
Curiously, the rate of
13
C enrichment was significantly greater in unsaturated FFAs, specifically
palmitoleate.(Fig 2.4C) This suggests a selective transfer of unsaturated FFAs from adipocyte into ALL
cells, in line with previous studies on the anti-apoptotic effects of unsaturated FFAs.

2.2.5 Downregulation of ALL de novo lipogenesis in the presence of adipocytes
Given the significant uptake of adipocyte-derived FFAs by ALL cells, we sought to determine the effect
this had on ALL de novo lipogenesis. To do this, we measured the ALL gene expression of the three key
enzymes in this pathway, FASN, ACC1 and SCD1.(Fig 2.5A) Gene expression of each of these enzymes is
significantly reduced in the presence of oleic acid, but not palmitic acid. Adipocyte co-culture also
Figure 2.4 – Stable-isotope lipidomic
identification of adipocyte-derived FFAs in ALL.
A) Representative spectra from DESI-MS
analysis of adipocytes differentiated without
(left) and with (right) U-
13
C-glucose. Spectra are
cropped to highlight triglycerides (m/z > 800).
Increased triglyceride results in increased peak
amplitude. B)
13
C enrichment in ALL oleic acid
(left) and phosphatidylcholine(18:0/16:1)
following co-culture with
13
C-labeled adipocytes
for 24 hours. Incorporation of
13
C into the lipids
follows synthesis from
13
C-glucose in
adipocytes. Enrichment values are relative to
abundance of non-labeled oleic acid or
phosphatidylcholine (PC). Natural abundance is
the calculated likelihood of
13
C incorporation
from the environment. Values are derived from
the average peak intensity at the corresponding
m/z over 5 samplings. C)
13
C enrichment in four
BV173 FFAs following adipocyte co-culture for
0, 6, 24 or 48 hours. Palmitate (C16:0, black
solid), stearate (C18:0, black dotted),
palmitoleic (C16:1, red solid) and oleic (C18:1,
red dotted). Values are derived from average
peak intensity for each FFA over 4 samplings.
(**=p<0.01; ***=p<0.005)
14

reduces expression of ALL lipogenesis enzymes.(Fig 2.5B) Similarity in the downregulation of ALL
lipogenesis in response to oleic acid and adipocytes lends further support to the specificity of
unsaturated FFA uptake seen in Figure 2.4C.
TOFA (5-(Tetradecyloxy)-2-furoic acid) is a competitive inhibitor of ACC1 and SCD1 and is cytotoxic to
BV173 cells in high doses, highlighting the importance of de novo lipogenesis in lipid-depleted media.(Fig
2.5D) However, TOFA cytotoxicity is diminished when exogenous FFAs are added back to the culture
media.(Fig 2.5C) BV173 proliferation is better restored by exogenous oleic acid than palmitic acid, due to
circumvention of the SCD1 inhibition by TOFA. FFAs found naturally bound to albumin also restore cell
proliferation. Additionally, BV173 co-culture over adipocytes offers significant protection from TOFA
cytotoxicity (At 2μg/mL TOFA, BV173 over Adipo: 2.62 ± 0.55 fold growth vs. BV173 over Fibro: 0.70 ±
0.18 fold growth; p<0.05; n=3). Similar restorative effects were seen following co-culture of BV173s with
adipocyte conditioned media (ACM) and adipocyte and leukemia conditioned media (ALCM), both which
contain exogenous lipids.(Fig 2.5E)

Figure 2.5 – De novo lipogenesis in ALL cells
co-cultured with adipocytes A) Diagram of
de novo lipogenesis pathway. Key enzymes
in the pathway are bolded. ACC1: Acetyl-CoA
Carboxylase 1; FASN: Fatty Acid Synthase;
SCD1: Steroyl-CoA Desaturase. TOFA is a
reversible, competitive inhibitor of both
ACC1 and SCD1. B) BV173 gene expression of
FASN, ACC1 and SCD1 following culture in
200μM exogenous FFAs (left) or co-culture
with fibroblasts or adipocytes for 72 hours.
Each gene is normalized to beta-actin before
normalization to “No FFA” or “No Feeder”
conditions. (*=p<0.05; **=p<0.01;
***=p<0.005; n=4) C) TOFA inhibition of
BV173 proliferation in exogenous FFAs.
BV173 cells were cultured in serum-free
complete media supplemented with 1% BSA
or 200μM FFAs and 2μg/mL TOFA for 72
hours. Cell counts were determined by
trypan blue exclusion. (n=1) D) TOFA
inhibition of BV173 proliferation during co-
culture. BV173 cells were cultured in serum-
free complete media over no feeder (N),
fibroblasts (F) or adipocytes (A) 2μg/mL
TOFA for 72 hours. Cell counts were
determined by trypan blue exclusion and
normalized to number of initial cells plated.
T-test between N and F/A: *=p<0.05;
**=p<0.01; ***=p<0.005. T-test between F
and A: †=p<0.05; †††=p<0.005.
n=3/condition and dose. E) TOFA inhibition
of BV173 proliferation in adipocyte
conditioned media. ACM: adipocyte
conditioned media. ALCM: adipocyte and
leukemia conditioned media. Cell counts
were determined by trypan blue exclusion.
(*=p<0.05; **=p<0.01; ***=p<0.005; n=3)
15

2.2.6 ALL utilization of adipocyte-derived FFAs for energy
Cancer cells can utilize FFAs for energy production by mitochondrial beta-oxidation.(54,55) To
understand if ALL uses adipocyte-derived FFAs for energy, we measured changes in mitochondrial
markers of beta-oxidation. The rate limiting step of beta-oxidation is the conjugation to carnitine and
subsequent shuttling of FFAs into the mitochondria by carnitine-palmitoyl transferase 1a (CPT1a).(Fig
2.6A) BV173 gene expression of CPT1a was upregulated two-fold 72 hours following the addition of
200μM palmitic or oleic acid.(Fig 2.6B, right) Adipocyte co-culture also increased BV173 CPT1a gene
expression 50% compared to co-culture with no feeder (p=0.018; n=4).(Fig 2.6B, left) Interestingly, co-
culture over fibroblasts also increased BV173 CPT1a gene expression (p=0.045; n=4), yet protein
expression was unaltered.(Fig 2.6C, right) Palmitic acid, oleic acid and adipocyte co-culture all similarly
increased protein expression of CPT1a. (p=0.0014; p=0.0345; p=0.030, respectively; n=3/condition)
We also assessed changes in pyruvate dehydrogenase (PDH) activation as an indirect measure of FFA
metabolic flux into the TCA cycle. PDH regulates pyruvate conversion into acetyl-CoA within the
mitochondrial matrix prior to entry into the TCA cycle and downstream oxidative phosphorylation.(Fig
2.6A) Phosphorylation of PDH by pyruvate dehydrogenase kinase (PDK) inactivates PDH and glucose
oxidation. Additionally, the acetyl-CoA and NADH formed from FFA catabolism inhibit PDH activity,
shutting down glucose utilization when fatty acid oxidation is underway.(138) BV173 cells co-cultured
over adipocytes exhibit a 4-fold increase in PDH phosphorylation compared to BV173 cells alone
(p=0.0026; n=3), suggesting an adipocyte-induced shift from glucose oxidation to FFA oxidation.(Fig 2.6D)
16

2.3 Discussion
Since the publishing of the “Warburg Effect” in 1956, a large portion of cancer research has been
devoted to the understanding of glucose metabolism in cancer cells. Yet, cells maintain metabolic
plasticity that allows a shift toward fatty acid metabolism in times of energy demand, cellular stress or
glucose depletion.(138–140) FFAs are also needed by cancer cells during proliferation to synthesize the
phospholipids necessary to comprise daughter cell membranes. This heavy demand for lipids is likely the
reason why many cancers are associated with upregulation of de novo lipogenesis.(63,64,67,70) To cope
with this demand, cancer cells can supplement endogenous production with uptake of exogenous
lipids.(73,78)
In this chapter, we show that ALL cells exhibit a similar metabolic plasticity and preference for
exogenous lipids when in the presence of neighboring adipocytes. First, ALL cells, partially through the
Figure 2.6 – ALL beta-oxidation in response to FFAs
and adipocytes A) Diagram of FFA mitochondrial
beta-oxidation. Key enzymes in the pathway are in
pink circles. Metabolites in blue are part of glucose
oxidation pathway. Metabolites of FFA oxidation are
in red. B) BV173 gene expression of CPT1a following
culture in 200μM exogenous FFAs (left) or co-culture
with fibroblasts or adipocytes for 72 hours. CPT1a is
normalized to beta-actin before normalization to
“No FFA” or “No Feeder” conditions. F=Fibroblast
feeder layer; A = Adipocyte feeder layer. (*=p<0.05;
***=p<0.005; n=4) C) BV173 protein expression of
CPT1a following culture in 200μM exogenous FFAs
(left) or co-culture with fibroblasts or adipocytes for
72 hours. CPT1a is normalized to GAPDH before
normalization to “No FFA” or “No Feeder”
conditions. (*=p<0.05; ***=p<0.005; n=3) D) BV173
protein expression of PDH phosphorylation, as
measured by Western blot. Ratio of phospho-PDH to
total PDH was measured by densitometric analysis of
Western blots. (n=3/condition; *=p<0.05, **=p<0.01)
17

secretion of TNFα, induce adipocyte lipolysis and release of FFAs into the cancer microenvironment. This
phenomenon is specific to leukemic B cells as normal B cells do not induce a response in adipocytes.
Using fluorescently-labeled FFAs, the translocation of adipocyte-derived FFAs into ALL phospholipids and
triglyceride-laden lipid droplets was visualized. Triglyceride-laden lipid droplets have been shown to
exist in breast and ovarian cancer cells following exposure to exogenous lipids, but never before in ALL
to our knowledge.(73,141) We utilized stable-isotope lipidomics to identify the FFAs being transferred
from adipocytes, detecting a preferential translocation of unsaturated FFAs over saturated FFAs. These
adipocyte-derived unsaturated FFAs were determined to be capable of downregulating ALL de novo
lipogenesis and restored proliferation when this pathway was inhibited. The limited reliance of ALL on
de novo lipogenesis in the presence of adipocyte underscores the limited efficacy of lipogenesis
inhibition. Finally by assessing mitochondrial markers of metabolism, we demonstrated that ALL cells
respond to adipocyte-derived FFAs by upregulating FFA shunting into the mitochondria and favor fatty
acid beta-oxidation over glucose oxidation.
Adipocytes are known to promote the progression of solid tumors and hematological malignancies. As
part of the tumor microenvironment, their close interaction with cancer cells provides the metabolites
necessary for growth and survival. In breast cancer, inflammatory mediators induce modification of
adipocytes into cancer-associated adipocytes that display similar lipid loss.(142) These cancer-associated
adipocytes have also been shown to switch to a glycolytic phenotype, releasing amino acids, ketones
and lipids for use in cancer cell oxidative metabolism, a process deemed the “reverse Warburg
effect.”(133) Our previous research has demonstrated the ability of adipocytes to release asparagine
and glutamine and now FFAs into the microenvironment for use in ALL metabolism and survival.(46)
Thus, it is likely ALL cells induce a similar phenotypic change toward cancer-associated adipocytes.
Preventing this phenotype switch could potentially limit the release of these vital metabolites and
negate the negative effect of obesity on ALL treatment efficacy.
Based on our findings, multiple potential targets exist to reverse the effect of adipocytes on ALL lipid
metabolism. Adipocyte lipolysis, and conversion into cancer-associated adipocytes, is mediated in part
by inflammatory cytokines with the tumor microenvironment. This adipose tissue inflammation is
already present in obesity and can contribute to carcinogenesis and cancer proliferation.(39,40)
Reducing inflammation within the tumor microenvironment with clinically available antibodies, such as
infliximab, could reverse adipocyte lipolysis and overall stromal support for cancer. Two preclinical
studies have demonstrated a role for TNF inhibition in suppressing breast cancer growth and
metastasis.(143,144) Alternatively, targeting ALL lipid metabolism can prevent the utilization of
adipocyte-derived FFAs. The upregulation of CPT1a and metabolic shift toward FFA oxidation in ALL cells
exposed to adipocytes suggests a preference for utilization of exogenous fuel sources, possibly freeing
glucose metabolites for other anabolic pathways such as nucleotide synthesis. Exposure to etomoxir, a
CPT1a inhibitor, could prevent the shuttling of adipocyte-derived FFAs toward beta-oxidation and
negate FFAs as a fuel source during times of stress. In fact, etomoxir induces cell cycle arrest and
apoptosis in multiple myeloma, AML and glioblastoma cell lines.(55,56,145)
Despite these findings, there is little evidence of the direct translocation of adipocyte-derived FFAs
within the ALL tumor microenvironment in vivo. The use of fluorescently- or
13
C-labeled fatty acids can
be translated into existing mouse models of ALL to verify and identify lipid translocation in both bone
marrow and adipose tissue niches. The identification of adipocyte-induced changes in the ALL lipidome
can lead to new prognostic biomarkers or treatment strategies, potentially opening the use of available
obesity-fighting drugs as adjuvants to chemotherapy.

18

Chapter 3:
Caloric and dietary fat restriction during chemotherapy improves survival in obese
mice with ALL
3.1 Introduction

The utility of dieting to address obesity has been long established. Recent research has also provided
evidence that the effects of dieting extend to prolonging lifespan, reducing oxidative stress and
bolstering immunity.(148,149) Dietary restriction exerts these effects in part by reducing insulin-like
growth factor 1 (IGF-1), a stimulator of cellular metabolism and activator of the PI3K/Akt/mTOR
axis.(150) Non-transformed cells respond to this low nutrient state by downregulating mTOR activity
and entering a state of quiescence.(151) However, cancer cells often contain mutations within this axis
causing constitutive activation of PI3K/Akt/mTOR. This constitutive activation cannot be modulated by
nutrient restriction.(152) This phenomenon has been deemed “differential stress resistance.” In the
presence of chemotherapy, dietary restriction causes a selective reduction in normal cell but not cancer
cell proliferation and metabolism, and thus, allowing better selectivity of replication-targeting
chemotherapeutics.(120)
Following this hypothesis, multiple studies have been performed testing the potential of dieting to
augment chemotherapy. Carbohydrate restriction limited carcinoma and breast cancer growth in mice,
partial reduction in caloric intake reduced breast cancer aggressiveness, and a 48 hour starvation
improved etoposide efficacy against neuroblastoma.(121–123) In our murine models, we have
previously shown that obesity impairs vincristine efficacy.(153) Here, we hypothesize that dietary
restriction during vincristine treatment will not only reverse obesity but also improve vincristine efficacy
against ALL in obese mouse models.

3.2 Results
3.2.1 Calorie and fat restriction improves vincristine efficacy in obese leukemic mice
We first tested whether dietary restriction improves chemotherapy efficacy in a previously established
diet-induced obese (DIO) leukemic murine model. At 3 weeks of age, C57BL/6J mice (obese) were
weaned onto a commercially-available 60% calories from fat diet. A separate cohort of mice (lean) was
weaned onto a 10% calories from fat control diet. After 20 weeks of age, the mice were implanted with
10,000 syngeneic 8093 ALL cells. After a 6 day engraftment period, half of the obese mice were switched
to the 10% control diet (obese dieted), while the remaining mice stayed on their respective diets. One
day later, mice began vincristine therapy (0.5mg/kg/week i.p. x 4 weeks).
Four months following implantation, survival of obese dieted mice was drastically improved over their
obese and lean counterparts (Obese dieted: 91.7%; Obese: 8.3%; Lean: 25%; n=12/group; p<0.0001).(Fig
3.1A) After the first week of diet restriction and vincristine, obese dieted mice lost 20.4% body weight
and 22.9% after the second week.(Fig 3.1B) Obese dieted mice maintained this weight loss for the
duration of the treatment. Food intake of each group of mice was measured on the day prior to the
dietary intervention, as well as 1, 3 and 6 days following the diet switch.(Fig 3.1C) Fat and protein intake
decreased in obese dieted mice upon intervention, while carbohydrate remained unchanged. Obese
19

dieted mouse caloric intake was reduced by about 75% in the day following the diet switch and
measured about half of the caloric intake of the lean controls. Obese mice had the greatest intake of
calories, fat and protein.

3.2.2 Dietary restriction does not improve efficacy of other chemotherapies
Using the same murine model of obesity and ALL, we evaluated the effect of dietary restriction on two
other chemotherapies given during Induction therapy, L-asparaginase and dexamethasone. Unlike
vincristine, a microtubule inhibitor and direct effector of cell replication, L-asparaginase and
dexamethasone exert their anti-leukemic activity independent of cell replication. L-asparginase breaks
Figure 3.1 – Dietary restriction improves obese leukemic mouse survival after
vincristine treatment A) Survival curve of lean, obese and obese dieted mice with 8093
ALL. Vehicle mice were equally comprised of obese, obese dieted and lean mice and were
treated with saline. Vincristine was dosed on days shaded in gray. (n=12/group;
***=p<0.005 by log-rank test) B) Periodic weight measurements of obese (red), obese
dieted (blue) and lean (black) mice. (n=12/group) C) Dietary intake measurements in mice
one day prior (-1), 1, 3 and 6 days after the diet switch. Fat, protein and carbohydrate
intake were calculated by multiplying total caloric intake by the percentage of each
nutrient in either the high or low fat food. Black: lean; Red = obese; Blue = obese dieted
(n=12/timepoint)
20

down asparagine, an essential amino acid for leukemia cell growth. Dexamethasone, a glucocorticoid,
induces ALL apoptosis through the downregulation of anti-apoptotic Bcl-2 family proteins.(154)
Obese dieted mice treated with dexamethasone (4mg/kg/day i.p. x 5 days/week x 4 weeks) did not
exhibit any significant alteration in survival, compared to their lean and obese counterparts.(Fig 3.2A)
The dietary restriction combined with either dexamethasone had the same effect on weight loss as in
combination with vincristine.(Fig 3.2B) Weight loss in the obese dieted group during the first week of
dexamethasone treatment coincides with reduced caloric intake.(Fig 3.2C) Similarly, there was no
difference in survival among the three groups when L-asparaginase (800IU/kg/day i.p. x 5 days/week x 4
weeks) was given.(Fig 3.2D) Obese dieted mice receiving L-asparaginase lost similar levels of body
weight; however, mouse weights of all groups dropped in the third week of treatment due to leukemia
progression.(Fig 3.2E) Dexamethasone, an appetite stimulant, did not appreciably increase food intake
compared to mice receiving L-asparginase, which was similarly limited in the first week of treatment.(Fig
3.2F) Food intake normalized to levels similar to non-dieted mice in the second week of treatment,
when weight loss began to slow.

3.2.3 Dietary restriction does not improve chemotherapy efficacy in a humanized murine model of ALL
To test the efficacy of dietary intervention in a more clinically translatable model, we utilized NOD-scid-
IL2Rγ
-/-
(NSG) mice which lack viable B, T and NK cells due to mutations in adaptive immune cell
development. Selective culling, delayed weaning and a high fat diet promote diet-induced obesity, albeit
Figure 3.2 – Dietary restriction does not improve survival with other chemotherapies A) Survival curve of lean, obese and
obese dieted mice with 8093 ALL. Dexamethasone was dosed on days shaded in gray. (n=6/group) B,C) Periodic weight and
food intake measurements of obese, obese dieted and lean mice receiving dexamethasone. (n=6/group) D) Survival curve
with L-asparaginase treated mice. (n=6/group) E,F) Periodic weight and food intake measurements of obese, obese dieted
and lean mice receiving L-asparaginase. (n=6/group)
21

to a lesser degree than C57BL/6J. However, these mice permit the implantation and engraftment of
primary human ALL for study. Here, we intravenously implanted 50,000 LAX7 (human primary ALL) cells
and allowed engraftment for 16 days. On day 16, half of the obese mice were switched onto the 10%
calories from fat diet, while the other obese and lean mice maintained their respective diets. A clinically
relevant “triple therapy”, combining vincristine (0.5mg/kg/week i.p. x 4 weeks), dexamethasone
(8mg/kg/day i.p. x 5 days/week x 4 weeks) and L-asparginase (800IU/kg/day i.p. x 5 days/week x 4 weeks)
was initiated on day 17 (“VDL”).
Unlike C57BL/6J mice treated with vincristine, there was no difference in survival among the three
groups of leukemic NSG mice, each with a median survival between 74 and 76 days.(Fig 3.3A)
Furthermore, dietary restriction only produced a moderate weight loss in the first two weeks compared
to that seen in the C57BL/6J mice (NSG dieted: 16.3% weight loss; n=8 vs. C57 dieted: 22.9% weight loss;
n=12).(Fig 3.3B, 3.1B) Despite this, reduction in food intake in dieted NSG mice over the first week was
comparable to the C57BL/6J model.(Fig 3.3C)

3.2.4 Serum restriction improves vincristine efficacy in ALL cell lines
To understand whether differential stress resistance explains the synergistic effect of dietary restriction
and vincristine therapy in obese C57BL/6J mice, we recapitulated dietary restriction in an in vitro model
by limiting fetal bovine serum (FBS). Serum restriction has been previously shown to protect normal
cells but not cancer cells against cyclophosphamide.(120) Mimicking this, three ALL cell lines (8093,
Figure 3.3 – Dietary restriction does not improve obese leukemic NSG mouse survival with triple
chemotherapy A) Survival curve of lean, obese and obese dieted NSG mice with human LAX7 ALL.
Dietary restriction began on day 16. Vincristine + Dexamethasone + L-asparginase (“VDL”) began on day
17 and lasted 4 weeks. (Lean: n=5; Obese: n=6; Dieted: n=8) B,C) Periodic weight and food intake
measurements of obese, obese dieted and lean mice receiving VDL triple therapy.
22

BV173 and Nalm6) were cultured in 5% or 10% FBS in complete media with increasing doses of
vincristine for 72 hours. Culturing in 5% FBS significantly reduced the EC
50
of vincristine in both 8093
(Vincristine EC
50
: 8093 w/ 5% FBS – 58.7 ± 2.4 nM vs. 8093 w/ 10% FBS – 97.9 ± 3.5 nM; p<0.0001; n=4)
and Nalm6 (Vincristine EC
50
: Nalm6 w/ 5% FBS – 8.8 ± 2.7 nM vs. 8093 w/ 10% FBS – 16.9 ± 3.3 nM;
p=0.04; n=4).(Fig 3.4A,B) Serum restriction also slightly increased vincristine efficacy in BV173 cells,
albeit non-significantly.(Fig 3.4C)
Serum restriction experiments were also performed with these three cell lines in the presence of
dexamethasone and L-asparaginase. Serum restriction had no effect on the efficacy of either
chemotherapy in any cell line tested.(Data not shown) This model, coupled with the in vivo findings,
supports the hypothesis that a diet-induced reduction in growth factors synergistically improves
vincristine efficacy against ALL.

3.3 Discussion
IGF-1 plays a vital role in the maintenance of cell and tissue growth. During puberty, IGF-1 levels spike to
stimulate the rapid growth during this stage then decrease throughout life.(155) In response to IGF-1
receptor signaling, normal cells activate the PI3K/Akt/mTOR pathway, stimulating downstream anabolic
processes. In the absence of IGF-1, cells instead arrest activity and enter a state of quiescence. However,
obesity and insulin resistance can disturb IGF-1 regulation, allowing for sustained increases in free IGF-1
and subsequent cell growth.(156) In a murine mammary tumor model, diet-induced obesity increases
Figure 3.4 – Effect of serum restriction on
vincristine efficacy in ALL cell lines
Seven-point dose response curves of
vincristine against 8093 (A), Nalm6 (B), and
BV173 (C) cells cultured in complete media
with 10% (black) or 5% (grey) FBS. Viability
was assessed by trypan blue exclusion.
Curves are semi-log fit. Mean EC
50
values are
derived from the dose curves of 4
independent tests per condition. (*=p<0.05;
***=p<0.005; n=4/condition)
23

IGF-1 expression promoting tumor growth.(157) In the same study, caloric restriction lowered
circulating IGF-1 and reduced cancer progression. Yet, a number of cancers contain activating mutations
of IGF-1R, PI3K and Akt that render them less susceptible to fluctuations in growth factors.(152,158,159)
The differential stress resistance hypothesis relies on this inability of cancer cells to halt metabolism in
the face of growth factor depletion. Promoting differential stress through caloric restriction protects
normal cells from chemotoxicity while maximizing the efficacy against cancer cells with constitutively
active metabolic pathways.(160,161) Here, we demonstrate the ability of a calorie and dietary fat
restriction to enhance vincristine efficacy against ALL and improve mouse survival. Interestingly, this
effect was only seen with vincristine and not dexamethasone or L-asparaginase. This suggests a
specificity in chemotherapy for synergy with dietary restriction. Since vincristine directly inhibits cell
proliferation, unlike the other two drugs, differential stress resistance may only be efficacious with
inhibitors of replication. Other studies assessing differential stress resistance have shown similar synergy
with replication inhibitors like etoposide and cyclophosphamide.(161)
To better determine if differential stress resistance is responsible for increased vincristine efficacy,
metabolic studies on calorie restricted mice should be performed. Measuring IGF-1, insulin, growth
hormone and IGFBPs before and during dietary intervention will elucidate whether dietary modulation
of IGF-1 occurs. The differential stress resistance hypothesis is two-fold, predicting not only increased
chemotherapy efficacy, but also increased normal cell protection from chemotoxicity. Further studies
can test whether dieted mice can tolerate higher doses of chemotherapy. This is especially important
given that obesity alters vincristine pharmacokinetics.(49) With chemotherapies dosed based on body
size, obese patients often receive insufficient doses to due toxicity limits. These limits could be raised
with greater toleration of chemotherapy during dietary restriction.
One limitation of this study is that the dietary intervention reduced intake of multiple nutrients. In
addition to restricting total caloric intake, protein and fat intake were reduced, leaving carbohydrate
intake unchanged.(Fig 3.1C) Other studies have independently identified glucose restriction(120),
protein restriction(162) and fat restriction as all having anti-tumorigenic effects.(163) Individually
limiting one nutrient source while maintaining caloric balance could determine whether a certain diet is
best for patients undergoing chemotherapy. We have formed a collaboration with Dr. Valter Longo, who
initially published about the differential stress hypothesis, to address whether a low protein, low calorie
“fasting mimicking diet” synergizes with vincristine in the obese C57BL/6J model. With their expertise,
we will also be able to take a deeper look into the cellular mechanisms responsible for this phenomenon.
Continued studies will also focus on recapitulating these findings in a humanized mouse model of ALL.
While NSG mice are receptive of ALL xenografts, they are not as responsive to diet-induced obesity as
C57BL/6J. In addition, selective culling and intensive husbandry limit the number of mice available for
each study. Instead, our focus will shift to another immunocompromised murine model, Rag2
-/-
IL2Rγ
-/-
.
Due to mutations in immune cell recombination, these mice lack functional B, T and NK cells, akin to the
NSG model. However, these mice have been bred on the C57BL/6J background, which is more amiable
to diet-induced obesity. Repeating the experiments above with primary human ALL in these mice should
control for any confounding caused by differences in NSG metabolism.
Using an in vitro model of nutrient restriction, we showed that a reduction in FBS increases vincristine,
but not dexamethasone or L-asparginase, efficacy in three ALL cell lines. FBS is added to media during
cell culture to provide growth factors and stimulate proliferation. IGF-1 is found within fetal bovine
serum at concentrations around 100ng/mL.(164) When FBS is used at the typical 10% dilution, the
concentration of IGF-1 in culture media hovers around 10ng/mL. This is nearly 10-fold higher than IGF-1
24

serum levels in children between 2-12 years old.(165) Reducing FBS from 10% to 5% in media results in a
reduction of about 50ng/mL, a concentration still 5-times that in pediatric patients. A dietary
intervention in obese pediatric patients could reduce circulating IGF-1 to levels far below that in culture
media, potentially maximizing differential stress and improving patient outcome.
25

Chapter 4
3
:
Clinical Trial Protocol:
Improving Diet and Exercise in Acute Lymphoblastic Leukemia
(IDEAL Weight in ALL Trial)
4.1 Introduction
Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy with almost 2,000
children diagnosed per year in the United States alone. While 5-year event-free survival rates have
topped over 90% in the past decade, overweight and obese pediatric ALL patients have a 50% greater
risk of relapse than normal weight children. With about 1 in 6 US children being overweight or obese, it
is urgently necessary to combat the negative role of obesity on ALL treatment in the clinical setting.
In our previous study, we have observed that: 1) nearly half ALL patients are overweight or obese at
diagnosis, 2) all patients, regardless of starting weight, gain significant fat mass over the first month of
therapy (on average 20-30%), and 3) obesity at the time of diagnosis is associated with a higher
likelihood of poor response to chemotherapy as evidenced by persistent leukemia (minimal residual
disease) after induction therapy. Together, these data show that body fat is a significant risk factor for
ALL treatment failure, and that its negative effects are evident within the first month of treatment.
Recent laboratory and clinical data illustrates the ability of diet restriction and physical activity to
improve chemotherapy efficacy, reduce treatment-related toxicities and better overall quality of life.
However, to our knowledge, no clinical trial has demonstrated the efficacy of such a comprehensive,
integrative medicine approach to improve chemotherapy efficacy and quality of life in ALL patients
during intensive therapy, let alone any pediatric cancer population. Given the importance of successful
induction therapy in predicting long term survival and the negative role of obesity on treatment success,
we are proposing a complete personalized dietary and exercise intervention for pediatric ALL patients
that aims to reduce fat gained during induction therapy, thereby improving their treatment response
and also quality of life.

3
This chapter is a partial re-creation of the IRB-approval clinical trial protocol which I authored. I am a co-
investigator of the clinical trial conducted at CHLA. More information can be found at www.clinicaltrials.gov,
identifier: NCT02708108.
Figure 4.1 – Experimental Design Schema
26

4.2 Goals and Objectives
4.2.1 Hypothesis
In pre-adolescents, adolescents, and young adults (AYA) diagnosed with NCI/Rome High-Risk B-
precursor acute lymphoblastic leukemia (HR-ALL), reducing gains in adiposity (i.e. fat mass) will improve
leukemia sensitivity to induction chemotherapy, reduce post-induction minimal residual disease (MRD),
reduce fatigue and obesity-associated toxicities, and improve quality of life.
4.2.2 Primary Aim
In AYA patients newly diagnosed with HR-ALL, to quantify the impact of a personalized dietary and
activity intervention to mitigate chemotherapy-induced body fat gain throughout the critical first month
of treatment ("induction").
4.2.3 Secondary Aims
In AYA subjects newly diagnosed with HR-ALL:
1. To compare the rate of leukemia “positive” minimal residual disease (MRD) in the bone
marrow at end of induction (≥0.01% mononuclear cells) in those who received the intervention
as compared to a historical controls.

2. To assess adherence to, and feasibility of, implementing a personalized and comprehensive
dietary and exercise intervention during the first month of intensive chemotherapy
4.2.4 Exploratory Aims
In AYA subjects newly diagnosed with HR-ALL:
1. To evaluate persistence or extinguishing of this effect over months of continued dose-intensive
pre-Maintenance phases of chemotherapy
2. To characterize the direct impact as compared to baseline of the intervention on self- and
family- reported quality of life (QOL) outcomes including fatigue, mood, social interaction, and
cognitive impairment reported via the PedsQL questionnaire and Child and Adolescent Scale of
Participation (CASP) following the induction phase and serially during dose-intensive phases of
chemotherapy.
3. To quantify the effect of adiposity on the activity of leukemogenic JAK2/STAT3,
PIK3K/AKT/mTOR, and MAPK/ERK signaling pathways in leukemia cells as determined by kinase
phosphorylation.
4. To quantify the effect of adiposity and of the intervention on the metabolic activity of leukemia
blasts and of adipocytes as assessed by IGF-1 signaling and obesity-associated cytokines,
adiponectin, leptin, free fatty acid synthesis and metabolism, and levels oxidative stress.

27

4.3 Background and Significance
4.3.1 Fat mass and ALL
Obesity increases the incidence of many cancer types, and obese cancer patients have a higher risk of
mortality from their disease.(23) In 2007, a landmark study in the Children’s Oncology Group (COG) led
by Dr. Butturini from the Children’s Hospital Los Angeles (CHLA) demonstrated in two large cohorts
(4,314 and 1,160 patients) that obesity at the time of diagnosis increases risk of relapse in children with
National Cancer Institute/Rome High-Risk B-precursor ALL (HR-ALL) by 50% (19), a finding independently
confirmed in a different population of children (24) in obese adults (25), and by meta-analysis (166). In a
recent study, 36% of children with ALL were overweight or obese at diagnosis (29), while in another
cohort 23% of children with HR-ALL continued to be obese throughout therapy.(31) In our earlier cohort
of adolescent and young adults with HR-ALL treated at CHLA, we found an even higher prevalence of
high body fat whereas 48% were overweight or obese at diagnosis. Our data also showed that all
individuals – both those lean and those obese- gain a significant amount of adipose tissue during the
first month of treatment alone (“induction”). On average, patients gained ~20-30% of fat above their
starting body fat percentage. The use of glucocorticoids such as dexamethasone and prednisone during
induction therapy likely contribute to this fat gain, as they stimulate adipogenesis and appetite.
Predisposition to inactivity due to intensive leukemia treatment combined with steroid-induced dietary
derangements are therefore likely moderating factors of this marked gain in body fat. As response to
leukemia treatment in the first month of therapy is a key determinant of overall prognosis and risk for
relapse, and as obesity and body fat are risks factors for relapse, an intervention aimed at reducing the
gain in body fat has potential to improve leukemia therapy efficacy starting from the initial time of
diagnosis.
4.3.2 Dieting, activity and cancer
The concept of introducing caloric restriction in animal cancer models has been explored throughout the
last century.(119) Recent experiments have focused on the theory of “differential stress resistance,” a
diet restrictive metabolic state that increases normal tissue, but not cancer cell, tolerance to
chemotherapy.(120) During carcinogenesis, cancer cells acquire mutations to various metabolic
oncogenes, such as Akt and Ras, which allow uncontrolled proliferation. During dietary restriction and
the subsequent lack of nutrients and growth factors, normal cells down-regulate their metabolic activity
while cancer cells maintain their elevated metabolic state, a condition that promotes greater
chemotherapy specificity toward cancer cells. This was demonstrated in a transgenic mice with human
neuroblastoma fasted for 48 hours prior to etoposide treatment. The fasted mice not only survived
longer than non-fasted mice but also suffered less drug-induced toxicity (121).
While such a severe starvation diet is not feasible in the clinical setting, altering dietary composition
and/or reducing caloric intake is sufficient to see similar results. In a murine prostate cancer model, mice
fed with either a low-fat or no-carbohydrate diet had significantly reduced tumor growth compared to
mice on a “Western” diet.(122) Similarly, a low carbohydrate, high protein, isocaloric diet limited
squamous cell carcinoma and breast cancer growth in mice.(122) Even restricting total caloric intake
during treatment by 30% regardless of dietary makeup reduced breast tumor aggressiveness and
tumoral fat content.(123) Our own preliminary research (described below) has demonstrated a similar
effect of caloric and fat restriction on reducing weight and improving survival of obese mice with ALL.
Physical activity during therapy has also been shown efficacious to augment cancer sensitivity. Mice that
were allowed to run on a wheel had slower breast tumor growth and improved immune function
28

compared to non-exercised mice.(124) Furthermore, the amount of running inversely correlated with
the size of the tumor. Similarly, serum from men who exercise for one hour prevented prostate cancer
growth in vitro compared to cells in serum from non-exercising men.(125) Despite this history and the
breadth of research into diet and exercise interventions as adjuvants to chemotherapy, the translation
of these laboratory findings into the clinical setting has remained a barrier.
Diet and exercise have concrete benefits in addition to potentially augmenting chemotherapy efficacy.
Multiple clinical trials conducted in the last ten years have demonstrated the ability of diet and/or
exercise to prevent chemotherapy-associated fat gain, reduce fatigue and improve emotional well-being
in adults with solid tissue and hematological cancers.(126–128) Furthermore, the American Cancer
Society has recommended that proper nutrition and physical activity play a role in all phases of cancer
treatment.(129)
4.3.3 Diet and activity interventions for obesity
With 16.9% of 2-19 year olds being obese (20) and at risk for serious co-morbidities (167), there is a
necessity for effective obesity-targeted pediatric interventions. While many interventions have long
existed for obese adults, their efficacy in obese children has only begun to be explored recently. Obese
children without cancer randomized to an intervention prescribing 90 minutes of moderate exercise
three times per week, a hypocaloric diet, and weekly meetings with a dietician had a lower BMI, body
fat percentage and LDL cholesterol level than children receiving only individual diet or exercise.(168)
Similarly, a 16 week low-carbohydrate plus aerobic and strength training intervention proved more
effective in reducing BMI, body fat and fasting glucose compared to diet or exercise alone.(169)
4.3.4 Quality of life during ALL therapy
As the treatment for ALL has become more successful, the assessment and improvement of patient QOL
are becoming the focus for new studies and treatment modalities. To date, multiple assessment tools
have been developed to assess QOL in the pediatric cancer population. One such tool, the Pediatric
Quality of Life Inventory (PedsQL), in conjunction with the PedsQL 3.0 Fatigue Module, has been shown
to be particularly effective in assessing physical, emotional and social functioning, fatigue, pain, nausea,
anxiety and cognitive problems among others.(170)
Using this assessment tool, it has been shown that children actively undergoing chemotherapy have a
lower QOL than healthy children (171) or even those 1 year removed from chemotherapy.(172)
Additionally, researchers have measured the changes in patient QOL over the course of ALL therapy. In
patients with SR-ALL or HR-ALL, nausea, procedural and treatment anxiety and worry were worse during
induction compared to maintenance therapy.(173) Another similar study demonstrated a lower health-
related QOL in patients in induction therapy compared to all other phases of treatment.(174)
Little research has been performed to analyze the effect of physical activity on QOL in ALL patients
undergoing chemotherapy. One randomized trial demonstrated improved QOL in pediatric cancer
patients, including those with ALL, who participated in physical activity sessions during
hospitalization.(175) In adolescent survivors of ALL, leisure-time physical activity was also associated
with improved QOL.(176) Greater research is needed to better understand the ability of physical activity,
and dietary intervention, to improve patient QOL during and after chemotherapy.

29

Figure 4.3 - BMI percentile and MRD positivity (≥0.01%).
4.3.5 Study significance
To our best knowledge, no clinical study has reported the effect of a combined diet and activity program
as an adjuvant to chemotherapy in overweight and obese pediatric patients with any cancer diagnosis.
However, with the combined expertise of our integrative medicine team of dieticians, physical
therapists, oncologists and endocrinologists, we are confident that a comprehensive obesity-targeted
intervention will reduce fat gain and lean muscle loss to improve treatment efficacy and QOL during
therapy. The intervention will have the added benefit of promoting healthier lifestyle choices
throughout the rest of treatment and into adulthood.
4.4 Preliminary Data
Obesity is a common problem in our patients with
ALL. In our cohort of adolescents with HR-ALL at
CHLA, 48% were overweight or obese at diagnosis.
Further, from the time of diagnosis to the end of the
induction phase, subjects had an ~25% increase in
body fat over these first 28 days of chemotherapy
alone (from 23.3±9.1% at time of diagnosis to
33.7±9.8% at end of induction, p<0.001, Fig. 4.2).
Even more striking, this gain in body fat pecentage
was present in the entire cohort regardless of
starting body composition.(Fig 4.2) Body fat then
increased even further, to a mean of 37.1±7.9% by the
end of Delayed Intensification, following
approximately seven months of intensive
chemotherapy (p<0.001, not shown).
Overall, this increase in body fat represents a gain of
5.2±4.9 kg of adipose tissue over the entire study
period. Given our findings that adipose tissue can
directly impair chemotherapy efficacy on ALL (46,153),
this gain in body fat during such the critical
chemotherapy dose-intensive treatment period is very
concerning.
Obesity impacts ALL survival within the first month of
treatment. Treatment for childhood ALL generally lasts
for 2-3 years. The first month of treatment (induction)
is intense including prolonged high doses of steroids,
and weekly chemotherapy, and frequent physician
visits. Response to induction therapy through clearance of leukemia from the bone marrow as measured
by flow cytometry and reported as “minimal residual disease” (MRD) is generally accepted as one of the
best predictors of long-term survival.(28) Given the association observed between obesity at diagnosis
and EFS (19), we examined whether weight status at diagnosis would increase the risk of residual
leukemia at the end of induction as measured by MRD. To do this, we retrospectively evaluated the
records of 198 children treated at CHLA for B-precursor ALL. We observed that MRD positivity (as
defined per COG by MRD with multicolor flow cytometry 0.01%) was increased in children who were
overweight or obese.(Fig 4.3) The strongest association was in obese patients, who had a statistically
Figure 4.2 - Body fat percentage measured by DXA
scan in 10-21 year old children at diagnosis and end
of induction. ***p<0.001
Diagnosis Day #29
0
20
40
60
***
Treatment Period
Body Fat (%)
30

Figure 4.4 - EFS per BMI during HR-ALL Therapy
and clinically significant higher risk of persistent MRD (Odds ratio 2.5, 95% CI 1.2 – 5.1, p = 0.014,
adjusted for NCI risk group and validated leukemia risk factors) but with increased risk present in the
overweight too (OR 1.37, p=0.046 for the three weight-
group analysis). Evaluation of BMI percentile as a
continuous variable further confirmed increased
prevalence beginning in the overweight range.(Fig 4.3)
Thus, the effect of overweight and obesity to worsen EFS
is present during Induction.
The effects of obesity are reversible. As weight is not
static during ALL therapy (31), we recently evaluated the
effect of duration of exposure to extreme weight on
survival (Fig 4.4, (147)). In a restrospective COG study led
by Orgel et. al., in 2,008 children with HR-ALL, we
determined that while children who were obese for greater than 50% of the early intensive
chemotherapy phase had a poorer event free survival (HR of event = 1.43 [1.04-1.96] compared to those
of “normal” weight), obese children whose weight normalized out of the obese range for more than 50%
of the time of early intensive therapy had an improved outcome similar to those never obese (HR = 0.99
[0.62-1.58]). These data suggest the effect of obesity might be reversible.
To address this important question, we designed experiments to determine whether or not dietary
intervention that was initiated when leukemia is diagnosed could improve outcome. Diet-induced obese
(DIO) mice and matched controls were transplanted with ALL cells and chemotherapy with vincristine
(VCR) was initiated 7 days after transplant, as previously described.(153) At this point, half of the obese
mice were switched to a low (10%) fat diet. Thus, this experiment simulated the clinical condition in
which a dietary intervention could be initiated at the time of diagnosis, namely at the same time that
chemotherapy would be started. Remarkably, obese mice switched to a low fat diet had a substantially
improved survival compared to the non-switched animals (p<0.001), and even survived longer than
controls that had been raised on the low fat diet. (p<0.01, Fig 3.1A) Thus, switching mice from high fat to
low fat diet when treatment is started substantially improves leukemia survival.
Obesity increases toxicity. As part of the same COG desribed above (147), we also evaluated obesity as
an ongoing risk for toxicity. In doing so, we found a striking effect of obesity on toxicity within each
phase of pediatric ALL chemotherapy for children with HR-ALL: in 2,008 children (representing 13,946
cycles of chemotherapy), obesity was associated with increases in hepatic (OR = 1.32 [1.15-1.51],
p<0.001) and pancreatic (OR = 1.53 [1.22-1.92], p<0.001) toxicity within each cycle of chemotherapy as
compared to lean or underweight children. Toxicity affecting the liver and pancreas are specifically
notable in ALL regimens as they limit our ability to deliver optimal dosing of chemotherapy. Of note, and
germane to the secondary objectives of this proposal, obese children also suffered from reduced
strength during therapy (OR = 1.33 [1.08-1.64], p<0.001) as compared to those lean/underweight.
Healthy reduction in body fat therefore has significant potential to not only improve survival, but to
reduce key toxicities during ALL therapy.
Physical activity can be targeted in ALL. In a recent pilot study on preferences for physical activities and
engagement in children and adolescents with ALL, we assessed 37 patients ages 10-18 (68% male; 65%
Latino) using the Activity Preferences and Participation Scale (APPS), a newly developed measure
designed to identify activity preferences, activity frequency, and social engagement in activity. The tool
was administered on an iPad, and included perceptions of activity levels, self-reported changes in
31

activity levels since diagnosis, and perceived barriers to engaging in physical activity and the importance
of physical activity. Of the participants, 14 were in the induction/consolidation phase of treatment, 12 in
Maintenance, and 11 off- treatment. Forty percent of individuals in the sample were overweight or
obese. At all phases of treatment, participants strongly preferred and participated in sedentary activities.
There was a high correlation between activity preference and activity participation in moderate-
vigorous activities. Of particular relevance to the present study is that more than half of the participants
in the induction/consolidation phase stated that fatigue, poor balance or weakness, and energy levels
were barriers to participation in physical activity, while approximately 1/3
rd
reported that feeling sick or
nauseated was a barrier. Most participants reported being less physically active since they were
diagnosed with ALL, with the greatest declines reported in the induction/onsolidation (100%). All
participants reported that they would like to be more physically active. As would be anticipated,
induction chemotherapy fosters a non-active lifestyle; an integrative medicine intervention educating
subjects and families how to safely exercise is both urgently needed and desired by families.
4.5 Patient Criteria for Eligibility
The eligibility criteria listed below are to be interpreted literally. All clinical and laboratory data required
for determining eligibility of a patient enrolled on this trial must be available in the patient’s medical and
research record which will serve as the source document for verification at the time of audit.
4.5.1 Inclusion criteria
Subjects:
a) Are greater than or equal to 10 years of age and less than or equal to 21 years of age at time of
diagnosis
b) Have a new diagnosis of untreated NCI/Rome High Risk B-precursor ALL (HR-ALL)
c) Are beginning treatment on- or as per- a CCG-COG protocol with a 4-drug Induction including
vincristine, daunorubicin (or doxorubicin), asparaginase, and at least 14 days of glucocorticoid
steroids
4.5.2 Exclusion criteria
Subjects cannot:
a) Have a diagnosis of Down syndrome (Trisomy 21) or any genetic disease associated with
abnormal body composition
b) Be underweight or “at risk for underweight” with moderate weight loss, defined as a starting
Body Mass Index (BMI) <10th percentile for age and sex (for those >20 years of age, defined as
an absolute BMI < 18.5)
c) Have pre-existing abnormal intestinal function (e.g. protein-wasting enteropathy, fat
malabsorption)
d) Be unable to comply with both the recommended diet and activity interventions (as determined
by study or treatment team)
32

e) Have a history of prior chemotherapy or radiation for other cancers
f) Be unable to complete the necessary radiology examinations with fully interpretable data (e.g.
hip replacement and metal prostheses preclude evaluation by DXA)
g) Be pregnant (to be confirmed by urine or serum pregnancy test as per institutional routine care
for chemotherapy and radiology exams)
4.5.3 Concomitant therapy
Patients may be receiving concurrent therapies including investigational agents for the treatment of
their underlying malignancy.
4.5.4 Co-enrollment on research studies
As per the Children’s Oncology Group (COG) standard practice, this study is a behavioral intervention
and does not include an investigational agent and is therefore not excluded from co-enrollment on COG
trials. Moreover, the study behavioral intervention occurs during a treatment period (induction) where
no COG or other research intervention is planned through the duration of this protocol. Of note, the
relevant COG trial AALL1131 specifically outlines multiple concomitant therapies that are excluded but
does not include behavioral interventions such as this one. For patient specimens, collection of samples
for research will be coordinated closely with the clinical leukemia team; should a conflict arise for
patient samples, priority will be first accorded to clinical care. Second priority will then be afforded to
COG studies required for co-enrollment on COG therapeutic trials. Following both these uses, remaining
sample will be obtained for this research study.
4.6 Study Plan
4.6.1 Summary of study plan
Pre-adolescent and AYA patients with newly diagnosed HR-ALL will have dietary and activity preferences
assessed by a registered dietician (RD) and physical therapist (PT) at the start of induction.
Subjects will receive an individualized comprehensive dietary and physical activity plan. The RD and PT
will devise a personalized dietary and activity intervention aimed at creating a minimum 10% caloric
deficit each day (10% nutritional + exercise) throughout the four weeks of induction therapy. Adherence
to the intervention will be assessed by the RD and PT at regular weekly intervals at routine clinic visits
for chemotherapy and with home phone-calls between clinic visits. For those subjects who are ≥13
years of age, home and hospital activity will also be recorded using a wearable electronic movement
monitoring device (Fitbit®). The primary efficacy of the intervention will be assessed in comparison to a
recent historical control via determining the change in body fat percentage (and lean muscle) during
induction as quantified by dual-energy x-ray absorptiometry (DXA). A key secondary aim will be the
effectiveness of the intervention to reduce chemoresistance as evidenced by decreased prevalence of
leukemia minimal residual disease (MRD) at the end of induction. MRD using multicolor flow cytometry
is routinely assessed as a predictor of outcome in all patients with HR-ALL. Exploratory analyses will also
examine biomarkers of the proposed mechanism including adiposity and intervention-related changes in
leukemogenic signaling pathways, oxidative stress, and cellular metabolism. Parent- and subject-
reported QOL assessments will consist of the PedsQL and Child and Adolescent Scale of Participation
(CASP) surveys and will be conducted pre- and post-induction and at two delayed time-points (mid-point
33

of intensive chemotherapy [3 months from diagnosis] and at end of intensive chemotherapy phase [10
months from diagnosis] to assess the psychosocial benefits of the intervention.
4.6.2 Treatment plan
4.6.2.1 Dietary intervention
The dietary intervention will be performed by an RD and is designed to achieve an at minimum ≥10%
daily caloric deficit to prevent fat gain along with a moderate fat (20-25%), high protein (20-25%), and
low glycemic index/high fiber carbohydrate (45-55%) nutritional plan to prevent loss of lean muscle
mass loss and to maintain micronutrient intake. The subject’s basal metabolic rate (BMR) will be
calculated using the Schofield equation as per the World Health Organization recommendations (World
Health Organization, Energy and Protein Requirements, Technical Report Series 724, 1985) with an
activity factor of 1.3 (“for a well-nourished child at bedrest with mild to moderate stress”) applied to
better estimate the subject’s resting energy expenditure (REE) from which to calculate the initial 10%
caloric deficit goal.
At the initial counseling session, the dietician and family will determine which dietary technique is most
likely to lead to dietary adherence. Dietary management tools will incorporate the My Plate (USDA) and
the Traffic Light Diet tools to help educate families regarding portion size and eating habits. The RD will
use a menu of common foods that meet the intake goals above as well as help families choose
“exchanges” on the menu to personalize the menu options to maximize adherence. During the initial
hospitalization, the RD will visit with the subject to assess caloric and nutrient intake using a 3-day food
intake log, counsel subjects and their families on nutrition and eating habits, and instruct how to
monitor food intake using a simplified log. If available, and if the family so desires, the option will be
available for families to use their personal cell phone or digital camera to take pictures of meals (before
consumption and after consumption) to email to the RD to help guide the dietary intervention.
During subsequent weekly outpatient chemotherapy clinic visits (or if the subject remains hospitalized),
the RD will follow-up with families on their perceived adherence and obtain intermittent dietary intake
via 24 hour diet histories. Between clinic visits, the RD will also contact the family to provide
reinforcement/motivation, answer questions, and obtain interval dietary history if necessary. Specific
dietary recommendations for foods/drinks, meals, and snacks will be adjusted weekly in discussion with
families to meet the daily caloric deficit and goal diet as described. The caloric goals may also be
adjusted ±5% depending on insufficient/excessive weight or body composition changes. At the end of
the acute intervention, the RD will discuss with the subject and family their dietary status and
sustainable healthy eating behaviors.
4.6.2.2 Physical activity intervention
The physical activity intervention will be performed by a PT who regularly works with children on
therapy for ALL as well as generally with pediatric oncology populations. The PT will meet the subject
and family surrounding the time of initial diagnosis. The PT will assess at baseline the subject’s usual
activity level, choices/preferences, and available activities at home once discharged. A key component
of this baseline assessment, and of beginning the exercise program during the initial hospitalization, will
be education provided to subjects and their families to allay concerns over potential muscle weakness
and/or fatigue and demonstrate with positive reinforcement how to exercise safely during leukemia
therapy. During the assessment, the subject’s “rate of perceived exertion” (RPE) will be assessed to gain
insight into the subject’s thresholds for exercise intensity.
34

A target of 200 minutes/week will be set for a combination of “moderate” cardiovascular exercise and
resistance training (177) with progressive goals based on adherence and capacity. As per latest
guidelines from the American Heart Association, this weekly target may be accomplished with a
minimum of 30minutes/day or divided into 15-minute sessions over the course of the day with the goal
of daily exercise. To quantify the prescribed “moderate” exercise, metabolic equivalents (METs) were
assigned to a variety of exercise modes from which the subject may choose, which best suit their
preference and home capabilities. While the goal exercise prescription in METs is uniform for the
intervention, the PT will work with the family and subject to outline an individual path to meet that goal
based on the subject’s physical capabilities, preference, and home availability. METs will be converted
to “points” and the subject will be able to choose from suggested exercise modes with the appropriate
number of minutes to meet daily and weekly “point” goals. Subjects will be asked if there are any
additional activities/exercises they would like to include. If so, these will be added and the “points”
(METs) calculated for them. Participants and their parents will be asked to record the selected mode
and number of minutes performed on a study log (or calendar) and weekly total scores will be tabulated
(METs-minutes). The exercise program will be progressive by nature such that the Daily Goal is increased
each week depending on adherence, ability, and clinical condition.
Subjects who are ≥13 years of age will also be provided a wearable electronic activity monitor (Fitbit®)
to assist in recording home activity levels in minutes of activity; the Fitbit® has the important secondary
benefit of providing visual reinforcement for the subject of their progress toward their Daily Goal as set
by the study team.
4.6.2.3 Motivational interviewing (Promotion of adherence to intervention)
To facilitate adherence to the dietary and behavioral changes above, motivational interviewing (MI)
techniques will be employed by the study team. MI is a patient-centered method for enhancing intrinsic
motivation to change health behavior by exploring and resolving ambivalence through the use of
empathetic, nonjudgmental, and supportive communication techniques.(178) Numerous studies have
illustrated the efficacy of MI as a promising strategy to encourage positive health behavior change (179),
including promoting health behavior change and weight loss in nutrition and exercise interventions in
children and adults (178,180). Specifically, MI has been used to promote diet and exercise in breast
cancer patients with some success.(181)
4.6.2.4 Integration of intervention into ALL therapy
While induction chemotherapy for pediatric ALL is a highly morbid and overwhelming time, the study
team has significant experience working both with this specific population as well as other populations
with high morbidity. While lifestyle changes in general are difficult to achieve, short-term changes are
generally more successful and patients and families in general are more receptive to short-term
achievable goals.
In this context, the 28 day intervention proposed here is purposefully designed to naturally integrate
into the four week induction phase beginning with the start of systemic chemotherapy. This phase
routinely includes an initial hospitalization followed by weekly clinic visits with the treating provider for
delivery of chemotherapy and evaluation of toxicity. The study intervention and assessments are
therefore formulated around this routine clinical schedule.
Subjects will be enrolled surrounding the time of initial diagnosis within 24 hours of starting systemic
chemotherapy. Children are routinely hospitalized for a minimum of four days from the start of
35

systemic chemotherapy. During this time, they will have their baseline DXA scan (within 96 hours from
start of systemic chemotherapy), the initial PT and RD assessments, and start with the supervised
activity intervention and diet intervention. Bedside nursing will be available to provide reinforcement
during that time. Following anticipated discharge, the subjects will be assessed at each weekly clinic
visit to have their diet and activity interventions monitored and adjusted as needed and also to receive
education/motivation from the psychosocial team. At the final clinic visit at the end of induction,
subjects will receive the post-intervention assessments along with additional motivation/education.
Subjects will then continue on chemotherapy per routine care with ~8-9 additional months of intensive
chemotherapy; subjects will receive PT, RD, and QOL assessments midway at the start of “interim
maintenance” and again at the final time-point at the start of the low-intensity maintenance phase.
These follow-up visits will help gauge whether the effect of the intervention and education extinguished
or persisted during the intervening post-intervention months.
4.6.3 Subject renumeration
While no payment is provided to subjects for participation, a Fitbit® will be provided to participants for
those ≥13 years of age, as part of the study assessments as indicated in the schema and described
further below. At the conclusion of the study’s follow-up portion, the subject will permitted to keep the
Fitbit® should they wish to do so.
4.7 Modifications of Intervention for Toxicity
4.7.1 Modification of activity intervention
Instances may arise throughout the course of induction therapy in which subjects may not be able to
adhere to the prescribed activity intervention due to complications from leukemia treatment. Initially,
attempts will be made by the PT to lower the intensity of the intervention until complications subside. If
treatment-toxicity is persistent or severe (i.e. subject in the PICU), the activity intervention will be
suspended until the subject is deemed to be able to resume the intervention by the PT in consultation
with the subject’s treatment team.
4.7.2 Modification of dietary intervention
Similarly, a subject may not be able to adhere to the nutrition intervention for reasons such as,
nausea/emesis or the treatment team determining the subject cannot receive liquids or food by mouth
(NPO). In such instances, the study team will continue to track all data at specified time-points and the
registered dietician will re-assess nutritional caloric goals. Moreover, for subjects at lower BMI
percentiles, despite the anticipated body fat gain, should the BMI percentile decrease to <5th percentile,
the subject will come off-therapy.
4.8 Required Observations
“At Diagnosis” blood samples should be collected before or in closest proximity as possible to starting
systemic chemotherapy (intrathecal therapy may have already been given), but all samples must be
collected before the start of the activity/nutrition intervention and within 24 hours of starting
systemic chemotherapy.
36

The DXA scan should be done in closest proximity to diagnosis as is feasible, but must be done within 96
hours from the beginning of steroid therapy and ideally before the start of the activity/nutrition
intervention.
The timing of the DXA scan in relation to chemotherapy and the intervention will be recorded.
STUDY MEASURE
Diagnosis
(Day 1)
Day 8
Day
15
Day
22
End
Induction
(Day 29)
Start
IM#1
Start
Maint
Patient History Clinical History
1
* X X X X X X X
Anthropo-
metrics
Height/Weight* X X X X X X X
Tricep skin folds X X X X X X X
Waist to hip ratio X X X X X X X
Clinical
Assessments

RD Assessment-
3 day food log
X X
RD Assessment-
24 hr recall
X X X X X X X
PT Assessment-
Complete BOT2
X X
PT Assessment- BOT2
–Brief
X X X X X
Fitbit Tracker
(for those ≥13 years)
Continuous from time of study entry until study end
Laboratory Tests
(blood)
Lipid Panel X X X X
Mittelman Labs
2
X X X X
Pregnancy Test* X X
Pathology Tests
Bone Marrow
Aspirate
3
*
X X
Biopsy Marrow
Biopsy
X* X
Radiology
Tests
DXA Scan

X X
4

Survey
Instruments
5
PedsQL - Core X X X X
PedsQL - Fatigue X X X X
CASP X X X X
*Indicates test per Standard of Care (SOC).
1
Clinical History includes any time NPO, any use of
nasogastrointestinal (NG) or nasojejunal (NJ) nutrition, any parenteral nutrition, any surgeries, any ICU
admissions, Grade 3 or 4 hepatic or pancreatic toxicity, presence of osteonecrosis or fracture.
2
Research
laboratories to include IGF-1 and obesity-related interleukins/signaling factors, leptin, adiponectin
3
In those with
circulating blasts, collection of pre-chemotherapy blasts from peripheral blood may be substituted if no aspirate
performed and absolute blast count >1000/uL.
4
End of induction scan to be done between days 29 and 36 of
therapy in as close proximity to day 29 as possible and prior to any subsequent systemic chemotherapy.
5
Available in Spanish and English; if subject does not speak either, will be administered in an assisted manner
using in-person or phone-based medical interpreters.

37

4.9 Statistical Considerations and Evaluation Criteria
4.9.1 Sample size and study duration
Based on available data over a recent 3-year period (2012-2014), we predict at least 43-45 subjects ≥10
years of age with HR-ALL patients will be eligible for enrollment during the three year study. We
anticipate >85% of subjects to be enrolled & evaluable for the primary and secondary aim surrounding
the Day 29 time-point, for an effective sample size of at least 36 subjects. As subjects historically gain
body fat during induction irrespective of starting body composition (i.e. both those lean and those
overweight/obese gain body fat), we will enroll a goal of 18 overweight/obese and 18 lean subjects on
the study to evaluate for an overall effect of the intervention, as well as a differential effect in those
“lean” by BMI percentile. We will continuously monitor accrual by weight category with a minimum
final target accrual of 14 overweight/obese and 22 lean subjects (40/60) which, as below, preserves our
ability to detect an effect on body fat and on the key secondary aim of MRD. For assessment of the
delayed endpoints, we expect that 80% of the initial cohort will additionally be evaluable for secondary
the aims at the final pre-start of maintenance time-point (due to treatment-related
morbidity/mortality/lost-to-follow-up).
4.9.2 Primary endpoint evaluation
The primary endpoint for efficacy is a reduction in gain of body fat percent (per DXA) from diagnosis to
the end of induction. From data on 36 patients from the historical cohort at CHLA with DXA scans pre
and post induction, there was a significant average fat gain during induction therapy of 5.5±3.3 percent
(mean ± s.d.), p<0.001. Based on a two-sample (36 historical, 36 present study) two-sided t-test with 5%
Type I error, there will be at least 90% power to detect a 2.5 percentage point reduction in change in
body fat as a result of intervention (e.g. from gain of 5.5 to a gain of 3.0%). Hence, this study has
sufficient power to detect subtle, achievable effects on body fat during induction, and will with certainty
detect stabilization of or a decrease in body fat during induction.
4.9.3 Secondary endpoints evaluation
To compare the rate of leukemia “positive” minimal residual disease (MRD) in the bone marrow at end
of induction (≥0.01% mononuclear cells) in those who received the intervention as compared to
historical controls.
The key secondary endpoint for efficacy is whether or not the bone marrow is “positive” for MRD at the
end of induction (using the COG definition of ≥0.01% mononuclear cells). From the retrospective study
at CHLA of B-precursor ALL/obesity and end-induction MRD, 69 patients in the cohort had HR-ALL over
the age of 10 at diagnosis. Of these, 53% of those overweight or obese (n=30) were MRD positive at the
end of induction as compared to only 26% of those lean at diagnosis (n=39). Using this cohort as the
historical comparison group, for the overweight/obese subset only, this study will have approximately
80% power to detect a reduction in the MRD positive rate to approximately that of the historical lean
group (i.e from 53% to 24%) based on a two-sample, one-sided test of proportions with a Type I error of
0.10 (as a commonly used “go/no go” threshold to continue to Phase III trials). For the overall cohort,
again in comparison to the historical cohort (MRD+ 38%, n=26/69) using a similar two-sample, one-sided
test of proportions, the study will have the ability at ~80% power to detect a decrease in MRD by 20%.
The study will therefore provide data on the potential reduction in the MRD positive rate that can be
38

expected in preparation for the subsequent randomized Phase III trial for efficacy. These analyses will
be adjusted for risk group, age, and other factors as appropriate and also compared to external
published rates for MRD positivity.
To assess adherence to, and feasibility of, implementing a personalized and comprehensive dietary and
exercise intervention during the first month of intensive chemotherapy
This endpoint will be reported as the proportion of study subjects who adhere to proposed dietary and
activity interventions. A threshold of 80% of RD and PT visits (combined, RD only, PT only) completed
will determine feasibility of incorporating the intervention itself into induction therapy. Adherence to
each component of the intervention will be further assessed using a threshold of 75% MET-minutes
prescribed/completed and 75% of dietary adherence prescribed/actual intake (overall, and to each
macronutrient group). Further exploratory analysis will examine which sets of activities and dietary
recommendations afforded the greatest level of adherence and any trends toward adherence by age,
sex, race, and/or ethnicity.
4.9.4 Exploratory endpoints evaluation
To evaluate persistence or extinguishing of this effect during continued dose-intensive phases of
chemotherapy
Reported continued adherence to activity and dietary recommendations will be evaluated by the RD and
PT as per last prescribed or recommended from the intervention versus actual minutes/dietary intake at
the delayed time-points of start of Interim Maintenance (~+3 months) and start of Maintenance (~+10
months). Activity and dietary intake patterns will also be compared to baseline at-diagnosis levels.
Similar exploratory analysis will examine the effect of age, sex, race, and/or ethnicity.
To characterize the direct impact as compared to baseline of the intervention on self- and family-
reported quality of life (QOL) outcomes including fatigue, mood, social interaction, and cognitive
impairment reported via the PedsQL questionnaire and Child and Adolescent Scale of Participation
(CASP) following the induction phase and serially during dose-intensive phases of chemotherapy
The PEDSQL questionnaire returns a QOL score between 0-100 for each patient at each time-point. The
CASP is scored as a percentage and then normalized to a 100 point score. Differences during therapy
will be compared using a two-sided, paired t-test during induction (the intervention) and using repeated
measures analysis for all four time-points.
To quantify the effect of adiposity at diagnosis on the activity of leukemogenic JAK2/STAT3,
PIK3K/AKT/mTOR, and MAPK/ERK signaling pathways in leukemia cells as determined by kinase
phosphorylation
Differences in levels of expression of the pathways will be analyzed according to body fat percentage
(adiposity) using a two-sided, two-sample t-test for the different pathways as well visually for overall
trends in related pathways.
To quantify the effect of adiposity and the intervention on the metabolic activity of leukemia blasts and
of adipocytes as assessed by IGF-1 signaling and obesity-associated cytokines, adiponectin, leptin, free
fatty acid synthesis and metabolism, and levels oxidative stress.
39

Exploratory analyses using similar t-tests will be performed to explore the effects of adiposity at
diagnosis on adipokines, obesity-associated cytokines, oxidative stress, and measures of cellular
metabolism. The effect of the intervention on oxidative stress and free fatty acid synthesis will be
analyzed using paired t-tests for pre/post intervention and compared to samples from the historical
cohort.
40

Chapter 5:
Concluding Remarks and Future Directions
5.1 Summary of Results
Whether in the bone marrow niche or in adipose tissue, ALL cells reside in close proximity to adipocytes.
Previously, our lab has demonstrated the benefit of such proximity for ALL cell survival. Adipocytes
provide ALL cells with asparagine and glutamine that supplement ALL cell growth and survival in the face
of L-asparaginase.(46) Adipocytes take up vincristine, limiting the effective concentration seen by ALL
cells.(49) Adipocytes also relieve ALL cell oxidative stress caused by daunorubicin (not published).
Despite these benefits, perhaps the largest contribution of adipocytes lies in their abundance of lipids.
Understanding the importance of adipocyte-derived lipids in ALL cell pathogenesis and metabolism
could be crucial in reversing the effect of obesity on ALL.
The first steps to answering this question centered on the translocation of FFAs from adipocyte to ALL
cells. Using the transwell co-culturing technique and conditioned media, we have demonstrated that ALL
cells secrete some factor responsible for stimulating adipocyte lipolysis and release of FFAs into the
surrounding microenvironment.(Fig 5.1) After cytokine analysis, we honed in on TNFα as the mediator of
lipolysis. TNFα was found to be only partly responsible as inhibition with infliximab did not fully abrogate
adipocyte lipolysis. ALL releases other cytokines, like IL-1beta, that may also play a role in adipocyte
lipolysis. Next, we developed a novel assay that uses fluorescently-labeled FFAs to show that ALL cells
take up lipolyzed FFA and incorporate them into lipid droplets, unknown to exist in ALL to our
knowledge. Follow-up studies using stable-isotope labeling and DESI-MS verified lipid translocation and
identified the preponderance of transferred lipids as unsaturated FFAs. In response to these adipocyte-
derived FFAs, ALL cells decrease the synthesis of and reliance on endogenous FFAs. Additionally, ALL
cells shuttle adipocyte-derived FFAs toward beta-oxidation, favoring energy production from FFAs over
glucose. The level to which ALL cells respond to exogenous FFAs describes the importance of adipocyte
lipids and their ability to supply ALL energy and metabolite demands.
The constitutive activation of cancer cell metabolism has traditionally been viewed as a “hallmark of
cancer.” In chapter 2, I demonstrated how adipocyte lipids can support ALL metabolism. In chapter 3, I
demonstrate how dietary restriction can exploit this “hallmark of cancer” to improve chemotherapy
efficacy. Following the theory of differential stress resistance, it was hypothesized that calorie and fat
restriction can reduce host cell metabolism with constitutive activation of ALL metabolism being
unaffected. This difference between normal and ALL cell metabolism would allow chemotherapy to
better target ALL while causing less damage to host cells. This effect was seen in obese leukemic
C57BL/6J that were switched to a low-calorie, low-fat diet before vincristine. The drastic improvement in
survival even surpassed the survival of mice that were lean the whole time. Furthermore, this effect was
only seen with vincristine, suggesting a specificity of chemotherapy to elicit a synergistic response.
Similarly, this effect was not evident in a humanized murine model of ALL. Yet, in vitro reduction of
serum also increased the efficacy of vincristine, mirroring the in vivo model.
These results from chapter 3 provide strong evidence for initiating a dietary intervention during ALL
treatment and served as the nidus for a new clinical trial seeking to do just that. As a co-investigator and
with the guidance of the principal investigator, Dr. Etan Orgel, we formed a multidisciplinary team of
oncologists, physical therapists, a nutritionist, endocrinologist, pathologist and statistician to implement
a dietary and activity intervention in children newly diagnosed with high-risk ALL during the first month
of chemotherapy. This pilot trial will chiefly assess the feasibility of this intervention to reduce therapy-
41

induced body fat gain. We will also evaluate the effect of this intervention on chemotherapy efficacy, as
measured by marrow minimal residual disease positivity. Metabolic activity assays on patient marrow
samples will assess whether the intervention affects leukemia and normal cell metabolism.

5.2 Study Limitations
A large limitation of this study is the adipocyte model utilized in chapter 2. 3T3-L1 murine adipocytes are
widely used mostly because of the ease of differentiation and culture. Compared to two other pre-
adipocyte cell lines, OP9 (murine calvarium fibroblasts) and ChubS7 (human subcutaneous pre-
adipocytes), 3T3-L1 cells have a consistently more complete differentiation with higher lipid
content.(182) Yet, being derived from mice, 3T3-L1 may not completely respond to human ALL cytokines
or cell-cell contact. Additionally, only using one adipocyte cell type limits the generalizability of these
findings.
Another large limitation is the NSG mouse model. This model is widely used for human xenografts and
allows good engraftment of human ALL, but their limitations lie in the difficulty to induce obesity. In
order to adequately promote diet-induced obesity in NSGs, mice must be culled down to 2 pups after
birth to allow greater access to milk. Weaning is also delayed to encourage greater feeding at a young
age. Then, pups are weaned onto a 60% calorie from fat diet. Despite this, a percentage of NSG never
get obese and those that do weigh noticeably less than obese C57BL/6J mice. The negative findings in
the humanized ALL NSG model may be confounded by the reduced obesity in this model. In future
Figure 5.1 – Summary of interaction between ALL and adipocytes. ALL cell (right) de novo lipogenesis is downregulated
(red) following uptake of adipocyte-derived FFAs. ALL cells also upregulate (green) beta-oxidation of these exogenous
FFAs. Adipocyte-induced changes in ALL cell lipid metabolism can support proliferation and survival. Dietary intervention
reduces body fat in obese mice and synergizes with vincristine to improve chemotherapy efficacy and mouse survival.
42

studies, we will utilize Rag2
-/-
IL2Rγ
-/-
mice that are bred onto a C57BL/6J background. These mice have
the same deficiency in B, T and NK cells as NSG but should respond to diet-induced obesity like a
C57BL/6J mouse.
5.3 Future Research
5.3.1 Lipidomic analysis of ALL cells
We will continue our collaboration with Dr. Richard Zare and his lab at Stanford University using
advanced mass spectrometry imaging techniques to detect adipocyte-associated changes in the ALL
lipidome. Specifically, we aim to detect changes in the lipidomic profile of ALL cells adjacent to bone
marrow adipocytes, comparing them against ALL cells at least 100 microns from an adipocyte. Using this
method, we will test the effects of diet-induced obesity in high-fat fed C57BL/6J and NSG mice on the
ALL cell lipidome compared to low-fat fed controls. Chemotherapy-induced alterations will also be
tested in mice receiving vincristine, dexamethasone and/or L-asparaginase. Through the clinical trial in
Chapter 4, we will also have access to bone marrow cores from patients before and after Induction
therapy. We will also analyze these samples for any notable alterations in the ALL lipidome that
associate with treatment efficacy or relapse.
5.3.2 Metabolic flux analysis
Understanding the ALL cell metabolic response to adipocyte-derived FFAs may underscore a large part
of the negative effect of obesity in ALL. The suspected shift of ALL cell metabolism from glycolysis to
beta-oxidation sheds light on many potential treatment strategies targeting the beta-oxidation pathway,
such as etomoxir, and subsequently, the utilization of adipocyte FFAs. Furthermore, the reduction in
glycolysis and increase in glycolytic metabolite shunting into the PPP not only fosters greater nucleotide
synthesis but also promotes NADPH production, a vital co-factor in a cancer cell’s ability to combat
oxidative stress. As such, the discovery of an adipocyte-induced metabolic shift in ALL cells may also
serve as a means of protection against various oxidative stress inducing chemotherapies like
daunorubicin. Metabolic flux assays using stable-isotope labeled metabolites allow their tracing through
various cellular pathways. Detecting adipocyte-induced alterations in ALL metabolic flux will pinpoint
targetable pathways that can reverse the effect of obesity on ALL.
5.3.3 IDEAL Weight in ALL Trial
At the time of writing, we have enrolled one patient into the clinical trial with continuing enrollment
until May 2019. By assessing both the efficacy of the intervention on reducing therapy-induced weight
gain and the feasibility of performing such an intervention, this study will serve as a pilot to a potential
multi-center trial. Similarly, analysis of patient serum and bone marrow will yield greater insight into
mechanisms responsible for any improvement in treatment efficacy. Lipidomic analysis will provide a
wealth of information into how the lipid profile of ALL cells change within the bone marrow over the
course of treatment and intervention, potentially revealing prognostic biomarkers and a deeper
understanding of ALL lipid metabolism. Given similar studies in adult populations, this intervention will
serve as a model for introducing a dietary and activity intervention in other cancer patient populations,
including pediatrics.

43

Chapter 6:
Materials and Methods
6.1 Experimental animals and in vivo dietary restriction
All mouse experiments were approved by the Children’s Hospital Los Angeles (CHLA) Institutional Animal
Care and Use Committee, and were performed in accordance with the USPHS Policy on Humane Care
and Use of Laboratory Animals. Diet-induced obese male C57BL/6J mice were weaned at 3 weeks of age
onto a 60% calories from fat diet (Research Diets, New Brunswick, NJ) at the Jackson Laboratory (Bar
Harbor, ME). Lean male C57BL/6J mice were weaned onto a 10% calories from fat diet (Research Diets)
and maintained at the Jackson Laboratory. NOD-scid-IL2Rγ
-/-
(NSG) mice (Jackson Labs) were bred in
house at CHLA. To promote diet-induced obesity, litters were culled down to 2 male pups three days
after birth. Four weeks after birth, pups were weaned onto the same 60% calories from fat diet from
Research diets. Lean NSG mice were not culled after birth and were weaned at three weeks of age onto
10% calories from fat diet.
At 20 weeks of age, 10,000 GFP-expressing 8093 (murine) ALL cells were transplanted retro-orbitally into
obese and lean C57BL/6J mice. After a 6 day engraftment period, half of the obese C57BL/6J mice were
switched to the 10% control diet (obese dieted), while the remaining mice stayed on their respective
diets. One day later, vincristine (0.5mg/kg/week i.p. x 4 weeks), dexamethasone (4mg/kg/day i.p. x 5
days/week x 4 weeks) or L-asparaginase (800IU/kg/day i.p. x 5 days/week x 4 weeks) therapy was
initiated. Daily mouse weights and food intake were assessed daily.
In the humanized model, at 18-20 weeks of age, 50,000 LAX7 (human) primary ALL cells were
transplanted intravenously through the tail vein into obese and lean NSG mice. After a 16 day
engraftment period, half of the obese C57BL/6J mice were switched to the 10% control diet (obese
dieted), while the remaining mice stayed on their respective diets. One day later, triple therapy
consisting of vincristine (0.5mg/kg/week i.p. x 4 weeks), dexamethasone (8mg/kg/day i.p. x 5 days/week
x 4 weeks) and L-asparaginase (800IU/kg/day i.p. x 5 days/week x 4 weeks) therapy was initiated. Daily
mouse weights and food intake were assessed daily.
All mice were tracked for survival and humanely removed from the study if they exhibit signs of
disseminated leukemic disease, such as >20% weight loss, lethargy, hunched posture, visible tumors and
hindlimb paralysis.
6.2 Cell culture and adipocyte differentiation
Murine pre-B 8093-ALL have been previously described here.(15) Human ALL cell lines BV173 and Nalm6
and murine 3T3-L1 pre-adipocytes were purchased from ATCC. Primary human LAX7 ALL cells were
kindly provided by Dr. Yong-mi Kim.
All media and supplements were supplied by Gibco (Waltham, MA) unless stated otherwise. Murine
8093 cells were cultured in McCoy’s 5A media, supplemented with 10% fetal bovine serum (FBS)
(Denville Scientific, South Plainfield, NJ), 1mM sodium pyruvate, 2mM Glutamax, and 10μg/mL
gentamicin. IL-3 (0.66nM) (Peprotech, Rocky Hill, NJ) and β-mercaptoethanol (55µM) were added to
fresh media during every passage. All human cell lines were cultured in RPMI 1640, supplemented with
the same ingredients except IL-3 and β-mercaptoethanol (complete media).
44

Non-leukemic pre-B cells were derived from harvests of femoral bone marrow of 4-6 week old male
C57BL/6J mice. Mice were anesthetized with ketamine and xylazene and perfused with heparinized
saline until liver clearing. Femurs were extracted and bone marrow was extracted by fluid force into
ACK lysis buffer and incubated at room temperature for 15 minutes (BD Biosciences, San Jose, CA).
Following red blood cell lysis, cells were centrifuged and washed in cell staining buffer. Cells were
labeled with FITC-conjugated anti-mouse CD127, APC-conjugated anti-mouse CD19 (both from
Biolegend, San Diego, CA) and DAPI (Sigma-Aldrich, St. Louis, MO) following manufacturer’s protocol.
Cells positive for both CD19 and CD127 were isolated by fluorescence activated cell sorting (FACS) on
the BD FACSAria-I cell sorter. Cells were then directly cultured on an OP-9 feeder layer in OPTI-MEM
media with 10% FBS, 10μg/mL gentamicin, IL-7 (0.66nM) (Peprotech) and β-mercaptoethanol (55µM).
Cells were passaged onto new OP9 feeder layers every 2-3 days and discarded after 3 weeks when pre-B
cells lose replicative potential.
3T3-L1 cells were cultured in DMEM with high glucose supplemented with 10% FBS, 1mM sodium
pyruvate, 2mM Glutamax, and 10μg/mL gentamicin. 3T3-L1 were differentiated into adipocytes by the
following protocol. Cells were seeded on day 0 and grown to confluence in poly-D-Lysine coated wells
for 72 hours. On day 3, the media were changed to differentiation media (3T3-L1 culture media except
with 15% FBS and 20mM HEPES), plus the 0.5mM IBMX (Sigma), 150nM porcine insulin (Sigma), and
250nM dexamethasone (Sigma). On day 5, new differentiation media was substituted, containing
150nM insulin only. On day 7, new differentiation media was substituted again, without any additional
supplementation. Mature adipocytes were used between day 7 and 11 of differentiation.
Pre-adipocyte (FCM) and adipocyte conditioned media (ACM) were collected after 48 hour conditioning
of 3T3-L1 pre-adipocytes and adipocytes in complete media. Pre-B cell (pre-B CM) and leukemia cell
conditioned media (LCM) were collected after 48 hour conditioning of pre-B, 8093 or BV173 cells in
complete media. Adipocyte and leukemia cell conditioned media (ALCM) was collected after 48 hour
conditioning of 8093 or BV173 with 3T3-L1 adipocytes in direct co-culture in complete media.
All cell culture was maintained in incubators held at 37°C with 5% CO
2
.
6.3 Oil Red O staining of neutral lipids
3T3-L1 adipocytes were indirectly co-cultured with 8093 or BV173 cells suspended in Transwells with a
0.4μm pore size or cultured with 8093 LCM, BV173 LCM or complete media for 72 hours. Following
incubation, adipocytes were fixed in 4% paraformaldehyde and stained with Oil Red O and DAPI (Sigma)
following the manufacturer’s protocol. Upon staining, adipocytes were viewed under a Zeiss Axio
Observer microscope and pictures were taken with 40x magnification. A blinded observer took pictures
of 10 randomly chosen fields and quantified red pixel count with ImageJ. Red pixel counts were
normalized to the number of adipocyte nuclei within each field.
BV173 cells stained with Oil Red O were taken straight from culture, fixed and stained according to
manufacturer’s protocol.
6.4 Quantification of adipocyte lipolysis
3T3-L1 adipocytes were incubated in complete media containing TNFα from 4pg/mL to 40ng/mL, pre-B
conditioned media or BV173 LCM for 24 hours. To test the ability of TNFα antibody to block adipocyte
lipolysis, 1μM infliximab (kindly provided by the CHLA Infusion Center) was simultaneously added to
TNFα-containing media and LCM during incubation. After 24 hours, 5μl of each condition was added to a
96-well plate in duplicate for colorimetric determination of FFA content. Media FFA content was
45

measured with the NEFA-HR(2) kit (Wako Pure Chemicals Industries, Ltd., Osaka, Japan) following
manufacturer’s protocols. Values of adipocyte-released FFAs are normalized to remove calculated levels
of basal lipolysis.
6.5 BODIPY-FFA tracing
Differentiated 3T3-L1 adipocytes were starved in serum-free complete media for 3 hours. Then,
adipocytes were incubated in serum-free complete media containing 10μM BODIPY® 500/510 C1, C12
(4,4-Difluoro-5-Methyl-4-Bora-3a,4a-Diaza-s-Indacene-3-Dodecanoic Acid) (Molecular Probes, Waltham,
MA) and 100nM insulin for 1 hour. Following incubation, adipocytes were washed 5 times with pre-
warmed complete media and co-cultured with either 8093 or BV173 cells suspended in Transwells for
various timepoints.
After the allotted incubation time, ALL cells were harvested from transwells, washed 3 times with cold
PBS, resuspended in cell staining buffer and stained with 1μg/mL DAPI for dead cell exclusion. Cells were
analyzed using flow cytometry on the LSR II Analyzer (BD Biosciences, San Jose, CA). BODIPY-FFAs were
detected using the GFP channel as BODIPY-FFA excitation/emission is 500/510. The median fluorescence
values of BODIPY-FFA from histogram plots were determined for each sample.
For confocal microscopy, 8093 and BV173 cells were grown in Transwells on poly-D-lysine coated
coverslips to promote adherence. Transwells were then placed over adipocytes pre-labeled with
BODIPY-FFA for 72 hours. Images were acquired with an LSM 700 confocal system mounted on an
AxioObserver.Z1 microscope equipped with a 63x/1.4 Plan-APOCHROMAT objective lens and controlled
with ZEN 2009 software (Carl Zeiss Microscopy, Thornwood, NY). A 488 nm laser and 560 nm long-pass
filter was used for fluorescence excitation and emission.
6.6
13
C-labeling of adipocyte FFAs and ALL cell lipidomics
3T3-L1 pre-adipocytes were differentiated following the normal procedure listed above with the
exception of using DMEM no glucose base media supplemented with 12.5mM U-
13
C-glucose (Sigma) and
12.5mM normal glucose. This mimics DMEM high glucose media but with 50%
13
C-labeled glucose.
Following 7 days of differentiation, adipocytes were incubated in complete media without labeled
glucose.
BV173 cells were plated on coverslips in Transwells and suspended above labeled adipocytes for various
time points. After co-culture, coverslips were washed twice with cold PBS and dried onto slides or wells
of plates, cells facing up. Coverslips were stored at -80°C until analysis.
Lipidomic analysis of samples was performed at Stanford University in the lab of Dr. Richard Zare. In
short, laboratory-built desorption electrospray ionization mass spectrometry (DESI-MS) source coupled
to an LTQ-Orbitrap-XL mass spectrometer (Thermo Fisher Scientific, Waltham, MA) was used for analysis.
DESI-MS was performed in the negative ion mode from m/z 90–1,200 with
dimethylformamide:acetonitrile 1:1 (vol/vol) used as the solvent.
6.7 TOFA inhibition of ALL lipogenesis
BV173 cells were co-cultured with feeder layers, exogenous FFAs or conditioned media and exposed to
various concentrations of TOFA (5-(Tetradecyloxy)-2-furoic acid) (Cayman Chemical) for 72 hours. Cell
counts were determined after 72 hours by trypan blue exclusion using a hemocytometer.

46

6.8 Gene expression analysis
ALL cells co-cultured in Transwells over adipocyte, undifferentiated fibroblasts or no feeder were
collected at designated time points for analysis. Cells were washed, resuspended in RNAProtect (Qiagen,
Valencia, CA) and RNA was extracted with RNEasy Mini kits (Qiagen). RNA concentration and quality
were determined by NanoDrop (ThermoFisher). RNA was subsequently converted to cDNA using the
High Capacity 1st Strand Synthesis kit (Applied Biosystems). Expressions of fatty acid synthase (FASN),
acetyl-CoA carboxylase (ACC1), stearoyl-CoA Desaturase 1 (SCD1) and carnitine palmitoyl transferase Ia
(CPT1a) were quantified by rtPCR on the ABI7900HT (Applied Biosystems, Waltham, MA) using Power
SYBR Green PCR Master Mix (Applied Biosystems). Primers for FASN, ACC1, SCD1 and CPT1a were
derived from a published study.(183) Transcript levels were normalized to β-actin (Forward: 5’-
ACAGAGCCTCGCCTTTGCCG-3’; Reverse: 5’-CGATGCCGTGCTCGATGGGG-3’).
6.9 Western blots
BV173 cells incubated in the presence of exogenous FFAs or feeder layers were harvested, washed in
cold PBS and lysed in buffer containing 0.1% Tween-20 and supplemented with PMSF, protease inhibitor
cocktail, and phosphatase inhibitor cocktail. Samples were sonicated (Bioruptor® Standard, Diagenode,
Denville, NJ) for 10 minutes at 30 second intervals on high power then centrifuged at 14,000g at 4 C for
15 minutes. The supernatant was aliquoted and stored at -20. Protein concentrations were quantified by
bicinchoninic assay (Pierce Biotechnology).
Whole cell lysates were run on 4-12% SDS-PAGE gel and blotted onto to a nitrocellulose membrane.
Membranes were blocked in 5% milk and probed with anti-human CPT1a, anti-human phospho-PDH and
anti-human PDH (all Cell Signaling). CPT1a expression was normalized to anti-human GAPDH (Cell
Signaling). Then, blots were probed with HRP-conjugated anti-rabbit secondary antibody (Cell Signaling)
followed by detection using HyGLO-HRP detection kit (Denville Scientific). Blots were imaged using
ImageQuant LAS 4000 (GE Healthcare Life Science, Pittsburgh, PA) and densitometric analysis of band
was performed with Image J (National Institute of Health).
6.10 Statistical analysis
All statistical tests were performed with GraphPad Prism (GraphPad Software, Inc., La Jolla, CA). Two-
sided student’s t-tests were used to compare the means of two groups and was the test used unless
otherwise noted. Dose response curves were derived from the best-fit semilog line using GraphPad
Prism. The data presented are all written as mean±SD. Significance was taken at p<0.05

47

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Abstract (if available)

Abstract Over one-third of adults and one-sixth of children in the United States are obese and at risk for developing multiple co-morbidities such as type II diabetes and cancer. The association between obesity and cancer pathogenesis has been observed across many cancer types, including acute lymphoblastic leukemia (ALL), the most common childhood cancer. Children that are obese at the time of diagnosis with ALL have a 50% greater risk of relapse over 5 years and have greater residual disease after the first month of chemotherapy. Despite these clinical findings, the cellular mechanisms responsible for the negative effect of obesity on ALL treatment remain unclear. This dissertation addresses how adipocyte-derived free fatty acids might aid leukemia growth and survival and the potential of dietary intervention to negate this interaction and improve chemotherapy efficacy.

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Asset Metadata

Creator Tucci, Jonathan Joseph (author)

Core Title The role of adipocyte-derived free-fatty acids in acute lymphoblastic leukemia

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Medical Biology

Publication Date 07/25/2016

Defense Date 06/21/2016

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

Tag acute lymphoblastic leukemia,adipocytes,clinical trial,diet,free fatty acids,OAI-PMH Harvest,obesity

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Bouret, Sebastien (committee chair), Fabbri, Muller (committee member), Kim, Yong-Mi (committee member), Mittelman, Steven D. (committee member)

Creator Email jtucci@chla.usc.edu,jtucci@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-276601

Unique identifier UC11281197

Identifier etd-TucciJonat-4596.pdf (filename),usctheses-c40-276601 (legacy record id)

Legacy Identifier etd-TucciJonat-4596-0.pdf

Dmrecord 276601

Document Type Dissertation

Format application/pdf (imt)

Rights Tucci, Jonathan Joseph

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

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA