AN ESSENTIAL ROLE OF THE IMMUNE SYSTEM IN …rb593gv5868/Kavya Rakhra... · an essential role of the immune system in remodeling the tumor microenvironment upon oncogene inactivation

AN ESSENTIAL ROLE OF THE IMMUNE SYSTEM IN

REMODELING THE TUMOR MICROENVIRONMENT

UPON ONCOGENE INACTIVATION

A DISSERTATION SUBMITTED TO THE PROGRAM IN IMMUNOLOGY AND

THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN

PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

Kavya Rakhra

August 2011

http://creativecommons.org/licenses/by-nc/3.0/us/

This dissertation is online at: http://purl.stanford.edu/rb593gv5868

© 2011 by Kavya Rakhra. All Rights Reserved.

Re-distributed by Stanford University under license with the author.

This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.

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http://purl.stanford.edu/rb593gv5868

I certify that I have read this dissertation and that, in my opinion, it is fully adequatein scope and quality as a dissertation for the degree of Doctor of Philosophy.

Dean Felsher, Primary Adviser


Sheri Krams


Calvin Kuo


Ronald Levy

Approved for the Stanford University Committee on Graduate Studies.

Patricia J. Gumport, Vice Provost Graduate Education

This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file inUniversity Archives.

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iv

ABSTRACT

The phenomenon of oncogene addiction has been presumed to occur in a cell

autonomous manner independent of the tumor microenvironment, through the

induction of proliferative arrest, apoptosis, differentiation and/or senescence. Immune

effectors have been implicated in both the induction and restraint of tumorigenesis but

their role in tumor regression upon the therapeutic inactivation of an oncogene is

unclear. Here we show that an intact immune system is required to mediate sustained

tumor regression upon oncogene inactivation in conditional mouse models of MYC

induced T-cell acute lymphoblastic leukemia (T-ALL) and BCR-ABL induced pro-B-

cell lymphocytic leukemia (B-ALL). We used these transgenic mouse models of

conditional oncogene inactivation, to show that the absence of an intact immune

system results in a 10-1000-fold reduction in the rate, extent, and duration of tumor

regression upon oncogene inactivation.

We demonstrate that CD4+ T-cells are critical to elicit oncogene addiction

upon inactivation of the MYC oncogene in a mouse model of T-ALL. The absence of

CD4+ T-cells had no effect on the ability of MYC inactivation to induce proliferative

arrest or apoptosis of tumor cells but markedly attenuated cellular senescence of tumor

cells and the shutdown of angiogenesis in the tumors. CD4+ T-cells were required

upon MYC inactivation to elicit inflammatory cytokines that regulate the

microenvironment. Provocatively, immune effectors knocked out for thrombospondins

failed to induce sustained tumor regression. Hence, CD4+ T-cells are critical immune

v

effectors, required for the remodeling of the tumor microenvironment through the

secretion of chemokines like thrombospondins in order to elicit oncogene addiction.

Most strategies to identify therapeutic agents utilize in vitro models or in vivo

xenograft models overlooking the effect of the immune system. Our results argue for

the necessity of models that include an intact host immune system to properly evaluate

the potential efficacy of targeted therapeutics for maximum clinical impact. Our

results also imply that the efficacy of new and existing cancer targeted therapeutics

can be increased by combining them with strategies to inhibit angiogenesis, induce

cellular senescence or increase CD4+ T-cell infiltration in the tumor

microenvironment.

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ACKNOWLEDGEMENTS

This Ph.D. required a lot of moral support and various colleagues, friends and

family members have listened to the incessant grumblings and travails of being a

graduate student over the past several years. It's going to be impossible to individually

mention everyone's contribution and I'd like to start by acknowledging everyone who

shared in the joy, excitement, enthusiasm, depression, anger, frustration and

experimental failure that are an inherent part of graduate school.

I did my first rotation in Dean's lab and knew almost immediately that this

would be my lab. I was mentored by Alice and Pavan and was introduced to tumor

immunology for the very first time. I continued to work with them through my

formative years in graduate school and have benefited greatly from this experience.

I've learnt so much from them, not just about scientific experimental design and career

development but also about fitness, music, movies, books and how to be a well

rounded individual.

Dean runs a fantastic high energy lab that has accommodated my constant

stream of questions, disorganized desk and bench and tendency to burst into song for

no apparent reason. This allowed me to enjoy coming into work every morning and

created a „microenvironment‟ for me to succeed. Dean has always been supportive,

encouraging or exacting as the situation warranted and allowed me to realize my

scientific potential. He has also served as an excellent role model as someone who has

it all, a clinical career, a research laboratory pushing the frontiers of cancer biology

and a wonderful family and I hope to have at least some combination of these in the

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years to come. I would also like to thank my committee members Sheri Krams, Ron

Levy and Calvin Kuo for their help navigating through my enormous project and

always bringing me back to the fundamentals of immunology.

My family of course, has supported me through all of my life and grad school

was no different. My parents would always make an effort to try and understand what

I've been working on and make me give lab meeting presentations when I went home

for the holidays. I love that they've managed to stay actively involved in my life even

though I've been 9000 miles away from them. It's also been awesome to have my

brother living in NYC, just far enough that we don't get on each others' nerves but

close enough to always have a place to visit for the holidays and have my phone bills

paid. To all of my family who've always called on my birthday and who are always

proud of me, thank you!!

I was also fortunate to have several friends who were always willing to lend an

ear or a beer or provide some good Indian food or catch a late night movie show. In no

particular order, I want to acknowledge Lux, Bharey, Addu, Div, Anu, Yashas,

Mallika, Peter, Cat, Alper, Lavoo, Nammo, Shariq, Anshul, Justine, Kiri, Masumi,

Nalini, Simona, Shreekar, Prasanthi, RSS, Ditch, Cherry, Ranji, Indra and Sanketh.

I'd also like to thank current and previous Felsher lab members Alice, Pavan,

Peter, Alper, Emelyn, Stacey, Tahera, Lowen, Qiwei, Hanan, Vanessa, Ramya, Prajna,

Yulin, Natalie, Ling, Dina, and Shelly for participating in various scientific and non-

scientific activities (happy hours, birthday cakes, dish walks, disney land, manicures,

tattoos, marathons, bay to breakers, etc.) with me and enriching my time in the Felsher

lab. All in all, it was so much more than just a Ph.D.

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TABLE OF CONTENTS

Abstract………………………………….………………………………………………....…..iv

Acknowledgements……………………………………………….……………………….…..vi

List of Tables…………………………………………….………………………………..…...xi

List of Figures……..…………………………………………….…………………………….xii

Chapter 1: Introduction

1.1 Overview: ............................................................................................................................. 2

1.2 Oncogenes and cancer: ......................................................................................................... 3

1.3 MYC: .................................................................................................................................... 4

1.3.1 The estrogen receptor-tamoxifen regulatory system: ........................................................ 5

1.3.2 The tetracycline regulatory system: .................................................................................. 6

1.4 Oncogene addiction: ............................................................................................................. 8

1.5 Mechanisms of tumor regression upon oncogene inactivation: ......................................... 11

1.5.1 Apoptosis:........................................................................................................................ 12

1.5.2 Inhibition of angiogenesis: .............................................................................................. 12

1.5.3 Cellular senescence: ........................................................................................................ 14

1.6 Interaction of a tumor with its immune microenvironment:............................................... 16

1.6.1 Role of CD4+ T-cells in the tumor microenvironment: ................................................... 21

1.6.2 Role of tumor associated marcophages (TAMs) in the tumor microenvironment….......23

1.6.2.1 TAMs and tumor progression: ................................................. 25

ix

1.6.2.2 TAMs and tumor inhibition: .................................................... 26

1.6.3 Role of eosinophils in the tumor microenvironment: ...................................................... 27

1.6.3.1 Eosinophils and tumor progression: ......................................... 28

1.6.3.1 Eosinophils and tumor inhibition: ............................................ 29

1.7 References: ......................................................................................................................... 33

Chapter 2: Contribution of the immune system to oncogene inactivation mediated tumor

regression

2.1 Overview: ........................................................................................................................... 44

2.2 Contribution of the adaptive immune system:.................................................................... 44

2.3 Contribution of the innate immune system: ....................................................................... 56

2.4 Contribution of T-cells to regression of primary MYC induced lymphoma: ...................... 60

2.5 Contribution of the adaptive immune system in other models of oncogene induced

hematologic malignancies: ....................................................................................................... 62

2.6 Contribution of an antigen specific immune response: ...................................................... 64

2.7 References: ......................................................................................................................... 96

Chapter 3: Discussion of findings, implications of results and future direction

3.1 Overview: ........................................................................................................................... 99

3.2 The adaptive immune system remodels the tumor microenvironment: ............................. 99

3.3 Potential role of T-regs and an antigen specific immune response: ................................. 105

3.4 Potential role of the innate immune system: .................................................................... 107

3.5 Implications: ..................................................................................................................... 110

x

3.6 References: ....................................................................................................................... 114

Appendix I: Materials and Methods ................................................................................... 119

xi

LIST OF TABLES


Table 1: Mechanisms of tumor regression upon oncogene inactivation……….…...31

Table 2: CD4+ T-cell polarization and cytokine secretion profile…………………..32

LIST OF FIGURES


Figure 1: A bi-transgenic mouse model of conditional MYC expression…………………….30

Chapter 2: Contribution of the immune system to oncogene inactivation mediation

tumor regression

Figure 1: An intact immune system is required for sustained tumor regression.....................66

Figure 2: An intact immune system is required for sustained tumor regression upon MYC

inactivation……………………………………………………………………………..…......69

Figure 3: CD4+ T-cells home to the tumor and are sufficient to induce sustained tumor

regression upon MYC inactivation……………………………………………….....................71

Figure 4: Splenocytes depleted of CD4+ T-cells home to the tumor microenvironment and

verification of RAG1-/-

reconstitution……………………………….……..………………….73

Figure 5: The immune system does not influence apoptosis and cellular arrest upon MYC

inactivation…….……………………………………………………………………………...75

Figure 6: An intact immune system is required for the inhibition of angiogenesis upon MYC

inactivation………..…………………………………………………………………………..77

Figure 7: TSP-1 expression in the tumor microenvironment is required for sustained tumor

regression upon MYC inactivation…………………………………………………………….79

Figure 8: An intact immune system is required for the induction of cellular senescence upon

MYC inactivation…………………………………………………………...............................81

xiii

Figure 9: Cytokines produced by the immune system contribute to sustained tumor regression

upon MYC inactivation ……………………………………….................................................83

Figure 10: Macrophages infiltrate tumors regressing in WT and CD8-/-

hosts upon MYC

inactivation…………………………………………………………………............................85

Figure 11: Increased levels of iNOS, Arg-1 and TSP-1 in macrophages from tumor bearing

WT host…………….……………………………………………………................................87

Figure 12: Cyclosporine A treatment inhibits induction of senescence and inhibition of

angiogenesis in primary MYC induced T-ALL…………………………………...…..............89

Figure 13: An intact immune system is required for sustained regression of tumors in a

conditional mouse model of BCR-ABL-induced B-ALL …………………………..................91

Figure 14: Increased Foxp3 expression in tumors regressing in WT hosts upon MYC

inactivation ……………………………………………………...............................................93

Figure 15: Transplanted tumors are rejected upon re-challenge in WT hosts that have

previously exhibited sustained tumor regression…………………………………...................95

Chapter 3: Discussion of findings, implications of results and future direction

Figure 1: Model of the interaction of the immune system with oncogene addiction……….113

1

CHAPTER 1: Introduction

2

1.1 Overview:

To set the stage for this dissertation thesis, I will discuss two important

discoveries in the field of cancer biology. The first is the discovery of oncogene

addiction, the phenomenon by which highly complex tumor cells that are a

consequence of multiple genetic and epigenetic changes become exquisitely dependent

upon a single oncogene for their continued growth and survival [1-2]. The generation

of conditional mouse models of cancer in which oncogene expression could be

spatially and temporally controlled allowed the study of the mechanisms by which

targeting oncogenes reversed the cancer phenotype. Consequently, inactivating

oncogenes in tumor cells has been therapeutically exploited to cause tumor regression

in a variety of cancer patients and drugs like Imatinib Mesylate or Gleevec, a small

molecule inhibitor of the BCR-ABL oncogene [3], have seen great clinical success.

The second important discovery is the complex interaction of the immune

system with tumor cells [4-5]. The immune system can influence various aspects of

tumor initiation, growth, progression [6-7] and tumor regression in response to various

anti-cancer radiation- and chemo-therapeutics [8-10]. While Gleevec and other

targeted therapies have been effective in causing tumor regression in various cancers

[11-14], the contribution of the immune system to tumor regression mediated by the

targeted inactivation of an oncogene remained unknown and studying this became the

focus of my graduate work.

In this introductory chapter, I describe the role of oncogenes in cancer with

particular emphasis on the MYC oncogene, various conditional mouse models

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designed to study the role of MYC in tumorigenesis, mechanisms of oncogene

addiction, various targeted therapies based on the concept of oncogene addiction and

how the immune response interacts with cancer focusing on the role of the CD4+ T-

cells of the adaptive immune system and macrophages of the innate immune system.

This will set the stage to understand the experiments described in this thesis (Chapter

2) and the discussion and interpretation of the results of these experiments (Chapter 3).

1.2 Oncogenes and cancer:

Oncogenes are genes that either initiate and/or are involved in progression of

cancer [15]. They often encode altered forms of proteins normally involved in cell

proliferation and apoptosis. These could be proteins like transcription factors, growth

factors, growth factor receptors, signal transducers or apoptosis regulators. In a normal

cell, genes that encode these proteins are known as proto-oncogenes. Proto-oncogenes

can be activated to oncogenes by genetic events such as mutation, gene fusion, gene

translocation, chromosomal rearrangement, gene amplification or juxtaposition of a

gene to enhancer elements [15].

In several mouse models of cancer, it has been demonstrated that tumors arise

after a period of latency upon oncogene activation. This suggests that oncogene

activation alone is not always sufficient for tumorigenesis. Other genetic events must

occur in addition to oncogene activation in order to cause neoplasia [16-18]. In fact,

tumorigenesis is known to occur as a result of sequential genetic aberrations, each of

which confers some growth advantage to a normal cell which eventually renders it

cancerous [19].

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1.3 MYC:

The MYC protein belongs to a family of basic helix loop helix transcription

factors that include c-MYC, N-MYC and L-MYC. For the purpose of this dissertation,

we will focus on c-MYC. For the remainder of this text, MYC refers to c-MYC unless

otherwise specified. MYC is a proto-oncogene found on chromosome 8 in humans and

on chromosome 15 in mice [20]. It encodes a transcription factor which controls the

expression of genes involved in critical cellular functions like cell cycle regulation,

apoptosis, proliferation, metabolism, angiogenesis, adhesion and differentiation. In

normal cells, the expression of MYC is tightly controlled, however in cancer cells

MYC expression is dysregulated due to genetic abnormalities [21-22]. Dysregulation

of MYC expression can occur due to chromosomal translocation resulting in MYC

being expressed from the immunoglobulin locus which is active in B-cells [23] or

gene amplification that results in increased copies of the MYC gene and hence

increased MYC expression [24]. Abnormal genetic events that lead to increased MYC

transcription or mRNA stability can also cause increased MYC protein expression.

Furthermore, increased MYC activity can often result from mutations in pathways

upstream of MYC such as the RAS and β-catenin pathways [21-22].

This dysregulation of MYC expression leads to tumorigenesis due to the

disruption of cellular functions related to cell cycle progression, metabolism, apoptosis

and genomic instability. Aberrant MYC expression is known to occur in 100% of

Burkitt‟s lymphomas, 90% of gynecological cancers, 80% of breast cancers, 70% of

colon cancers, 50% of hepatocellular cancers, 50% of T-ALLs and 5% of adult acute

5

lymphoblastic leukemia in humans. Thus MYC is the quintessential oncogene since it

causes cellular transformation upon inappropriate expression [21-22].

As an important gene that mediates human cancers, MYC‟s role in

tumorigenesis has been explored through several genetic mouse models in which MYC

overexpression induces tumor formation. In order to recapitulate sporadic human

cancer, mouse models were designed to regulate MYC expression in a time dependent

and tissue specific manner using a number of different genetic strategies [18, 25-27].

This ensures that the tumor initiating mutation occurs in cells surrounded by an

un-mutated tumor microenvironment to accurately model spontaneous tumor initiation

seen in humans [28]. Several conditional models of MYC induced cancer have been

designed and are discussed below:

1.3.1 The estrogen receptor-tamoxifen regulatory system:

In this genetic system, the MYC gene is fused to the hormone binding domain

of the estrogen receptor (ER). In the absence of any ER ligands, the MYC-ER fusion

protein forms a complex with intracellular proteins like HSP-90, thus preventing MYC

from entering the nucleus. However, in the presence of an appropriate ER ligand such

as 17β-estradiol, MYC-ER is released from these intracellular complexes and can be

transported into the nucleus where it can function as a transcription factor. This allows

MYC function to be estrogen dependent [29]. To prevent the effects of endogenous

estrogen on this fusion protein, second generation fusion proteins have been generated

in which MYC is fused to a mutant murine estrogen receptor G525R which can no

longer bind to 17β-estradiol, but can still bind to the synthetic steroid

6

4-hydroxytamoxifen (4OHT). This allows MYC function to be dependent on

exogenous 4OHT. In mouse models, tissue specificity of MYC expression is achieved

by cloning the MYC-ER fusion protein downstream of a tissue specific promoter [30].

The advantage of this model is that MYC function is controlled at the protein

level and not at the level of transcription. This ensures that MYC becomes functional

within minutes of systemic administration of 4-OHT and this can be easily reversed by

withdrawing 4-OHT administration. This strategy has been used to overexpress MYC

in pancreatic β cells [31], primary rodent fibroblasts [30] and thymocytes [32].

1.3.2 The tetracycline regulatory system:

Derived from the bacterial tetracycline resistance operon, this genetic system

has been designed to incorporate two regulatory elements. One element is a

tetracycline transactivator (tTA) and the second element is a tetracycline response

element (TRE) consisting of tet-O sequences of the bacterial operon within a minimal

promoter. The gene of interest (in this case MYC) is cloned downstream of the tet-O

promoter. In order to induce target gene expression, tTA must bind to the tet-O

promoter to activate it. Gene expression from the tet-O promoter can be controlled by

using tetracycline or tetracycline analogs like doxycycline (dox). In the presence of

dox, tTA can no longer bind to the tet-O promoter, thus causing gene expression to be

turned off. This is known as the Tet-Off system (Figure 1) [33-34].

Conditional mouse models of MYC induced cancers are generated by

crossing a transgenic mouse line expressing the tTA element in a tissue specific

manner with a transgenic mouse line that carries the human MYC transgene under the

7

control of the TRE. The progeny of this cross will express human MYC in tissues in

which tTA is expressed. Gene expression can be turned off by administering

doxycycline to these mice in their drinking water and by delivering a doxycycline

injection intra-peritoneally (IP). This model has been used to overexpress MYC in the

bone, liver, mammary glands and hematopoietic system [18, 26, 35].

A variation of this genetic switch is the Tet-On system, in which a modified

tTA element known as the reverse tTA (rtTA) is used. The rtTA element requires dox

to bind to the tet-O promoter and thus transgene expression turned on only in the

presence of doxycycline. In the absence of doxycycline, rtTA cannot bind the tet-O

promoter and transgene expression is off [33-34].

The data described in chapter 2 have been generated using a model of MYC

induced lymphoma, using the Tet-Off system. In this model, tTA expression is

restricted to the lymphoid compartment as it is transcribed downstream of the

Eµ-Immunoglobulin heavy chain enhancer. Once crossed with mice bearing a

tet-O-MYC construct, MYC expression is induced in the lymphoid compartment. When

MYC is turned on from birth, these mice develop lymphoma within 8-10 weeks. The

phenotype of this lymphoma is CD4+CD8

+ in 90% of the mice analyzed [18] (Figure

1).

These models have been helpful in characterizing the role of MYC in tumor

initiation and progression and have also served as excellent means to test novel cancer

therapeutics against MYC induced cancers. Additionally, the conditional regulation of

MYC expression in these models has facilitated the analysis of the consequences of

8

inactivating MYC in tumors initiated by this oncogene. It has been shown that various

tumors initiated by MYC overexpression such as hepatocellular carcinomas [35],

osteosarcomas [26], lymphomas [18] and pappilomas [36] undergo regression upon

MYC inactivation. These tumor cells are dependent on MYC for their growth and

survival and are thus addicted to the MYC oncogene. These models have been used

extensively to study the mechanisms of tumor regression upon oncogene inactivation.

It is important to note that whether or not tumor cells are dependent on MYC is highly

contextual and in certain cases inactivation of MYC fails to cause tumor regression of

a MYC induced tumor [37].

1.4 Oncogene addiction:

Tumor cells are notorious for their genetic and epigenetic complexity and are

known to harbor several mutations. Despite this, they often show dependence on a

single oncogene or pathway for their growth and survival, a phenomenon defined as

oncogene addiction [1, 38]. As a consequence of this addiction, when an oncogene

that tumor cells are dependent on is inactivated, the tumor undergoes regression.

The phenomenon of oncogene addiction has been demonstrated in several

mouse models. In addition to the inducible models of MYC initiated tumorigenesis

described earlier, oncogene addiction has also been shown to occur in conditional

mouse models of H-RAS induced melanoma [39], K-RAS induced lung

adenocarcinomas [40] and BCR-ABL induced leukemia [41] and others [2].

9

With the advent of targeted therapeutics like Imatinib Mesylate or Gleevec,

compelling evidence accrued suggesting that oncogene addiction occurs in tumors

from human patients. Gleevec inhibits the BCR-ABL oncogene that causes chronic

myelogenous leukemia (CML). The mechanism of action of Gleevec involves

preventing access of the ATP molecule to the constitutively active BCR-ABL tyrosine

kinase by competitive inhibition. This prevents tyrosine phosphorylation and

activation of the proteins involved in the BCR-ABL signaling cascade which is

required for CML cells to proliferate [3]. Gleevec can also inhibit other tyrosine

kinases like KIT and has also proved to be effective in the treatment of

Gastrointestinal Stromal tumors (GIST) [42].

Other successful examples of cancer therapies based on oncogene inactivation

and tyrosine kinase inhibition are:

Traztazumab/Herceptin which blocks HER2 function in breast

cancers [12].

Erlotinib/Tarceva which blocks EGFR function in non-small cell

lung cancers (NSCLC) [14].

Sorafenib/Nexavar to block B-RAF and VEGFR function in

melanoma and renal cell carcinoma [11, 13].

While current therapies based on oncogene addiction are limited to tyrosine

kinase inhibitors, several efforts are underway to target other oncogenes like MYC,

RAS and β-catenin. Strategies being tested to target MYC include using anti-sense

oligonucleotides or small interfering RNA (siRNA) to inhibit MYC mRNA, using

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phosphorodiamidate morpholino oligomers (PMOs) to prevent mRNA translation, and

targeting the interaction of MYC with its binding partner MAX. However these

strategies have seen limited success and active research is being done to improve the

efficacy, sensitivity, specificity and delivery of these drugs [43-44].

Since oncogene addiction was first characterized in human tumor derived cell

lines in vitro, it was largely thought to be a cancer cell autonomous phenomenon that

occurred independently of tumor-stromal interactions [45]. However, it is becoming

increasingly evident that overexpression of an oncogene can cause changes in the

tumor microenvironment. Activation of the RET oncogene in normal human

thymocytes induces an inflammatory response leading to tumor tissue remodeling,

angiogenesis and metastasis, all of which contribute to the maintenance of the

transformed state of the tumor [46]. Oncogenic RAS upregulates expression of the

cytokines IL-6 [47] and IL-8 [48] which in turn contributes to tumorigenesis. In a

MYC-induced model of lymphoma, MYC overexpression is associated with the

activation of macrophages which can cause tumor suppression [49]. Furthermore,

endogenous MYC levels have also been shown to maintain the angiogenic tumor

microenvironment in certain tumor models [50]. This dynamic cross talk between the

oncogene and the tumor microenvironment suggested that this interplay might be

fundamental to eliciting oncogene addiction.

Additionally, the complex interaction of the immune system with tumor cells

has been investigated in great detail. The immune system can play a significant role in

influencing not only aspects of tumor initiation, growth and progression, but also the

11

outcome of a cancer therapy [6-7, 9-10]. This has been well studied for various

radiation- and chemo-therapies [10]. The kind of tumor cell apoptosis caused by a

specific anti-cancer therapy determines the contribution of the immune system to the

therapy [8-9, 51].

This suggested that there might be a significant contribution of the immune

system to tumor regression mediated by targeted therapeutics as well. My goals were

to ascertain whether or not there is a non-cell autonomous, immune based component

to oncogene addiction and to characterize this contribution by identifying key players

of the immune system that are involved and the mechanisms by which they influence

oncogene addiction.

1.5 Mechanisms of tumor regression upon oncogene inactivation:

Tumor regression upon oncogene inactivation has been demonstrated in

several inducible mouse models of cancer as described above. Analysis of tumor

regression in these mouse models shows that inactivation of the oncogene after tumor

establishment leads to tumor regression through a number of different mechanisms

depending on the oncogene being inactivated and the context of the tumor (Table 1).

For example, even brief oncogene inactivation can induce a permanent loss of a

neoplastic phenotype in osteosarcoma [26] and lymphoma [18] but not in epithelial

tumors such as hepatocellular carcinoma [35] and breast carcinoma [25].

We investigated the influence of the immune system on various mechanisms of

regression known to occur upon inactivation of the MYC oncogene. Experiments were

12

performed to study the mechanisms of apoptosis, inhibition of angiogenesis and

irreversible cellular growth arrest or senescence known to contribute to tumor

regression upon MYC inactivation in the conditionally inducible Eµ-tTA; tet-O-MYC

model of MYC induced murine lymphoma [18, 52-53].

1.5.1 Apoptosis:

Studies have shown that both MYC overexpression [54-55] and loss of MYC

expression [56] can lead to apoptosis. The precise mechanisms governing MYC‟s role

in apoptosis have not been clearly elucidated though several cases of MYC induced

apoptosis appear to involve p53 activity [57-58]. However MYC induced apoptosis can

also occur in the absence of p53 [59]. Apoptosis that occurs upon reduction of MYC

levels can occur through increasing p27kip1

[60] and caspase activation [61].

In the conditional model of MYC induced lymphoma used in our experiments,

after 3-6 days of MYC inactivation, certain areas of the tumor appear to be undergoing

apoptosis in a cell autonomous manner, which contributes to tumor regression upon

MYC inactivation [18].

1.5.2 Inhibition of angiogenesis:

Angiogenesis is the process by which new blood vessels are generated from

pre-existing blood vessels. Angiogenesis is required for tumor cells to grow and

become invasive and targeting angiogenesis in cancer is being actively studied as a

means of controlling tumor growth [62].

13

The angiogenic microenvironment in a tumor is governed by an “angiogenic

switch” that depends on a balance of pro- and anti-angiogenic factors. If there is a

predominance of pro-angiogenic factors (VEGF, bFGF), the angiogenic switch is

considered “on” and this leads to tumor vascularization and thus to tumor growth.

However if there is an abundance of anti-angiogenic factors (TSP-1, endostatin,

angiostatin), then the angiogenic switch is turned “off” and tumor vascularization is

prevented [63].

In a model of conditional MYC induced lymphoma that is also p53-/-

, it has

been shown that MYC inactivation alone could not cause sustained tumor regression.

In order for regression to be sustained upon MYC inactivation, the angiogenic switch

had to be turned off through the production of Thrombospondin-1 (TSP-1), a potent

anti-angiogenic factor [52].

TSP-1 is an extracellular matrix glycoprotein known to be secreted by various

cell types such as platelets, endothelial cells, fibroblasts, vascular smooth muscle cells,

bone marrow stromal cells, monocytes and macrophages [64-65]. TSP-1 was the first

endogenous inhibitor of angiogenesis to be identified. It inhibits angiogenesis by

preventing endothelial cell migration, inducing endothelial cell apoptosis and

antagonizing the effect of pro-angiogenic factor VEGF. TSP-1 is a pleiotropic

molecule and its effects are not restricted to inhibition of angiogenesis. Its other

functions include activation of latent TGF-β, suppression of nitric oxide signaling,

modulation of thrombosis, regulations of T-cell chemotaxis, and regulation of

inflammation by influencing the functioning of several immune cell types [66-68].

14

Interestingly, TSP-1 expression is activated by tumor suppressor genes like

p53 and PTEN [69-70] and repressed by oncogenes like RAS, MYC and c-JUN [71-

72]. Downregulation of TSP-1 expression by MYC occurs due to increased TSP-1

mRNA turnover [73]. Thus tumor regression seen upon MYC inactivation in a

conditional model of MYC induced tumorigenesis can be attributed to the angiogenic

switch being turned off by increased TSP-1 expression. Other mechanisms by which

increased TSP-1 expression causes tumor regression include activation of TGF-β and

recruitment of macrophage infiltration to the tumor site [65].

1.5.3 Cellular senescence:

Several years ago, it was noticed that cells growing in culture enter a state of

permanent proliferative arrest after a fixed number of cell divisions [74]. This

irreversible cellular growth arrest is known as cellular senescence and was first

characterized as a mechanism of cellular aging. More recently there has been evidence

that cellular senescence also functions as a mechanism of tumor suppression and can

prevent cells from undergoing neoplastic transformation. Senescent cells have been

identified in pre-malignant and benign tumors but not in malignant tumors suggesting

that cellular senescence could be a barrier to tumor progression [75-77].

It has also been observed that cells that accumulate oncogenic insults and

induce cellular senescence programs as a mechanism of tumor suppression, can only

become malignant if the senescence program is bypassed due to mutations in genes

like p53 and the p16INK4a locus [77]. Oncogenic insults known to drive cells into

senescence are events like RAS or MYC overexpression or DNA damage [78-80].

15

In addition to being an important restraint to tumorigenesis, cellular senescence

has also been implicated as an important mechanism of tumor regression upon

oncogene inactivation. Suppression of MYC expression even in normal fibroblasts can

induce senescence [81]. Wu et. al. have shown that upon inactivation of MYC in

conditional primary tumor models of MYC induced lymphoma and hepatocellular

carcinoma, tumor cells undergo cellular senescence. This is shown by the upregulation

of senescence-associated acidic β-galactosidase (SA β–gal) and the increased

expression cyclin-dependent kinase inhibitors like p16INK4A and p21CIP1. Senescent

tumor cells are also known to up regulate heterochromatin foci [53]. Thus, cellular

senescence has been documented as an important mechanism of regression upon

oncogene inactivation.

Recent studies have revealed that senescent cells develop a secretory

phenotype that results in the secretion of inflammatory mediators such as interleukins,

chemokines, growth factors and proteins that alter the extra-cellular matrix. These

mediators can significantly alter the tumor microenvironment and cause increased

angiogenesis, increased cell motility and proliferation leading to tumor promotion [82-

86].

Several of the mediators of this senescence associated secretory phenotype

(SASP) like MCP-1, IL-8 and IL-15 can cause infiltration of immune cells including

macrophages, natural killer (NK) cells and neutrophils, to the tumor

microenvironment. Depending on the amount of these factors secreted and the type of

immune cells that infiltrate the tumor microenvironment, this could be beneficial or

16

harmful to the tumor. In a model of p53 mediated senescence in the context of a

murine liver tumor, it was shown that senescence causes infiltration of neutrophils and

macrophages which cause senescent liver tumor cells to be cleared away, thus causing

an anti-tumor response [87]. However, mediators secreted by senescent cells are also

known to attract TH-2 polarized T-cells and M2 polarized macrophages which are

known to be tumor promoting [82, 88].

Thus, on one hand, senescence appears to be a mechanism of tumor

suppression by causing irreversible cellular arrest, but on the other, it can also lead to

tumor promotion depending on the SASP of the senescent cells and the context of the

tumor. The parameters that determine the net effect of cellular senescence on a tumor

are not well understood and are most likely governed by complex interactions of

senescent tumor cells with immune cells of the tumor microenvironment. This

duplicity of character is also seen with respect to infiltrating immune cells. Studies

have shown that depending on the polarization of infiltrating immune cells and the

type of tumor they infiltrate, they can either promote or antagonize tumor growth [6-7,

89-91]. The relationship between immune cells and cancer is discussed in further

detail in the next section.

1.6 Interaction of a tumor with its immune microenvironment:

The immune system can be subdivided into the innate immune system and the

adaptive immune system. The innate immune system comprises cells like the

macrophages, dendritic cells, NK cells, mast cells, neutrophils and basophils which are

17

the first line of defense in the body and can recognize danger signals on invading

pathogens and self cells in a non-specific way.

The adaptive immune system comprises the B-cells and the CD4+ and CD8

+ T-

cells. These cells bear receptors that can recognize specific antigens on pathogens or

tumor cells with the help of antigen presenting cells. Cells of the adaptive immune

system can also develop long lived memory against the antigens that they recognize in

order to make subsequent immune responses to the same pathogen faster and more

efficient.

Since early studies of the functionality of the immune system were done with

respect to invading pathogens that were foreign to the body, the interaction of the

immune system with cancer cells that are known to be self cells was largely ignored.

However recent evidence such as increased incidence of tumor formation in

immunocompromised mice and human patients has led to extensive characterization

of the interaction of the immune system with various aspects of tumor formation,

progression and regression [4-5].

We now know that tumor cells interact intimately with the immune system.

Tumors co-evolve with the immune system and while the immune response can

protect the host from tumors by causing tumor cell death, it can also modify the tumor

cells in such a way that eventually tumors can escape the immune response. The

interaction of tumor cells with immune cells has been extensively studied and

Schreiber et al. have proposed the “Cancer Immunoediting” model to understand this

interaction. It is proposed that this interaction occurs in three distinct but continuous

18

phases: Elimination, Equilibrium and Escape. These phases are briefly described

below [4]:

Elimination: As a tumor grows invasively, it elicits a local inflammatory

response and causes innate immune cells like macrophages and NK cells to home to

the site of the tumor. These cells recognize the transformed cells and secrete

cytokines like IFN-γ which causes further tumor cell death. This eventually leads to a

cascade of immune activation that results in the presentation of tumor antigens to T-

cells in the tumor draining lymph nodes and recruitment of tumor antigen specific

CD4+ and CD8

+ T-cells of the adaptive immune system to the site of the tumor. These

cells can now recognize and eliminate the tumor cells. If this elimination is complete,

the host remains tumor free. However, if the elimination is incomplete, the next phase

of interaction (Equilibrium) between the tumor cells and the infiltrating immune cells

ensues.

Equilibrium: Tumor cells that have not been eliminated enter into a dynamic

equilibrium with the infiltrating immune cells. During this phase, the tumor cells do

not proliferate. The immune cells exert a Darwinian selective pressure on the tumor

cells during this phase.

Escape: At the end of the equilibrium phase, in response to the selection

pressure exerted by the immune cells, tumor cell variants arise that can escape the

immune response. These tumor cell variants can now proliferate and manifest as a

clinical tumor in the host.

19

Clinical studies of breast cancer, colon cancer, neuroblastoma and melanoma

have demonstrated that increased presence of tumor infiltrating lymphocytes (TILs)

correlated with better patient survival [92-95]. Mice lacking various components of

the immune system such as RAG1-/-

mice (lacking the adaptive immune system),

perforin-/-

mice (lacking lymphocyte cytotoxicity), and IFN-γ-/-

mice showed increased

incidence of tumor formation in various assays [4, 96]. This suggested that the

immune system, particularly the T-cells, could play a protective role against tumor

formation.

However, there is also ample evidence that various immune cell populations

that are involved in establishing chronic inflammatory responses such as T-cells,

macrophages and mast cells can promote tumor development in certain tumor models.

This can occur either by directly enhancing tumor cell survival or by inhibiting anti-

tumor immune responses in the tumor microenvironment. For example, when

macrophages are depleted in a mouse model of cervical cancer, tumorigenesis

decreases [97]. Creation of a pro-inflammatory environment by these cells occurs

through secretion of pro-inflammatory cytokines like IL-1, IL-6, VEGF and TNF-α.

This leads to the formation of a pro-angiogenic tumor microenvironment which

promotes tumor growth. Chronic inflammation can contribute to tumor initiation

through inducing genotoxic stresses, to tumor maintenance by causing tumor cell

proliferation and to tumor progression by causing tumor cells to be invasive [7].

Additionally, subsets of innate immune cells known as myeloid derived

suppressor cells (MDSCs) and subsets of adaptive immune cells known as regulatory

20

T-cells (T-regs) have been shown to inhibit anti-tumor T-cell function [98-99].

MDSCs inhibit T-cell proliferation by metabolizing L-arginine in the tumor

microenvironment that is required for T-cell proliferation or by producing reactive

oxygen species (ROS) and peroxynitrite which can cause T-cell suppression [100]. T-

regs can either kill activated T-cells or inhibit them from proliferating through

multiple mechanisms including secretion of immunosuppressive cytokines like IL-10

and TGF-β [101-103].

Thus it is clear that the immune system plays a dual role in the tumor

microenvironment. The anti-tumor immune response is counter-acted by the creation

of a pro-tumor microenvironment through the secretion of pro-inflammatory cytokines

and through recruitment of cells that suppress the anti-tumor immune response. The

contribution of the immune system varies depending on the context of the tumor and

the composition of the tumor microenvironment. Moreover different components of

the immune system can be pro- or anti-tumor in the same microenvironment

depending on their temporal and spatial recruitment to the tumor microenvironment

[5].

We have identified anti-tumor CD4+ T-cells as being important to mediate the

effects of oncogene inactivation. This warrants a discussion of the role of CD4+ T-

cells in the tumor microenvironment. CD4+ T-cells often exert their anti-tumor effect

through innate immune cells like macrophages and eosinophils and their roles in the

tumor microenvironment are also discussed below.

21

1.6.1 Role of CD4+ T-cells in the tumor microenvironment

While studying the anti-tumor function of T-cells, focus has largely been on

the CD8+

T-cell population. This has been for three reasons. The first being, CD8+ T

cells are known to be cytotoxic and their ability to kill infected cells has been well

characterized. Moreover CD4+ T-cells are required to provide help to the CD8

+ T-cells

in order for them to perform their cytotoxic function, thus implicating the CD4+ T-

cells with an indirect role in anti-tumor immunity [104]. Secondly, most tumors that

were studied did not express MHC Class II molecules that are required to enable CD4+

T-cells to recognize tumor antigens. On the other hand, MHC Class I molecules,

expressed in all nucleated cells, were found on the surface of most tumor cells. Since

CD8+ T-cells recognize antigen only when presented by MHC Class I molecules, they

were presumed to be the primary mediators of immunity against tumors. Third, studies

using adoptive transfer of purified populations of T-cells into tumor bearing hosts

often showed that CD8+ T-cells could induce an anti-tumor response comparable to

CD4+ and CD8

+ T-cells together, provided that the CD8

+ T-cells were activated. Once

again, this argued for an indirect role of the CD4+ T-cells in this immune response

[105]. For these reasons, the role of CD8+ T-cells has been extensively characterized

in the context of anti-tumor immunity while that of CD4+ T-cells has been under

appreciated.

The earliest reports providing evidence that CD4+ T-cells could exert an anti-

tumor response independent of CD8+ T-cells date back to 1985 [106]. More recent

reports have shown that CD4+ T-cell anti-tumor immunity can be superior to CD8

+ T-

cell anti-tumor immunity in specific tumors [107]. The mechanism by which CD4+ T-

22

cells exert their anti-tumor effect is known to involve macrophages [108] or NK cells

[107] or eosinophils [109] depending on the kind of tumor and the context of CD4+ T-

cell activation. Some reports have also attributed a cytotoxic function to CD4+ T-cells

enabling them to directly kill tumor cells on which MHC Class II expression has been

upregulated by exposure to IFN-γ [110].

Depending on the context in which CD4+ T-cells are activated, they can

differentiate into a range of polarization states as described below (Table 2) [89]. The

polarization state of the CD4+ T-cells and the context of the tumor they infiltrate

determine their role in the tumor microenvironment. For example, increased TH-17

cell infiltration in human hepatocellular carcinoma correlates with a poor prognosis

[111]. Similar pro-tumor roles for TH-17 cells have been reported in mouse models of

mammary and epithelial cancers [112-113]. However in a model of B16 murine

melanoma, it has been shown that TH-17 cells can eradicate established tumors [114].

TH-1 and TH-2 subsets of CD4+ T-cells are also known to elicit anti-tumor

responses [115-116], but it is generally accepted that TH-1 cells play a more important

role in anti-tumor immunity [117] as TH-2 cells have also been implicated in pro-

tumor immunity in several models of cancer [91]. The different immune infiltrating

cells and the various cytokines, chemokines and other immune mediators secreted in

the tumor microenvironment determine whether the net effect of the immune response

is pro- or anti-tumor [118]. The role of CD4+ T-cells in cancer has not yet been clearly

elucidated due to the complex biology of these cells and the different effects they elicit

depending on their polarization and site of action. The work presented in this thesis

23

uncovers a novel role for CD4+ T-cells in remodeling the tumor microenvironment

upon oncogene inactivation.

1.6.2 Role of tumor associated macrophages (TAMs) in the tumor

microenvironment:

Similar to macrophages found in normal tissues, tumor associated

macrophages (TAMs) also have specialized functions. These functions are dependent

on the particular tumor microenvironment and anatomical location of the tumor [119].

Human clinical data from several different cancers such as breast, prostate, kidney and

bladder cancers, has shown that the presence of TAMs is correlated with poor

prognosis of disease [119]. This agrees with data generated from a mouse model of

breast cancer in which mice lacking macrophages, show slower progression of tumors

and lesser incidence of lung metastasis [120]. However, a small number of clinical

studies of TAMs in stomach cancer [121], colorectal cancer [122] and melanoma

[123] have shown that high levels of TAM infiltration correlate with favorable disease

prognosis. This illustrates the different roles that macrophages can play in different

tumor microenvironments.

Cytokine signals in the tumor microenvironment determine TAM functional

polarization. These signals determine macrophage receptor expression and cytokine

production thus determining macrophage function [124]. At any given time, the state

of macrophage polarization can lie in between a spectrum of states, the ends of which

are defined as M1 or classically activated macrophages and M2 or alternatively

activated macrophages. This nomenclature parallels the TH-1/TH-2 polarization states

24

of the CD4+ helper T-cells described earlier [124-125]. TH-1 cytokines like IFN-γ can

induce M1 macrophage polarization either alone or in conjunction with microbial

products like LPS or cytokines like TNF. They produce IL-12, IL-23, IL-1β, TNF, IL-

6 and reactive oxygen and nitrogen species. Reactive nitrogen species are formed due

to metabolism of arginine through the iNOS pathway, a hallmark of M1 macrophages.

These classically activated M1 macrophages can present antigens and can cause tumor

cell cytotoxicity [125].

On the other hand, TH-2 cytokines like IL-4 and IL-13 induce M2 polarization

of macrophages. These macrophages produce IL-10 and show increased expression of

IL-1 decoy receptor and IL-1RA [124, 126]. Alternatively activated macrophages

function to dampen the inflammatory response and enhance tissue remodeling and

repair. These macrophages can cause cellular proliferation through the generation of

ornithine and polyamines by metabolism of arginine through the arginase pathway, a

hallmark of M2 macrophages. These macrophages are responsible for tumor

progression.

TAMs are derived from circulating monocytes in response to monocyte

chemotactic factors derived from the tumor. One such factor that is frequently

produced by several different tumors is CCL2 or monocyte chemotactic protein-1

(MCP-1) [124, 127]. Other tumor derived macrophage chemoattractants include

colony-stimulating factor-1 (CSF-1), CCL3, CCL4, CCL5, CCL7, CCL8 and VEGF

[119]. TAM polarization is often skewed towards the M2 alternative state of activation

25

[128] and these macrophages can influence several aspects of tumor progression and

carcinogenesis as discussed below.

1.6.2.1 TAMs and tumor progression:

Promoting tumor angiogenesis: As described earlier, angiogenesis is required in order

for tumors to grow and become malignant. TAMs are capable of secreting several pro-

angiogenic factors such as VEGF, TNF-α, IL-8 and bFGF. TAMs can also secrete

enzymes that modulate angiogenesis such as MMP-2, MMP-7, MMP-9 and MMP-12

[119]. Furthermore, hypoxic regions of a tumor can also attract TAMs [129]. TAMs

that accumulate in regions of hypoxia upregulate hypoxia inducible transcription

factors HIF-1 and HIF-2 which can induce the expression of angiogenic proteins in

these TAMs. [130-132].

Suppressing the immune response: M1 macrophages can function as antigen

presenting cells and are robust inducers of an anti-tumor immune response; however

TAMs are often M2 macrophages which cannot perform these functions. In fact, M2

TAMs can suppress a T-cell mediated immune response by inhibiting T-cell

proliferation and activation by secreting immunosuppressive cytokines like IL-10,

TGF-β and prostaglandins [133-134].

Tumor cell growth: In various tumors, the presence of TAMs correlates with increased

tumor cell proliferation [135-137]. TAMs are known to upregulate the expression of

factors that promote tumor cell survival and proliferation such as EGF [138], PDGF,

hepatocytes growth factor, TGF-β [139] and bFGF [140].

26

Tumor invasion: TAMs are capable of secreting proteolytic enzymes like cathepsin-b

and various matrix metalloproteinases (MMPs) [139] that can cause areas of

extracellular matrix and basement membrane to breakdown. This allows the tumor

cells to invade into surrounding normal tissue.

Tumor metastasis: The presence of TAMs has also been correlated with increased

tumor metastasis. TAMs contribute to tumor cells leaving their primary site and

growth of tumor cells at secondary sites of metastasis [141-142]. In fact, De nardo

et.al. have done elegant studies in a mouse model of breast carcinoma showing that

IL-4 produced by TH-2 CD4+ T-cells can induce M2 TAMs to express EGF to promote

lung metastases of breast cancer [143].

It is important to note that the pro-tumor functions of TAMs described above

are highly dependent on the cytokine milieu of the tumor microenvironment and

depend on the context of the tumor. Different factors released in the tumor

microenvironment cause macrophages to express different gene programs that

determine their function. This function can also be anti-tumor in certain cases as

described below.

1.6.2.2 TAMs and tumor inhibition:

Although uncommon, certain tumor microenvironments have been shown to

harbor TAMs that can prevent tumor growth through different mechanisms:

Inhibiting tumor angiogenesis: TAMs in certain tumor microenvironments are known

to produce MMP-12. MMP-12 is an enzyme that is known to be involved in the

27

production of the potent angiogenic inhibitor angiostatin [144]. However, most reports

of TAMs in the tumor microenvironment suggest that they are pro-angiogenic.

Promoting tumor cell cytotoxicity and generating an anti-tumor response: In certain

tumor microenvironments, as the tumor grows, it remodels the surrounding stroma,

thus releasing pro-inflammatory cytokines that serve as danger signals to attract and

activate M1 macrophages [145]. These M1 TAMs metabolize L-arginine using the

iNOS enzyme which results in the production of reactive nitric oxide species which

cause tumor cell death [146]. In addition, they produce IL-12 and TNF-α which causes

further tumor cell death. These M1 macrophages can also act as antigen presenting

cells and present tumor antigens to T-cells in the tumor draining lymph nodes causing

activation of anti-tumor T-cells and their infiltration into the tumor thus contributing

to tumor eradication [147]. Macrophages can also interact with NK cells in some

tumor microenvironments to get activated and generate an anti-tumor response [148].

1.6.3 Role of eosinophils in the tumor microenvironment:

Eosinophils are granulocytic cells of the innate immune system. They are

found in circulation in the peripheral blood as well as in mucosal tissues and within

primary and secondary lymphoid organs [149]. These cells contain specialized

granules carrying cytotoxic cationic proteins like major basic protein (MBP) and

eosinophil peroxidase (EPO) in their cytoplasm [150-152]. Additionally, eosinophils

can secrete cytokines like IL-4, IL-5, IL-6, IL-10, IL-13 and TNF-α and G-MCSF.

Eosinophils are also rich sources of various lipid mediators like leukotrienes [149,

153].

28

Secretion of these mediators allows eosinophils to modulate the immune

microenvironment to cause anti-pathogen responses, recruitment of other immune

cells, tissue remodeling and repair. Eosinophils are recruited to their site of action by

IL-5 and eotaxin-1 often secreted by TH-2 cells. Historically eosinophils function as

effector cells of the TH-2 immune response and have been implicated in the immune

response to parasites like helminthes [154] and in allergic responses like asthma [149].

Eosinophils can also function as phagocytic cells and help in the clearance of bacterial

and viral infections [155].

Eosinophils can also influence the tumor microenvironment to generate both

pro- and anti-tumor responses. Like all the other immune cell populations discussed so

far, the contribution of eosinophils to the tumor microenvironment also depends on the

context of the tumor and the specific tumor microenvironment. However, unlike other

immune cell populations, their role in tumor progression has not been extensively

studied. Described below is the evidence for the role of eosinophils in cancer.

1.6.3.1 Eosinophils and tumor progression:

It has been shown that eosinophil ablation in a rodent model of squamous cell

carcinoma, delayed the onset of tumor development and reduced tumor burden

suggesting that eosinophils might play role in tumor promotion [156]. Eosinophils are

also known to play a role in angiogenesis and can secrete VEGF in hypoxic

microenvironments [157]. Eosinophils can also secrete other pro-angiogenic factors

like PDGF, bFGF and IL-6 [149] and have been shown to promote angiogenesis in

29

various pathological conditions involving tissue eosinophilia. It has been proposed that

this can occur in tumors as well [158].

1.6.3.1 Eosinophils and tumor inhibition:

Eosinophils can accumulate in a tumor microenvironment either as a result of a

TH-2 adaptive immune response [109] or independently [159]. Increased eosinophil

infiltration of tumors correlates with increased survival in patients with esophageal

squamous cell carcinoma, gastric cancer, head and neck cancer and colorectal

carcinoma [160] suggesting that eosinophils could play a role in inhibiting tumor

growth. Furthermore, Eotaxin-1/IL-5-/-

mice showed increased MCA induced

tumorigenesis which also suggests an anti-tumor role for eosinophils [161].

Possible mechanisms by which eosinophils can exert an anti-tumor effect

include tumor cell cytotoxicity by releasing eosinophil granules [162] and recruiting

an anti-tumor immune response dependent on eotaxin-1 and STAT-6. Interestingly

eosinophils have been shown to induce a TH-2 anti-tumor response contrary to

evidence that suggests that most TH-2 responses are pro-tumor [109].

30

Figure 1: A bi-transgenic mouse model of conditional MYC expression

Figure 1: A bi-transgenic mouse model of conditional MYC expression. The

tetracycline regulatory system for conditional oncogene expression. Doxycycline

prevents transcription of the target gene, MYC. In this model, the transactivating

protein (tTA is driven by a lymphocyte specific promoter, SRα and immunoglobulin

heavy chain enhancer, Eμ.

31

Table 1: Mechanisms of tumor regression upon oncogene inactivation

ONCOGENE

CANCER

MECHANISM OF

REGRESSION

BCR-ABL

Lymphoblastic leukemia

Apoptosis

c-MYC

T- and B-cell lymphoma,

Acute myeloid leukemia

Cell cycle arrest, Differentiation,

Apoptosis

Osteosarcoma

Differentiation

Hepatocellular

carcinoma

Apoptosis, Differentiation

Pancreatic islet cell

carcinoma

Growth arrest, Differentiation, Cell

adhesion, Vascular collapse

RAS

Melanoma

Apoptosis

Glioblastoma

Apoptosis

MET

Hepatocellular carcinoma

Decreased proliferation, Apoptosis

32

Table 2: CD4+ T-cell polarization and cytokine secretion profile

POLARIZATION

STATE

TRANSCRIPTION

FACTOR

INDUCTION

SECRETION

TH-1

T-bet

IL-12, IFN-γ

IFN-γ, TNF-α, IL-2, IL-10,

MCP-1, MIP1α

TH-2

GATA3

IL-4

IL-4,IL-5, IL-6, IL-10,

IL-25, IL-33

TH-17

ROR-γ

TGF-β, IL6,

IL-21,IL-1,

IL-23

IL-17A,IL-17F, IL-2,

IL-9, IL- 10, IL-21, TNF-α,

CCL-2

T-reg

FoxP3

TGF-β

TGF-β, IL-10

33

1.7 References:

1. Weinstein, I.B., Cancer. Addiction to oncogenes--the Achilles heal of cancer.

Science, 2002. 297(5578): p. 63-4.

2. Weinstein, I.B. and A. Joe, Oncogene addiction. Cancer Res, 2008. 68(9): p.

3077-80; discussion 3080.

3. Druker, B.J., et al., Efficacy and safety of a specific inhibitor of the BCR-ABL

tyrosine kinase in chronic myeloid leukemia. N Engl J Med, 2001. 344(14): p.

1031-7.

4. Dunn, G.P., et al., Cancer immunoediting: from immunosurveillance to tumor

escape. Nat Immunol, 2002. 3(11): p. 991-8.

5. Schreiber, R.D., L.J. Old, and M.J. Smyth, Cancer immunoediting: integrating

immunity's roles in cancer suppression and promotion. Science, 2011.

331(6024): p. 1565-70.

6. de Visser, K.E., A. Eichten, and L.M. Coussens, Paradoxical roles of the

immune system during cancer development. Nat Rev Cancer, 2006. 6(1): p. 24-

37.

7. Grivennikov, S.I., F.R. Greten, and M. Karin, Immunity, inflammation, and

cancer. Cell, 2010. 140(6): p. 883-99.

8. Apetoh, L., et al., Molecular interactions between dying tumor cells and the

innate immune system determine the efficacy of conventional anticancer

therapies. Cancer Res, 2008. 68(11): p. 4026-30.

9. Zitvogel, L., et al., The anticancer immune response: indispensable for

therapeutic success? J Clin Invest, 2008. 118(6): p. 1991-2001.

10. Zitvogel, L., O. Kepp, and G. Kroemer, Immune parameters affecting the

efficacy of chemotherapeutic regimens. Nat Rev Clin Oncol, 2011. 8(3): p.

151-60.

11. Escudier, B., et al., Sorafenib in advanced clear-cell renal-cell carcinoma. N

Engl J Med, 2007. 356(2): p. 125-34.

12. Hudis, C.A., Trastuzumab--mechanism of action and use in clinical practice.

N Engl J Med, 2007. 357(1): p. 39-51.

13. Karasarides, M., et al., B-RAF is a therapeutic target in melanoma. Oncogene,

2004. 23(37): p. 6292-8.

14. Pao, W., et al., EGF receptor gene mutations are common in lung cancers

from "never smokers" and are associated with sensitivity of tumors to gefitinib

and erlotinib. Proc Natl Acad Sci U S A, 2004. 101(36): p. 13306-11.

15. Croce, C.M., Oncogenes and cancer. N Engl J Med, 2008. 358(5): p. 502-11.

16. Adams, J.M., et al., The c-myc oncogene driven by immunoglobulin enhancers

induces lymphoid malignancy in transgenic mice. Nature, 1985. 318(6046): p.

533-8.

17. Alexander, W.S., J.W. Schrader, and J.M. Adams, Expression of the c-myc

oncogene under control of an immunoglobulin enhancer in E mu-myc

transgenic mice. Mol Cell Biol, 1987. 7(4): p. 1436-44.

18. Felsher, D.W. and J.M. Bishop, Reversible tumorigenesis by MYC in

hematopoietic lineages. Mol Cell, 1999. 4(2): p. 199-207.

34

19. Hanahan, D. and R.A. Weinberg, The hallmarks of cancer. Cell, 2000. 100(1):

p. 57-70.

20. Sakaguchi, A.Y., P.A. Lalley, and S.L. Naylor, Human and mouse cellular myc

protooncogenes reside on chromosomes involved in numerical and structural

aberrations in cancer. Somatic Cell Genet, 1983. 9(3): p. 391-405.

21. Gardner, L., Lee, L. and Dang, C., The c-Myc Oncogenic Transcription

Factor. 2002.

22. Oster, S.K., et al., The myc oncogene: MarvelouslY Complex. Adv Cancer Res,

2002. 84: p. 81-154.

23. Erikson, J., et al., Translocation of an immunoglobulin kappa locus to a region

3' of an unrearranged c-myc oncogene enhances c-myc transcription. Proc

Natl Acad Sci U S A, 1983. 80(24): p. 7581-5.

24. Wong, A.J., et al., Gene amplification of c-myc and N-myc in small cell

carcinoma of the lung. Science, 1986. 233(4762): p. 461-4.

25. Boxer, R.B., et al., Lack of sustained regression of c-MYC-induced mammary

adenocarcinomas following brief or prolonged MYC inactivation. Cancer Cell,

2004. 6(6): p. 577-86.

26. Jain, M., et al., Sustained loss of a neoplastic phenotype by brief inactivation of

MYC. Science, 2002. 297(5578): p. 102-4.

27. Pelengaris, S., et al., Reversible activation of c-Myc in skin: induction of a

complex neoplastic phenotype by a single oncogenic lesion. Mol Cell, 1999.

3(5): p. 565-77.

28. Jonkers, J. and A. Berns, Conditional mouse models of sporadic cancer. Nat

Rev Cancer, 2002. 2(4): p. 251-65.

29. Soucek, L. and G.I. Evan, The ups and downs of Myc biology. Curr Opin Genet

Dev, 2010. 20(1): p. 91-5.

30. Littlewood, T.D., et al., A modified oestrogen receptor ligand-binding domain

as an improved switch for the regulation of heterologous proteins. Nucleic

Acids Res, 1995. 23(10): p. 1686-90.

31. Pelengaris, S., M. Khan, and G.I. Evan, Suppression of Myc-induced apoptosis

in beta cells exposes multiple oncogenic properties of Myc and triggers

carcinogenic progression. Cell, 2002. 109(3): p. 321-34.

32. Rudolph, B., A.O. Hueber, and G.I. Evan, Reversible activation of c-Myc in

thymocytes enhances positive selection and induces proliferation and

apoptosis in vitro. Oncogene, 2000. 19(15): p. 1891-900.

33. Giuriato, S., et al., Conditional animal models: a strategy to define when

oncogenes will be effective targets to treat cancer. Semin Cancer Biol, 2004.

14(1): p. 3-11.

34. Freundlieb, S., The Tet System: Powerful, Inducible Gene Expression. 2007.

35. Shachaf, C.M., et al., MYC inactivation uncovers pluripotent differentiation

and tumour dormancy in hepatocellular cancer. Nature, 2004. 431(7012): p.

1112-7.

36. Flores, I., et al., Defining the temporal requirements for Myc in the

progression and maintenance of skin neoplasia. Oncogene, 2004. 23(35): p.

5923-30.

35

37. Tran, P.T., et al., Combined Inactivation of MYC and K-Ras oncogenes

reverses tumorigenesis in lung adenocarcinomas and lymphomas. PLoS One,

2008. 3(5): p. e2125.

38. Weinstein, I.B. and A.K. Joe, Mechanisms of disease: Oncogene addiction--a

rationale for molecular targeting in cancer therapy. Nat Clin Pract Oncol,

2006. 3(8): p. 448-57.

39. Chin, L., et al., Essential role for oncogenic Ras in tumour maintenance.

Nature, 1999. 400(6743): p. 468-72.

40. Fisher, G.H., et al., Induction and apoptotic regression of lung

adenocarcinomas by regulation of a K-Ras transgene in the presence and

absence of tumor suppressor genes. Genes Dev, 2001. 15(24): p. 3249-62.

41. Huettner, C.S., et al., Reversibility of acute B-cell leukaemia induced by BCR-

ABL1. Nat Genet, 2000. 24(1): p. 57-60.

42. Demetri, G.D., et al., Efficacy and safety of imatinib mesylate in advanced

gastrointestinal stromal tumors. N Engl J Med, 2002. 347(7): p. 472-80.

43. Ponzielli, R., et al., Cancer therapeutics: targeting the dark side of Myc. Eur J

Cancer, 2005. 41(16): p. 2485-501.

44. Vita, M. and M. Henriksson, The Myc oncoprotein as a therapeutic target for

human cancer. Semin Cancer Biol, 2006. 16(4): p. 318-30.

45. Sharma, S.V. and J. Settleman, Oncogene addiction: setting the stage for

molecularly targeted cancer therapy. Genes Dev, 2007. 21(24): p. 3214-31.

46. Borrello, M.G., et al., Induction of a proinflammatory program in normal

human thyrocytes by the RET/PTC1 oncogene. Proc Natl Acad Sci U S A,

2005. 102(41): p. 14825-30.

47. Ancrile, B., K.H. Lim, and C.M. Counter, Oncogenic Ras-induced secretion of

IL6 is required for tumorigenesis. Genes Dev, 2007. 21(14): p. 1714-9.

48. Sparmann, A. and D. Bar-Sagi, Ras-induced interleukin-8 expression plays a

critical role in tumor growth and angiogenesis. Cancer Cell, 2004. 6(5): p.

447-58.

49. Reimann, M., et al., Tumor Stroma-Derived TGF-beta Limits Myc-Driven

Lymphomagenesis via Suv39h1-Dependent Senescence. Cancer Cell, 2010.

17(3): p. 262-272.

50. Sodir, N.M., et al., Endogenous Myc maintains the tumor microenvironment.

Genes Dev, 2011. 25(9): p. 907-16.

51. Panaretakis, T., et al., The co-translocation of ERp57 and calreticulin

determines the immunogenicity of cell death. Cell Death Differ, 2008. 15(9): p.

1499-509.

52. Giuriato, S., et al., Sustained regression of tumors upon MYC inactivation

requires p53 or thrombospondin-1 to reverse the angiogenic switch. Proc Natl

Acad Sci U S A, 2006. 103(44): p. 16266-71.

53. Wu, C.H., et al., Cellular senescence is an important mechanism of tumor

regression upon c-Myc inactivation. Proc Natl Acad Sci U S A, 2007. 104(32):

p. 13028-33.

54. Evan, G.I., et al., Induction of apoptosis in fibroblasts by c-myc protein. Cell,

1992. 69(1): p. 119-28.

36

55. Shi, Y., et al., Role for c-myc in activation-induced apoptotic cell death in T

cell hybridomas. Science, 1992. 257(5067): p. 212-4.

56. Kaptein, J.S., et al., Anti-IgM-mediated regulation of c-myc and its possible

relationship to apoptosis. J Biol Chem, 1996. 271(31): p. 18875-84.

57. Hermeking, H. and D. Eick, Mediation of c-Myc-induced apoptosis by p53.

Science, 1994. 265(5181): p. 2091-3.

58. Prasad, V.S., et al., Upregulation of endogenous p53 and induction of in vivo

apoptosis in B-lineage lymphomas of E(mu)-myc transgenic mice by

deregulated c-myc transgene. Mol Carcinog, 1997. 18(2): p. 66-77.

59. Hsu, B., et al., Evidence that c-myc mediated apoptosis does not require wild-

type p53 during lymphomagenesis. Oncogene, 1995. 11(1): p. 175-9.

60. D'Agnano, I., et al., Myc down-regulation induces apoptosis in M14 melanoma

cells by increasing p27(kip1) levels. Oncogene, 2001. 20(22): p. 2814-25.

61. Russo, P., et al., c-myc down-regulation induces apoptosis in human cancer

cell lines exposed to RPR-115135 (C31H29NO4), a non-peptidomimetic

farnesyltransferase inhibitor. J Pharmacol Exp Ther, 2003. 304(1): p. 37-47.

62. Carmeliet, P. and R.K. Jain, Angiogenesis in cancer and other diseases.

Nature, 2000. 407(6801): p. 249-57.

63. Hanahan, D. and J. Folkman, Patterns and emerging mechanisms of the

angiogenic switch during tumorigenesis. Cell, 1996. 86(3): p. 353-64.

64. Chen, D., et al., Vascular smooth muscle cell growth arrest on blockade of

thrombospondin-1 requires p21(Cip1/WAF1). Am J Physiol, 1999. 277(3 Pt

2): p. H1100-6.

65. Martin-Manso, G., et al., Thrombospondin 1 promotes tumor macrophage

recruitment and enhances tumor cell cytotoxicity of differentiated U937 cells.

Cancer Res, 2008. 68(17): p. 7090-9.

66. Lawler, J., The functions of thrombospondin-1 and-2. Curr Opin Cell Biol,

2000. 12(5): p. 634-40.

67. Lawler, J., Thrombospondin-1 as an endogenous inhibitor of angiogenesis and

tumor growth. J Cell Mol Med, 2002. 6(1): p. 1-12.

68. Lawler, J., Thrombospondin 1. UCSD-Nature Molecule Pages, 2010.

69. Dameron, K.M., et al., Control of angiogenesis in fibroblasts by p53

regulation of thrombospondin-1. Science, 1994. 265(5178): p. 1582-4.

70. Schwarte-Waldhoff, I., et al., Smad4/DPC4-mediated tumor suppression

through suppression of angiogenesis. Proc Natl Acad Sci U S A, 2000. 97(17):

p. 9624-9.

71. Tikhonenko, A.T., D.J. Black, and M.L. Linial, Viral Myc oncoproteins in

infected fibroblasts down-modulate thrombospondin-1, a possible tumor

suppressor gene. J Biol Chem, 1996. 271(48): p. 30741-7.

72. Watnick, R.S., et al., Ras modulates Myc activity to repress thrombospondin-1

expression and increase tumor angiogenesis. Cancer Cell, 2003. 3(3): p. 219-

31.

73. Janz, A., et al., Activation of the myc oncoprotein leads to increased turnover

of thrombospondin-1 mRNA. Nucleic Acids Res, 2000. 28(11): p. 2268-75.

37

74. Hayflick, L., The Limited in Vitro Lifetime of Human Diploid Cell Strains. Exp

Cell Res, 1965. 37: p. 614-36.

75. Collado, M., et al., Tumour biology: senescence in premalignant tumours.

Nature, 2005. 436(7051): p. 642.

76. Michaloglou, C., et al., BRAFE600-associated senescence-like cell cycle arrest

of human naevi. Nature, 2005. 436(7051): p. 720-4.

77. Narita, M. and S.W. Lowe, Senescence comes of age. Nat Med, 2005. 11(9): p.

920-2.

78. Chen, Q., et al., Oxidative DNA damage and senescence of human diploid

fibroblast cells. Proc Natl Acad Sci U S A, 1995. 92(10): p. 4337-41.

79. Grandori, C., et al., Werner syndrome protein limits MYC-induced cellular

senescence. Genes Dev, 2003. 17(13): p. 1569-74.

80. Serrano, M., et al., Oncogenic ras provokes premature cell senescence

associated with accumulation of p53 and p16INK4a. Cell, 1997. 88(5): p. 593-

602.

81. Guney, I., S. Wu, and J.M. Sedivy, Reduced c-Myc signaling triggers

telomere-independent senescence by regulating Bmi-1 and p16(INK4a). Proc

Natl Acad Sci U S A, 2006. 103(10): p. 3645-50.

82. Coppe, J.P., et al., The senescence-associated secretory phenotype: the dark

side of tumor suppression. Annu Rev Pathol, 2010. 5: p. 99-118.

83. Coppe, J.P., et al., Senescence-associated secretory phenotypes reveal cell-

nonautonomous functions of oncogenic RAS and the p53 tumor suppressor.

PLoS Biol, 2008. 6(12): p. 2853-68.

84. Krtolica, A., et al., Senescent fibroblasts promote epithelial cell growth and

tumorigenesis: a link between cancer and aging. Proc Natl Acad Sci U S A,

2001. 98(21): p. 12072-7.

85. Parrinello, S., et al., Stromal-epithelial interactions in aging and cancer:

senescent fibroblasts alter epithelial cell differentiation. J Cell Sci, 2005.

118(Pt 3): p. 485-96.

86. Coppe, J.P., et al., Secretion of vascular endothelial growth factor by primary

human fibroblasts at senescence. J Biol Chem, 2006. 281(40): p. 29568-74.

87. Xue, W., et al., Senescence and tumour clearance is triggered by p53

restoration in murine liver carcinomas. Nature, 2007. 445(7128): p. 656-60.

88. Allavena, P., et al., The inflammatory micro-environment in tumor

progression: the role of tumor-associated macrophages. Crit Rev Oncol

Hematol, 2008. 66(1): p. 1-9.

89. Muranski, P. and N.P. Restifo, Adoptive immunotherapy of cancer using

CD4(+) T cells. Curr Opin Immunol, 2009. 21(2): p. 200-8.

90. DeNardo, D.G., P. Andreu, and L.M. Coussens, Interactions between

lymphocytes and myeloid cells regulate pro- versus anti-tumor immunity.

Cancer Metastasis Rev, 2010. 29(2): p. 309-16.

91. Johansson, M., D.G. Denardo, and L.M. Coussens, Polarized immune

responses differentially regulate cancer development. Immunol Rev, 2008.

222: p. 145-54.

38

92. Clemente, C.G., et al., Prognostic value of tumor infiltrating lymphocytes in

the vertical growth phase of primary cutaneous melanoma. Cancer, 1996.

77(7): p. 1303-10.

93. Naito, Y., et al., CD8+ T cells infiltrated within cancer cell nests as a

prognostic factor in human colorectal cancer. Cancer Res, 1998. 58(16): p.

3491-4.

94. Rilke, F., et al., Prognostic significance of HER-2/neu expression in breast

cancer and its relationship to other prognostic factors. Int J Cancer, 1991.

49(1): p. 44-9.

95. Palma, L., N. Di Lorenzo, and B. Guidetti, Lymphocytic infiltrates in primary

glioblastomas and recidivous gliomas. Incidence, fate, and relevance to

prognosis in 228 operated cases. J Neurosurg, 1978. 49(6): p. 854-61.

96. Dunn, G.P., C.M. Koebel, and R.D. Schreiber, Interferons, immunity and

cancer immunoediting. Nat Rev Immunol, 2006. 6(11): p. 836-48.

97. Giraudo, E., M. Inoue, and D. Hanahan, An amino-bisphosphonate targets

MMP-9-expressing macrophages and angiogenesis to impair cervical

carcinogenesis. J Clin Invest, 2004. 114(5): p. 623-33.

98. Gabrilovich, D.I., et al., Mechanism of immune dysfunction in cancer mediated

by immature Gr-1+ myeloid cells. J Immunol, 2001. 166(9): p. 5398-406.

99. Shimizu, J., S. Yamazaki, and S. Sakaguchi, Induction of tumor immunity by

removing CD25+CD4+ T cells: a common basis between tumor immunity and

autoimmunity. J Immunol, 1999. 163(10): p. 5211-8.

100. Gabrilovich, D.I. and S. Nagaraj, Myeloid-derived suppressor cells as

regulators of the immune system. Nat Rev Immunol, 2009. 9(3): p. 162-74.

101. Marie, J.C., et al., TGF-beta1 maintains suppressor function and Foxp3

expression in CD4+CD25+ regulatory T cells. J Exp Med, 2005. 201(7): p.

1061-7.

102. Sakaguchi, S., et al., Regulatory T cells: how do they suppress immune

responses? Int Immunol, 2009. 21(10): p. 1105-11.

103. Bopp, T., et al., Cyclic adenosine monophosphate is a key component of

regulatory T cell-mediated suppression. J Exp Med, 2007. 204(6): p. 1303-10.

104. Ossendorp, F., et al., Specific T helper cell requirement for optimal induction

of cytotoxic T lymphocytes against major histocompatibility complex class II

negative tumors. J Exp Med, 1998. 187(5): p. 693-702.

105. Melief, C.J., Tumor eradication by adoptive transfer of cytotoxic T

lymphocytes. Adv Cancer Res, 1992. 58: p. 143-75.

106. Greenberg, P.D., D.E. Kern, and M.A. Cheever, Therapy of disseminated

murine leukemia with cyclophosphamide and immune Lyt-1+,2- T cells. Tumor

eradication does not require participation of cytotoxic T cells. J Exp Med,

1985. 161(5): p. 1122-34.

107. Perez-Diez, A., et al., CD4 cells can be more efficient at tumor rejection than

CD8 cells. Blood, 2007. 109(12): p. 5346-54.

108. Corthay, A., et al., Primary antitumor immune response mediated by CD4+ T

cells. Immunity, 2005. 22(3): p. 371-83.

39

109. Mattes, J., et al., Immunotherapy of cytotoxic T cell-resistant tumors by T

helper 2 cells: an eotaxin and STAT6-dependent process. J Exp Med, 2003.

197(3): p. 387-93.

110. Heller, K.N., C. Gurer, and C. Munz, Virus-specific CD4+ T cells: ready for

direct attack. J Exp Med, 2006. 203(4): p. 805-8.

111. Zhang, J.P., et al., Increased intratumoral IL-17-producing cells correlate with

poor survival in hepatocellular carcinoma patients. J Hepatol, 2009. 50(5): p.

980-9.

112. Nam, J.S., et al., Transforming growth factor beta subverts the immune system

into directly promoting tumor growth through interleukin-17. Cancer Res,

2008. 68(10): p. 3915-23.

113. Xiao, M., et al., IFNgamma promotes papilloma development by up-regulating

Th17-associated inflammation. Cancer Res, 2009. 69(5): p. 2010-7.

114. Muranski, P., et al., Tumor-specific Th17-polarized cells eradicate large

established melanoma. Blood, 2008. 112(2): p. 362-73.

115. Hung, K., et al., The central role of CD4(+) T cells in the antitumor immune

response. J Exp Med, 1998. 188(12): p. 2357-68.

116. Nishimura, T., et al., Distinct role of antigen-specific T helper type 1 (Th1) and

Th2 cells in tumor eradication in vivo. J Exp Med, 1999. 190(5): p. 617-27.

117. Nishimura, T., et al., The critical role of Th1-dominant immunity in tumor

immunology. Cancer Chemother Pharmacol, 2000. 46 Suppl: p. S52-61.

118. Coussens, L.M. and Z. Werb, Inflammation and cancer. Nature, 2002.

420(6917): p. 860-7.

119. Lewis, C.E. and J.W. Pollard, Distinct role of macrophages in different tumor

microenvironments. Cancer Res, 2006. 66(2): p. 605-12.

120. Lin, E.Y., et al., Colony-stimulating factor 1 promotes progression of

mammary tumors to malignancy. J Exp Med, 2001. 193(6): p. 727-40.

121. Ohno, S., et al., The degree of macrophage infiltration into the cancer cell nest

is a significant predictor of survival in gastric cancer patients. Anticancer Res,

2003. 23(6D): p. 5015-22.

122. Funada, Y., et al., Prognostic significance of CD8+ T cell and macrophage

peritumoral infiltration in colorectal cancer. Oncol Rep, 2003. 10(2): p. 309-

13.

123. Piras, F., et al., The predictive value of CD8, CD4, CD68, and human

leukocyte antigen-D-related cells in the prognosis of cutaneous malignant

melanoma with vertical growth phase. Cancer, 2005. 104(6): p. 1246-54.

124. Mantovani, A., et al., Macrophage polarization: tumor-associated

macrophages as a paradigm for polarized M2 mononuclear phagocytes.

Trends Immunol, 2002. 23(11): p. 549-55.

125. Mantovani, A., et al., The chemokine system in diverse forms of macrophage

activation and polarization. Trends Immunol, 2004. 25(12): p. 677-86.

126. Gordon, S. and P.R. Taylor, Monocyte and macrophage heterogeneity. Nat

Rev Immunol, 2005. 5(12): p. 953-64.

127. Conti, I. and B.J. Rollins, CCL2 (monocyte chemoattractant protein-1) and

cancer. Seminars in Cancer Biology, 2004. 14(3): p. 149-154.

40

128. Sica, A., et al., Tumour-associated macrophages are a distinct M2 polarised

population promoting tumour progression: potential targets of anti-cancer

therapy. Eur J Cancer, 2006. 42(6): p. 717-27.

129. Murdoch, C., A. Giannoudis, and C.E. Lewis, Mechanisms regulating the

recruitment of macrophages into hypoxic areas of tumors and other ischemic

tissues. Blood, 2004. 104(8): p. 2224-34.

130. Burke, B., et al., Expression of HIF-1alpha by human macrophages:

implications for the use of macrophages in hypoxia-regulated cancer gene

therapy. J Pathol, 2002. 196(2): p. 204-12.

131. White, J.R., et al., Genetic amplification of the transcriptional response to

hypoxia as a novel means of identifying regulators of angiogenesis. Genomics,

2004. 83(1): p. 1-8.

132. Lewis, J.S., et al., Expression of vascular endothelial growth factor by

macrophages is up-regulated in poorly vascularized areas of breast

carcinomas. J Pathol, 2000. 192(2): p. 150-8.

133. Sica, A., et al., Autocrine production of IL-10 mediates defective IL-12

production and NF-kappa B activation in tumor-associated macrophages. J

Immunol, 2000. 164(2): p. 762-7.

134. Kambayashi, T., et al., Potential involvement of IL-10 in suppressing tumor-

associated macrophages. Colon-26-derived prostaglandin E2 inhibits TNF-

alpha release via a mechanism involving IL-10. J Immunol, 1995. 154(7): p.

3383-90.

135. Tsutsui, S., et al., Macrophage infiltration and its prognostic implications in

breast cancer: the relationship with VEGF expression and microvessel density.

Oncol Rep, 2005. 14(2): p. 425-31.

136. Wang, F.Q., et al., Matrilysin (MMP-7) promotes invasion of ovarian cancer

cells by activation of progelatinase. Int J Cancer, 2005. 114(1): p. 19-31.

137. Hamada, I., et al., Clinical effects of tumor-associated macrophages and

dendritic cells on renal cell carcinoma. Anticancer Res, 2002. 22(6C): p.

4281-4.

138. Goswami, S., et al., Macrophages promote the invasion of breast carcinoma

cells via a colony-stimulating factor-1/epidermal growth factor paracrine

loop. Cancer Res, 2005. 65(12): p. 5278-83.

139. Pollard, J.W., Tumour-educated macrophages promote tumour progression

and metastasis. Nat Rev Cancer, 2004. 4(1): p. 71-8.

140. Lewis, C. and C. Murdoch, Macrophage responses to hypoxia: implications

for tumor progression and anti-cancer therapies. Am J Pathol, 2005. 167(3):

p. 627-35.

141. Leek, R.D., et al., Association of macrophage infiltration with angiogenesis

and prognosis in invasive breast carcinoma. Cancer Res, 1996. 56(20): p.

4625-9.

142. Hanada, T., et al., Prognostic value of tumor-associated macrophage count in

human bladder cancer. Int J Urol, 2000. 7(7): p. 263-9.

41

143. DeNardo, D.G., et al., CD4(+) T cells regulate pulmonary metastasis of

mammary carcinomas by enhancing protumor properties of macrophages.

Cancer Cell, 2009. 16(2): p. 91-102.

144. O'Reilly, M.S., et al., Angiostatin: a novel angiogenesis inhibitor that mediates

the suppression of metastases by a Lewis lung carcinoma. Cell, 1994. 79(2): p.

315-28.

145. Lamagna, C., M. Aurrand-Lions, and B.A. Imhof, Dual role of macrophages

in tumor growth and angiogenesis. J Leukoc Biol, 2006. 80(4): p. 705-13.

146. Keller, R., M. Geiges, and R. Keist, L-arginine-dependent reactive nitrogen

intermediates as mediators of tumor cell killing by activated macrophages.

Cancer Res, 1990. 50(5): p. 1421-5.

147. Dunn, G.P., L.J. Old, and R.D. Schreiber, The immunobiology of cancer

immunosurveillance and immunoediting. Immunity, 2004. 21(2): p. 137-48.

148. Diefenbach, A., et al., Ligands for the murine NKG2D receptor: expression by

tumor cells and activation of NK cells and macrophages. Nat Immunol, 2000.

1(2): p. 119-26.

149. Shamri, R., J.J. Xenakis, and L.A. Spencer, Eosinophils in innate immunity: an

evolving story. Cell Tissue Res, 2011. 343(1): p. 57-83.

150. Gleich, G.J., D.A. Loegering, and J.E. Maldonado, Identification of a major

basic protein in guinea pig eosinophil granules. J Exp Med, 1973. 137(6): p.

1459-71.

151. Carlson, M.G., C.G. Peterson, and P. Venge, Human eosinophil peroxidase:

purification and characterization. J Immunol, 1985. 134(3): p. 1875-9.

152. Larson, K.A., et al., The identification and cloning of a murine major basic

protein gene expressed in eosinophils. J Immunol, 1995. 155(6): p. 3002-12.

153. Bandeira-Melo, C. and P.F. Weller, Eosinophils and cysteinyl leukotrienes.

Prostaglandins Leukot Essent Fatty Acids, 2003. 69(2-3): p. 135-43.

154. Klion, A.D. and T.B. Nutman, The role of eosinophils in host defense against

helminth parasites. J Allergy Clin Immunol, 2004. 113(1): p. 30-7.

155. Cline, M.J., J. Hanifin, and R.I. Lehrer, Phagocytosis by human eosinophils.

Blood, 1968. 32(6): p. 922-34.

156. Wong, D.T., et al., Eosinophil ablation and tumor development. Oral Oncol,

1999. 35(5): p. 496-501.

157. Nissim Ben Efraim, A.H., R. Eliashar, and F. Levi-Schaffer, Hypoxia

modulates human eosinophil function. Clin Mol Allergy, 2010. 8: p. 10.

158. Samoszuk, M., Eosinophils and human cancer. Histol Histopathol, 1997.

12(3): p. 807-12.

159. Cormier, S.A., et al., Pivotal Advance: eosinophil infiltration of solid tumors is

an early and persistent inflammatory host response. J Leukoc Biol, 2006.

79(6): p. 1131-9.

160. Ellyard, J.I., L. Simson, and C.R. Parish, Th2-mediated anti-tumour immunity:

friend or foe? Tissue Antigens, 2007. 70(1): p. 1-11.

161. Simson, L., et al., Regulation of carcinogenesis by IL-5 and CCL11: a

potential role for eosinophils in tumor immune surveillance. J Immunol, 2007.

178(7): p. 4222-9.

42

162. Huland, E. and H. Huland, Tumor-associated eosinophilia in interleukin-2-

treated patients: evidence of toxic eosinophil degranulation on bladder cancer

cells. J Cancer Res Clin Oncol, 1992. 118(6): p. 463-7.

43

CHAPTER 2: CONTRIBUTION OF

THE IMMUNE SYSTEM TO

ONCOGENE INACTIVATION

MEDIATED TUMOR REGRESSION

Portions of this chapter are adapted from "CD4+ T-Cells Contribute

to the Remodeling of the Microenvironment Required for Sustained

Tumor Regression upon Oncogene Inactivation"

Kavya Rakhra*, Pavan Bachireddy*, Tahera Zabuawala, Robert Zeiser,

Liwen Xu,1 Andrew Kopelman, Alice C. Fan, Qiwei Yang, Lior

Braunstein, Erika Crosby, Sandra Ryeom, and Dean W. Felsher

Cancer Cell, 18: 485-498, November 2010

*Authors contributed equally

44

2.1 Overview:

Using the conditionally regulatable model of MYC induced T-cell lymphoma

(Eµ-tTA X tet-O-MYC) described earlier [1], experiments were designed to investigate

the role of the adaptive immune system during tumor regression upon MYC

inactivation. Data were generated using both transplanted and primary tumor models

and a compelling role for CD4+ T-cells in remodeling the tumor microenvironment

upon MYC inactivation was identified. CD4+ T-cells remodel the tumor

microenvironment to cause inhibition of angiogenesis and induction of cellular

senescence programs which is required for sustained tumor regression to occur upon

MYC inactivation. These results were also extended to a conditionally regulatable

model of BCR-ABL induced pro-B-cell lymphocytic leukemia [2].

2.2 Contribution of the adaptive immune system:

The adaptive immune system is required for rapid, complete and sustained tumor

regression upon MYC inactivation:

The Eµ-tTAXtet-O-MYC murine model of lymphoma is an excellent model to

study the addiction of tumor cells to the MYC oncogene since the expression of MYC

can be spatially and temporally regulated. In this model, when MYC is turned on from

birth, mice develop lymphoma within 8-10 weeks. Upon MYC inactivation, the

established lymphoma undergoes sustained regression [1]. Tumor cell lines were

generated from primary tumors derived from this mouse model and transduced with a

luciferase transgene. This allowed transplantation of these MYC dependent tumors into

45

various immunocompetent and immmunodeficient hosts and allowed us to monitor

tumor growth and regression kinetics using bioluminescence imaging [3].

Tumor cell lines were transplanted into wildtype (WT) immunocompetent

hosts and into hosts with different immunodeficiencies such as RAG1-/-

, SCID,

RAG2cγc-/-

, CD4-/-

CD8-/-

, CD4-/-

and CD8-/-

hosts. Tumors were allowed to grow to a

comparable size in all cohorts of mice, as quantified by average radiance, a measure of

bioluminescence signal. At this stage, MYC was inactivated by treating these mice

with doxycycline (dox). Dox was administered both intra-peritoneally (i.p.) and orally

in the drinking water. We found that initial tumor regression upon oncogene

inactivation, occurred both in the presence and in the absence of the immune system as

tumors regressed in all cohorts of mice (Figure 1A, B). However, the quality and

extent of tumor regression varied significantly between WT and immunodeficient

hosts.

Severely immune compromised hosts (SCID and RAG2-/-

cc-/-

mice deficient

in the adaptive immune system and NK cells) demonstrated significantly delayed

kinetics of tumor regression upon MYC inactivation compared to wild-type (WT) hosts

Figure 1 D, SCID versus WT p < 0.001) and failed to execute complete tumor

elimination with up to 1,000-fold more minimal residual disease (MRD) after MYC

inactivation (Figure 1E, SCID versus WT, p < 0.001; RAG2-/-

cc-/-

versus WT p =

0.01 at the nadir of luciferase activity upon MYC inactivation). Similarly, less severely

immune compromised hosts (RAG1-/-

and CD4-/-

CD8-/-

) also exhibited delayed

kinetics (Figure 1B, D, RAG1-/-

versus WT, p = 0.02; CD4-/-

CD8-/-

versus WT, p =

46

0.02) and a significantly increased MRD (Figure 1E, RAG1-/-

versus WT, p = 0.01;

CD4-/-

CD8-/-

versus WT, p < 0.01). Hence, an intact immune system is required for

rapid and complete tumor regression.

Previously, we have described that after MYC inactivation some tumors will

recur within 2 months [4-5]. To determine if host immune status influenced the

frequency of tumor recurrence, we continued to observe mice for 80 days after MYC

inactivation. We observed that tumors recurred at a statistically significant increase in

frequency in SCID, RAG2-/-

cc-/-

, RAG1-/-

, and CD4-/-

CD8-/-

hosts (87.5%, 100%,

100%, and 80% respectively) compared to WT hosts (9%) (Figure 1F, immune

compromised hosts versus WT, p < 0.0001). Surprisingly, CD4-/-

but not CD8-/-

hosts

exhibited a significant influence on tumor recurrence (Figure 1F, 28.5%, 0%

respectively). Correspondingly, CD4+, but not CD8

+ T-cell deficiency alone was

sufficient to impede sustained tumor regression compared to WT mice (Figure 1F, WT

versus CD4-/-

p = 0.02). Similar results could be obtained using non-luciferase labeled

tumors (Figure 2A). By qPCR analysis it was confirmed that doxycycline treatment

resulted in similar suppression of transgenic MYC expression regardless of host

immune status (Figure 2B). Hence, defects in the host immune system prevented

sustained tumor regression upon MYC inactivation. Specifically a deficiency in CD4+

T-cells alone was sufficient to increase tumor recurrence upon oncogene inactivation.

47

CD4+ T-cells home to the tumor and are sufficient to restore sustained tumor

regression:

We further investigated the notion that CD4+ T-cells were playing a critical

role in the mechanism by which MYC inactivation was inducing tumor regression.

First, we examined if CD4+ T-cells were homing to the tumor site upon oncogene

inactivation. Upon adoptive transfer into RAG1-/-

hosts, luciferase+ CD4

+ T-cells

rapidly localized to the tumor site upon MYC inactivation as seen by bioluminescence

imaging of these tumors before and after MYC inactivation (Figure 3A). Inactivating

this oncogene causes CD4+ T-cells to localize at the tumor site as early as 4 days after

oncogene inactivation, peak at day 12 and persist up to 3 weeks after MYC

inactivation. Thus, MYC inactivation is associated with trafficking of CD4+ T-cells to

sites of tumor involvement. Notably, CD4+ T-cell depleted luciferase

+ splenocytes also

localized to the site of the tumor upon MYC inactivation, suggesting the recruitment of

additional host immune effector populations (Figure 4A).

Next, we evaluated if we could restore the ability of MYC inactivation to

induce sustained tumor regression in immune compromised hosts by adoptively

transferring specific lymphocyte populations into RAG1-/-

mice. By FACS analysis,

we confirmed reconstitution of effector cells (Figure 4B). As expected, RAG1-/-

mice

adoptively transferred with splenic lymphocytes exhibited sustained regression (Figure

3B). As described above, RAG1-/-

hosts demonstrated a significant amount of MRD

after MYC inactivation compared to WT hosts (Figure 3B, C, RAG1-/-

versus WT, p =

0.007). Importantly, reconstitution of immunodeficient hosts with naive CD8+ T-cells

48

continued to have a significant burden of MRD (Figure 3C, RAG1-/-

CD8+ versus WT,

p = 0.03) whereas reconstitution of RAG1-/-

hosts with naive CD4+ T-cells completely

eliminated MRD, similar to WT hosts upon MYC inactivation (Figure 3C, RAG1-/-

CD4+ versus WT, p = 0.09). Moreover, RAG1

-/- hosts adoptively transferred with

CD4+ T-cells exhibited statistically significant prolonged tumor-free survival

compared to RAG1-/-

or RAG1-/-

hosts reconstituted with CD8+

T-cells (Figure 3B, D,

RAG1-/-

versus RAG1-/-

CD4+ p = 0.007, RAG1

-/-CD4

+ versus RAG1

-/-CD8

+ p = 0.03).

Hence, restoration of CD4+ T-cells alone was sufficient for the ability of MYC

inactivation to eliminate MRD and induce sustained tumor regression.

The adaptive immune system is not required to induce proliferative arrest or apoptosis:

Previously, we have shown that upon MYC inactivation in a transgenic model

of T-ALL, tumor cells undergo proliferative arrest and apoptosis [1]. We determined if

the mechanism by which immune cells were contributing to the process of tumor

regression was through effects on proliferation and apoptosis of tumor cells before and

after MYC inactivation (Figure 5A, B). After 4 days of MYC inactivation, tumors from

both wildtype and immunodeficient hosts exhibited an overall loss of pleomorphic

characteristics as evidenced by a marked reduction in cell size and nuclear to

cytoplasmic ratio, similarly in both cohorts. Importantly, we observed that upon MYC

inactivation there were marked changes in the total number of cells per field and we

carefully controlled for these changes in our quantification of TUNEL and Ki67

staining to measure apoptosis and proliferation respectively.

49

To measure apoptosis, TUNEL staining was performed. Apoptosis occurred

equivalently upon MYC inactivation regardless of host immune status (Figure 5A)

suggesting that initial tumor regression occurs similarly regardless of the presence or

absence of an immune system. This suggests that initial tumor regression might be a

cell autonomous process. Quantification of TUNEL staining revealed a 2-fold increase

in the extent of apoptosis upon MYC inactivation in tumors from WT hosts (Figure

5B, WT MYC On versus Off, p = 0.05). Moreover, the apoptosis in regressing tumors

from WT hosts was not significantly different from that of regressing tumors in either

RAG1-/-

or CD4-/-

hosts (Figure 5B, WT versus RAG1-/-

, CD4-/-

MYC Off, p = 0.3 and

0.3 respectively). Finally there was a small but statistically insignificant increase in the

levels of apoptosis upon MYC inactivation in RAG1-/-

and CD4-/-

hosts (Figure 5B,

RAG1-/-

, CD4-/-

MYC On versus Off, p = 0.07 and 0.09 respectively). Hence, the

absence of the immune system does not seem to impede apoptosis of tumor cells upon

MYC inactivation.

Next, changes in cellular proliferation upon MYC inactivation were measured

by Ki67 staining. MYC inactivation in tumors from both WT and immunodeficient

hosts resulted in a significant reduction in Ki67 staining (Figure 5A, B, WT, RAG1-/-

,

CD4-/-

MYC On versus MYC Off, p < 0.01). Interestingly, in comparison to WT hosts,

RAG1-/-

but not CD4-/-

hosts, underwent a statistically significant further decrease in

Ki67 staining upon MYC inactivation (WT versus RAG1-/-

or CD4-/-

MYC Off p = 0.02

or p < 0.05, respectively). Thus, the absence of the host immune system either has no

effect or modestly enhanced the effect of MYC inactivation in inducing proliferative

arrest.

50

The adaptive immune system is required to inhibit angiogenesis in the tumor

microenvironment:

Since we could not account for the influence of host immune status on tumor

regression and recurrence upon MYC inactivation through effects on apoptosis or

proliferative arrest, we considered that other mechanisms were likely to be

responsible. We have previously reported that sustained regression of tumors upon

MYC inactivation requires the angiogenic switch to be turned off and this is achieved

by the secretion of anti-angiogenic extra-cellular matrix glycoprotein thrombospondin-

1 (TSP-1) [4]. We examined if an intact host immune system was required for MYC

inactivation to induce the shutdown of angiogenesis through the secretion of TSP-1.

We quantified TSP-1 expression in transplanted tumors before and after MYC

inactivation from WT, RAG1-/-

and CD4-/-

hosts, using immunohistochemistry. Upon

MYC inactivation there was a robust 3.5-fold induction of TSP-1 in tumors from WT

hosts but not in RAG1-/-

or CD4-/-

hosts (Figure 6A, WT versus RAG1-/-

, CD4-/-

MYC

Off, p = 0.001). Furthermore, while tumors in WT mice demonstrated very little

change in mean vascular density (MVD) as measured by CD31 staining upon MYC

inactivation (Figure 6B), RAG1-/-

and CD4-/-

mice exhibited a 5- and 12-fold, increase

respectively, in tumor MVD upon MYC inactivation (Figure 6A, B, RAG1-/-

MYC On

versus Off, p < 0.0001; CD4-/-

MYC On versus Off, p = 0.07). We also found that

tumors from CD8-/-

hosts showed induction of TSP-1 expression upon MYC

inactivation (data not shown). Thus, the absence of host immune effectors, in

51

particular CD4+ T-cells, markedly impairs the ability of MYC inactivation to shut

down angiogenesis.

Finally, our results suggested that TSP-1 expression requires host immune

cells and specifically CD4+ T cells. Indeed, we found that TSP-1 protein expression is

markedly decreased in spleens of immune compromised versus wild type hosts (Figure

6C). Upon isolating CD4+ T-cells from wild type spleens, we show that TSP-1

production is induced upon activation of CD4+ T-cells (Figure 6D), thus

demonstrating that CD4+ T-cells are a source of TSP-1.

Thrombospondin expression is required for sustained tumor regression upon MYC

inactivation:

Our results suggested to us the possibility that specific cytokines may be

critical to the remodeling of the tumor and the tumor microenvironment upon MYC

inactivation. We used two approaches to investigate the role of TSP-1. First, we

reconstituted RAG1-/-

mice with splenocytes from either TSP-1,2+/+

(WT) or TSP-1,2-/-

mice. Both TSP-1 and 2 have been implicated in the inhibition of angiogenesis and

have similar structural domains [6-7]. By FACS analysis, we verified equivalent

immune reconstitution (Figure 7A). Indeed, RAG1-/-

mice reconstituted with

TSP-1,2-/-

splenocytes completely failed to protect from sustained tumor regression

upon MYC inactivation compared to RAG1-/-

mice reconstituted with WT splenocytes

(Figure 7B, relapse rate WT versus TSP-1,2-/-

, 10% versus 100%, p = 0.02). We

conclude that TSP expression in immune effectors is important for sustained tumor

regression upon MYC inactivation.

52

Next, we addressed whether we could bypass the requirement for TSP-1

expression from host immune cells, by artificially introducing TSP-1 into tumor cells.

We compared tumor recurrence upon MYC inactivation in RAG1-/-

hosts transplanted

with tumors transduced with an empty vector control versus tumors transduced with a

TSP-1 expression vector. TSP-1 overexpressing tumors exhibited a delay in kinetics

(mean latency 80 versus 102 days) and a decreased frequency of tumor recurrence

(100% versus 40%) resulting in a statistically significant survival advantage (Figure

7C, RAG1-/-

TSP-1+ versus RAG1

-/-, p = 0.02). Thus, TSP-1 overexpression of tumor

cells is sufficient to increase the duration and frequency of sustained tumor regression

upon MYC inactivation in immune compromised hosts.

Encouraged by these results, we used our tumor model to study the effect of

3TSR, a synthetic peptide based drug designed to incorporate the three

thrombospondin repeats (TSR) that are known to mediate the anti-angiogenic activity

of TSP-1 [8]. We transplanted tumor cell lines into 2 cohorts of SCID mice. After

tumors had reached a comparable size, we inactivated MYC in both cohorts. Upon

MYC inactivation, one cohort was treated with a daily injection of 3 TSR (a gift from

Jack Lawler) while the other cohort received a mock injection containing PBS. When

we compared tumor recurrence upon MYC inactivation, we found that median survival

in the control cohort was 18 days compared to 23 days in the cohort treated with 3

TSR. Although there was a slight increase in survival with 3 TSR drug treatment, this

was not found to be statistically significant (Figure 7D).

53

The adaptive immune system is required to induce cellular senescence upon MYC

inactivation:

Another mechanism that contributes to sustained tumor regression upon

oncogene inactivation, in this conditional model of MYC induced lymphoma is the

induction of cellular senescence [9]. Since cellular senescence is known to be

governed by the inflammatory signaling pathway [10-12], we investigated whether

induction of cellular senescence was influenced by the immune system. We

investigated this by assaying for levels of senescence-associated acidic β-gal (SA- β -

Gal) activity and the induction of cyclin dependent kinase inhibitors like p16INK4a

and p21. Tumors from WT hosts expressed a 20-fold increase in (SA-β-Gal) activity

upon MYC inactivation and demonstrated a 26- and 6-fold increase in senescence-

associated markers, p16INK4a and p21, respectively, upon MYC inactivation (Figure

8A, B). In contrast, MYC inactivation in tumors from RAG1-/-

and CD4-/-

mice did not

result in an increase in SA-ß-Gal or in the induction of p16INK4a or p21 (Figure 8A,

B, WT versus RAG1-/-

MYC Off SA-ß-Gal p = 0.01, p16 staining p = 0.002, p21

staining p = 0.01. WT versus CD4-/-

MYC Off SA- ß-Gal, p = 0.009, p16 staining, p =

0.0005, p21 staining, p = 0.004). Thus, in immune deficient mice, MYC inactivation is

impeded from inducing cellular senescence in tumor cells. Notably, CD4+ T-cells

specifically appeared to be required for this induction of cellular senescence.

54

Understanding the cytokine profile in the tumor microenvironment in the presence and

absence of the immune system:

The processes of angiogenesis and cellular senescence are governed by the

secretion of several different cytokines. The angiogenic switch is determined by a

delicate balance of pro-angiogenic factors like VEGF and anti-angiogenic factors like

TSP-1 [13]. Similarly recent findings have suggested that cytokine loops might drive

cellular senescence [14]. We now know that cytokines like IL-6 and IL-8 are required

for both replicative and oncogene induced senescence to occur [10-11].

In our tumor model, we have demonstrated that the presence of the immune

system is required for the shutdown of angiogenesis and induction of cellular

senescence to occur upon MYC inactivation. Moreover, cytokines are the key

mediators of immune cell functions. Thus, we decided to assay levels of various

cytokines in the tumor microenvironment before and after MYC inactivation, in the

presence and absence of an immune system using the luminex assay. The limitation of

this assay is that we were only able to gauge levels of the 21 mouse cytokines that this

assay has been optimized for.

We measured relative fold changes in cytokine levels upon MYC inactivation

in tumors from WT and RAG1-/-

hosts (Figure 9A). MYC inactivation in tumors from

WT compared to RAG1-/-

hosts revealed an up regulation of anti-proliferative and

anti-angiogenic (“anti-tumor”) cytokines that suggest potential involvement by other

immune effectors. Eotaxin-1 and IL-5 (Figure 9A, WT versus RAG1-/-

fold change

upon MYC inactivation p = 0.02 and p = 0.003 respectively) are potent TH2 cytokines

55

that have been implicated in the recruitment of an eosinophil-mediated anti-tumor

inflammatory response [15]. IFN- was observed to increase over 4-fold upon MYC

inactivation in the WT hosts with virtually no change in the absence of the host

immune system (WT versus RAG1-/-

fold change upon MYC inactivation p = 0.03).

On the other hand, TNF- was significantly downregulated in RAG1-/-

hosts (RAG1-/-

MYC On versus Off, p = 0.02), while its upregulation was close to statistical

significance in the WT hosts (WT MYC On versus Off, p = 0.07). Both cytokines have

been established as critical mediators of potent CD4+ anti-tumor activity [16-17].

Interestingly, MCP-1, a potent chemo-attractant of inflammatory tumor-associated

macrophages (TAMs) [18-19], was significantly downregulated in the tumors from

immunodeficient hosts compared to WT hosts (WT versus RAG1-/-

fold change upon

MYC inactivation p = 0.008).

Further, we also measured the downregulation of “pro-tumor” cytokines in

tumors from WT and RAG1-/-

hosts. Upon MYC inactivation, vascular endothelial

growth factor (VEGF) was significantly downregulated almost 4-fold in WT hosts

(WT MYC On versus Off, p = 0.01) whereas no significant change in its expression

could be detected in tumors from immunodeficient hosts. IL-1 levels were

significantly decreased in WT hosts compared to RAG1-/-

hosts upon MYC

inactivation (WT versus RAG1-/-

fold change upon MYC inactivation, p = 0.02);

downregulation of these two cytokines suggests enhanced suppression of angiogenesis

in the presence of an intact host immune system upon MYC inactivation [20-21].

56

Finally, RAG1-/-

hosts that had been reconstituted with CD4+ T-cells exhibited

similar changes in chemokine expression to WT hosts upon MYC inactivation (Figure

9B). The anti-tumor cytokines (eotaxin, IFN- and RANTES) increased, while the pro-

tumor cytokine, VEGF decreased in protein expression (Figure 9B). Overall, we

conclude that changes in the cytokine milieu in the tumor microenvironment upon

MYC inactivation are profoundly influenced by host immune status and that CD4+ T-

cells alone appear to be responsible for the regulation of many of these changes.

2.3 Contribution of the innate immune system:

Chemokines that attract macrophages and eosinophils are upregulated upon MYC

inactivation in tumors regressing in WT hosts:

We observed that there was a 3-fold higher level of MCP-1 in tumors from WT

compared to RAG1-/-

hosts when MYC was on compared to a 7-fold higher expression

of MCP-1 in tumors from WT compared to RAG1-/-

hosts upon MYC inactivation

(Figure 9C, WT versus RAG1-/-

MYC ON, p = 0.001, MYC Off p = 0.02). We

observed similar results for monocyte chemoattractant protein-3 (MCP-3), which can

also attract macrophages to tissues and is known to be produced by various tumor cells

[22] (Figure 9D, WT versus RAG1-/-

MYC ON 2-fold higher expression in WT, p =

0.02, MYC Off 7-fold higher expression in WT p = 0.006).

The most dramatic differences between the WT and RAG1-/-

tumor

microenvironments were observed in the protein levels of eotaxin-1. Eotaxin-1 levels

appear to be significantly higher in the WT microenvironment compared to the

57

RAG1-/-

microenvironment even when MYC is on. (Figure 9E, WT versus RAG1-/-

MYC On, 8-fold higher expression in WT, p = 0.04). Upon MYC inactivation, there is

an increase in eotaxin-1 expression in WT hosts while there is no change in expression

in RAG1-/-

hosts (WT versus RAG1-/-

MYC Off, 20-fold higher expression in WT, p =

0.007).

Macrophages infiltrate the WT and CD8-/-

tumor microenvironment upon MYC

inactivation:

After observing increased levels of expression of macrophage chemoattractants

like MCP-1 and MCP-3 in the WT tumor microenvironment, we investigated whether

there was a difference in macrophage recruitment to the tumor in WT and RAG1-/-

hosts before and after MYC inactivation.

We measured the amount of macrophage infiltration by staining tumor sections

before and after MYC inactivation for F480, a macrophage surface marker. We

performed immunohistochemistry and quantified the amount of macrophages stained

and found that upon MYC inactivation, macrophage recruitment occurred in tumors

from WT hosts but not in tumors from RAG1-/-

hosts (Figure 10A, B, WT versus

RAG1-/-

p = 0.004). This correlated with our observation of increased expression of

macrophage chemoattractants upon MYC inactivation in tumors from WT compared to

RAG1-/-

hosts (Figure 9C, D).

We also investigated macrophage infiltration in tumors transplanted into CD4-/-

and CD8-/-

hosts. As we had identified that CD4+ T-cells played a critical role in

mediating sustained tumor regression and previous literature has implicated CD4+

T-

58

cells of the tumor microenvironment in the recruitment, differentiation and activation

of macrophages [23], we checked whether tumors growing in CD4-/-

hosts had

impaired macrophage recruitment. Upon MYC inactivation, tumors growing in CD4-/-

hosts had significantly less macrophage infiltration compared to tumors form WT and

CD8-/-

hosts (Figure 10A, B, WT versus CD4-/-

MYC Off, p < 0.0001, CD4-/-

versus

CD8-/-

MYC Off, p < 0.0001).

Furthermore, we observed that amongst WT, RAG1-/-

, CD4-/-

and CD8-/-

hosts,

only tumors from CD8-/-

hosts were infiltrated by macrophages when MYC was on.

Interestingly, upon MYC inactivation, tumors from CD8-/-

hosts had the highest

amount of macrophage infiltration (Figure 10A, B, CD8-/-

versus WT, 10-fold higher

in the CD8-/-

, MYC Off, p < 0.0001). These results suggest that CD4+ T-cells are

required for macrophage recruitment to the tumor microenvironment upon MYC

inactivation. At this time, we have not investigated the expression levels of MCP-1

and MCP-3 in tumor lysates from CD4-/-

and CD8-/-

hosts.

Macrophages cultured from WT tumor bearing mice express both iNOS and

arginase-1:

After observing macrophages in the tumor microenvironment of WT mice

upon MYC inactivation, we wanted to characterize these macrophages to study

whether they were pro- or anti-tumor. To do this, we first attempted to isolate

macrophages from the tumor microenvironment using magnetically activated cell

sorting (MACS). However, the number of macrophages obtained using this technique

was insufficient to perform RNA extraction experiments.

59

To circumvent this issue, we isolated splenic macrophages from tumor bearing

WT and SCID mice and cultured them in vitro as described before [24]. We then used

qPCR analysis to investigate which macrophage markers were upregulated before and

after MYC inactivation.

Our results show that splenic macrophages from WT tumor bearing mice

before and after MYC inactivation express equivalent levels of iNOS and arginase-1.

Splenic macrophages from tumor bearing SCID mice did not show appreciable levels

of expression of iNOS and arginase-1 (Figure 11A, B, WT versus SCID, MYC On,

iNOS p = 0.04, arginase-1 p = 0.01 , MYC Off, iNOS p = 0.007 , arginase-1, p <

0.0001). Instead, splenic macrophages from SCID mice showed increased expression

of arginase-2 both before and after MYC inactivation compared to splenic

macrophages isolated from WT mice (Figure 11C, WT versus SCID, MYC Off p <

0.0001).

As described in the introduction to this thesis, M1 macrophages produce iNOS

while M2 macrophages produce arginase-1. Arginase-2 is an isoform of the arginase-1

gene and both these isoforms can metabolize arginine into urea and ornithine [25].

Arginase-1 is usually expressed cytoplasmically in hepatic tissues where as arginase-2

is expressed mitochondrially in non-hepatic tissues [26]. The role of arginase-2

expression in determining macrophage polarity is not clear. There have been reports

suggesting that arginase-2 expressing macrophages might be polarized towards the M1

phenotype in experimental atherosclerosis [27].

60

Interestingly we also found that upon MYC inactivation, splenic macrophages

from WT tumor bearing hosts expressed significantly higher levels of TSP-1

compared to when MYC was on. Macrophages from SCID hosts expressed

significantly lower levels of TSP-1 before and after MYC inactivation compared to

macrophages form WT hosts (Figure 11D, WT MYC On versus MYC Off p = 0.001,

WT versus SCID, MYC Off, p = 0.0001). This suggests that macrophages could be a

potential source of TSP-1 in the tumor microenvironment upon MYC inactivation,

described to occur in section 2.2.

2.4 Contribution of T-cells to regression of primary MYC induced

lymphoma:

Characterizing the contribution of the immune system to tumor regression mediated by

MYC inactivation in a primary model of MYC induced T-cell lymphoma:

All of the experiments described above have been performed by transplanting

tumor cell lines into various WT and immunodeficient hosts. A caveat of this

experimental design is that results obtained from these experiments might be

influenced by the fact that primary tumors were adapted to growth in-vitro while

generating tumor cell lines. Furthermore, the host immune response elicited by a

transplanted tumor may differ from the immune response to a tumor that arises

spontaneously within the host. To address whether the immune system could influence

shut down of angiogenesis and induction of cellular senescence in a spontaneously

61

arising tumor, we performed experiments in primary tumor hosts of the murine Eµ-

tTA X tet-O-MYC lymphoma model [1].

Since 90% of the tumors arising in this mouse model are known to be

CD4+CD8

+, we were unable to use antibody mediated depletion of T-cells to study the

effect of T-cell function in primary transgenic tumor regression upon MYC

inactivation. Instead, we inhibited T-cell function in primary tumor hosts using

Cyclosporine A, a drug obtained from the fungus, Tolypocladium inflatum, which

prevents T-cell activation and function through inhibiting the N-FAT pathway [28].

Notably, we first determined that cyclosporine A did not have any direct effects on the

proliferation of tumor cells in vitro (Figure 12A).

Compared to untreated primary transgenic mice, cyclosporine A treated

primary transgenic mice illustrated a marked inhibition of the ability of MYC

inactivation to induce both cellular senescence as measured by staining for SA β-

galactosidase (Figure 12B, 70% versus 1%, p < 0.01), p16 (Figure 12B, 6% versus

2%, p < 0.05) and p21 (Figure 12B, 0.5% versus 0.1%, p < 0.01) as well as the

suppression of angiogenesis as measured by decrease in staining for CD31 (Figure

12B, 0.2% versus 0.4%, p = 0.05) and the induction of TSP-1 (Figure 12B, 6% versus

1%, p = 0.0006). Thus, cyclosporine A mediated immune suppression in the primary

tumor model blocked the ability of MYC inactivation to induce senescence and shut

down angiogenesis. We observed no effects on apoptosis as measured by TUNEL

staining (data not shown). However, interestingly, cyclosporine A treatment may

suppress the ability of MYC inactivation to induce proliferative arrest, suggesting that

http://en.wikipedia.org/wiki/Tolypocladium_inflatum

62

in primary tumors, cyclosporine A mediated suppression of the immune system

engenders this additional consequence. Long term experiments to check whether

cyclosporine A treated primary tumor hosts would relapse upon MYC inactivation

were inconclusive due to nephrotoxicity caused by cyclosporine A upon frequent

administration.

2.5 Contribution of the adaptive immune system in other models of

oncogene induced hematologic malignancies:

Characterizing the contribution of the immune system to tumor regression mediated by

oncogenes other than MYC:

After establishing a significant role for the immune system in the regression of

lymphomas upon MYC inactivation, we wanted to investigate whether the immune

response would contribute similarly to the regression of hematopoietic tumors induced

by oncogenes other than MYC. To test this, we used conditionally regulatable models

of RAS induced lymphoma (Eµ-tTA X tet-O-RAS) and BCR-ABL induced pro-B-cell

acute lymphocytic leukemia (Eµ-tTA X tet-O-BCR-ABL).

Tumor cell lines were derived from primary conditionally regulatable RAS

induced tumors and transplanted sub-cutaneously into WT and RAG1-/-

mice. After

allowing tumors to grow to a comparable size, RAS was inactivated by administering

dox to the mice intra-peritoneally and orally in their drinking water. Tumor regression

was seen to occur in both WT and RAG1-/-

hosts. These mice were followed up to 6

63

months post RAS inactivation and no evidence of tumor relapse was seen either in WT

or RAG1-/-

hosts (data not shown).

We then tested the contribution of the immune system to BCR-ABL

inactivation in transplanted tumors derived from cell lines generated from a

conditionally regulatable model of BCR-ABL induced B-ALL. Similar to MYC

inactivation, tumors underwent sustained regression upon BCR-ABL inactivation in

WT hosts while 100% of the immunodeficient hosts relapsed within 14 days of BCR-

ABL inactivation (Figure 13A, WT versus RAG1-/-

, p = 0.006). Hence, BCR-ABL

inactivation also induces sustained tumor regression only in immune intact hosts. We

demonstrate that a host immune system is required for BCR-ABL inactivation in B-

ALL to induce cellular senescence, TSP-1 expression and sustained tumor regression.

We conclude that for both MYC and BCR-ABL inactivation, an intact host immune

system is required to elicit oncogene addiction.

We investigated the effect of host immune status on the ability of BCR-ABL

inactivation to induce changes in the tumor microenvironment (Figure 13B). Upon

BCR-ABL inactivation, there was a non-significant decrease in Ki67 expression in

tumors transplanted into immunocompetent hosts. In tumors from immunodeficient

hosts, Ki67 expression upon BCR-ABL inactivation did not change. Ki67 expression

was higher in tumors transplanted into immunodeficient hosts compared to those

transplanted into immune intact hosts (Figure 13B, WT BCR-ABL off versus

immunodeficient BCR-ABL off p = 0.03). Cellular senescence increased upon BCR-

ABL inactivation in tumors from wild type hosts versus immunodeficient hosts as

64

measured by increased SA-β-gal staining (4% versus 0.4%, p = 0.05), p16 staining

(0.1% versus 0%) and p21 staining (0.3% versus 0%). Finally, there was a 3-fold

increase in TSP-1 upon BCR-ABL inactivation in tumors from immunocompetent

hosts while TSP-1 expression did not change upon BCR-ABL inactivation in

immunodeficient hosts (Figure 13B, TSP-1 panel, WT BCR-ABL on versus BCR-ABL

off, p < 0.0001; WT BCR-ABL Off versus immunodeficient BCR-ABL Off, p =

0.0001). We were unable to, measure any significant CD31 expression in the

BCR-ABL induced tumors.

2.6 Contribution of an antigen specific immune response:

Differential recruitment of regulatory T-cells (T-regs) to the tumor microenvironment

upon MYC inactivation:

T-regs are a population of immune cells that can suppress a T-cell mediated

immune response. This has evolved from a need to inhibit auto-reactive

T-cells and to keep immune responses to foreign antigens in check [29-30]. The best

characterized population of suppressor T-cells are the CD4+CD25

+ Foxp3 expressing

regulatory T-cells. Since we had evidence that CD4+ T-cells home to the tumor

microenvironment upon MYC inactivation, (Figure 3A), we decided to investigate

whether a subset of these cells were T-regs.

We used immunohistochemistry to test for the expression of Foxp3, a

transcription factor responsible for the development of T-regs [31], in tumor sections

before and after MYC inactivation from WT and RAG1-/-

hosts. We observed an 8-fold

65

increase in Foxp3 expression upon MYC inactivation in tumors from WT hosts (Figure

14A, B MYC On versus MYC Off, p = 0.002). As expected, tumors in RAG1-/-

hosts

did not show significant Foxp3 expression as these hosts are T-cell deficient.

Antigen specificity of the anti-tumor response to transplanted MYC induced tumors:

We wanted to investigate whether tumors from the EµtTAXtet-O-MYC model

could elicit an antigen specific immune response upon transplantation into WT hosts.

We tested this indirectly by studying whether anti-tumor immune memory was

generated in WT hosts in which tumors had previously regressed upon MYC

inactivation. The rationale behind this experiment was that immune memory is always

generated in response to specific antigens and if anti-tumor immune memory was

generated against MYC induced lymphomas, this would suggest that a tumor antigen

specific immune response had occurred.

We generated a cohort of WT mice in which tumors were established and

underwent regression by MYC inactivation. After complete tumor regression was

achieved, doxycycline delivery was removed from these mice. We then identified the

minimum number of luciferase labeled tumor cells required to be transplanted into

naïve WT hosts in order to achieve sub-cutaneous tumor growth. This minimum

number of tumor cells was transplanted into naïve WT mice and WT mice in which

tumors had previously undergone sustained regression. Tumor growth was monitored

using bioluminescence imaging. We found that while tumors were able to grow in the

naïve mice, all the mice that were re-challenged with tumor remained tumor free

(Figure 15, Naïve WT versus Re-challenged WT, p < 0.001).

66

Figure 1: An intact immune system is required for sustained tumor regression

67

Figure 1: An intact immune system is required for sustained tumor regression.

1(A,B): Graphical representation and representative data are shown of tumor

regression and relapse kinetics as measured by bioluminescence imaging. Luciferase-

labeled tumor cell lines from our conditional mouse T-ALL model [1] were injected

subcutaneously into different cohorts of mice (WT n = 11, CD8-/-

n = 7, CD4-/-

n = 6,

CD4-/-

CD8-/-

n = 5, SCID n = 8, RAG1-/-

n = 7, RAG2-/-

cc-/-

n = 3) and tumor

regression and relapse kinetics were monitored. MYC was inactivated by administering

doxycycline (dox) to the mice when tumors reached a comparable bioluminescence

signal (108p/s/sr/cm

2). Data is presented as bioluminescence signal (average radiance)

plotted against time after MYC inactivation. 1(C): Representative bioluminescence

images of tumors regressing in the different immunodeficient hosts. Data shown is

representative of 3 different experiments. 1(D): Quantitative analysis of tumor

regression in the indicated hosts 8 days post MYC inactivation. 1(E): Quantification of

minimum residual disease in the indicated hosts at the maximally regressed state of the

tumor. Data is presented as the minimum bioluminescence signal after MYC

inactivation. Each symbol represents an individual animal. Average signal for each

cohort is indicated by solid black lines. 1(F): Kaplan Meier curves of tumor-free

survival in the various immunodeficient genotypes. A mouse was scored as a relapse

when its tumor bioluminescence signal first begins to increase after tumor regression.

The table shows the results of a log-rank test to compare the WT survival curve with

those of the indicated immunodeficient mice. Data shown are representative 3

different experiments repeated with 2 cell lines and 1 primary tumor.

68

For panels 1(D E), statistical significance (p value evaluated by unpaired Student‟s t-

test) is shown. * p < 0.01, ** p < 0.001, *** p < 0.0001

69


upon MYC inactivation


upon MYC inactivation. 2(A): Kaplan-Meier survival curve of WT versus. SCID

70

mice. Mice were transplanted with 10^7 unlabeled lymphoma cells and tumors were

treated with doxycyline when they reached a size of 1000 mm3. Mice were scored as

relapses when they showed signs of morbidity. 2(B): Tumors were harvested 0 and 4

days after MYC inactivation, snap frozen in liquid nitrogen and stored in -80oc. RNA

was extracted from frozen tumor samples and a qPCR was run using primers specific

for human MYC and UBC (housekeeping gene). Relative fold change in MYC

expression normalized to UBC is plotted against tumors from different hosts. Error

bars are represented as +/- SEM.

71

Figure 3: CD4+ T-cells home to the tumor and are sufficient to induce sustained

tumor regression upon MYC inactivation

Figure 3: CD4+ T-cells home to the tumor and are sufficient to induce sustained

tumor regression upon MYC inactivation. 3(A): Representative images of

bioluminescence signal from luciferase+

CD4+ T-cells that home to the tumor

microenvironment. RAG1-/-

mice were reconstituted with luciferase+ CD4

+ T-cells and

unlabeled tumor cell lines were injected s.c. 8 days post reconstitution. When tumors

72

grew to a size of 1000 mm3

MYC was inactivated and bioluminescence imaging was

used to observe and measure the distribution pattern of luciferase+ CD4

+ T-cells. Data

is represented as bioluminescence signal (average radiance) plotted against time after

MYC inactivation (n=3). 3(B): Graphical representation of tumor regression and

relapse kinetics as measured by bioluminescence imaging. RAG1-/-

mice were

reconstituted with CD4+ (n=5) or CD8

+ (n=6) T-cells isolated from spleens and lymph

nodes of WT mice using magnetically activated cell sorting (MACS). 8 days post

reconstitution, luciferase+ tumor cell lines were injected s.c. MYC was inactivated

when tumors in all hosts reached a comparable bioluminescence signal and tumor

regression and relapse kinetics were monitored. Data is presented as bioluminescence

signal (average radiance) plotted against time after MYC inactivation. WT (n=3) and

RAG1-/-

(n=3) mice were used as positive and negative controls. 3(C): Quantification

of minimum residual disease in the indicated hosts. Bioluminescence signals of tumors

at their maximally regressed state are plotted against genotype. Statistical significance

(p value evaluated by unpaired Student‟s t-test) is shown. * p < 0.01, ** p < 0.001,

*** p < 0.0001 3(D): Kaplan Meier curves of tumor-free survival in the reconstituted

RAG1-/-

, RAG1-/-

and WT mice. A mouse was scored as a relapse when the

bioluminescence signal first begins to increase after tumor regression. The table shows

the results of a log-rank test to compare the survival curve of RAG1-/-

reconstituted

with CD4+ T-cells with survival curves of the other indicated genotypes. Data shown

are representative 3 different experiments. reconst. = reconstituted with, rec =

reconstituted with

73

Figure 4: Splenocytes depleted of CD4+ T-cells home to the tumor

microenvironment and verification of RAG1-/-

reconstitution

74

Figure 4: Splenocytes depleted of CD4+ T-cells home to the tumor

microenvironment and verification of RAG1-/-

reconstitution. 4(A): Representative

bioluminescence images of CD4+ T-cell depleted luciferase

+ splenocytes homing to

the tumor microenvironment. Luciferase+

splenocytes were depleted for CD4+ T-cells

were injected i.v into RAG1-/-

mice. 8 days after reconstitution, unlabeled tumors were

injected s.c. MYC was inactivated and bioluminescence imaging was used to observe

the distribution pattern of the CD4+ T-cell depleted splenocytes. 4(B): FACS analysis

of peripheral blood of RAG1-/-

mice reconstituted with CD4+ or CD8

+ T-cells, 8 days

post reconstitution. Data shown is representative of 4 different experiments.

75

Figure 5: The immune system does not influence apoptosis and cellular arrest


Figure 5: The immune system does not influence apoptosis and cellular arrest

upon MYC inactivation. 5(A): Micrographs of Hematoxylin and Eosin staining (top

panel), TUNEL (middle panel) and Ki67 (bottom panel) immunostaining of tumors

derived from untreated (MYC On) and six-day dox treated mice (MYC Off) from WT

(left panel) RAG1-/-

(middle panel) and CD4-/-

(right panel) hosts. Scale Bar = 100 μm.

76

5(B): Quantitative representation of TUNEL (left panel) and Ki67 (right panel)

immunostaining shown in 3(A). Quantification of TUNEL and Ki67 immunostaining

is presented as the average percentage of TUNEL-positive cells and area of Ki67-

positive regions, respectively, within the tumors. At least five different fields from

three different tumors injected with at least two different tumor cell lines for each

different condition. Statistical significance (p value evaluated by unpaired Student‟s t-

test) is shown. * p < 0.01, ** p < 0.001, *** p < 0.0001

77

Figure 6: An intact immune system is required for the inhibition of angiogenesis


78

Figure 6: An intact immune system is required for the inhibition of angiogenesis

upon MYC inactivation. 6(A): Micrographs of TSP-1 (top panel) and CD31 (bottom

panel) immunofluorescence staining of tumors derived from untreated (MYC On) and

4 day dox treated (MYC Off) mice of the indicated genotypes. Scale Bar = 100μm.

6(B): Quantification of TSP-1 (left panel) and CD31 (right panel) staining shown in

6(A). Quantification is presented as the average percentage of positively stained

regions within the tumors. At least five different fields from two different tumors were

analyzed for each different condition. Statistical significance (p value evaluated by

unpaired Student‟s t-test) is shown. * p < 0.01, ** p < 0.001, *** p < 0.0001 6(C):

Spleens from WT and RAG1-/-

mice were harvested, lysed and probed for TSP-1 by

western blot analysis. HSP-90 was probed as a loading control. 6(D): Splenocytes

were harvested from wild-type mice and purified by positive selection with either anti-

CD45 or anti-CD4 coated beads. Isolated cells were cultured for 3 days in the presence

of anti-CD3 and anti-CD28, harvested, lysed and probed by western blot analysis for

TSP-1. β-actin was probed as a loading control.

79

Figure 7: TSP-1 expression in the tumor microenvironment is required for

sustained tumor regression upon MYC inactivation

80

Figure 7: TSP-1 expression in the tumor microenvironment is required for

sustained tumor regression upon MYC inactivation. 7(A): FACS analysis of

RAG1-/-

mice reconstituted with splenocytes from either WT or TSP-1,2-/-

mice. 8

days after reconstitution, mice were bled from the tail vein to check for reconstitution

by flow cytometry. Data shown is representative of 3 different experiments 7(B):

Kaplan-Meier curves of tumor free survival of reconstituted RAG1-/-

, RAG1-/-

and WT

mice. RAG1-/-

mice were reconstituted with splenocytes from WT (n=18) or TSP-1,2-/-

(n=16) mice i.v. 8 days post reconstitution mice were transplanted with unlabelled

lymphoma cells s.c. Tumors were allowed to grow to a size of 1000mm3 after which

MYC was inactivated and mice were scored for relapse. WT (n=8) and RAG1-/-

(n=11)

mice were used as positive and negative controls. The table shows the results of a log-

rank test to compare the survival curve of RAG1-/-

reconstituted with TSP-1,2-/-

splenocytes with survival curves of the other indicated genotypes. Data shown are

representative 3 different experiments. 7(C): Kaplan-Meier curves of tumor free

survival of RAG1-/-

mice injected with tumor cell lines that were either transduced

with retrovirally expressed TSP-1 (n=5) or with an empty vector (n=5). Tumors were

allowed to grow to a size of 1000mm3 after which MYC was inactivated and mice

were scored for relapse. 7(D): Kaplan-Meier survival curve of SCID mice treated with

PBS (vehicle control) or 3 TSR (drug). Mice were transplanted with 10^7 unlabeled

lymphoma cells and tumors were treated with either doxycycline alone or in

combination with 3 TSR when they reached a size of 1000 mm3. Mice were scored as

relapses when they showed signs of morbidity.

81

Figure 8: An intact immune system is required for the induction of cellular

senescence upon MYC inactivation

Figure 8: An intact immune system is required for the induction of cellular

senescence upon MYC inactivation. 8(A): Micrographs of Senescence Associated β-

galactosidase (SA β-gal, top panel), p16 (middle panel) and p21 (bottom panel)

immunostaining of tumors derived from untreated (MYC On) and four-day dox treated

(MYC Off) mice of the indicated genotypes. Scale Bar = 100 μm. 8(B): Quantification

of SA-β-gal (left panel), p16 (middle panel) and p21 (right panel) staining shown in

82

8(A). Quantification is presented as the average percentage of positively stained

regions within the tumors. At least five different fields from three different tumors

injected with at least two different tumor cell lines were analyzed for each different

condition. Statistical significance (p value evaluated by unpaired Student‟s t-test) is

shown. * p < 0.01, ** p < 0.001, *** p < 0.0001

83

Figure 9: Cytokines produced by the immune system contribute to sustained

tumor regression upon MYC inactivation

84

Figure 9: Cytokines produced by the immune system contribute to sustained

tumor regression upon MYC inactivation. Graphical representation of fold change

of indicated cytokines upon MYC inactivation in tumors from 9(A): WT and RAG1-/-

hosts and 9(B): RAG1-/-

hosts reconstituted with CD4+ T-cells. Tumors were

harvested at tumor onset and 4 days after MYC inactivation and run on a luminex

platform to check for the expression of 21 different cytokines. The significant fold

changes in the various cytokines upon MYC inactivation were log2 transformed and

plotted for various pro- and anti-tumor cytokines. 9(C,D,E): Quantification of protein

levels represented as concentration (pg/ml) obtained from running the luminex assay

on lysates derived from untreated (MYC On) and four-day dox (MYC Off) treated

tumors from WT and RAG1-/-

mice. 9(C): MCP-1 9(D): MCP-3 9(E): Eotaxin-1. Data

are representative of three different tumors run in duplicate. Statistical significance (p

value evaluated by unpaired Student‟s t-test) is shown. * p < 0.01, ** p < 0.001, *** p

< 0.0001

* on top of the bars represents significance in cytokine expression upon MYC

inactivation in the indicated host.

85


hosts


86


hosts

upon MYC inactivation. 10(A): Micrographs of F480 immunostaining (top panel) of

tumors derived from untreated (MYC On) and three-day dox treated mice (MYC Off)

from WT, RAG1-/-

, CD4-/-

and CD8-/-

hosts (ordering is from top to bottom). Scale Bar

= 100 μm. 10(B): Quantitative representation of F480 (bottom panel) immunostaining

shown in 10(A). Quantification of F480 immunostaining is presented as the average

percentage of F480-positive regions, respectively, within the tumors. At least five

different fields from two different tumors were analyzed for each different condition.

Statistical significance (p value evaluated by unpaired Student‟s t-test) is shown. ** p

< 0.001, *** p < 0.0001

87

Figure 11: Increased levels of iNOS, Arg-1 and TSP-1 in macrophages from

tumor bearing WT hosts

Figure 11: Increased levels of iNOS, Arg-1 and TSP-1 in macrophages from

tumor bearing WT hosts. Quantification of relative gene expression compared to

housekeeping gene UBC from mRNA derived from in vitro cultured splenic

macrophages from WT and SCID mice bearing untreated (MYC On) and four-day dox

(MYC Off) treated tumors. 11(A): iNOS 11(B): Arginase-1 11(C): Arginase-2 11(D):

Thrombospondin-1 Data are representative of 2 different tumors injected for each

88

condition, run in triplicate. Statistical significance (p value evaluated by unpaired

Student‟s t-test) is shown. ** p < 0.001, *** p < 0.0001

89

Figure 12: Cyclosporine A treatment inhibits induction of senescence and

inhibition of angiogenesis in primary MYC induced T-ALL

90

Figure 12: Cyclosporine A treatment inhibits induction of senescence and

inhibition of angiogenesis in primary MYC induced T-ALL. 12(A): Conditional

MYC overexpressing tumor cell lines were treated in vitro with either 500 ng/ml

cyclosporine A, 1000 ng/ml cyclosporine A or 20 ng/ml doxycycline and their growth

was compared to untreated cells at 24, 48 and 72 hours post drug treatment.12(B):

Micrographs and quantification of Hematoxylin and Eosin, Ki67, SA-β-gal, p16, p21,

CD31 and TSP-1 immunostaining (ordered from top to bottom) of tumors derived

from untreated and cyclosporine A treated primary tumor bearing mice (MYC On and

4 day dox treated MYC Off). Scale Bar = 100μm. Quantification is presented as the

average percentage of positively stained regions within the tumors. At least five

different fields from two different tumors were analyzed for each different condition.

Statistical significance (p value evaluated by unpaired Student‟s t-test) is shown. * p <

0.01, ** p < 0.001, *** p < 0.0001

91

Figure 13: An intact immune system is required for sustained regression of

tumors in a conditional mouse model of BCR-ABL-induced B-ALL

92

Figure 13: An intact immune system is required for sustained regression of

tumors in a conditional mouse model of BCR-ABL-induced B-ALL. 13(A):

Kaplan-Meier curves of tumor free survival of RAG1-/-

(n=9) and WT (n=4) mice

transplanted with unlabelled leukemia cells i.p. When mice were moribund with

tumor, BCR-ABL was inactivated, and mice were scored for relapse. 13(B):

Micrographs and quantification of Ki67, SA-β-gal, p16, p21, and TSP-1

immunostaining (ordered from top to bottom) of tumors derived from untreated (BCR-

ABL On) and doxycycline treated (BCR-ABL Off) wildtype and immunodeficient

tumor bearing mice. Scale Bar = 100μm. Quantification is presented as the average

percentage of positively stained regions within the tumors. At least five different fields

from two different tumors were analyzed for each different condition. Statistical

significance (p value evaluated by unpaired Student‟s t-test) is shown. * p < 0.01, ** p

< 0.001, *** p < 0.0001

93

Figure 14: Increased Foxp3 expression in tumors regressing in WT hosts upon

MYC inactivation

Figure 14: Increased Foxp3 expression in tumors regressing in WT hosts upon

MYC inactivation. 14(A): Micrographs of Foxp3 immunostaining of tumors derived

from untreated (MYC On) and four-day dox treated mice (MYC Off) from WT (top

panel) and RAG1-/-

(bottom panel) hosts. 14(B): Quantitative representation of Foxp3

94

immunostaining shown in 14(A). Quantification of Foxp3 immunostaining is

presented as the average percentage of Foxp3-positive regions, respectively, within the

tumors. At least five different fields from three different tumors were analyzed for

each different condition. Statistical significance (p value evaluated by unpaired

Student‟s t-test) is shown. ** p < 0.001

95

Figure 15: Transplanted tumors are rejected upon re-challenge in WT hosts that

have previously exhibited sustained tumor regression

Figure 15: Transplanted tumors are rejected upon re-challenge in WT hosts that

have previously exhibited sustained tumor regression. Graphical representation and

representative data are shown of tumor growth as measured by bioluminescence

imaging. Luciferase-labeled tumor cell lines from our conditional mouse T-ALL

model [1] were injected subcutaneously into different cohorts of WT mice (Naïve n =

5, WT mice that have previously exhibited tumor regression and were being re-

challenged n = 5). Data is presented as bioluminescence signal (average radiance)

plotted against time after tumor challenge (days).

96

2.7 References:



2. Huettner, C.S., et al., Reversibility of acute B-cell leukaemia induced by BCR-

ABL1. Nat Genet, 2000. 24(1): p. 57-60.

3. Contag, C.H., et al., Visualizing gene expression in living mammals using a

bioluminescent reporter. Photochem Photobiol, 1997. 66(4): p. 523-31.



Acad Sci U S A, 2006. 103(44): p. 16266-71.

5. Karlsson, A., et al., Genomically complex lymphomas undergo sustained tumor

regression upon MYC inactivation unless they acquire novel chromosomal

translocations. Blood, 2003. 101(7): p. 2797-803.

6. Kazerounian, S., K.O. Yee, and J. Lawler, Thrombospondins in cancer. Cell

Mol Life Sci, 2008. 65(5): p. 700-12.


2000. 12(5): p. 634-40.

8. Miao, W.M., et al., Thrombospondin-1 type 1 repeat recombinant proteins

inhibit tumor growth through transforming growth factor-beta-dependent and -

independent mechanisms. Cancer Res, 2001. 61(21): p. 7830-9.

9. Wu, C.H., et al., Cellular senescence is an important mechanism of tumor

regression upon c-Myc inactivation. Proc Natl Acad Sci U S A, 2007. 104(32):

p. 13028-33.

10. Acosta, J.C., et al., Chemokine signaling via the CXCR2 receptor reinforces

senescence. Cell, 2008. 133(6): p. 1006-18.

11. Kuilman, T., et al., Oncogene-induced senescence relayed by an interleukin-

dependent inflammatory network. Cell, 2008. 133(6): p. 1019-31.

12. Kuilman, T. and D.S. Peeper, Senescence-messaging secretome: SMS-ing

cellular stress. Nat Rev Cancer, 2009. 9(2): p. 81-94.

13. Hanahan, D. and J. Folkman, Patterns and emerging mechanisms of the

angiogenic switch during tumorigenesis. Cell, 1996. 86(3): p. 353-64.

14. Bartek, J., Z. Hodny, and J. Lukas, Cytokine loops driving senescence. Nat

Cell Biol, 2008. 10(8): p. 887-9.



178(7): p. 4222-9.

16. Qin, Z. and T. Blankenstein, CD4+ T cell--mediated tumor rejection involves

inhibition of angiogenesis that is dependent on IFN gamma receptor

expression by nonhematopoietic cells. Immunity, 2000. 12(6): p. 677-86.

17. Thomas, W.D. and P. Hersey, TNF-related apoptosis-inducing ligand (TRAIL)

induces apoptosis in Fas ligand-resistant melanoma cells and mediates CD4 T

cell killing of target cells. J Immunol, 1998. 161(5): p. 2195-200.

97

18. Allavena, P., et al., The inflammatory micro-environment in tumor

progression: the role of tumor-associated macrophages. Crit Rev Oncol

Hematol, 2008. 66(1): p. 1-9.

19. Hu, H., et al., Tumor cell-microenvironment interaction models coupled with

clinical validation reveal CCL2 and SNCG as two predictors of colorectal

cancer hepatic metastasis. Clin Cancer Res, 2009. 15(17): p. 5485-93.

20. Kowanetz, M. and N. Ferrara, Vascular endothelial growth factor signaling

pathways: therapeutic perspective. Clin Cancer Res, 2006. 12(17): p. 5018-22.

21. Shchors, K., et al., q. Genes Dev, 2006. 20(18): p. 2527-38.

22. Conti, I. and B.J. Rollins, CCL2 (monocyte chemoattractant protein-1) and

cancer. Seminars in Cancer Biology, 2004. 14(3): p. 149-154.



24. Alatery, A. and S. Basta, An efficient culture method for generating large

quantities of mature mouse splenic macrophages. J Immunol Methods, 2008.

338(1-2): p. 47-57.

25. Shi, O., et al., Structure of the murine arginase II gene. Mamm Genome, 1998.

9(10): p. 822-4.

26. Maarsingh, H., T. Pera, and H. Meurs, Arginase and pulmonary diseases.

Naunyn Schmiedebergs Arch Pharmacol, 2008. 378(2): p. 171-84.

27. Khallou-Laschet, J., et al., Macrophage plasticity in experimental

atherosclerosis. PLoS One, 2010. 5(1): p. e8852.

28. Ho, S., et al., The mechanism of action of cyclosporin A and FK506. Clin

Immunol Immunopathol, 1996. 80(3 Pt 2): p. S40-5.

29. Belkaid, Y., Regulatory T cells and infection: a dangerous necessity. Nat Rev

Immunol, 2007. 7(11): p. 875-88.

30. Maloy, K.J. and F. Powrie, Regulatory T cells in the control of immune

pathology. Nat Immunol, 2001. 2(9): p. 816-22.

31. Fontenot, J.D., M.A. Gavin, and A.Y. Rudensky, Foxp3 programs the

development and function of CD4+CD25+ regulatory T cells. Nat Immunol,

2003. 4(4): p. 330-6.

98

CHAPTER 3: DISCUSSION OF

FINDINGS, IMPLICATIONS OF

RESULTS, AND

FUTURE DIRECTION

99

3.1 Overview:

Oncogene addiction is often studied with an emphasis on what happens to the

tumor cells upon oncogene inactivation. My work has shifted this emphasis from the

tumor cells to the immune cells of the tumor microenvironment to study the

contribution of the immune system to tumor regression mediated by oncogene

inactivation. Oncogene addiction had been presumed to be a largely cell autonomous

process [1] but results described in this thesis have shown that interactions between

the tumor microenvironment and the immune system are essential for sustained tumor

regression to occur upon oncogene inactivation.

3.2 The adaptive immune system remodels the tumor

microenvironment:

We have demonstrated that in the absence of an intact adaptive immune

system, we see a 10-1000-fold reduction in the rate, extent, and duration of tumor

regression upon MYC inactivation in the Eµ-tTA X tet-O-MYC mouse model of T-

ALL. Provocatively, we found that the absence of CD4+

T-cells alone was sufficient to

markedly impede sustained tumor regression. Thus, oncogene addiction is not

necessarily cell autonomous. The immune system, specifically CD4+ T-cells, may play

a critical role in enabling MYC inactivation to elicit changes in the microenvironment

and in cytokine expression that appear to be required for cellular senescence and the

shutdown of angiogenesis. TSP-1 is one critical cytokine that must be expressed by

immune effectors to cooperate with MYC inactivation to induce sustained tumor

regression. Importantly, our results generalized to primary tumors from MYC-induced

100

T-ALL bearing hosts that had been treated with the immunosuppressive agent

cyclosporine A and a conditional transgenic model of BCR-ABL induced B-ALL. We

conclude that oncogene inactivation may induce tumor regression through immune

cell dependent mechanisms. Our findings have potentially important implications for

the development of targeted therapeutics, for they suggest that testing potential

therapeutics in vitro or in vivo in immune deficient hosts may significantly

underestimate their potential efficacy. Our findings also imply that the efficacy of

existing targeted therapeutics can be improved by combining them with strategies to

increase CD4+ T-cell infiltration of tumors or strategies to inhibit angiogenesis and

induce cellular senescence in the tumor microenvironment.

Our observations are consistent with a multitude of reports that document the

role of the immune system in neoplasia [2-5]. Tumors co-evolve in the context of an

intact immune system through the process of immune editing, resulting in tumor

elimination, dormancy or evolving to escape the immune system and progress to full

malignancy [4, 6-7]. Hence, MYC-induced tumors may evolve to subvert the immune

elimination response. Then, upon MYC inactivation, a massive recruitment of CD4+ T-

cells occurs that is associated with marked changes in cytokine production in the

tumor microenvironment leading to cellular senescence and the shutdown of

angiogenesis.

Provocatively, CD4+ T-cells emerged as the critical host effector population

for sustained tumor regression upon MYC inactivation. The rationale used to obtain

data described in chapter 2 was to observe how CD4+ T-cells influenced the different

101

mechanisms of tumor regression known to occur upon MYC inactivation. We deviated

from classical immunological approaches which would entail investigating the

interaction of CD4+ T-cells with tumor cells with respect to antigen presentation and

CD4+ T-cell activation through antigen recognition in the context of MHC II on the

surface of antigen presenting cells and uncovered a non-canonical role for CD4+ T-

cells in the tumor microenvironment.

CD4+ T-cells may play a direct role in tumor cytotoxicity as has been

described before [8] but we have not performed experiments to test whether or not this

occurs in our lymphoma model. CD4+

T-cells have been previously implicated in the

restraint of tumor growth through regulation of antigen dependent mechanisms

involving either macrophages or cytotoxic T-cells [9-11]. Some reports also suggest

that the anti-tumor effect of CD4+ T-cells is mediated by eosinophils [12-13] and we

explore these possibilities briefly. Further characterization of CD4+ T-cells in this

model is warranted to understand what cytokines they secrete and whether they are

polarized along the TH-1, TH-2 or TH-17 pathway. Future experiments to interrogate

whether or not the CD4+ T-cells that influence tumor regression in this model system

are antigen specific also need to be performed. Additionally, important parameters like

the kinetics of CD4+ T-cell activation post tumor transplantation and post MYC

inactivation need to be determined.

Notably, hosts deficient in CD4+ T-cells exhibited impaired kinetics, degree

and durability of tumor regression as well as reduced senescence and suppression of

angiogenesis upon MYC inactivation. Moreover, the reconstitution of CD4+ T-cells

102

into RAG1-/-

hosts alone was capable of restoring the ability of MYC inactivation to

induce sustained tumor regression. Indeed, the reconstitution of CD4+ T-cells

into

RAG1-/-

hosts had more potent effects on tumor regression compared with the

depletion of these cells, perhaps reflecting that in hosts that are congenitally defective

in a specific immune compartment there may be compensation from other immune

effectors [14].

Intriguingly, host CD4+ T-cells sculpted the tumor‟s response to MYC

inactivation, likely not by their modest influence upon apoptosis or proliferation, but

by dramatically inducing cellular senescence and the shutdown of angiogenesis,

processes previously shown by us to be integral to the ability of MYC inactivation to

effect sustained tumor regression. Moreover, two of the hallmarks of oncogene

addiction, both the induction of cellular senescence and the suppression of

angiogenesis, have been linked to the expression of cytokines known to be expressed

by CD4+ T-cells [15-18]. We found that CD4

+ T-cells were required to effect changes

in the microenvironment and have identified TSP-1 as one of the critical chemokines

that might mediates these changes. Our results are consistent with other reports that

immune effectors and associated changes in chemokines occur upon restoration of the

tumor suppressor p53 in both liver cancer [19] and upon MYC inactivation in

lymphoma [20].

Thus, CD4+ T-cells are one important component of the mechanism of tumor

regression upon oncogene inactivation. It should be noted, that upon MYC inactivation

tumors recurred in only 28.5% of the CD4-/-

hosts compared to 100% of the RAG1-/-

103

and SCID hosts. This suggests that other host immune effectors are likely to contribute

and we recognize the possibility that other innate and adaptive immune compartments

are also involved including macrophages, eosinophils, NK cells, mast cells, and B-

cells. Recent work suggests that mast cells and macrophages both may be critical [5,

19]. Indeed, it is possible that CD4+ T-cells are mediating part of the effects we have

observed by recruiting these effector populations.

We specifically identified TSP-1 as being critical for the mechanism by which

host immune effectors mediate tumor regression upon MYC inactivation. TSP-1 is a

potent cytokine that has been implicated in the regulation of many cellular processes

including the regulation of angiogenesis [21-25]. Furthermore, TSP-1 has also been

implicated in the regulation of lymphocyte homing and function [26]. Our results

suggest that TSP-1 is required for the ability of CD4+ T-cells to contribute to sustained

regression upon oncogene inactivation and we showed that this could be in part due to

the ability of TSP-1to inhibit angiogenesis upon MYC inactivation.

Moreover, TSP-1 has been shown to activate latent TGF-β [27]. Notably, TGF-

β can play a tumor suppressive role in certain tumor microenvironments [28-29].

TGF-β can also contribute to both the restraint of tumor onset as well as oncogene

addiction through the regulation of cellular senescence upon MYC activation and

inactivation [30]. Thus, it is tempting to speculate that TSP-1 may contribute to

oncogene addiction via its influence on TGF-β.

In addition to TSP-1, we identified several other cytokines including eotaxin-1,

IL-5, IFN- and TNF- as possible candidates for mediating changes in cellular

104

senescence and angiogenesis upon MYC inactivation, consistent with reports that these

chemokines may be involved in these processes [16, 31]. Also the observed

downregulation of other cytokines such as VEGF, IL-1, and MCP-1 could contribute

to these mechanisms [32-34]. IFN- and TNF- have been previously implicated in

the regulation of cellular quiescence and angiogenesis [16-18, 31], and eotaxin-1 and

IL-5 have demonstrated potent anti-tumor activity in numerous mouse models of

cancer [35]. Notably, tumor regression induced by the restoration of p53 expression

was also associated with marked changes in chemokine expression [19].

We also found that in primary transgenic tumor hosts, an immune

compromised state induced via treatment with cyclosporine A greatly impeded the

consequences of oncogene inactivation. Our observations in the primary tumor model

are important because they show that our results generalize in the case when

endogenous tumor-host interactions evolved throughout tumorigenesis. Cyclosporine

A treatment is well known to increase the frequency of hematological malignancies in

patients [36-37]. Our results imply that this agent may impede sensitivity to oncogene

directed therapies. Intriguingly, we observe that treatment with cyclosporine A seems

to affect proliferation of primary tumors when MYC is on suggesting T-cells and/or B-

cells could enhance tumor development and progression as has been reported in

several cases [38-39]. If this were the case, it would imply that MYC influences T-cell

function and in the presence of MYC, T-cells are pro-tumor, but in its absence, T-cells

play an anti-tumor role.

105

We also found that an immune intact host is required for BCR-ABL

inactivation to induce sustained tumor regression in B-ALL. Similar to MYC

inactivation, inactivation of the BCR-ABL oncogene resulted in the induction of

cellular senescence, the shutdown of tumor angiogenesis, and ultimately sustained

tumor regression only in the presence of the host immune system. However, different

from MYC inactivation, BCR-ABL inactivation appeared to be less capable of

suppressing cellular proliferation. Hence, the host immune system appears to be

generally important in mediating the consequences of oncogene inactivation. We

recognize that there are likely to be differences in the specific contribution of the

immune system in different types of tumors and this contribution would also depend

on the oncogene being inactivated.

We are currently in the process of designing experiments to test whether

Gleevec, a small molecule inhibitor of the BCR-ABL tyrosine kinase [40] requires an

intact immune system to cause sustained tumor regression in this model of B-ALL and

whether CD4+ T-cells can improve the quality of Gleevec induced regression. If the

immune system contributes to sustained tumor regression initiated by Gleevec, the

findings of this thesis have immediate clinical relevance and efforts can be made

towards testing a combination of Gleevec and anti-angiogenic therapy or CD4+ T-cell

reconstitution to treat chronic myelogenous leukemia patients.

3.3 Potential role of T-regs and an antigen specific immune response:

We have generated data suggesting a potential role for T-regs in the tumor

microenvironment upon MYC inactivation. As T-regs are known to suppress the

106

immune response, they are thought to help the tumor evade an anti-tumor immune

surveillance response [41]. In fact, in several solid tumor models, it has been shown

that increased T-reg infiltration of tumors correlates with poor prognosis [42-43] and

T-regs are generally thought to be tumor promoting. The role of T-regs in

hematological malignancies is not entirely clear. One study has shown that increased

T-reg infiltration in tumor biopsies of patients with cutaneous T-cell lymphoma

(CTCL) is associated with improved survival [44]. One possible explanation is that the

T-regs can inhibit the proliferation of malignant T-cells and thus inhibit tumor growth.

As tumors in our MYC induced lymphoma model are double positive CD4+CD8

+ T-

cells, T-regs might have a direct anti-tumor effect in this model and this warrants

further investigation.

The major part of the work performed in this thesis characterizes a non-

canonical role of the immune system in the anti-tumor response. However, we have

preliminary evidence indicating that there is an antigen specific anti-tumor response

that develops in our MYC induced transplanted tumor model. We show that WT mice

in which tumors have achieved sustained regression are able to reject tumor re-

challenge. It is not clear whether this anti-tumor immune memory develops after

tumor transplantation when MYC is on or after MYC has been inactivated and the

tumor begins to regress. Furthermore, it is not clear whether the immune memory that

is generated contributes to sustained tumor regression upon MYC inactivation.

107

3.4 Potential role of the innate immune system:

There is extensive literature describing the complex role of tumor associated

macrophages in promoting and/or inhibiting tumor growth and progression [45-47].

However the role of macrophages in a tumor microenvironment upon oncogene

inactivation had not been previously studied. We show that macrophage

chemoattractants MCP-1 and MCP-3 are expressed at higher levels in tumors

regressing in WT hosts compared to RAG1-/-

hosts. Upon comparing macrophage

infiltration after MYC inactivation in these hosts, we observe that tumors from WT

hosts show significantly more macrophage infiltration compared to tumors from

RAG1-/-

hosts.

It should be noted that even when MYC is activated, tumors from WT hosts

show significantly increased levels of MCP1- and MCP-3 compared to RAG1-/-

hosts,

but no significant macrophage infiltration is observed in the tumor microenvironments

of either host when MYC is on.

In another model of MYC induced lymphoma, macrophages have been

described to be recruited to the tumor microenvironment in response to MYC induced

apoptosis [48]. Once recruited to the microenvironment, these macrophages

phagocytose apoptotic tumor cells and secrete TGF-β that can induce cellular

senescence in the non-apoptotic tumor cells [48]. While this process has been

described as a mechanism of tumor suppression upon MYC activation, we show that in

our model of MYC induced lymphoma, macrophages accumulate in the tumor

microenvironment only upon MYC inactivation in WT and CD8-/-

hosts. We have

108

shown that MYC inactivation leads to apoptosis and cellular senescence of tumor cells

(Figure 5, 8) in WT hosts and it would be worthwhile to investigate whether

macrophage infiltration contributes to inducing this cellular senescence response.

We do not observe significant macrophage infiltration in tumors from RAG1-/-

hosts and those from CD4-/-

hosts show reduced macrophage infiltration compared to

WT and CD8-/-

hosts upon MYC inactivation. This suggests that the presence of CD4+

T-cells is required to elicit macrophage infiltration in these regressing tumors. This is

in accordance with other reports that CD4+

T-cells recruit macrophages into the tumor

microenvironment [12, 39].

To fully understand the role played by macrophages in our tumor model

system, it will be essential to characterize the functional polarization of the tumor

infiltrating macrophages. At present, we have not been able to successfully extract

RNA from the infiltrating macrophages as we have been unable to retrieve a

significant number of macrophages from the tumor microenvironment. Instead, we

attempted to characterize the phenotype of splenic macrophages from tumor bearing

mice to get a better idea of macrophage functional polarization. We find that splenic

macrophages from WT mice carrying tumors before and after MYC inactivation

express both iNOS and arginase-1 suggesting that both M1 and M2 macrophages may

be present in the spleen of WT tumor bearing mice.

We did not observe either iNOS or arginase-1 expression in splenic

macrophages cultured from tumor bearing SCID hosts. Interestingly, however, we did

observe arginase-2 expression in these cultured macrophages. Arginase-2 was not

109

expressed by WT splenic macrophages. The role of arginase-2 in macrophage

polarization is not well elucidated and without analyzing several other markers of

macrophage polarization (IL-6, IL-10, IL-1β, CCL-17,CXCL9, MRC-1) we cannot

definitively identify the polarization state of these aringase-2 expressing macrophages.

We also found that splenic macrophages from WT hosts upregulated the

expression of TSP-1 upon MYC inactivation. This indicates that macrophages could be

a potential source of increased TSP-1 expression seen in tumors from WT hosts upon

MYC inactivation (Figure 6). However to confirm this, TSP-1 expression from tumor

infiltrating macrophages will have to be measured.

Another innate immune cell type that might contribute to tumor regression

upon MYC inactivation in our tumor model is the eosinophil. We found that eotaxin-1,

a potent eosinophil chemoattractant, was upregulated several fold in tumor lysates

from WT hosts compared to RAG-1-/-

hosts. Future experiments need to be performed

to investigate whether or not there are significant differences in infiltration of

eosinophils in tumors from WT and immunodeficient hosts before and after MYC

inactivation.

Several confirmatory experiments need be performed to interrogate the role of

macrophages and eosinophils in tumor regression upon MYC inactivation. Current

efforts are underway to knock out macrophages using clodronate liposomes [49] to

study their effect in tumor regression and relapse. Similarly, strategies to deplete

eosinophils can be used if preliminary eosinophil infiltration data suggests that this

cell type is involved. There have been several descriptions of anti-tumor immune

110

responses mediated by macrophages and eosinophils together [50-51]. Since neither

macrophages nor eosinophils have inherent tumor specificity, they require adaptive

immune cells to confer anti-tumor specificity. The most likely candidate cell would be

CD4+ T-cells that are known to recruit both macrophages and eosinophils into various

tumor microenvironments [12]. Once we understand the roles played by various innate

populations in mediating tumor regression to targeted therapeutics, strategies to

combine these therapeutics with immune based therapies can be designed.

3.5 Implications:

We propose a model whereby oncogene addiction is a consequence of both cell

autonomous processes such as proliferative arrest and apoptosis as well as host-

immune dependent mechanisms such as cellular senescence and angiogenesis (Figure

1). Immediately upon oncogene inactivation, tumor cells are eliminated primarily in a

cell autonomous manner, and hence we observe a similar effect of oncogene

inactivation in vitro or in vivo and in immune intact or deficient hosts. However, the

kinetics of tumor cell elimination and the extent of tumor elimination, or minimal

residual disease, as well as the durability of sustained tumor regression are all dictated

by the presence of an immune system and appear to be strongly associated with its

ability to elicit cellular senescence and shut down angiogenesis. These latter processes

have been proposed to contribute to the constraint of minimal residual disease by

others [52], and our data extends this paradigm to oncogene addiction. Thus, host

immune effectors appear to be critical to the mechanism of sustained tumor regression

elicited by oncogene inactivation, and their absence invariably results in tumor

111

recurrence. Specifically, we demonstrate that CD4+

T-cells are one critical component

to this phenomenon and that, moreover, TSP-1 emerges as a possible cytokine

regulating these processes.

Another implication of our work is that other immune effectors and

chemokines/cytokines (including IFN-, eotaxin-1, IL-5, TNF-, and MCP-1) are

likely to be involved. Numerous reports have indicated that immune cells and

inflammation can be important to the pathogenesis of cancer through many effects on

the tumor microenvironment [19,53-54]. The host immune system is critical for the

remodeling of the tumor microenvironment required to elicit oncogene addiction and

induce sustained tumor regression. The precise cues that come from the tumor cells

vary depending on their oncogenic state dictating whether immune effectors are

directed to either support tumor growth or mediate tumor regression.

We infer that oncogene addiction is not solely cell autonomous. CD4+ T-cells

are required for both the tumor intrinsic mechanisms of cellular senescence and the

host-associated mechanism of shutdown of angiogenesis. A deficiency in CD4+ T-

cells may render the treatment of tumors in patients less efficacious and impede the

complete elimination of tumor cells. Indeed, AIDS patients exhibit not only a more

than 100-fold increased frequency of lymphomas often associated with MYC

overexpression but are also much less responsive to therapy [55-56], suggesting that

CD4+ T-cells may contribute to the efficacy of therapeutic agents.

Furthermore, methods used to identify targeted therapies that rely on the in

vitro study of cell lines or in vivo analysis of xenograft models in immune

112

compromised hosts may underestimate the efficacy of a therapy by failing to faithfully

recapitulate tumor-host interactions [57-58]. Our model system can provide an

experimental strategy to further dissect the role of specific immune effectors and

cytokines in the mechanism of tumor regression upon MYC inactivation and their role

in the shutdown of angiogenesis and induction of cellular senescence. Our

experimental approach can be generalized to study other oncogenes and cancers. Our

findings support the notion that modulation of CD4+ T-cell function may enhance the

efficacy of therapeutics for cancer [59-60]. The careful choice of a combination of

targeted and immune therapy may therefore be more efficacious in mediating

sustained tumor regression.

We anticipate that the various components of the innate and adaptive immune

system will contribute differently to different targeted therapeutics. Our work suggests

that the efficacy of targeted therapeutics can be improved by understanding the

intricacies of host-tumor interactions in individual patients and exploiting this

knowledge to mediate sustained tumor regression.

113

Figure 1: Model of the interaction of the immune system with oncogene addiction

Figure 1: Model of the interaction of the immune system with oncogene

addiction. Proposed model depicting the importance of the immune system for

eliciting oncogene addiction through induction of cellular senescence and inhibition of

angiogenesis based upon our observations in two different conditional transgenic

mouse tumor models (MYC induced T-ALL and BCR-ABL induced B-ALL).

114

3.6 References:

1. Sharma, S.V. and J. Settleman, Oncogene addiction: setting the stage for

molecularly targeted cancer therapy. Genes Dev, 2007. 21(24): p. 3214-31.

2. de Visser, K.E., A. Eichten, and L.M. Coussens, Paradoxical roles of the

immune system during cancer development. Nat Rev Cancer, 2006. 6(1): p. 24-

37.

3. de Visser, K.E., L.V. Korets, and L.M. Coussens, De novo carcinogenesis

promoted by chronic inflammation is B lymphocyte dependent. Cancer Cell,

2005. 7(5): p. 411-23.

4. Dunn, G.P., et al., Cancer immunoediting: from immunosurveillance to tumor

escape. Nat Immunol, 2002. 3(11): p. 991-8.

5. Soucek, L., et al., Mast cells are required for angiogenesis and macroscopic

expansion of Myc-induced pancreatic islet tumors. Nat Med, 2007. 13(10): p.

1211-8.

6. Guerra, N., et al., NKG2D-deficient mice are defective in tumor surveillance in

models of spontaneous malignancy. Immunity, 2008. 28(4): p. 571-80.

7. Teng, M.W., et al., Immune-mediated dormancy: an equilibrium with cancer. J

Leukoc Biol, 2008. 84(4): p. 988-93.

8. Perez-Diez, A., et al., CD4 cells can be more efficient at tumor rejection than

CD8 cells. Blood, 2007. 109(12): p. 5346-54.

9. Corthay, A., et al., Primary antitumor immune response mediated by CD4+ T

cells. Immunity, 2005. 22(3): p. 371-83.

10. Dranoff, G., et al., Vaccination with irradiated tumor cells engineered to

secrete murine granulocyte-macrophage colony-stimulating factor stimulates

potent, specific, and long-lasting anti-tumor immunity. Proc Natl Acad Sci U S

A, 1993. 90(8): p. 3539-43.

11. Qin, Z. and T. Blankenstein, CD4+ T cell--mediated tumor rejection involves

inhibition of angiogenesis that is dependent on IFN gamma receptor

expression by nonhematopoietic cells. Immunity, 2000. 12(6): p. 677-86.



13. Mattes, J., et al., Immunotherapy of cytotoxic T cell-resistant tumors by T

helper 2 cells: an eotaxin and STAT6-dependent process. J Exp Med, 2003.

197(3): p. 387-93.

14. Xing, Z., et al., Protection by CD4 or CD8 T cells against pulmonary

Mycobacterium bovis bacillus Calmette-Guerin infection. Infect Immun, 1998.

66(11): p. 5537-42.

15. Acosta, J.C., et al., Chemokine signaling via the CXCR2 receptor reinforces

senescence. Cell, 2008. 133(6): p. 1006-18.

16. Beatty, G. and Y. Paterson, IFN-gamma-dependent inhibition of tumor

angiogenesis by tumor-infiltrating CD4+ T cells requires tumor

responsiveness to IFN-gamma. J Immunol, 2001. 166(4): p. 2276-82.

17. Kuilman, T., et al., Oncogene-induced senescence relayed by an interleukin-

dependent inflammatory network. Cell, 2008. 133(6): p. 1019-31.

115

18. Muller-Hermelink, N., et al., TNFR1 signaling and IFN-gamma signaling

determine whether T cells induce tumor dormancy or promote multistage

carcinogenesis. Cancer Cell, 2008. 13(6): p. 507-18.

19. Xue, W., et al., Senescence and tumour clearance is triggered by p53

restoration in murine liver carcinomas. Nature, 2007. 445(7128): p. 656-60.



Acad Sci U S A, 2006. 103(44): p. 16266-71.

21. Jimenez, B., et al., Signals leading to apoptosis-dependent inhibition of

neovascularization by thrombospondin-1. Nat Med, 2000. 6(1): p. 41-8.


2000. 12(5): p. 634-40.

23. Short, S.M., et al., Inhibition of endothelial cell migration by thrombospondin-

1 type-1 repeats is mediated by beta1 integrins. J Cell Biol, 2005. 168(4): p.

643-53.

24. Zaslavsky, A., et al., Platelet-derived thrombospondin-1 (TSP-1) is a critical

negative regulator and potential biomarker of angiogenesis. Blood, 2010.

25. Kazerounian, S., K.O. Yee, and J. Lawler, Thrombospondins in cancer. Cell

Mol Life Sci, 2008. 65(5): p. 700-12.

26. Li, S.S., et al., Endogenous thrombospondin-1 is a cell-surface ligand for

regulation of integrin-dependent T-lymphocyte adhesion. Blood, 2006. 108(9):

p. 3112-20.

27. Beyne-Rauzy, O., et al., Tumor necrosis factor alpha induces senescence and

chromosomal instability in human leukemic cells. Oncogene, 2004. 23(45): p.

7507-16.

28. Shchors, K., et al., q. Genes Dev, 2006. 20(18): p. 2527-38.

29. Su, X., et al., Tumor microenvironments direct the recruitment and expansion

of human Th17 cells. J Immunol, 2010. 184(3): p. 1630-41.

30. Kowanetz, M. and N. Ferrara, Vascular endothelial growth factor signaling

pathways: therapeutic perspective. Clin Cancer Res, 2006. 12(17): p. 5018-22.



178(7): p. 4222-9.

32. Cockburn, I.T. and P. Krupp, The risk of neoplasms in patients treated with

cyclosporine A. J Autoimmun, 1989. 2(5): p. 723-31.

33. Opelz, G. and B. Dohler, Lymphomas after solid organ transplantation: a

collaborative transplant study report. Am J Transplant, 2004. 4(2): p. 222-30.

34. Andreu, P., et al., FcRgamma activation regulates inflammation-associated

squamous carcinogenesis. Cancer Cell, 2010. 17(2): p. 121-34.

35. DeNardo, D.G., et al., CD4(+) T cells regulate pulmonary metastasis of

mammary carcinomas by enhancing protumor properties of macrophages.

Cancer Cell, 2009. 16(2): p. 91-102.

36. Druker, B.J., et al., Efficacy and safety of a specific inhibitor of the BCR-ABL

tyrosine kinase in chronic myeloid leukemia. N Engl J Med, 2001. 344(14): p.

1031-7.

116

37. Shevach, E.M., Fatal attraction: tumors beckon regulatory T cells. Nat Med,

2004. 10(9): p. 900-1.

38. Salama, P., et al., Tumor-infiltrating FOXP3+ T regulatory cells show strong

prognostic significance in colorectal cancer. J Clin Oncol, 2009. 27(2): p. 186-

92.

39. Beyer, M. and J.L. Schultze, Regulatory T cells in cancer. Blood, 2006.

108(3): p. 804-11.

40. Gjerdrum, L.M., et al., FOXP3+ regulatory T cells in cutaneous T-cell

lymphomas: association with disease stage and survival. Leukemia, 2007.

21(12): p. 2512-8.

41. Lewis, C.E. and J.W. Pollard, Distinct role of macrophages in different tumor

microenvironments. Cancer Res, 2006. 66(2): p. 605-12.

42. Mantovani, A., et al., Macrophage polarization: tumor-associated

macrophages as a paradigm for polarized M2 mononuclear phagocytes.

Trends Immunol, 2002. 23(11): p. 549-55.

43. Sica, A., et al., Tumour-associated macrophages are a distinct M2 polarised

population promoting tumour progression: potential targets of anti-cancer

therapy. Eur J Cancer, 2006. 42(6): p. 717-27.

44. Reimann, M., et al., Tumor Stroma-Derived TGF-beta Limits Myc-Driven

Lymphomagenesis via Suv39h1-Dependent Senescence. Cancer Cell, 2010.

17(3): p. 262-272.

45. Zeisberger, S.M., et al., Clodronate-liposome-mediated depletion of tumour-

associated macrophages: a new and highly effective antiangiogenic therapy

approach. British Journal of Cancer, 2006. 95(3): p. 272-281.

46. Nathan, C.F. and S.J. Klebanoff, Augmentation of Spontaneous Macrophage-

Mediated Cytolysis by Eosinophil Peroxidase. Journal of Experimental

Medicine, 1982. 155(5): p. 1291-1308.

47. vanderVliet, A., et al., Formation of reactive nitrogen species during

peroxidase-catalyzed oxidation of nitrite - A potential additional, mechanism

of nitric oxide-dependent toxicity. Journal of Biological Chemistry, 1997.

272(12): p. 7617-7625.

48. Aguirre-Ghiso, J.A., Models, mechanisms and clinical evidence for cancer

dormancy. Nat Rev Cancer, 2007. 7(11): p. 834-46.

49. Coussens, L.M. and Z. Werb, Inflammation and cancer. Nature, 2002.

420(6917): p. 860-7.

50. Greten, F.R. and M. Karin, The IKK/NF-kappaB activation pathway-a target

for prevention and treatment of cancer. Cancer Lett, 2004. 206(2): p. 193-9.

51. Carbone, A., Emerging pathways in the development of AIDS-related

lymphomas. Lancet Oncol, 2003. 4(1): p. 22-9.

52. Boshoff, C. and R. Weiss, AIDS-related malignancies. Nat Rev Cancer, 2002.

2(5): p. 373-82.

53. Ronnov-Jessen, L. and M.J. Bissell, Breast cancer by proxy: can the

microenvironment be both the cause and consequence? Trends Mol Med,

2009. 15(1): p. 5-13.

117

54. Weigelt, B. and M.J. Bissell, Unraveling the microenvironmental influences on

the normal mammary gland and breast cancer. Semin Cancer Biol, 2008.

18(5): p. 311-21.

55. Lake, R.A. and B.W. Robinson, Immunotherapy and chemotherapy--a

practical partnership. Nat Rev Cancer, 2005. 5(5): p. 397-405.

56. Gattinoni, L., et al., Adoptive immunotherapy for cancer: building on success.

Nat Rev Immunol, 2006. 6(5): p. 383-93.

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APPENDIX I: MATERIALS AND

METHODS

119

Materials and Methods

Transgenic Mice: The generation and characterization of Tet system transgenic lines

for conditional expression of MYC, have been described [1]. CD4-/-

, CD8-/-

, CD4-/-

CD8-/-

and RAG1-/-

in the FVB/N background were generously provided by Lisa

Coussens (University of California, San Francisco). TSP-1,2-/-

mice were generously

provided by Ben Barres (Stanford University). Luciferase+L2G85 mice were

generously provided by Robert Negrin (Stanford University). Tet-o-BCR-ABL mice

were generously provided by Daniel Tenen (Harvard Unviersity). Genotyping was

performed by PCR on genomic DNA from tails. Animals were housed in the Stanford

vivarium as per animal protocols approved by Stanford University.

Tumor Surveillance and Tumorigenicity Assays: Transgenic mice were observed

biweekly for tumor development. When mice were moribund with tumor burden, they

were either humanely euthanized or treated with doxycycline in their drinking water

(100 μg/ml) to follow tumor regression and relapse. To monitor for tumor regression

and relapse, percent survival was measured as the time between doxycycline treatment

(if tumor regression occurred within 1 week) and relapse, which is defined as

recurrence of signs of morbidity. Statistical comparison of Kaplan–Meier curves is

based on the log-rank test. For transplantation experiments, primary tumors were first

adapted to in vitro growth as described [1] and then 107 cells were washed once in

PBS before subcutaneous (s.c.) or intra-peritoneal (i.p) injection into FVB/N and

immunodeficient syngeneic mice. 5 different tumors were adapted to in vitro growth

for this study. For primary tumor experiments, mice were treated with either

120

doxycycline or cyclosporine A (Bedford Labs, Ohio) i.p (20 mg/kg) or both when first

signs of tumor were observed (unkempt fur, distended abdomen and labored

breathing).

Reconstitution of RAG1-/-

mice: RAG1-/-

mice were injected intravenously (i.v.) with

either (i) 20X106 splenocytes from WT or TSP-1,2

-/- mice or (ii) 4X10

6 CD4

+ or CD8

+

T-cells isolated from spleens and lymph nodes of WT mice using Magnetically

Activated Cell Sorting (MACS). 8 days post reconstitution, mice were bled from the

tail vein and CD4+ and CD8

+ T-cell reconstitution was verified using FACS. Mice

were then transplanted with tumor s.c. Tumors were allowed to grow to a size of 1000

mm3 after which MYC was inactivated by administration of doxycyline and mice were

either imaged by bioluminescence or scored as relapses when they showed signs of

morbidity.

Cell Culture: Tumor-derived cell lines were generated by mechanical disruption of

tumor tissue followed by Ficoll–Paque purification of the single cell suspension. 5 cell

lines were generated from 5 different tumors. Cells were then maintained in vitro as

described [1].

Retrovirus Constructs, Virus Production and Tumor Cell Infection: MSCV-Puro-

LUC construct, a modified version of the pDON plasmid vector (Takara Mirus Bio,

Madison, WI), was kindly provided by Mobin Karimi and Robert Negrin (Stanford

University). Retrovirus containing supernatants were prepared by transient

transfection of 293T cells, and viral titers were measured as described [2]. Tumor cells

were incubated with retrovirus containing supernatants for 12 h at 32°C in media

121

containing 4 μg/ml polybrene. Cells were then expanded at 37°C for an additional 48 h

and cells containing MSCV-Puro-LUC were selected with puromycin.

In Vivo Bioluminescence Imaging: Tumor cells, expressing the luciferase enzyme,

were injected s.c. into syngeneic mice. Tumors were allowed to develop until reaching

a similar bioluminescent signal. Tumor regression was then induced by doxycycline

treatment (100 μg/ml). Mice developing transplanted tumors were anesthetized with a

combination of inhaled isoflorane/oxygen delivered by the Xenogen XGI-8 5-port Gas

Anaesthesia System. The substrate d-luciferin (150 mg/kg) was injected into the

animal's peritoneal cavity 10 min. before imaging. Animals were then placed into a

light-tight chamber and imaged with an IVIS-200 cooled CCD camera (Xenogen,

Alameda, CA). First, a grayscale body surface reference image (digital photograph)

was taken under weak illumination. Next, photons emitted from luciferase expressing

cells within the animal and transmitted through the tissues were collected for a period

of 5 sec to 1 min and quantified by the software program Living Image (Xenogen) as

an overlay on the image analysis program “Igor” (Wavemetrics, Seattle, WA). For

anatomical localization, a pseudocolor image representing light intensity (blue, least

intense; red, most intense) was generated in Living Image and superimposed over the

gray scale whole body reference image as described previously [3]. Living Image was

used to collect, archive, and analyze photon fluxes and transform them into

pseudocolor images by using Living Image software (Xenogen). At least 5 mice per

group were injected with tumors expressing luciferase.

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Western Blotting: Spleens were harvested from naïve WT and RAG1-/-

mice and

were snap frozen in liquid nitrogen and stored at -80oc. Frozen samples were lysed in

RIPA buffer and protein lysates were run on a 5% SDS-PAGE gel to test for TSP-1

protein expression by western blotting. Anti-mouse TSP-1 Ab-11 (Neomarkers,

1:1000) was used. Blots were stripped and re-probed with anti-HSP-90 (BD

Pharmingen, 1:1000) as a loading control.

Quantitative PCR: Tumors were harvested from WT and RAG1-/-

hosts at tumor

onset and 4 days post MYC inactivation and were snap frozen in liquid nitrogen and

stored at -80oc. RNA was extracted from frozen tumor samples using Nucleospin

mRNA extraction kits (Machery-Nagel). c-DNA was synthesized using a reverse

transcriptase reaction performed with Superscript II (Invitrogen) by using 2 μg of total

RNA. Quantitative PCR was done by using an ABI PRISM 7900HT cycler (Applied

Biosystems) using SYBR green as a method of detection.

Immunohistochemistry and Immunofluorescence: Mice were euthanized at tumor

onset and 4 and 6 days after MYC inactivation, and transplanted tumors were

harvested and fixed in neutral buffered formalin for paraffin sections and embedded in

OCT freezing medium (Tissue-tek) for frozen sections. Paraffin embedded tumor

sections were deparaffinized by successive incubations in xylene, 95% ethanol, 90%

ethanol, 70% ethanol followed by PBS. Epitopes were unmasked by steaming in

DAKO antigen retrieval solution for 45 minutes and rinsed twice in PBS. Frozen

Sections were immunostained with mouse anti-TSP1 (clone A6.1, 1:50; Lab Vision,

Fremont, CA), or an isotype matched control (Pharmingen), and paraffin embedded

123

sections were immunostained with p16 (1:100, Santa Cruz F-12 antibody) or p21

(1:100 Santa Cruz M-19 antibody) overnight at 4oc. This was followed by incubation

for 2 h with goat anti-rat Alexa 594 (1:500; Molecular Probes) or for 30 minutes at

room temperature with biotinylated anti-mouse (1:300 Vectastain ABC kits). Sections

were mounted in Vectashield mounting media containing dapi (Vector Labs) to stain

the nuclei or developed using 3,3'-Diaminobenzidine (DAB) and counterstained with

hematoxylin. Images were obtained on a Nikon microscope and analyzed by using

Metamoprh software (Meta Imaging Series). Statistical analysis of quantification of

immunostaining was done using an unpaired Student‟s t-test.

Senescence associated β-galactosidase assay: Mice were euthanized at tumor onset

and 4 and 6 days after MYC inactivation, and transplanted tumors were embedded in

OCT freezing medium (Tissue-tek) and stored at -80oc. 8 μm thick tissue sections

were cut using a cryostat. Sections were fixed in 0.5% glutaraldehyde for 10 minutes

and washed with PBS. Sections were then stained for 5-7 hours in a solution

containing 1 mM potassium ferricyanide, 1 mM potassium ferrocyanide and 1mM

magnesium chloride in PBS (pH=5.5).

Microvessel Density: Transplanted tumors were harvested at tumor onset and 6 days

after MYC inactivation and paraffin embedded. Microvessel density was determined

by immunofluorescence staining of deparaffinized tumor sections with an anti-CD31

mAb (B.D. PharMingen; 1:500) overnight at room temperature followed by a goat

anti-rat Alexa 594 (Molecular Probes; 1:500) for 2 h at room temperature. Regions of

highest vessel density were captured at a X200 magnification and area stained by

http://www.pnas.org/cgi/redirect-inline?ad=Molecular%20Probes

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124

vessels was calculated. At least five fields were counted in a representative tumor

section, and at least three different transplanted tumors were counted.

Luminex cytokine Assay: The concentration of 21 cytokines was measured from

tumor tissue lysates from WT and RAG1-/-

mice at tumor onset and 4 days post MYC

inactivation. Concentrations were measured using Luminex xMAP technology. Data

were obtained as mean fluorescence intensity based on a standard curve generated for

each cytokine. Preconfigured kits are purchased from Panomics/Affymetrix and assay

is performed according to manufacturer‟s recommendation with the following

modifications. Samples are added in duplicates (25ul) to a 96 well filter plate

containing assay buffer. Following the addition of Standards (7 point dilutions) and

controls, the appropriate mix of antibody linked to polystyrene beads are added. The

plate is covered with foil and incubated for 2 hours at room temperature while shaking

at a constant speed (500 rpm). Incubation is continued overnight at 4oC without

shaking. Following overnight incubation the plate is allowed to warm up for 20

minutes and is then vacuum filtered, washed 2X with 140ul of wash buffer to remove

unbound sample. Biotinylated detection antibody solution (25ul) is then added to the

bead mixture in the plate and incubated for 2 hours with shaking at room temperature

as above. The mixture is vacuum filtered and washed 2X to remove excess detector

antibody. SA-PE (50ul) is added to the wells and incubated for 30 minutes with

shaking at room temperature. The plate is vacuum filtered, washed 2X, and re-

suspended in 120ul reading buffer and incubated for 3 minutes at room temperature

with shaking. The plate is transferred to the Luminex reader for quantitative analysis.

Individual cytokines are identified and classified by the Red laser and cytokine levels

125

are quantified using the Green laser. Digital images of the bead array are captured

following laser excitation and are processed on a computer workstation. Standard

curves and reports of the unknown cytokine levels in the samples are prepared using

BeadView and MiraiBio software.

126

References:



2. Pear, W.S., et al., Production of high-titer helper-free retroviruses by transient

transfection. Proc Natl Acad Sci U S A, 1993. 90(18): p. 8392-6.

3. Contag, C.H., et al., Visualizing gene expression in living mammals using a

bioluminescent reporter. Photochem Photobiol, 1997. 66(4): p. 523-31.

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