the role of immune effector cells in the 4t1.2 murine

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The Pennsylvania State University The Graduate School College of Health and Human Development THE ROLE OF IMMUNE EFFECTOR CELLS IN THE 4T1.2 MURINE MAMMARY TUMOR MODEL A Thesis in Nutritional Sciences by Shizhao Duan © 2018 Shizhao Duan Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science December 2018

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Page 1: THE ROLE OF IMMUNE EFFECTOR CELLS IN THE 4T1.2 MURINE

The Pennsylvania State University

The Graduate School

College of Health and Human Development

THE ROLE OF IMMUNE EFFECTOR CELLS IN THE 4T1.2

MURINE MAMMARY TUMOR MODEL

A Thesis in

Nutritional Sciences

by

Shizhao Duan

© 2018 Shizhao Duan

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Master of Science

December 2018

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The thesis of Shizhao Duan was reviewed and approved* by the following:

Connie Rogers Associate Professor of Nutrition and Physiology Thesis Advisor Gregory Shearer Associate Professor of Nutritional Sciences Laura Murray-Kolb Associate Professor of Nutritional Sciences Professor-in-Charge of the Nutritional Sciences Graduate Program

*Signatures are on file in the Graduate School

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ABSTRACT

Breast cancer is the most commonly diagnosed cancer among women and

the second leading cause of cancer related death in the US (1). Despite recent

advances made in breast cancer research, triple negative breast cancer (TNBC)

remains the subtype with the poorest prognosis due to limited treatment options.

The 4T1 murine mammary metastatic model has been widely used as a model for

TNBC, because of the similarities in hormone receptor profile to human TNBC (2).

One caveat of the 4T1 model is that there are few known tumor associated

antigens which has limited the use of this model in preclinical immunotherapeutic

studies (3, 4). The firefly luciferase gene, luc2, has been transfected into various

tumor cell lines as a reporter gene for imaging studies. However, previous studies

demonstrate that the luciferase epitope can induce CD8+ cytotoxic T cell specific

responses, thus may be serving as a tumor antigen for immune recognition (5-7).

The goal of the current study was to explore the role of luciferase in 4T1.2 cells, a

clone that was selected for greater metastatic potential, and a model used to

evaluate nutrition and exercise interventions in our laboratory. Specifically, we

compared in vitro and in vivo growth rates, the role of immune components in tumor

growth, metastatic progression and survival rate in the parental 4T1.2 and

luciferase transfected 4T1.2 clone (4T1.2luc).

The goal of the first study was to determine if luciferase expression by the

4T1.2luc cell line altered the in vitro proliferative capacity compared to the parental

4T1.2 cell line. We cultured both 4T1.2 and 4T1.2luc mammary tumor cell lines

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(2,500 cells/well in serial dilution) in triplicate for 72 hours, and assessed in vitro

proliferation using the MTS assay. The proliferation rate of 4T1.2luc cell line did not

differ significantly from 4T1.2 cell line, which indicated luciferase expressed by the

4T1.2luc cell line is not actively involved in signaling cascades mediating cell

proliferation.

In the second study, we examined in vivo growth rates of 4T1.2 and 4T1.2luc

cells in immunocompetent BALB/c mice. We demonstrated that 4T1.2luc tumor-

bearing mice had a significantly reduced primary tumor growth compared to 4T1.2

tumor-bearing mice. Next, we wanted to determine which immune subtype was

responsible for the delayed tumor growth observed in 4T1.2luc tumor-bearing mice,

and if any of these immune population were important in controlling metastatic

progression or survival. To this end, we depleted the major effector immune cell

populations, CD4+ T cells, CD8+ T cells and NK cells, in both 4T1.2 and 4T1.2luc

tumor-bearing animals. We observed that CD4+ T cell, CD8+ T cell and NK cell

depletion did not affect primary tumor growth in 4T1.2 tumor-bearing mice.

However, CD8+ T cell depletion increased primary tumor growth and NK cell

depletion decreased primary tumor growth in 4T1.2luc tumor-bearing mice.

Metastatic burden in the lung and femur was not significantly different among

isotype control, CD4+ T cell-depleted and CD8+ T cell-depleted, and NK cell-

depleted 4T1.2luc tumor-bearing mice.

The final aim of this study was to determine the role of CD4+ T cells, CD8+

T cells and NK cells in the survival of 4T1.2 and 4T1.2luc tumor-bearing mice. We

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observed that 4T1.2luc tumor-bearing mice treated with PBS or the isotype control

antibody (LTF-2) had a significantly longer median survival than PBS or isotype

control antibody-treated 4T1.2 tumor-bearing mice. In 4T1.2 tumor-bearing mice,

CD4+ T cell, CD8+ T cell and NK cell depletion did not alter median survival.

However, CD4+ T cell, CD8+ T cell depletion reduced median survival in 4T1.2luc

tumor-bearing mice in comparison to control groups.

In conclusion, luciferase expression in the 4T1.2luc cell line did not alter the

in vitro proliferation rate but potentially served as an antigen for immune cell

recognition. In 4T1.2luc tumor-bearing mice, CD8+ T cells are important in

controlling primary tumor growth. Depletion of CD4+ T cells, CD8+ T cells and NK

cells did not significantly affect lung and femur metastatic burden. However, both

CD4+ T cell and CD8+ T cell populations are important for survival. In contrast, the

absence of CD4+ T cells, CD8+ T cells or NK cells did not significantly influence

primary tumor growth or survival in 4T1.2 model. Results from the current study

provide important information about the interaction between host immune

components and 4T1.2 and 4T1.2luc tumor cells.

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TABLE OF CONTENTS

LIST OF FIGURES...............................................................................................8

LIST OF ABBREVIATIONS.................................................................................9

ACKNOWLEDGEMENTS..................................................................................12

CHAPTER 1: LITERATURE REVIEW...............................................................13

1.1. Breast Cancer............................................................................................13 1.1.1. Overview of Mammary Gland........................................................13 1.1.2. Breast Cancer...............................................................................14

1.1.2.1. Overview...........................................................................14 1.1.2.2. Grade and Stage...............................................................15 1.1.2.3. Risk Factors......................................................................16 1.1.2.4. Current Treatment Strategies............................................18

1.1.2.4.1. Overview.......................................................................18 1.1.2.4.2. Surgical Resection........................................................18 1.1.2.4.3. Chemotherapy...............................................................19 1.1.2.4.4. Targeted Therapy..........................................................19 1.1.2.4.5. Immunotherapy..............................................................20

1.2. Immune System........................................................................................22 1.2.1. Overview........................................................................................22 1.2.2. Innate and adaptive immunity........................................................23

1.2.2.1. Innate Immunity...................................................................23 1.2.2.1.1. Overview........................................................................23 1.2.2.1.2. Innate Immunity Components........................................24

1.2.2.2. Adaptive Immunity...............................................................27 1.2.2.2.1. Overview........................................................................27 1.2.2.2.2. B Lymphocytes and Humoral Immunity.........................27 1.2.2.2.3. T Lymphocytes and Cellular Immunity...........................28

1.2.3. Immune Response to Malignancy…..............................................30 1.3. Animal Models of Breast Cancer..............................................................32

1.3.1. Overview........................................................................................32 1.3.2. 4T1 Breast Cancer Model Series...................................................34

1.4. Rationale of Current Study........................................................................37

CHAPTER 2: AIMS AND HYPOTHESES...........................................................38

2.1. Aim 1.........................................................................................................38

2.2. Aim 2.........................................................................................................39

2.3. Aim 3.........................................................................................................39

CHAPTER 3: MATERIAL AND METHODS.........................................................40

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3.1. Experimental Design.................................................................................40 3.2. Materials and Methods..............................................................................42

3.2.1. Cell Lines and Cell Culture..............................................................42 3.2.2. In vitro Cell Proliferation Assay.......................................................42 3.2.3. Animal Models and Tumor Implantation..........................................43 3.2.4. In vivo Immune Cell Depletion.........................................................43 3.2.5. Flow Cytometric Analyses...............................................................44 3.2.6. Metastatic Burden Quantification....................................................45

3.3. Statistical Analyses...................................................................................45

CHAPTER 4: RESULTS......................................................................................47

4.1. In Vitro Proliferation...................................................................................47 4.2. Depletion of Immune Cell Populations.......................................................49 4.3. Primary Tumor Growth..............................................................................51 4.4. Metastatic Burden Quantification...............................................................57 4.5. Survival Analyses......................................................................................59

CHAPTER 5: DISCUSSION.................................................................................64

CHAPTER 6: CONCLUSION AND FUTURE DIRECTIONS................................69

REFERENCES....................................................................................................70

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LIST OF FIGURES

Figure 3.1. Experimental design.............................................................

Figure 4.1. In vitro proliferation of 4T1.2 and 4T1.2luc cell lines............................

Figure 4.2. In vivo proliferation of 4T1.2 and 4T1.2luc cell lines............................

Figure 4.3. Splenic immune cell populations depletion in control and antibody

depleted mice........................................................................................

Figure 4.4. Tumor growth of individual mice in each treatment group by tumor

cell types..............................................................................................

Figure 4.5. Primary tumor growth in immunocompetent and immune cell

depleted 4T1.2 and 4T1.2luc tumor bearing mice.................................

Figure 4.6. Primary tumor growth of immune cell depleted groups compared to

control group of 4T1.2 and 4T1.2luc tumor bearing mice................................

Figure 4.7. Primary tumor growth comparison between 4T1.2 and 4T1.2luc tumor

bearing mice receiving the same treatment.................................

Figure 4.8. Lung and femur metastatic burden comparison of 4T1.2luc tumor

bearing mice treatment groups.................................

Figure 4.9. Survival curves in 4T1.2 tumor-bearing mice.................................

Figure 4.10. Survival curves in 4T1.2luc tumor-bearing mice.............................

Figure 4.11. Survival comparison between 4T1.2 and 4T1.2luc tumor-bearing

mice receiving the same treatment.............................................................

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LIST OF ABBREVIATIONS

2.43 Anti-mouse CD8α monoclonal antibody

4T1 Murine metastatic breast cancer model

ANOVA Analysis of variance

Asialo GM1 Anti Asialo ganglio-N-tetraosylceramide polyclonal antibody

APC Antigen-presenting cell

BCR B cell receptor

BRCA Breast cancer susceptibility gene

CD Cluster of differentiation

CLP Common lymphoid progenitor

CTLA-4 Cytotoxic T-lymphocyte-associated protein 4

DC Dendritic cell

DNA Deoxyribonucleic acid

ER Estrogen receptor

FBS Fetal bovine serum

FoxP3 Forkhead box O3

GK1.5 Anti-mouse CD4 monoclonal antibody

GM-CSF Granulocyte-macrophage colony-stimulating factor

HER2 Human epidermal growth factor 2

HSC Hematopoietic stem cell

HR Hormone receptor

IFN Interferon

IDO Indoleamine 2,3-dioxygenase

IGF Insulin-like growth factor

IgG Immunoglobulin G, isotype control

IL Interleukin

LTF-2 Rat IgG2b Isotype Control

MDSC Myeloid-derived suppressor cell

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MHC Major histocompatibility complex

MMP Matrix metalloprotenase

MMTV Murine mammary tumor virus

NK Natural killer cell

NKG2D Natural-killer group 2, member D

NLR Nod-like receptor

ORR Objective response rate

PAMP Pathogen-associated molecular pattern

PBS Phosphate-buffered saline

PCR Polymerase chain reaction

PD-1 Programmed cell death protein-1

PD-L1 Programmed death-ligand 1

PFS Progression-free survival

PGE Prostaglandin E

PR Progesterone receptor

PRR Pathogen recognition receptor

PTHrp Parathyroid hormone-related protein

RLR RIG-like receptor

ROS Reactive oxygen species

SHBG Sex hormone binding globulin

TAA Tumor-associated antigens

TAM Tumor-associated macrophage

TCR T cell receptor

TERT Telomerase reverse transcriptase

TGF-β Transforming growth factor beta

TH Helper T cell

TIL Tumor infiltrating lymphocyte

TLR Toll-like receptor

TME Tumor microenvironment

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TNBC Triple-negative breast cancer

TNF Tumor necrosis factor alpha

Treg Regulatory T cell (CD4+CD25+FoxP3+ TH cells)

VEGF Vascular endothelial growth factor

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ACKNOWLEDGEMENT

First of all, I would like to thank my advisor Dr. Rogers. It would be

impossible for me to be where I am right now without her guidance, mentorship,

and support during the darkest time of my life. She helped me develop the

confidence to conduct my own research and to seek out my own answers. She

taught me not to get hung up on negative results

I would like to acknowledge my other committee members, Dr. Laura

Murray-Kolb and Dr. Gregory Shearer. I want to thank them for committing their

time and expertise to helping me complete my degree. Their guidance and advice

were valuable in completing my research and organizing my findings into a

coherent story.

I would like to thank my lab mates Yitong Xu for her help with my project,

Bill Turbitt, Shawntawnee Collins and Donna Sosnoski for their guidance on

experimental techniques; Hannah VanEvery and Ester Oh for their emotionally

support. I am lucky to have you all.

I would like to thank my parents for their support both mentally and

physically during my most difficult time, I would not be here without their

unconditionally support. Finally, I would like to thank my wife Yalu Zhang, she

gave up everything coming to the States to take care of me, she made my difficult

days easier to get through, while I made her life harder. I can never repay her

sacrifice. This degree is dedicated to her.

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CHAPTER 1

LITERATURE REVIEW

1.1. Breast Cancer

1.1.1. Overview of Mammary Glands

Mammary glands are composed of various types of cells including

epithelial cells, adipocytes, fibroblasts, vascular endothelial cells and immune

cells (8, 9). Histologically, mammary tissue contains epithelium and stroma.

Mammary epithelium is primarily composed of luminal, basal epithelium and a

small population of stem cells. The inner luminal layer of epithelium faces a

central apical cavity and is surrounded by outer basal myoepithelial cells (10, 11).

Morphologically, the mammary gland consists of 15 to 20 lobes, each lobe is

made up of milk production units called lobules that are built up by ductal and

alveolar luminal epithelial cells (12). Growth and development of the mammary

gland is a complex process that is tightly controlled by hormones and growth

factors, which induce cell differentiation and proliferation (13). For example,

postnatal development is regulated by growth hormone and insulin-like growth

factor-1 (IGF-1) and estrogen plays an important role in breast development

during puberty. After reaching adulthood, progesterone is responsible for

alvelogenesis that prepares the breast tissue for pregnancy and lactation (9).

Mammary gland epithelium undergoes dramatic morphogenetic changes over

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the lifespan. Exposure to carcinogens or/and genetic predisposition can disrupt

intracellular signaling cascades that could trigger tumorigenesis (11).

1.1.2. Breast Cancer

1.1.2.1. Overview

Breast cancer is the most common diagnosed cancer among women in

the US and the second leading cause of cancer related death (1). It is estimated

266,120 new cases of breast cancer (15.3% of all new cancer cases) and 40,920

breast cancer deaths (6.7% of all cancer deaths) are to occur among US women

in 2018 (1, 14). Breast cancer, originates from the epithelial cells of the milk ducts,

is a heterogeneous disease in terms of histology, response to treatments,

metastatic patterns, prognosis and clinical outcome (15). Molecular subtypes of

breast cancer are primarily based on the expression of estrogen receptor (ER),

progesterone receptor (PR) and human epidermal growth factor 2 (HER2 also

known as ERBB2), which can provide important information in treatment

selection and prognosis (16-18). These subtypes include luminal A (ER+, PR+),

luminal B (ER+, PR+, HER+), HER2+ (ER-, PR-, HER2+) and Basal-like (Triple-

negative). Luminal A has the best prognosis mainly because this subtype is less

aggressive and more responsive to endocrine therapy, followed by luminal B

subtype (19-21). HER2+ subtype is negative in hormone receptors expression but

overexpresses human epidermal growth factor 2 (HER2+), which has been

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exploited for targeted therapy development (21-23). Basal-like subtype is usually

considered a synonym of the triple-negative subtype (TNBC), and lack

expression of sex hormone receptors and HER2. Treatment options are limited

to conventional chemotherapy and radiation therapy and has the poorest

prognosis relative to other subtypes (21, 23, 24). TNBC subtype itself is a group

of heterogeneous tumors that can be, based on molecular expression profile,

further classified into basal-like, mesenchymal, luminal androgen receptor, and

immune-enriched subtypes. Subclassification of TNBC provides crucial

information that may be important in determining the most effective treatment and

in exploring new therapeutic targets (25).

1.1.2.2. Grade and Stage of Breast Cancer

Tumor grade is a pathological method of tumor classification which

indicates the tendency of tumor cells to grow and spread based on the

resemblance of tumor cells appearance compared to the tissue of origin (26). In

general, tissues obtained from biopsy or surgical resection are graded as G1

through G4, with G1 tumor cells being low grade and well differentiated meaning,

while G4 tumor cells being poorly differentiated or undifferentiated that are

morphologically abnormal (tubule formation, nuclear morphology, mitotic figures

etc.) and may lack normal tissue structure (26). The most widely used grading

system for breast cancer is Nottingham grading system (27, 28), which classifies

tumors into three grades namely, low (Grade I), intermediate (Grade II), high

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(Grade III) based on differentiation or tubule formation, pleomorphism (shape and

size of tumor cells), hyperchromatic and mitotic nuclei (28).

1.1.2.3. Risk Factors

The etiology of breast cancer usually involves combinations of multiple

contributing factors (29, 30). Population based epidemiological studies have

identified a number of breast cancer risk factors including age, age at menarche

and menopause, age at first pregnancy, family history, lifestyle factors (diet,

weight, alcohol intake), smoking and hormone replacement therapy etc. (31, 32).

Breast cancer risk factors mentioned above can be classified into

nonmodifiable and modifiable (or life-style related) risk factors (29). The

nonmodifiable risk factors include age, sex, family and personal BC history, race

and ethnicity, genetic alterations, higher breast density, early menstruation or late

menopause and environmental exposures such as ionizing radiation (29, 33).

Among these factors, age is the most significant non-modifiable risk factor.

Female breast cancer is most frequently diagnosed in women aged from 55 to

64 years old with the median age of 61-years-old (14). Being female significantly

increases the risk of breast cancer as less than 1% of all breast cancer cases are

diagnosed in males (34). Family history, especially having a first-degree relative

(mother, sister or daughter) with breast cancer is associated with a two to three

fold increase in breast cancer risk (35).

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Disparities of breast cancer occurrence among ethnic groups are

significant: i.e. African American women tend to develop more aggressive breast

cancer and poorer prognosis than Caucasian women. In contrast, Asian,

Hispanic, and Native American women have a lower risk of developing and dying

from breast cancer than African and Caucasian American women (33, 36).

The most common genetic alterations associated with breast cancer is an

inheritable mutation in the BRCA1 or BRCA2 genes which are involved in DNA

repair (33). Mutation of either is associated with increased breast cancer and

ovarian cancer risks (37, 38). Higher breast density, characterized by higher

percentage of fibroglandular tissue and less adipose tissue, is also associated

with higher breast cancer risk (39). Starting menstruation younger than age 12 or

going through menopause older than 55 increase risk of breast cancer later in life

possibly due to increased exposure to ovarian hormones (40, 41).

Modifiable risk factors include diets, alcohol consumption, overweight or

obesity, physical inactivity, nulliparity, breast feeding, menopausal hormone

replace therapy (29, 33). Alcohol consumption, even at moderate level, is a risk

factor for multiple cancer types including breast cancer, and the association can

be extended to multiple ethnic groups (42, 43). An increase in BMI is associated

with postmenopausal breast cancer but does not increase breast cancer risk in

premenopausal women (33, 44), which can be partially explained by obesity

induced insulin resistance. Hyperinsulinemia followed by obesity decreases

circulating insulin-like growth factor binding proteins (IGFBPs) and sex hormone

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binding globulin (SHBG), which in turn, increase the availability of insulin-like

growth factor (IGF) and estrogen in blood circulation. These hormones together

with increased circulating insulin, significantly promote cell proliferation which

might lead to mutation of breast epithelial cells into malignancy (33, 45, 46).

Obesity induced low-grade chronic inflammation is associated with increased

proinflammatory cytokines, enhanced aromatase expression and hormone

receptors expression which also contribute to the development of breast cancer

(47). Physical inactivity together with increased BMI elevate breast cancer risk by

negatively affecting energy balance in terms of energy intake and expenditure,

insulin sensitivity, circulating IGF and IGFBPs and steroid sex hormones (48, 49).

Reproductive factors such as early full-term pregnancy and breast feeding have

been associated with decreased breast cancer (33, 50).

1.1.2.4. Current Treatment Strategies

1.1.2.4.1 Overview

Multiple therapeutic options are available for breast cancer patients and

can be classified into local and systemic treatments. Surgery and radiation

therapy are considered local treatments while chemotherapy, hormone therapy,

targeted therapy and immunotherapy are classified as systemic treatments due

to their treatment agents being transported throughout the body via the

bloodstream.

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1.1.2.4.2 Surgical Resection

Surgical approaches to remove breast cancer include breast-conserving

surgery (also known as lumpectomy) and mastectomy (51). Lumpectomy or

partial mastectomy is a surgical procedure that only the cancer and some

surrounding normal tissue are removed while mastectomy is a radical surgical

procedure in which the entire breast and sometimes other nearby tissues are

resected (51, 52). Clinical trials indicate that the combination of lumpectomy with

radiation therapy (using ionizing radiation to damage DNA of fast dividing cancer

cells) is associated with reduced recurrence and improved survival over

lumpectomy or mastectomy alone; therefore, lumpectomy with radiation is an

appropriate therapeutic strategy for early stage breast cancer patients (53, 54).

1.1.2.4.3 Chemotherapy

Chemotherapy is one of the systemic therapy strategies for breast cancer,

aiming to control the primary tumor growth and eliminate distant metastasized

microscopic tumors or single cancer cells circulating within the body. Based on

the mechanism of action and chemical structure, chemotherapy can be classified

into alkylating agents, antimetabolites, anti-microtubule, and topoisomerase

inhibitors (55-58). Despite the side effects and toxicity, chemotherapy remains a

standard systemic therapeutic strategy for triple-negative breast cancer (TNBC)

in neoadjuvant, adjuvant and metastatic settings (24, 59).

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1.1.2.4.4 Targeted Therapy

With better understanding of the underlying breast cancer biology and

molecular subtypes of breast cancer, a great number of targeted therapeutic

agents have been developed in recent years (21, 60). Based on hormone

receptor expression (i.e. ER+, PR+) of breast cancer patients, hormone receptor

antagonists such as ER inhibitor tamoxifen and degrading agents such as

fulvestrant (by binding to the hormone receptor and causing the cell's normal

protein degradation processes) can be used to block sex hormones from binding

to their receptors (60). HER2+ subtypes are generally resistant to hormone-based

therapies despite the expression of hormone receptors (HR). HER2 blockers

such as monoclonal antibodies pertuzumab and trastuzumab (Herceptin) are

effective in HER2+ subtype patients, and combination strategies such as HER2

blocker with HR inhibitors significantly reduces the risk of progression (18, 61).

1.1.2.4.5 Immunotherapy

Breast cancer was originally considered non-immunogenic or less

inflamed than those cancer types with high somatic mutation rates such as lung

squamous carcinoma (62). However, after decades of research focused on the

role of the immune system in breast cancer development and progression, the

field of breast cancer immunotherapy has been expanding dramatically (63).

ER+ or luminal breast cancer subtypes are less immunogenic compared

to TNBC subtype. Some successful immunotherapeutic approaches on other

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cancer types including checkpoint inhibitors, and adoptive T cell transfer are

being investigated pre-clinically (64).

HER2+ subtype is considered more immunogenic and has more tumor

infiltrating lymphocytes (TILs) compared to luminal subtypes (65) which led to the

investigation efficacy of several immunotherapeutic strategies on HER2+ breast

cancer, including immune checkpoint inhibitors. Immune checkpoints are

molecules expressed by immune cells that are crucial for self-tolerance which

prevent autoimmunity but can also limit immune cells from killing cancer cells.

Preclinical studies have shown that antibodies against immune checkpoint

(checkpoint inhibitors) such as anti-PD-1 can increase the effectiveness of anti-

HER2 therapy, which led to the initiation of several phase I and II trials (66, 67),

to evaluate the potential superiorities of checkpoint inhibitors and anti-HER2

monoclonal antibodies (mAbs) combinations versus single anti-HER2 antibody

treatment (65, 68).

Among subtypes of breast cancer, TNBC is considered most immunogenic

among all the breast cancer subtypes due to the significant amount of genetic

mutations and subsequent immunogenic protein products such as MAGE-A3 and

NY-ESO-1(69, 70). These neoantigens can be recognized by the immune system

as foreign invaders therefore more likely to attract greater number of antigen

specific lymphocytes (tumor-infiltrating lymphocytes or TILs) into tumor

microenvironment (TME) (65, 71). Efficacy of Immune checkpoint inhibitors in

breast cancer have been clinically investigated including monoclonal antibodies

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(mAb) targeting Programmed Cell Death 1 (PD-1) or Programmed Cell Death

Ligand 1 (PD-L1) (72, 73), showing preliminary evidence of clinical activity and

acceptable safety profile; there is an ongoing phase III trial aimed to compare

overall survival (OS) and progression-free survival (PFS) between participants

receiving pembrolizumab and chemotherapy (74). In addition to single agent

immunotherapy, combination approaches of chemotherapy and checkpoint

inhibitors have also been extensively studied. Some chemotherapeutic drugs can

selectively inhibit the proliferation of regulatory T cells (Tregs) and myeloid-

derived suppressor cells (MDSCs) so that relieving the suppression of antigen

specific response against cancer cells. Moreover, by causing cancer cell death,

chemotherapy promotes the release of neoantigens that can be taken up and

presented by antigen presenting cells (APCs) and therefore increases antigen

specific CD8+ T cell infiltration and activation (75-77). Based on these findings,

several phase I and II clinical trials were conducted to evaluate the combination

of different chemotherapy drugs and PD-1 or PD-L1 inhibitors in metastatic TNBC

patients, preliminary results showed promising objective response rate (ORR)

and good tolerance, which paved the way for the ongoing phase III double-

blinded randomized controlled trials (78, 79).

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1.2 Immune System

1.2.1. Overview

The immune system is a host defense system comprising various

specialized organs, tissues, cells, and proteins that protect against foreign

pathogenic agents and transformed self-cells (80). Specialized immune cells are

differentiated from bone-marrow-dwelling hematopoietic precursor cells, and the

differentiation processes are a tightly controlled intricate series of highly regulated

signaling events. The immune system is divided into two parts determined by the

rapidity and specificity of the reaction, namely innate and adaptive immune

systems (81).

1.2.2. Innate and Adaptive Immunity

1.2.2.1. Innate Immunity

1.2.2.1.1 Overview

Innate immunity is a primitive host defense mechanism and the first-line of

defense against foreign invaders. After breaching host’s anatomic barriers,

pathogens will encounter a series of antimicrobial enzymes and peptides that can

digest bacterial structural components such as cell wall and membrane and the

complement system will target pathogens that facilitate phagocytosis by cellular

components of innate immunity. Most of the cellular components of the innate

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immune system are derived from the common myeloid progenitor cells, including

macrophages (mature form of monocytes), granulocytes (including neutrophils,

eosinophils, basophils and mast cells) and dendritic cells. Natural Killer cells (NK

cells) of lymphoid lineage are also part of innate immunity (82). These immune

cells recognize pathogens by various mechanisms including Fc receptors,

scavenger receptors and pathogen recognition receptors (PRRs). PRRs include

Toll-like receptors (TLRs), Nod-like receptors (NLRs), C type lectin receptors and

RIG-like receptors (RLRs). Microbes contain classes of molecules including

lipopolysaccharides, endotoxins, viral DNA and double-stranded RNA; these

molecules, called pathogen-associated molecular patterns (PAMPs), can be

recognized by innate immunity as foreign via their cell surface or cytoplasm PRRs

to trigger phagocytosis and subsequent inflammatory responses that are

characterized by proinflammatory cytokine and chemokine production (81, 83).

Besides eliminating pathogens at the sites of infection, professional antigen

presentation cells will migrate to lymphoid organs and present antigens to

activate adaptive immune cell populations including T cells and B cells will be

activated to carry out prolonged antigen-specific immune responses (81).

1.2.2.1.2 Innate Immunity Components

Macrophages, together with granulocytes and dendritic cells, comprises

phagocyte types of immune system and also play an important role in activating

adaptive immunity by presenting antigens (82). These cell populations can

recognize pathogens (bacteria, virus and transformed cells) and pathogen

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components (LPS, viral DNA, and neoantigen etc.) via cell surface receptors

including PRRs, Fc receptors, C-type lectin receptors and scavenger receptors

and ingest pathogens via phagocytosis. Despite their similarities, macrophages

are usually the first defensive cell population that pathogens encounter after

breaching physical barrier. Upon recognition and phagocytosis, macrophages

are activated, pathogens are killed and degraded by lysozymes and reactive

oxygen species (ROS) contained in lysosomes. Pathogen components are

processed into small immunogenic molecules and conjugated with MHCII (major

histocompatibility complex II) to present on the cell surface. Simultaneously,

activated macrophages secrete pro-inflammatory cytokines and chemokines

such as IL-1β, IL-6, TNF-α and GM-CSF to initiate inflammatory response by

recruiting other immune cells to the site of infection for pathogen clearance (81,

82).

Granulocytes (include neutrophils, eosinophils, basophils and mast cells)

contain specialized granules that are either low in pH or holding reactive oxygen

species (ROS), lysozymes and antimicrobial peptides to kill microbes or initiate

allergic reactions (81). Neutrophils are the most abundant granulocytes in

circulation and the first to be recruited to the site of infection, primarily in response

to GM-CSF secreted by macrophages (81, 82). Besides the importance in killing

pathogens, neutrophils are also professional antigen presenting cells (APC) that

present antigens via MHCII in response to cytokines such as GM-CSF, IFN-γ,

TNF-α (84). Eosinophils and basophils are less abundant than neutrophils and

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eosinophils mainly focus on battling parasitic infection while basophils and mast

cells are involved in allergic reactions (82).

Dendritic cells (DCs), of either lymphoid or myeloid lineage, are also

phagocytes, their functions are more focused on antigen presentation rather than

pathogen clearance (85, 86). A large number of dendritic cells migrate to infection

sites in response to the cytokines and chemokines secreted by macrophages and

other tissue residence immune cell types (81, 85). After encountering infectious

agents, dendritic cells recognize pathogens via various surface receptors

including opsonin receptors, Fc receptors, scavenger receptors and pattern

recognition receptors (PRRs) (86). After encountering pathogens, dendritic cells

mature into potent antigen presenting cells that are characterized by increased

expression of cell adhesion molecules such as E-selectin, ICAM-1 and VCAM-1

that facilitate dendritic cells’ migration to secondary lymphoid organs, expression

of antigen-conjugated MHC molecules and costimulatory ligands such as B7 that

are crucial to prime and activate naïve T cells (83, 85, 87).

Common lymphoid progenitor (CLP) derived Natural Killer cells (NKs) are

important first line innate effector cells against foreign or mutated cells (81). NK

cells are nonspecific effector cells that recognize pathogens and transformed

cells via multiple mechanisms including Fc receptor binding to antibody coated

cells and NK activating receptors such as natural-killer group 2, member D

(NKG2D) binding to NKG2D ligands (81, 88). Healthy body cells express major

histocompatibility complex I (MHCI) on their surface that can bind to inhibitory

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receptors of NK cells thus prevent NK cells from attacking healthy tissue, while

transformed cells or pathogens that lack self MHCI can activate NK cell (88). The

pathogen-killing effects of NK cell are carried out by their cytoplasmic granules

that contain cytotoxic proteins such as granzyme and perforin (89). After binding

of activating receptors to target cells which lack MHCI expression, and in

response to macrophage derived cytokines such as IFNs and IL-12, NK cells

release cytotoxic proteins to induce apoptosis of the targets and secrete large

amount of IFN-γ to contain infection before adaptive immunity is activated (89-

91).

1.2.2.2. Adaptive Immunity

1.2.2.2.1 Overview

The adaptive immune system is composed of T and B lymphocytes and is

characterized by their ability to specifically respond to immunogenic proteins

expressed on pathogenic foreign microorganisms and transformed cells (63). The

pathogen recognition receptors of innate immunity undergo somatic

hypermutation that reshuffles the genetic coding of variable region of T cell

receptors (TCR) and B cell receptors (BCR), which enable them to recognize

specific antigenic molecules (92).

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1.2.2.2.2 B Lymphocytes and Humoral Immunity

B cells are derived from common lymphoid progenitor cells (CLPs) that

can be traced back to hematopoietic stem cells (HSCs). In the bone marrow, in

response to various cytokine signals, CLPs give rise to pre-B cells which undergo

several developmental stages that involve specific transcription factors into

immature B cells and leave the bone marrow; Immature B cells will arrive in

spleen and proceed through transitional stages namely T1 and T2, then into

mature B cells in germinal center and migrate to lymphatic system. In this

process, heavy chain and light chain genes of pre-BCRs proceed through

somatic hypermutation and transcribe into antigen specific BCRs. Mature/naïve

B cells express IgM and IgD on their cell surface (81, 92, 93).

B cells are activated after encounter with antigen and become either

memory B cells or plasma cells, the activation processes are either T cell

dependent or independent (92). B cells can recognize antigen by the surface

BCRs and then internalize, process and present the antigen on MHCII that can

be recognized by T cells (T follicular helper cells) in secondary lymphoid organs,

T cells in turn produce cytokines that are essential for B cells maturation and

activation into memory or plasma cells (94). On the other hand, some molecules

can interact with BCRs without the assistance of T cells and elicit an activating

signal, with additional cytokines or other cells (such as DCs) in contact, B cells

can be activated into memory or plasma cells (95).

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Antibodies produced by B cells are the key mediators of humoral immunity.

Antibodies can prevent pathogens such as viruses and intracellular bacteria from

entering host cells by binding to their surface molecules (96). Antibodies also

facilitate phagocytosis by coating pathogen surfaces (97). Last but not the least,

antibodies binding to pathogens can activate the complement system to enhance

phagocytes recognition via complement receptors (97).

1.2.2.2.3 T Lymphocytes and Cellular Immunity

T cells are also derived from CLPs from bone marrow but the maturation

process takes place in the thymus where individual T cells with specific binding

capacity are formed.

In order to be activated, mature yet naïve T cells need to interact with

antigenic molecules in the context of MHC molecules on APCs. There are two

types of MHC that T cell receptors bind: MHCI expressed on all nucleated cell

surfaces that presents endogenous such as viral or tumor antigens, and MHCII

on APCs that present exogenous antigen by endocytosis (92). Besides

interaction between TCRs and MHC/peptide complex, costimulatory molecules

such as CD28 (binds to CD80/CD86 (B7)) from APCs are also required to activate

T cells (81). Lastly, various cytokines can drive the differentiation of CD4+ T cells

into various subsets with distinct functions, including T helper 1 (TH1), T helper 2

(TH2), T helper 9 (TH9), T helper 17 (TH17), T helper 22 (TH22), follicular helper T

cells (TFH), and regulatory T cells (Tregs) (92).

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The major functions of CD4+ helper T cells are regulating immune

responses via cytokine secretion, including B cell antibody class switching,

cytotoxic T cell activation, and phagocytes pathogen clearing activities (81, 92).

Activated CD8+ cytotoxic T cell population can eliminate bacteria or virus infected,

stressed, and tumor cells by recognizing antigens presented on MHC class I

molecules and inducing apoptosis via the release of cytotoxins, perforins, and

granzymes or through the expression of surface proteins such as Fas ligand (92,

98).

1.2.3. Immune Response to Malignancies

The interaction between the immune system and cancer is a complex

process that involves the balance between pro- and anti-tumor mediators. Based

on the initial concept of ‘immune surveillance’ introduced by Burnett and Thomas,

the interaction of the immune system and cancer now includes three phases:

elimination, equilibrium and escape phase (99-102).

Elimination phase of cancer immunoediting is the process that innate and

adaptive immune components recognize and eliminate transformed cells from

developing into visible tumors. Both innate and adaptive immune cells are

involved in killing of cancer cells, major effectors include NK cell of innate

immunity, and adaptive immunity mainly CD8+ cytotoxic T cell with the assistance

of CD4+ Helper T, especially TH1 cells (99). NK cells are activated when tumor

cells (usually with reduced MHCI expression) are recognized via surface binding

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of activating receptor NKG2D to NKG2D ligands such as MICA/B of human and

H60, Rae-1 of mouse (99, 103). Initial recognition of cancer cells by innate

immune cells such as NK, NKT, macrophages and dendritic cells (DCs) triggers

the production of proinflammatory cytokines such as IFN-γ, which increases anti-

tumor activity in multiple ways such as upregulating tumor cells’ MHCI expression

that facilitates CD8+ T cell’s recognition and killing process (99). Activated DCs

migrate to secondary lymphoid organs to initiate the production of tumor-specific

T cells (99). Classic tumor antigens include differentiation (i.e. melanocyte

differentiation antigen), mutation (i.e. mutated p53), overexpressed (i.e.

HER2/neu) testis (i.e. MAGE) and viral antigens (104-106). Activated NK, CD8+

T cell and other immune cell populations target and kill tumor cells by releasing

perforin, granzyme from secretory lysosome, increasing expression of TNF-

related apoptosis-inducing ligand (TRAIL) and First apoptosis signal Ligand

(FasL) inducing apoptosis of tumor cells (99, 107).

The equilibrium phase is the immunity-tumor interaction where cancer is

stably controlled by immune system or becomes dormant but not eliminated.

Tumor cells in the equilibrium phase will eventually be eliminated or escape from

immunosurveillance and develop into visible tumors (99).

The escape phase describes the failure of the immune system to eradicate

transformed cells and the outgrowth of these cells into clinically detectable

tumors. Cancer cells achieve evasion of destruction by the immune system via a

combination of various mechanisms. Cancer cells are rapidly mutating due to the

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unstable genome that will eventually contribute to heterogeneity of tumor cells,

therefore it is likely that the immune system fails to recognize and eliminate all

the variants, such as the ones that lack TAAs, NKG2D ligands expression, or the

variants with increased expression of PD-L1 including breast cancer cells (108,

109). Tumor cells together with tumor associated macrophages (TAMs) can also

generate an immunosuppressive microenvironment by producing anti-

inflammatory cytokines, such as TGF-β, IL-10, and recruit regulatory T cells

(Tregs) that can prevent the activation of DCs, NK cells, T cells and B cells (99,

110). Cytokines such as granulocyte-macrophage colony-stimulating factor (GM-

CSF), interleukin-1β (IL-1β), vascular endothelial growth factor (VEGF), and

prostaglandin E2 (PGE2) are responsible to recruit myeloid-derived suppressor

cells (MDSCs) to TME, which are another source of immunosuppressive

cytokines such as TGF-β. MDSCs can also deplete arginine (essential for T cell

function) by secreting arginase, and debilitate T cell receptor (TCR) function by

nitrosylation (80, 111). Lastly, tumor cells can directly inhibit T cell proliferation

by producing indoleamine 2,3-dioxygenase (IDO) to deplete tryptophan leading

to cell cycle arrest (112).

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1.3 Animal Models of Breast Cancer

1.3.1 Overview

For decades, animal models have been used to study primary tumor

growth and metastatic spread with and without therapeutic interventions (113)..

Current available in vivo murine models for metastatic breast cancer can be

classified into two categories: experimental metastasis models and spontaneous

(metastasis arises spontaneously from primary tumor) models including

transgenic and transplantable models (114). Experimental metastatic models are

designated for the investigation of tumor colonization mechanisms at a secondary

site, by injecting tumor cells into circulation or specific organs. Transgenic models

have several advantages that allow researchers to study the entire process of

cancer progression including tumor initiation, pre-metastatic niche as well as

distant colonization, additional oncogene or tumor suppressor genes can also be

inserted to study oncogenic pathways (113-116). Compared to transgenic

models, transplantable models allow researchers to quickly assess metastatic

process, because of their short metastatic onset latency and multiple metastatic

sites such as brain, liver and bone that most transgenic models lack. Tumor cell

lines of transplantable models usually can be modified in vitro before inoculation,

such as transfection of a foreign gene (114).

Murine transplantable models can be divided into two groups, xenograft

and syngeneic transplantable models (113). Xenograft models involve

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transplanting human cell lines or cells isolated directly from patients into

immunocompromised hosts. However, several limitations weaken the predictive

power of xenograft models as pre-clinical cancer models. First,species specificity

sets a boundary for tumor-stromal interaction which is critical for clinically relevant

cancer progression and metastasis (113, 117). Secondly, in order to prevent host

rejection of human cell implantation, the murine host must be

immunocompromised which makes it impossible to investigate the role of

immune system in tumor progression (118). Lastly, immunocompromised mice

such as nude mice have been reported containing impaired or altered

angiogenesis within transplanted tumors (119, 120). Syngeneic transplantable

model tumor cell lines are isolated from spontaneous tumors triggered by

carcinogens and can be repeatedly and orthotopically injected into the host

animal to initiate primary tumor growth and metastasis (121, 122). Currently, the

4T1 series is the most widely used transplantable breast cancer model.Tumor

cells can be injected into mammary gland as allograft with genetic and

immunological compatibility while spontaneous metastasis to distant organs can

be achieved quickly (2, 114, 121).

1.3.2 4T1 Breast Cancer Model Series

The 4T1 transplantable model mimics human stage IV triple negative

breast cancer; the 4T1 cell line was originally isolated by Miller et al. and was one

of four sublines (67NR, 168FARN, 4T07, and 4T1) derived from 410.4 tumor

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(121, 123). The 410.4 cell line was isolated from a spontaneously initiated

mammary tumor of a BALB/c female mouse triggered by murine mammary tumor

virus (MMTV) infection (123). These four cell lines display different metastatic

capacities: with 67NR being nonmetastatic, 168FARN being local micro-

metastatic, 4TO7 being weakly metastatic to distant organs but unable to form

metastatic nodules and 4T1 cell line being highly tumorigenic and can

spontaneously metastasize from primary mammary tumor also form visible

nodules in distant organs including lung, liver, bone and brain (121, 124, 125).

The 4T1.2 transplantable tumor cell line is a single cell clone derived from

the 4T1 cell line as a site-specific metastatic breast cancer model to the bone

(122). 4T1.2 is currently one of a few transplantable models with molecular

features of a human triple-negative and basal like phenotype (ERα-, PR-, HER2-

and EGFR+) (2), which makes it a valuable model for investigating bone

metastasis and developing new therapeutic strategies to the triple-negative and

basal like human breast cancer patients (20). Interaction with surrounding stroma

is important to initiate metastasis. 4T1.2 cell adhere to collagen I, IV, fibronectin

and especially stronger to vitronectin and lamin-511 than its non-metastatic

cousin 67NR (126). Matrix metalloproteinases (MMPs) are an enzyme family that

are crucial for cancer metastasis by degrading basement membrane in human

breast cancer, it was reported 4T1.2 cells produce more active MMP-9 than 67NR

with the stimulation of its substrate laminin-511 (127, 128). It has also been

reported that compared to 67NR, metabolic plasticity and adaptivity enables 4T1

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cells to better adapt in the tumor microenvironment which is important to establish

metastasis (125). As a bone metastatic model and similar to human breast cancer

cells, 4T1.2 cell line is also characterized by elevated parathyroid hormone-

related protein (PTHrP) secretion compare to other 4T1 family cell lines, and Ca2+

circulation of 4T1.2 tumor bearing mice is also significantly increased relative to

other 4T1 family tumor bearing mice (122, 129).

4T1 transplantable model family are valuable tools to study breast cancer

metastasis due to their similarity with human TNBC in molecular profile; yet unlike

human TNBC, mouse 4T1.2 breast cancer model lacks identifiable tumor

associated antigen (3, 4) which limits the model’s applicability in investigating the

interaction of immune system especially antigen-specific immunity with tumor

cells. To preclinically examine immunotherapeutic approaches against TNBC,

modifications to 4T1 series were done aimed to increase the immunogenicity,

such as introducing human TAAs to these cell lines (130).

4T1.2luc cell line was originally developed by Lou and Dedhar (131) by

transfecting a plasmid shuttle vector containing luciferase reporter gene luc2 into

4T1.2 cells and thus established a luciferase-expressing cell line (132). Firefly

luciferase gene luc2, as a reporter gene, was first reported more than three

decades ago and later adopted by scientists as an approach to design

informative, noninvasive yet cost-effective in vivo studies (133). In the field of

cancer research, transfection of luc2 into transplantable tumor cell line allows

scientists to track metastasis and micro-metastasis noninvasively with the aids of

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bioluminescent imaging and PCR technologies (134-136). Despite the benefits

brought by luciferase reporter gene in the application of orthotopic transplantable

models, it has been suggested that reporter transgenes including β-

galactosidase, Enhanced green fluorescent protein (EGFP) and luciferase

epitopes can induce CD8+ T cell specific response that is characterized by

increased interferon-γ (IFN-γ) secretion (5). Moreover, it has been reported that

4T1 cell lines labeled with luciferase reporter gene displayed a reduced tumor

growth rate and a suppressed metastatic activity in immunocompetent BALB/c

mice, which could potentially compromise the utility of these models, but it may

also provide important information for immunotherapy development (6, 7).

Until now, no study has been published characterizing the in vivo

tumorigenesis, metastasis and immunogenicity of 4T1.2luc cell line compared to

the parental 4T1.2 cell line. With the preliminary evidence that firefly luciferase

may be immunogenic in the 4T1 model, it is reasonable to hypothesize similar

antigenic effect of luciferase expressed by 4T1.2 cells will be observed.

1.4 Rationale of Current Study

The 4T1.2 transplantable model is the most widely used for modeling

human triple negative breast cancer (TNBC) due to the similarities in molecular

profile (Lacking in ER, PR and HER2 expression) and sites of metastases. Unlike

human breast cancer, however, the 4T1.2 tumor cell line lacks defined tumor

associated antigens (TAAs) which limits its utility in immunotherapeutic research.

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Previous studies demonstrate that luciferase (as a foreign protein) can elicit CD8+

T cell specific response in vitro and reduce primary tumor growth in both the 4T1

and other tumor models (5, 7), but no studies have been done to directly

characterize the role of luciferase in the luciferase-expressing 4T1.2luc model.

Therefore, the primary goal of this study was to explore the in vitro and in vivo

growth rates of 4T1.2 vs. the 4T1.2luc mammary tumor cells. In addition, we also

investigated the role of major cancer immunosurveillance components (CD4+ T

cells, CD8+ T cells and NK cells) in primary tumor growth, metastatic progression

and survival rate. Findings of this study can provide important information for

future pre-clinical research in immunotherapeutic strategies targeting TNBC.

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CHAPTER 2

AIMS AND HYPOTHESES

2.1. Aim 1

Determine if the expression of luciferase in the 4T1.2 clone (4T1.2luc), alters

the in vitro or in vivo proliferative capacities compared to the parental cell

line 4T1.2.

Hypothesis 1: Luciferase serves only as an antigen and has no known functions

in mediating signaling cascades that govern tumor cell proliferation. Therefore,

we hypothesize 4T1.2 and 4T1.2luc cell lines will have similar in vitro proliferation

rates.

Hypothesis 2: In an immunocompetent host, luciferase will be recognized as a

foreign antigen. Thus, primary tumor growth of 4T1.2luc cells will be reduced

compared to the growth of 4T1.2 cells.

2.2. Aim 2

Determine the role of CD4+ T cells, CD8+ T cells and NK cells in controlling

primary tumor growth and metastatic progression in 4T1.2luc and 4T1.2

tumor-bearing mice.

Hypothesis 1: Depletion of CD4+ T cells, CD8+ T cells and NK cells in 4T1.2luc

tumor-bearing mice will enhance 4T1.2luc tumor growth and metastatic burden.

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Hypothesis 2: Depletion of CD4+ T cells, CD8+ T cells and NK cells in 4T1.2

tumor-bearing mice will have no effect on 4T1.2 tumor growth and metastatic

burden.

2.3. Aim 3

Determine if the absence of CD4+ T cells, CD8+ T cells and NK cells alters

the survival rate of 4T1.2 and 4T1.2luc tumor-bearing mice respectively.

Hypothesis 1: Immunocompetent 4T1.2luc tumor-bearing mice (i.e. mice treated

with PBS or isotype control antibody, LTF-2) will have a significantly higher

survival rate compared to 4T1.2 tumor-bearing mice.

Hypothesis 2: Depletion of CD4+ T cells, CD8+ T cells or NK cells will not

significantly affect the survival rate of 4T1.2 tumor-bearing mice.

Hypothesis 3: Depletion of CD4+ T cells, CD8+ T cells or NK cells will significantly

decrease the survival rate of 4T1.2luc tumor-bearing mice.

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CHAPTER 3

MATERIAL AND METHODS

3.1. Experimental Design

The study was designed to investigate the role of CD4+ T cells, CD8+ T cells

and NK cells in controlling primary tumor growth, metastatic burden, and survival

in 4T1.2 and 4T1.2luc tumor-bearing mice. Two cohorts of female BALB/c mice

were used for either 4T1.2 and 4T1.2luc tumor cell inoculation. Each cohort was

randomized into five treatment groups, including PBS control (intraperitoneal

injection [i.p.] with PBS), isotype control (i.p. injected with 100 µg LTF-2 antibody),

CD4+ T cell depletion (i.p. injected with 100 µg GK1.5 antibody), CD8+ T cell

depletion (i.p. injected with 100 µg 2.43 antibody) and NK cell depletion (i.p.

injected with 20 µl anti-asialo GM1 antibody). Injection of PBS and the

aforementioned antibodies started three days prior to tumor cell inoculation and

was maintained every three days until day 23 post tumor implantation. 4T1.2 or

4T1.2luc cells (5 × 104 tumor cells in 50 l of PBS) were implanted into the fourth

mammary gland of each mouse at day zero. Primary tumor growth was measured

two-three times per week using digital caliper until the day 35 post tumor

implantation. The experimental design and sample size of each group are shown

in Figure 3.1.

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Figure 3.1. Experimental design. Two groups of BALB/c mice were orthotopically injected with either 5 X 104 4T1.2 or 4T1.2luc tumor cells into the fourth mammary gland. Each treatment group was injected with depleting antibodies for specific immune cell population starting three days before tumor cell inoculation and maintained every three days until day 23 post tumor implantation. Primary tumor volume was measured every two-three days. Mice were sacrificed on day 35, spleens were collected to confirm immune cell depletion, lungs and femurs of 4T1.2luc tumor bearing mice were collected to quantify metastatic burden.

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3.2. Materials and Methods

3.2.1. Cell Lines and Cell Culture

The 4T1.2 murine breast cancer cell line was maintained in α minimum

essential medium (Life Technologies; Grand Island, NY) supplemented with 10%

fetal bovine serum (Gemini Bio-Products, Sacramento, CA), 2 mM L-glutamine

(Mediatech; Manassas, VA) 100U/ml penicillin (Mediatech) and 100 μg/ml

streptomycin (Mediatech) and incubated at 37°C with 5% CO2. The 4T1.2luc cell

line was maintained in Dulbecco’s modified Eagle’s medium (Life Technologies;

Grand Island, NY) containing 10% fetal bovine serum (Gemini Bio-Products,

Sacramento, CA), 2 mM L-glutamine (Mediatech; Manassas, VA), nonessential

amino acid (Mediatech), and 8 μg/ml puromycin (Mediatech) and incubated at

37°C with 5% CO2.

3.2.2. In Vitro Cell Proliferation Assay

Trypsin/EDTA (0.25%/2.21 mM) in HBSS was added to culture flasks to

harvest 4T1.2 and 4T1.2luc cells. Tumor cells were washed twice in their

respective media, adjusted to 2.5×103/ml, and plated using serial dilutions in a 96

well plate. Cells were allowed to proliferate for 48 prior to the removal of 70 l of

supernatant for cytokine analysis. 50 µl media and 20µl/well of CellTiter 96®

AQueous One Solution Reagent (Promega) were added back to well to quantify

proliferative capacity of the cells. After incubation for 90 minutes the plate was

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read using an Epoch™ microplate spectrophotometer (BioTek, Winooski, VT) to

quantify absorbance at 490nm. Each assay was performed in triplicate.

3.2.3. Animal Model

Six-week-old female BALB/c mice were purchased from Jackson

Laboratory (Bar Harbor, MA). Mice were orthotopically injected either with 5×104

4T1.2 cells (parental cell line) or 4T1.2 cells transfected with luciferase (4T1.2luc)

into the fourth mammary gland. Primary tumor growth was measured two-three

times/week using digital caliper until the endpoint day 35 post tumor implantation

and tumor volume was calculated following the equation of v=(short2×long)/2.

For the survival study, mice were sacrificed when either the tumor size reached

the ethical limit (1.5cm3) or if the mice were moribund. All mice were housed at

The Pennsylvania State University in the Chandlee Laboratory animal facility and

maintained on a 12-hour light/dark cycle with free access to AIN-76A diet

(Research Diets, New Brunswick, NJ) and water. The Institutional Animal Care

and Use Committee of The Pennsylvania State University approved all animal

experiments.

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3.2.4. Depletion of immune Cells

Two cohorts of female BALB/c mice were orthotopically injected into the

fourth mammary gland with either 5X104 4T1.2 or 4T1.2luc tumor cells (Figure

4.2). Within each cohort mice were randomized into five treatment groups:

control (i.p. injected with PBS), isotype control (i.p. injected with 100 µg LTF-2

antibody), CD4+ T cell depletion (i.p. injected with 100 µg GK1.5 antibody), CD8

T cell depletion (i.p. injected with 100 µg 2.43 antibody) and NK cell depletion

(i.p. injected with 20 µl anti asialo GM1 antibody). Injection of PBS and antibodies

started three days prior to tumor cell inoculation and was maintained every three

days until day 23 post tumor implantation. Primary tumor growth was measured

two-three times per week using digital caliper until the day 35 post tumor injection.

3.2.5. Flow Cytometric Analyses

Single cell suspensions of splenocytes were washed twice in PBS

containing 0.01% bovine serum albumin (flow buffer) at 4°C. Cells were

incubated with Fc block (Biolegend) and 1×106 cells were stained with saturating

concentrations of conjugated antibodies for 30 min at 4°C. Fluorescent dye

conjugated antibodies used in flow cytometric analyses were hamster α-mouse

CD3 (145-2C11), rat α-mouse CD4 (RM4-5), rat α-mouse CD8 (53-6.7), mouse

α-mouse NK1.1 (PK136); hamster IgG1 (A19-3), Rat IgG2a (RTK2758) and

mouse IgG2a (MG2a-53) were used as isotype controls. Following incubation

with the conjugated antibodies, cell samples were washed twice in flow buffer

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and fixed in 1% paraformaldehyde (BD Biosciences) in flow buffer and analyzed

on a BD LSR-Fortessa (BD Bioscience) flow cytometer by collecting 50,000

events for each sample analyzed. Flow cytometric data were analyzed using

FlowJo software (Tree Star; Ashland, OR).

3.2.6. Metastatic Burden Quantification

At sacrifice, lungs and femurs of mice were collected, flash frozen in liquid

nitrogen and stored at -80°C. Tissues were homogenized and genomic DNA was

isolated using DNeasy Blood and Tissue Kit (Qiagen; Valencia, CA) according to

manufacturer’s instructions. DNA concentration of each sample was measured

using Nanodrop ND-2000c spectrophotometer (Thermo Scientific; Wilmington,

DE). Luciferase copies for each individual tissue were quantified using TaqMan™

assay on StepOnePlus™ (Life Technologies) real-time PCR system to determine

metastatic burden. Forward and reverse primers for luciferase sequence were

CAGCTGCACAAAGCCATGAA, and CTGAGGTAATGTCCACCTCGATATG

and probe was TACGCCCTGGTGCCCGGC with 5’ FAM reporter and 3’ BHQ

quencher. Mouse telomerase reverse transcriptase (TERT) was used as

reference gene for normalizing luciferase data and was analyzed using the

TaqMan™ Copy Number Reference Assay TERT (Life Technologies). The

standard curve was performed with five 10-fold serial dilutions (200ng-20pg) of

DNA extracted from cultured 4T1.2luc cells. TERT and luciferase reactions for

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Standard curve and 200ng of each tissue sample were performed in duplicate on

StepOnePlus™ real-time PCR system.

3.3. Statistical Analyses

All data are presented as the mean plus or minus the standard error mean.

Tumor volume and metastatic burden were assessed for normality and equal

variances and either parametric or nonparametric analyses were used based on

sample distribution to detect differences between treatment groups. In vitro

proliferation of 4T1.2 and 4T1.2luc, and primary tumor growth was assessed using

2-way ANOVA, followed by Bonferroni correction for multiple comparisons where

appropriate. Metastatic burden among treatment groups was assessed using

Kruskal-Wallis test, followed by Dunn's multiple comparisons test. Survival of

tumor-bearing mice in all treatment groups were analyzed using Kaplan-Meier

curves with subsequent log rank (Mantel-Cox) test. Significance was accepted at

p<0.05.

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36

CHAPTER 4

RESULTS

4.1. In Vitro and in vivo Proliferation of 4T1.2 and 4T1.2luc tumor cells

The expression of luciferase in the 4T1.2 cell line did not alter the in vitro

proliferation rate as the proliferation rates of 4T1.2 and 4T1.2luc cells were similar

(Fig. 4.1; 2-way ANOVA, time × cell number, F (7, 28) =1.768, p=0.137).

Mean tumor volume of PBS-treated 4T1.2luc tumor-bearing mice was

significantly reduced compared to PBS treated 4T1.2 tumor-bearing mice (Fig 4.2;

n=5/group; 2-way ANOVA, time × treatment, F (12, 96) =1.876, p=0.047).

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S ta rt in g C e ll N u m b e r

Ab

so

rb

an

ce

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0

0 .0

0 .5

1 .0

1 .5

2 .04 T 1 .2

4 T 1 .2lu c

Figure 4.1. In vitro proliferation of 4T1.2 and 4T1.2luc cell lines. 4T1.2 or 4T1.2luc

mammary tumor cells (2,500 cells/well in serial dilution) were cultured for 72 hours and

quantified proliferation. The in vitro proliferation rates were similar between 4T1.2 and

4T1.2luc cell lines (2-way ANOVA, time × cell number, F (7, 28) =1.768, p=0.137).

Figure 4.2. In vivo tumor growth of 4T1.2 and 4T1.2luc mammary tumor cell lines.

Primary tumor growth of PBS-treated 4T1.2luc tumor-bearing mice was significantly

reduced compared to PBS-treated 4T1.2 tumor-bearing mice (n=5/group; 2-way ANOVA,

time × treatment, F (12, 96) =1.876, p=0.047).

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4.2. Immune Cell Depletion

Splenocytes from each treatment group were stained with anti-CD3, anti-

CD4, anti-CD8 or NK1.1 to quantify the number of CD4+ T cells, CD8+ T cells and

NK cells, respectively, in the spleens of either PBS or antibody-depleted mice

(Figure 4.3). In PBS-treated mice, 27.8% of splenocytes were CD3+/CD4+ T cells,

whereas in GK1.5-treated mice, only 0.28% of splenocytes were CD3+/CD4+ T

cells (Figure 4.3A). In PBS-treated mice, 13.3% of splenocytes were CD3+/CD8+

T cells, whereas in 2.43-treated mice 1.42% of splenocytes were CD3+/CD8+ T

cells (Figure 4.3B). Lastly, in PBS-treated mice 12.28% of splenocytes were

NK1.1+, whereas in anti-asialo GM-treated mice 1.91% of splenocytes were

NK1.1+ cells (Figure 4.3C).

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Figure 4.3. Splenic immune cell depletion in control and antibody depleted mice. At

sacrifice on day 35 post tumor implantation, spleens were harvested and single cell

suspension of splenocytes were prepared for flow cytometric analysis. CD3+/CD4+ helper

T cells (A), CD3+/CD8+ cytotoxic T cells (B) and NK1.1+ NK cells (C) populations were

quantified in PBS treated (left column) and antibody-depleted mice (right column).

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4.3. Primary Tumor Growth

Individual tumor growth curves demonstrate the variability that was

observed in 4T1.2 and 4T1.2luc tumor growth among different animals (Fig.4.4).

In 4T1.2 tumor bearing mice, administration of an isotype control antibody

(Figure 4.5A; ANOVA, time × treatment, F (9, 99) = 1.184, p=0.313); depletion of

CD4+ T cells (Figure 4.5B; 2-way ANOVA, time × treatment, F (7, 77) = 1.763,

p=0.107); depletion of CD8+ T cells (Figure 4.5C; 2-way ANOVA, time ×

treatment, F (9, 90) = 0.9577, p=0.480); and depletion of NK cells (Figure 4.5D; 2-

way ANOVA, time × treatment, F (9, 99) = 1.874, p=0.065) did not significantly alter

primary tumor growth compared to PBS treated 4T1.2 tumor-bearing mice.

In 4T1.2luc tumor bearing mice, administration of an isotype control

antibody (Figure 4.6A; 2-way ANOVA, time × treatment, F (12, 384) = 0.2934, p=

0.990) and depletion of CD4+ T cells (Figure 4.6B; 2-way ANOVA, time ×

treatment, F (12, 420) = 0.5773, p=0.861) did not significantly alter tumor growth

compared to PBS treated mice. However, depletion of CD8+ T cells (Figure 4.6C;

2-way ANOVA, time × treatment, F (12, 408) = 1.847, p=0.039) significantly

enhanced 4T1.2luc tumor growth while NK cell depletion significantly reduced

4T1.2luc tumor growth (Figure 4.6D; 2-way ANOVA, time × treatment, F (12, 408)

=1.878, p=0.035).

When 4T1.2 and 4T1.2luc tumor growth was compared within each

antibody treatment group, 4T1.2luc tumor growth was significantly lower than

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4T1.2 tumor growth in PBS-treated (Figure 4.7A; PBS; n=5/group; 2-way ANOVA,

time × treatment, F(12, 96)=1.876, p= 0.047); isotype control-treated (Figure 4.7B;

LTF-2; n=8/group; 2-way ANOVA, time × treatment, F (12, 168)=4.845, p<0.001);

CD4+ T cell depleted (Figure 4.7C; GK1.5; n=8/group; 2-way ANOVA, time ×

treatment, F(12, 168)=3.118, p<0.001) and NK cell depleted (Figure 4.7E; anti-

asialo GM1; n=7-8/group; 2-way ANOVA, time × treatment, F(12, 156)=3.560,

p<0.001) mice. However, 4T1.2luc tumor growth was similar to 4T1.2 tumor

growth in CD8+ T cell depleted mice.

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Figure 4.4. Tumor growth of individual mice in each treatment group by tumor cell types. Individual tumor growth curves of

BALB/c mice inoculated with (A-E) 5X104 4T1.2 or (F-J) 5X104 4T1.2luc cells and treated with either PBS (n=5-6/group), isotype

control antibody (LTF-2; n=8/group), anti-CD4 antibody (GK1.5; n=8/group), anti-CD8α antibody (2.43; n=8/group) or anti-asialo

GM1 antibody (n=8/group) antibodies.

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Figure 4.5. Primary tumor growth of 4T1.2 cells in control and immune cell depleted

mice. (A) Isotype control (LTF-2; 2-way ANOVA, time × treatment, F (9, 99) = 1.184,

p=0.313), (B) CD4+ T cell depletion (GK1.5; 2-way ANOVA, time × treatment, F (7, 77) =

1.763, p=0.107), (C) CD8+ T cell depletion (2.43; 2-way ANOVA, time × treatment, F (9, 90)

= 0.9577, p=0.480) and (D) NK cell depletion (anti-asialo GM1; 2-way ANOVA, time ×

treatment, F (9, 99) = 1.874, p=0.065) did not significantly change 4T1.2 tumor growth

compared to PBS-treated mice.

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Figure 4.6. Primary tumor growth of 4T1.2luc cells in control and immune cell

depleted mice. In 4T1.2luc tumor bearing mice, (A) Isotype control (LTF-2; 2-way ANOVA,

time × treatment, F (12, 420) = 0.3230, p=0.985), and (B) CD4+ T cell depletion (GK1.5; 2-

way ANOVA, time × treatment, F (12, 420) = 0.5773, p=0.861) did not alter tumor growth.

However, (C) CD8+ T cell depletion significantly increased primary tumor growth (2.43; 2-

way ANOVA, time × treatment, F (12, 408) = 1,765, p=0.039) and (D) NK cell depletion

significantly reduced tumor growth compared to the PBS-treated control group (anti-asialo

GM1; 2-way ANOVA, time × treatment, F (12, 408) = 1.878, p=0.035).

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Figure 4.7. Primary tumor growth in 4T1.2 and 4T1.2luc tumor bearing mice receiving

control or immune cell depleting antibodies. (A) control (PBS; n=5/group; 2-way

ANOVA, time × treatment, F (12, 96) =1.876, p=0.047), (B) isotype control (LTF-2; n=8/group;

2-way ANOVA, time × treatment, F (12, 168) = 4.85, p<0.001), (C) CD4+ depletion (GK1.5;

n=8/group; 2-way ANOVA, time × treatment, F (12, 168) = 3.118, p<0.001), (D) CD8+ T cell

depletion (2.43; n=6-8/group; 2-way ANOVA, time × treatment, F (12, 144) = 0.5127,

p=0.904).and (E) NK cell depletion (anti-asialo GM1; n=7-8/group; 2-way ANOVA, time ×

treatment, F (12, 156) = 3.560, p<0.001) in 4T1.2 and 4T1.2luc tumor bearing mice. Tumor

growth was significantly reduced in 4T1.2luc tumor-bearing mice compared to 4T1.2 tumor-

bearing mice in all treatment groups except in CD8* T cell depleted mice.

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4.4. Metastatic Burden

Metastatic burden in the lung (Figure. 4.8A; Kruskal-Wallis, KW=8.452,

p=0.076) and the femur (Figure. 4.8B; Kruskal-Wallis, KW=3.073, p=0.546) was

not significantly different among treatment groups.

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Figure 4.8. Metastatic burden in the lung and femur in 4T1.2luc tumor-bearing mice.

Lung (A) metastatic burden was not significantly different among treatment group

(Kruskal-Wallis, KW=8.452, p=0.076). Femur (B) metastatic burden was not significantly

different among treatment groups (Kruskal-Wallis, KW=3.073, p=0.546).

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4.5. Survival Analyses

The median survival of PBS-treated 4T1.2luc tumor-bearing mice was

significantly longer than 4T1.2 tumor-bearing mice (Figure 4.9; n=6-18, log-rank

test, p=0.045).

In 4T1.2 tumor bearing mice, the median survival of PBS and LTF-2

treated were not significantly different (Figure 4.10A; n=6-8/group, log-rank test,

p=0.431). Depletion of CD4+ T cells (Figure 4.10B; GK1.5; n=6-8/group, log-rank

test, p=0.385), CD8+ T cells (Figure 4.10C; 2.43; n=6-8/group, log-rank test,

p=0.135) or NK cells (Figure 4.10D; anti-asialo GM1, n=6-8, log-rank test,

p=0.709) did not significantly change the median survival in 4T1.2 tumor-bearing

mice compared to PBS treated mice.

In 4T1.2luc tumor-bearing mice, the median survival of isotype control

(Figure 4.11A; LTF-2; n=5-8/group, log-rank test, p=0.899) and NK cell depleted

(Figure 4.11D; anti-asialo GM1, n=5-8, log-rank test, p=0.825) mice were not

significantly different than PBS–treated mice. CD4+ T cell depletion (Figure

4.11B; GK1.5; n=8-16/group, log-rank test, p=0.004) and CD8+ T cell depletion

(Figure 4.11C; 2.43; n=8-16/group, log-rank test, p=0.025) significantly reduced

median survival in 4T1.2luc tumor bearing mice compared to PBS-treated mice.

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Figure 4.9. Median survival of 4T1.2 and 4T1.2luc tumor-bearing mice. Median survival

of PBS-treated 4T1.2luc tumor-bearing mice was significantly higher than 4T1.2 tumor-

bearing mice (PBS, n=6-18, log-rank test, p=0.045).

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Figure 4.10. Median survival in antibody depleted 4T1.2 tumor-bearing mice

compared to PBS treated mice. Median survival of (A) isotype control (LTF-2; n=6-

8/group, log-rank test, p=0.431), (B) CD4+ T cell depleted (GK1.5; n=6-8/group, log-rank

test, p=0.385), (C) CD8+ T cell depleted (2.43; n=6-8/group, log-rank test, p=0.135) and

(D) NK cell depleted (anti-asialo GM1, n=6-8, log-rank test, p=0.709) mice were not

significantly different than PBS-treated mice.

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Figure 4.11. Median survival of antibody-treated 4T1.2luc tumor-bearing mice

compared to PBS-treated control mice. Median survival of (A) isotype control (LTF-2;

n=8-16/group, log-rank test, p=0.899), (B) CD4+ T cell depleted (GK1.5; n=8-16/group,

log-rank test, p=0.004), (C) CD8+ T cell depleted (2.43; n=8-16/group, log-rank test,

p=0.025) and (D) NK cell depleted (anti-asialo GM1, n=8-16, log-rank test, p=0.825) mice.

CD4+ and CD8+ T cell depletion significantly reduced median survival compared to PBS-

treatment.

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CHAPTER 5

DISCUSSION

Breast cancer is the most commonly diagnosed cancer and the second

leading cause of cancer related deaths among American women (1). Despite

recent advances in breast cancer therapeutics, triple negative breast cancer

(TNBC) remains the subtype with poorest prognosis due to limited treatment

options. The 4T1 murine mammary metastatic model has been widely used as a

model for TNBC because of the similarities in hormone receptor profile to human

TNBC (2). One caveat of the 4T1 model is that there are few known tumor

associated antigens which has limited the use of this model in preclinical

immunotherapeutic studies (3, 4). The firefly luciferase gene, luc2, has been

transfected into various tumor cell lines as a reporter gene for imaging studies.

However, previous studies demonstrate that the luciferase epitope can induce

CD8+ cytotoxic T cell specific responses, thus may be serving as a tumor antigen

for immune recognition (5-7). Therefore, the first goal of this study was to explore

the in vitro and in vivo growth rates of the parental 4T1.2 cell line and the

luciferase transfected clone (4T1.2luc). In addition, we also investigated the role

of CD4+ T cells, CD8+ T cells, and NK cells in primary tumor growth, metastatic

progression and survival.

Consistent with our hypothesis, we found that 4T1.2 and 4T1.2luc cell lines

had similar in vitro proliferation rates suggesting that luciferase expression by

4T1.2luc cells does not interfere with pathways important in cell proliferation.

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However, in vivo tumor growth differed in 4T1.2 and 4T1.2luc tumor-bearing mice.

4T1.2luc tumor-bearing mice had significantly reduced primary tumor growth

compared to 4T1.2 tumor-bearing mice. Thus, in an immunocompetent host, the

4T1.2luc cell line may be more immunogenic than the 4T1.2 cell line, i.e. 4T1.2luc

cell line was more effectively recognized by the host immune system than the

parental 4T1.2 cell line. Baklaushev et al. reported similar in vitro growth rates

between the parental 4T1 cell line and two luciferase-expressing 4T1 cell lines.

However, significantly lower growth rates were observed in luciferase-expressing

4T1 tumor cells compared to the parental 4T1 in vivo in BALB/c mice (7).

Moreover, luciferase-specific IFN-γ production was detected in the two luciferase-

expressing clones of 4T1 in tumor-bearing mice, but not in the mice implanted

with the parental 4T1 cell line (7). In summary, our data are similar to the results

reported by Baklaushev et al., and demonstrate that expression of luciferase did

not alter the in vitro proliferative capacity of 4T1.2luc cell line, but luciferase could

be recognized by the immune system as a foreign protein in vivo. This recognition

likely influences tumor growth as 4T1.2luc tumor growth was slower than 4T1.2

tumor growth in BALB/c mice.

Both innate and adaptive immune components are actively involved in the

elimination phase of cancer immunosurveillance and the major immune cell

populations involved are CD4+ helper T cells, CD8+ cytotoxic T cells and NK cells

(99). By depleting each immune cell type in 4T1.2 tumor-bearing mice, we found

that the absence of any aforementioned immune cell types did not significantly

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alter the trajectory of primary tumor growth compared to immunocompetent

controls. However, in 4T1.2luc tumor-bearing mice, depletion of CD8+ cytotoxic T

cells significantly increased primary tumor growth in comparison to the PBS-

treated control group. Furthermore, we demonstrated that NK cell depletion

significantly reduced primary tumor growth compared to PBS-treated group.

Our results confirm that CD8+ T cells are key effector cells of anti-tumor

immunity in the 4T1.2luc model. In breast cancer patients, tumor-infiltrating CD8+

T cells are significantly inversely correlated with advanced tumor stages,

positively correlated with relapse free survival (RFS) and overall survival (OS),

while the CD4+:CD8+ ratio is negatively correlated with RFS and OS (137-139).

Baklaushev et al. demonstrated that immunization of mice using a epitope from

luciferase that is recognized by CD8+ T cells resulted in growth inhibition of

luciferase-expressing 4T1 primary tumors (7). In the current study, the absence

of CD8+ T cells augmented 4T1.2luc primary tumor growth suggesting that CD8+

cytotoxic T cells are important in mediating host anti-tumor effector immune

responses in the 4T1.2luc tumor model.

Contrary to our hypothesis, depletion of CD4+ T cells did not result in

increased primary tumor growth in both 4T1.2 and 4T1.2luc tumor-bearing mice.

CD4+ T cells are a heterogeneous group of immune cells including T helper 1

(TH1), T helper 2 (TH2), T helper 9 (TH9), T helper 17 (TH17), T helper 22 (TH22),

follicular helper T cell (TFH), and regulatory T cells (Tregs). Among these CD4+ T

cell subsets, TH 1 provide help to activate CD8+ cytotoxic T cells, while Tregs are

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potent inhibitors of antigen-specific immunity (140). Huang et al. demonstrated

that in the 4T1 and EO771 mammary tumor models, both tumor-infiltrating CD4+

and CD8+ T cells accumulated with the progression of tumor, but CD4+ TILs

became increasingly high in the CD4+CD25+Foxp3+ Treg subset late in tumor

progression, and the CD4+:CD8+ ratio also increased with tumor progression

(139). It is possible that TH1 plays an important role in the 4T1.2luc model, but

depleting all subsets may have masked the effect of the loss of TH1 cells.

Therefore, depletion of TH1 cells and Tregs separately in subsequent

experiments may reveal more about the role CD4+ cell subsets in the 4T1.2 and

4T1.2luc tumor models.

In the current study, depletion of NK cells did not affect 4T1.2 primary

tumor growth which supported our hypothesis. However, depletion of NK cells

resulted in decreased tumor growth in 4T1.2luc tumor bearing mice, suggesting a

pro-tumorigenic role for NK cells in this model. These findings contradict the

evidence in some tumor models that NK cells exert an anti-tumor effect. Based

previous data collected in the Rogers laboratory, the expression of major

histocompatibility complex I (MHCI) by 4T1.2 and 4T1.2luc cell lines is negligible.

All healthy nucleated cells express MHCI on their surface which can bind to

inhibitory receptors of NK cells, thus preventing NK cells from attacking healthy

tissue. In contrast, transformed, tumor cells often lack MHCI which can activate

NK cell recognition of tumors (88). Therefore, since 4T1.2 and 4T1.2luc lack MHCI

expression, we do not believe these tumors are recognized by NK cells. One

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possible explanation for our findings is that NK cells can inhibit CD8+ T cell activity

(141) and depletion of NK cells may allow a greater CD8+ T cell cytotoxicity

against 4T1.2luc tumors. It is reported that NK cells can regulate T cell immunity

via secretion of cytokines or direct lysing of T cells (142, 143). NK cells have been

reported to increase IL-10 secretion after various infections (144, 145). NK cells

can also interact with T cells by engaging NKG2D to NKG2D ligands on T cells

and can kill activated T cells via cytolytic granules or death ligand pathways such

as TRAIL or FasL (141, 142). Therefore, examining the interaction between NK

cells and CD8+ T cells in the 4T1.2a model is necessary to explain the

protumorigenic role of NK cells we observed in this study.

In 4T1.2luc tumor bearing mice, no statistically significant increase in lung

and femur metastatic burden was observed in CD4+ T cell, CD8+ T cell and NK

cell depleted groups. The current study was designed to examine the role of key

immune components in 4T1.2 and 4T1.2luc models. Thus, we collected lungs and

femurs at the end of study (day 35) based on our previous metastatic burden data.

However, there were a large number of mice that were taken off prior to day 35

because their tumors reached the ethical limit or they were moribund. This may

have introduced a bias in that animals with the lowest metastatic burden may

have survived until day 35 post tumor implantation. Future studies are aimed at

examining the metastatic burden of immune-depleted mice at an earlier time point

to avoid a survival bias in the data. Also, we did not examine the metastatic

burden of 4T1.2 tumor bearing mice, therefore we cannot compare to what extent

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does immune system influence metastases between 4T1.2 and 4T1.2luc tumor-

bearing mice.

PBS-treated 4T1.2luc tumor-bearing mice had a significantly longer median

survival than PBS-treated 4T1.2 tumor-bearing mice. One reason that PBS-

treated 4T1.2luc tumor-bearing mice exhibit a significantly greater median survival

compared to 4T1.2 group may be greater recognition of the tumor by the immune

system due to the expression of luciferase. This immune control of the tumor may

prevent accelerated tumor growth and/or the initiation of cachexia which

contribute to survival. Consistent with our hypothesis, depletion of CD4+ T cells,

CD8+ T cells and NK cells did not alter the median survival in 4T1.2 tumor-bearing

mice compared to PBS-treated group. These results can also be explained by

the lack of tumor antigens of 4T1.2 tumors, thus the importance of CD4+ T cells,

and CD8+ T cells is less prominent in this tumor model.

In 4T1.2luc tumor-bearing mice, CD4+ T cell and CD8+ T cell depletion

groups had significantly reduced median survival compared to the PBS-treated

group. NK cell depleted mice had identical survival rate with PBS-treated 4T1.2luc

tumor-bearing mice. It is reported CD8+ T cells and NK cells are crucial in 4T1

tumor-bearing mice survival, while CD4+ T cells are negatively associated with

patient overall survival and the inhibitory CD4+/FOXP3+ Treg subset is reported

to be dominant in the late tumor stage (139, 146, 147). However, our data

demonstrated that CD4+ T cells and CD8+ T cells are important immune cell

populations to maintain survival in the 4T1.2luc tumor model. Eventhough our

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58

results contradict published data that CD4+ T cells are negatively associated with

survival, it is possible that total number and percentage of Treg cells are low in

the CD4+ T cell population in the 4T1.2luc model, so that most of the CD4+ T cells

may be performing a protective role. Future experiments need to be conducted

to confirm the proportion of pro- or anti-tumor CD4+ T cell subsets at sacrifice and

the effect of depleting these CD4+ T cell subsets on tumor growth and survival in

4T1.2luc tumor-bearing mice.

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CHAPTER 6

CONCLUSION

In summary, 4T1.2 and 4T1.2luc tumor cell lines are widely used as TNBC

models due to the similarity of cell surface expression of hormone receptors to

human TNBC. Here we found both cell lines have comparable in vitro proliferation

rates. More importantly 4T1.2luc had significantly reduced in vivo proliferation rate

compared to 4T1.2 tumor cells and we demonstrated that this is due to

recognition of luciferase on 4T1.2luc cells by CD8+ T cells. As a TNBC model,

4T1.2 cell line lacks defined tumor associated antigens, but 4T1.2luc cell line is

more immunogenic which potentially expands its use to immunotherapeutic

studies. Our data also suggest a pro-tumorigenic role of NK cells in this model.

Future studies need to be conducted to clarify the interaction between NK cells,

CD8+ T cells and tumor cells. We did not observe a significant increase in

metastatic burden in the lung or femur in immune cell depleted 4T1.2luc tumor-

bearing mice. Additional studies with a larger sample size are needed to clarify

the roles that CD4+, CD8+ T cells and NK cells in controlling metastases in

4T1.2luc tumor bearing mice. Lastly, we demonstrated that CD4+ T cells and CD8+

T cells are crucial for the survival of 4T1.2luc tumor-bearing mice but not for 4T1.2

tumor-bearing which suggests an important role for antigen-specific immunity in

tumor growth and survival.

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Results from the current study have solidified our understanding of the role

of CD4+ and CD8+ T cells and NK cells in tumor growth, metastases, and survival

in the 4T1.2luc model. This information will enable our laboratory to investigate

the immune mechanisms underlying the diet and exercise effects on tumor

progression and survival previously reported. Specifically, future studies are

aimed at determining if our diet and exercise interventions are enhancing the anti-

luciferase response to 4T1.2luc tumors, or may be preventing the emergence of

immune suppressive cells, such as regulatory T cells.

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