3

Acknowledgments

I would like to thank the Honor’s council for the privilege of writing and defending this work.

Never in my wildest dreams did ever image that when I made the decision to return to school four years ago that I would end up at such a prestigious University as Bucknell and in the company of so many great people. None of my achievements over these past four years could have ever happened without help; in fact, rarely do we ever accomplish anything purely on our own. There are countless people, both known and unknown, who have influenced me in one way or another and has led me to be the person that I am today. I can never know who they all are; I thank them all, and I am grateful that they have been put into my life. That said, the following list is by no means complete.

First: I would like to thank my family and friends for their unwavering love and support. My parents who believed in me when I could not and for their unconditional love.

Second: My advisor and mentor, Dr. Ken Field, whose guidance and relentless pursuit for truth and knowledge has been an inspiration to me. Additionally, I am extremely grateful for Ken’s guidance on matters both personal and professional.

Third, I would like to thank Dr. Pizzorno, Dr. Gates, and Dr. Chernin for their constant support and expert advice during this study and for all their experience and knowledge, which surely I have absorbed on levels I have not yet begun to understand.

Finally, I would like to thank Mark Davies and all the faculty and people here at Bucknell for the opportunity to explore my life and to grow in new directions I never imagined.

4

Table of Contents

I. INTRODUCTION

II. MATERIAL AND METHODS

III. RESULTS

IV. DISCUSSION

V. LIST OF TABLES A. GRAFT SCORE DATA B. RNA INTEGRITY DATA

VI. LIST OF FIGURES

1. DENDRITIC CELL MIGRATION 2. T CELL DIFFERENTIATION 3. GENE AMPLIFICATION USING QRT-PCR 4. ALLOGRAFT REJECTION IMAGES OF MICE 5. AXILLARY AND BRACHIAL LYMPH NODES 6. CYTOKINE GENE EXPRESSION DURING ALLOGRAFT

REJECTION IN THE GRAFT DRAINING LYMPH NODES

VII. REFERENCES

5

Abstract

Farnesyltransferase inhibitors (FTI) are a therapeutic class of anti-cancer drugs

that have been shown to block the expansion and differentiation of T-helper cells

in vitro, and delay graft rejection of mismatched tail skin grafts in C57BL/6 mice.

The effects that FTIs have on cytokines and the Th1/Th2 balance during immune

responses is not completely understood. In order to advance our understanding

of the effects that FTIs have on Th1/Th2 differentiation during allograft rejection

in mice, we used a disparate MHC II mismatch between C57BL/6 and bm12 mice

and then measured mRNA cytokine gene expression in the lymph nodes that

were draining the allograft. The FTI ABT-100 was able to significantly decrease

the expression of IFN-γ without affecting levels of TGF-β or IL-4 mRNA

transcripts during allograft rejection. These results clearly demonstrate that ABT-

100 has the ability to selectively immunomodulate the differentiation of

alloreactive T cells by blocking the expansion of Th1 cells but not Th2 or Treg

cells in mice. This means that FTIs may be a good candidate for

immunosuppressive therapy concerning solid organ transplantations and other

Th1 mediated immune responses.

6

I. Introduction

A. Graft Rejection

Graft rejection is a normal immunological response caused by cells of the

immune system that recognize the transplant as non-self. Organ transplantation

has become the standard procedure for end-stage organ failure, and each year

only about a quarter of people needing transplants will receive an organ

transplant [1]. In addition to the lack of donors, graft rejection due to imperfect

matching of human leukocyte antigen (HLA), remains a formidable barrier to

long-term graft survival [2]. The HLA system is the common name for the major

histocompatibility gene complex (MHC), and due to polymorphism in this gene

complex, it is extremely rare to find a perfect match between donor and recipient.

In order to help accommodate inevitable MHC mismatches, the recipient will

more than likely undergo immunosuppressive therapy for the duration of the

graft [3]. Major advancements in immunosuppressive therapy have significantly

improved the success of organ transplants, but there is still a need to better

understand the complex mechanisms behind graft rejection.

B. The Major Histocompatibility Complex

MHC are a set of genes that code for a series of cell surface markers that

when mismatched between the recipient and the host cause the activation of the

host immune system and consequent rejection of the graft [4]. MHC proteins are

expressed on the surface of cells in the body, and it is the high variability of these

7

proteins between individuals that serves to aid the immune system in

identification of foreign or “non-self” antigen. The specificity for self vs. non-self

is such that differences as small as three amino acid residues on a single gene in

the MHC complex can cause the graft to be rejected as evidenced by studies of

disparate skin grafts in mouse models [5].

MHC molecules are broken down into two groups known as class I and

class II that have distinct functions [6]. The MHC I molecules are expressed by all

nucleated cells in the body, and it is this cell surface marker that confers the

quality of what is known as “self” recognition in the body. The MHC I proteins

are complexed with peptide fragments in the endoplasmic reticulum and

presented on the surface of the cell. The peptide fragments are derived from the

cytosol or nucleus and can be either self peptides broken down and degraded

from normal cellular maintenance, or processed protein fragments from the

digestion of intracellular pathogens. Foreign antigenic peptides, such as viral

peptides, bound to MHC I attract and activate CD 8+ T cells (cytotoxic killer T-

cells) that destroy infected cells expressing antigenic “non-self” peptides [7].

Unlike MHC I molecules that are ubiquitously expressed, MHC II

molecules are expressed by antigen presenting cells (APCs) like dendritic cells,

macrophages and B-cells [6]. APCs digest and present peptides from antigens

that they engulf such as bacteria, fungi and other foreign invaders. These

peptides can then be presented to naïve CD4+ T lymphocytes [7]. When a naïve

CD4+ T-lymphocyte recognizes specific antigen, it can become activated and

8

differentiate and expand into T helper (Th) cell sub-sets. These Th effector cells

then migrate to the source of infection and mount an adaptive response by

mediating the destruction of the foreign invader [8]. It is the recognition of non-

self MHC molecules and peptide fragments, followed by the consequential clonal

expansion of specific Th effector cells that is the cause graft rejection.

C. Rejection Pathway

Graft rejection is therefore a CD4+/CD8+ effector T cell-dependent response to an

MHC peptide incompatibility. The donor graft is known as an allograft, and the

host T cells that respond are called alloreactive. In this study, I used a mouse

model in which allograft rejection occurs via the direct pathway due to a MHC

class II mismatch recognized by CD4+ T cells. The two strains of mice used in my

study differ by only 3 amino acid residues located on a single gene of the MHC

class II gene complex [11]. After transplantation of a skin graft from one strain of

mouse to the other, dendritic cells (DCs) present in the graft tissue migrate from

the graft to the nearest lymph node (known as the graft draining lymph node or

GDLN) of the recipient (Figure 1). When the naïve CD4+ T cells in the lymph

node express a T-cell receptor that recognizes the MHC on the donor DCs as

“non-self,” they become activated and then differentiate into a specific subset of

effector Th cells [8,9]. These alloreactive cells that respond to the donor antigen

mediate the destruction of the transplant tissue.

9

It has been shown that MHC class II deficient mice will reject graft

transplants only after receiving adoptive transfer of CD4+ T-cells [10]. This

specificity demonstrates that the response is initiated by CD4+ cells recognizing

the MHC class II mismatch and not CD8+ cells which would respond to MHC I

mismatch. Therefore, the disparate MHC class II model used in this study

10

ensures only CD4+ T cell expansion, even though rejection can still occur via two

other pathways involving both MHC class I and II molecules, as well as antigen

peptide fragments.

D. Effector T cell Differentiation

A naïve CD4+ T cell needs to receive 2 signals to become fully activated

[12]. One of these signals occurs through the T cell receptor and the other is

through the CD 28 receptor. The result is the activation and the induction of

important cytokines and growth factors such as: Interferon Gamma (IFN-γ),

Transforming Growth Factor Beta (TGF-β), Interleukin 2 (IL-2), and IL-4.

Cytokines are usually produced transiently and locally and are active at very low

concentrations, specifically in the picogram range. Activated lymphocytes and

antigen presenting cells such as DCs, secrete cytokines that act in a paracrine or

autocrine fashion causing the monoclonal expansion of effector T cells [13]. The

dominant effector T cell subtype is determined by the secretion and

concentration of the specific cytokines [14].

Effector T cell differentiation is a pivotal process and plays a critical role in

host defense, and in the case of graft rejection, is contingent upon the type of

cytokine in the microenvironment of the lymph node (Figure 2). For example, if

IL-4 or IFN-γ cytokines are blocked, the duration of purposely mismatched skin

grafts can be significantly extended in mice [5]. Th cells can be characterized by

the “signature” cytokines that they produce (Figure 2) [8]. For example, IFN-γ is

11

the quintessential Th1 cytokine produced by Th1 effector cells, Th2 cells produce

IL-4, Th17 cells produce IL-17, and regulatory T cells (Tregs) produce TGF-β. The

differentiation of Th1/Th2 cells is determined by the type of pathogenic invader

and the concentrations of specific cytokines in the microenvironment [15]. Th1

help promote the destruction of intracellular pathogens such as viral infections,

while Th2 produce IL-4 and are central to the stimulation of humoral immunity

for the protection against parasitic infections such as helminthes [16,17]. Both

responses driven by Th1 and Th2 cells are involved in and independently capable

of causing allograft rejection [21]. The key to Th1/Th2 polarization is the

presence of the specific signature cytokine during the autocrine expansion phase

of the immune response. If for example IFN-γ is the dominant cytokine secreted

in the microenvironment of the graft draining lymph node, then the resulting

expansion is the Th1 subset; conversely, if IL-4 concentration is greater, Th2

expansion dominates. Importantly, Th1/Th2 cytokines also act to inhibit each

other’s expansion to further ensure a specific pathogen based response [16].

The Th17/Treg balance can enhance or suppress the immune system

response. Th17 differentiation is caused by the cytokine TGF-β and IL-6 [18].

Th17 cells then go on to secrete their signature pro-inflammatory cytokine IL-17.

Because IL-17 plays a proinflammatory role, it has been implicated in many

inflammatory and autoimmune diseases in mice and humans [19]. Tregs secrete

TGF-β, and as with previous effector cells, this signature cytokine enhances the

differentiation of the Treg lineage in an autocrine forward feeding loop. As

12

opposed to Th17 cells, Tregs have an anti-inflammatory role and act to regulate

the immune response and promote tolerance [20].

13

E. Farnesyltransferase Inhibitors

Since the signature cytokine from each subset ensures the expansion of

like subsets, the dominant response is mediated by which cell type is activated

and can expand first. In past studies, farnesyltransferase inhibitors (FTIs) have

been shown to affect the Th1/Th2 differentiation by blocking the secretion of the

signature cytokines INF-γ and IL-4 in vitro [22] and in mouse models [23]. FTIs

have also demonstrated the ability to significantly delay graft rejection of

disparate MHC class II skin grafts in C57BL/6 mice by blocking cytokine

secretion from alloreactive T cells [5]. Furthermore, FTIs have been shown to

block the secretion of IL-2 (the primary T cell mitogen) and the proliferation of T

cells without interfering with T cell activation or causing cell death [24]. These

results indicate that FTIs show selective immunomodulatory effects.

FTIs are a class of therapeutic drugs that were originally intended to block

the effects of oncogenic Ras mutations in tumor cells [25]. Mutations in

oncogenic Ras proteins result in constitutive activation of downstream signaling

that lead to inhibition of apoptosis and uncontrolled growth and proliferation of

tumor cells [26]. Protein farnesylation is a type of prenylation that is required for

the proper subcellular localization of Ras to the cytosolic face of the plasma

membrane [27]. This ensures Ras interaction with cell surface receptors leading

to a signaling cascade and downstream nuclear events. There are three known

enzymes that catalyze a posttranslational prenyl modification to newly

manufactured proteins: Farnesyltransferase (FTase), and

14

Geranylgeranyltransferase GGTase I and II [28]. Oncogenic Ras is believed to

play a key role in malignant transformation, thus FTIs were designed to block

prenylation and render Ras biologically ineffective. Since it was discovered that

the ligation of the T cell receptor leads to T cell activation through signaling

events downstream of Ras [29], then it was thought that FTIs would be a good

candidate for immunosuppressive therapy.

There have been several studies done to investigate the effect of FTIs on T

lymphocyte activation and expansion. Marks et al. demonstrated that FTIs were

able to block secretion of IL-2, IL-4, IL-5, and INF-γ in artificially stimulated Th1

and Th2 clones in cell culture [22]. Additionally, they showed that FTIs can

inhibit cytokine production without suppressing cytokine messenger RNA

(mRNA). Gaylo et al. found that the FTI ABT-100 could significantly block the

secretion of INF-γ and IL-4 by alloreactive T cells (responder cells) when

stimulated with allogeneic disparate MHC II cells (stimulator cells) in cell culture

[5]. In order to advance our understanding of the immunomodulatory effect that

FTI ABT-100 has on allograft rejection and Th1/Th2 differentiation, we used an

allograft mouse model with an identical MHC II mismatch as the previous studies

and then measured cytokine mRNA levels to determine gene expression in the

graft draining lymph nodes.

15

F. qRT-PCR amplification

Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR),

also known as “real-time PCR” can be used to measure cytokine gene expression

in tissue samples [30-32]. PCR in general uses repeated cycles of heating and

cooling to amplify copies of a specific region of DNA. Because of reagent

limitations, self-annealing of the strands, byproducts of the reaction such as

pyrophosphates, and inhibitor mechanisms found within the DNA template, the

PCR reaction eventually ceases to amplify the target sequence at an exponential

rate [33]. A plateau effect occurs making the endpoint quantification of the PCR

product unreliable. “Real time” PCR enables the PCR products to be measured

simultaneously as they are accumulating during the exponential phase (Figure 3).

A fluorescence signaling molecule, such as SYBR Green I, intercalates and into

double-stranded DNA and fluoresces as the number of double-stranded DNA

copies increases. The fluorescence given off is then detected by a CCD camera and

the change in fluorescence is plotted over time. To verify that only one gene

product is being amplified, a melt curve analysis reveals the temperature at which

the newly synthesized double-stranded product melts or dissociates. Non-specific

products will appear with different melting point temperatures.

16

There are primarily two methods used for qRT-PCR analysis to quantify

gene expression: relative quantitation and standard curve quantitation [34]. In

this study, we relied on relative quantitation and use what is known as the ΔΔCt

17

method which compares fold change between Ct values (see Figure 3). First, the

Ct value obtained for the reference gene (or housekeeping gene) is subtracted

from the Ct values of all of the genes of interest within a single experiment. This

normalizes the experimental genes back to a gene that is known have a relatively

constant expression level regardless of the conditions. Then, the experimental

genes can be compared to one another within the individual experiment.

To avoid confusion when interpreting PCR fold change data, it is

convenient to think of gene expression in terms of up regulation or down

regulation with respect to that same gene expression in the control. If the

normalized Ct value of the experimental gene, for example IFN-γ, is greater than

the Ct value of the control IFN-γ, then gene expression was down regulated.

Because the Ct value is a measure of the fluorescence at the threshold generated

during the PCR amplification cycle, then the lower cycle number indicates that

there were more initial mRNA transcripts. Comparatively speaking, if there were

less transcripts, then the treatment caused a down regulation of gene expression.

Accordingly, if the normalized Ct value of the experimental gene is less than the

Ct value of the control, then gene expression was up regulated.

G. Experimental Design

This study compares the gene expression of T-lymphocytes in the GDLN

during allograft rejection in the presence or absence of the FTI ABT-100. Full

thickness tail skin was grafted on to the dorsal trunk of female C57BL/6 mice.

18

One group received the FTI ABT-100 ad libitum in their drinking water, while the

other group drank water without the drug. After half of the mice in any group

fully rejected the graft, the axillary and brachial GDLNs were immediately

harvested and stored in RNA later. Total RNA was extracted and then reverse

transcribed to cDNA, and qRT-PCR was performed to compare relative gene

expression of the T lymphocyte signature cytokines IFN-γ, IL-4, IL-17, and TGF-

β.

19

II. Materials and Methods

A. Mice and Reagents

Seven to twelve week old female B6-H2-Ab1bm12 mice (bm 12 or donor

mice), and C57BL/6 female mice (BL/6 or recipient mice) were purchased from

the Jackson Laboratories in Bar Harbor, Maine. They were maintained in a

specific pathogen-free environment and treated according to an animal protocol

approved by the Animal and Care and Use Committee at Bucknell University.

Mice in the drug treatment groups were given ABT-100 48 hours prior to

surgeries. The orally bio-available FTI ABT-100 was generously donated by

Abbott Laboratories, Abbott Park, Illinois, USA, and provided to the mice ad

libitum in the drinking water. ABT-100 was partially dissolved in 100% ethanol

at a concentration of 50 mg/ml, then it was diluted to 0.625 mg/ml in 0.5%

hydroxypropylmethylcellulose (HPMC). The solution was adjusted to a pH of 3.5

and brought to final concentration of 1% ethanol, 0.4% HPMC, and 0.5 mg/ml

ABT-100. The drug solution was freshly prepared and stored at room

temperature for no more than two weeks. Drinking water bottles were gently

shaken by hand twice a day to help ensure that the drug stayed in suspension.

Daily analysis of consumption determined that mice received approximately 82.7

mg/kg/mouse (data not shown).

20

B. Skin Grafts

Mice were anesthetized intraperitoneally with a mixture of 9:1 ketamine

HCl 100 mg/mL to xylazine 20 mg/mL, and all surgeries were performed in a

sterile environment under a laminar flow hood. For the syngeneic control group,

full thickness tail skin (~ 1 cm x 1 cm) from one female BL/6 mouse was grafted

on to the dorsal trunks of other female BL/6 mice, and this constituted a fully

matched skin graft. For the allogeneic groups, tail skin from female bm12 mice

was grafted onto female BL/6 in the same manner and this constituted a MHC

class II mismatch differing at only one allele. The allogeneic group was split in

two, and one group received (+) ABT-100 (n= 7) in their drinking water, while

the other did not (-) Abt (n=8). The syngeneic group was also split in two;

however, only the group that did not receive (-) ABT-100 (n=6) was used for the

syngeneic control.

Bandages were removed after 7 days and the grafts were scored according

to the following criteria (Figure 4): a perfect 100 – pink color or normal color as

appeared in tail skin with no sign of peeling or fraying or shrinkage in the graft

bed; 75 – color may still be normal; however, small discolored spots can be seen;

the graft still fits in the graft bed, but redness may start to show around graft

edge; 50 – larger discolored spots in graft and shrinkage away from the graft bed.

The graft now appears to be peeling or frayed, and may begin to shrink away from

the graft bed; 25 – Graft is completely discolored and is clearly beginning to

separate from the graft bed; 0 – full rejection – graft is either missing or mostly

21

detached from the graft bed. Once 50 % of all the mice in any group reached full

rejection, the experiment was terminated, and the mice were sacrificed. Axillary

and brachial lymph nodes were removed and stored in RNAlater at 4 ºC for 24

hours before being stored at -20 ºC until RNA extraction.

22

C. Total RNA extraction

A nuclease-free work area was created and carefully maintained, and all

reagents used were certified nuclease free. All glassware, surfaces and

instruments such as pipettes, scalpels, sonicator tip, mortar and pestles were

cleaned with RNAzap from Sigma, and rinsed with Diethylpyrocarbonate (DEPC)

treated water that was autoclaved twice to deactivate the DEPC. Untreated

nuclease-free water was used as a reagent for any downstream application.

Total RNA was extracted using RNeasy mini kits (Qiagen). The lymph

nodes were removed from storage and meticulously cleaned of any excess tissue

or crystals that had formed (Figure 5). Lymph nodes were then homogenized in

2Molar dithiothreitol (DTT) using Kontes pellet pestle grinders in 1.5 mL tubes

(purchased from Kontes). Sonication and tissue disruption (Ultrasonics Inc.) was

performed on ice using a 1/8 inch micro tip probe with an output set at 3.5 and 8-

10 one second bursts at 40% duty cycle. To prevent cross contamination, the tip

was cleaned with RNAzap and rinsed with DEPC treated water between

applications. Total RNA integrity was determined on a Agilent Bioanalyzer

(Genomics Core Facility, Penn State University). No sample with an RNA

Integrity Number (RIN) below 7.9 (average RIN for all samples 9.46 +/- 0.49)

was used in the study. 1000 ng total RNA was then reverse transcribed to cDNA

with RT2 HT First Strand Kit (Qiagen) following the manufacturer’s protocol,

which included elimination of genomic DNA.

23

D. qRT-PCR and DNA Primers

iQ CYBER green Supermix (Bio-Rad) was used, and two step qRT-PCR

were performed on an iCycler from Bio-Rad in a total volume of 25 µL as follows:

1) denaturation: 3 min at 95°C; 2) amplification: 40 cycles at 60 ºC; 3) melt curve

analysis in 0.5 º increments starting at 55 ºC. PCR primers used consisted of the

following: ACTN-β Forward 5ʹ – TGCCGCATCCTCTTCCTCCCT-3ʹ and Reverse 5ʹ

– GATGCCACAGGATTCCATACCCAG – 3ʹ: INF-γ Forward 5ʹ –

CATCAGCAACAACATAAGCGTCA – 3ʹ and Reverse 5ʹ –

CGCTGGACCTGTGGGTT – 3ʹ: IL-4 Forward 5ʹ – ACAGGAGAAGGGACGCCAT –

3ʹ and Reverse 5ʹ – TGCAGCTTATCGATGAATCCAG – 3ʹ: IL-10 Forward 5ʹ –

CATTCATGGCCTTGTAGACACCCTTAATGCAGGACTTTAAGGGTTA-3ʹ and

24

Reverse 5ʹ - CTTAATGCAGGACTTTAAGGGTTA – 3ʹ: TGF-β Forward 5ʹ –

GGACACACAGTACAGCAAGGTC – 3ʹ Reverse 5ʹ – TCAGCTGCACTTGCAGGAG –

3ʹ. 1000 ng of total RNA was reverse transcribed to cDNA using RT2 HT first

strand kit (Qiagen). qRT-PCR reactions were carried out in triplicate in 96 well

plates each well containing 12.5 µl master mix, 10.5 µl nuclease free water, 1 µl

cDNA, and 1 µl of primer pairs 10 µM (forward and reverse) for a total reaction

volume of 25 µl. Actn-β was used as the reference gene, and water and SYBR

green master mix containing DNA Taq polymerase was used as the negative

control. Melt curve analysis was used to determine non-specific amplification of

gene products.

E. Data Analysis

To examine the differences in gene expression, the fold increase/decrease

in gene expression was quantified using the ∆∆ Ct method which appropriately

quantifies and compares exponential gene amplification of PCR. First, the Ct

numbers of the genes of interest, such as IFN-y or IL-4, were averaged and then

subtracted from the average Ct of the reference gene Actin-β in each experiment.

This was defined as the ΔCt. To calculate the data points in Figure 6, the ΔCt

average for the syngeneic group was subtracted from each individual mouse in

the allogeneic groups, and the points were plotted as a whisker box plot

conveniently showing individual response in the context of the group. Negative

results indicate down regulation and will have a fold change value of less than 1.0.

25

This constitutes a fractional amount of transcript abundance compared to

control; for example: 20 = a 1 fold change meaning no change at all, 2-1 = 0.5 fold

change meaning half as many transcripts were amplified at the cycle threshold,

and finally, 21 = a 2 fold change or twice as many transcripts were amplified. The

significance of relative gene expression levels was evaluated using a Mann-

Whitney U non-parametric test (p < 0.05).

26

III. Results

A. Allograft Rejection

Previous studies have shown that FTIs can delay alloreactive immune

responses and block cytokine secretion [5, 22, 24, 35]; therefore, we wished to

determine if FTIs can alter the balance of effector T cells produced during an

alloreactive immune response. To accomplish this goal, three groups of female

C57BL/6 (BL6) mice received either perfectly matched skin grafts (syngeneic) or

the disparate MHC class II mismatches (allogeneic). GDLNs were harvested and

the gene expression between groups was measured using qRT-PCR. The average

ΔCt from all the mice in the syngeneic group was calculated for each gene of

interest. Accordingly, either the group averages from the allogeneic, or individual

gene Ct values from each mouse was compared to the syngeneic control.

In order to determine whether FTIs affect the balance of effector T cells

produced during allograft rejection, I looked at the gene expression of the

signature cytokines IL-4, IFN-γ, IL-17, and TGF-β in the axillary and brachial

lymph nodes that were draining the allograft. These disparate skin grafts were

vigorously rejected in untreated mice with a mean graft survival time of 13.67 +/-

0.5 days (Table 1, panel C). The MHC class II mismatch and quick rejection

response is indicative of acute rejection via the direct pathway. Given that Th1

and Th2 effector sub-types can both independently cause graft rejection, I wanted

to see which effector cell subset was dominating the immune response, and if

27

treatment with the FTI ABT-100 could block this expansion and promote

tolerance of the allograft.

B. Interleukin-4 Gene Expression

First, I tested if the gene expression of the Th2 cytokine, IL-4, was affected

by treatment with ABT-100 during allograft rejection by looking at the average

fold change of the groups (Figure 6, Panel A). The group average ∆Ct for the (-)

ABT-100 was 12.59 and 12.42 for (+) ABT-100 group. Since the ∆Ct of IL-4 in the

control group was 13.16 and higher than Ct values for the treatment groups, then

that means that IL-4 gene expression in both treatment groups was slightly up

regulated. There was a 1.48 fold increase in the abundance of IL-4 transcripts in

28

the untreated allogeneic group compared to the control group. In the allogeneic

group receiving ABT-100, there was an average 1.67 fold increase the abundance

of IL-4 transcripts compared to the control. Mann Whitney U non-parametric

test showed that the drug had no significant effect on IL-4 gene expression

during allograft rejection when compared to untreated syngeneic grafts. This

result means that the level of Th 2 was relatively unchanged in both the presence

and absence of ABT-100.

29

Figure 6: Cytokine Gene Expression During

Allograft Rejection. Female bm12 mouse tail

skin was grafted onto the dorsal trunks of

BL/6 recipient mice (n=3-10 mice per

treatment group). Mice were maintained in a

pathogen free environment for the duration of

the experiments. Mice were sacrificed by CO2

inhalation, and the GDLNs were immediately

collected and immersed in RNA later for 24

hours at 4º C before being transferred to -20º

C for no longer than 30 days until RNA was

extracted. Qiagen RNeasy mini kits and RT2

HT First Strand Kit were used for total RNA

extraction and creation of cDNA templates

respectively. PCR Supermix from Biorad was

used with an iQ 5 thermocycler for Qrt-PCR

reactions. The delta Ct’s of the syngeneic mice

(control group) were combined and averaged

after gene expression was determined relative

to individual Actn-B reference gene.

Individual gene expression +/- ABT-100 was

compared to group average gene expression of

the mice receiving syngeneic grafts so that

each plot represents a single mouse result. A

value of 1 on the Y axis represents no change

in gene expression compared to the syngeneic

mouse group. Statistical significance was

determined using a Mann-Whitney U non-

parametric test.

30

C. Interferon-γ Gene Expression

Next, I used the group average ΔCt to determine if ABT-100 would have

similar effects on the Th1 cytokine, IFN-γ (Figure 6, panel B). The group average

∆Ct for the (-) ABT-100 was 12.89 and 13.97 for (+) ABT-100 group. The

syngeneic control group average ∆Ct was 12.64, and INF-γ gene expression was

down regulated in both groups compared to the control. There was an average

0.25 fold change in transcript abundance in the untreated allogeneic group when

compared to the control. In the allogeneic (+) ABT-100 group, INF-γ gene

expression was significantly down regulated and there was an average 1.33 fold

change, or approximately 2 and a half times as many IFN-γ mRNA transcripts

being produced in the syngeneic control groups compared to the allogeneic drug

treatment group. This indicates that there were significantly less Th1 cells in the

allogeneic group that received the FTI (*p < 0.05).

Since ABT-100 was able to significantly decrease the clonal expansion of

the Th1 subtype, and if Th2 differentiation was about the same in both allogeneic

groups, I decided to next look at what other effector subsets may be dominating

the acute response in the GDLNs. ABT-100 was previously shown to extend the

life of disparate skin grafts in an identical model as the one I used [5], and Table 1

shows the graft rejection scores for the mice in each group at the end of the

experiments. Group C shows that after approximately 14 days, all the grafts in the

allogeneic group not receiving ABT-100 except one are either fully rejected or in

the process of rejection. Looking at the middle column, we can see that after

31

approximately 14 days, all but one of the allografts of the (+) ABT-100 drug

treatment group show no signs of rejection. This is analogous to the syngeneic

group, and possibly indicates some level of tolerance was achieved towards the

graft.

D. Transforming Growth Factor Beta

In order to determine if some level of tolerance was achieved during the

rejection phase, I next looked at the ΔCt fold change of the T regulatory cell

(Treg) cytokine, TGF-β, and the Th-17 signature cytokine, IL-17. Melt curve

analysis of qRT-PCR results (data not shown) indicated that the primers for the

IL-17 gene were producing 2 separate PCR products; therefore, I was only able to

analyze the results for TGF-β. I found that in the GDLN, the average ∆Ct in TGF-β

(Figure 6, Panel C) for the both allogeneic groups was 8.11 (-) ABT-100 and 8.05

(+) ABT-100 and 8.29 for the syngeneic group. There was no significant change

in TGF-β gene expression between treatment groups and the control; accordingly,

the FTI had no effect on the number of regulatory T cells during graft rejection.

32

IV. Discussion

A. Farnesyltransferase Inhibitors

FTIs are a therapeutic class of drugs originally developed to treat patients

with cancer. The drugs were designed to prevent the farnesyltransferase enzyme

from post-translationally modifying (prenylating) the cell-signaling protein Ras,

thus inhibiting proper sub-cellular localization and biological function within the

cell. FTIs promote apoptosis in the tumor cells of cancer patients and prevent

aberrant cell proliferation. Importantly, they were found to be non-toxic to

normal, non-cancerous cells and were well tolerated by the patient [39]. These

drugs showed promising success in the first stages of pre-clinical trials; however,

it was eventually discovered that alternate prenylation by other enzymes such as

GGTase I sometimes allowed for the effects of FTIs to be overcome. Redundant

signaling pathways in cells also prevented FTIs from predictably blocking the

biological activity of Ras, and consequently, later stages of clinical trials were

disappointing [40, 41]. The incomplete inhibition of farnesylation and selective

effects of alternate prenylation by other enzymes led to the discovery of novel

applications for this class of drugs such as immunosuppressive therapy [42-44]

B. Effects of FTIs on Th1/Th2 Balance

In previous studies, FTIs have been shown to be able to block both IFN-γ

and IL-4 secretion by T lymphocytes in cell culture when stimulated with the T

cell receptor ligand CD-3 monoclonal antibodies [22], or with allogeneic

33

stimulator cells [5]. On the contrary, my results clearly show that in mice, IL-4 is

not being blocked, and Th2 cells are not being affected by the FTI ABT-100

(Figure 6). One reason for this discrepancy is that in vivo there are other

mechanisms controlling naïve CD4+ activation that affect T cell differentiation

that may not be present in cell culture. Artificial stimulation with anti-CD3 does

not include B7 and other co stimulatory molecules present during cell to cell

contact. Furthermore, stimulation with T lymphocyte clones may not include

other effector molecules. The GDLN is a micro environment that includes a

mixture of extracellular matrix and the cytokine/chemokine milieu. Therefore

FTIs are having a more selective effect in the complex environment of the GDLN.

This may explain the fact that FTIs are not immune suppressive in humans in

clinical trials and are generally well tolerated.

By looking at the change in gene expression of effector cell signature

cytokines in the GDLN during allograft rejection, we can infer the Th effector

subsets that are undergoing differentiation and expansion. The results here

indicate that there are fewer Th1 cells in the GDLN in mice treated with ABT-100,

because ABT-100 is able to block secretion of the Th1 cytokines IFN-γ and IL-12

during allograft rejection. The inhibition of one or both of these cytokines

prevents Th1 effector cell differentiation in the GDLN. The FTI had no significant

effect on the differentiation of the Th2 or Treg effector cell lineage as shown by

IL-4 and TGF-β transcript levels. Because ABT-100 blocked Th1 expansion

34

without effecting Th2 or Treg expansion, these results indicate that FTIs may be

selective immune modulators.

C. Gene Expression Among Mice Within Groups

I measured the levels of cytokine transcripts in each mouse. Interestingly,

in the group not receiving the drug, IFN- was up regulated in 3 of the 8 mice;

however, the group tendency was still towards down regulation. The IL-4 gene

expression in these same three mice was also up regulated. This may mean that it

is possible for both Th1 and Th2 cells to expand simultaneously in the same

lymph node as opposed to inhibiting each other’s differentiation. Because acute

graft rejection is thought to be a Th1 mediated response, it is also interesting that

in the untreated allogeneic group, IFN- was down regulated in 5 of the 8 mice,

and the overall IL-4 gene expression was slightly up regulated. There was a 1.48

fold change in IL-4 transcripts being produced in the GDLN compared to the

syngeneic control. Remarkably, 2 of the eight mice experienced a down

regulation of IL-4 with a corresponding down regulation of INF-γ. It may

therefore be possible that neither Th1 or Th2 effector cells took part in these

individual graft rejection processes, or that in some cases, Th2 cells are mediating

the response. Considering the mixed results of cytokine production and apparent

complexity of effector T cell balance within individual mice during allograft

rejection, it would be useful for future experiments to consider effector T cell

differentiation relative to the stage of graft rejection by looking at other time

points.

35

D. Future Studies

Since the naïve CD4+ T cells are not becoming either Th1, Th2 or Tregs,

then future experiments using qRT-PCR may be able to reveal more about what

type of cells are mediating the response. Gaylo et al. found that FTIs were able to

extend the duration of an allograft in mice, although not indefinitely [5]. Other T

helper cell lineages, such as the inflammatory effector cell Th17, may be

dominating the immune response. It may be that the FTIs are able to prevent

cells in the GDLNs from migrating to the allograft and that the rejection response

in this case is independent of any help from cells in the GDLNs. There is evidence

that IL-4 and IL-5 mRNA found in the donor graft during acute rejection is able

to recruit eosinophils to the allograft which destroy the cells of the transplant [36,

37]. This effect is reversed by monoclonal antibodies to IL-4 and IL-5.

Additionally, it is thought that the inflammatory chemokine CXCL9 is associated

with macrophage activation and migration to the source of infection [38].

A PCR array that can measure cDNA levels for specific cytokines and

chemokines, such a profiler PCR array from Qiagen, can measure up to 84 genes

at once in 96 well micro-plate per sample. A focused panel of

cytokines/chemokines could be used to narrow down any specific effects that

FTIs have on lymphocyte differentiation in both the graft area and GDLN. By

examining cytokine/chemokine transcripts in both areas, such an array could

also determine if FTIs are able to specifically block induction of graft infiltrating

lymphocytes and thus effector cell migration to the allograft.

36

E. qRT-PCR

qRT-PCR quantification of gene expression is considered the gold

standard for gene expression analysis, and has become the method of choice for

validating microarray data in basic research, molecular medicine, and

biotechnology [45]. The method is highly sensitive with reproducible results;

however, there are many factors that can contribute to erroneous results. For

example, the IL-17 primers I used failed to work correctly and amplified more

than one gene product rendering the results unreliable (data not shown). Another

important factor to consider is total RNA sample integrity (Table 2). The purity of

the extracted RNA must be determined, otherwise, starting amounts of RNA

could never be confirmed because of degradation due to nucleases is

unpredictable. All of the RNA used in my experiments was validated via capillary

electrophoresis on an Agilent Bioanalyzer. A RNA Integrity Number (RIN) of 10

is the highest possible value and the RNA is considered extremely pure and free

of degradation. Finally, the Minimum Information for Publication of Quantitative

Real-Time PCR Experiments (MIQE) urges investigators to determine gene

efficiency for each gene used, and make the necessary adjustments in fold change

data. The data reported here assumes 100% gene efficiency, meaning that each

PCR amplification cycle doubles the number of newly made DNA templates. This

is likely not the case, and our data is therefore an overestimate of the fold change.

With these and other considerations mentioned in the MIQE guidelines, gene

expression analysis of alloreactive T cells during allograft rejection in mice is

37

therefore an excellent method to consider to continue investigation of ABT-100

on alloreactive T cells.

38

F. Conclusion

By examining the signature cytokines for the three of the four primary Th

effector cells, a modest beginning was made to unravel the immunomodulatory

effect that the FTI ABT-100 has on allograft rejection in mice. These results

clearly demonstrate that ABT-100 has the ability to selectively immunomodulate

the differentiation of alloreactive T cells by blocking the expansion of Th1 cells

but not Th2 cells in mice. There was also no overall effect on Treg differentiation.

Future experiments can continue to look at gene expression in both the GDLN

and the corresponding tissue of the allograft. By examining gene expression

simultaneously in both the GDLN and the allograft tissue, we could further

determine which T helper cells are differentiating upon activation in the GDLN

and how they are specifically mediating the rejection process. Little is currently

known about the effect of ABT-100 on chemokines and the consequential

migration of effector cells to the source of infection. By investigating the

differences of gene expression compared to a control in the presence and absence

of FTIs, we can gain a better understanding of the mechanisms behind graft

rejection in mice as well as continue to elucidate the immunomodulatory effects

of ABT-100.

39

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