McMichael THESIS

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
References
1. Organ Donation and Transplantation Save Lives. Retrieved on October 12,
2012 from: http://www.organdonor.gov/index.html
2. After the Transplant. Retrieved on October 12, 2012:
http://www.transplantliving.org/after-the-transplant/medications/post-
transplant-medications/
3. Organ Procurement and Transplantation. Retrieved on October 12, 2012
from: http://optn.transplant.hrsa.gov
4. Issa, F., Wood, K. J., & Schiopu, A. (2010). Role of T cells in graft rejection
and transplantation tolerance. Expert Review of Clinical Immunology, 6,
1, 155-169.
5. Gaylo, A. E., Laux, K. S., Batzel, E. J., Berg, M. E., & Field, K. A. (2009).
Delayed rejection of MHC class II-disparate skin allografts in mice treated
with farnesyltransferase inhibitors. Transplant Immunology, 20, 3, 163-
170.
6. Neefjes, J., Jongsma, M. L., Paul, P., & Bakke, O. (2011). Towards a
systems understanding of MHC class I and MHC class II antigen
presentation. Nature Reviews. Immunology, 11, 12, 823-36.
7. Burgdorf, ., Kautz, A., B hnert, ., Knolle, P. A., & Kurts, C. (2007).
Distinct pathways of antigen uptake and intracellular routing in CD4 and
CD8 T cell activation. Science. 316, 5824, 612-6.

40
8. Fazilleau, N., Mark, L., McHeyzer-Williams, L. J., & McHeyzer-Williams,
M. G. (2009). Follicular Helper T Cells: Lineage and Location. Immunity,
30, 3, 324-335.
9. Pietra, B. A., Wiseman, A., Bolwerk, A., Rizeq, M., & Gill, R. G. (2000).
CD4 T cell-mediated cardiac allograft rejection requires donor but not host
MHC class II. The Journal of Clinical Investigation, 106, 8, 1003-10.
10. Lechler, R. I., & Batchelor, J. R. (1982). Restoration of immunogenicity to
passenger cell-depleted kidney allografts by the addition of donor strain
dendritic cells. The Journal of Experimental Medicine, 155, 1, 31-41.
11. Jackson Laboratories. Informatics BM12 mice. Retrieved on October 12,
2012 from:
http://www.informatics.jax.org/javawi2/servlet/WIFetch?page=alleleDet
ail&id=MGI:3586447#mutationDescription
12. Fraser, J. D., Newton, M. E., & Weiss, A. (1992). CD28 and T cell antigen
receptor signal transduction coordinately regulate interleukin 2 gene
expression in response to superantigen stimulation. The Journal of
Experimental Medicine, 175, 4, 1131-4.
13. Agnello, D., Lankford, C. S., Bream, J., Morinobu, A., Gadina, M., O'Shea,
J. J., & Frucht, D. M. (2003). Cytokines and transcription factors that
regulate T helper cell differentiation: new players and new insights.
Journal of Clinical Immunology, 23, 3, 147-61.

41
14. Curtsinger, J. M., Schmidt, C. S., Mondino, A., Lins, D. C., Kedl, R. M.,
Jenkins, M. K., & Mescher, M. F. (1999). Inflammatory cytokines provide a
third signal for activation of naive CD4+ and CD8+ T cells. Journal of
Immunology. 162, 6, 3256-62.
15. Zygmunt, B., & Veldhoen, M. (2011). T Helper Cell Differentiation.
Advances in Immunology, 109, 159-196.
16. Weichhart, T., & Saemann, M. D. (2010). T Helper Cell Differentiation:
Understanding the Needs of Hierarchy. Immunity, 32, 6, 727-729.
17. Nguyen, K. B., Watford, W. T., Salomon, R., Hofmann, S. R., Pien, G. C.,
Morinobu, A., Gadina, M., ... Biron, C. A. (2002). Critical role for STAT4
activation by type 1 interferons in the interferon-gamma response to viral
infection. Science. 297, 5589, 2063-6.
18. McGeachy, M. J., Bak-Jensen, K. S., Chen, Y., Tato, C. M., Blumenschein,
W., McClanahan, T., & Cua, D. J. (2007). TGF-beta and IL-6 drive the
production of IL-17 and IL-10 by T cells and restrain T(H)-17 cell-
mediated pathology. Nature Immunology, 8, 12, 1390-7.
19. Afzali, B., Lombardi, G., Lechler, R. I., & Lord, G. M. (2007). The role of T
helper 17 (Th17) and regulatory T cells (Treg) in human organ
transplantation and autoimmune disease. Clinical & Experimental
Immunology, 148, 1, 32-46.
20.Takahashi, T., Tagami, T., Yamazaki, S., Uede, T., Shimizu, J., Sakaguchi,
N., Mak, T. W., ... Sakaguchi, S. (2000). Immunologic self-tolerance

42
maintained by CD25+ /CD4+ regulatory T cells constitutively expressing
cytotoxic T lymphocyte-associated antigen 4. Journal of Experimental
Medicine, 192, 303-309.
21. Barbara, J. A., Turvey, S. E., Kingsley, C. I., Spriewald, B. M., Hara, M.,
Witzke, O., Morris, P. J., ... Wood, K. J. (2000). Islet allograft rejection can
be mediated by CD4+, alloantigen experienced, direct pathway T cells of
TH1 and TH2 cytokine phenotype. Transplantation, 70, 11, 1641-9.
22.Marks, R. E., Ho, A. W., Robbel, C., Kuna, T., Berk, S., & Gajewski, T. F.
(2007). Farnesyltransferase inhibitors inhibit T-cell cytokine production at
the posttranscriptional level. Blood, 110, 6, 1982-8.
23.Dunn, S. E., Youssef, S., Goldstein, M. J., Prod'homme, T., Weber, M. S.,
Zamvil, S. S., & Steinman, L. (2006). Isoprenoids determine Th1/Th2 fate
in pathogenic T cells, providing a mechanism of modulation of
autoimmunity by atorvastatin. The Journal of Experimental Medicine,
203, 2, 401-12.
24.Si, M. S., Ji, P., Lee, M., Kwok, J., Kusumoto, J., Naasz, E., Ng, S. C., ...
Imagawa, D. K. (2005). Potent farnesyltransferase inhibitor ABT-100
abrogates acute allograft rejection. The Journal of Heart and Lung
Transplantation : the Official Publication of the International Society for
Heart Transplantation, 24, 9, 1403-9.
25.Kloog, Y., & Cox, A. D. (2000). RAS inhibitors: potential for cancer
therapeutics. Molecular Medicine Today, 6, 10, 398-402.

43
26.Prior, I. A., Lewis, P. D., & Mattos, C. (2012). A comprehensive survey of
ras mutations in cancer. Cancer Research, 72, 10, 2457-2467.
27. Hancock, J. F., Magee, A. I., Childs, J. E., & Marshall, C. J. (1989). All ras
proteins are polyisoprenylated but only some are palmitoylated. Cell, 57, 7,
1167-77.
28.Zhang, F. L., & Casey, P. J. (1996). Protein prenylation: molecular
mechanisms and functional consequences. Annual Review of
Biochemistry, 65, 241-69.
29.Downward, J., Graves, J. D., Warne, P. H., Rayter, S., & Cantrell, D. A.
(1990). Stimulation of p21ras upon T-cell activation. Nature, 346, 6286,
719-23.
30.Kimkong, I., Avihingsanon, Y., & Hirankarn, N. (2009). Expression profile
of HIN200 in leukocytes and renal biopsy of SLE patients by real-time RT-
PCR. Lupus, 18, 12, 1066-1072.
31. Le, M. A., Flamand, ., Demoor, F. ., No l, J. C., urquin, M., Kiss, R.,
Nahori, M. A., ... Abramowicz, D. (1999). Critical roles for IL-4, IL-5, and
eosinophils in chronic skin allograft rejection. The Journal of Clinical
Investigation, 103, 12, 1659-67.
32.Yin, J. L., Shackel, N. A., Zekry, A., McGuinness, P. H., Richards, C.,
Putten, K. V., McCaughan, G. W., ... Bishop, G. A. (2001). Real-time
reverse transcriptase-polymerase chain reaction (RT-PCR) for
measurement of cytokine and growth factor mRNA expression with

44
fluorogenic probes or SYBR Green I. Immunology and Cell Biology, 79, 3,
213-21.
33.National Center for Biotechnology Information. Retrieved from:
http://www.ncbi.nlm.nih.gov/projects/genome/probe/doc/TechQPCR.sh
tml
34.Schmittgen, T. D., & Livak, K. J. (2008). Analyzing real-time PCR data by
the comparative CT method. Nature Protocols, 3, 6, 1101-1108.
35.Hechinger, A.-K., Maas, K., Durr, C., Leonhardt, F., Prinz, G., Marks, R.,
Gerlach, U., ... Zeiser, R. (2012). Inhibition of protein geranylgeranylation
and farnesylation protects against GvHD via effects on CD4 effector T
cells. Haematologica.
36.Le, M. A., Flamand, ., Demoor, F. ., No l, J. C., urquin, M., Kiss, R.,
Nahori, M. A., ... Abramowicz, D. (1999). Critical roles for IL-4, IL-5, and
eosinophils in chronic skin allograft rejection. The Journal of Clinical
Investigation, 103, 12, 1659-67.
37. Le, M. A., urquin, M., Demoor, F. ., No l, J. C., Nahori, M. A., Pretolani,
M., Flamand, V., ... Abramowicz, D. (1999). IL-5 mediates eosinophilic
rejection of MHC class II-disparate skin allografts in mice. Journal of
Immunology. 163, 7, 3778-84.
38.Flier, J., Boorsma, D. M., van, B. P. J., Nieboer, C., Stoof, T. J., Willemze,
R., & Tensen, C. P. (2001). Differential expression of CXCR3 targeting

45
chemokines CXCL10, CXCL9, and CXCL11 in different types of skin
inflammation. The Journal of Pathology, 194, 4, 398-405.
39. Adjei, A. A. (2006). Farnesyltransferase inhibitors. Update on Cancer
Therapeutics, 1, 1, 17-23.
40. Braun, T., & Fenaux, P. (2008). review: Farnesyltransferase inhibitors and
their potential role in therapy for myelodysplastic syndromes and acute
myeloid leukemia. British Journal of Haematology, 141, 5, 576-586.
41. Kloog, Y., & Cox, A. D. (2000). RAS inhibitors: potential for cancer
therapeutics. Molecular Medicine Today, 6, 10, 398-402.
42. Yang, W., Yamada, M., Tamura, Y., Chang, K., Mao, J., Zou, L., Feng, Y., ...
Yao, S. (2011). Farnesyltransferase inhibitor FTI-277 reduces mortality of
septic mice along with improved bacterial clearance. Journal of
Pharmacology and Experimental Therapeutics, 339, 3, 832-841.
43. Shinozaki, S., Inoue, Y., Yang, W., Fukaya, M., Carter, E. A., Ming-Yu, Y.,
Fischman, A., ... Kaneki, M. (2010). Farnesyltransferase inhibitor
improved survival following endotoxin challenge in mice. Biochemical and
Biophysical Research Communications, 391, 3, 1459-1464.
44.Na, H. J., Lee, S. J., Kang, Y. C., Cho, Y. L., Nam, W. D., Kim, P. K., Ha, K.
S., ... Kim, Y. M. (2004). Inhibition of farnesyltransferase prevents
collagen-induced arthritis by down-regulation of inflammatory gene
expression through suppression of p21(ras)-dependent NF-kappaB
activation. Journal of Immunology, 173, 2, 1276-83.

McMichael THESIS

More Related Content

What's hot (18)

Viewers also liked (8)

Similar to McMichael THESIS (20)

McMichael THESIS