CHANGES IN GENE EXPRESSION IN CYCLOSPORINE A TREATED GINGIVAL FIBROBLASTS

by

Jeffrey S. Wallis

A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Biological Sciences

Summer 2005

Copyright 2005 Jeffrey S. Wallis All rights reserved

UMI Number: 1428256

Copyright 2005 by Wallis, Jeffrey S.

All rights reserved.

UMI Microform 1428256 Copyright 2005 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code.

ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346

Changes in Gene Expression In Cyclosporine A Treated Gingival Fibroblasts

by

Jeffrey S. Wallis

Approved: ______Mary C. Farach-Carson, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee

Approved: ______Daniel D. Carson, Ph.D. Chair of the Department of Biological Sciences

Approved: ______Thomas Apple, Ph.D. Dean of the College of Arts and Sciences

Approved: ______Conrado M. Gempesaw II, Ph.D. Vice Provost for Academic and International Programs DEDICATION

I would like to give very special thanks to my advisor Dr. Cindy Farach-Carson for

being an incredible mentor and teacher. Over the past 3 years I have been fortunate to have been given the opportunity to explore a subject of great personal interest in an environment that has allowed me to grow both as a scientist and a person. Her knowledge and patience is an inspiration to all those around her. I would not be the individual I am today nor would my life be headed in its current direction if it were not for her and I will be forever grateful for everything she has taught me.

I would like to thank Dr. Daniel Carson for his guidance and valuable opinions. His advice on where the direction of my research should go has been integral to its success.

I would like to thank Dr. David Usher for all his contributions towards my project as well as keeping me employed as a teaching assistant during my time at the University of

Delaware. I thank you and perhaps most importantly, my parents thank you.

I would also like to thank Dr. Jonathan Korostoff, whose expert knowledge in the field of dentistry, specifically periodontics, has been both a valuable asset to my scientific endeavors and an inspiration for me as I pursued my acceptance to dental school.

I must also thank all the members of the Carson and Farach-Carson labs. I could not have made it through the rigors of graduate school without their help and friendship. I will always have fond memories of my time spent with you all.

Finally, I would like to thank my parents for their love and support as I move on to my next challenge. I hope that I can continue to make you both proud and become the doctor I so admire in the both of you. I love you both very much.

iii ACKNOWLEDGEMENTS

• National Institutes of Health, R03 Grant

• I would like to thank the following people for their personal contributions towards

my research: Ben Rohe and Dr. Chu Zhang for their assistance in RT-PCR, Q-

PCR and cell staining work; Joanne Julian for her advice and expertise involving

cell culture and staining; Anissa Brown, Melissa Brayman, and Caroline Muir for

their help with western blot techniques and analysis; Lynn Schwarting and John

O’Connor for their help and assistance in microarray analysis. Doreen Anderson

for her help in formatting and submission of my thesis.

iv

TABLE OF CONTENTS

TABLE OF CONTENTS……………………………………………………………….v

LIST OF TABLES……………………………………………………………………..vii

LIST OF FIGURES……………………………………………………………………viii

LIST OF ABBREVIATIONS………………………………………………………...... ix

ABSTRACT…………………………………………………………………………...... xi

HYPOTHESIS………………………………………………………………………….20

Chapter 1 Introduction……..……………….…………………………………………..1

1.1 Gingival Overgrowth.…………………………………………………………….1

1.2 Gene Changes Associated with CsA…..………………………………………….8

1.3 Microarray Analysis ………………………………………………………..….. 16

Chapter 2 Materials and Methods………………..……………………………………21

2.1 Cell Line and Culture……………………………………………………………21

2.2 RNA Extraction and Northern Blot……………………………………………..22

2.3 Microarray Analysis……………………………………………………………..22

2.4 Microarray Statistics…………………………………………………………….23

2.5 Reverse-transcript PCR (RT-PCR) and Real-Time PCR……………………….23

2.6 Antibodies……………………………………………………………………….25

2.7 Western Blots……………………………………………………………………26

2.8 Cell Staining……………………………………………………………………..28

Chapter 3 Results……………………………………………………………….………30

v 3.1 RNA Gel Electrophoresis and Northern Blot…………………………………...30

3.2 Microarray Results………………………………………………………………32

3.3 Real-Time PCR………………………………………………………………….36

3.4 Western Blots……………………………………………………………………40

3.5 Cell Staining……………………………………………………………………..42

Chapter 4 Discussion and Conclusion…………………………………………………46

4.1 Discussion……………………………………………………………………….46

4.2 Conclusions……………………………………………………………………...53

Chapter 6 Future Work………………………………………………………………...55

References……………………………………………………………………………….57

Appendix………………………………………………………………………………...64

vi

TABLES

Table 1. Relative Intensities of Array Genes Chosen for Validation………..………….35

Table 2. List of Extracellular Matrix Genes…………………………………………….64

Table 3. List of MAP Kinase Genes…………………………………………………….67

vii

FIGURES

Figure 1. Cross-Section of Tooth Microenvironment…...………………………………..3

Figure 2. Molecular Structure of Cyclosporine A…………..…………………………..14

Figure 3. Proposed Mechanism of Action of Cyclosporine A ..………………………...15

Figure 4. Sample protocol of GEArray™ Q Series Microarray……….………...………18

Figure 5. Sample of Microarray………………………………………………………....19

Figure 6. RNA Gel and Northern Blot Analysis………………………………………...31

Figure 7. Extracellular Matrix Microarray Images of 6 Day Vehicle vs. CsA………….33

Figure 8. MAP Kinase Microarray Images of 6 Day Vehicle vs. CsA………………….34

Figure 9. Q-PCR of Collagen 1 alpha 1…………………………………………………38

Figure 10. Q-PCR of Fibronectin…………………………..……………………………39

Figure 11. Western Blot Analysis………………………………………………………..41

Figure 12. Trypan Blue Staining………………………………………………………...43

Figure 13. Crystal Violet Staining………………………………………………………44

Figure 14. Syto13 and Phalloidin Staining………….…………………………………..45

Figure 15. Fold Difference of Collagen 1 alpha 1 Q-PCR cycle threshold using ∆∆ct method……………………………………………………………………..…70

viii

ABBREVIATIONS

Bp base pairs

CaN calcineurin

CD1 cyclin D1 cDNA complementary DNA

CEACAM5 CarcinoEmbryonic Antigen Cell Adhesion Molecule 5

Col1α1 collagen type 1 alpha 1 chain

CpN cyclophilin

CsA cyclosporine A

dNTP deoxynucleoside 5'-triphosphate

ECM extracellular matrix

EDTA ethylenediaminetetraacetic

EGR-1 Early Growth Response 1

FACS fluorescence activated cell sorter

FBS fetal bovine serum

FDA Food and Drug Administration

FK506 tacrolimus

FN-1 fibronectin

GAGs glycosaminoglycans

GAPDH glyceraldehyde-3-phosphate dehydrogenase

HGFs human gingival fibroblasts

IFN-γ interferon gamma

ix IL-2 interleukin-2

MEM minimal essential media

mRNA messenger RNA

NF-AT Nuclear Factor of Activated T Cell

PBS phosphate buffered saline

PBS-T PBS + Tween 20 solution

PIC Protease Inhibitor Cocktail

PMSF phenylmethylsulphonylfluoride

Q-PCR quantitative RT-PCR or real time RT-PCR

RT-PCR reverse transcript-DNA polymerase chain reaction

SEB Sample Extraction Buffer

SDS-PAGE sodium dodecyl sulfate-polyacrylamide gel electrophoresis

SPARC Secreted Protein, Acidic, Cysteine-Rich

Ta annealing temperature

TCA trichloroacetic acid

TGFβ transforming growth factor β

Tm melt temperature

x

ABSTRACT

Cyclosporine A (CsA) is a potent immunosuppressant drug, produced by the fungus

Tolypocladium inflatum, used to prevent allograft rejection after organ transplantation. It

is distributed under the name Sandimmune® and has increased the success rate of transplants to approximately 95% over a one year period. The immunosuppressant effect is due to the effect of CsA on the serine-threonine Ca2+-calmodulin protein phosphatase calcineurin. Calcineurin is responsible for activation of NF-AT (nuclear factor of activated T cell) which translocates to the nucleus of the T cell to activate interleukin-2 for T cell maturation and proliferation. CsA complexes with cyclophilin and binds to calcineurin to inhibit its phosphatase activity thereby preventing T cell proliferation.

A common side effect of CsA is gingival overgrowth. The exact cause of gingival overgrowth remains unsolved and controversy remains over whether the overgrowth is a result of hypertrophic growth or hyperplastic growth. In this study, gingival fibroblasts were used to examine whether gene changes after treatment with CsA cause hypertrophic growth, hyperplastic growth, or a combination of both. Gene arrays representing pathway specific genes associated with each form of growth, as well as cellular stains to

examine nuclear and cytoskeletal changes, were employed to address the problem. Five

genes expressed by gingival fibroblasts were identified from the arrays and selected for

validation. The results indicate that Collagen 1α1 mRNA expression decreases after six

days of treatment with CsA, but that overall there were modest changes in gene

expression in gingival fibroblasts treated with CsA over a six day period. It was

xi concluded that gingival fibroblasts are not solely responsible for the overgrowth seen in patients treated with CsA. Overgrowth is more likely due to a combination of factors involving paracrine interactions with the epithelium, endothelium, and tooth microenvironment.

xii

Chapter 1

INTRODUCTION

1.1 Gingival Overgrowth

Gingival overgrowth is a condition commonly found in patients taking medication

such as phenytoin, nifedipine (a calcium channel blocker), and immunosuppressants

including FK506, and CsA. On average, CsA-induced overgrowth occurs in

approximately 27% of patients and may be seen four to six weeks after the beginning of

treatment (Jaiarj 2003), (Rateitschak-Pluss, Hefti et al. 1983).

It remains controversial as to whether gingival overgrowth occurs as the result of

hyperplastic growth or hypertrophic growth. In other words, it is unclear if there occurs

an increase in the number of gingival fibroblasts or an increase in extracellular matrix

secreted by these cells or both. In addition to medication, other contributing factors may

include age (with younger patients experiencing a more pronounced effect), genetic

predisposition, and oral hygiene of the patient (Rateitschak-Pluss, Hefti et al. 1983),

(Jaiarj 2003), (Seymour, Thomason et al. 1996), (Stabellini, Calastrini et al. 2004).

Bartold et al. (1989) and Willershausen-Zonnchen et al. (1992) observed an increase in the number of gingival fibroblasts which would correspond to hyperplastic change. A recent study on gingival fibroblasts in rats showed that there is an increase after CsA treatment as well (Yoshida, Nagata et al. 2005). However, Bolzani et al. (2000) reported that an inhibition of matrix metalloproteinases results in accumulation of extracellular

1 matrix proteins, corresponding to a hypertrophic change (Bartold 1989; Bolzani, Della

Coletta et al. 2000) (Bartold 1989; Willershausen-Zonnchen, Lemmen et al. 1992). To

confound things further, others report changes in both categories of growth and suggest

that an increase in both the number of fibroblasts as well as an increase in extracellular

matrix occurs (Wysocki, Gretzinger et al. 1983). Furthermore, in a study by Mariani et

al., characteristics of the ground substance in CsA-induced gingival overgrowth were

examined. The authors observed that the increase in gingival tissue was a result of an

increase in the production of glycosaminoglycans (GAGs) by gingival fibroblasts.

Relative levels of GAGs were higher in tissue taken from patients experiencing

overgrowth as a result of CsA treatment as well as in cultures of gingival fibroblasts

treated with CsA. The authors suggest a direct response of connective tissue in CsA-

induced gingival overgrowth may be the underlying cause of the condition (Mariani,

Calastrini et al. 1996). Today, the molecular cause of gingival overgrowth remains

unclear, as do the wide range of responses associated with the condition seen among a

diverse patient population.

Another important aspect of CsA-induced gingival overgrowth is the observation that not all patients receiving the drug will react to this treatment with gingival overgrowth.

The terms “responder” and “non-responder” are used frequently in the literature with reference to patients who develop gingival overgrowth as a result of drug therapy and those patients who do not have gingival overgrowth even during long courses of drug

therapy (Fujii, Matsumoto et al. 1994; Matsumoto and Fujii 2002; Bulut, Sokmensuer et

al. 2004). The variation in response to CsA may be a direct result of genetic

2 epithelia

stroma

Modified from http://medic.med.uth.tmc.edu/Lecture/Main/tool2.htm, Anne LeMaistre, M.D.

Figure 1. The image above shows a cross-section of the tooth microenvironment displaying tooth, gingiva, and bone layers. Gingival fibroblasts are located in the stromal layer of the gingiva.

3 predisposition and age, but this concept remains unclear (Seymour, Thomason et al.

1996).

The first known cases of CsA-induced gingival overgrowth were reported in the early

1980’s by Rateitschak-Pluss et al. (1983). In their study, three cases out of fifty patient cases who had received kidney transplants, experienced gingival overgrowth. In all cases

CsA was administered at 10 mg / kg body weight per day. The three symptomatic patients had been receiving CsA for 9 months, 7 months, and 8 months, respectively, with pretreatment conditions ranging in oral hygiene from generalized gingivitis to severe periodontitis. The first patient was found to have typical overgrowth with the anterior region especially noted with pocket depths of up to seven mm. Large buildups of plaque and calculus also were observed. The second patient had less overgrowth than the first or third patient primarily due to proper oral hygiene care and had pocket depths of six mm.

The third patient had severe periodontitis prior to treatment and subsequently developed prominent overgrowth. Pocket depths of twelve mm were recorded. The histologic appearance of the third patient was examined in detail. The examiners noted that overgrowth tissue almost extensively was comprised of vascularized connective tissue.

Abnormal arrangement of collagen fiber bundles and inflammatory cell buildup also were observed. This patient, as a result of overgrowth and vomiting from CsA treatment, had to have all maxillary teeth removed. It also was noted that when teeth were extracted, there was no recurrence of gingival overgrowth, implicating the microenvironment surrounding the tooth as a requirement for gingival overgrowth. Overall, overgrowth was greatly reduced by proper oral hygiene techniques and daily care (Rateitschak-Pluss,

Hefti et al. 1983).

4 Tyldesley et al. (1984) also conducted a study on renal transplant patients taking

CsA. 36 patients (23 male and 13 female) varying in age from 15 to 68 years old, were

part of a trial in which they report a 25% incidence of overgrowth. Incidence of

overgrowth occurred more in females (38%) than in males (17%). Time of incidence

varied anywhere from 1 month to 12 months with the most severe overgrowth taking

place in patients with poor or lack of proper hygiene. They also report that tissue from

several of these patients had an increase in number of collagen fibers and that this is the

most significant histopahtological characteristic in terms of gingival overgrowth. They

stress the importance of proper oral hygiene care to control the severity of gingival overgrowth (Tyldesley and Rotter 1984).

Seymour et al. (1991) conducted a study focusing primarily on the effects of oral

hygiene care on severity of gingival overgrowth. In their study, 27 adult renal allograft

patients taking CsA or prednisolone for prevention of rejection were assigned either an

intensive oral care program or no treatment program at all. After a six month period,

patients were reexamined and conditions of the upper and lower anterior teeth were

recorded. Scoring of plaque and gingiva was done according to the plaque index and

gingival index systems of Silness and Loee (Loee and Silness 1963), (Silness and Loee

1964). After six months, the treatment group had plaque and gingival index scores

notably lower than the non-treatment group although both groups had incidences of

overgrowth when compared to initial post-transplant assessments. Through their study,

they concluded that an intensive oral hygiene program is beneficial in helping to reduce

the severity of gingival overgrowth, but that plaque is not the sole factor in drug induced gingival overgrowth (Seymour and Smith 1991).

5 McGaw et al. (1987) examined whether or not there was a connection between

overgrowth and the accumulation of plaque, gingivitis, and CsA levels in serum or saliva

samples. Thirty patients undergoing immunosuppressive therapy for renal

transplantations with CsA were scored for their respective levels of plaque and gingivitis.

The patient pool consisted of 15 men and 15 women from ages 18 to 62. Eight patients recorded incidences of overgrowth with variations in severity, but most notably in the areas with plaque accumulation. These patients were deemed responders to CsA treatment and had larger plaque and gingivitis scores than nonresponders. Scores for both plaque and gingivitis showed an association with scores given for overgrowth. In addition, CsA levels in the saliva were higher in the responder group. Among responders, higher levels were found in those with more severe conditions of overgrowth.

They did find some connection between saliva and serum levels, but admit a low degree of correlation (McGaw, Lam et al. 1987).

The immunohistochemical differences in gingival overgrowth among 30 renal transplant biopsies were examined by O’Valle et al. (1994). Patients were taking CsA, prednisone, and anti-lymphocytic globulin. The focus of their study was to determine if there were changes in the numbers of inflammatory cells, plasmatic cells, and T- lymphocytes. The study involved 17 men and 13 women with ages approximately 39 years old with 22.2% suffering from severe CsA-induced overgrowth, 33.3% from moderate overgrowth, and 44.4% from mild overgrowth. Most patients had poor oral hygiene with high plaque and bleeding in 24 of the 30 cases. Histopathological examination revealed that all specimens had different levels of papilomatosis, acanthosis, and epithelial spongiosis, but an increase in the number of collagen bundles was observed

6 on the whole along with increasing numbers of vessels. The group was compared to a

healthy control group consisting of four men and six women. In the more severe cases of

gingival overgrowth, total inflammatory infiltrate increased as did helper/inducer

lymphocytes and macrophages. The authors hypothesized that accumulation of dental

plaque may act to concentrate CsA since higher concentrations of the drug has been

found in plaque than blood. Also, the high number of lymphocytes may hold at least a

partial explanation. Lymphokines induce fibrogenic activity (Kovacs 1991).

Specifically, interferon-γ inhibits fibrogenic activity. Because CsA inhibits interferon-γ

and they observe an increase in the number of lymphocytes, the authors conclude that

overgrowth may be a result of both factors. They further stress that proper oral hygiene

may help the condition (O'Valle, Mesa et al. 1994).

Nishikawa et al. (1996) reported in their studies on gingival overgrowth in Fischer rats treated with immunosuppressant drugs that all 344 animals tested displayed incidence of overgrowth caused by the drugs phenytoin, CsA, or nifedipine. The authors claimed that drug blood levels are most important in inducing gingival overgrowth in

rats, and that the animals responded to CsA with the most severe incidences of

overgrowth. Age also was considered to be a determining factor according to the results

of this study. In 15 day old rats, the severity of overgrowth was 55% greater than in rats

that were 30 days old. Rats 60 days old showed no noteworthy signs of overgrowth.

Finally, the importance of dental plaque in gingival overgrowth was assessed. The

authors noted that bacterial infection promoted the buildup of dental plaque, and used this

method as a way to examine the effect of dental plaque on gingival overgrowth.

Overgrowth was more pronounced in infected animals than in non-infected animals

7 indicating that plaque is an important factor in the severity of gingival overgrowth

(Nishikawa, Nagata et al. 1996).

1.2 Gene Changes Associated With CsA

Cyclosporine A (CsA) is a neutral, cyclic, hydrophobic, antilymphocytic,

endecapeptide derived from the soil fungus Tolipocladium inflatum Gams, having a

molecular weight of 1202.6 (Borel, Feurer et al. 1976), (Petcher, Weber et al. 1976).

The fungus metabolite is used specifically to prevent allograft rejection after organ

transplant surgery by inhibiting Interleukin-2 (IL-2) dependent differentiation of T cells

as well as interferon-γ, thus preventing T-lymphocyte proliferation and indirect response

from B-cells (Borel and Wiesinger 1979), (Sigal and Dumont 1992). Borel et al.

demonstrated that the drug prevents humoral as well as cellular immunity, making it

especially useful in organ transplantation because of its low level of cytotoxicity,

myelotoxicity, and non-steroidlike effects (Borel, Feurer et al. 1976). The first trial of

CsA in humans was performed by Calne et al. in 1978 on patients undergoing renal

allografts during which side effects such as hirsutism, hepatotoxicity and nephrotoxicity

were observed (Calne, White et al. 1978). Other side effects may include elevated blood

pressure, tremors, and gingival overgrowth (Ota 1983). CsA was approved by the FDA

® in 1983 and was first distributed under the drug name Sandimmune by Sandoz Research

Laboratories (Novartis Pharmaceuticals). Today, the one year survival rate of those receiving allograft transplants has increased from 50% to 95% (Sigal and Dumont 1992).

The typical dose required for immunosuppression is 10 mg / kg body weight / day

(Rateitschak-Pluss, Hefti et al. 1983). CsA also is used to treat a multitude of

8 autoimmune conditions including psoriasis, rheumatoid arthritis, inflammatory bowel disease, asthma, insulin dependent diabetes mellitus and atopic dermatitis (Bach 1999).

As shown in figure 3, CsA elicits its effect through complexing with the protein cyclophilin. This complex then acts to inhibit the activity of the calcium/calmodulin- dependent protein phosphatase calcineurin. This inhibition prevents nuclear factor of activated T-cells (NF-AT) from activating the transcription of the lymphokine genes IL-2 and IFN-γ (Kronke, Leonard et al. 1984; Schwaninger, Blume et al. 1993). This inhibition prevents the proliferation of T-lymphocytes in a dose dependent manner, making it useful in optimizing the success of organ transplants by reducing allograft rejection (Buurman, Ruers et al. 1986), (Reem, Cook et al. 1983).

CsA may have indirect effects on other genes affected by elements of the calcineurin pathway. The calcium/calmodulin element of the calcineurin pathway is involved in regulation of the cell cycle. Specifically, the calcium/calmodulin complex is required for the progression of the cell cycle at the G1/S boundary (Kahl and Means 2003). It has been shown that overexpression of calmodulin increases cell proliferation by decreasing the duration of the G1 phase of the cell cycle (Rasmussen and Means 1987).

A recent study by Kahl et al. (2004) examined cyclin D1 accumulation in dipoid human fibroblasts. Cyclin D1 is required for progression into G1 phase. Fibroblasts treated with CsA showed a marked decrease in cyclin D1 protein synthesis. The authors then examined the effect of calcineurin overexpression on cyclin D1 and found an increase in expression of cyclin D1. The authors conclude that calcineurin regulates cyclin D1 accumulation for G1 phase regulation (Kahl and Means 2004).

9 The calcineurin pathway is also involved in extracellular matrix turnover. Gooch et

al. (2003) looked at the involvement of calcineurin in diabetes and ECM accumulation.

The authors studied the effect of calcineurin inhibition on ECM accretion in diabetic rats.

The authors found that after inhibition of calcineurin with CsA, ECM accumulation was

drastically reduced in glomeruli of rats, but no significant reduction in cortical tissue was

observed. A reduction in mRNA expression of fibronectin was found in the

tubulointerstitium, but not the glomeruli as well. The authors conclude calcineurin has an

important role in regulation of the ECM in the kidneys of diabetic rats (Gooch, Barnes et

al. 2003). Furthermore, a study conducted by Esposito et al. (2004) examined calcineurin

inhibition in human glomeruli. After treatment with CsA, kidney biopsies had marked

increases in collagen IV alpha 2 and TIMP-2 mRNA levels, but MMP9 levels remained

constant. The authors determined that calcineurin inhibition, as a result of CsA

treatment, regulates the ECM in human glomeruli (Esposito, Foschi et al. 2004).

NF-AT, the protein that calcineurin directly acts on, has been examined for its roles in

the ECM as well as its involvement in the cell cycle. Jauliac et al. (2002) observed that

NFAT transcription factors are involved in integrin signaling in carcinoma invasion.

Specifically, NFAT1 and NFAT5 were shown to be active in breast carcinoma and that

their activity is associated with the presence of integrin α6β4, an integrin involved in cell

motility. The authors conlclude that NFATs have implications in cancer (Jauliac, Lopez-

Rodriguez et al. 2002).

Molkentin et al. (2004) reviewed calcineurin/NFAT signaling in connection with

MAPKs in cardiac hypertrophy. In the review he cites that in cardiac myocytes, hypertrophy may be attributed to the relationship of the calcineurin pathway and MAPK

10 signaling (Molkentin 2004). In relation to this review, a study by Sanna et al. (2005) examined the relationship of the calcineurin/NFAT pathway to MEK1, an element of the

MAPK cascade linked to cardiac hypertrophy in mice. The authors showed that after inhibition of calcineurin in cardiomyocytes, hypertrophy was decreased and that upon inhibition of MEK1-ERK1/2 after calcineurin stimulation, hypertrophy was reduced as well. The authors also observe that MEK1-ERK1/2 and calcineurin/NFAT proteins bind in cardiomyocytes for NFATc3 phosphorylation. The authors conclude that the two pathways are interconnected in cardiac hypertrophy (Sanna, Bueno et al. 2005).

In addition to IL-2, other cytokines have been examined to see if inhibition occurs after CsA treatment. The mRNA expression levels of IL-4, IL-5, and IL-13 were examined in peripheral blood mononuclear cells from a patient treated with CsA by

Katagiri et al. (1997). All mRNA levels of the interleukin genes mentioned decreased in expression, but the authors note no change in IFN-γ mRNA expression (Katagiri, Itami et al. 1997).

In a study conducted by Shihab et al. (2002), the authors addressed the role of CsA in angiogenesis. Specifically, they examined the role of an angiotensin II blockade on vascular endothelial growth factor (VEGF) in rats. They found that VEGF mRNA and protein expression increased after treatment CsA, but were reduced after blocking of

angiotensin II. They conclude that increased VEGF expression after CsA treatment is

related to angiotensin II and that they may have implications for ECM composition

(Shihab, Bennett et al. 2002).

Tuglular et al. (2004) looked at the effects of CsA on renal Bone Morphogenetic

Protein-7 (BMP-7) expression in male Wistar rats due to its known anti-fibrotic effect. In

11 connection to Shihab et al. (2002), the effect of an angiotensin-converting enzyme inhibitor was examined as well. Through immunohistochemical staining, the authors observed that there were decreases in BMP-7 expression in rats treated with CsA. The effects of an angiotensin-converting enzyme inhibitor in treated rats showed that BMP-7 expression was partially restored and that the anti-fibrotic effect of inhibitors of angiotensin-converting enzyme is supported by this data. The authors conclude that

BMP-7 may have implications CsA toxicity prevention (Tuglular, Gogas Yavuz et al.

2004).

With regards to renal fibrosis, Saggi et al. (2004) observed that before the onset of fibrosis in rat kidney, CsA increases mRNA levels of two protooncogenes, c-fos and c- jun and TGF-β. The authors note that this supports the idea that protooncogenes may be connected with CsA nephrotoxicity (Saggi, Andoh et al. 2004).

CsA has also been studied in connection with cell death. Ciesielski et al. (1997) examined the effects of CsA on tumor necrosis factor alpha (TNF-α). The protein was examined because of its connection to cardiac allograft rejection. Levels of TNF-α were evaluated rats undergoing cardiac allografts after treatment with CsA. In rats treated with

CsA, TNF-α levels were lower than in rats receiving no preventative treatment linking

CsA with the prevention of cell death in addition to inhibition of T cell proliferation

(Ciesielski, Mei et al. 1997).

Contrastly, Pyrzynska et al. (2002) have claimed that CsA causes apoptosis via the p53 tumor suppressor in rat glioma cells. The authors reported increases in p53 nuclear accumulation and the activation of genes dependent on p53 activation. They also reported that p53 knockout mice show a greater opposition to apoptosis caused by CsA.

12 The authors determined that CsA induces apoptosis using a p53 pathway (Pyrzynska,

Serrano et al. 2002).

These results help illustrate the vast genetic changes that occur upon treatment with

CsA over a broad range of subjects. The large variation in response of organisms and patients to this drug also explains many conflicting reports in the literature. It is clear, however, that CsA and the corresponding elements of the calcineurin pathway are involved in ECM and cell cycle regulation in a multitude of tissues and that there are implications for changes in gene expression in many tissues, such as the gingiva.

13 Adapted from www.world-of-fungi.org Harriet Upton

Figure 2. The molecular structure of cyclosporine A. The molecule is a neutral, cyclic, hydrophobic, endecapeptide comprised of eleven amino acids.

14 Ca2+ T Cell

CsA Ca2+ Calm

+

CsA NF-AT P + CaN CsA -

CpN P NF-AT

+

Nucleus IL-2

Modified from “Mechanism of Action of Cyclosporine or Tacrolimus (FK506)” Expert Reviews in Molecular Medicine™ 2000 Cambridge University Press

Figure 3. Proposed mechanism of action of Cyclosporine A. CsA binds to cyclophilin to inhibit phosphatase activity of calcineurin, preventing NF-AT (nuclear factor of activated T-cell) from traveling to the nucleus and activating transcription of IL-2.

15 1.4 Microarray Analysis

With the advent of the discovery of the sequence of the human genome, many

researchers have looked to microarray analysis to examine wide changes in gene

expression (Ewis, Zhelev et al. 2005). Microarray technology can be used to examine a

broad range of genes in multiple gene pathways or it can be used to study a small range

of genes, examining individual pathways (Russo, Zegar et al. 2003). There are two types

of arrays typically used, cDNA gene arrays and oligonucleotide gene arrays. The arrays

work through hybridization of an mRNA derived cDNA probe onto gene products from

PCR (polymerase chain reaction) or oligonucleotides. These products correspond to

specific sequences within specific genes of interest (Schena, Shalon et al. 1995).

Through this technology, scientists can examine thousands of genes at a time in

association with many different experimental conditions and tissues. It also is possible to use this technology to evaluate gene expression in certain signaling pathways and to identify these pathways in addition to genes of interest (Swamy, Tan et al. 2004). There are, however, limitations to microarrays. A gene array is not an exact assessment of gene expression (Welford, Gregg et al. 1998). Gene changes of interest must be verified by other experimental procedures such as reverse transcription PCR (RT-PCR), quantitative

real-time PCR (Q-PCR), Western Blot, and similar methods.

Matthew et al. (2003) used micrarray technology to examine gene changes associated

with CsA treatment for the protection of lungs after hyperoxic injury in mice. They

report that mRNA levels change in several hyperoxic injury associated genes such as SP-

C (surfactant protein C) and cyclins B1 and G. They report that mRNA levels of these

decrease after treatments (Matthew, Kutcher et al. 2003).

16 Recently, scientists have used new microarray technology to examine gene expression in gingival fibroblasts (Abiko, Hiratsuka et al. 2004). A sample of a microarray membrane can be seen in figure 5. Wang et al. (2003) used microarray analysis to examine changes in gingival fibroblasts from both healthy tissue and inflammatory tissue associated with periodontitis. Because gingival fibroblasts secrete cytokines associated with the inflammatory response and immunoregulation, these molecules were a good subject for examining expression changes among inflamed tissue

(Wang and Ohura 2002). In their study, these authors examined changes in inflammatory cytokines. The bacteria Porphyromonas gingivalis, a bacteria frequently observed in periodontitis, was used to stimulate gingival fibroblast immune responses, specifically the lipopolysaccharide of P. gingivalis. FACS then was used to analyze microarray results to show secretion of cytokines interleukin 1 alpha (IL-1α), interleukin 1 beta (IL-1β), interleukin 6 (ΙL-6), interleukin 8 (IL-8), and tumor necrosis factor alpha (TNF-α), as well as cyclin 14 (CD14), toll-like receptor 2 (TLR2), and toll-like receptor 4 (TLR4) increase in lipopolysaccharide stimulated gingival fibroblasts versus healthy gingival fibroblasts (Wang, Ohura et al. 2003).

Han et al. used microarray analysis to visualize the differences in gene expression between cultured human periodontal ligament fibroblasts and human gingival fibroblasts and grouped them in terms of their biological significance. Verification was performed using Northern blots and microarray analysis software.

17

Adapted from GEArray™ Q and S Series User Manual www.superarray.com

Figure 4. Sample protocol of GEArray™ Q Series Microarray.

18

Adapted from GEArray™ Q and S Series User Manual www.superarray.com

Figure 5. Sample of microarray after hybridization with biotinylated cDNA probe and chemilumenescence.

19 HYPOTHESES: CsA causes changes in gene expression associated with the proliferation and/or growth of responder gingival fibroblasts cultured in vitro.

Alternative hypotheses:

A. CsA causes changes in genes associated with the proliferation of responder

gingival fibroblasts in vitro (hyperplastic response).

B. CsA causes changes in genes associated with the production of

extracellular matrix of responder gingival fibroblasts in vitro (hypertrophic

response).

C. CsA causes changes in genes involved in both proliferative and

hypertrophic responses.

20

Chapter 2

MATERIALS AND METHODS

2.1 Cell line and culture

Human gingival fibroblasts (HGFs) were taken from primary explants of human gingiva from a single patient who was a known responder to CsA as described by Ta et al. (Ta, Baraniak et al. 2002). All usage of HGFs was limited to passages 4 and 5.

HGFs were maintained in MEM (GIBCO Cell Culture, Invitrogen Corporation, Carlsbad,

California, USA) with 10% (v/v) FBS and 1% (v/v) penicillin/streptomycin (P/S)

(GIBCO, 10000 units/ml penicillin and 10000 µg/ml streptomycin) before treatment, then to 1% FBS and 1% P/S upon treatment with CsA or vehicle only. Cultures were grown in T75 flasks for microarray and Real-Time PCR analysis, six well plates for Western blot, and 24 well plates for cell staining analysis (Corning, Corning, NY) to approximately 90-95% confluence when appropriate treatments with either 95% ethanol vehicle only or final concentration of 10µg/ml CsA in 95% (v/v) ethanol in media were conducted as described by Morton et al. (Morton and Dongari-Bagtzoglou 1999). Total

RNA was collected from T75 flasks at 1 and 6 days, while whole cell lysates were collected from 6 well plates at days 2, 4, and 6. HGFs cultured on glass coverslips for cell staining were grown in 24 well plates and collected at days 2, 4, and 6 as well.

Media was not changed between the beginning and end of treatments.

21 2.2 RNA extraction and Northern Blot

Total RNA was extracted by using the QIAGEN RNeasy Mini Kit (QIAGEN Inc,

Valencia, CA) following the manufacturer’s instructions. Relative amounts of mRNA

were established through measuring the absorbance of each sample at 260nm using a

BioRand SmartSpec 3000 spectrophotometer (BioRand lab, Hercules, CA, USA). RNA

condition was determined by running 1 µg of each sample through denaturing gel

electrophoresis and staining with ethidium bromide. Intensities of the 18S and 28S

ribosomal bands were examined for quality using a Multimage™ Light Cabinet (Alpha

Innotech Corp., San Leandro, CA, USA). A Northern blot was conducted and probed for

GAPDH to ensure mRNA quality (Maxim Biotech, Inc., San Francisco, CA, USA) using

the NorthernMax™-Gly protocol as per the manufacturer’s instructions (Ambion, Inc.,

Austin, TX, USA).

2.3 Microarray Analysis

cDNA microarrays were supplied and performed as per the manufacturer’s instructions (Superarray Bioscience Corp., Frederick, MD, USA). Two 96 gene microarrays were used: GEArray Q Series Human Extracellular Matrix & Adhesion

Molecules Gene Array and GEArray Q Series Human MAP Kinase Signaling Pathways

Gene Array. Four independent RNA samples at one and six days corresponding to each treatment were tested. The GEArray™ Q and S series assay protocol was followed and

supplied by Superarray.

22 2.4 Microarray Statistics

Images of the microarrays were captured using a Multimage™ Light Cabinet (Alpha

Innotech). Microarrays were then analyzed using Adobe Photoshop version 7.0 (Adobe

Systems Incorporated, San Jose, CA, USA) for inverting the image from black spots to

white for compatibility with the ScanAlyze program (Superarray). The ScanAlyze

program (Superarray) was used to quantify the intensities of the spots on the microarray.

Data was then imported to Microsoft® Excel (Microsoft Corp., Redmond, WA, USA) for interpretation by GEArray Analyzer v1.3 (Superarray). The intensities of the genes were normalized to that of β-actin, a housekeeping gene, in order to obtain the numerical values of the individual gene intensities.

2.5 Reverse-transcript PCR (RT-PCR) and Real-Time PCR

Reverse transcription polymerase chain reaction (RT-PCR) involves the combining of

template RNA, reverse transcriptase, dNTPs, and proper buffers at 37°C to build a first

strand cDNA template for further PCR. The cDNA is then used with appropriate primers

to amplify the sequence. RNA must be intact to ensure reaction effectiveness

(QIAGEN).

Q-PCR involves the quantification of RNA transcripts. Q-PCR also uses template

RNA to build cDNA followed by PCR amplification of the cDNA template. However,

fluorescence is used to measure the amount of cDNA during the exponential phase of the

PCR reaction. Fluorescence is generated by fluorophores that are integrated into the PCR

product. The level of fluorescence is a measurement of the amount of RNA transcripts.

When this crosses a certain threshold, the amount of RNA at a specific number of cycles

23 is determined and can be used to compare relative levels of RNA among different

samples in the same reaction (QIAGEN). Typically, quantification involves normalizing

to levels of a normally expressed gene such as β-Actin. Levels are analyzed by using the

InStat statistical analysis program by GraphPad which uses One-way Analysis of

Variance (ANOVA) followed by Tukey-Kramer Multiple Comparisons Test to indicate

statistical significance.

RNA was extracted from HGF cultures at 1 and 6 days treated with either 95%

ethanol vehicle or 10µg/ml CsA in 95% ethanol in media. 2µg of total RNA of each

sample was used for the reverse transcription reaction to make first strand cDNA in 20 µl

reactions using Omniscript RT Kit (QIAGEN). Real-Time PCR Primers for Collagen

1α1 (Col1α1) and Fibronectin (FN-1) were designed using the assistance of SDSC

Biology Workbench Primer3 program http://workbench.sdsc.edu/. The primers used in the PCR and Real-Time PCR are as follows and were made by Sigma Genosys (Sigma,

The Woodlands, TX, USA).

Fibronectin forward – 5’- CGGTCAGTCGGTATCCTGTT-3’,

Fibronectin reverse – 5’- GATGCTCCCACTAACCTCCA-3’;

Collagen 1 α1 forward -5’- AATCCATCGGTCATGCTCTC-3’,

Collagen 1 α1 reverse – 5’-GGCCCAGAAGAACTGGTACA-3’

24 5 µl of the first strand cDNA was used for the PCR template. The optimal annealing

temperature (Ta) for each primer set was determined through a temperature gradient PCR

(QIAGEN Taq PCR kit, Valencia, CA). Temperatures ranged from 8ºC above and below

the melting temperature (Tm) of each primer set. The optimal temperatures were

determined by Touchgene Gradient instrument (Techne Inc., Princeton, NJ, USA). The

program was set as follows: denature at 95ºC, 10 minutes; 35 cycles of denature at 95ºC,

45 seconds; anneal at gradient temperatures 1 min; and extension at 72ºC, 30 seconds

followed by a final extension at 72ºC for 7 minutes. 2.0% agarose (GIBCO)/1.0% TAE

(Tris-acetate-EDTA) gels were used to find the optimal annealing temperature and

product size by examining the band intensities using a Multimage™ Light Cabinet

(Alpha Innotech).

Real-time PCR reactions were conducted using the optimal annealing temperatures

found for each primer set to compare the relative changes in gene expression levels of the

four treatments of HGFs. The QIAGEN Quanti Tect SYBR® Green PCR Kit (QIAGEN) and the BioRad iCycler iQ Real-time detection system (BioRad lab, Hercules, California,

USA) were used as described by the menu for Q-PCR (quantitative PCR).

2.6 Antibodies

Cyclin D1 (CD1) antibody is from BD Pharmingen™ (BD Pharmingen, cat. #

554180, San Jose, CA, USA). Early Growth Response-1 (EGR-1) antibody is from Santa

Cruz Biotechnology, Inc. (Santa Cruz Biotechnology, Inc., cat. #sc-110, Santa Cruz, CA,

USA). Carcinoembryonic Antigen (CEACAM5) antibody is from Abcam Inc. (Abcam

Inc., cat. # ab4451, Cambridge, MA, USA).

25 2.7 Western Blots

Western Blot analysis involves the separation of total protein using SDS (sodium

dodecyl (lauryl) sulfate)-polyacrylamide gel electrophoresis. SDS is an anionic detergent

that binds to, linearizes, and gives protein an overall negative charge for easier travel

through the gel as they flow towards the positive cathode. This ensures proteins are separated based on their size only. SDS binds to proteins in proportion to the number of amino acids that make up the protein. Once the gel is run, proteins are transferred to a nitrocellulose membrane. After transfer, the membrane must be placed in a blocking

solution, typically 5% (w/v) nonfat dry milk, to prevent inspecific binding of the primary

antibodies. The membrane is then blotted with a primary antibody in block for the

protein of interest. An enzyme conjugated secondary antibody then is added that will

recognize the primary antibody. The conjugated enzyme allows visualization of the

bands through chemilumenescent fluorescence of the enzyme and examination of the blot

on film (Sambrook 2001).

At 95%-100% confluence, days one and six cells were washed 2X with 1X Phosphate

Buffered Saline (PBS) (Fisherbiotech, Fair Lawn, NJ, USA) for 1 minute. Sample

Extraction Buffer (SEB) (500 µl) containing 0.05 M Tris pH 7.0, 8M Urea, 1% (v/v)

SDS, 0.01% (v/v) PMSF, 1% (v/v) β-Mercaptoethanol, was used to collect protein for

CEACAM5 Western blot. Protein was concentrated using TCA (trichloroacetic acid)

precipitation where needed. For Western blots on CD-1 and EGR-1, 500 µl of lysis

buffer containing 20mM Na2HPO4 pH 7.4, 150 mM NaCl, 0.3% (v/v) Triton x-100, 2

mM EDTA, 0.01% (v/v) PMSF was used for protein extraction. 10% Protease Inhibitor

Cocktail (PIC) (Roche, Indianapolis, IN, USA) was added fresh, post extraction. The

26 protein concentrations were determined using the method described by Lowry et al. for

CEACAM5 protein in SEB (sample extraction buffer) while the BCA Protein Assay

Reagent Kit (Pierce, Rockford, IL, USA) was used for protein collected using lysis buffer involved in CD-1 and EGR-1 analysis (Lowry, Rosebrough et al. 1951).

Proteins were separated on 10% SDS-PAGE gels (NuPAGE Bis-Tris Gel, Invitrogen-

Novex). 20µg of protein were loaded in each well. Electrophoresis was continued for

1.5 hours at 100v and proteins were transferred electrophoretically to Protran® nitrocellulose membrane (Schlescher and Schuell, Bioscience Inc., Keene, NH, USA).

Membranes were blocked in PBS containing 5% nonfat, dry milk (Nestle, Solon, OH,

USA) overnight at 4ºC. Primary antibodies were diluted in PBS-T (0.1% Tween-20

(FisherBiotech) in 1X PBS) 5% nonfat, dry milk and the membrane was incubated at 4ºC for 6 hours to overnight. Membranes then were washed 3X for 10 minutes in 25 ml PBS-

T and secondary antibodies, also in 5% nonfat dry milk, were added at a 1:200,000 dilution. For CD1 primary antibody, the secondary antibody used was peroxidase- conjugated sheep anti-mouse IgG (Jackson Immunoresearch Laboratories). For EGR-1 primary antibody, the secondary antibody was peroxidase conjugated goat anti-rabbit IgG

(Sigma). Secondary antibodies were incubated at room temperature for two hours and then washed 3X with PBS. Membranes then were placed in six ml of SuperSignal™

West Dura Extended Duration Substrate for 5 minutes and visualized using BioMax

Light Film (Eastman Kodak Company, New Haven, CT, USA). Films were developed on a M35A X-OMAT Processor (Kodak). Film images were captured using a

Multimage™ Light Cabinet (Alpha Innotech).

27 2.8 Cell Staining

A 0.5% (w/v) Crystal Violet solution (Sigma) was used to stain gingival fibroblasts in

triplicate in 6 well plates. After 1 and 6 day treatments with vehicle or CsA, cells were

stained to examine cell morphology. Crystal Violet was diluted in water and after rinsing

of the cells 3X with 1X PBS, 0.5 ml was placed in each well. Excess stain was removed

after five minutes and cells then were washed 3X with 1X PBS. Fibroblasts then were

visualized using Nikon Diaphot Microscope.

To examine cell viability of cells treated 2, 4, and 6 days, 0.4% Trypan Blue

(GIBCO) was diluted to 0.2% using 1x PBS supplemented with CaCl and MgCl. One ml

was used for each well and incubated at room temperature for 5 minutes. Cover slips

then were washed 3X in PBS w/CaCl and MgCl. Cover slips then were placed in one ml

PBS with 1 µl SYTO13® (Invitrogen) green fluorescent nucleic acid stain was added for a 1:1000 dilution. Trypan Blue cells were visualized using a Nikon Diaphot Microscope.

Day 2 cells were stained with SYTO13® only, while cells cultured for four or six days were stained with both SYTO13® and Alexa Flur® 633 phalloidin (Invitrogen). Cells in

24 well plates were fixed with 4% (w/v) paraformaldehyde for 10 minutes. Following

fixation, excess aldehyde was quenched with 50 mM NH4Cl for 15 minutes at room

temperature. Fixed cells were permeabilized with 0.2% (v/v) Triton X-100 in PBS for 5

minutes at room temperature and then blocked for 45 minutes in 3% (w/v) BSA. Alexa

Flur® 633 phalloidin was added at 1:100 dilution in PBS and incubated for 40 minutes at

37ºC. Cells then were washed 3X in PBS after which, To-Pro®-3 iodide solution

(Invitrogen) diluted 1:5000 in PBS was added and incubated for 10 minutes at room

28 temperature. Cells then were washed 3X in PBS and observed on a Zeiss LSM 510 VIS attached to an Axiovert 100M confocal microscope.

29

Chapter 3

RESULTS

3.1 RNA Gel Electrophoresis and Northern Blot

As seen in figure 1, 28S and 18S bands were clearly visible among all gingival fibroblast mRNA samples with little or no smearing indicating that the quality of mRNA was good and could be used for microarray analysis. Northern blot probing for GAPDH revealed similar levels in all four samples. GAPDH was used as a load control to insure equal amounts of RNA were loaded onto the gel. GAPDH is a housekeeping gene frequently used as an indicator of equal levels of RNA in Northern Blot analysis due to its relative expression and abundance in many cell types.

30 1D Veh. 1D CsA 6D Veh. 6D CsA

28S

18S

GAPDH

Figure 6. RNA gel analysis revealed the quality of rRNA through imaging of solid 28S and 18S ribosomal bands in both one day and six day control and treated gingival fibroblasts. Northern Blot analysis shows relative levels of GAPDH are constant in all samples indicating that there are equal amounts of mRNA in the four lanes. One microgram of RNA was loaded in each lane.

31 3.2 Microarray Results

The microarray hypbridization was performed as described by the Superarray

protocol and the resulting images are shown in Figure 2. Based on the magnitude of

expression on the two microarrays both through computer analysis and by visual

examination, as well as their physiological significance in the gingiva and tooth

microenvironment, genes were chosen for evaluation. Genes were normalized to β-actin

and those genes with the greatest changes in expression were identified as potential genes

for validation. The five genes chosen for validation were Carcinoembryonic Antigen-

Related Cell Adhesion Molecule 5 (CEACAM5), Early Growth Response 1 (EGR-1),

Cyclin D1 (CD1), Fibronectin (FN-1), and Collagen 1 α1 (Col1α1) and are shown in

Table 1. Other gene changes are shown in tables 2 and 3 in the appendix.

32 Extracellular Matrix and Cell Adhesion Molecules Gene Array

6D Veh 6D CsA

Figure 7. The two microarray images display the intensities of the 96 genes plus housekeeping genes on the Extracellular Matrix and Cell Adhesion Molecules Gene Array after six day treatments with either vehicle or Cyclosporine A. Genes chosen for validation from this array were fibronectin (FN-1, left circle) and CarcinoEmbryonic Antigen (CEA, right circle) and are circled. The legend for all extracelluar matrix and cell adhesion molecule genes can be found in Table 4 located in the appendix.

33 Human MAP Kinase Signaling Pathway Gene Array

6D Veh 6D CsA

Figure 8. The two microarray images display the intensities of the 96 genes plus housekeeping genes on the Human MAP Kinase Signaling Pathway Gene Array after six day treatments with either vehicle or Cyclosporine A. Genes chosen for validation from this array were cyclin D1 (CD1, top circle), Collagen 1 alpha 1 (Col1α1, middle circle), Early Growth Response 1 (EGR-1, bottom circle) and are circled above. The legend for all human MAP kinase signaling genes can be found in Table 5 located in the appendix. Genes were chosen by intensity and relevance to gingival microenvironment.

34 Table 1. Relative gene intensities as determined by the GEArray Analyzer v1.3 program (Superarray) used to quantify the intensities of the spots on each microarray. Fold change compares day six vehicle to day six CsA treatment. Day 1 vehicle shows initial intensities of genes at the start of the treatments. Green highlights indicate a decrease in transcript expression while red indicates an increase in transcript expression.

Relative Intensities of Array Genes Gene Day 6 Veh Day 6 CsA Day 1 Veh Fold Change

COL1A1 1.58 0.53 0.62 2.99 Egr-1 0.26 0.30 0.19 1.13 fibronectin 2.51 4.67 1.27 1.86 CEA 1.2 0.52 1.23 2.31 cyclin D1 0.22 0.49 0.68 2.18

35 3.3 Real-Time PCR

Real-Time PCR analysis shows the results of the two genes chosen for verification

from the ECM microarray. These genes were chosen for both level of change seen on the

microarray and potential contribution to hyperplastic and hypertrophic growth with

regard to their role in CsA-induced gingival overgrowth. The significance of the genes

was

The primers used for Real-Time or quantitative PCR (Q-PCR) had to be confirmed

for use via a gradient Q-PCR. There are several factors that determine the primers’

annealing temperatures (Ta). Internal properties such as primer sequence length,

secondary structure and G/C content all determine what the Ta will be. The gradients

were designed with the knowledge that the Ta will be approximately 5°C lower than the

melting temperature (Tm) which has been calculated by Sigma Genosys. To show the

result of the PCR gradients, products were electrophoresed on 2% agarose gels and the

bands were visualized using Multimage™ Light Cabinet (Alpha Innotech) to illuminate

the ethidium bromide in the cDNA products. Through visualization, product size in base

pairs (bp) can be determined and matched with the known size of the particular target sequence.

Initial observations of microarray analysis showed a decrease in Col1α1 expression in gingival fibroblasts after six days of treatment with CsA. After using Q-PCR to analyze

Col1α1 levels, it was observed that levels appear fairly similar on the first three treatments, but then dropped in the six day CsA sample as seen in Figure 5. These levels were compared using the InStat statistical analysis program by GraphPad. This program uses One-way Analysis of Variance (ANOVA) followed by Tukey-Kramer Multiple

36 Comparisons Test. Comparisons show a *** P < 0.001 value for six day vehicle control

versus six day CsA treatment indicating a statistical significance. Samples were

normalized to β-actin. Analysis of the GEArray™ Q Series Human Extracellular Matrix and Adhesion Molecules Gene Array by eye revealed a very high level of expression of

FN-1 transcripts. Q-PCR analysis followed by InStat analysis showed no significant change in FN-1 expression. Results of Q-PCR on FN-1 are illustrated in Figure 6.

37 Relative Col1α1 Levels After Cyclosporine A Treatment of Gingival Fibroblasts

1.00 *** n i t d c e A

- 0.75 hol a t s e e B / 1 Cycl

d 0.50 α Thr 1 e l l hol c s y Co e

C 0.25 Thr

0.00 h A Veh y Ve y CsA y y Cs a a D D 1 Da 1 Da 6 6

Figure 9. Q-PCR of Col1α1 shows a reduction in expression after six days of treatment with CsA in gingival fibroblasts in vitro. Bars were generated by dividing Col1α1 threshold cycle number by β-actin threshold cycle number of the listed sample. Larger bars represent the longer time needed for RNA levels to reach cycle threshold. A P < 0.001 value indicates statistical significance between 6 day control and 6 day CsA treatments. The ∆∆ct method for calculating cycle threshold fold difference was also done and is shown in figure 14 located in the appendix.

38 Relative Fibronectin Levels After Cyclosporine A Treatment of Gingival Fibroblasts

1.00 n i t e l c d l c A o y

- 0.75 a t C e esh n i r B t / h c

d 0.50 e e T on hol cl s y br e

C 0.25 Fi Thr

0.00 h A Veh y Ve y CsA y y Cs a a D D 1 Da 1 Da 6 6

Figure 10. Q-PCR of FN-1 shows that there is no change in gene expression in cultured gingival fibroblasts treated with CsA in vitro. Bars were generated by dividing threshold cycle number of fibronectin by the threshold cycle number of β- actin of the listed samples. Larger bars represent the longer time needed for RNA levels to reach cycle threshold. InStat analysis revealed no significant change in the expression of fibronectin indicating levels remain constant among the four treatments.

39 3.4 Western Blots

Western blot analysis was used to compare expression of the genes EGR-1, CD-1, and CEA at the protein level. Western blots for EGR-1 and CD1 were repeated three times with mouse 3T3 osteoblast protein and LNCaP protein serving as controls respectively due to the genes known expression in the control cell types. The Western blot for CEA was repeated twice with LNCaP protein serving as a control. Analysis revealed that there was a loss of expression in EGR-1 after six days of treatment with

CsA. CD1 levels remained relatively unchanged with some loss of expression after one day of treatment, but returning to similar levels after six days of treatment. CEA levels remained at similar levels through all four days of treatment.

40 A) 3T3 1D Veh 1D CsA 6D Veh 6D CsA

EGR-1 80 kDa

β-Actin 42 kDa

B) LNCaP 1D Veh 1D CsA 6D Veh 6D CsA

CD1 36 kDa

1D Veh 1D CsA 6D Veh 6D CsA

CEA 180 kDa C)

Β-Actin 42 kDa

Figure 11. A) Western Blot analysis shows a reduction of expression in EGR-1 in gingival fibroblasts treated 6 days with CsA in vitro. EGR-1 protein levels appear lower in both one day treated and six day treated samples. 3T3 mouse osteoblast protein was used as a positive control. Bands in human samples appear higher due to an additional 10 amino acids in the protein sequence. Comparison with β-actin levels reveal changes seen are comparable. B) Western Blot analysis shows there is a decrease initially in CD1 at day 1, but no change in CD1 after 6 days in gingival fibroblasts treated with CsA in vitro. LNCaP protein served as a positive control. C) Western Blot analysis shows the presence of CEA in both treated and control gingival fibroblasts. Relative β-actin levels show CEA levels appear unchanged among all four treatments.

41 3.5 Cell Staining

Trypan blue stain was used to determine cell viability after treatment with vehicle only or CsA. Trypan Blue is a cellular dye that will stain dead or dying cells. If the cell are viable, Trypan Blue will be expelled from the cell. As shown in figure 8, gingival fibroblasts on all three days and under both treatments did not contain any blue within.

This indicates that the cells are not losing viability after treatments of days two, four, and six. Cells express expected morphology and adhesion with associated treatments.

42 D2 Veh D2 CsA

D4 Veh D4 CsA

D6 Veh D6 CsA

Figure 12. Trypan Blue stain reveals all cells lack dye and are viable in both vehicle and CsA treatments of cultured gingival fibroblasts in vitro.

43 D1 Veh D1 CsA

D6 Veh D6 CsA

Figure 13. Crystal Violet staining shows treatments of 1 day vehicle, 6 day vehicle, and 1 day CsA all have normal elongated, spindle-like morphology while 6 day CsA treatment produce distinct morphological changes. Fibroblasts lose normal spindle structure, have wide gaps between cells, and lack normal fibrous meshwork.

44 D2 Veh D2 CsA

D4 Veh D4 CsA

D6 Veh D6 CsA

Figure 14. Staining of HGFs with Syto13 and phalloidin reveal no nuclear alterations. Nuclei in the day two treatments appear round and intact with no blebbing or irregular shape under 10X magnification with Syto13 staining only. Under 20X magnification, Syto13 and phalloidin staining reveal slight structural changes occur after four days of treatment with CsA. Yellow colored nuclei is a result of blending of the Syto13 green and phalloidin red dyes with normal, round nuclei clearly visible. An even greater alteration in HGF morphology appears after six days of treatment with CsA. Cells lose their fibrous, netlike structure and gain greater space between cells, but nuclei continue to maintain normal appearance.

45

Chapter 4

Discussion and Conclusion

4.1 Discussion

Despite the observation of gingival overgrowth with treatment of many

immunosuppressant drugs over the past 30 years, the cause of overgrowth remains

unsolved. To date, there have been many studies examining potential sources.

Researchers have examined various gene products for potential leads and discoveries.

Controversy remains over not only the source of gingival overgrowth, but also the type of

growth as well. As mentioned previously, gingival overgrowth has been referred to as

both hyperplastic growth and hypertrophic growth, and it remains unclear if overgrowth

occurs because of an increase in the number of gingival fibroblasts, the amount of

secretion by gingival fibroblasts, or a combination of both (Bonnaure-Mallet, Tricot-

Doleux et al. 1995), (James, Irwin et al. 1998), (Wondimu, Reinholt et al. 1995),

(Mariani, Calastrini et al. 1996).

Koh et al. (2004) conducted a study examining angiogenic genes. Through their

research, they discovered that thrombospondin 2 (TSP2), a gene responsible for the inhibition of angiogenesis, decreased over time in both rat and human gingival fibroblasts and concluded that the decrease in the expression of this gene is what leads to increased vascularization commonly seen in CsA-induced gingival overgrowth (Koh, Kim et al.

2004). This study correlates with the extracellular matrix gene array results shown in my

46 study in that TSP2 mRNA transcript levels, although not validated, decreased as well.

Koh et al. saw a dose dependant decrease with the greatest dose at 1000 ng/ml creating a

42% decrease in mRNA expression and a nearly five fold decrease in TSP2 protein

expression. In my study, HGFs were treated with 10µg/ml and the microarray analysis

reveals a two and a half fold decrease in TSP2 gene expression. Together, these

combined results support the idea that gingival overgrowth is not necessarily a result of hyperplastic growth by gingival fibroblasts.

Another ECM molecule at the center of the CsA-induced gingival overgrowth controversy is collagen type I. The Q-PCR data displayed in this study shows that

Col1α1 decreased significantly upon treatment with CsA. In addition, Tissue Inhibitor of

Metalloproteinases 1, 2, and 3 (TIMP-1, TIMP-2, and TIMP-3) mRNA transcripts all decreased according to the extracellular matrix gene array without validation. These genes are responsible for inhibition of matrix metalloproteinases which break down and degrade the extracellular matrix. Without inhibition, MMPs are free to breakdown more

ECM and may be the source of lower collagen levels in the CsA treated gingival

fibroblasts in this study. Conflicting results have been given in relation to this premise.

Gagliano et al. found that collagen levels increase in gingival fibroblasts upon treatment with CsA. They pointed to a decrease in MMP levels as the source of the accumulation as do Hyland et al. (Gagliano, Moscheni et al. 2004), (Hyland, Traynor et al. 2003). In our study, it is not clear what happens to MMP mRNA transcript levels in my ECM array due to the negative values given after normalization to β-actin, but there is a decrease in collagen mRNA. A possible explanation may be that even with lower expression of collagen mRNA, there remains enough production of collagen for a decrease in MMP

47 expression mRNA to cause overgrowth. Wondimu et al. examined biopsies from thirteen

kidney transplant patients to examine tissue components. The authors findings support

the information displayed here in that there is a decrease in collagenous matrix

(Wondimu, Reinholt et al. 1995). In addition, Bonnaure-Mallet et al. report that after

histological examination, comparisons between CsA-induced overgrowth and normal

gingival biopsies reveal there is no significant change in the area occupied by fibroblasts.

The authors also report that healthy gingival contains more total collagen, but less type

IV collagen than CsA-induced overgrowth gingival (Bonnaure-Mallet, Tricot-Doleux et

al. 1995). The findings presented in my study agree with a loss of collagen type I alpha I,

however microarray analysis showed a decrease in type IV collagen in this study.

Additionally, an investigation by James et al. reports that collagen levels are much lower in gingival fibroblasts treated with CsA and that the presence of TGFβ with CsA reduces protein and collagen accumulation more than TGFβ only (James, Irwin et al. 1998).

Furthermore, Kataoka et al. describe a decrease in integrin alpha 2, a collagen receptor, on rat gingival fibroblasts treated with CsA, suggesting a decrease in collagen phagocytosis by gingival fibroblasts (Kataoka, Seto et al. 2003). This information agrees more with my study due to the findings that MMP levels decrease. A recent study by

Brook et al. (2005) examined the effects of an antifibrotic agent on the fibrotic effects of

CsA and tacrolimus (FK-506) in rats. In the study, the authors saw that CsA reduces the mRNA levels of MMP2 while increasing the mRNA levels of TIMP-1 and collagen III.

In my study MMP2 transcript levels appear to decrease, but this information has not been validated. However, TIMP-1 transcript levels appear to increase. The difference may be due to the difference in species used (Brook, Waller et al. 2005). In addition, integrin

48 alpha 2 levels, although initially low, decreased in my studies as well. This may be a

possible explanation of the Col1α1 mRNA decrease in our array.

An interest in collagen led me to investigae FN-1 because of its necessity for the

binding of collagen. Fibronectin is a large protein of 440 kDa found in connective tissue,

basement membranes, and plasma and is partially responsible for proper cytoskeletal

structure (McDonagh 1981). My results are similar to those found by Khanna et al. In

their study, FN-1 levels remained constant in renal biopsies from patients undergoing

immunosuppressive therapy with CsA (Khanna, Plummer et al. 2002). Also, in the same

study by Bonnaure-Mallet et al., fibronectin levels remain unchanged after histological

examination of gingival biopsies (Bonnaure-Mallet, Tricot-Doleux et al. 1995). It

remains that FN-1 levels are constant and are not responsible for the decrease in collagen

commonly seen in the literature.

A recent publication by Gagliano et al. examined changes in secreted protein, acidic, cysteine-rich (SPARC) mRNA expression in HGFs treated with CsA. The results agree with what has been observed through my microarray analysis. The authors see an increase in mRNA expression after 72 hours of treatment with CsA (Gagliano, Moscheni et al. 2005). The information presented in my study shows that SPARC levels increase after six days of treatment with CsA as well. These similar results help to validate the results presented in the ECM microarray.

Western blot analysis of EGR-1 showed a decrease in expression in gingival fibroblasts after treatment with CsA. EGR-1 is partially responsible for regulation of the cell cycle specifically between G0 and G1 phases (Forsdyke 1985). EGR-1 has also been implicated in T-cell activation (Skerka, Decker et al. 1995), (Decker, Nehmann et al.

49 2003). Decker et al. specifically implicated the importance of EGR-1 in IL-2 gene

transcription. The data displayed here showed that EGR-1 protein expression decreases

in cultured gingival fibroblasts after treatment with CsA. Thus, it seems probable that

CsA also inhibits EGR-1 in addition to inhibition of IL-2. A study by Alfonso-Jaume et

al. (2004) shows that there is an EGR-1 binding site on the promoter of MT1-MMP

(membrane –associated type 1 matrix metalloproteinase) and that this is partially

responsible for induction of MT1-MMP expression in glomerular mesangial cells. The

authors also point out that MT1-MMP is regulated by NF-AT. Based on these results,

there appears to be a connection between CsA treatment and MMP expression (Alfonso-

Jaume, Mahimkar et al. 2004). A decrease in EGR-1 protein expression supports the idea

that an increase in cell proliferation does not occur after treatment with CsA.

Furthermore, a proliferation assay done by a former post doctoral fellow in the Farach-

Carson lab, Dr. Van Ta, showed that after addition of CsA to cultured gingival fibroblasts

in vitro, there was no change in cell number (Ta 2004).

EGR-1 also has been implicated in many biological processes involving TGFβ, but

conflicting reports exist describing various conditions under which EGR-1 activates or

suppresses TGFβ expression (Lee, Cho et al. 2004); (Liu, Rangnekar et al. 1998); (Liu,

Yao et al. 1999). TGFβ has been implicated as a potential source of CsA-induced

gingival overgrowth, in that an increase in TGFβ expression results in overgrowth (Ellis,

Morgan et al. 2004); (Cotrim, de Andrade et al. 2002); (Hojo, Morimoto et al. 1999).

Because of the influence EGR-1 can have on TGFβ and TGFβ’s involvement in gingival overgrowth and ECM molecules, it may be that a decrease in EGR-1 by CsA causes and elevation in TGFβ levels contributing to CsA-induced gingival overgrowth.

50 Western blot analysis examing levels of CD1 revealed that there is no change in protein expression of CD1 despite an apparent increase in mRNA transcript expression.

CD1 is expressed during G1 phase of the cell cycle and is needed for progression through the G1 phase (Sherr 1993). Together, with the data collected by Ta et al., it seems that overgrowth is not a result of proliferation of gingival fibroblasts at least in the absence of gingival epithelial cells. However, other cyclins have not been examined in this study.

Parkar et al. saw an increase in cyclin B1 after CsA treatment of gingival fibroblasts, but also concludes that other cyclins such as A, D3, and E remain unchanged. CB1 is required for entry of cells into M phase of the cell cycle and they claim that it may be at least a potential source for gingival overgrowth. It could be argued that my examination of CD1 along with the data of Parkar et al., showing no change in cyclins A, D3, and E as well as a decrease in EGR-1, support the notion that the cell cycle is inhibited or unchanged more than upregulated (Parkar, Hussain et al. 2004).

Western analysis of CEA showed that the protein is located in gingival fibroblasts where it was previously believed to be absent. Although CEA protein levels are relatively constant, its presence in a known CsA responder may be significant. CEA has been used primarily as a metastasis marker (Oyama, Osaki et al. 2005). The glycoprotein has a molecular weight of 180 kDa and is found abundantly in the colon making it a good marker for colon cancer (Naghibalhossaini and Ebadi 2005), (Lin, Wang et al. 2005),

(Chan and Stanners 2004). Because of the protein’s wide use as a metastasis marker,

CEA may have implications in CsA-induced gingival overgrowth as well. CsA and CEA have already been implicated together in connection with antitumor antibody therapy

(Ledermann, Begent et al. 1988). It’s presence in a known responder patient may offer a

51 way to predict if future patients are susceptible to overgrowth, however more evidence is

required, specifically on non-responder patients, before this can be determined.

Cell staining reveals that there occur significant morphological changes in cultured gingival fibroblasts treated with CsA in vitro, but all HGFs remained viable and there were no nuclear alterations suggesting apoptosis. As seen in figures 8 through 10, all

HGFs remain viable after trypan blue staining, as can be seen by the lack of blue anywhere inside the HGFs. However, cells undergo drastic structural changes as can be seen through crystal violet staining and phalloidin staining. Crystal violet staining shows a significant change in morphology after treatment of HGFs with CsA. After six days of treatment with CsA, HGFs appear thinned and string-like with large gaps separating cells, possibly due to a loss of adhesion. There is an overall loss of normal fibrous, spindle-like structure as well as a loss of adhesion. The loss of adhesion was observed during washing of cells. HGFs treated with CsA were much more prone to detaching from plates and wells than HGFs treated with vehicle only.

Phalloidin staining supports the same observations. As seen in figure 13, staining reveals that after treatment with CsA, gingival fibroblasts lose normal elongated, spindle- like structure and attain a more string-like shape. Large gaps between cells appear possibly due to a loss of adhesion. It also was noted that while collecting protein, there was less in the day six CsA treated fibroblasts than the other three treatments. Because cells were washed prior to protein collection, a loss of adhesion could explain these observations. The cause of loss of normal spindle-like morphology remains unknown, however, but may be a result of a decrease in adhesion molecules.

52 4.2 Conclusions

The data shown in this study indicate that CsA-induced gingival overgrowth is not a result of increased proliferation of gingival fibroblasts and that extracellular matrix interactions are responsible for the overgrowth commonly seen. A decrease in collagen mRNA is observed as reported in studies mentioned previously, but MMPs, and collagen receptor integrin alpha 2 decreases may be a more important factor in terms of responsibilty for the accumulation of collagen typically observed in this condition.

The reduction of EGR-1 may have larger implications. As mentioned in the discussion, EGR-1 is a regulator of TGFβ and a reduction in EGR-1 may cause an increase in TGFβ expression contributing to CsA-induced gingival overgrowth. CD1 levels showed no change and lead to speculation that there is no significant alteration of the cell cycle to cause an elevation in proliferation of gingival fibroblasts treated with

CsA. CEA remains a protein of interest in its implications for predetermination of gingival overgrowth. Together, its presence in responder gingival fibroblasts, treated and untreated with CsA, and its known use as a cancer marker, make it a protein of great potential in determining predisposition of patients to CsA-induced gingival overgrowth.

It is important to note that microarray analysis is not a perfect system and that pathway specific arrays merely provide a useful starting point of an investigation. They are extremely useful in analyzing certain pathways and genes within those pathways, but results are not to be taken as definitive profiling of gene expression. Validation is crucial for proper microarray analysis. Normalization to different housekeeping genes may alter the expression seen in the other genes in the array causing one to overlook a gene that may change under different normalization methods. A gene that appears to decrease in

53 expression may not change or even increase in expression upon different validation methods as well. This is due to the fact that while an mRNA transcript may increase or decrease, this may not correlate to a direct increase or decrease in the translation of that mRNA into its respective protein. It is crucial, then, to find a pathway of interest and validate several genes to prove or disprove what is seen in the microarray.

54

Chapter 5

FUTURE WORK

The five genes analyzed (Col1α1, FN-1, EGR-1, CD1, and CEA) were chosen

because of their connection to known studies on the causes of CsA-induced gingival

overgrowth and their potential for new observations in the condition. There do remain,

however, many genes suitable for validation on these arrays.

As mentioned earlier, integrin α2, a receptor for collagen, decreases, although

slightly, in our extracellular matrix array. As mentioned in the discussion, it may prove

useful to see if this change does contribute to the change in collagen seen in CsA-induced

gingival overgrowth. Further validation of genes such as MMPs and TIMPs should be validated to further confirm collagen’s role in CsA-induced gingival overgrowth. Other genes of interest in table 2 in the appendix (noted by higher intensities), are genes also worth validating.

CEA protein expression should also be examined in a patient who is a known non- responder to CsA treatment. This could give insight to whether or not the presence of

CEA seen in this study is significant in marking the likelihood of CsA-induced gingival overgrowth or if it is present in many different patients whether they are responsive to

CsA treatment or not.

55 Also, TGFβ, while known to increase in previous studies mentioned, should be

explored to see if it follows popular trends. This could further validate our findings with

EGR-1 and its role in CsA-induced gingival overgrowth.

It also may prove useful to examine changes in gene expression in an angiogenesis gene array. It has been noted that in CsA-induced gingival overgrowth there is a marked increase in vascularization in many patients (Koh, Kim et al. 2004). Koh et al. reports a

decrease in TSP2 as our gene array results point out as well, indicating the angiogenic

role in the decrease of the gene. An angiogenesis array may add valuable information to

the cause of formation of gingival overgrowth attributed to CsA treatment.

Finally, the role of the epithelium and epithelium/stromal interactions should be

addressed in the future. The study conducted here only examines the effects of CsA on

human gingival fibroblasts, a stromal cell line. In the natural environment there are

constant paracrine interactions and signaling between the stromal and epithelial cell

layers. With this in mind, it may prove useful to look at changes in gene expression of

HGFs treated with CsA after co-culture with gingival epithelial cells. This may give a

more accurate representation of what is actually occurring in the gingiva

mircroenvironment and may offer better clues as to the cause of CsA-induced gingival

overgrowth.

56

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63

APPENDIX

Note: The following tables are normalized to β-actin because it was validated by Q-PCR as a reasonable standard that did not change at the transcript level in response to cyclosporine A over a six day period. It should be noted that the results of this analysis, including the identity of genes that change and the magnitude of the changes, differ when other normalization standards are chosen. For this reason, it is critically important to validate any gene expression changes noted below at the protein level in order to get a real notion of what may be happening to cellular function at the tissue level. This issue represents a limitation of cDNA pathway arrays for analysis of gene expression changes, and is not related to quality of cell culture nor of the mRNA isolates.

Table 2. List of extracellular matrix genes expressed differentially and organized according to “potential” and “fold change”. Genes that are candidates for validation are those listed as “potential” and have a fold change greater than 2. Fold change was calculated by dividing Day 6 CsA by Day 6 Veh or Day 6 Veh by Day 6 CsA with the higher number in the numerator and the lower in the denominator. The “Potential” was determined by the estimating error values of Day 6 Veh and Day 6 CsA intensities. Error values were determined to be +/- the lowest value for each column giving 0.2 for Day 6 Veh and 0.5 for Day 6 CsA. “Yes” = both numbers are higher than error value, “maybe” = one number is higher and one number is lower than error value, “no” = both numbers are lower than error value. HK denotes housekeeping genes. Fold change decreases in expression are represented by green while increases are represented by red. All genes were normalized to β-actin.

Day 1 Day 6 Fold Gene Veh Veh CsA Change Potential cathepsin D 0.31 0.43 1.83 4.26 yes Cathepsin B 0.59 0.67 2.21 3.30 yes TSP-2 0.16 1.07 0.43 2.49 yes CEA 1.23 1.2 0.52 2.31 yes CD44 0.71 0.72 1.55 2.15 yes TIMP1 0.24 0.97 1.92 1.98 yes caveolin 1 0.98 1.34 2.54 1.90 yes TIMP2 1.13 2.06 3.9 1.89 yes fibronectin-1 1.27 2.51 4.67 1.86 yes

64 Integrin beta 1 0.91 1.15 2.13 1.85 yes laminin B2 -0.01 1.18 2.02 1.71 yes PAI-1 0.37 0.48 0.79 1.65 yes TIMP3 0.38 0.85 1.31 1.54 yes gelatinase A 0.52 1.7 2.5 1.47 yes SPARC 1.20 1.77 2.39 1.35 yes TMPRSS4 0.25 0.23 0.21 1.10 yes fibrinogen beta 0.20 0.39 0.36 1.08 yes Heparanase 0.17 0.37 0.4 1.08 yes TSP-1 1.33 2.35 2.43 1.03 yes cathepsin L 0.05 0.14 0.46 3.29 no TSP-3 0.00 0.16 0.07 2.29 no maspin 0.06 0.13 0.07 1.86 no Meth 1 0.02 -0.03 -0.03 1.00 no gelatinase B -0.05 -0.18 -0.39 0.46 no collagenase-1 -0.05 -0.21 -0.49 0.43 no Integrin alpha L/LFA1a /(CD11A) -0.05 -0.21 -0.52 0.40 no Integrin beta 6 -0.05 -0.21 -0.52 0.40 no L-Selectin -0.05 -0.14 -0.36 0.39 no Integrin beta 5 -0.05 -0.18 -0.5 0.36 no P-selectin -0.05 -0.08 -0.24 0.33 no Integrin alpha M -0.05 -0.14 -0.49 0.29 no NCAM -0.05 -0.08 -0.28 0.29 no stromelysin 2 -0.05 -0.13 -0.51 0.25 no Integrin beta 7 -0.05 -0.12 -0.52 0.23 no neutrophil collagenase -0.05 -0.12 -0.53 0.23 no stromelysin-3 -0.05 -0.11 -0.51 0.22 no Integrin beta 4 -0.05 -0.11 -0.53 0.21 no MMP16 -0.05 -0.11 -0.53 0.21 no Integrin alpha 2b -0.04 -0.08 -0.4 0.20 no matrilysin, uterine -0.03 -0.1 -0.53 0.19 no MUC-18 -0.05 -0.1 -0.53 0.19 no contactin 1 0.01 -0.08 -0.47 0.17 no Meth 2 0.04 -0.08 -0.47 0.17 no Integrin alpha 9 -0.05 -0.09 -0.53 0.17 no macrophage elastase -0.05 -0.09 -0.53 0.17 no stromelysin-1 -0.02 -0.09 -0.53 0.17 no MMP26 0.24 -0.07 -0.53 0.13 no MMP24 -0.05 -0.06 -0.49 0.12 no collagenase-3 -0.05 -0.06 -0.53 0.11 no MMP15 -0.03 -0.06 -0.53 0.11 no Integrin beta 8 -0.05 -0.04 -0.51 0.08 no Integrin alpha 2/LFA1b -0.03 -0.04 -0.53 0.08 no Integrin alpha 8 -0.05 -0.04 -0.53 0.08 no MT-4-MMP -0.05 -0.02 -0.28 0.07 no Endostatin 0.17 -0.02 -0.37 0.05 no Integrin beta 3/CD61 -0.05 -0.02 -0.53 0.04 no NRCAM -0.03 -0.01 -0.29 0.03 no tPA 0.01 -0.01 -0.41 0.02 no Integrin alpha 7 -0.05 0 -0.53 0.00 no

65 caspase 8 0.10 0.01 -0.39 -0.03 no DCC 0.01 0.03 -0.51 -0.06 no Integrin alpha 10 -0.03 0.03 -0.51 -0.06 no uPAR 0.06 0.03 -0.44 -0.07 no ECM1 0.10 0.04 -0.53 -0.08 no COL1A1 1.22 0.03 -0.29 -0.10 no enamelysin -0.05 0.03 -0.29 -0.10 no Integrin alpha 1 0.00 0.05 -0.35 -0.14 no ELAM-1/E-selectin 0.05 0.09 -0.52 -0.17 no Hyaluronidases 0.03 0.08 -0.45 -0.18 no uPA 0.09 0.08 -0.44 -0.18 no MT1-MMP -0.02 0.09 -0.47 -0.19 no Integrin alpha 6 -0.04 0.09 -0.39 -0.23 no Integrin beta 2 -0.01 0.1 -0.43 -0.23 no Integrin alpha X 0.00 0.08 -0.33 -0.24 no integrin alpha 11 0.03 0.16 -0.48 -0.33 no PAI-2 -0.04 0.02 -0.06 -0.33 no PECAM-1 -0.04 0.1 -0.28 -0.36 no catenin alpha-like 1 0.14 0.18 -0.42 -0.43 no laminin B1 0.01 0.15 -0.32 -0.47 no cathepsin G 0.06 0.08 -0.17 -0.47 no caspase 9 0.15 0.13 -0.21 -0.62 no vitronectin 0.23 0.15 -0.19 -0.79 no Integrin alpha 5 0.03 0.1 -0.12 -0.83 no Integrin alpha V 0.01 0.16 -0.19 -0.84 no ICAM-1 0.04 0.13 -0.11 -1.18 no catenin delta 1 0.13 0.11 -0.07 -1.57 no Integrin alpha 3 0.09 0.15 -0.02 -7.50 no osteopontin 0.36 0.44 0.09 4.89 maybe catenin delta 2 0.18 0.23 0.51 2.22 maybe E-cadherin 0.47 0.33 -0.31 -1.06 maybe COL4A2 0.27 0.2 -0.16 -1.25 maybe catenin beta 1 0.20 0.25 -0.13 -1.92 maybe catenin alpha 1 0.28 0.26 -0.04 -6.50 maybe Integrin alpha 4 (VLA-4) 0.11 0.22 -0.03 -7.33 maybe VCAM1 0.32 0.17 -0.01 -17.00 maybe cystatin C 0.18 0.27 -0.01 -27.00 maybe GAPDH 0.89 0.77 2.2 2.86 HK cyclophilin A 0.74 0.54 1.22 2.26 HK RPL13A 1.29 2.37 4.63 1.95 HK b-actin 1.00 1 1 1.00 HK

66 Table 3. List of MAPK genes expressed differentially and organized according to “potential” and “fold change”. Genes that are candidates for validation are those listed as “potential” and have a fold change greater than 2. Fold change was calculated by dividing Day 6 CsA by Day 6 Veh or Day 6 Veh by Day 6 CsA with the higher number in the numerator and the lower in the denominator. The “Potential” was determined by the estimating error values of Day 6 Veh and Day 6 CsA intensities. Error values were determined to be +/- the lowest value for each column giving 0.04 for Day 6 Veh and 0.06 for Day 6 CsA. “Yes” = both numbers are higher than error value, “maybe” = one number is higher and one number is lower than error value, “no” = both numbers are lower than error value. HK denotes housekeeping genes. Fold change decreases in expression are represented by green while increases are represented by red. All genes were normalized to β-actin.

Day 1 Day 6 Fold Gene Veh Veh CsA Change Potential COL1A1 0.62 1.58 0.53 2.99 yes cyclin B1 0.15 0.20 0.08 2.62 yes cyclin B2 0.15 0.19 0.07 2.56 yes cyclin A 0.15 0.18 0.07 2.54 yes cyclin A1 0.13 0.17 0.07 2.38 yes p18 (cdk4 inhibitor) 0.15 0.21 0.09 2.27 yes cyclin D1 0.68 0.22 0.49 2.18 yes DLK 0.13 0.17 0.08 2.09 yes cyclin E2 0.16 0.20 0.10 2.06 yes B-raf 0.16 0.18 0.09 2.04 yes cdk2 0.18 0.23 0.11 1.99 yes E2F1 0.14 0.17 0.09 1.95 yes cyclin E1 0.14 0.16 0.08 1.93 yes p57Kip2 0.14 0.19 0.10 1.91 yes p16ink4 0.14 0.17 0.09 1.90 yes CREB 0.17 0.30 0.16 1.89 yes p19Ink4d 0.15 0.18 0.09 1.89 yes c-fos 0.12 0.15 0.08 1.85 yes Ksr 0.11 0.15 0.09 1.76 yes p15 Ink2b 0.20 0.20 0.12 1.65 yes cdk4 0.22 0.25 0.15 1.64 yes N-ras 0.10 0.12 0.07 1.63 yes cdk6 0.10 0.14 0.09 1.62 yes ATF-2 (creb-2) 0.18 0.19 0.12 1.62 yes Ets1 0.16 0.16 0.10 1.60 yes CBP 0.21 0.25 0.16 1.60 yes JNKK2 0.11 0.14 0.09 1.58 yes Elk1 0.09 0.14 0.09 1.54 yes c-ets2 0.14 0.14 0.09 1.51 yes PLA2 0.52 0.67 0.45 1.50 yes Grp78 0.98 0.44 0.66 1.50 yes

67 K-ras 0.14 0.17 0.12 1.49 yes MKP1/DUSP1 0.20 0.21 0.14 1.48 yes A-raf 0.16 0.19 0.13 1.45 yes hsp27 (hsp b1) 0.33 0.31 0.45 1.44 yes cyclin D3 0.17 0.18 0.12 1.43 yes Cdc42 0.81 0.74 0.52 1.41 yes ERK1 0.09 0.12 0.09 1.39 yes NFAT3 (NSATc4) 0.12 0.14 0.10 1.38 yes p27Kip1 0.23 0.25 0.19 1.34 yes TAK1 0.17 0.22 0.17 1.32 yes V-jun 0.23 0.18 0.23 1.31 yes Mkk4 (JNKK1) 0.08 0.09 0.07 1.27 yes MAPKAP kinase-2 0.21 0.31 0.25 1.24 yes 14-3-3 (stratifin) 0.18 0.18 0.22 1.22 yes GRB2 0.26 0.31 0.25 1.21 yes MEKK3 0.08 0.12 0.10 1.21 yes DPC4 0.32 0.33 0.28 1.20 yes Elk-4/Sap 1a 0.17 0.18 0.15 1.20 yes Rac1 0.40 0.44 0.36 1.19 yes MEK1 0.18 0.19 0.16 1.18 yes p53 0.27 0.25 0.29 1.16 yes cyclin D2 0.22 0.14 0.17 1.15 yes Rb 0.14 0.16 0.14 1.15 yes raf (c-raf-1) 0.23 0.28 0.25 1.13 yes max 0.13 0.12 0.10 1.13 yes Egr-1 0.19 0.26 0.30 1.13 yes c-myc 0.13 0.14 0.12 1.12 yes EGFR 0.54 0.47 0.43 1.08 yes MSK1 0.13 0.14 0.13 1.07 yes autotaxin (ATX) 0.34 0.27 0.28 1.07 yes p21Waf1 (p21Cip1) 0.98 0.72 0.75 1.05 yes JIP-1 0.01 0.04 0.00 23.35 no JNK1 -0.01 0.06 0.01 6.71 no MP1 0.02 0.05 0.01 3.66 no MST1 0.04 0.06 0.04 1.62 no MKK3 0.05 0.04 0.06 1.53 no H-ras 0.04 0.04 0.02 1.52 no MEK2 0.01 0.01 0.01 0.98 no MLK3 -0.06 -0.04 -0.05 0.69 no MNK1 -0.03 -0.02 -0.03 0.64 no PAK3 -0.05 -0.02 -0.03 0.52 no ERK5 -0.05 -0.01 -0.03 0.47 no MEF2C -0.07 -0.03 -0.06 0.46 no ERK3 -0.03 -0.02 -0.04 0.34 no NIK -0.03 0.00 -0.03 0.12 no JNK3 -0.03 0.01 -0.01 -0.76 no c-Mos -0.03 0.01 -0.01 -2.13 no GLK 0.00 0.08 -0.01 -8.30 no p38b MAPK 0.00 0.03 0.00 -16.21 no MAPK 0.04 0.08 0.02 4.31 maybe

68 p38g MAPK 0.04 0.08 0.02 3.82 maybe HPK1 0.06 0.10 0.03 3.59 maybe IKK-a 0.07 0.19 0.07 2.67 maybe MEKK4 0.05 0.10 0.04 2.41 maybe MEKK1 0.08 0.10 0.04 2.39 maybe MKK6 0.07 0.10 0.04 2.34 maybe p38 MAPK 0.08 0.11 0.05 2.27 maybe MAPKAP kinase-3 0.07 0.10 0.05 1.99 maybe MEK5 0.09 0.11 0.06 1.75 maybe JNK2 0.06 0.08 0.05 1.64 maybe ERK2 0.06 0.07 0.04 1.63 maybe MEKK5 0.07 0.10 0.06 1.60 maybe Pak1 0.10 0.10 0.06 1.60 maybe MEKK2 0.05 0.07 0.05 1.37 maybe Rac2 0.06 0.09 0.07 1.26 maybe cyclophilin A 0.39 0.20 0.35 1.74 HK GAPDH 1.55 1.46 1.18 1.23 HK RPL13A 1.09 0.72 0.68 1.05 HK b-actin 1.00 1.00 1.00 1.00 HK

69 2∆∆ct Treatment vs. 1 Day Vehicle of Col1α1

5

e 4 c n e r

e 3 f f

d Di 2 Fol 1

0

sA eh sA Veh V y y C y y C a a a a D D 1 1 6 D 6 D

Figure 15. The graph above represents the fold difference of Col1α1 Q-PCR cycle threshold normalized to β-actin Q-PCR cycle threshold levels after CsA treatment of gingival fibroblasts in vitro. Numbers were generated using the ∆∆ct method for calculating fold differences of cycle thresholds.

70 Table 4. The table below represents the location of the 96 genes plus housekeeping genes on the Extracelluar Matrix and Adhesion Molecules Gene Array as supplied by Superarray.

Gene Table For Extracellular Matrix and Adhesion Molecules Gene Array (Cat. # HS-010)

Array Layout

ADAMTS1 ADAMTS8 CASP8 CASP9 CAV1 CD44 CDH1 CEACAM5 1 2 3 4 5 6 7 8

CNTN1 COL18A1 COL1A1 COL4A2 CST3 CTNNA1 CTNNAL1 CTNNB1 9 10 11 12 13 14 15 16

CTNND1 CTNND2 CTSB CTSD CTSG CTSL DCC ECM1 17 18 19 20 21 22 23 24

FGB FN1 HPSE ICAM1 ITGA1 ITGA10 ITGA11 ITGA2 25 26 27 28 29 30 31 32

ITGA2B ITGA3 ITGA4 ITGA5 ITGA6 ITGA7 ITGA8 ITGA9 33 34 35 36 37 38 39 40

ITGAL ITGAM ITGAV ITGAX ITGB1 ITGB2 ITGB3 ITGB4 41 42 43 44 45 46 47 48

ITGB5 ITGB6 ITGB7 ITGB8 LAMB1 LAMC1 MGEA5 MICA 49 50 51 52 53 54 55 56

MMP1 MMP10 MMP11 MMP12 MMP13 MMP14 MMP15 MMP16 57 58 59 60 61 62 63 64

MMP17 MMP2 MMP20 MMP24 MMP26 MMP3 MMP7 MMP8 65 66 67 68 69 70 71 72

MMP9 NCAM1 NRCAM PECAM1 PLAT PLAU PLAUR SELE 73 74 75 76 77 78 79 80

SELL SELP SERPINB2 SERPINB5 SERPINE1 SPARC SPP1 THBS1 81 82 83 84 85 86 87 88

THBS2 THBS3 TIMP1 TIMP2 TIMP3 TMPRSS4 VCAM1 VTN 89 90 91 92 93 94 95 96

PUC18 PUC18 PUC18 Blank Blank Blank GAPDH GAPDH 97 98 99 100 101 102 103 104

PPIA PPIA PPIA PPIA RPL13A RPL13A ACTB ACTB 105 106 107 108 109 110 111 112

Adapted from www.superarray.com

71 Table 5. The table below represents the locations of the 96 genes plus housekeeping genes on the MAP Kinase Signaling Pathway Gene Array as supplied by Superarray.

Gene Table For Human MAP Kinase Signaling Pathway Gene Array (Cat. # HS-017)

Array Layout

PRDX6 ARAF ATF2 BRAF CCNA1 CCNA2 CCNB1 CCNB2 1 2 3 4 5 6 7 8

CCND1 CCND2 CCND3 CCNE1 CCNE2 CDC42 CDK2 CDK4 9 10 11 12 13 14 15 16

CDK6 CDKN1A CDKN1B CDKN1C CDKN2A CDKN2B CDKN2C CDKN2D 17 18 19 20 21 22 23 24

CHUK COL1A1 CREB1 CREBBP DLK1 DUSP1 E2F1 EGFR 25 26 27 28 29 30 31 32

EGR1 ELK1 ELK4 ENPP2 ETS1 ETS2 FOS GRB2 33 34 35 36 37 38 39 40

HRAS HSPA5 HSPB1 JUN KRAS2 KSR SMAD4 MAP2K1 41 42 43 44 45 46 47 48

MAP2K1IP1 MAP2K2 MAP2K3 MAP2K4 MAP2K5 MAP2K6 MAP2K7 MAP3K1 49 50 51 52 53 54 55 56

MAP3K11 MAP3K14 MAP3K2 MAP3K3 MAP3K4 MAP3K5 MAP3K7 MAP4K1 57 58 59 60 61 62 63 64

MAP4K3 MAPK1 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 65 66 67 68 69 70 71 72

MAPK6 MAPK7 MAPK8 MAPK8IP2 MAPK9 MAPKAPK2 MAPKAPK3 MAX 73 74 75 76 77 78 79 80

MEF2C MKNK1 MOS MST1 MYC NFATC4 NRAS PAK1 81 82 83 84 85 86 87 88

PAK3 RAC1 RAC2 RAF1 RB1 RPS6KA5 SFN TP53 89 90 91 92 93 94 95 96

PUC18 PUC18 PUC18 Blank Blank Blank GAPDH GAPDH 97 98 99 100 101 102 103 104

PPIA PPIA PPIA PPIA RPL13A RPL13A ACTB ACTB 105 106 107 108 109 110 111 112 Adapted from www.superarray.com

72