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Microarray Analysis of Gene Expression Patterns on Healing Rat Skin Wounds with Human Recombinant Platelet Derived Growth Factor

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Title:
Microarray Analysis of Gene Expression Patterns on Healing Rat Skin Wounds with Human Recombinant Platelet Derived Growth Factor
Creator:
YANG, HEEJUNG ( Author, Primary )
Copyright Date:
2008

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Subjects / Keywords:
Chemokines ( jstor )
Complementary DNA ( jstor )
Human growth ( jstor )
Ligands ( jstor )
Messenger RNA ( jstor )
Rats ( jstor )
Receptors ( jstor )
RNA ( jstor )
Skin ( jstor )
Wound healing ( jstor )

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University of Florida
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University of Florida
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Copyright Heejung Yang. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
5/31/2010
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75274263 ( OCLC )

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MICROARRAY ANALYSIS OF GENE EXPRESSION PATTERNS ON HEALING RAT SKIN WOUNDS WITH HUMAN RECOMBINANT PLATELET DERIVED GROWTH FACTOR By HEEJUNG YANG A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Heejung Yang

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This thesis is dedicated to my pare nts, Hosuk Jun and Kooktae Yang, and Youngnyun Kim for their support and encouragement in the pursuit of my education in biomedical science.

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ACKNOWLEDGMENTS I would like to sincerely thank my mentor, Dr. Gregory Schultz, for his patience in my progress, support, and encouragement. Without his expertise, advice, and faith in me throughout the course of my research for this thesis, I would not have made it. I would also like to thank all of my committee members: Dr. Henry Baker and Dr. Donna H. Duckworth. I thank Dr. Henry Baker for his valuable time in analyzing microarray data. I would also like to express my deepest thanks to Youngnyun Kim, Angel Sampson, Cecilia Lopez, Brett Baskovich, Dr. Michael P. Popp, John Azeke, Blanca G. Ostmark, Brian Morrison, Suresha Rajaguru, Siva Radhakrishnan, Timothy D. Blalock, Vikram Palkar, Angela Prevatt, David Reyes, and Kavita Gandhi for all of the experimental advice, friendship, and support they have helped me. Finally, I would like to thank my parents, Hosuk Jun and Kooktae Yang, for their supports that they have provided me over the years. iv

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES ............................................................................................................vii LIST OF FIGURES .........................................................................................................viii ABSTRACT .......................................................................................................................ix CHATER 1 LITERATURE REVIEW.............................................................................................1 The Skin........................................................................................................................1 The Cellular and Molecular Events of Normal Wound Healing..................................2 Chronic Non-healing Wounds......................................................................................7 Platelet-derived Growth Factor (PDGF).......................................................................8 Structure of PDGF.................................................................................................9 The Role of PDGF.................................................................................................9 Recombinant Human Platelet-Derived Growth Factor-BB (PDGF-BB)............10 Microarray..................................................................................................................11 Biology of Microarrays.......................................................................................11 Two dye cDNA Microarrays...............................................................................12 Oligonucleotide Microarrays...............................................................................12 Image Processing and Data Analysis..................................................................13 2 MATERIALS AND METHODS...............................................................................15 Animal Wound Model................................................................................................15 Topical Treatment of Wounds with rhPDGF Protein and Wound Area Measurement16 RNA Isolation.............................................................................................................17 RNA Quality Control..................................................................................................18 Spectrophotometer...............................................................................................18 Bioanalyzer..........................................................................................................18 Microarray Assay........................................................................................................19 cRNA Preparation...............................................................................................19 Array Hybridization.............................................................................................20 Data Analysis..............................................................................................................20 Image Analysis....................................................................................................20 Unsupervised Analysis........................................................................................21 v

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Supervised Analysis: Cross Validation and Permutation Analysis.....................21 3 RESULTS...................................................................................................................23 Wound Area................................................................................................................23 Quantification and Quality of Total RNA..................................................................24 c RNA.........................................................................................................................28 Unsupervised Analysis...............................................................................................31 Supervised Analysis....................................................................................................33 Leave-one-out Cross-validation..........................................................................33 Permutation analysis............................................................................................34 4 DISCUSSION.............................................................................................................51 APPENDIX LIST OF THE 691 GENES AND THEIR NORMALIZED LOG-TRANSFORMED MEDIAN-CENTERED GENE EXPRESSIONS OF NON-ISCHEMIC WOUNDS56 LIST OF REFERENCES...................................................................................................75 BIOGRAPHICAL SKETCH.............................................................................................82 vi

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LIST OF TABLES Table page 3-1 The concentration of total RNA and the ratio of spectrophotometer absorbance at a wavelength of 260 nm to a wavelength of 280 nm of one time series at day 7.......25 3-2 Summary of cross-validation analysis......................................................................35 3-3 The p-values of each prediction model based on 2000 random permutations.........35 3-4 Genes in which expression level increased more than 3-fold in non-ischemic wounds at day 3 relative to the controls (normal skin)............................................36 3-5 Genes in which expression level decreased more than 3-fold in non-ischemic wounds at day 3 relative to the controls (normal skin)............................................38 3-6 Genes in which expression level increased more than 3-fold in non-ischemic wounds at day 7 relative to the controls (normal skin)............................................40 3-7 Genes in which expression level decreased more than 3-fold in non-ischemic wounds at day 7 relative to the controls (normal skin)............................................40 3-8 Genes classified into functional categories based on GeneOntology and cumulative hypergeometric probabilities in the 4363 functionally annotated genes on the array45 vii

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LIST OF FIGURES Figure page 3-1 Rat skin healing profile in ischemic and non-ischemic (normal) wounds treated with PDGF or Vehicle, created with a 6-mm diameter punch.................................24 3-2 Electropherogram of the total RNA sample. Two well-defined peaks of the 18S and 28S ribosomal RNAs were observed.........................................................26 3-3 Electropherogram of the total RNA samples. Two well-defined peaks of the 18S and 28S ribosomal RNAs were observed.................................................................27 3-4 Total RNA of samples in a gel-like image...............................................................28 3-5 Purified and unfragmented Biotin-labeled cRNAs in a gel-like image showing the 9 samples that were used in the microarray experiments........................................29 3-6 Electropherogram of purified and unfragmented Biotin-labeled cRNAs................30 3-7 Electropherogram of purified and unfragmented Biotin-labeled cRNAs................30 3-8 Unsupervised cluster analysis of the variance normalized dataset using dCHIP, whose gene expression changed the most among all 27 microarrays......................32 3-9 The expression profiles of four selected genes with the largest differential expression among three time points of 691 genes....................................................42 3-10 Genes with at least a 3-fold change in expression relative to control (normal skin) in response to rat skin injury....................................................................................42 3-11 Hierarchical clustering patterns................................................................................44 3-12 Functional categories of genes using hierarchical clustering analysis.....................50 viii

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MICROARRAY ANALYSIS OF GENE EXPRESSION PATTERNS ON HEALING RAT SKIN WOUNDS WITH HUMAN RECOMBINANT PLATELET DERIVED GROWTH FACTOR By Heejung Yang May 2005 Chair: Gregory S. Schultz Major Department: Molecular Genetics and Microbiology Skin wound healing is a complex biological process that has been investigated at the molecular level. Gene expression profiling of wound healing in the skin using oligonucleotide arrays allows for simultaneous comparison of tens of thousands of genes. The goal of this research is to determine the changes in the patterns of gene expression in ischemic/non-ischemic rat skin wounds produced by topical treatment with platelet-derived growth factor (PDGF) over three time points (days 0, 3, and 7). Previous studies showed that healing of ischemic wounds is accelerated by topical treatment with PDGF as protein levels of a small number of selected growth factors, receptors, and extracellular matrix genes that are thought to participate in wound healing. In the previous study by Santosh Gowda, it was shown that the levels of pro-inflammatory cytokines (TNF-, and IL-1) and MMPs are reduced in rat ischemic wounds treated with PDGF. These studies provided important information about the effect of platelet-derived growth factor on healing and biochemical parameters of normal and ischemic rat skin wounds. However, in this study, the expression of genes was simultaneously analyzed by ix

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analyzing mRNA levels and compared on day 0, days 3 and 7 after rat surgeries with four different groups: non-ischemic wounds, non-ischemic wounds with topical PDGF treatment, ischemic wounds, and ischemic wounds with topical PDGF treatment, using GeneChip Rat Expression Array 230A (Affymetrix, Santa Clara, CA). Unsupervised hierarchical clustering using dCHIP showed the close clustering of the chips based on the time after injury, which means that the biggest factor influencing the gene expression profile of rat skin is the time after injury. Further examination under supervised analysis was performed to study relationships between expression profile and experimental groups using BRB Array Tools. Only one set of “Time Points in Non-ischemic Wounds Treated with Vehicle” was chosen for further analysis, excluding the other sets and the 691 genes in the non-ischemic wound group over three time points (day 0, day 3, and day 7) were determined as significant differentially expressed at the p < 0.001 significant level and applied to hierarchical clustering analysis as well as straightforward lists of increased and decreased genes based on user-defined thresholds. In overall gene expression on day 3 compared with day 7, a relatively large number of genes (144 genes) showed at least 3-fold change relative to day 0, which suggests that more changes at the molecular level were going on during the early stage of healing (day 3) than during the later stage (day 7) with a correlation of gene expression in normal wounds of rat skin with known events present in wound healing. There were also many genes (71%) with unknown functions that were dramatically increased or decreased over time points, suggesting that the molecular events occurring in wound healing are more complicated than the current knowledge. The study of these genes may provide additional findings to improve understanding of the wound healing process. x

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CHAPTER 1 LITERATURE REVIEW The Skin The skin is a bilayer organ, an external membranous layer that provides a vital protective barrier against the outside environment. The skin is the largest organ of the body, weighing approximately 16 percent of the body weight. Stratified (multilayered) epithelium serves as a barrier and protective surface (Lodish et al., 2003). Skin protects the body from water loss, bleeding, and invading bacteria. Damaged skin can cause significant morbidity. The epidermis forms the outermost part of the skin, acting as a water-tight barrier for the prevention of desiccation and the protection against abrasion (Lodish et al., 2003). It is mainly made up of keratinocytes, which differentiate to basal layer, prickle cell layer, granular layer, and surface layer. In epidermal cells, keratin filaments are cross-linked by filagrin, an intermediate filament-associated protein (IFAP), and adhere at their ends to desmosomes. The basal epidermal cells are anchored by mature fibronectin, form keratin, and replace injured cells. The normal regenerative process of the epidermis takes 2 to 3 weeks (Woodley and Okeefe, 1985). The dermis, divided from the epidermis by the basement membrane, consists of collagen, elastin fibers, and proteoglycans that provide mechanical strength to the skin. The subcutaneous layer, the innermost layer of the skin, contains adipose tissue and helps to control body temperature. 1

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2 The Cellular and Molecular Events of Normal Wound Healing Wound healing is a complicated process that is regulated by interactions between cells, cytokines, and extracellular matrix (ECM) (Clark, 1996). The complicated healing process results from the involvement of many factors involved in wound repair that affect each other (Falanga, 2001). The healing pathway is characterized by several overlapping stages, including inflammation, proliferation, and remodeling (Singer and Clark, 1999) which act to restore the functional integrity of tissue. After a skin injury, the first major process is the formation of a blood clot and degranulation of platelets (Bennett and Schultz, 1993). This is accompanied by the vascular response in which blood vessels initially constrict and later become very permeable, allowing substantial increase in edematous fluid in the tissue around the injury (Bennett and Schultz, 1993; Mast and Shultz, 1996). The blood clot consists of platelets, cross-linked fibrin molecules, fibronectin, and thrombospondin, and provides a provisional matrix for cell migration (Clark, 1996; Nicosia and Villaschi, 1999). As platelets adhere to collagen molecules exposed by the injury, they release the contents of the -granules that promote clotting formation (Heldin and Westermark, 1996; Nicosia and Villaschi, 1999). -granules release a cascade of chemical signals, cytokines or growth factors such as platelet-derived growth factor (PDGF), epidermal growth factor (EGF), and transforming growth factor(TGF-1 and TGF-2), which attract inflammatory cells from the bloodstream to the site of wound repair to initiate the repair process (Mast and Schultz, 1996; Heldin and Westermark, 1996; Nicosia and Villaschi, 1999; Falanga, 2001).

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3 The complement system is also activated by tissue injury, releasing a variety of chemo-attractant factors. Neutrophils are the first leukocytes, or immune system white blood cells, to increase at the site of the wound in the early response to injury (Simpson and Ross, 1972). Normally neutrophils move along microvascular walls with low-affinity binding to selectins. Selectins are a family of transmembrane molecules, containing a carbohydrate-binding lectin domain that recognizes specialized sugar structures on glycoproteins and glycolipids on adjacent cells. They are expressed on the surface of activated endothelial cells and facilitate adhesion and movement of leukocytes (Pierce et al., 1995; Lodish et al., 2003). Recruited neutrophils destroy foreign material and bacteria that may be present in the injured tissue (Nicosia and Villaschi, 1999; Falanga, 2001), and release proteases such as collagenase, a member of the matrix metalloproteinase superfamily of proteases (MMPs), and the serine protease, elastase, which remove damaged ECM components (Hibbs et al., 1985). Inflammatory cytokines such as TNFinduce MMPs transcription ( Abraham et al., 2000). Undamaged matrix in tissue contains protease inhibitors which act to limit the actions of proteases (Yager and Nwomeh, 1999). Within a few hours, monocytes are also recruited to the wound site, and adhere to the ECM components. The monocytes become activated and transform into tissue macrophages, which play a central role in wound healing (Rappolee et al., 1988). Activated macrophages secrete a variety of growth factors, such as PDGF, vascular endothelial growth factor (VEGF), and TGF-. These growth factors attract epithelial cells, fibroblasts, smooth muscle cells, and vascular endothelial cells to the wound site. They also are very active in phagocytizing tissue debris and microorganism which aids

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4 the healing process (Clark, 1996; Falanga, 2001). Failure of macrophage activity is known to cause a delayed healing response (Diegelmann, 1981). Re-epithelialization, which is the resurfacing the wound by epidermal cells, serves as a significant step in the healing process (Clark, 1996). It is directed in part by fibroblasts due to their secretion of keratinocyte growth factor-2 (KGF-2) and IL-6, which stimulate the proliferation and migration of keratinocytes (Soler et al., 1999). Keratinocyte migration across a wound surface accomplishes re-epithelialization or closure of the wound (Falanga, 2001). After skin injury, keratinocytes at the wound margin lose their anchorage to basement membrane components such as laminin, which allow hemidesmosomes and 64 integrins to dissolve for the migration of keratinocytes (Clark, 1996; Nicosia and Villaschi, 1999; Falanga, 2001). Normally, hemidesmosomes are found primarily on the basal surface of epithelial cells where they act to adhere epithelial cells to components of the underlying extracellular matrix (ECM). Hemidesmosomes also provide strength and rigidity to the entire epithelial cell layer. Integrins are heterodimers that act as major cell-surface adhesion receptors to anchor cells to the basal lamina connected to other ECM components (Lodish et al., 2003). Integrins also provide important signals to the cell about the matrix environment. Integrin receptors are rich at hemidesmosomes in epithelial cells. The expression of integrin receptors on epidermal cells allows the basal lamina anchoring to dissolve and interact with extracellular matrix (ECM) proteins in stromal type I collagen at the wound margin (Martin, 1997). Induction of MMP-1 (interstitial collagenase/collagenase-1) by fibroblast is mediated in part by interaction of the 21 integrin with dermal collagen. MMP-1 is essential for keratinocyte migration on type I collagen matrix (Pilcher, et al.,

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5 1997). Keratinocytes at the wound edge up-regulate MMP-10 (stromelysin-2), and it degrades non-collagenous extracellular matrix (ECM) proteins (Saarialho-Kere et al., 1994). When keratinocytes cover the wound area, migration of the epidermal cells stops and begin to form a stratified epithelium and an underlying basal lamina (Clark, 1996). The signal for the migration and proliferation of epidermal cells is unclear, but the loss of contact with other epidermal at the edge of the wound margin may stimulate the migration and proliferation of epidermal cells (Singer and Clark, 1999). Release of several growth factors such as EGF, TGF-, and KGF and increased expression of growth factor receptors may also stimulate these processes (Singer and Clark, 1999). It is clear that some growth factors have the ability to activate guanosine triphosphate (GTP), which controls lamellopodial extension and the assembly of focal adhesion complexes (Ridley and Hall, 1992; Ridley et al, 1995; Nobes and Hall, 1995). During re-epithelialization of cutaneous wounds, KGF sunthesis by the dermal fibroblasts is up-regulated over 150-fold through the stimulation of pro-inflammatory cytokines such as IL-1 and TNF(Werner et al., 1992). IL-1 and TNFare also known to help motile keratinocytes to cut through the wound eschar by promoting expression of proteases including plasminogen activator and MMP-10 (Tsuboi et al., 1993; Madlener et al., 1996). TGF-1 and the several of the pro-inflammatory cytokines are also involved in the migration of keratinocytes (Gailit et al., 1994; Hertle et al., 1995). Granulation tissue, or new stroma, consists of cellular components including fibroblasts and inflammatory cells with numerous new capillaries in a loose extracellular matrix. Macrophages move into the wound site with fibroblasts and blood vessels (Hunt, 1980) to provide an ongoing source of growth factors required to stimulate fibroblast

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6 proliferation and angiogenesis. Fibroblasts play a key role in synthesis of new scar through the production of large quantities of collagen, which is a major constituent of the extracellular wound matrix. The proliferation of fibroblasts, expression of appropriate integrin receptors, and fibroblast migration into the wound site are stimulated by growth factors, including PDGF (Heldin and Westermark, 1989) and TGF-1 (Clark, 1996; Gary et al., 1993). TGFis also involved in granulation tissue formation, such as reduced expression of MMPs and enhanced production of tissue inhibitors of metalloproteinase (TIMP) (Herlyn and Malkowitz, 1991). Angiogenesis is the branching growth of the vasculature, and it is critical to the generation of granulation tissue (Clark, 1996; Falanga, 2001). The induction of angiogenesis is attributed to the initiation of paracrine signals that stimulate the proliferation and migration of endothelial cells. Fibroblast growth factor (FGF) and VEGF are angiogenic ligands that have interact with specific receptors on endothelial cells. FGF binds to FGFR-1 and FGFR-2, and VEGF binds to specific receptors including VEGFR-1 and VEGFR-2. The expression and activity of proteases are also necessary for angiogenesis (Madri, 1996). During the remodeling stage of healing, angiogenesis ceases and through apoptosis many new blood vessels break down (Ilan, et al., 1998). Wound contraction is the inward movement of the wound edge, and it involves a complex interaction of cells, extracellular matrix, and cytokines. Fibroblasts migrate from the wound margins into granulation tissue, bind collagen fibers via their integrin receptors, and transform into myofibroblasts with express contractile actin fibers under the influencing of growth factors including TGF-1 (Majno et al., 1971). Myofibroblasts

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7 can generate the contractile forces, which are applied to collagen fibers and reduce the wound area (Majno et al., 1971). Once wound contraction has ceased, the numbers of fibroblasts and myofibroblasts in the wound decrease, primarily due to apoptosis (Desmouliere et al., 1995). During the remodeling phase, the numbers of inflammatory cells, fibroblasts and vascular endothelial cells decrease at the wound site (Schultz and Bennett, 1992; Clark, 1996) and the dermis becomes stronger as collagen fibers become cross-liked by enzymatic action. The synthesis and degradation of collagen continues at a low level for many months to years and eventually a new balance is reached in the amount of scar tissue that remains in the wound. Chronic Non-healing Wounds If normal wound healing fails to restore tissue integrity of the wound site, it becomes chronic (Lazarus et al., 1994). Chronic non-healing wounds, such as pressure ulcers and diabetic ulcers, contribute to the morbidity and mortality of medical patients (Keller et al., 2002) and impose a huge social and financial burden on the health care system. The annual cost estimate related to the care of patients with pressure ulcers in the United States is over $1.3 billion (Allman, 1998), and the increasing numbers of elderly individuals suggest that the problem will continue to increase in the future. Chronic wounds are typically characterized by bacterial colonization due to poor blood flow, hypoxia, and the wound site remaining open for a prolonged period of time (Hunt and Hopf, 1997). Ischemia is an important principal feature of chronic wounds that contributes frequently to impaired wound healing in patients by decreasing the amount of oxygen-containing blood delivered to a specific organ, or tissue (Robson, 1997).

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8 Prolonged ischemia causes infection, inflammation, and necrosis in wounds. Ischemia must be controlled to study treatment for chronic wounds. Normal wound healing is dependent on a multitude of growth factors and cytokines at different stages. Disruption of the coordinated process in normal wound healing can lead to chronic non-healing wounds. The prolonged inflammatory response in chronic wounds that is characterized by the over-abundance of neutrophil infiltration (Diegelmann and Evans, 2004) causes poor re-epithelialization and extra formation of granulation tissue. The neutrophils release collagenase (MMP-8) that degrades the connective tissue matrix (Nwomeh et al., 1999) and release elastase that destroys important growth factors such as PDGF and TGF(Yager et al., 1996). Extremely high concentrations of MMPs have been found in wound fluid collected from chronic wounds (Trengove et al., 1999). The MMPs are thought to inhibit cellular proliferation and angiogenesis (Bucalo, 1993, Madlener et al., 1998). Balanced degradation and reconstruction of the ECM is required for normal wound healing. However, the elevated levels of the MMPs in chronic wounds are thought to contribute to the impaired healing of chronic wounds (Rogers et al., 1995). Platelet-derived Growth Factor (PDGF) Growth factors stimulate cell proliferation and migration and induce a change in the pattern of protein synthesis and secretion. PDGF, a factor originally isolated from platelets, is a powerful mitogen that affects proliferation of fibroblasts in vitro (Clark, 1996; Mast and Schultz, 1996; Martin, 1997). PDGF is also produced by a variety of other cells such as activated monocytes, macrophages, vascular smooth muscle cells, and endothelial cells (Meyer-Ingold and Eichner, 1995; Clark, 1996). PDGF initiates the

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9 chemotaxis of neutrophils, macrophages, smooth muscle cells and fibroblasts as well as stimulating mitogenesis of the fibroblasts and smooth muscle cells. Structure of PDGF Platelet-derived growth factor (PDGF) is approximately a 30 kDa dimeric protein (Westermark et al., 1989) that is composed of two disulfide-linked polypeptide chains, defined PDGF-A and PDGF-B chains, which are products of two genes, PDGF-A and B on chromosomes 7 and 22, respectively (Betsholtz et al., 1986; Ross, 1989). Many studies show that the expression of the two genes appear to be controlled by different regulatory mechanisms, meaning that the two PDGF chains are produced in different cell types in different ratios to each other (Meyer-Ingold and Eichner, 1995). PDGF is a member of the cysteine-knot growth factor superfamily including nerve growth factor (NGF) and TGF, which share the feature of a cysteine knot motif in the tertiary structure (Sun and Davies, 1995). These two chains can naturally form either homodimers (PDGF-AA, PDGF-BB) or heterodimers (PDGF-AB) in human platelets (Clark, 1996). The most abundant isoform in platelets is the AB heterodimer (Meyer-Ingold and Eichner, 1995), but the most potent isomer is PDGF-BB (Greenhalgh, 1996). Relatively late availability of pure PDGF-AB and poor in vitro effects of PDGF-AA make PDGF-BB a potential therapeutic agent for stimulating wound healing (Meyer-Ingold and Eichner, 1995). In preclinical studies, PDGF-BB is known to be involved in granulation tissue formation at the wounds, eventually contributing to wound healing (Grotendorst et al., 1985). The Role of PDGF PDGF is usually undetectable in normal human plasma and added PDGF is removed rapidly (Ross, 1989). PDGF isoforms are powerful mitogens for connective

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10 tissue cells, dermal fibroblasts, arterial smooth muscle cells, chondrocytes, and some epithelial and endothelial cells (Brewitt and Clark, 1988; Bornfeldt et al., 1994; Guerne et al., 1994; Lubinus et al., 1994). Studies of the effects of PDGF in vitro have shown that PDGF is a potent mitogen for connective tissue cells and stimulates chemotaxis of fibroblasts, smooth muscle cells, neutrophils, and macrophages as well as activating macrophages to produce other important growth factors in wound healing (Clark, 1996). PDGF promotes chemotaxis and proliferation of cells in wound healing, and stimulates the formation of granulation tissue. Upon formation of blood clots after injuries, platelets adhere to clots and release PDGF. Biological activity of PDGF in normal wound healing PDGF requires the expression of PDGF receptors on cells at the wound site (Heldin and Westermark, 1999). Both the absolute and relative amount of PDGF isoforms exposed to a cell and the number of and PDGF receptor monomers expressed on the cell surface modulate the response of the cell to PDGF (Hughes et al., 1996). Clinical trials have shown that PDGF-BB stimulates healing of chronic diabetic ulcers (Heldin and Westermark, 1999). Recombinant Human Platelet-Derived Growth Factor-BB (PDGF-BB) Becaplermin is a recombinant human platelet-derived growth factor-BB (rhPDGF-BB) produced by recombinant DNA technology having similar biological activity to endogenous platelet-derived growth factor. Over-expression of the complementary deoxyribonucleic acid (cDNA) using suitable expression systems is important for the production and isolation of a recombinant protein. cDNA clones of the PDGF-B and –A chains produced by recombinant DNA technology allowed biologically active PDGF isoforms to be expressed (Betsholtz et al., 1986). Becaplermin, produced by insertion of the gene for the B chain of PDGF into the yeast Saccharomyces cerevisiae, was

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11 formulated in a sodium carboxymethylcellulose (NaCMC)-based gel for topical administration. This also provided a moist condition to the wound site (d’Hemecourt et al., 1998). Becaplermin gel was approved by the United States Food and Drug Administration for the treatment of lower extremity diabetic neuropathic ulcers. Becaplermin gel is a novel, pharmacologically active treatment for chronic lower extremity diabetic ulcers. Microarray DNA microarray technologies have revolutionized biological research. Microarray-based research enables the investigation of global patterns of gene expression. The expression levels of tens of thousands of genes in a single hybridization can be measured simultaneously with microarray technology instead of the traditional approach of investigating individual gene products. Prepared mRNAs from experimental samples are fluorescently labeled in the target preparation, and are hybridized to a large number of DNA sequences on the array and scanned to produce images for the analysis (Schena et al, 1995). Several methods for the various microarray systems have been developed, but the most commonly used types are cDNA and oligonucleotide microarrays. Biology of Microarrays Microarray technology measures gene expression at the transcription level for tens of thousands of genes simultaneously in a sample (Gabig and Wegrzyn, 2001). Biological information necessary for cellular functions is stored in genes that are composed of DNA. The encoded information containing instructions for the synthesis of proteins is transcribed into messenger ribonucleic acid (mRNA). The transcribed mRNA is processed to mature mRNA without introns. The purpose of microarray research is to

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12 quantify the amount of transcribed mRNA for a large number of genes in cells under such diverse conditions as cancer and compare it to conditions in normal cells. (Nguyen et al, 2002). Two dye cDNA Microarrays Using a two-dye cDNA microarray system, the pattern of gene expression of an experimental sample is measured relative to the gene expression of a reference sample labeled with a different fluorescent dye. Total RNA is isolated from the experimental samples and the control samples and used to generate labeled complementary DNAs (cDNAs). The labeled cDNAs are mixed with reference cDNA and hybridized to probes on the array. Fabrication of cDNA array requires the preparation of the glass slide to increase binding of the cDNA to the glass surface, the amplification of the DNA sequences using a technology of polymerase chain reaction (PCR) and depositing the cDNA sequences onto a glass slide (Duggan et al., 1999). Since cDNA probes deposited on the array are double strands, the array is heated to denature the double-stranded cDNA for the binding of a complementary DNA strand obtained from the experimental sample to a cDNA probe on the array (Schena et al., 1995). Oligonucleotide Microarrays Experiments with high density oligonucleotide arrays produce extraordinary amounts of genetic and cellular information by monitoring levels of sRNA expression in response to genetic and environmental differences. A given gene is represented by 11 different 25 mer oligonucleotides synthesized in situ using a photolithographic manufacturing process (Lockhart et al., 1996). Unique sequences of a given transcript can be designed as an oligonucleotide probe that serves as a sensitive, unique, sequence

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13 specific detector. In a probe pair, a perfect match (PM) probe that is designed to be complementary to a reference sequence (or EST). It is paired with a mismatch (MM) probe as a control that is identical to its PM except the middle (13th) base is a mismatch. Hybridization to the MM is a good measure of non-specific binding. The presence and quantity of a gene is determined by statistical analysis based on the PM/MM intensities. The oligomer probes are designed to be unique to minimize cross-hybridization between similar sequences. This requires gene sequence information be known at the start of the design of oligonucleotides on chips. The MM probes allow the estimate of cross-hybridization and random hybridization by subtracting from the PM probe signal. Differences between the PM and MM feature intensities are assumed to be from hybridization kinetics of the different feature sequences and nonspecific background RNA hybridizations. Each oligonucleotide is positioned at a specific location on the array, a probe cell that contains millions of copies of a given oligonucleotide. Image Processing and Data Analysis The high-density oligonucleotide array allows the accurate comparison of the levels of gene transcripts in individual samples produced by separated arrays with the high reproducibility of in situ synthesis of oligonucleotide chips (Lockhart et al., 1996). In the Affymetrix GeneChip system, mRNA extracted from cells or tissue is converted to biotinylated cRNA from oligo-dT-primed cDNA. Each target sample is hybridized to a separate array and goes through an automated staining/washing step using the Affymetrix fluidics station, and the array is scanned to produce an image of the array from the fluorescently labeled cRNA, then which is converted into a 16-bit intensity value. The scanned image is sent to the GeneChip software supplied by Affymetrix to perform

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14 fundamental operations, such as image segmentation, background correction, scaling/normalizing arrays for array-to-array comparisons, and statistical calculation for the presence and the differential expression of gene transcripts for the analysis of an array (Schadt et al, 1999). The image segmenting may be the simplest operation in the analysis of gene expression profile produced by the Affymetrix GeneChip technology (Schadt et al., 1999). The GeneChip software uses a gridding algorithm based on alignment features on the array for the segmenting of the image and a percentile algorithm for the determining of the feature intensity value (Lockhart et al., 1996). To determine accurate signal intensity, i.e., the amount of RNA present for each gene on the array, background noise intensities are corrected (Schadts et al., 1999). Scaling and normalization allow for array-to array comparison in GeneChip data. Since only a single sample hybridizes to each GeneChip array, arrays must be adjusted to the same scale for the comparison of replicate samples (Schadts et al, 1999). In addition to image segmentation, background correction, and scaling/normalization, the presence and differential expression of genes are assessed by verifying probe performance (Schadts et al, 1999). The signals of the scanned image files are then analyzed with software, such as Affymetrix GCOS and dCHIP for the quantification and normalization. Once a representative single signal of each transcript is obtained by probe set algorithms including dCHIP then statistical methods are applied to identify differences in gene expression levels between different arrays.

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CHAPTER 2 MATERIALS AND METHODS Animal Wound Model Animal procedures were performed under a protocol approved by the University of Florida Animal Care and Use Committee, and complied with the standards in “Guide for the Care and Use of Laboratory Animals”, prepared by the National Institute of Health (NIH Publication no. 86-23, revised 1985). The original surgical procedure from Schwartz et al. was modified to create an ischemic bipedical rat skin model. A total of 32 adult Sprague-Dawley male rats weighing approximately 250-300 mg were randomly assigned to four experimental groups of 8 rats each designated as non-ischemic Vehicle treated wound, non-ischemic PDGF treated wound, ischemic Vehicle treated wound, and ischemic PDGF treated wound groups. Rats initially were anesthetized by Isoflurane IsoFlo (Abbott, North Chicago, IL) inhalation through a nose cone. The backs of rats were shaved with clippers and marked with an 11 x 2.5 cm rectangular template, which has 4 uniform holes arranged in pairs at 3.9 cm and 6.5 cm from the end of template and 3 mm from each edge, centered on the spine and sited between the base of the scapulae and the iliac crest. Under aseptic circumstances, after the marked dorsal skin was folded to align the two circles of each row opposite each other, and a wooden dowel was positioned against one side of skin to create a pair of full thickness wounds using a 6 mm Sklar TRu-Punch disposable Biopsy Punch (Sklar Instruments, West Chester, PA) set in an electric drill. These normal skin punch biopsies 15

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16 were immediately frozen in liquid nitrogen and stored at -80C for a microarray experiment as control groups (time point: day 0). To create the ischemic groups of rats, two parallel incisions extending deep to the panniculus carnosus muscle layer were made along the long side of the template on the back of the rat. The skin flap was then elevated and repositioned using AUTOCLIP (CLAY ADAMS Brand, Sparks, MD) staples on each incision side. Topical Treatment of Wounds with rhPDGF Protein and Wound Area Measurement Beginning on the day of wounding (day 0), the rats were anesthetized by isoflurane inhalation, and wounds from each individual rat were photographed every day for 7 days following surgery using a Nikon D 100 digital camera with two standard-size dots, a circular white paper with a 6mm diameter, placed beside the wound area. The images of wounds recorded by the digital camera were imported to Sigma Scan Software (Jandel Scientific, Corte Madera, CA) to measure the wound area with the area of standard-size dots for the ratio of wound area to standard-size, which was then expressed as the mean standard error in mm 2 and the percentage of the wound area compared to the initial area of the wound. Differences in wound areas among non-ischemic vehicle treated wounds, non-ischemic PDGF treated wounds, ischemic vehicle treated wounds, and ischemic PDGF treated wounds on day 3 and 7 after surgery were tested statistically by ANOVA, LSD, and Tukey HSD methods. Post surgery follow-up was performed on a daily basis and the four full thickness punch wounds in the respective groups of eight rats each were topically treated with a daily dose of approximately 50 ul of either vehicle gel (1% carboxymethylcellulose gel) or 0.01% recombinant PDGF-BB (Regranex gel). After treatment, the rats were returned

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17 to their dry cages in the animal care facility with unrestricted food and water. Two rats were assigned to a single cage. On days 3 and 7 post-surgery the wound sites of selected rats were harvested using a bigger 8 mm-punch biopsy, which would include all of the wound area and a bit of normal skin, and then those rats were euthanized using 0.3 ml of euthanasia solution Beuthanasia-D (Schering-Plough Animal Health Corp, Union, NJ) on those particular days. The collected samples were frozen immediately in liquid nitrogen and stored at -80C until use for further RNA extraction. RNA Isolation Total RNA was isolated using RNeasy Mini kits (Qiagen, Valencia, CA) according to manufacture’s protocol with some modifications. Briefly, tissue samples (weight 70-100 mg), which were stored at -80C, were disrupted using a mortar and pestle in liquid nitrogen and homogenized using a 15 ml glass homogenizer (Kontes #22, Fisher Scientific, Pittsburgh, PA) in Buffer RLT solution containing guanidine thiocyanate and -mercaptoethanol. The homogenate was loaded onto a QIA shredder Spin column (Qiagen; Valencia, CA) in a collection tube to enhance the efficiency of homogenization without the cross contamination of samples. The homogenized lysate was collected by centrifugation, treated with QIAGEN Proteinase K to inactivate DNases and RNases. Proteinase K is a broad acting protease which cleaves peptide bonds at the carboxylic sides of aliphatic, aromatics or hydrophobic amino acids. After a DNase treatment to remove any containing genomic DNA, RNA was bound to the RNeasy silica-gel membrane and the eluant was cleaned using RNeasy Mini kits (Qiagen, Valencia, CA).

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18 RNA Quality Control Spectrophotometer The concentration of the total RNA and the first check of the quality and purity were confirmed by a spectrophotometer. For a 1:100 dilution, 1 ul of each sample was diluted with 99 ul of DEPC-treated H 2 O and the ratio of absorbance readings at 260 nm and 280 nm was measured for the first estimate of RNA purity and concentration. Bioanalyzer BioAnalyzer 2100 (Agilent Technologies, Palo Alto, CA) with RNA 6000 Nano LabChip Kit (Agilent Technologies, Palo Alto, CA) was used to assess both the quality and integrity of isolated total RNA of 200 ng aliquots. It is important to ensure the quality of purified RNA for the successful microarray assay since cellular proteins, lipids and carbohydrates can interrupt the specific binding of fluorescent labeled cRNA to the array (Duggan et al., 1999). The Agilent 2100 Bioanalyzer can detect the quality of RNA by determining size and quantity of nucleic acids, providing both a gel-like image and electrophoretic data. The Agilent 2100 Bioanalyzer system is composed of microfluidics, capillary electrophoresis, and fluorescent dyes that attach to nucleic acids. Each disposable RNA chip contains micro-channels filled with gel for the separation of nucleic acid fragments based on their size. The small bench-top system determines purity, such as ribosomal RNA contamination and sample degradation of 12 RNA samples in a single assay. Along with the movement of nucleic acid fragments through microchannels, the nucleic acid fragments are bound to intercalating dye within the separating matrix and the fluorescence of these molecules is measured. Briefly, after preparing the gel with RNA 6000 Nano gel matrix and the Gel-Dye Mix included in the kit, the Gel-Dye Mix was loaded to RNA 6000 Nano Chips on the Chip Priming Station, which was followed by

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19 the loading of 5 ul of the RNA 6000 Nano Marker, 1 ul of heat denatured RNA 6000 ladder, and 1 ul of sample from each of the 12 samples into wells. After being vortexed for 1 min in the adapter at 2400 rpm, the chip was run in the Agilent 2100 bioanalyzer within 5 min. Microarray Assay cRNA Preparation Five micrograms of total RNA were converted into double-stranded complementary DNA (cDNA) using SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen, Carlsbad, CA). To initiate the first strand cDNA synthesis, the T7-Oligo (dT) promoter primer, containing a T7 RNA polymerase promoter sequence on the 5’end, (Affymetrix, Santa Clara, CA) was added to RNA samples and incubated at 70C for 10 min to break the secondary structure of RNA for primer hybridization. From an oligo-dT primer, SuperScript II RT (Invitrogen Life Technologies, Gaithersburg, MD), a reverse transcriptase, synthesized a strand of DNA complimetary to each mRNA molecule in several steps. The cDNA products were purified with the GeneChip Sample Cleanup Module (Affymetrix, Santa Clara, CA). The purified cDNA was used to generate a labeled cRNA in vitro transcription reactions using Enzo BioArray TM HighYield TM RNA Transcript Labeling Kit (Enzo Diagnostics, Farmindale, NY). Biotinylated antisense cRNA was cleaned with the GeneChip Sample Cleanup Module (Affymetrix, Santa Clara, CA) and a 15 ug aliquot of cRNA was fragmented to break down full-length cRNA to 35-200 base fragments by metal-induced hydrolysis in the fragmentation buffer provided with the GeneChip Sample Cleanup Module (Affymetrix, Santa Clara, CA) at 94C for 35 min. The concentration of the biotin-labeled cRNA was increased by

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20 evaporation using the SpeedVac to meet the required concentration for the fragmentation step. Array Hybridization Fragmented biotinylated cRNA samples were hybridized to GeneChip Rat Expression Array 230A (Affymetrix, Santa Clara, CA) chips at 45C for 16 hours with rotation at 60 rpm as recommended in the Affymetrix Expression Analysis technical manual (Affymetrix, Santa Clara, CA). Three control probe sets were added to the hybridization cocktail to enable information of the hybridization, washing, and staining procedures. The control probe sets were: (1) Control Oligonucleotide B2, which provides signals to the Affymetrix Microarray Suite software for the automatic grid alignment during image analysis; (2) Biotinylated Hybridization Controls bioB, bioC, bioD, which are the biotin synthesis pathway genes from the bacteria E.coli; and (3) cre, the recombinase gene from P1 bacteriophage. After washing the hybridized chip, a strepavidin phycoerythrin solution, which binds to the biotin for the strepavidin fluorescents on a laser scanner, was used to stain the chip. Final washing, staining, and scanning process were performed using the fluidics protocol of EukGE-WS2v4 in collaboration with Dr. Baker’s laboratory at the University of Florida. Data Analysis Image Analysis The scanned image files (*.dat file: a raw GeneChip image file) were analyzed with Affymetrix GCOS version 1.2 to generate .CEL files, which is a processed image file of signal intensities determined for each probe cell on the GeneChip. An expression matrix was generated using dCHIP, which is a software package for model-based analysis of oligonucleotide arrays (Li et al., 2003) in which Affymetrix .CEL files in an

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21 experimental group were used for a median chip invariant set normalization and then model-based expression intensity (MBEI) values were produced. The GeneChip Detection Algorithm was used to eliminate the probe sets indicated as absent on arrays. Unsupervised Analysis Cluster analysis was performed to see which genes behave similarly during the time course in the various conditions. After removing the probe sets indicated as absent on arrays, the coefficient of variation (the standard deviation divided by the mean) was calculated for each gene across all arrays. According to the coefficient of variation (CV), the probe sets with the greater CV value of 0.5 were ranked and subjected to hierarchical cluster analysis using variance normalized data in which the mean was normalized to 0 and the standard deviation to 1 across all arrays using dCHIP software. Supervised Analysis: Cross Validation and Permutation Analysis Supervised analysis was performed to study relationships between expression profile and experimental groups using BRB Array Tools. Probe sets whose signal intensities varied significantly across all the chips were identified using an F test at the p<0.001 levels. The probe sets were used as a classifier. Four algorithms (Diagonal Linear Discriminant Analysis, 1-Nearest Neighbor, 3-Nearest Neighbor, and Nearest Centroid) were used to predict the class of a given sample. The classifier was tested using leave-one-out cross-validation. Leave-one-out cross-validation was used to estimate the accuracy of the performance of four prediction models. Briefly, the entire samples are, in turn, divided into a test set that consists of a single sample and a training set that are the rest of the samples to predict the class of the test set by the construction of the prediction rule on only the training set. Percent correctly classified are given in the result table.

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22 The significance of the result of leave-one-out cross-validation was determined using permutation Monte Carlo simulations. Permutation analysis assesses the significance of prediction results for the identification of genes that can be used to distinguish between phenotypes based on expression level, providing a corresponding p value of each class prediction model used that indicate the significance of the result of the observed data. The expression profile of each gene was visualized using hierarchical clustering with expression that varied over the three time points as a continuum of color luminescence from green to red, representing the average multiple of change for each gene across the three time points using dCHIP software.

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CHAPTER 3 RESULTS Wound Area Previous research by Santosh Gowda in this lab showed that there was a significant difference between the ischemic PDGF treated and Vehicle treated groups in terms of wound area and healing rate. The tendency of wound healing in the experimental groups with wound areas from post-surgical day 0 to day 7 was shown in Figure 3-1. The non-ischemic experimental groups displayed the improved healing compared to the ischemic experimental groups. Three days post-surgery, there were statistically significant differences between the means of the 4 experimental groups at the p < 0.05 significance level in ANOVA analysis. Furthermore, multiple comparison analysis performed by LSD and Tukey HSD only detected statistically significant differences between Ischemic PDGF vs. Non-ischemic PDGF, Ischemic Vehicle vs. Non-ischemic Vehicle, and Ischemic Vehicle vs. Non-ischemic PDGF at a 95% confidence level. However, the tests failed to detect a statistically significant difference between Ischemic PDGF vs. Ischemic Vehicle and Non-ischemic PDGF vs. Non-ischemic Vehicle on post surgical day 3. The same statistical analysis was performed on post surgical day 7. In ANOVA analysis, the means of the 4 experimental groups were statistically significantly different at the 5.0 % significant level, but LSD and Tukey HSD tests failed to identify statistically significant differences in comparisons between Ischemic PDGF and Ischemic Vehicle 23

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24 and between Non-ischemic PDGF and Non-ischemic Vehicle at the 95% confidence level. 0.005.0010.00 35.00 IP IV 15.0020.00Wound Are 25.0030.00day 0day1day 2day 3day 4day 5day 6day 7day after surgerya (mm2 NP NV Figure 3-1. Rat skin healing profile in ischemic and non-ischemic (normal) wounds treated with PDGF or Vehicle, created with a 6-mm diameter punch. After daily topical application of Vehicle or PDGF, the wound areas were measured. (IP: Ischemic PDGF, IV: Ischemic Vehicle, NP: Non-ischemic PDGF, and NV: Non-ischemic Vehicle) Quantification and Quality of Total RNA The concentration and the ratio of spectrophotometric absorbance at a wavelength of 260 nm and a wavelength of 280 nm of the total RNA of one time series at day 7 were shown in Table 3-1. Similar results were obtained from the other samples.

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25 Table 3-1. The concentration of total RNA and the ratio of spectrophotometer absorbance at a wavelength of 260 nm to a wavelength of 280 nm of one time series at day 7 Sample Concentration (ug/ul) A260/A280 IP 1 3.14 1.93 IP 2 2.9 1.94 IP 3 3.41 1.95 IV 1 1.66 2.02 IV 2 2.02 1.91 IV 3 2.02 1.91 NP 1 1.66 1.95 NP 2 1.27 1.95 NP 3 2.61 2.03 NV 1 1.7 1.87 NV 2 1.8 2.00 NV 3 1.68 1.98 The Agilent 2100 Bioanalyzer was used to ensure the quality of purified RNA. A successful total RNA has 1 marker peak in fluorescence between 19 and 24 seconds and 2 distinct ribosomal peaks in fluorescence; no other bands should be observed between the 2 ribosomal peaks or below the 18S peak with a flat baseline (Deborah, 2001). Since quality of ribosomal RNA (rRNA), which is the majority of total RNA, is assumed to reflect that of messenger RNA (mRNA), mRNA quality can be assessed by the ratio between the 28S and 18S rRNAs. However, the optimal ratio can vary according to the tissue type and species as well as the RNA isolation technique. Bioanalyzer profiles of total RNA isolated from samples met the criteria mentioned above as successful total RNAs, showing high quality and integrity of all RNA samples (Figure 3-2, 3-3 and 3-4). Another important note, no genomic DNA contamination was found in RNA samples, which is commonly observed as a broad peak in the gel.

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26 18S 28S FluorescenceTime (seconds) 0 5 10 15 20 25 30 35 19 24 29 34 39 44 49 54 59 64 69 Figure 3-2. Electropherogram of the total RNA sample. Two well-defined peaks of the 18S and 28S ribosomal RNAs were observed.

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27 Figure 3-3. Electropherogram of the total Rmples. Two well-defined peaks of the 18S and 28S ribosomal RNAs were observed. NA sa

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28 FigurThe quality of unfragmented cRNAs was checked by Agilent Bioanalyzer in Figure 3-5. Similar results were obtained from the other samples. e 3-4. Total RNA of samples in a gel-like image. c RNA

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29 Figure 3-5. Purified and unfragmented Biotin-labeled cRNAs in a gel-like image showing the 9 samples that were used in the microarray experiments.

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30 FluorescenceTime (seconds) 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 Figure 3-6. Electropherogram of purified and unfragmented Biotin-labeled cRNAs Figure 3-7. Electropherogram of purified and unfragmented Biotin-labeled cRNAs

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31 Unsupervised Analysis Ce the . ised hierarchical cluster in Figure 3-8 shows the close cluste . day emic genes, luster analysis was performed to group genes whose expression patterns behavsimilarly during the time course in the various conditions. After removing the probe sets indicated as absent on all arrays, the coefficient of variation, the standard deviation divided by the mean, was calculated for each gene across all arrays. According tocoefficient of variation (CV), 121 genes, whose CV value were greater than 0.5, wereranked and subjected to hierarchical cluster analysis using variance normalized data inwhich the mean was normalized to 0 and the standard deviation to 1 across all arrays using dCHIP software. The hierarchical cluster pattern of the 121 genes is shown in Figure 3-8 Examination of the unsuperv ring of the chips based on the time after injury. The three controls on day 0 (non-wounded skin) chips were clustered together. 11 of the 12 chips on day 7 and day 3 wereclustered together. This means that the biggest factor influencing changes in gene expression was the time after injury, not the ischemic state or treatment with PDGFAlso, day 7 was closer to patterns of gene expression in normal non-injured skin than3 wounds. The chips clustered together based on the time, but not based on the ischstate or treatment with PDGF. There were three major patterns of the gene expression. About 35% of the which were low in day 0, showed increased expression at day 3 and likely to return to the levels of normal skin at day 7, relatively to the mean of their expression across all the chips. Also, approximately 57% of the genes in normal skin that showed increased expression became decreased at day 3 and showed the beginning of return to levels found in normal skin, relatively to the mean of their expression across all the chips.

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32 Interestingly, about 8% genes appeared to become turned on later in wound healing (day7) whereas about 35% of the genes increased expression strongly at day 3. dCHIP, whose gene expression changed the most among all 27 microaOne hundred and twenty-one genes (coefficient of variation > 0.5) were shown. The dendrogram at the top of the figure shows the similarity of gene column an experimental group. The color scale represents the extents of tIf the expression of the gene is higher than its mean expression value, thevehicle treated groups; NP: non-ischemic wounds PDGF treated groups; IVgroups; V: vehicle treated groups; P: PDGF treated groups; r1, r2, r3 = replicate number Figure 3-8. Unsupervised cluster analysis of the variance normalized dataset using rrays. expression patterns between chips. Each row represents a single gene and each he expression of the gene comparing to its mean expression value between chips. color is redder and if lower, then it is greener; NV: non-ischemic wounds : ischemic wounds vehicle treated groups; IP: ischemic wounds PDGF treated

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33 Supervised An alysis Supervised analysis was performed to study relationships between expression To, whegent inh cy olass prd to identify the genes thagroups. Four algorithms (Diagonal Linear D Neighbor, 3-Nearest Neighbor, and Nearest Ceven sample. The significance of the result one-ocross-lidatanrmtianLeave-one-out Cross-validation The accuracy of class prediction was estimated leavene-ooslionperformance of the prediction models during the leave-one-out cross-validation was summarized in Table 3-2 as percent correctly classifiedlano determine the effect of the PDGF treatment in different condition (ischemise point (day 0, day 3, and day7) resulted in a low F or classification rates of Diagonal Linear Discriminant Analysis, 1-Nearest Neighbor, 3profile and experimental groups using BRB Array ols re es tha dist guis the experimental groups are identified and the accura f c ediction based on gene expres use ssion profile is estimated. An F test wa t are differentially expressed among the experimental iscriminant Analysis, 1-Nearest ntroid) were used to predict the class of a gi f the prediction models was assessed by leave-o ut va ion d pe uta on alysis. by -o ut cr s-va dati . Sinceia, and PDGF treatment) that can influencechanges in the gene expression during the wound healing, the leave-one-out cross-validation was performed on every possible combination of the three factors. The there were three factors (time, ischem . Genera ly, the alysis tic or nonchemic state) at different tim percentage of performance from all prediction methods, with values ranging from 17% to 100 %. For example, a set of “Ischemic vs. Non-ischemic Wounds Treated with PDGVehicle at Day 3”, which determines the effect of the ischemia at day 3 between ischemic and non-ischemic wounds with PDGF treatment, showed the lowest performance that the

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34 Nearest Neighbor, and Nearest Centroid were 17%, 25%, 17%, and 17%, respectively. A set of “Ischemic vs. Non-ischemic Wounds Treated with Vehicle at Day 3”, which determines the effect of ischemia at day 3 between ischemic and non-ischemic wounds without PDGF treatment, also showed high misclassification rates of 83%, 33%, 50%and 50%. However, the analysis to determine the effect of the ischemia at day 7, regardless of treatment, showed relatively higher classification rates (100%, 92%, 92%, and 92%) of performance from all prediction models, which means there is diffe , rence betwer (100%, 89%, 89%, and and PDGF treatment), at least 16 genes out of 15,923 genes are expected to be differentially expressed with p < 0.001, simply due to the large number of genes beaPetedifference in experimental groups for theidneen phenotypes based onevformed generating experimentally dep-es that indicate the significance of the result of the observed data. The re 3-3. The relationship between non-ischemore diexsmall p-values is unlikely hedical effect beingte en ischemic wounds and non-ischemic wounds at day 7 at the p < 0.001 significance level. Also, the classification rate for the set of “Time Points in Non-ischemic Wounds Treated with Vehicle” was a relatively highe 89%). Although there is no effect from any factor out of three factors (time, ischemia, ing nalyzed. ermutation analysis To d rmine the significance of the entificatio of genes that can be used to distinguish betw xpression le el, permutation analysis was per termined valu esult of perm utation analysis is shown in Tabl ic (n mal) wounds and time was stronger than expected due to chance. Th fferential pression observed in those genes with very to ave occurr by chance, and therefore has resulted from the biolog sted.

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35 Table 3-2. Summary o f cross-validation analysis Factors Control (Normal ns) Group DLDA (%) 1-NN (%) 3-NN(% ski ) NC (%) Ischemic vs. Non-ischemic Wounds at Day 7 N 2 100 92 9 2 92 Isoehicle N 2 83 83 83 oy 7 N 4 33 42 33 3 N 2 83 67 67 I N 2 83 33 50 Io4 17 25 17 heon-ischemic Wounds N 2 88 83 79 89 89 Time Points i Time Points ined with Vehicle Y 3 78 78 89 78 Ts in3 89 89 78 67 67 Y 5 67 73 53 PDGF or Vehicle Y 9 30 41 41 s.cle Treated Wounds at Day 3 N 2 25 50 42 .N 2 50 33 50 chemic vs. N n-ischemic Wounds Treated with V at Day 7 83 Ischemic vs. N n-ischemic Wounds Treated with PDGF or Vehicle at Da 58 Ischemicsch No vs. Non-ischemic Wounds at Day 75 emic vs. n-ischemic Wounds Treated with Vehicle at Day 3 n-ischemic Wounds Treated with PDGF 50 schemic vs. N or Vehicle at Day 3 N 17 Isc mic vs. N 75 Time Points i n Non-ischemic Wounds Treated with Y 3 100 Vehicle 89 n Non-ischemic Wounds Treated with PDGF Y 3 89 89 89 Ischemic Wounds Treat 89 ime Point Ischemic Wounds Treated with PDGF Y 78 Time Points in Ischemic vs. Non-ischemic Wounds Y 5 60 Treated with Vehicle 67 Time Points i n Ischemic vs. Non-ischemic Wounds Treated with PDGF 67 Time Points i n Ischemic vs. Non-ischemic Wounds Treated with 37 PDGF v Vehi 50 PDGF vs Vehicle Treated Wounds at Day 7 42 Pctd. NV: non-ischemic wounds vehicle treated groups; NP: non-isc wounds PDGF treated groups; IV: ischemic wounds vehicle treated groups; IP: ischemic wounds P ghicle treated groups; P: PDGF treated groups; DLDA: DiagonaLinear Discriminant Analysis; 1-NN: 1-Nearest Neighbor; 3-NN: 3-Nearest Neighbor; NC: No Table 3-3. Thes of each prediction model based on 2000 random permutatioControl Group DLDA (%) 1-NN (%) 3-NN (%) N( ercent corre ly classifie hemic DGF treated roups; V: ve l earest Centr id e p-valu ns Factors C %) Time Points ea0 in Non-ischemic ted with Vehicle Y 3 0.001 0.003 0.007 Wounds Tr .007 DonNearest Neighbor; 3-NN: 3-NearNC: o-2) pa3), the set of “Time Points in Non-ischemic Wounds Treated with Vtion a pet, was chosen as a set being further examined t LDA: Diagei al Linear Discriminant Analysis; 1-NN: 1-entroid est ghbor; N Nearest C Based n the result of the leave-one-out cross-validation analysis (Table 3 and ermutation naly sis (Table 3ehicle”, which has shown the second highest successful classifica rate cross every ossible combination s o

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36 identify genes which w ere upor down-regulated in three time points (Table 3-4). The set of “ischemic wounds at day c due to the lack of time points to be com. Teant differentially expressed at three time points; day 0, day 3 and, day 7 at the 0.001 level. List of the 691 genes and their no lo expression in non-ischemic woutreated with Vehicle at day 0, day 3, ahnes among the 691 genes that were dshemic wounds over thretidTable 3-4. Ge in which expression level increased more than 3-fold in non-ischeal skin) Change (0 vs. 3) ic and non-ischem 7”, which has shown the highest successful lassification rate, was not further analyzed pared he 691 gen s were determined as signific rmalized g-transformed median-centered gene nds nd day 7 were summarized in Appendix. More t an 3-fold up or down-regulated ge etermined a significant differentially expressed in non-isc e me points ( ays 0, 3, 7) were summarized in Table 3-4~3-7. nes mic wounds at day 3 relative to the controls (norm Accession # Gene Title Fold AB001382 secr eted phosphoprotein 1 26.59 AI764437 --22.76 NM_053647 chemokine (C-X-C motif) ligand 2 N 0 calcium binding protein A9 (calgranulin B) N1 X73371 Fc receptor, IgG, low affinity IIb 9.82 M60616 --9.70 NM_053819 Nschlafen 3 BI275261 --Feptor, IgG, low affinity III seory leukocyte protease inhibitor -Sr to Small inducible cytokine A6 precursor (CCL6) (C10 protein) (L287910), mRNA Sr to MS4A6B protein (LOC293749), mRNA Si), mRNA S -SimRNA 14.79 M_053587 S10 13.76 NM_053843 Fc receptor, IgG, low affinity III 12.30 M_13074 lipocalin 2 10.43 BF395317 Similar to MS4A6D protein (LOC361735), mRNA 9.66 NM_031530 chemokine (C-C motif) ligand 2 9.61 tissue inhibitor of metalloproteinase 1 9.539.12 M_053687 8.33 AI170394 7.92 NM_053843 c rec 7.70 NM_053372 cret 7.69 BE098739 7.39 BE095824 imila OC 7.09 BI294706 imila 6.71 AI577849 milar to Carboxypeptidase X 1 (M14 family) (LOC296156 6.52 BF411036 imilar to interferon regulatory factor 7 (LOC293624), mRNA 6.20 BI275261 6.03 BF393825 milar to RIKEN cDNA 3110037K17 (LOC362431), 5.97

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37 Table 3-4 Continued A ccession # Gene Title FoldChange (0 vs. 3) BF396602 seizzled-related protein 2 creted fr 5.97 NM_133523 m metalloproteinase 3 imnoglobulin superfamily, member 6 inkin 1 beta al prnthase 2 Si292594), mRNA Fc receptor, IgE, high affinity I, gamma polypeptide D 7 S361422), mRNA C Si homologous to two hukDa proteins; ORF (L killer cell lectinfamily A, member 5 mse) li al Si), mRNA --ap le ar nkin 6 -cootein 1A inkin 1 receptor-like 1 he -ly -Si interferon induced trn); interferon induced transmembrane prNA SiNA ni Sirsor (PF-4) (CXCL4) (LOC360918), mRNA m malactosamine specific lectin 1 so carrier family 7 (cationic amino acid transporter, y+ system), member 7 U22414 chemokine (C-C motif) ligand 3 3.64 AA849399 cathepsin Y 3.64 NM_019370 ectonucleotide pyrophosphatase/phosphodiesterase 3 3.62 atrix 5.94 NM_133542 mu 5.93 NM_03151296 terleu 5.87 NM_0171 lograft inflammatory factor 1 5.85 U03389 ostaglandin-endoperoxide sy 5.79 BF282961 milar to gp49B2 (LOC 5.73 BE111722 5.71 AI102519 AP12 5.31 AI41105 imilar to coactosin-like 1; coactosin-like protein (LOC 5.28 NM_012523 D53 antigen 5.22 AW531805 milar to This ORF is capable of encoding 404aa which is kDa and 56 man interferon-inducible proteins, 54309526), mRNA OC 4.84 U56824 -like receptor, subatrix metalloproteinase 9 (gel 4.83 NM_031055 atinase B, 92-kDa type IV collagena 4.77 BF289368 popolysaccharide binding protein do-keto reductase family 1, member B8 4.71 AI233740 4.62 BG378630 milar to onzin (LOC360914 4.49 BI286411 4.49 BF288130 4.37 NM_012907 olipoprotein B editing complex 1 4.35 AF154349 gumain se 1 4.27 NM_017134 gina 4.22 NM_012589 i terleu 4.12 AI406660 n, actin binding pr 4.08 NM_130411 roni 4.05 NM_013037 terleu 4.04 NM_012580 me oxygenase (decycling) 1 4.03 BI296317 3.97 L12458 sozyme 3.93 BF389682 -3.92 AA892854 r to interferon induced transmembrane protein 2 like; 3.90 BG380285 mila ansmembrane protein like 2 (humaotein 2 like (human) (LOC293618), m Rmilar to macrosialin (LOC287435), mR 3.89 AI177761 3.88 U72660 njurin 1 3.87 AI169104 milar to Platelet factor 4 precu 3.81 NM_012862 atrix Gla protein 3.80 BE116084 3.79 NM_022393 acrophage galactose N-acetyl-g 3.78 AF200684 lute 3.73

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38 Table 3-4 Continued A ccession # Gene Title FoldChange(0 vs. 3) NM_030845 chne (C-X-C motif) ligand 1 emoki 3.54 NM_053822 Scium binding protein A8 (calgranulin A) coement component factor h -C an Srecursor mouse (LOC293154), mRNA -le binding protein 50 m su ca gootropin inducible ovarian transcription factor 1 ge Si precursor (LOC290644), mRNA pu -Rocus Ba ch SiveOC299783), mRNA m l -coor 1 R 100 cal 3.53 NM_130409 mpl 3.53 BF284262 3.38 AI408440 3.38 NM_021744 D14 antigen 3.37 L81174 kyrin repeat domain 1 (cardiac muscle) 3.36 BI274054 imilar to folate-binding protein 2 p 3.31 AA875124 3.31 AF065438 ctin, galactoside-binding, soluble, 3 3.25 NM_1343 yxovirus (influenza virus) resistance 2 3.20 BG671549 peroxide dismutase 2, mitochondrial 3.17 NM_017320 thepsin S 3.17 NM_133563 nad 3.14 D87927 ne model 1960, (NCBI) 3.14 BM389261 milar to lysosomal thiol reductase 3.12 AA819034 tative ISG12(b) protein 3.10 BG379319 3.10 BG378249 T1 class II, l 3.07 AF084544 ondroitin sulfate proteoglycan 2 (versican) genesis-related 1 (glioma); related to testes-specific, 3.06 BF287967 milar to GLI patho spid, and pathogenesis proteins (L 3.05 AI407953 metalloproteinase 9 (gelatinase B, 92-kDa type IV collagenase) 3.04 NM_031055 58 g atrix 3.03 NM_0193 ycoprotein 38 3.02 AI179422 3.02 NM_053619 mplement component 5, recept 3.01 Y00480 T1 class II, locus Da 3.00 Tnes in which expression level decreased more than 3-fold in non-isch ucontrols (normal skin) C (0) able 3-5. Ge emic wo nds at day 3 relative to the Accession # Gene Title Fold hange vs. 3 AI175539 p arvalbumin 8.85 AW919180 ---7.17 NM_012949 ---6.91 4 actinin alpha 3 NM_13342--BI2transporting, cardiac muscle, fast twitch 1 sin binding protein C, fast-type (LOC292879), mRNA onin 1, type 2 NM_012786 Cytochrom c oxidase subunit VIII-H (heart/muscle) -5.17 -6.62 -6.53 BI275633 76959 --6.27 AI407239 ---6.07 NM_058213 ATPase, Ca++ ilar to Myo -5.99 BG378588 NM_017185 Simtrop -5.59 -5.20

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39 Table Accession # Gene Title Change 3) 3-5 Continued Fold (0 vs. AJ243304 triadin -5.08 NM_012530 ---5.07 BF395095 ---5.06 BF521859 ---5.04 J02811 adenosine monophosphate deaminase 1 (isoform M) -4.97 AF372216 tropomyosin 1, alpha AI717476 muscle glycogen phosphorylase -4.37 NM_019292 carbonic anhydrase 3 -4AA997590 Similar to osteoglycin precursor (LOC291015), mRNA -NM_012505 ATPase, Na+K+ transporting, alpha 2 -4.05 AI598442 ---4.05 NM_012605 myosin, light polypeptide 2 -3.94 AI177059 Similar to RIKEN cDNA 1110007F23 (LOC287382), mRNA -3.91 BG663128 Similar to TROPONIN C, SKELETAL MUSCLE (STNC) (LOC296369), mRNA -3.89 BE111310 ---3.84 BF285350 Similar to APOBEC-2 protein (LOC301226), mRNA -3.81 NM_019131 tropomyosin 1, alpha -3.80 AA799471 ---3.77AA800892 ---3.74AF370889 tropomyosin 1, alpha BI296037 --NM_017328 phosphoglycerate mutase 2 -4.88 -4.68 BI294983 ---4.45 D29960 heat shock protein, alpha-crystallin-related, B6 -4.34 .23 4.05 AF399874 troponin T1, skeletal, slow -3.84 NM_012840 ---3.81 -3.73 -3.72 AI59BI27BM389619 myosin binding protein C, slow type -3.58 L46791 carboxylesterase 3 -3.48 AA945955 ---3.36 -3.21 -3.17 myoglobin -3.10 ---3.08 M_020104 fast myosin alkali light chain -3.00 M_017156 ---3.00 8315 ---3.60 7586 myosin, heavy polypeptide 4 -3.58 NM_012812 cytochrome c oxidase, subunit VIa, polypeptide 2 -3.52 AI104354 Similar to FATZ related protein 2 (LOC295426), mRNA -3.48 AI169092 thyroid hormone responsive protein -3.36BF420810 histidine rich calcium binding protein -3.26 BI291434 phosphofructokinase, muscle BI277545 type 2X myosin heavy chain NM_021588 AI577508 NN

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40 Tablewounds at day 7 relative to the controls (normal skin) Accession # Gene Title Change 7) 3-6. Genes in which expression level increased more than 3-fold in non-ischemic Fold (0 vs. AA866443 --16.6 2 AI764437 --11.69 AA965084 --9.14 AB001382 secreted phosphoprotein 1 M60616 --8.74 6.90 NM_133537 extracellular proteinase inhibitor 6.75 NM_053587 S100 calcium binding protein A9 (calgranulin B) 6.35 NM_053843 Fc receptor, IgG, low affinity III 6.31 AA892854 --6.24 BF396602 secreted frizzled-related protein 2 6.08 L81174 ankyrin repeat domain 1 (cardiac muscle) 5.85 NM_053372 secretory leukocyte protease inhibitor 4.76 BF289368 lipopolysaccharide binding protein 4.71 AI170394 --4.68 NM_053819 tissue inhibitor of metalloproteinase 1 4.67 NM_031530 chemokine (C-C motif) ligand 2 4.19 NM_053843 Fc receptor, IgG, low affinity III 3.92 BE098739 --3.76 NM_130741 lipocalin 2 3.64 AI411057 Similar to coactosin-like 1; coactosin-like protein (LOC361422), mRNA 3.54 AI102519 DAP12 3.34 X73371 Fc receptor, IgG, low affinity IIb 3.34 U56824 ily A, member 5 3.23 L124BE1NM_013151 plasminogen activator, tissue 3.03 (LOC287910), mRNA AI577849 Similar to Carboxypeptidase X 1 (M14 family) (LOC296156), mRNA 3.30 AA875124 --3.30 killer cell lectin-like receptor, subfam 58 lysozyme 3.21 08345 procollagen, type XII, alpha 1 3.20 BI294706 Similar to MS4A6B protein (LOC293749), mRNA 3.18 BI286411 --3.14 BF284262 --3.10 NM_017196 allograft inflammatory factor 1 3.08 BE095824 Similar to Small inducible cytokine A6 precursor (CCL6) (C10 protein) 3.01 NM_133542 immunoglobulin superfamily, member 6 3.00 Table 3-7. Genes in which expression level decreased more than 3-fold in non-ischemic wounds at day 7 relative to the controls (normal skin) Accession # Gene Title Fold Change (0 vs. 7) AI175539 parvalbumin -3.18 NM_133424 actinin alpha 3 -3.16 4 BI275633 ---3.0

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41 At day 3, there were 92 genes whose expression were increased, and 52 genes decreased, at least 3-fold relative to the controls (normal skins), which might suggest that there are m ore genes in enhanced expression than in decreased expression at day 3 in respo least onally, it in 1 aling pathway. However, the expressions of parvalbumin #AI175539 and troponin 1, type 2 #NM_017185, which is involved in muscle devactin bindimuscle, fasAt dathan 3-fold comcontrols (normal skins), and those 34 genes were decreased when 8345, which is intion between extracellular matrix molecules and cells, show2-fold and increaspntond re nse to injury. Of the 24 (26%) known genes, 6 are known to be involved in cytokine activity, such as secreted phosphoprotein 1 #AB001382, chemokine (C-X-C motif) ligand2 #NM_053647, chemokine (C-C motif) ligand 2 #NM_031530 and 3 #U22414, interleukin 1 #NM_031512, and interleukin 6 #NM_012589 were up-regulated at3-fold in expression; the rest of genes are involved in receptor activity, transporter activity, metalloendopeptidase inhibitor activity, and calcium ion binding. Additiwas a noticeable increase in expression (26-fold change) for secreted phosphoprote#AB001382 that is involved in TGF-Beta sign elopment and muscle contraction, actinin alpha 3 #NM_133424 associated to ng, and transport related genes, such as ATPase, Ca +2 transporting, cardiac t twitch 1 #NM_058213, were down-regulated at day 3. y 7, only the 3 genes were suppressed and 34 genes were increased more pared to the compared to day 3 in response to injury. However, 1 type XII procollagen #BE10volved in the interac ed 3. 1.8-fold e in ex ressio relative day 0 a day 3, spectively.

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42 0 5 10 15 ch 20 25 30 03 7Day after surgery Fold ang e secretedphosphoin 1(AB001382 prote ) unknown (I764437) A chemokine-X-Cmotif) ligan 2(NM_0536) (Cd 47 S100 calcium bindingprotein A9 (calgranulinB) (NM_053587) iff Figure 3-9. The expression profiles of four selected genes with the largest derenexmong three timint91 gnes. wny unknown function of genes (71%) with at least 3-fold change in ext d 7 relative to nl sthereore a trend in the overall gene expression over three time points in response to rat skin injury were emphasized and shogu at tharly stage in wounds in the overall differential gesi coning presson. tial pression a e po s of 6 e There ere ma pression a day 3 an orma kins, f wn in Fi re 3-10. An increase e e ne expres on was followed by a tinu sup i 0 10 20Gen 30 wit 40at 50Days after syesh least 3-han 80 90ge 100 6070fold C Increased Dec rea sed 3 7 urger Figure 3-10. Genes with at least a 3-fold change in expression relative to control (normal krat skin injury s in) in response to

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43 The e xpile of each geaalized using hierarchical clustering of 691 genes with expression that varied over the three tim points continm olumcem green (low expression) to termediate level of expression) topression), representinthe avrage multiple of chor ea gens thee0, 3, and 7) igure 3-11. About 63 % of the genes that were low relative to their own expression in normal skin increased significantly at day 3 and began to return to levels of normal skial skin that showreased expression ecame decreased at day 3 and showed the tendency of return to levels found in normal skin at day 7. Notably, approximately 3% of the genes appeared to become turnd on lateat day 7whrogenererease relative their ow expresion at day 3. 6sified functional categories based on GeneOntology database with the probability of obtaining gene members of similar gene ontology within the lused beracal clustering in Table 3-8, which indicates the significance of the cluster by the functional genes. In general, genes invchtory resok activity and negative regulation of cell proliferation were consistently up-regulated relatively to the control (dayThe oin functional groups was shown in Figure 3-12. ression prof ne w s visu e as a uu f color inescen fro black (an in red (high ex g e ange f ch e acros three tim points (day n Fi n at day 7. Also, about 33% of the genes in norm ed inc relative to their own expression b e r ereas app ximately 63% of the es w inc d to n s Those 91 genes were clas into major c ters as p-value obtain y hi rchi olved in emotaxis, inflamma ponse, immune response, chem ine activity, plasminogen activator 0). number f genes

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44 e genesemic Figure 3-11. Hierarchical clustering patterns. Six hundred andn, wgene expression changednghipischwounds), were clustered hierarchically into groups on the basis of the similarity of their xprofiles using dC sore. The dendrogram at the top of the figure shows the similarity neessio patternsbetweenhips. Eah row represents a single gene and eaolum an experimental group. The cothe extents of the expression of the gene comparing to itsn value ben s. If the expression of the gene is ean expression value, the color is redder and if lower, then it er. ninety-os (nonhose the mo st amo all 9 c e pression HIP ftwa of ge expr n c c ch c n lor scale represents mean expressio etwe chip higher than its m is green

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45 Table 3-8. Gectiocateies bed on GeOntoloy and umetric probabilities in the 4363 functionally annotated Functional Accession F(0 F(0 Ges from Functional Group in Cluster Annotated genes in Cluster Functional GGenes P value nes classified into fun nal gor as en g cgenes on the array mulative hypergeo Group/ Gene Name C vs.3) C vs.7) ne roup Glutamate-ammonia ligase 3 254 3 0.000195 BI27529 BI27529 Pase 254 0.000153 -6.53 -3.04 lase -4.37 -2.41 oprotein 1 26.59 etic protein 4 -1.60 -1.26 -C motif) 14.79 1.68 d okine (C-C motif) ligand 9.61 4.19 N Ear m 14 254 0.000127 rich rotein -1.55 -1.19 A2-1.08 or of inase 1 9.53 4.67 -1.55 -1.27 NM_022605 heparanase 2.50 1.69 Nmatrix metalloproteinase 12 3 5 N matrix mse 3 matrix metalloproteinase 9 92-kDa type IV lagenase) d polypeptide 44 glutamine synthetase 1 glutamine sy 2.01 2.03 1.25 1.19 nthetase 1 glutamine synthetase 1 BI275294 1.95 1.23 hosphoryl activity 4 6 BI275633 AI102495 nucleo side phosphorymuscle glycogen 1.90 1.40 AI717476 phosphorylase AW919180 -7.17 -2.84 Cytokine activity 11 254 54 0.000214 NM_031051 macrophage migration inhibitory factor interleukin 6 1.40 1.11 NM_012589 4.12 1.63 NM_031512 interleukin 1 beta secreted ph 5.87 1.81 8.74 AB001382 osphNM_012827 bone morphogen chemokine (C-C motif) ligand3 chemokine U22414 3.64 1.45 (C-Xligand 12 AF189724 1.43 2.03 chemokine (C-X-C motif) ligand 2 NM_053647 chemokine (C-C motif) ligan5 NM_031116 1.50 1.62 NM_031530 chem 2 M_017113 granulin xtracellul 2.15 1.49 atrix 78 D28875 glycop secreted acidic cysteine B001382 secreted phosphoprotein 1 biglycan 6.59 8.74 NM_017087 1.39 NM_053819 metalloproteNM_012774 glypican 3 tissue inhibit M_053963 1.7 1.4 M_133523 etalloproteina 5.94 1.58 NM_031055 3.03 1.56 (gelatinase B,collagenase) matrix metalloproteinase 9 (gelatinase B, 92-kDa type IV col NM_031055 4.77 2.49 transforming growth factor, 1.91 1.42 NM_021578 beta 1 AA893484 BE108345 fibronectin 1 procollagen, type XII, alpha 1 2.30 1.78 1.97 3.20 lamina-associate U20286 1.65 1.34 1C

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46 Taon FC (0FC (0 Ges fr Functional Group in Cluster Annotated genes in Cluster Functional Goup Genes P value ble 3-8 C tinued neom Functional r Group/ Accession Gene Name vs.3) vs.7) L 254 0.000544 ysosome 9 42 N7 NM_017125 1.83 1.50 in rane 5 -1.14 BM383531 1.08 -1.61 Hn c 254 0.000195 Nmoglobin beta chain Cytoskeleton 13 254 0.000097 -1.60 -1.45 ha -3.80 -1.61 ha -4.68 -1.79 1, alpha --N-3.94 -1.63 1 NM NM_021261 1.40 1.57 Chis 254 0.000003 and 9.61 4.19 NM_053822 m binding protein A8 (calgranulin A) 3.53 2.32 complement component 5, receptor 1 3.01 1.89 chemokitif) ligand 2 chemokine (C-X-C motif) ligand 12 1.43 2.03 NM_134350 s (influenza virus) resistance 2 3.20 1.24 M_02259 cathepsin B 1.74 1.34 NM_134334 cathepsin D CD63 antigen 1.73 1.39 NM_017320 cathepsin S 3.17 2.60 NM_053538 lysosomal-associated protetransmemb 2.75 1.98 NM_012732 lipase A, lysosomal acid 1.66 1.30 AI232474 cathepsin L 2.09 1.37 AF411318 Metallothionein 1.56 --omplex he emoglobi 3 3 M_033234 1.78 1.29 complex X05080 --1.70 1.19 BI287300 --2.80 1.57 67 NM_030863 moesin thymosin 1.80 1.46 BG668902 AI104913 beta-4 tropomodulin 1.51 1.47 1 myosin 4 NM_012678 tropoNM1 1.58 1.26 _01913 tropomyosin 1, alp AF372216 AF370889 tropomyosin 1, alptropomyosin 3.73 1.47 M_012605 myosin, light polypeptide 2 BM389673 cofilin _022511 1.74 1.68 1.35 1.39 profilin 1 Janus kinase 2 --NM_031514 2.10 1.44 BF281185 --2.09 1.56 emotax 8 18 NM_031530 2 S100 calciu chemokine (C-C motif) lig NM_053619 NM_053647 ne (C-X-C mo 14.79 1.68 AF189724 NM_013085 plasminogen activator, urokinase 1.53 1.48 U22414 chemokine (C-C motif) ligand 3 3.64 1.45 NM_031116 chemokine (C-C motif) ligand5 1.50 1.62 Defense response 8 254 31 0.000289 NM_012512 beta-2 microglobulin myxoviru 1.78 1.48

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47 Taon (0FC (0 Gs fr Functional Group in Cluster Annotated genes in Cluster Functional GGenes P value ble 3-8 C tinued Functional Group/ Accession Gene Name vs.7) eneom FC vs.3) roup N myxovirus (influenza virus) resistance 2 1.93 1.61 M_017028 BI285141 n 1.90 1.40 NM_021578 transforming growth factor, beta 1 1.91 1.42 AF065147 CD44 antigen 2.19 1.48 X57523 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) 1.62 1.25 X52711 myxovirus (influenza virus) resistance 1 2.31 1.45 Inflammatory response 10 254 39 0.000053 AB001382 secreted phosphoprotein 1 26.59 8.74 NM_031051 macrophage migration inhibitory factor 1.40 1.11 NM_031530 chemokine (C-C motif) ligand 2 9.61 4.19 NM_031512 interleukin 1 beta 5.87 1.81 NM_021744 CD14 antigen 3.37 1.68 NM_053619 complement component 5, receptor 1 3.01 1.89 NM_053647 chemokine (C-X-C motif) ligand 2 14.79 1.68 U22414 chemokine (C-C motif) ligand 3 3.64 1.45 NM_031116 chemokine (C-C motif) ligand 5 1.50 1.62 NM_021578 transforming growth factor, beta 1 1.91 1.42 Immune response 19 254 66 0.00000 CD74 antigen (invariant antigen-associated) NM_080767 proteosome (prosome, macropain) subunit, beta type 8 2.47 1.64 NM_031530 chemokine (C-C motif) ligand 2 9.61 4.19 NM_021744 CD14 antigen 3.37 1.68 NM_053647 chemokine (C-X-C motif) ligand 2 14.79 1.68 NM_057194 phospholipid scramblase 1 2.02 1.32 NM_012589 interleukin 6 4.12 1.63 NM_017028 myxovirus (influenza virus) resistance 2 1.93 1.61 AF189724 chemokine (C-X-C motif) ligand 12 1.43 2.03 U22414 chemokine (C-C motif) ligand 3 3.64 1.45 NM_031116 chemokine (C-C motif) ligand 5 1.50 1.62 NM_130399 adenosine deaminase 1.68 1.45 AI599350 proteosome (prosome, macropain) subunit, beta type 9 2.78 1.72 X52711 myxovirus (influenza virus) resistance 1 2.31 1.45 CD24 antige NM_013069 polpypeptide of major histocompatibility class II 2.55 2.13

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48 Table 3-8 Continued Functional Group/ Accession Gene Name FC (0 vs.3) FC (0 vs.7) Genes from Functional Group in Cluster Annotated genes in Cluster Functional Group Genes P value NM_134350 myxovirus (influenza virus) resistance 2 3.20 1.24 BG668902 thymosin beta-4 1.51 1.47 BEchemokine (C-C motif) ligand NM_053647 ligand 2 14.79 1.68 chemokine (C-C motif) ligand 5 3 0.000195 U54791 2.76 1.88 AA Ferric iron binding 3 254 4 0.000747 inhibitor, member 1 Negative regulation of cell U03389 5.79 1.42 NM_031590 WNT1 inducible signaling 1.06 1.60 NMbeta 1 195 alpha 1 polypeptide 110597 Fc receptor, IgG, alpha chain transporter 2.59 1.61 X57523 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) 1.62 1.25 NM_031512 interleukin 1 beta 5.87 1.81 Chemokine activity 5 254 10 0.000127 NM_031530 2 9.61 4.19 chemokine (C-X-C motif) AF189724 chemokine (C-X-C motif) ligand 12 1.43 2.03 U22414 3 3.64 1.45 NM_031116 chemokine (C-C motif) ligand 1.50 1.62 Neuronal cell recognition 3 254 chemokine (C-X-C motif) receptor 4 945737 chemokine (C-X-C motif) receptor 4 2.07 1.60 AA945737 chemokine (C-X-C motif) receptor 4 2.08 1.61 L01122 ferritin light chain 1 2.75 2.09 NM_012848 ferritin, heavy polypeptide 1 1.98 1.41 AF372216 tropomyosin 1, alpha -4.68 -1.79 Plasminogen activator activity 3 254 4 0.000747 NM_013151 plasminogen activator, tissue 2.57 3.03 NM_012620 serine (or cysteine) proteinase 2.81 1.31 NM_013085 plasminogen activator, urokinase 1.53 1.48 proliferation 4 254 8 0.000652 prostaglandin-endoperoxide synthase 2 NM_031514 Janus kinase 2 2.10 1.44 pathway protein 2 _021578 transforming growth factor, 1.91 1.42 Nitrogen fixation 3 254 3 0.000BI275294 glutamine synthetase 1 2.01 1.25 BI275294 glutamine synthetase 1 1.95 1.23 BI275294 glutamine synthetase 1 2.03 1.19 Hydrolase activity 38 254 376 0.000419 M28647 ATPase, Na+/K+ transporting, 1.51 1.19 NM_022597 cathepsin B 1.74 1.34

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49 Table 3-8 Continued Functional Accession (0 vs.3) (0 vs.7) Genes from Group in Cluster Annotated Cluster FunctionaGenes Group/ Gene Name FC FC Functional genes in l Group P value NM_134334 cathepsin D 1.73 1.39 NM_080767 macropain) subunit, beta type 2.47 1.64 NMNM_012732 lipase A, lysosomal acid 1.66 1.30 apolipoprotein B editing NM_057104 pyrophosphatase/phosphodiest-2.00 -1.73 NM_031055 (gelatinase B, 92-kDa type IV 3.03 1.56 bone marrow stromal cell NM_130399 adenosine deaminase 1.68 1.45 9 12505 ATPase, Na+K+ transporting, alpha 2 -4.05 -2.40 NM_017320 cathepsin S 3.17 2.60 NMNM_02435urokinase J02811 adenosine monophosphate deaminase 1 (isoform M) -4.97 -2.04 proteosome (prosome, 8 _013151 plasminogen activator, tissue 2.57 3.03 NM_058213 ATPase, Ca++ transporting, cardiac muscle, fast twitch 1 -5.99 -2.27 NM_013143 meprin 1 alpha -1.43 -1.09 NM_017134 arginase 1 4.22 1.91 NM_012907 complex 1 4.35 2.07 NM_053591 dipeptidase 1 (renal) -1.55 -1.32 NM_053963 matrix metalloproteinase 12 1.73 1.45 ectonucleotide erase 2 NM_133523 matrix metalloproteinase 3 5.94 1.58 D30795 CD38 antigen 2.11 1.42 matrix metalloproteinase 9 collagenase) NM_021576 5 nucleotidase 1.71 1.10 NM_030848 antigen 1 2.05 1.52 NM_133572 cell division cycle 25B 1.49 -1.06 NM_053311 ATPase, Ca++ transporting, plasma membrane 1 1.69 1.04 AI599350 proteosome (prosome, macropain) subunit, beta type 2.78 1.72 AI232474 cathepsin L 2.09 1.37 U69550 phospholipase D1 1.58 1.42 M10072 --2.40 1.52 NM_053290 phosphoglycerate mutase 1 1.59 1.21 NM_0 _053883 dual specificity phosphatase 6 1.72 1.18 6 --2.72 1.40 U84410 caspase 3 2.00 1.63 NM_012593 kallikrein 7 1.20 1.87 M60616 --9.70 6.90 BI294841 --1.63 1.56 BF288130 --4.37 2.61 NM_031055 matrix metalloproteinase 9 (gelatinase B, 92-kDa type IV collagenase) 4.77 2.49 NM_013085 plasminogen activator, 1.53 1.48

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50 Table 3-8 Continued Functional Accession (0 vs.3) (0 vs.7) Genes from Group in Cluster Annotated Cluster FunctionaGenes Group/ Gene Name FC FC Functional genes in l Group P value IgG receptor 3 254 3 0.000195 NM_053843 Fc receptor, IgG, low affinity 12.30 6.31 NM_053843 Fc receptor, IgG, low affinity III 7.70 3.92 transporter Retinol binding 3 254 4 0.0NM_012733 cellular 2.22 2.45 NM_012640 retinol binding protein 2, 2.49 2.28 AA858962 retinol binding protein 4 -2.44 -1.94 NM_053843 Fc receptor, IgG, low affinity III 12.30 6.31 NM_053843 III 7.70 3.92 BE110597 Fc receptor, IgG, alpha chain 2.59 1.61 III BE110597 Fc receptor, IgG, alpha chain 2.59 1.61 00747 retinol binding protein 1, cellular IgG binding 3 254 3 0.000195 Fc receptor, IgG, low affinity transporter 0510152025303540Glutamate-ammonia ligasePhosphorylase activity Cytokine activityacellular matrixLysosomeHemoglobin complexNitrogen fixationRetinol bindingFunctional GroupNumber of Genes ExtrCytoskeletonChemotaxisDefense responseInflammatory responseImmune responseChemokine activityNeuronal cell recognitionFerric iron bindingPlasminogen activator activityNegative regulation of cellHydrolase activityIgG receptorIgG binding Figure 3-12 Functional categories of genes using hierarchical clustering analysis

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CHAPTER 4 DISCUSSION Gene expression profiling of wound healing in the skin using microarrays allowfor simultaneous comparison of tens of thousands of genes in the complex biological process of wound healing. Previous research showed that healing of ischemic rat wois accelerated by topical treatment with PDGF as protein levels of a small numselected growth factors, receptors, and extracellular matrix genes, which provided important information about the effect of platelet-derived growth factor on healing anbiochemical parameters of normal and ischemic rat skin wounds. This study was aimed at identifying genes that are upor down-regulated in ischemic wound healing following PDGF treatment at three time points (day 0, day 3, and day 7) with the GeneChip Rat Expression Array 230A based on the association between the function of a gene and its pattern of expression. Compared to the normal skin of rat (day 0, control), 3 days and 7 days after injury were chosen for the analysis of the gene expression study. Unsupervised hierarchical clustering using dCHIP showed the close clustering of the chips based on the time after injury, which means that the biggest factor influencing the gene expression profile of rat skin is the time after injury. Further examination under supervised analysis was performed to study relationships between expression profile and experimental groups using BRB Array Tools. Differentially expressed genes were determined among the experimental groups by an F test, and four prediction models were used for class prediction. The performance s unds ber of d of prediction models was cross-validated and the significance of the cross-validated error 51

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52 rate was assessed by permutation analysis. Since there were three factors (time, ischemistate, and PDGF treatment) that could affect the gene expression profile during the wound healing, these analyses were performed on all the possible combinations othree factors to find statistically significant differences. Based on the result of the leave-one-out cross-validation analysis (Table 3-2) and c f the permuds er which has e in gene expression across exper gh to detect a specific low abundrward n user-defined thresholds. In overall gene expression on day 3 compared with day 7, a relatively large number of genes (144 genes) tation analysis (Table 3-3), only one set of “Time Points in Non-ischemic WounTreated with Vehicle” with the second highest classification rate was chosen for furthanalysis, excluding the set of “Ischemic and Non-ischemic Wounds at day 7”,shown the highest classification rate, due to the lack of time points to be compared. Unexpectedly, no statistically significant differenc imental groups by PDGF treatment was shown. It might result from the relatively minimal effect of the PDGF treatment on the rate of wound healing. It might be possiblethat only a small number of genes were differentially expressed in response to PDGF treatment, or that there were small changes in levels of gene expression, which are difficult to identify by microarrays that are not sensitive enou ance mRNA. Finally, the number of replicates might be too small to identify differences by the PDGF treatment because the level of variation between animals was large. The 691 genes in the non-ischemic wound group over three time points (day 0, day 3, and day 7) were determined as significant differentially expressed at the p < 0.001 significant level and applied to hierarchical clustering analysis as well as straightfolists of increased and decreased genes based o

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53 showed at least 3-fold change relatively to day 0 (Figure 3-10), which suggests that more changes at the molecular level were going on during the early stage of healing (day 3) than during the later stage (day 7). Also, e in exin TGFsignaling pathway for an enhanced response of the mteopontin, which is encoded e ethe#A2”, is heaisniudncandy, 1994). AdditionallymeXoli_05kinev0ibein A9 (c #NM_07edtg tshhighe3-foret)pi known function genes, at day 3 with secreted phosphoprotein 1 #AB001382. S100 cing proulin B)5sittiny pte floslaf that plays an importantronic inflat4ktorocteioiaen cells tote, and enhance provisional mfthge of heali3-11). The functional categories that were oeintecdday 3 and bega 0 in gene expression, and the identified genes hn cell sigmatory nmeoe m a mg co ih at day 3, there was a noticeable increas pression (26-fold change) for secreted phosphoprotein 1 #AB001382 that is involved atrix durin g the early s tage of healing. Os by th gene “secr ed p ospho prot in 1 B00138 knl in own to be critica ling a fter t sue i jury n cell lar a hesio , hemotaxis, /or phagocytosis (Murr , che okin (C-C m tif) gand 2 #NM 3647 involved in cyto e/chem okin acti ity an d S10 calc um inding prot algranulin B) 5358 wer foun as th e top hree enes hat owed the st increase (14and 1 ld cha nge, spec ively in ex ress on, of the alcium bind teinran A9 (calg #NM _053 87, a socia ted w h acu e flammator rocesses, has been sugges d as a new ibrob ast gr wthtimu ting actor role in ch mma ion (Shibata et al. , 200 ). Ta en gether, it p bably implies that an enhan ed cy okin activ ty is ccurr ng th t courages migrate, prolifera atrix ormation during e early sta ng. The genes were classified by Gene Onto logy functional groups (Table 3-8, Figure ver r prese nted clus ers w re in rease at n to return to levels of day ave a role i naling, inflam respo se, i mun resp nse, nergy etabolism, nd structural proteins. Also, any enes were ateg rized nto t e

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54 hydrolase activity associated group, including arginase 1 # N13 oun arg1 iama mdi-dr1stre aN sntupn of thesion in ndriviblastedlatism-ertita2002). Cytokine activity related genes, such as chem#7, che) liga03ei#93,hwrnleast 4-fold change relative to day 0, teamtasuuk growth fgene expoiaTnlt1inoou telt(F0nayigration and proliferation involves mny cytokines and the interaction with the extracellular m19nsenlarixtncgrpeinibflte5,mllaamlo 9a i caoinh degradation of oin thl renjuiona#7 aonty_01e deptrated ge, Ca to,if M_0 7134 with 4.2-f ld p-regulatio t day 3 relative to day 0. A inase 1 # N M_0 7134 is a b nucle r nganese etalloenzyme that catalyzes th e hy rolys s of L argin ine (W u an Mor is, 998), a sub ate of inducible nitric oxid synth se (i OS). It has been how that he -regulatio arginase expres wou -de ed f rob t de rmines the istinct regu iol n of L-arginine metabo in w ound deriv d fib oblas s (W te et l., okine (C -X-C m otif) ligand 2 NM_05364 mokine (C-C motif nd 2 # NM_ 315 0, int rleuk n 6 NM_01258 , and interleukin-1 #NM_0 1512 whic sho ed in crease d exp essio at nd to be up-regulated at day 3, suggesting an ctive inflam atory response and chemo xis. IL -1 i know n to p-reg late eratinocyte actor (KGF) ressi n in f brobl sts ( ang a d Gi chres , 996). Kerat cyte migration across a w nd su rface leads o repithe ializa ion alanga, 20 1). During re-epithelializatio , ker tinoc te m a atrix (Garlick et al, 96;Steffe et al., 2001). Extracellu matr rela ed ge es in ludin sec eted hosphoprot 1 #AB001382, tissue inh itor o meta lopro einas 1 #N M_0 3819 atrix meta oproteinase 3 #NM_133523, nd m trix etal prote inase #NM _031 055 lso showed ncreased expression at day 3 omp red t norm al sk s, w ich im plies that matrix components were g ng o for e cel migration into tissues in sponse to i ry. However, the express of p rvalb umin AI1 5539 nd tr poni 1, pe 2 #NM 7185, involved in muscl velo ment and muscle contraction and ansport rel enes, such as ATPas +++ ransp rting card ac mu scle, ast tw itch

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55 1 #NM_058213, whose activities are likely to be seen during the later stage of healing, were decreased at day 3. ATPase, Ca++ transporting, cardiac muscle, fast twitch 1 # N, pic eetrse caePrsmtr beeajorncnalpha1 #BE108345 involved in extracellular matrix structural constituent conferring teth ac sdpl.upregulation of this gene is probably a resuhtigoe mverhe imary focus of this analysis in normaufkangthe genes differentially expressed over the three time points (days 0, 3, and 7). Most of thially exprat day 3 rol 0whreturn to control levels at day 7. A correlatiskownnd hg s -ey%unknown functions that were dramatically sreoimisua7 wTa-A9w.dg(in Table 3-5), and #AA866443 with 16.6-fold ch -ginmolecular events occurring in wound heali ld u kTh pil n understanding of the wound healing process. M_058213 encoding sarcoplasmic-endo lasm c reti ulum Ca (2 +)-ad nosin iphosphata (ATPase) (SERCA1) that talyz s AT hyd olysi and c alciu ion ansport has n reported to play a m role i mus le co traction (Inesi et al., 1990). Notably, by 7 days after injury, the expre ssion pattern of proc ollagen, type XII, nsile streng and strulecular ctural mo tivity hifte to u -regu ation The lt of t e ac ve re ulati n of e xtrac llular atrix turno during the later stage of aling. The pr l wo nds o rat s in w s to i vesti ate e different essed genes elativ e to c ntro (day ) sho ed t e tren d to on of gene expression in norm al wounds of rat in with kn events present in wou ealin was een. As sho wn in the Table 3-3 through 3 8, th re we re also man gene s (71 ) wit h increa ed o decr ased ver t e po nts, ch s #AI76443 ith 22.7-fold change (in ble 3 4), # W91 180 ith 7 1-fol chan e ange (in Ta ble 3 6), su gest g tha t the ng are more comp icate than the c rrent nowledge. e study of these genes may rovid e add tiona findi gs to impro ve

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APPILIST OF THE 691 GENES AND THEIR NORMALIZED LOG-TRANSFORMED N-CRENFNIOy END X MEDIA ENTERED GENE EXP SSIO S O NO -ISC HEM C W UND S da 0 day 3 day 7 Fold C hange Ac# cession Gene Title Mean SD Mean SD Mean SD 0 vs. 3 0 vs. 7 NM_033234 hemoglobin beta chain complex -0.38 0.24 0.44 0.07 -0.02 0.11 1.78 1.29 L01122 ferritin light chain 1 NM_012848 ferritine 1 secrein 1 polytide m per 1 NM_019904 g NM_012998 NM7 ankyrin r (cardiac anc Ce of major hislity class II a -1.13 0.27 0.33 0.17 -0.07 0.14 2.75 2.09 D28875 secreted acidic cysteine rich glycoprotein 0.26 0.15 -0.38 0.01 0.01 0.12 -1.55 -1.19 , heavy polypeptid -0.42 0.06 0.57 0.07 0.08 0.17 1.98 1.41 NM_012862 matrix Gla protein -1.59 0.15 0.34 0.18 -0.02 0.05 3.80 2.98 NM_031511 insulin-like growth factor 2 -0.04 0.04 0.08 0.22 0.91 0.24 1.08 1.92 NM_031140 vimentin NM_012554 -0.76 -0.34 0.18 0.00 0.33 0.60 0.18 0.00 0.16 0.02 2.13 1.69 1.92 enolase 1, alpha 0.04 0.08 1.30 S41066 ---0.74 0.23 0.34 0.24 -0.01 0.08 2.11 1.66 AB001382 ted phosphoprote -2.78 0.15 1.96 0.04 0.35 0.77 26.59 8.74 M28647 ATPase, Na+/K+ transporting, alpha 1 pep -0.20 0.02 0.40 0.08 0.05 0.09 1.51 1.19 NM_017087 biglycan 0.02 0.08 -0.09 0.08 0.49 0.13 -1.08 1.39 NM_012512 beta-2 microglobulin -0.62 0.17 0.21 0.26 -0.06 0.11 1.78 1.48 NM_022511 profilin 1 -0.49 0.07 0.26 0.16 -0.02 0.10 1.68 1.39 NM_031051 acrophage migration inhibitory factor oxiredoxin -0.20 0.01 0.29 0.04 -0.04 0.08 1.40 1.11 NM_057114 -0.39 0.00 0.28 0.13 -0.06 0.14 1.60 1.26 NM_012495 aldolase A 0.58 0.22 -0.16 0.15 0.00 0.17 -1.67 -1.50 NM_012530 --lectin, galactoseding, soluble 1 1.34 0.39 -1.00 0.88 0.17 0.42 -5.07 -2.25 bin -0.52 0.10 -0.05 0.14 0.25 0.10 1.39 1.71 BI275294 BI275294 lutamine synthetase 1 -0.28 -0.29 0.36 0.17 0.73 0.73 0.24 0.22 -0.04 0.12 0.04 0.11 2.01 2.03 1.25 1.19 glutamine synthetase 1 prolyl 4-hydroxylase, beta polypeptide -0.62 0.20 0.23 0.07 -0.02 0.07 1.80 1.51 _02259 cathepsin B cathepsin D -0.50 0.13 0.30 0.11 -0.08 0.15 1.74 1.34 NM_134334 -0.48 0.18 0.31 0.06 -0.01 0.05 1.73 1.39 NM_031819 FAT tumor suppressor (Drosophila) homolog 0.30 0.18 -0.50 0.14 -0.03 0.21 -1.74 -1.25 NM_021261 ---0.44 0.05 0.05 0.14 0.21 0.12 1.40 1.57 L81174 epeat domain 1 muscle) kyrin repeat domain 1 (cardia -1.60 0.11 0.15 0.36 0.95 0.53 3.36 5.85 L81174 muscle) -0.97 0.26 -0.10 0.19 0.52 0.19 1.83 2.81 NM_053610 peroxiredoxin 5 -0.41 0.15 0.43 0.13 0.01 0.13 1.79 1.34 NM_013069 D74 antigen (invariant polpypeptid tocompatibi antigen-associated) cetyl-coenzyme A dehydrogenase, -1.01 0.25 0.34 0.16 0.08 0.15 2.55 2.13 NM_016986 medium chain 0.26 0.12 -0.35 0.11 -0.04 0.10 -1.52 -1.22 56

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57 NM_017125 CD63 antigen -0.60 0.12 0.27 0.14 -0.01 0.04 1.83 1.50 NM_053819 tissue inhibitor of metalloproteinase 1ec -2.44 0.21 0.81 0.30 -0.22 0.55 9.53 4.67 NM_031621 0.17 0.35 0.29 -0.04 0.18 1.81 1.38 a1pr) S100 calcium-binding pr4 Fc recty III pNM_019370 NM_030847 epithelialprotein 3 NM_022715 Ue NM_012733 retinol ellular -1.10 NM_017328 phoe 2 NM_017185 NM_031530 chemokine (tif) ligand 2 1.14 NM_013197 aminolevase 2 secretibitorNM_053538 N NM_012732 NM_133595 GTP cycleedback AI712719 NM_133380 NM_053380 solute carrier family (sodium phosphate), member 2 NM_057107 NM_133298 NM_021909 FXYD doining ion NM_031531 0.00 0.03 1.37 0.44 -0.15 0.05 2.59 -1.11 NM_031664 so-coupled nsporter), linker of T-cell reptor pathways -0.50 Cytochrom c oxidase subunit VIII-H eart/muscle NM_012786 (h) etyl-coenzyme A acetyltransferase 0.82 0.46 -1.55 0.46 0.08 0.20 -5.17 -1.67 D13921 c cytochrome c oxidase, subunit VIa, polypeptide 2 0.35 0.11 -0.32 0.19 -0.08 0.15 -1.60 -1.35 NM_012812 0.80 0.47 -1.02 0.44 0.07 0.23 -3.52 -1.65 NM_080767 oteosome (prosome, macropain subunit, beta type 8 -0.62 0.12 0.68 0.42 0.09 0.30 2.47 1.64 NM_012660 statin-like 0.42 0.36 -0.86 0.30 0.05 0.17 -2.42 -1.29 NM_013151 plasminogen activator, tissue -1.14 0.06 0.22 0.43 0.46 0.31 2.57 3.03 NM_012618 NM_053843 otein Aeptor, IgG, low affini -0.34 -2.76 0.12 0.40 0.47 0.86 0.32 -0.01 0.02 0.41 1.75 12.30 1.25 6.31 -0.10 0.47 BI291434 phole rotein tyrosine phosphatase, nonsphofructokinase, musc 1.12 0.49 -0.56 0.32 0.18 0.38 -3.21 -1.91 NM_013016 receptor type substrate 1 -0.51 0.04 0.27 0.19 -0.07 0.20 1.71 1.36 NM_019292 carbonic anhydrase 3 ectonucleotide 0.39 0.31 -0.80 0.19 0.03 0.15 -2.29 -1.29 pyrophosphatase/phosphodiesterase 3 -0.79 0.19 1.07 0.35 -0.16 0.45 3.62 1.54 membrane -0.21 0.10 0.63 0.21 0.00 0.11 1.79 1.16 major vault protein -0.70 0.20 0.27 0.35 -0.03 0.21 1.97 1.60 NM_031325 DP-glucose dehydrogenasnding protein 1, -0.52 0.11 0.47 0.33 -0.04 0.18 1.99 1.40 bi csphoglycerate mutas 0.13 0.50 0.05 -0.97 0.18 0.19 0.16 0.47 2.22 2.45 -4.88 1.32 0.14 0.32 -2.27 NM_133424 ac 3 troponin 1, type 2 tinin alpha 1.78 0.43 -0.95 0.83 0.12 0.56 -6.62 -3.16 1.09 0.25 -1.29 0.84 0.08 0.35 -5.20 -2.01 C-C mo -2.13 0.44 0.46 -0.06 0.48 9.61 4.19 ulinic acid synth -0.32 0.26 1.08 0.22 -0.06 0.11 2.65 1.20 NM_053372 ory leukocyte protease inh -2.37 0.31 0.57 0.27 -0.12 0.21 7.69 4.76 lysosomal-associated protein trans membrane 5 quiescin Q6 -0.98 0.10 0.47 0.21 0.00 0.16 2.75 1.98 AB044285 0.23 0.24 -0.53 0.22 0.05 0.05 -1.68 -1.13 BF284821 synaptoj protein --anin 2 binding 0.19 0.15 -0.38 0.03 0.01 0.05 -1.48 -1.13 M_012804 0.29 0.02 -0.32 0.15 0.04 0.11 -1.53 -1.19 lipase A, lysosomal acid -0.38 0.04 0.35 0.24 0.00 0.11 1.66 1.30 ohydrolase I f regulatory protein -0.39 0.13 0.50 0.25 -0.04 0.24 1.85 1.27 ATP-binding cassette, sub-family G -0.62 0.10 0.55 0.37 0.10 0.30 2.26 1.65 (WHITE), member 1 NM_058213 ATPase, Ca++ transporting, cardiac muscle, fast twitch 1 interlptor 1.32 0.39 -1.26 0.90 0.13 0.47 -5.99 -2.27 eukin 4 rece -0.35 0.04 0.95 0.23 0.10 0.25 2.47 1.37 34 0.06 0.06 -0.44 0.12 0.01 0.04 -1.42 -1.04 acyl-CoA synthetase long-chain family member 3 0.43 0.28 -0.42 0.17 -0.01 0.18 -1.80 -1.35 glycoprotein (transmembrane) nmb main-conta -0.79 0.44 0.28 0.16 0.00 0.17 2.09 1.73 transport regulator 5 -1.12 0.09 0.37 0.27 0.03 0.18 2.82 2.22 Serine protease inhibitor lute carrier family 28 (sodiumucleoside tran -0.38 0.05 0.96 0.40 -0.07 0.28 2.53 1.24

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58 member 2 NM_013143 N NM_017134 arginase NM_012907 a NM_053591 -1.55 NM_020086 plasted protein NM_031766 0.18 0.11 -0.40 0.15 -0.02 0.06 -1.50 -1.15 NM_017007 -0.22 0.19 0.46 0.15 0.05 0.09 1.60 1.21 NM_019175 -1.30 0.11 0.25 0.07 -0.04 0.21 2.93 2.40 soluino acid trmber NM_012774 0.34 0.08 -0.29 0.16 -0.01 0.12 -1.55 -1.27 NM_022605 -0.66 0.04 0.67 0.43 0.10 0.17 2.50 1.69 cae AF154349 legumain -1.45 0.11 0.64 0.44 -0.04 0.26 4.27 2.65 NM_133416 -0.31 0.10 0.35 0.08 0.00 0.18 1.58 1.24 S100 calcrotein A8 (cal A) NM_012620 i prostaglandin-enroxide synthase NM_053963 NM_057104 pyrophosphatase/phosphodiesterase 2N NM_133523 NM_030857 NM_024145 FGR N NM_019298 cha NM_053619 complement component 5, receptor 1NM_053647 NM_133563 g transcripfactor 1 NM_019192 BG380723 meprin 1 alpha 0.13 0.10 -0.39 0.12 0.00 0.02 -1.43 -1.09 M_022290 tenomodulin 0.76 0.11 -0.56 0.22 -0.07 0.19 -2.48 -1.77 1 -0.71 0.30 1.37 0.66 0.23 0.42 4.22 1.91 polipoprotein B editing complex 1idase 1 ( -1.19 0.15 0.93 0.54 -0.14 0.27 4.35 2.07 dipeptrenal) malemma vesicle associa 0.41 0.15 -0.23 0.14 0.01 0.02 -1.32 -0.58 0.34 0.24 0.13 -0.05 0.10 1.77 1.45 carboxypeptidase Z glutamate decarboxylase 1 kallikrein 6 te carrier family 7 (cationic amansporter, y+ system), me1 glypican 3 heparanase AB066224 0.54 0.16 -0.09 0.12 0.00 0.15 -1.55 -1.46 J02844 rnitine O-octanoyltransferas 0.25 0.22 -0.51 0.16 0.01 0.04 -1.70 -1.18 NM_019174 carbonic anhydrase 4 -0.19 0.05 0.79 0.19 0.13 0.37 1.97 1.25 NM_022393 macrophage galactose N-acetyl-galactosamine specific lectin 1 BCL2-related protein A1 -0.57 0.26 1.35 0.67 0.04 0.17 3.78 1.52 NM_021744 CD14 antigen ium p -0.75 0.30 1.01 0.41 0.00 0.14 3.37 1.68 bindinggranulin -1.13 0.16 0.69 0.33 0.09 0.33 3.53 NM_053822 2.32 NM_133303 basic helix-loop-helix domain containing, class B3 0.61 0.12 -0.14 0.12 -0.16 0.21 -1.69 -1.71 NM_012523 CD53 antigen serine (or cysteine) proteinase -1.64 0.25 0.74 0.38 -0.09 0.16 5.22 2.94 nhibitor, member 1 -0.41 0.23 1.08 0.36 -0.02 0.24 2.81 1.31 U03389 dope 2 matrix metalloproteinase 12 -0.44 0.37 2.10 1.08 0.07 0.35 5.79 1.42 -0.53 0.05 0.25 0.22 0.00 0.04 1.73 1.45 ectonucleotide 0.72 0.04 -0.28 0.25 -0.07 0.17 -2.00 -1.73 NM_017196 allograft factor 1 --inflammatory -1.65 0.22 0.90 0.70 -0.03 0.19 5.85 3.08 M_020074 -0.38 0.04 0.97 0.40 0.07 0.22 2.54 1.36 matrix metalloproteinase 3 -0.73 0.25 1.84 0.46 -0.07 0.17 5.94 1.58 lyn protein non-receptor kinase -0.34 -0.31 0.13 0.14 0.45 0.47 0.21 0.20 0.05 0.19 0.06 0.12 1.73 1.71 1.28 1.32 M_022403 tryptophan 2,3-dioxygenase 0.52 0.26 -0.86 0.52 -0.07 0.28 -2.60 -1.50 NM_019131 tropomyosin 1, alpha 0.82 0.35 -1.11 0.70 0.13 0.26 -3.80 -1.61 olinergic receptor, nicotinic, deltpolypeptide -0.31 0.12 -0.01 0.07 0.45 0.27 1.23 1.69 -0.97 0.16 0.63 0.41 -0.05 0.09 3.01 1.89 chemokine (C-X-C motif) ligand 2 -0.93 0.06 2.96 1.34 -0.18 0.50 14.79 1.68 onadotropin inducible ovarian tion -0.78 0.11 0.87 0.83 -0.04 0.19 3.14 1.67 selenoprotein P, plasma, 1 -0.28 0.03 0.34 0.21 -0.02 0.06 1.54 1.20 CAP, adenylate cyclase-associated protein 1 (yeast) -0.35 0.11 0.30 0.18 -0.01 0.12 1.57 1.27 AI407364 lamin B1 0.02 0.10 0.31 0.05 -0.36 0.22 1.23 -1.30

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59 NM_032612 N N0 NM_012555 v-ets er oncoan) NM_031514 AB050011 v-maf musculoaponeurotic fibrosarcoma (avian) oncogene family, protein G -0.52 0.04 0.35 0.26 -0.04 0.15 1.83 1.40 AI014001 glyceronephosphate O-acyltransferase0.40 0.15 -0.26 0.17 -0.01 0.07 -1.59 -1.33 AI014001 glyceronephosphate O-acyltransferase0.70 0.03 -0.39 0.17 0.08 0.17 -2.13 -1.53 NM_017325 runt related transcription factor 1 -0.53 0.06 -0.03 0.22 0.21 0.15 1.41 1.67 NM_030863 moesin -0.54 0.23 0.30 0.06 0.00 0.01 1.80 1.46 NM_133609 eukaryotic translation initiation factor 2B, subunit 3 (gamma, 58kD) 0.47 0.19 -0.20 0.18 -0.01 0.06 -1.59 -1.39 D30795 CD38 antigen -0.47 0.19 0.60 0.36 0.03 0.10 2.11 1.42 NM_057194 phospholipid scramblase 1 -0.50 0.16 0.51 0.23 -0.10 0.18 2.02 1.32 NM_022853 solute carrier family 30 (zinc transporter), member 1 0.65 0.14 -0.21 0.34 -0.18 0.23 -1.82 -1.78 NM_031055 matrix metalloproteinase 9 (gelatinase B, 92-kDa type IV collagenase) -0.53 0.10 1.07 0.39 0.11 0.19 3.03 1.56 NM_012589 interleukin 6 -0.70 0.12 1.35 0.66 0.01 0.14 4.12 1.63 NM_021576 5 nucleotidase -0.17 0.10 0.60 0.17 -0.04 0.10 1.71 1.10 NM_017028 myxovirus (influenza virus) resistance 2 -0.63 0.06 0.32 0.14 0.06 0.30 1.93 1.61 NM_053738 Wnt inhibitory factor 1 0.69 0.12 -0.11 0.11 -0.19 0.29 -1.74 -1.84 NM_013185 hemopoietic cell kinase -0.70 0.13 0.68 0.37 0.02 0.04 2.61 1.65 NM_030848 bone marrow stromal cell antigen 1 -0.48 0.05 0.55 0.16 0.12 0.24 2.05 1.52 NM_022617 macrophage expressed gene 1 -0.49 0.12 1.03 0.30 0.16 0.29 2.87 1.57 NM_031590 WNT1 inducible signaling pathway protein 2 -0.09 0.09 -0.01 0.07 0.59 0.19 1.06 1.60 NM_019195 CD47 antigen (Rh-related antigen, integrin-associated signal transducer)-0.45 0.10 0.34 0.24 -0.01 0.05 1.73 1.35 AF189724 chemokine (C-X-C motif) ligand 12 -0.60 0.09 -0.08 0.29 0.42 0.20 1.43 2.03 AI145313 ---0.49 0.07 0.09 0.31 0.35 0.24 1.49 1.80 NM_033098 TAP binding protein -0.35 0.03 0.27 0.12 0.02 0.03 1.53 1.29 U32497 purinergic receptor P2X, ligand-gated ion channel, 4 -0.34 0.02 0.32 0.13 0.01 0.11 1.57 1.27 U22414 chemokine (C-C motif) ligand 3 -0.51 0.12 1.35 0.67 0.03 0.17 3.64 1.45 NM_021863 testis-specific heat shock protein-related gene hst70 0.79 0.10 -0.33 0.31 -0.03 0.16 -2.19 -1.77 NM_024485 cholinergic receptor, nicotinic, alpha polypeptide 1 (muscle) -0.15 0.13 0.02 0.15 0.70 0.29 1.12 1.80 NM_019212 actin, alpha 1, skeletal muscle 0.44 0.15 -0.67 0.50 0.03 0.15 -2.16 -1.33 NM_031969 calmodulin 1 -0.37 0.02 0.33 0.21 0.00 0.07 1.63 1.30 BI275994 tissue-type transglutaminase -0.28 0.13 0.31 0.08 0.05 0.10 1.50 1.26 BI285141 CD24 antigen -0.47 0.16 0.45 0.08 0.01 0.25 1.90 1.40 NM_053783 interferon gamma receptor -0.77 0.21 0.33 0.28 -0.07 0.14 2.16 1.63 NM_019341 regulator of G-protein signaling 5 -0.52 0.17 0.11 0.22 0.52 0.35 1.55 2.06 NM_022542 rhoB gene -0.44 0.07 0.15 0.07 0.04 0.20 1.51 1.40 NM_130411 coronin, actin binding protein 1A -1.29 0.25 0.72 0.30 0.02 0.07 4.05 2.49 AB046616 RNA binding protein p45AUF1 -0.03 0.06 0.36 0.04 -0.42 0.19 1.31 -1.32 signal transducer and activator of -0.63 0.14 0.30 0.37 0.10 transcription 1 0.13 1.90 1.66 M_01267 8 tropomyosin 4 TO -0.34 0.13 0.32 0.14 -0.01 0.09 1.58 1.26 M_13439 RID -0.81 0.06 0.21 0.23 -0.09 0.20 2.02 1.64 ythroblastosis virus E26gene homolog 1 (avi -0.66 0.16 0.16 0.37 0.12 0.13 1.76 1.71 Janus kinase 2 -0.65 0.06 0.42 0.17 -0.12 0.34 2.10 1.44

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60 NM_017154 xanthine dehydrogenase -0.05 0.06 0.81 0.30 0.06 0.16 1.81 1.08 NM_130413 src family associated phosphoprotein 2 -0.54 0.09 0.30 0.28 -0.05 0.09 1.79 1.41 NM_031008 adaptor protein complex AP-2, alpha 2 subunit -0.41 0.16 0.61 0.30 0.02 0.18 2.03 1.35 NM_031116 chemokine (C-C motif) ligand 5 -0.47 0.13 0.11 0.27 0.23 0.06 1.50 1.62 AF394783 sulfotransferase family 1A, phenol-preferring, member 1 0.68 0.14 -0.23 0.18 -0.02 0.20 -1.88 -1.62 NM_020104 fast myosin alkali light chain 0.63 0.15 -0.96 0.69 0.08 0.19 -3.00 -1.46 NM_133572 cell division cycle 25B -0.06 0.11 0.52 0.20 -0.15 0.07 1.49 -1.06 BG668493 stathmin-like 2 -0.48 0.11 0.23 0.20 0.18 0.17 1.63 1.58 NM_053311 ATPase, Ca++ transporting, plasma membrane 1 -0.16 0.15 0.60 0.24 -0.10 0.25 1.69 1.04 NM_020103 Ly6-C antigen gene -0.41 0.06 0.73 0.37 0.04 0.29 2.21 1.36 NM_130399 adenosine deaminase -0.56 0.03 0.19 0.23 -0.02 0.16 1.68 1.45 NM_012580 heme oxygenase (decycling) 1 -1.31 0.33 0.70 0.28 -0.01 0.03 4.03 2.48 NM_021578 transforming growth factor, beta 1 -0.48 0.04 0.45 0.13 0.02 0.19 1.91 1.42 NM_020542 macrophage inflammatory protein-1 alpha receptor gene -0.39 0.20 1.14 0.38 -0.04 0.14 2.89 1.28 U54791 chemokine (C-X-C motif) receptor 4-0.88 0.16 0.59 0.26 0.03 0.08 2.76 1.88 L12458 lysozyme -1.57 0.25 0.40 0.17 0.11 0.31 3.93 3.21 AI406565 small muscle protein, X-linked 0.24 0.20 -0.75 0.17 0.08 0.21 -1.99 -1.12 BG671549 superoxide dismutase 2, mitochondrial -0.47 0.18 1.20 0.28 0.14 0.33 3.17 1.52 AI548856 poliovirus receptor -0.42 0.09 0.58 0.18 0.00 0.09 1.99 1.34 BM389673 cofilin 1 -0.45 0.08 0.34 0.13 -0.02 0.07 1.74 1.35 AI599350 proteosome (prosome, macropain) subunit, beta type 9 -0.72 0.17 0.76 0.47 0.06 0.19 2.78 1.72 AJ243304 triadin 1.25 0.48 -1.10 0.61 0.10 0.31 -5.08 -2.21 AI175539 parvalbumin 1.62 0.49 -1.53 0.67 -0.05 0.57 -8.85 -3.18 AA848319 lactate dehydrogenase B 0.29 0.06 -0.45 0.18 -0.11 0.19 -1.67 -1.31 AI232788 cytochrome b-245, alpha polypeptide-0.98 0.10 0.50 0.31 -0.04 0.20 2.79 1.91 AA945178 Transferrin -0.42 0.22 0.86 0.34 0.03 0.29 2.43 1.37 AA893484 fibronectin 1 -1.00 0.15 0.21 0.20 -0.02 0.23 2.30 1.97 AI179404 hemoglobin alpha, adult chain 1 -0.20 0.15 0.43 0.07 0.03 0.11 1.55 1.17 AI179404 hemoglobin alpha, adult chain 1 -0.24 0.13 0.42 0.10 0.01 0.03 1.57 1.19 AI232474 cathepsin L -0.44 0.21 0.62 0.35 0.02 0.13 2.09 1.37 AI008680 benzodiazepin receptor -0.39 0.17 0.46 0.22 0.05 0.09 1.80 1.35 U44948 cysteine and glycine-rich protein 2 -0.23 0.24 0.00 0.07 0.95 0.24 1.17 2.26 AF372216 tropomyosin 1, alpha 0.76 0.43 -1.46 0.82 -0.08 0.28 -4.68 -1.79 AB000489 solute carrier family 20 (phosphate transporter), member 1 -0.29 0.07 0.29 0.13 0.01 0.11 1.49 1.23 X64589 cyclin B1 -0.12 0.21 0.56 0.19 -0.28 0.21 1.60 -1.12 U72660 ninjurin 1 -1.28 0.27 0.67 0.33 -0.10 0.20 3.87 2.26 J02585 stearoyl-Coenzyme A desaturase 1 0.20 0.18 -0.84 0.27 -0.03 0.28 -2.05 -1.17 AF146738 testis specific protein 0.08 0.03 -0.47 0.12 -0.01 0.05 -1.46 -1.06 U66470 cell growth regulator with EF hand domain 1 0.84 0.25 -0.30 0.14 -0.08 0.14 -2.20 -1.89 L46791 carboxylesterase 3 0.48 0.42 -1.32 0.50 0.01 0.40 -3.48 -1.39 U23056 CEA-related cell adhesion molecule 1 /// CEA-related cell adhesion molecule 10 -0.29 0.05 0.45 0.18 0.01 0.13 1.66 1.23

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61 BI279526 RT1 class II, locus Db1 -1.13 0.22 0.45 0.46 0.03 0.15 2.98 2.23 AF399874 troponin T1, skeletal, slow 1.32 0.72 -0.62 0.21 0.14 0.34 -3.84 -2.27 AJ249701 RT1 class Ib, locus Aw2 -0.94 0.31 0.14 0.07 -0.13 0.42 2.12 1.76 U69550 phospholipase D1 -0.57 0.08 0.08 0.13 -0.07 0.20 1.58 1.42 U53475 RAB8B, member RAS oncogene family -0.43 0.08 0.42 0.26 -0.04 0.12 1.80 1.31 X04440 protein kinase C, beta 1 -0.18 0.02 0.59 0.28 0.03 0.08 1.70 1.15 M10072 ---0.64 0.07 0.62 0.43 -0.04 0.27 2.40 1.52 AF461738 UDP glycosyltransferase 1 family polypeptide A4 /// UDP glycosyltransferase 1 family, polypeptide A1 /// UDP glycosyltransferase 1 family, polypeptide A6 /// UDP glycosyltransferase 1 family, polypeptide A7 /// UDP glycosyltransferase 1 family, polypeptid -0.65 0.10 0.43 0.23 0.05 0.12 2.12 1.63 D87927 gene model 1960, (NCBI) -0.06 0.06 1.59 0.67 0.07 0.33 3.14 1.10 BM389426 platelet derived growth factor receptor, beta polypeptide -0.44 0.11 0.06 0.11 0.32 0.15 1.41 1.70 AF169636 Similar to PIRB1 (LOC361493), mRNA /// Paired Ig-like receptor-B (Pirb) mRNA, complete cds -0.46 0.18 0.66 0.27 0.00 0.21 2.17 1.38 AB071036 leucine-rich repeat protein induced by beta-amyloid 0.18 0.14 -0.61 0.27 -0.08 0.16 -1.72 -1.20 AF220558 triadin 0.62 0.22 -0.57 0.38 0.00 0.07 -2.27 -1.53 AF411216 vacuole Membrane Protein 1 -0.68 0.17 0.09 0.15 0.07 0.06 1.71 1.68 AF307302 RT1 class II, locus Ba -0.96 0.27 0.13 0.37 0.06 0.06 2.12 2.03 AF387513 BMP and activin membrane-bound inhibitor, homolog (Xenopus laevis) 0.81 0.23 -0.47 0.44 0.14 0.34 -2.43 -1.59 J02582 apolipoprotein E -0.47 0.06 -0.04 0.14 0.04 0.05 1.34 1.43 M30596 --0.24 0.16 -0.59 0.27 -0.07 0.14 -1.78 -1.24 AI171966 major histocompatibility complex, class II, DM beta -0.90 0.12 0.39 0.40 0.17 0.19 2.43 2.09 Y00480 RT1 class II, locus Da -1.32 0.27 0.26 0.24 0.00 0.03 3.00 2.50 AA849399 cathepsin Y -0.97 0.15 0.90 0.40 -0.04 0.25 3.64 1.90 BI292004 actin-related protein 3 homolog (yeast) -0.27 0.04 0.42 0.07 -0.08 0.20 1.61 1.14 BI285347 complement component 4a -0.81 0.31 -0.04 0.25 0.24 0.34 1.71 2.07 AI233740 aldo-keto reductase family 1, member B8 -1.18 0.05 1.03 0.30 0.00 0.04 4.62 2.26 BI301490 major histocompatibility complex, class II, DM alpha -0.97 0.20 0.44 0.25 -0.01 0.20 2.67 1.95 BE108345 procollagen, type XII, alpha 1 -0.90 0.06 -0.07 0.20 0.77 0.15 1.78 3.20 BI284739 LPS-induced TNF-alpha factor -0.74 0.18 0.61 0.18 -0.04 0.19 2.54 1.62 AI170661 ---0.41 0.20 0.62 0.33 -0.02 0.28 2.04 1.32 BI274401 prolyl 4-hydroxylase alpha subunit -0.71 0.21 0.39 0.31 -0.12 0.37 2.14 1.51 BI277545 type 2X myosin heavy chain 0.26 0.40 -1.40 0.47 0.16 0.15 -3.17 -1.07 BI275633 --1.82 0.45 -0.89 0.70 0.21 0.68 -6.53 -3.04 AJ245707 2-hydroxyphytanoyl-CoA lyase 0.30 0.21 -0.58 0.04 -0.01 0.03 -1.84 -1.24 X52711 myxovirus (influenza virus) resistance 1 -0.71 0.05 0.50 0.39 -0.17 0.42 2.31 1.45 AW527515 cut (Drosophila)-like 1 0.60 0.14 -0.11 0.23 -0.13 0.15 -1.64 -1.66

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62 X73371 Fc receptor, IgG, low affinity IIb -1.80 0.17 1.49 0.46 -0.07 0.46 9.82 3.34 BM387006 secretory carrier membrane protein 2-0.31 0.13 0.46 0.12 -0.04 0.14 1.70 1.20 L06804 LIM homeobox protein 2 0.63 0.10 -0.22 0.36 -0.12 0.20 -1.81 -1.68 X05080 ---0.28 0.25 0.49 0.04 -0.03 0.08 1.70 1.19 AJ299017 ret proto-oncogene 0.29 0.14 -0.48 0.16 -0.03 0.06 -1.71 -1.25 AJ243973 MHC class Ib RT1.S3 -0.47 0.15 0.73 0.37 0.00 0.04 2.29 1.38 M14952 apolipoprotein B -0.26 0.13 0.53 0.22 0.10 0.17 1.73 1.28 AF159103 ---0.71 0.07 0.35 0.47 0.27 0.28 2.08 1.97 AJ243338 RT1 class I, CE5 -1.05 0.28 0.22 0.33 0.04 0.22 2.41 2.14 AF084544 chondroitin sulfate proteoglycan 2 (versican) -0.58 0.20 0.62 0.26 -0.09 0.24 2.30 1.40 AF411318 Metallothionein 0.07 0.24 0.71 0.19 -0.12 0.08 1.56 -1.14 AF053361 tropomyosin 3, gamma /// tropomyosin isoform 6 -0.48 0.32 0.53 0.24 -0.13 0.23 2.01 1.27 AF370889 tropomyosin 1, alpha 0.68 0.23 -1.22 0.90 0.13 0.27 -3.73 -1.47 BI287300 ---0.64 0.09 0.84 0.24 0.01 0.18 2.80 1.57 BF521859 --1.13 0.30 -1.21 0.80 0.08 0.36 -5.04 -2.07 AI169104 Similar to Platelet factor 4 precursor (PF-4) (CXCL4) (LOC360918), mRNA -1.38 0.21 0.55 0.55 -0.03 0.20 3.81 2.56 BF284168 H19 fetal liver mRNA 0.02 0.32 -1.31 0.46 0.16 0.14 -2.52 1.10 AI408677 Basophilic leukemia expressed sequence 01 (Bles01) mRNA, partial sequence -0.44 0.10 0.36 0.15 0.00 0.05 1.74 1.36 AI169092 thyroid hormone responsive protein 1.16 0.34 -0.59 0.33 0.08 0.28 -3.36 -2.11 BM390600 ---0.32 0.06 0.40 0.23 -0.01 0.10 1.64 1.24 BI284849 ---0.38 0.06 0.28 0.12 0.05 0.09 1.57 1.34 BF285649 ---0.16 0.07 0.64 0.25 0.02 0.05 1.74 1.13 BG378630 Similar to onzin (LOC360914), mRNA -1.46 0.14 0.70 0.44 0.03 0.05 4.49 2.81 BG666075 Similar to SH3 domain binding glutamic acid-rich protein-like 3 (LOC298544), mRNA -0.50 0.19 0.22 0.22 0.02 0.06 1.64 1.44 BF285350 Similar to APOBEC-2 protein (LOC301226), mRNA 1.43 0.50 -0.50 0.28 0.18 0.51 -3.81 -2.38 AI009775 Similar to actin related protein 2/3 complex subunit 2; ARP2/3 protein complex subunit 34 (LOC301511), mRNA -0.24 0.07 0.38 0.15 0.06 0.13 1.54 1.23 AI233208 calcium regulated heat stable protein 1-0.60 0.22 0.31 0.21 0.03 0.06 1.88 1.55 AI179422 ---0.91 0.06 0.68 0.54 0.02 0.28 3.02 1.91 AA799471 --0.77 0.30 -1.15 0.73 -0.25 0.58 -3.77 -2.03 BF281185 ---0.65 0.12 0.41 0.23 -0.01 0.05 2.09 1.56 BI277433 --0.61 0.19 -0.61 0.20 -0.13 0.32 -2.33 -1.68 AI008441 Similar to 6-phosphogluconate dehydrogenase, decarboxylating (LOC362660), mRNA -0.43 0.14 0.21 0.14 0.07 0.17 1.55 1.41 BI281955 ---0.33 0.07 0.39 0.10 0.06 0.19 1.66 1.31 AA891940 Similar to Transforming protein RhoC (H9) (LOC295342), mRNA -0.43 0.07 0.03 0.07 0.07 0.03 1.38 1.42 BE113393 --0.58 0.33 -0.75 0.53 0.10 0.20 -2.50 -1.39 BI282993 Similar to CHO functionally unknown type II transmembrane protein (LOC297073), mRNA -0.72 0.10 0.23 0.33 0.25 0.22 1.92 1.95

PAGE 73

63 AI177059 Similar to RIKEN cDNA 1110007F23 (LOC287382), mRNA 0.29 0.28 -1.68 0.53 -0.01 0.19 -3.91 -1.22 BI286411 ---0.72 0.10 0.30 0.28 -0.05 0.15 2.03 1.60 BI286411 ---1.58 0.11 0.59 0.16 0.07 0.16 4.49 3.14 AA858962 retinol binding protein 4 0.96 0.23 -0.33 0.40 0.00 0.27 -2.44 -1.94 AI104354 Similar to FATZ related protein 2 (LOC295426), mRNA 0.32 0.42 -1.47 0.31 0.17 0.34 -3.48 -1.11 BI295971 ---0.75 0.15 0.40 0.45 0.15 0.22 2.23 1.87 AI409037 ---0.44 0.12 0.66 0.37 0.09 0.26 2.14 1.44 BI279646 Similar to keratin complex 1, acidic, gene 14 (LOC287701), mRNA -0.25 0.01 0.28 0.04 0.03 0.07 1.44 1.21 BG379319 ---1.35 0.21 0.28 0.38 0.20 0.18 3.10 2.94 BM386334 --0.53 0.48 -0.88 0.46 0.01 0.06 -2.66 -1.44 BG380355 --0.00 0.07 0.33 0.05 -0.20 0.06 1.26 -1.15 AI228039 --0.83 0.30 -0.70 0.63 0.13 0.35 -2.90 -1.63 BG373288 Similar to kidney predominant protein (LOC295231), mRNA -0.45 0.08 0.23 0.18 -0.05 0.09 1.61 1.32 BF287282 Similar to schwannoma-associated protein (LOC361527), mRNA -0.60 0.10 0.34 0.16 -0.02 0.03 1.92 1.50 AI598442 --1.24 0.51 -0.78 0.43 0.04 0.35 -4.05 -2.30 BI303641 ---0.13 0.13 0.49 0.12 -0.02 0.05 1.54 1.08 BG380285 Similar to interferon induced transmembrane protein 2 like; interferon induced transmembrane protein like 2 (human); interferon induced transmembrane protein 2 like (human) (LOC293618), mRNA -1.39 0.07 0.56 0.46 -0.01 0.22 3.89 2.61 BI294844 ---0.76 0.19 0.14 0.19 0.13 0.16 1.88 1.85 BI285146 Similar to Cystatin related protein 2 precursor (Prostatic 22 kDa glycoprotein P22K15) (LOC296230), mRNA -0.93 0.41 0.20 0.36 0.10 0.13 2.20 2.05 AI406687 ---0.17 0.13 0.53 0.17 0.04 0.21 1.63 1.16 BM389261 Similar to lysosomal thiol reductase precursor (LOC290644), mRNA -0.88 0.12 0.76 0.27 -0.02 0.05 3.12 1.82 AI237657 --0.47 0.09 -0.23 0.22 -0.09 0.13 -1.62 -1.48 BG666916 hypertrophic agonist responsive protein -0.25 0.01 0.34 0.12 0.06 0.12 1.50 1.23 BF284262 ---1.56 0.09 0.20 0.24 0.08 0.08 3.38 3.10 BI284307 ---0.56 0.04 0.49 0.33 0.00 0.10 2.08 1.48 BI279729 Similar to Cytosolic nonspecific dipeptidase (Glutamate carboxypeptidase-like protein 1) (LOC291394), mRNA -0.68 0.05 0.54 0.28 -0.06 0.15 2.33 1.54 BM385502 type I keratin KA15 0.62 0.16 -0.50 0.45 -0.09 0.19 -2.17 -1.64 BI295768 LRP16 protein 0.45 0.13 -0.43 0.18 0.01 0.07 -1.84 -1.36 AI235942 --1.18 0.24 -0.19 0.07 -0.05 0.44 -2.60 -2.35 BG663128 Similar to TROPONIN C, SKELETAL MUSCLE (STNC) (LOC296369), mRNA 0.80 0.16 -1.16 0.74 0.12 0.22 -3.89 -1.60 AW915763 serine (or cysteine) proteinase inhibitor, clade G (C1 inhibitor), member 1, (angioedema, hereditary) -1.19 0.17 0.10 0.28 0.19 0.23 2.45 2.60 BF550246 ---0.72 0.34 0.37 0.33 0.09 0.18 2.12 1.75 AA800892 --1.08 0.43 -0.83 0.28 0.21 0.37 -3.74 -1.83

PAGE 74

64 AI013919 cyclin-dependent kinase inhibitor 1C, p57 0.04 0.10 -0.29 0.20 0.48 0.21 -1.25 1.36 BE111805 Similar to Lyl-1 protein (Lymphoblastic leukemia derived sequence 1) (LOC304663), mRNA -0.55 0.04 0.40 0.28 0.06 0.19 1.93 1.52 BI303596 Similar to elastin microfibril interface located protein 1 (LOC298845), mRNA -0.82 0.10 0.45 0.23 -0.11 0.34 2.42 1.64 AI170687 --0.36 0.28 -1.03 0.37 -0.05 0.22 -2.62 -1.33 AI599079 Similar to hypothetical protein FLJ25059 (LOC366146), mRNA 0.32 0.18 0.11 0.02 0.22 -1.87 -1.23 BG372437 Similar to Ab2-225 (LOC310201), mRNA 0.84 0.31 -0.64 0.23 -0.13 0.42 -2.80 -1.97 AI231308 ---0.41 0.08 0.30 0.11 0.06 0.17 1.64 1.38 AI710604 --0.28 0.19 -0.86 0.24 0.12 0.26 -2.21 -1.12 BI289527 Similar to tropomodulin 4 (LOC295261), mRNA 0.79 0.31 -0.50 0.26 -0.02 0.32 -2.46 -1.76 BI278620 ---0.27 0.03 0.37 0.22 0.03 0.05 1.55 1.23 BI275818 serine (or cysteine) proteinase inhibitor, clade E, member 2 -0.08 0.25 -0.61 0.31 0.68 0.09 -1.45 1.69 AW253616 ---0.49 0.23 0.35 0.28 -0.02 0.08 1.79 1.39 AW520792 Similar to vasodilator-stimulated phosphoprotein (LOC361517), mRNA -0.56 0.08 0.22 0.11 -0.03 0.07 1.72 1.44 BI296525 Similar to CD97 protein (LOC361383), mRNA -0.16 0.11 0.63 0.25 0.04 0.15 1.73 1.15 AI137605 Similar to LNV (LOC367179), mRNA -0.40 0.08 0.42 0.26 0.04 0.14 1.76 1.35 AI103616 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) -0.27 0.15 0.54 0.16 -0.05 0.10 1.75 1.17 BG380684 reticulon 2 (Z-band associated protein) 0.67 0.50 -0.65 0.37 -0.08 0.24 -2.50 -1.68 AI105042 Similar to Cabc1 protein (LOC360887), mRNA 0.43 0.16 -0.31 0.16 -0.04 0.20 -1.68 -1.39 BM388445 ---1.13 0.11 0.43 0.57 0.09 0.16 2.95 2.32 AI172271 Similar to endomucin-1 (LOC295490), mRNA -0.47 0.04 0.13 0.24 0.20 0.15 1.51 1.59 BF284889 Similar to actinin, alpha 2 (LOC291245), mRNA 0.10 0.37 -0.85 0.31 0.12 0.14 -1.94 1.01 AA800245 Similar to RING-finger protein MURF (LOC362708), mRNA 0.87 0.47 -0.67 0.61 -0.07 0.06 -2.90 -1.92 BI276210 Similar to FK506 binding protein 11 (LOC300211), mRNA -0.67 0.11 0.11 0.16 -0.07 0.12 1.71 1.52 BE113362 Similar to cyclin-dependent kinase inhibitor 3; CDK2-associated dual specificity phosphatase; cyclin-dependent kinase interactor 1; cyclin-dependent kinase interacting protein 2; kinase-associated phosphatase (LOC289993), mRNA -0.10 0.07 0.77 0.32 -0.05 0.12 1.83 1.03 BI292558 Similar to uridine phosphorylase (LOC289801), mRNA -0.30 0.09 0.67 0.35 0.08 0.27 1.96 1.30 BG374196 --1.05 0.26 -0.36 0.24 0.11 0.20 -2.66 -1.92 BF395095 --1.18 0.64 -1.16 0.53 0.13 0.39 -5.06 -2.07 AI409727 Similar to Snx5 protein (LOC296199), mRNA -0.62 0.07 0.57 0.48 -0.04 0.13 2.28 1.49 BE112453 --0.51 0.19 -0.52 0.09 -0.10 0.19 -2.04 -1.52 -0.59

PAGE 75

65 BE109102 ---0.33 0.14 -0.06 0.11 0.44 0.28 1.21 1.70 AA957342 Similar to peptidylprolyl isomerase D (cyclophilin D) (LOC316726), mRNA0.41 0.15 -0.43 0.04 -0.03 0.18 -1.80 -1.36 AI179227 ---0.37 0.05 0.20 0.10 -0.03 0.13 1.48 1.26 AA900367 --0.13 0.18 -0.59 0.22 0.05 0.12 -1.65 -1.06 AA818334 Similar to sushi-repeat containing protein (LOC317181), mRNA -0.35 0.11 0.02 0.06 0.60 0.24 1.29 1.94 AI411618 Similar to C1q C chain (LOC362634), mRNA -0.90 0.32 0.33 0.24 0.03 0.23 2.35 1.90 BI303598 Similar to RIKEN cDNA 2410030K01 (LOC363028), mRNA -0.03 0.03 0.54 0.10 -0.06 0.22 1.48 -1.02 BI275923 Similar to SDF2 like protein 1 (LOC287936), mRNA -0.69 0.09 0.29 0.31 0.06 0.10 1.98 1.69 BM388650 ---0.47 0.14 0.11 0.13 0.05 0.12 1.49 1.44 AW916153 Similar to protein tyrosine phosphatase 20 (LOC301333), mRNA-0.74 0.12 0.39 0.45 -0.01 0.09 2.19 1.66 AA893743 --0.68 0.33 -0.23 0.07 -0.01 0.11 -1.88 -1.61 AI407239 --1.27 0.37 -1.33 0.52 0.12 0.38 -6.07 -2.22 AA945183 --0.57 0.13 -0.33 0.32 0.00 0.11 -1.86 -1.49 AI137995 sodium channel, voltage-gated, type IV, beta 0.47 0.28 -0.40 0.15 -0.02 0.13 -1.83 -1.40 BM388911 Hypothetical LOC297077 (LOC297077), mRNA -0.90 0.06 0.37 0.25 -0.09 0.20 2.41 1.75 BF397920 --0.54 0.11 -0.34 0.23 -0.02 0.09 -1.85 -1.48 AI102745 ---0.42 0.03 0.14 0.13 -0.02 0.07 1.47 1.32 AW527403 Similar to Sh3yl1 (LOC362724), mRNA 0.54 0.07 -0.10 0.27 -0.04 0.06 -1.56 -1.49 AI764437 ---3.72 0.48 0.79 0.33 -0.17 0.33 22.7611.69AI176034 ---0.84 0.06 0.73 0.23 0.03 0.05 2.98 1.83 BE104219 --0.22 0.20 -0.80 0.21 0.00 0.25 -2.03 -1.16 BG666787 ---0.68 0.09 0.68 0.38 -0.04 0.26 2.57 1.56 BF287967 Similar to GLI pathogenesis-related 1 (glioma); related to testes-specific, vespid, and pathogenesis proteins (LOC299783), mRNA -0.94 0.16 0.67 0.35 0.07 0.18 3.05 2.01 BF397848 Similar to mena protein (LOC360891), mRNA -0.42 0.02 -0.05 0.18 0.20 0.08 1.29 1.54 AI145081 mini chromosome maintenance deficient 4 homolog (S. cerevisiae) -0.03 0.06 0.38 0.19 -0.29 0.17 1.33 -1.20 BE111722 Fc receptor, IgE, high affinity I, gamma polypeptide -1.68 0.15 0.84 0.36 -0.12 0.27 5.71 2.95 AA945737 chemokine (C-X-C motif) receptor 4-0.69 0.18 0.36 0.14 -0.02 0.10 2.07 1.60 AI598315 --1.08 0.11 -0.77 0.65 -0.17 0.46 -3.60 -2.37 AA818643 --0.95 0.32 -0.42 0.26 0.06 0.15 -2.57 -1.85 AI171656 --0.50 0.08 -0.10 0.06 0.02 0.07 -1.52 -1.40 BG378588 Similar to Myosin binding protein C, fast-type (LOC292879), mRNA 1.61 0.90 -0.88 0.77 0.15 0.45 -5.59 -2.75 BE117010 ---0.43 0.38 -0.19 0.22 0.84 0.46 1.18 2.41 AI176129 --0.52 0.16 -0.09 0.06 -0.09 0.19 -1.53 -1.52 AI408351 ---0.51 0.05 0.22 0.27 -0.01 0.09 1.66 1.41 AI175346 --0.66 0.16 -0.14 0.12 -0.13 0.35 -1.74 -1.73 BF285771 Similar to GDP-dissociation inhibitor (LOC362456), mRNA -1.02 0.22 0.32 0.34 0.03 0.08 2.54 2.08 AI170324 ---0.40 0.05 0.13 0.02 0.01 0.10 1.44 1.32

PAGE 76

66 BF387360 Similar to Igsf7 protein (LOC287813), mRNA -0.42 0.07 0.59 0.21 0.10 0.24 2.01 1.43 AA945986 --0.27 0.12 -0.41 0.16 -0.01 0.04 -1.61 -1.21 BF410946 ---0.74 0.08 -0.01 0.13 0.12 0.08 1.66 1.81 BM389026 Similar to osteoblast specific factor 2 precursor (LOC361945), mRNA -0.01 0.13 -0.56 0.15 0.43 0.10 -1.46 1.36 BM389075 --0.26 0.02 -0.29 0.04 0.00 0.01 -1.46 -1.20 BE098739 ---1.95 0.27 0.93 0.60 -0.04 0.11 7.39 3.76 BI290779 Similar to adaptor protein kanadaptin (LOC298805), mRNA 0.31 0.24 -0.41 0.16 0.00 0.07 -1.65 -1.24 AI716248 ---0.81 0.26 0.32 0.44 0.01 0.19 2.19 1.76 AA850715 ---0.16 0.01 0.44 0.16 -0.07 0.17 1.51 1.06 AI408440 ---1.35 0.16 0.40 0.64 0.16 0.29 3.38 2.85 BG373505 Similar to proteasome (prosome, macropain) subunit, beta type 10 (LOC291983), mRNA -0.18 0.09 0.47 0.19 -0.01 0.09 1.57 1.13 AI411374 --0.58 0.22 -0.60 0.21 -0.03 0.14 -2.27 -1.53 BF282054 Similar to RIKEN cDNA 1110055L24 (LOC295629), mRNA -0.54 0.27 0.65 0.46 0.03 0.09 2.27 1.48 AI716756 ---0.28 0.08 0.34 0.16 0.01 0.11 1.54 1.22 AI010883 --0.39 0.18 -0.85 0.31 -0.03 0.15 -2.35 -1.34 BF398424 B7-H3 -0.47 0.08 0.01 0.08 0.05 0.04 1.39 1.43 BM389619 myosin binding protein C, slow type 0.44 0.43 -1.40 0.64 -0.25 0.56 -3.58 -1.61 AI408294 ---0.47 0.02 0.41 0.19 0.00 0.03 1.84 1.39 BF408611 Similar to sarcolipin (LOC367086), mRNA -0.51 0.12 0.09 0.32 0.94 0.26 1.51 2.72 AA801107 EH-domain containing 4 -0.42 0.13 0.50 0.18 0.00 0.07 1.89 1.34 AI549249 Similar to sorting nexin 2 (LOC291464), mRNA -0.19 0.15 0.87 0.49 -0.05 0.20 2.08 1.10 BE098506 Similar to alcohol dehydrogenase Pan1b (LOC289456), mRNA -0.67 0.14 0.42 0.45 0.09 0.20 2.13 1.69 AI179464 RM1 mRNA, partial sequence -0.24 0.08 0.28 0.02 -0.01 0.02 1.43 1.17 AI236590 myeloid differentiation primary response gene 88 -0.46 0.20 0.33 0.24 0.02 0.12 1.73 1.40 BG372375 ---0.30 0.07 0.90 0.23 -0.07 0.16 2.30 1.18 AI406660 ---0.99 0.20 1.04 0.30 -0.03 0.22 4.08 1.94 AI010048 --0.45 0.10 -0.37 0.19 0.04 0.17 -1.76 -1.33 AI406533 ---0.72 0.12 0.07 0.27 0.28 0.28 1.74 2.01 BM384374 ---0.70 0.11 0.68 0.41 -0.02 0.29 2.61 1.61 BF394235 CG6210-like 0.24 0.05 -0.31 0.04 0.06 0.11 -1.46 -1.13 BI301280 --0.44 0.14 -0.51 0.26 -0.11 0.20 -1.93 -1.45 BF282365 ---1.12 0.09 0.32 0.40 -0.01 0.23 2.73 2.17 AI103993 --0.51 0.25 -0.36 0.09 0.07 0.14 -1.82 -1.35 BM384311 Similar to platelet-derived growth factor receptor-like (LOC290771), mRNA 0.57 0.10 -0.33 0.06 -0.05 0.10 -1.86 -1.53 BE107309 --0.26 0.02 -0.26 0.04 -0.02 0.09 -1.44 -1.21 BG371585 Similar to leucine-rich alpha-2-glycoprotein (LOC367455), mRNA -1.03 0.16 0.40 0.36 0.05 0.22 2.70 2.11 BI298596 --0.53 0.16 -0.19 0.16 0.06 0.10 -1.65 -1.39 AW524523 ---0.27 0.02 0.42 0.17 0.08 0.15 1.61 1.28 AI577508 --1.00 0.39 -0.62 0.22 0.09 0.27 -3.08 -1.88

PAGE 77

67 AA850867 Similar to gamma-sarcoglycan (LOC305941), mRNA 0.05 0.30 -0.34 0.24 0.99 0.08 -1.31 1.93 AA945915 ---0.62 0.06 0.58 0.48 -0.01 0.18 2.29 1.52 AI411941 Similar to KIAA1866 protein (LOC308099), mRNA -0.03 0.06 -0.19 0.13 1.21 0.30 -1.11 2.37 AI102519 DAP12 -1.75 0.10 0.66 0.34 -0.01 0.11 5.31 3.34 BE103235 --0.70 0.13 -0.35 0.27 0.09 0.18 -2.07 -1.53 BI277043 melanoma cell adhesion molecule -0.54 0.10 0.27 0.08 0.00 0.19 1.76 1.45 BI274660 Similar to RIKEN cDNA 5730457F11 (LOC302972), mRNA -0.51 0.04 0.36 0.29 -0.06 0.16 1.82 1.37 AI177761 Similar to macrosialin (LOC287435), mRNA -1.40 0.21 0.56 0.36 -0.16 0.29 3.88 2.36 AA818819 --0.64 0.03 -0.20 0.20 -0.14 0.29 -1.79 -1.72 AI706777 ---0.79 0.08 0.50 0.51 -0.08 0.35 2.44 1.63 AI171653 --0.57 0.27 -0.66 0.08 -0.05 0.22 -2.34 -1.54 BI292651 --0.64 0.24 -0.70 0.33 -0.01 0.10 -2.54 -1.57 BG378926 Similar to endothelial monocyte-activating polypeptide (LOC295195), mRNA -0.27 0.06 0.22 0.03 0.01 0.02 1.40 1.21 BI294983 --1.27 0.57 -0.88 0.50 -0.03 0.32 -4.45 -2.48 AI717476 muscle glycogen phosphorylase 1.42 0.82 -0.71 0.43 0.15 0.63 -4.37 -2.41 AI104533 --0.38 0.38 -1.19 0.66 -0.01 0.16 -2.97 -1.31 AI237401 Similar to alpha globin (LOC287167), mRNA -0.40 0.33 0.89 0.22 0.02 0.14 2.44 1.34 AI012221 LOC361792 (LOC361792), mRNA /// RT1 class I, CE5 -0.58 0.07 0.38 0.16 0.05 0.22 1.94 1.55 AA892795 ubiquitin conjugating enzyme 0.54 0.22 -0.33 0.04 -0.01 0.07 -1.82 -1.46 BI278813 Similar to transmembrane protein (63kD), endoplasmic reticulum/Golgi interm; transmembrane protein (63kD), endoplasmic reticulum/Golgi intermediate compartment (LOC362859), mRNA -0.58 0.27 0.55 0.33 0.09 0.27 2.19 1.59 BF420426 Similar to interferon alpha/beta receptor (LOC288264), mRNA -0.48 0.32 0.44 0.24 -0.02 0.15 1.88 1.37 BF395171 EH-domain containing 4 -0.69 0.29 0.69 0.31 0.04 0.12 2.61 1.67 BM384701 ---0.72 0.28 0.06 0.08 0.17 0.30 1.71 1.85 AI144944 --0.49 0.13 -0.06 0.14 -0.14 0.13 -1.47 -1.55 BM392055 --0.37 0.14 -0.21 0.13 -0.03 0.06 -1.49 -1.32 BF282961 Similar to gp49B2 (LOC292594), mRNA -1.14 0.23 1.38 0.35 0.12 0.29 5.73 2.39 BF281879 Similar to germ cell-less protein (LOC312516), mRNA 0.31 0.10 -0.43 0.06 -0.03 0.10 -1.66 -1.26 BI296037 --1.23 0.55 -0.66 0.52 -0.01 0.25 -3.72 -2.37 BE109334 --0.63 0.25 -0.24 0.12 -0.08 0.17 -1.82 -1.63 BI295991 RAB2, member RAS oncogene family-like -0.42 0.15 0.44 0.18 -0.10 0.17 1.82 1.26 AI103572 --0.46 0.12 -0.32 0.11 -0.11 0.20 -1.71 -1.48 BI282296 ---0.44 0.26 0.36 0.21 0.01 0.02 1.75 1.37 AI599143 --0.21 0.17 -0.66 0.20 0.13 0.29 -1.83 -1.06 BI276069 --0.47 0.12 -0.10 0.25 -0.17 0.02 -1.49 -1.56 AI407953 ---1.01 0.19 0.59 0.60 0.16 0.46 3.04 2.26 AI137506 Ab1-046 mRNA, complete cds 0.46 0.14 -0.98 0.64 -0.12 0.23 -2.71 -1.49 AI716887 Similar to hypothetical protein 0.93 0.51 -0.38 0.27 0.05 0.34 -2.49 -1.85

PAGE 78

68 FLJ12921 (LOC305675), mRNA AI010267 --0.73 0.12 -0.17 0.18 -0.04 0.18 -1.86 -1.71 BF399639 Hypothetical LOC317423 (LOC317423), mRNA 0.23 0.08 -0.03 0.11 -0.34 0.06 -1.20 -1.48 BF395317 Similar to MS4A6D protein (LOC361735), mRNA -1.50 0.20 1.77 0.62 0.03 0.11 9.66 2.89 BI303340 --0.12 0.21 0.25 0.06 -0.44 0.15 1.10 -1.47 AI102249 Similar to RIKEN cDNA 1810048J11 (LOC314219), mRNA 0.56 0.02 -0.29 0.26 0.10 0.25 -1.81 -1.38 BI282932 ---0.83 0.05 0.17 0.10 0.02 0.25 2.00 1.80 BE095847 ---0.25 0.09 0.42 0.13 0.07 0.15 1.59 1.25 BF288208 ---0.65 0.09 0.30 0.30 -0.01 0.12 1.93 1.56 BF418957 Similar to Complement component 1, q subcomponent, alpha polypeptide (LOC298566), mRNA -1.17 0.26 0.32 0.30 -0.10 0.17 2.81 2.10 AW532489 --0.71 0.22 -0.42 0.37 -0.39 0.34 -2.18 -2.13 BF288115 ---0.82 0.07 0.31 0.42 0.19 0.35 2.19 2.01 AA998964 ---1.04 0.06 0.51 0.63 -0.05 0.21 2.91 1.99 AI170671 --0.44 0.21 -0.43 0.10 0.02 0.04 -1.83 -1.34 AA945955 --0.25 0.22 -1.50 0.44 -0.05 0.16 -3.36 -1.23 BF397709 --0.34 0.03 -0.21 0.11 0.03 0.06 -1.46 -1.24 BM386777 --0.25 0.16 -0.47 0.15 -0.10 0.19 -1.64 -1.27 AA819034 putative ISG12(b) protein -0.73 0.06 0.90 0.43 0.07 0.22 3.10 1.75 AW525240 --0.30 0.05 -0.41 0.13 -0.04 0.23 -1.64 -1.27 BE111378 Similar to 60S ribosomal protein L3-like (LOC287122), mRNA 0.97 0.38 -0.34 0.33 0.05 0.10 -2.47 -1.89 AW531805 Similar to This ORF is capable of encoding 404aa which is homologous to two human interferon-inducible p roteins, 54 kDa and 56 kDa proteins; ORF (LOC309526), mRNA -0.57 0.22 1.71 0.70 0.05 0.09 4.84 1.54 BF408536 ---0.46 0.05 0.19 0.25 0.07 0.10 1.56 1.44 BM386570 ---0.45 0.02 0.49 0.22 0.06 0.12 1.91 1.43 BI296868 --0.26 0.30 -0.67 0.10 0.16 0.30 -1.90 -1.07 BF411331 Similar to serine (or cysteine) proteinase inhibitor, clade B, member 1b; serine (or cysteine) proteinase inhibitor, clade B (ovalbumin), member 1b (LOC291091), mRNA -0.98 0.07 0.23 0.33 -0.05 0.24 2.31 1.91 BI291872 ---0.46 0.05 0.35 0.05 -0.02 0.15 1.75 1.36 AI233530 --0.00 0.03 -0.82 0.17 1.24 0.21 -1.77 2.37 BF389682 ---1.23 0.23 0.75 0.45 -0.13 0.61 3.92 2.14 BI301478 ---0.49 0.09 0.46 0.20 0.00 0.12 1.93 1.40 BG378317 --0.69 0.16 -0.35 0.30 -0.07 0.33 -2.06 -1.70 AI010237 ---0.70 0.25 0.40 0.46 0.03 0.09 2.15 1.66 BM386169 Similar to Apbb1ip protein (LOC307171), mRNA -0.90 0.10 0.62 0.67 0.07 0.11 2.87 1.95 AI071674 --0.62 0.15 -0.16 0.11 0.00 0.17 -1.71 -1.54 BG378249 RT1 class II, locus Ba -1.31 0.20 0.31 0.35 0.02 0.04 3.07 2.50 BI275485 Similar to semaphorin A (LOC363142), mRNA 0.74 0.27 -0.16 0.14 -0.09 0.18 -1.87 -1.78 AI179507 tissue factor pathway inhibitor 2 -0.85 0.06 0.13 0.33 0.17 0.17 1.97 2.02 AA800814 Similar to Tumor necrosis factor -0.74 0.19 0.31 0.42 0.00 0.13 2.08 1.68

PAGE 79

69 ligand superfamily member 13 (A proliferation-inducing ligand) (APRIL) (LOC287437), mRNA BE099439 Similar to hypothetical protein FKSG28 (LOC293997), mRNA 0.29 0.05 -0.28 0.10 0.03 0.08 -1.48 -1.20 BF420810 histidine rich calcium binding protein0.99 0.10 -0.71 0.72 0.09 0.31 -3.26 -1.88 BI296317 ---1.43 0.11 0.57 0.44 -0.10 0.19 3.97 2.51 AA799711 ---0.54 0.09 0.31 0.15 -0.08 0.20 1.80 1.37 AA848916 ---0.28 0.16 0.55 0.29 -0.01 0.15 1.77 1.20 AA965084 ---0.78 0.02 0.08 0.19 2.41 0.23 1.82 9.14 BF284791 ---0.17 0.12 0.71 0.40 -0.09 0.19 1.84 1.05 AI639103 ---1.02 0.14 0.47 0.41 -0.04 0.10 2.80 1.97 BE120719 ---0.33 0.07 0.34 0.19 0.06 0.16 1.59 1.31 BI275261 ---1.46 0.17 1.60 0.89 -0.18 0.42 8.33 2.43 AA866443 ---0.66 1.28 -0.13 0.08 3.39 0.32 1.45 16.62AI500952 ---0.73 0.17 0.46 0.45 -0.07 0.19 2.29 1.58 BG670778 --0.49 0.29 -0.79 0.33 -0.23 0.45 -2.42 -1.64 AI639412 Similar to asporin precursor (LOC306805), mRNA 0.06 0.28 -1.02 0.30 0.47 0.36 -2.12 1.32 AI638986 --0.54 0.34 -0.94 0.25 0.03 0.06 -2.79 -1.43 AI170660 --0.33 0.24 -0.46 0.14 0.00 0.22 -1.74 -1.26 AI408425 Similar to toll-like receptor 7 (LOC317468), mRNA -0.54 0.09 0.70 0.46 -0.01 0.13 2.36 1.44 BG673602 adipose differentiation-related protein-0.20 0.08 1.08 0.37 0.05 0.20 2.42 1.19 BE116084 ---0.42 0.08 1.50 0.55 0.10 0.38 3.79 1.43 AW919180 --1.77 0.65 -1.07 0.68 0.27 0.73 -7.17 -2.84 BF563716 --0.45 0.11 -0.15 0.08 -0.05 0.12 -1.52 -1.42 BG664221 Similar to osteoglycin precursor (LOC291015), mRNA 0.21 0.14 -1.11 0.30 0.02 0.18 -2.49 -1.14 BI290159 Similar to PEST phosphatase interacting protein (LOC300732), mRNA -0.07 0.18 0.53 0.02 -0.02 0.03 1.52 1.04 BF411036 Similar to interferon regulatory factor 7 (LOC293624), mRNA -0.76 0.16 1.87 0.59 0.24 0.47 6.20 2.01 BM388456 procollagen, type XI, alpha 1 0.08 0.42 -0.79 0.38 0.54 0.37 -1.83 1.37 BM389391 Similar to serine protease (LOC302971), mRNA 0.00 0.05 -0.09 0.10 0.43 0.09 -1.06 1.34 AA997590 Similar to osteoglycin precursor (LOC291015), mRNA 0.79 0.06 -1.23 0.35 -0.01 0.62 -4.05 -1.74 AA923974 --0.64 0.12 -0.21 0.07 0.06 0.12 -1.80 -1.49 AA875124 ---1.54 0.10 0.19 0.45 0.19 0.18 3.31 3.30 BF290410 ---0.39 0.28 0.67 0.28 0.05 0.31 2.07 1.36 BF550033 --0.50 0.11 -0.42 0.18 0.05 0.15 -1.89 -1.37 NM_053290 phosphoglycerate mutase 1 -0.34 0.10 0.33 0.14 -0.06 0.14 1.59 1.21 BI275294 glutamine synthetase 1 -0.25 0.26 0.72 0.18 0.06 0.12 1.95 1.23 NM_022952 clathrin-associated protein 17 -0.34 0.05 0.52 0.30 0.01 0.08 1.82 1.28 NM_017113 granulin -0.57 0.13 0.53 0.23 0.00 0.07 2.15 1.49 NM_012949 --1.55 0.43 -1.24 0.76 0.24 0.50 -6.91 -2.48 NM_012505 ATPase, Na+K+ transporting, alpha 21.31 0.27 -0.71 0.50 0.05 0.28 -4.05 -2.40 NM_019358 glycoprotein 38 -0.77 0.19 0.83 0.43 0.01 0.21 3.02 1.71 NM_019289 actin related protein 2/3 complex, subunit 1B -0.62 0.17 0.64 0.23 0.03 0.11 2.39 1.57

PAGE 80

70 BI291434 phosphofructokinase, muscle 1.09 0.58 -0.37 0.34 0.14 0.29 -2.75 -1.94 NM_022676 protein phosphatase 1, regulatory (inhibitor) subunit 1A 0.78 0.30 -0.33 0.13 -0.01 0.20 -2.16 -1.73 NM_053950 eukaryotic translation initiation factor 2B 0.56 0.26 -0.34 0.19 0.04 0.20 -1.87 -1.43 NM_019292 carbonic anhydrase 3 1.01 0.41 -1.07 0.41 0.07 0.40 -4.23 -1.93 NM_012716 solute carrier family 16 (monocarboxylic acid transporters), member 1 -0.28 0.20 0.75 0.28 0.00 0.03 2.05 1.22 NM_017320 cathepsin S -1.31 0.08 0.35 0.46 0.07 0.08 3.17 2.60 NM_130741 lipocalin 2 -1.96 0.12 1.43 0.33 -0.10 0.84 10.433.64 NM_053883 dual specificity phosphatase 6 -0.25 0.12 0.53 0.16 -0.02 0.06 1.72 1.18 NM_130409 complement component factor h -1.27 0.11 0.55 0.63 0.16 0.16 3.53 2.70 NM_012829 cholecystokinin 0.55 0.14 -0.15 0.28 -0.08 0.08 -1.62 -1.55 NM_031703 aquaporin 3 -0.47 0.07 0.42 0.19 0.01 0.05 1.85 1.40 NM_053587 S100 calcium binding protein A9 (calgranulin B) -2.64 0.40 1.15 0.18 0.03 0.31 13.766.35 NM_053687 schlafen 3 -1.32 0.14 1.87 0.61 0.16 0.33 9.12 2.79 NM_020308 a disintegrin and metalloproteinase domain 15 (metargidin) -0.37 0.13 0.31 0.20 0.00 0.05 1.60 1.29 NM_019311 inositol polyphosphate-5-phosphatase D -0.49 0.09 0.34 0.31 0.02 0.11 1.77 1.42 NM_031565 carboxylesterase 1 0.57 0.26 -0.77 0.26 0.01 0.28 -2.53 -1.47 NM_024356 ---0.48 0.09 0.97 0.33 0.00 0.07 2.72 1.40 NM_012827 bone morphogenetic protein 4 0.28 0.10 -0.40 0.11 -0.05 0.16 -1.60 -1.26 NM_019335 Protein kinase, interferon-inducible double stranded RNA dependent -0.30 0.11 0.56 0.25 -0.04 0.12 1.82 1.20 AF007789 plasminogen activator, urokinase receptor -0.25 0.15 0.79 0.36 0.01 0.11 2.05 1.19 NM_013037 interleukin 1 receptor-like 1 -0.93 0.15 1.08 0.28 0.07 0.31 4.04 2.00 NM_021584 activity and neurotransmitter-induced early gene protein 4 (ania-4) -0.49 0.12 -0.09 0.18 0.20 0.18 1.32 1.62 NM_134350 myxovirus (influenza virus) resistance 2 -0.19 0.07 1.49 0.67 0.12 0.37 3.20 1.24 NM_030845 chemokine (C-X-C motif) ligand 1 -0.33 0.24 1.49 0.71 0.00 0.23 3.54 1.26 NM_019205 small inducible cytokine subfamily A11 -0.40 0.01 0.28 0.12 0.07 0.25 1.60 1.38 NM_032612 signal transducer and activator of transcription 1 -0.68 0.07 0.40 0.30 -0.01 0.16 2.11 1.58 NM_012840 --0.36 0.31 -1.57 0.89 0.35 0.57 -3.81 -1.01 NM_022294 ETL protein -0.77 0.10 0.00 0.20 0.22 0.15 1.70 1.98 J02679 NAD(P)H dehydrogenase, quinone 1-0.18 0.01 0.52 0.18 0.00 0.04 1.63 1.13 NM_133542 immunoglobulin superfamily, member 6 -1.56 0.17 1.00 0.62 0.02 0.24 5.93 3.00 U84410 caspase 3 -0.72 0.12 0.28 0.09 -0.01 0.14 2.00 1.63 NM_133537 extracellular proteinase inhibitor -0.86 0.23 -0.07 0.29 1.90 0.42 1.72 6.75 NM_017156 --0.34 0.22 -1.24 0.66 -0.18 0.38 -3.00 -1.43 J02612 UDP glycosyltransferase 1 family polypeptide A2 /// UDP glycosyltransferase 1 family polypeptide A4 /// UDP glycosyltransferase 1 family, polypeptide A1 /// UDP glycosyltransferase 1 family, polypeptide A6 /// UDP -0.39 0.01 0.29 0.14 -0.08 0.18 1.59 1.24

PAGE 81

71 glycosyltransferase 1 family, polypeptide NM_012640 retinol binding protein 2, cellular -1.19 0.33 0.12 0.08 0.00 0.17 2.49 2.28 NM_021588 myoglobin 0.13 0.27 -1.50 0.29 0.51 0.17 -3.10 1.30 NM_130743 putative ISG12(a) protein -0.72 0.13 0.43 0.29 0.05 0.15 2.22 1.71 NM_012605 myosin, light polypeptide 2 0.67 0.18 -1.31 0.84 -0.03 0.28 -3.94 -1.63 AF129400 FXYD domain-containing ion transport regulator 2 -0.96 0.15 0.51 0.51 0.13 0.14 2.75 2.12 AF200684 solute carrier family 7 (cationic amino acid transporter, y+ system), member 7 -1.09 0.05 0.81 0.34 0.04 0.09 3.73 2.19 NM_012593 kallikrein 7 -0.29 0.10 -0.02 0.16 0.61 0.20 1.20 1.87 NM_022194 interleukin 1 receptor antagonist -0.37 0.03 0.59 0.35 -0.01 0.02 1.95 1.28 NM_012703 thyroid hormone responsive protein 0.40 0.19 -0.55 0.22 -0.13 0.26 -1.93 -1.44 BF289368 lipopolysaccharide binding protein -2.09 0.14 0.14 0.24 0.14 0.63 4.71 4.71 BG668902 thymosin beta-4 -0.53 0.16 0.06 0.12 0.03 0.03 1.51 1.47 BE110597 Fc receptor, IgG, alpha chain transporter -0.65 0.17 0.73 0.30 0.04 0.28 2.59 1.61 D88250 complement component 1, s subcomponent -0.77 0.13 0.04 0.24 0.31 0.17 1.75 2.12 D29960 heat shock protein, alpha-crystallin-related, B6 0.80 0.34 -1.32 0.72 -0.04 0.32 -4.34 -1.79 AF065438 lectin, galactoside-binding, soluble, 3 binding protein -1.13 0.03 0.57 0.38 0.01 0.09 3.25 2.20 AF065147 CD44 antigen -0.59 0.13 0.54 0.04 -0.02 0.19 2.19 1.48 AF047707 UDP-glucose ceramide glucosyltransferase -0.49 0.16 0.36 0.19 0.06 0.13 1.80 1.46 AF159245 cytochrome P450 CYP2B21 0.24 0.36 -0.77 0.36 0.33 0.29 -2.01 1.07 BI285494 interferon induced transmembrane protein 2 (1-8D) -0.58 0.26 0.36 0.16 -0.04 0.09 1.91 1.45 U20286 lamina-associated polypeptide 1C -0.44 0.12 0.28 0.24 -0.02 0.04 1.65 1.34 AF072892 chondroitin sulfate proteoglycan 2 (versican) -0.72 0.24 0.53 0.33 -0.16 0.31 2.37 1.48 M24024 RT1 class Ib, locus Aw2 -0.74 0.16 0.15 0.28 0.04 0.04 1.85 1.71 BI300274 G protein-coupled receptor 48 0.40 0.10 -0.29 0.18 -0.09 0.15 -1.61 -1.40 AA943537 zyxin -0.30 0.06 0.34 0.14 0.05 0.13 1.55 1.28 BI277586 myosin, heavy polypeptide 4 0.32 0.28 -1.52 0.59 0.18 0.75 -3.58 -1.10 AW253722 RAB13, member RAS oncogene family -0.37 0.04 0.22 0.17 -0.03 0.09 1.51 1.26 AA850991 chondroitin sulfate proteoglycan 2 (versican) -0.36 0.04 0.71 0.37 -0.12 0.24 2.10 1.17 BI288582 collagen, type XVIII, alpha 1 -0.60 0.03 0.16 0.16 0.05 0.09 1.70 1.57 X57523 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) -0.24 0.09 0.46 0.11 0.08 0.21 1.62 1.25 AF029241 MHC class Ib RT1.S3 -0.62 0.13 0.53 0.39 -0.06 0.17 2.21 1.47 BF419995 --1.00 0.60 -0.44 0.08 0.00 0.38 -2.71 -2.00 M60616 ---2.63 0.07 0.65 0.21 0.16 0.37 9.70 6.90 K01677 eukaryotic translation initiation factor 5 0.51 0.03 -0.11 0.11 0.06 0.16 -1.54 -1.37 AJ243974 MHC class Ib RT1.S3 -0.47 0.15 0.71 0.39 -0.08 0.15 2.28 1.31 AJ243973 MHC class Ib RT1.S3 -0.52 0.20 0.73 0.38 -0.01 0.04 2.39 1.43 BG663422 putative G protein coupled receptor -0.36 0.18 -0.03 0.07 0.23 0.08 1.26 1.51 AF084544 chondroitin sulfate proteoglycan 2 (versican) -0.93 0.41 0.68 0.24 -0.25 0.52 3.06 1.60

PAGE 82

72 BM383531 --0.05 0.06 0.16 0.18 -0.63 0.20 1.08 -1.61 AW251927 Ly6-C antigen gene 0.23 0.20 -1.07 0.60 0.33 0.49 -2.46 1.07 U56824 killer cell lectin-like receptor, subfamily A, member 5 -1.57 0.10 0.70 0.88 0.12 0.13 4.83 3.23 BI285865 Similar to transgelin 2; SM22-alpha homolog (LOC304983), mRNA -0.25 0.16 0.43 0.04 0.01 0.04 1.60 1.19 AI102495 nucleoside phosphorylase -0.51 0.19 0.42 0.21 -0.02 0.05 1.90 1.40 AI233210 ---0.75 0.22 0.81 0.39 0.07 0.18 2.94 1.76 AA799557 --1.20 0.34 -0.31 0.23 0.06 0.16 -2.85 -2.21 BI275880 Similar to RIKEN cDNA 1110033G07 (LOC362087), mRNA 0.37 0.20 -0.37 0.21 -0.05 0.11 -1.66 -1.34 AA800199 Similar to RIKEN cDNA 1110020C13 (LOC363004), mRNA -0.76 0.09 0.36 0.37 -0.05 0.16 2.17 1.64 BG671569 Similar to RIKEN cDNA D130038B21 (LOC315594), mRNA-0.68 0.09 0.09 0.19 0.05 0.05 1.70 1.66 AA946351 Similar to adipocyte-specific protein 3 (LOC313770), mRNA -0.35 0.08 -0.05 0.09 0.25 0.10 1.23 1.51 AI228548 Similar to S-100 protein, alpha chain (LOC295214), mRNA 0.37 0.21 -0.54 0.37 -0.01 0.03 -1.89 -1.30 BM384693 Similar to Capg protein (LOC297339), mRNA -0.25 0.06 0.41 0.11 0.06 0.14 1.58 1.25 BI294841 ---0.64 0.04 0.07 0.07 0.00 0.25 1.63 1.56 BF284922 --0.29 0.28 -0.72 0.25 -0.12 0.27 -2.01 -1.34 AI102215 LOC360614 (LOC360614), mRNA -0.38 0.08 0.33 0.17 0.00 0.20 1.63 1.30 AA943740 --0.23 0.08 -0.49 0.21 -0.08 0.17 -1.64 -1.24 AI411057 Similar to coactosin-like 1; coactosin-like protein (LOC361422), mRNA -1.74 0.12 0.66 0.38 0.09 0.23 5.28 3.54 BI276959 --1.16 0.41 -1.49 0.68 0.17 0.39 -6.27 -1.98 AI577319 hemoglobin alpha, adult chain 1 -0.30 0.26 0.44 0.04 -0.09 0.15 1.67 1.16 BF392884 --0.52 0.03 -0.35 0.32 -0.18 0.26 -1.83 -1.62 AI012109 Similar to Lsp1 protein (LOC361680), mRNA -1.12 0.15 0.45 0.27 -0.03 0.06 2.97 2.13 AI104913 tropomodulin 1 0.54 0.15 -0.14 0.07 0.01 0.25 -1.60 -1.45 AI177645 Similar to cDNA sequence BC032204 (LOC309186), mRNA -0.85 0.04 0.64 0.48 -0.04 0.34 2.81 1.75 AW533234 --0.79 0.30 -0.35 0.19 0.03 0.12 -2.21 -1.69 AA945877 ---0.52 0.06 0.11 0.18 0.02 0.03 1.54 1.45 BF417032 Transferrin receptor 0.39 0.11 -0.43 0.19 0.03 0.10 -1.76 -1.28 AI169176 Similar to scotin (LOC301013), mRNA -0.57 0.12 0.35 0.24 -0.02 0.06 1.89 1.47 BI285793 Similar to Macrophage colony stimulating factor I receptor precursor (CSF-1-R) (Fms proto-oncogene) (c-fms) (LOC307403), mRNA -0.72 0.11 0.83 0.39 0.07 0.22 2.92 1.73 BM389498 Similar to acid sphingomyelinase-like phosphodiesterase (LOC294422), mRNA -0.68 0.08 0.34 0.44 0.05 0.16 2.01 1.65 BE109616 --0.86 0.25 -0.39 0.17 -0.09 0.19 -2.37 -1.92 BF399310 --0.55 0.19 -0.42 0.31 -0.10 0.27 -1.97 -1.57 BI296340 --0.04 0.18 -0.15 0.13 0.90 0.21 -1.14 1.81 BM385779 --0.55 0.07 -0.19 0.17 0.00 0.16 -1.66 -1.47 BI283756 Similar to talin (LOC313494), mRNA-0.50 0.03 0.30 0.12 -0.02 0.06 1.74 1.39 AI170394 ---2.29 0.17 0.70 0.48 -0.06 0.13 7.92 4.68 BI274408 --0.53 0.04 -0.53 0.14 -0.03 0.16 -2.08 -1.47

PAGE 83

73 AI639268 Similar to DKFZP566O084 protein (LOC287411), mRNA 1.03 0.22 -0.26 0.35 -0.05 0.35 -2.45 -2.12 AI178808 interleukin 2 receptor, gamma chain -1.01 0.17 0.38 0.33 -0.01 0.09 2.63 2.01 AI407351 ---0.52 0.03 0.13 0.19 0.07 0.12 1.57 1.50 BE095824 Similar to Small inducible cytokine A6 precursor (CCL6) (C10 protein) (LOC287910), mRNA -1.47 0.15 1.36 0.44 0.12 0.39 7.09 3.01 AW253339 ---0.67 0.16 0.24 0.07 -0.04 0.10 1.88 1.55 AI104326 --0.86 0.39 -0.51 0.33 0.05 0.29 -2.58 -1.75 BI281183 --1.10 0.60 -0.35 0.32 0.11 0.31 -2.72 -1.97 BE109711 ---1.09 0.27 0.32 0.09 -0.05 0.23 2.65 2.05 BF406693 Similar to Lama4 protein (LOC309816), mRNA -0.46 0.15 0.30 0.09 -0.03 0.20 1.70 1.35 AI410467 Similar to Intercellular adhesion molecule-2 precursor (ICAM-2) (CD102) (Lymphocyte function-associated AG-1 counter-receptor) (LOC360647), mRNA -0.59 0.16 0.21 0.25 -0.06 0.11 1.74 1.44 AA945737 chemokine (C-X-C motif) receptor 4-0.73 0.14 0.33 0.30 -0.05 0.12 2.08 1.61 BE110616 ---0.45 0.13 0.03 0.11 0.21 0.17 1.40 1.59 BG381256 --0.54 0.01 -0.34 0.18 -0.02 0.11 -1.83 -1.47 AI411761 Similar to RIKEN cDNA 4832415H08 gene (LOC304960), mRNA -0.46 0.04 0.02 0.08 0.21 0.13 1.39 1.59 AI102248 ---0.47 0.06 0.07 0.15 0.13 0.18 1.45 1.52 AI317821 --0.70 0.14 -0.66 0.45 -0.03 0.22 -2.56 -1.65 BG379338 ---0.09 0.13 0.80 0.37 -0.20 0.24 1.85 -1.08 AI177869 ---0.80 0.21 0.08 0.31 0.17 0.23 1.83 1.96 BI279325 ---0.81 0.08 0.62 0.49 0.01 0.03 2.69 1.76 AI236615 Hypothetical LOC289904 (LOC289904), mRNA 0.81 0.29 -0.25 0.10 -0.02 0.06 -2.08 -1.78 BG373049 --0.69 0.33 -0.41 0.08 -0.08 0.32 -2.14 -1.71 BF393825 Similar to RIKEN cDNA 3110037K17 (LOC362431), mRNA -1.54 0.13 1.04 0.55 0.01 0.22 5.97 2.93 BG666368 ---0.19 0.03 0.52 0.25 0.00 0.08 1.63 1.14 BF390510 Similar to RIKEN cDNA 9230117N10 (LOC361749), mRNA -0.47 0.05 0.29 0.28 0.04 0.10 1.69 1.42 BM392135 Similar to ETS-domain protein ELK-3 (ETS-related protein NET) (ETS-related protein ERP) (LOC362871), mRNA -0.67 0.10 0.35 0.34 0.18 0.23 2.02 1.79 AI177057 ---0.86 0.17 0.11 0.08 -0.15 0.29 1.95 1.63 AI171655 --0.47 0.11 -0.19 0.23 -0.08 0.09 -1.58 -1.46 BE111310 --1.52 0.22 -0.42 0.34 0.19 0.44 -3.84 -2.53 BE104098 ---0.56 0.03 0.47 0.26 -0.02 0.18 2.04 1.45 BE107296 --0.42 0.17 -0.66 0.23 -0.18 0.33 -2.11 -1.51 AI412625 --0.16 0.14 -0.93 0.33 -0.02 0.33 -2.13 -1.13 BI283388 ---0.43 0.10 0.30 0.17 0.03 0.06 1.65 1.37 BM391206 Similar to Histone H2B 291B (LOC306945), mRNA 0.25 0.11 -0.47 0.12 -0.01 0.04 -1.64 -1.19 AA946538 ---0.55 0.13 0.28 0.27 -0.05 0.12 1.78 1.41 AI171686 --0.42 0.08 -0.22 0.17 -0.08 0.15 -1.56 -1.42 BE110671 ---0.32 0.10 0.36 0.14 0.07 0.17 1.61 1.31

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74 BF396602 secreted frizzled-related protein 2 -2.42 0.24 0.16 0.55 0.18 0.21 5.97 6.08 BG378721 ---0.24 0.03 0.72 0.44 0.05 0.09 1.93 1.22 BF558075 ---0.55 0.08 0.25 0.16 0.00 0.11 1.74 1.46 AI231279 --0.43 0.22 -0.58 0.28 -0.04 0.24 -2.00 -1.38 BI274054 Similar to folate-binding protein 2 precursor mouse (LOC293154), mRNA -0.90 0.07 0.83 0.38 -0.14 0.43 3.31 1.69 AI577849 Similar to Carboxypeptidase X 1 (M14 family) (LOC296156), mRNA-1.41 0.15 1.29 0.61 0.31 0.57 6.52 3.30 BF389398 Notch gene homolog 1, (Drosophila)0.45 0.10 -0.26 0.25 -0.05 0.11 -1.63 -1.41 BF284190 --0.65 0.13 -0.09 0.24 -0.07 0.08 -1.66 -1.64 AI111559 ---0.53 0.05 0.28 0.28 0.16 0.22 1.75 1.61 AA945955 --0.22 0.34 -1.14 0.28 0.33 0.34 -2.58 1.08 AI412627 Similar to 2210023K21Rik protein (LOC305237), mRNA -0.38 0.10 0.38 0.27 0.00 0.04 1.69 1.29 BE108860 --0.49 0.04 -0.11 0.11 -0.01 0.10 -1.51 -1.41 BI294706 Similar to MS4A6B protein (LOC293749), mRNA -1.68 0.23 1.06 0.57 -0.01 0.16 6.71 3.18 AI169829 mannose-binding protein associated serine protease-1 -0.15 0.14 0.06 0.12 0.60 0.22 1.16 1.68 AI072459 --0.83 0.13 -0.63 0.45 -0.05 0.33 -2.75 -1.84 AI556803 Similar to pleckstrin (LOC364206), mRNA -0.48 0.14 0.71 0.45 0.03 0.21 2.27 1.42 BE105721 --0.62 0.11 -0.32 0.28 -0.02 0.15 -1.91 -1.56 BF288130 ---1.34 0.18 0.78 0.57 0.04 0.10 4.37 2.61 BI275261 ---1.03 0.21 1.56 0.76 0.04 0.07 6.03 2.11 AI576758 --0.27 0.17 -0.32 0.02 0.03 0.05 -1.51 -1.18 AA800908 ---0.49 0.33 0.81 0.36 -0.01 0.24 2.47 1.40 AW921478 Similar to MS4A6D protein (LOC361735), mRNA -0.42 0.17 0.96 0.29 0.02 0.15 2.59 1.35 BE128699 Similar to Collagen alpha 1(VIII) chain precursor (LOC304021), mRNA -0.63 0.17 0.07 0.07 0.04 0.10 1.62 1.59 NM_053843 Fc receptor, IgG, low affinity III -2.20 0.20 0.74 0.39 -0.23 0.43 7.70 3.92 NM_031512 interleukin 1 beta -0.93 0.18 1.63 0.84 -0.07 0.12 5.87 1.81 NM_031055 matrix metalloproteinase 9 (gelatinase B, 92-kDa type IV collagenase) -1.47 0.18 0.78 0.42 -0.16 0.40 4.77 2.49 NM_013085 plasminogen activator, urokinase -0.49 0.09 0.13 0.15 0.08 0.07 1.53 1.48 BI295970 tropomyosin isoform 6 -0.31 0.12 0.37 0.16 -0.08 0.17 1.61 1.18 J02811 adenosine monophosphate deaminase 1 (isoform M) 1.02 0.51 -1.30 0.35 -0.02 0.30 -4.97 -2.04 BI282332 Similar to Nur77 downstream protein 2 (LOC361824), mRNA 0.55 0.29 -0.53 0.33 -0.01 0.14 -2.12 -1.48 BF413643 ---0.87 0.08 0.14 0.17 0.08 0.21 2.01 1.94 AA892854 ---1.80 0.40 0.17 0.32 0.84 0.32 3.90 6.24 NM_130823 ATPase, H+ transporting, lysosomal (vacuolar proton pump) 16 kDa -0.39 0.06 0.40 0.13 0.03 0.09 1.73 1.33 NM_031986 syntenin -0.76 0.07 0.42 0.30 0.02 0.14 2.26 1.71 NM_053467 integral membrane protein Tmp21-I (p23) -0.32 0.09 0.30 0.17 0.03 0.05 1.54 1.27 BI287960 epididymal secretory protein 1 -0.66 0.10 0.20 0.15 -0.02 0.07 1.82 1.57

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82 BIOGRAPHICAL SKETCH Heejung Yang, the second child of Hosuk Jun and Kooktae Yang, was born in Seoul, Korea, in 1977. Heejung grew up in Seoul , Korea, until she came to Gainesville, Florida, in 2002. Heejung received her bachel or’s degree in biotechnology from Yonsei University, Seoul, in 2000. While attending college, Heejung ga ined laboratory skills in Dr. Ryun Yang’s biotechnology laboratory. After graduation, Heejung gained work experience in the biotechnology field in H yosung Corporation until Heejung came to the United States to continue her graduate study. In 2002, Heejung was accepted to the master’s program in medical sciences at the University of Florida College of Medicine. She joined the Institute for Wound Research at the Department of Obstetrics and Gynecology under Dr. Gregory Schultz. Since August 2004, Heejung has been continuing her Ph D research in the Interdisciplinary Program in Biomedical Sciences (IDP) at the University of Florida College of Medicine.