Research Article

Cancers as Wounds that Do Not Heal: Differences and Similarities between Renal Regeneration/Repair and Renal Cell Carcinoma

Joseph Riss,1 Chand Khanna,2 Seongjoon Koo,8 Gadisetti V.R. Chandramouli,1 Howard H. Yang,3 Ying Hu,3 David E. Kleiner,4 Andreas Rosenwald,5 Carl F. Schaefer,3 Shmuel A. Ben-Sasson,11 Liming Yang,9 John Powell,9 David W. Kane,6 Robert A. Star,10 Olga Aprelikova,1 Kristin Bauer,1 James R. Vasselli,7 Jodi K. Maranchie,7 Kurt W. Kohn,6 Ken H. Buetow,3 W. Marston Linehan,7 John N. Weinstein,6 Maxwell P. Lee,3 Richard D. Klausner,1 and J. Carl Barrett1

1Laboratory of Biosystems and Cancer, 2Comparative Oncology Program, 3Laboratory of Population Genetics, 4Laboratory of Pathology, 5Metabolism Branch, 6Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, 7Urologic Oncology Branch, Center for Cancer Research, 8Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9Bioinformatics and Molecular Analysis Section, Computational Bioscience and Engineering Laboratory, Center for Information Technology, 10Renal Diagnostics and Therapeutics Unit, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland; and 11Hebrew University-Hadassah Medical School, Jerusalem, Israel

Abstract microenvironment. A variety of signals orchestrate the response to Cancers have been described as wounds that do not heal, injury that results in regeneration and repair of a wound. Both suggesting that the two share common features. By comparing tissue regeneration and carcinogenesis involve cell proliferation, microarray data from a model of renal regeneration and survival, and migration that are controlled by growth factors and repair (RRR) with reported gene expression in renal cell cytokines as well as inflammatory and angiogenic signals. Signals carcinoma (RCC), we asked whether those two processes do, in that promote cell proliferation, survival, and invasiveness derive fact, share molecular features and regulatory mechanisms. from multiple cellular and extracellular sources in the microenvi- The majority (77%) of the genes expressed in RRR and RCC ronment of wounds and cancer. Therefore, wounds and cancers were concordantly regulated, whereas only 23% were discor- share a number of phenotypic similarities in cellular behavior, dant (i.e., changed in opposite directions). The orchestrated signaling molecules, and gene expression. Haddow first recognized processes of regeneration, involving cell proliferation and the similarities between wound healing and carcinogenesis, immune response, were reflected in the concordant genes. The whereas Dvorak described cancer as wounds that do not heal discordant gene signature revealed processes (e.g., morpho- (1, 2). Understanding the similarities between wounds and cancers genesis and glycolysis) and pathways (e.g., hypoxia-inducible may yield new insights into the malignant phenotype. Under- factor and insulin-like growth factor-I) that reflect the standing the differences which relate to the ‘‘failure to heal’’ may intrinsic pathologic nature of RCC. This is the first study that provide insights into the loss of control in cancer, thereby compares gene expression patterns in RCC and RRR. It does providing the basis for novel diagnostic and therapeutic targets. so, in particular, with relation to the hypothesis that RCC Microarray technology has allowed the characterization and resembles the wound healing processes seen in RRR. However, comparison of global gene expression signatures of regenerating careful attention to the genes that are regulated in the and malignant tissues. A microarray study comparing skin wounds discordant direction provides new insights into the critical and tumors provided molecular evidence that keratinocytes at differences between renal carcinogenesis and wound healing. wound margins have gene expression profiles similar to these of The observations reported here provide a conceptual frame- squamous cell carcinoma (3). Chang et al. studied changes in the work for further efforts to understand the biology and to global gene expression profiles of fibroblasts exposed to serum in vitro develop more effective diagnostic biomarkers and therapeutic and compared those profiles with the publicly available strategies for renal tumors and renal ischemia. (Cancer Res gene expression data for numerous tumors (4, 5). That analysis 2006; 66(14): 7216-24) suggested a similarity between the gene expression profile of fibroblasts, a cell type associated with the wound healing process, Introduction and that of the cancer. Furthermore, the serum response signature was predictive for survival of breast cancer patients. Our present Tissue regeneration and tumorigenesis are complex, adaptive study extends those observations to renal regeneration and renal processes controlled by cues from the host and from the tissue carcinoma, and also for the first time examines comprehensively the differences between the two gene expression profiles as well as the similarities. Note: Supplementary data for this article are available at the authors’ web site: The kidney is a member of a restricted class of organs capable of http://home.ccr.cancer.gov/who/rissj/cdc/ and http://discover.nci.nih.gov/host/ 2006_cancers_abstract.jsp. regeneration and repair following damage events such as ischemic Current address for J.C. Barrett: Novartis Institutes for BioMedical Research, injury, a major cause of acute renal failure in both native (6) and Cambridge, MA 02139. transplanted organs (7). Clinically and biologically, ischemic acute Requests for reprints: Joseph Riss, Wound Healing and Oncogenesis, Laboratory of Biosystems and Cancer, Center for Cancer Research, National Cancer Institute, NIH, renal failure is a complex but orderly continuum that, for Building 37/Room 5032, 37 Convent MSC 4264, Bethesda, MD 20892. Phone: 301-402- simplification, can be separated into a series of four overlapping 7203; Fax: 301-480-2772; E-mail: [email protected]. I2006 American Association for Cancer Research. phases referred to as ‘‘initiation’’ (renal blood flow and cellular ATP doi:10.1158/0008-5472.CAN-06-0040 decrease), ‘‘extension’’ (a prolonged hypoxia and continued

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Downloaded from cancerres.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancers as Wounds that Do Not Heal production and release of inflammatory chemokines and cytokines processed, and frozen in an identical manner. For histologic studies, the after acute ischemia ceases), ‘‘maintenance,’’ (some cells undergo kidneys were bivalved in the coronal plane and fixed in formalin (10%). apoptosis whereas others proliferate, acquire the ability to migrate, Immunohistochemistry. Fixed and paraffin-embedded tissue speci- and synthesize extracellular matrix proteins, which help reestablish mens were deparaffinized, rehydrated, subjected to antigen unmasking (16), and treated to block nonspecific staining. For the latter procedure, sections and maintain the structural integrity of cells and tubules), and were incubated for 20 minutes at 24jCwith1%HO in methanol, followed ‘‘recovery’’ (cellular function improves slowly, blood flow returns to 2 2 by blocking for 30 minutes with 5% normal horse serum in PBS. Polyclonal normal or near normal, and epithelial cells establish intracellular antibody against Ki67 (NCL-Ki67p; Novocastra Labs, New Castle upon Tyne, and intercellular homeostasis; ref 8). United Kingdom) or mouse glucose transporter (Glut-1; Alpha Diagnostic Renal cell carcinoma (RCC), which accounts for 3% of all adult Int., San Antonio, TX) was added (1:1,000 dilution) for 16 hours at 4jC, male malignancies in the U.S. (9), is a clinicopathologically followed by incubation for 30 minutes at room temperature with heterogeneous disease that includes several histologically distinct biotinylated secondary goat anti-rabbit IgG and incubation for 30 minutes cellular subtypes (10). RCC is thought to originate in proximal renal with avidin-biotin peroxidase conjugate (1:50 dilution; Vectastain Elite tubules most of the time and in distal tubules occasionally (11). Universal Kit; Vector Laboratories, Burlingame, CA). Color was developed Five human genes are associated with predisposition to RCC: von using Vector Laboratories 3,3-diaminobenzidine kit for 10 minutes, followed Hippel-Lindau (VHL), met proto-oncogene (MET), fumarate by counterstaining with Mayer’s hematoxylin. Negative controls were done with nonimmune serum or PBS. Three investigators evaluated the hydratase (FH), Birt-Hogg-Dube (BHD/FLCN), and hyperparathy- HRPT2 immunohistochemistry independently. roidism 2 ( ; ref. 12). RCC could develop following chronic Microarray procedures. Mouse cDNA microarrays (NIH/NCI GEM2) renal regeneration and repair (RRR) in individuals with polycystic containing 9,596 cDNA spots from the Integrated Molecular Analysis of kidney disease or in renal allografts (13, 14). Genomes and their Expression consortium were used to quantitate mRNA Our study tests the hypothesis that there are patterns of gene expression in the kidney samples. A reference sample consisting of an equal expression common to RRR and RCC. We used a mouse model of mixture of six normal mouse tissues (brain, heart, kidney, liver, lung, and ischemia/reperfusion (in which the left renal artery was ligated spleen) was used in the competitive hybridization experiments. For the transiently) to characterize gene expression changes at several time reference sample, 50 Ag of total RNA was reverse transcribed using an points during the first 2 weeks of RRR. Differential gene expression oligo(dT)-primer. For experimental samples, 3.0 Ag of polyadenylated RNA associated with RRR was then compared qualitatively with from whole kidney was reverse-transcribed using an oligo(dT)-primer. The differential gene expression reported in the literature for human labeling and remaining hybridization procedures have been described previously (17). Gene expression data are presented in their entirety in RCC. The results revealed two distinct genomic signatures: (a)a supplemental online material at the authors’ web site. large group of genes (which we will call ‘‘concordant’’) that are Quantitative real-time reverse transcription-PCR. RNA was isolated differentially expressed in the same direction in RRR and RCC, and using Trizol Reagent (Invitrogen, CA). Total RNA (1 Ag) was reverse b ( ) a smaller divergent group (‘‘discordant’’) that are differentially transcribed in a volume of 50 AL. Five microliters of the resulting solution expressed in opposite directions in RRR and RCC. We analyzed was then used for PCR according to the manufacturer’s instructions concordant and discordant differentially expressed genes for (Applied Biosystems, Inc., Foster City, CA). Gene expression for IGFBP1, biological significance by comparing categories and functional IGFBP3, CTGF, AKT, FRAP, MYC, NF-jB, HK1, and SIRT7 were quantified pathways. The concordant gene expression signature qualitatively relative to the expression level of ribosomal 18s. PHD1, PHD2, and PHD3 h reflects the normal regenerative phenotype, and the discordant were quantified relative to the expression level of filamin B ( -actin binding signature provides new insight into critical differences between the protein 278; FLNB). All probes were purchased from Applied Biosystems. Normalized data are presented as fold difference in log gene expression. malignancies and processes of tissue repair. The results could 2 potentially lead to the development of more effective diagnostic Data Analysis and therapeutic strategies for cancer and for wound healing. Statistical analysis of microarray data. The experimental RNA was labeled with Cy3 (green) and the reference pool with Cy5(red). Two Materials and Methods different batches of reference were used for the two experiments. Log ratios used base 2 logarithms. There were 9,984 spots on each array, but 388 had Experimental Procedures Clone id = 0 and were excluded. Spots were filtered out if the log intensity in Animals. Five-week-old C57BL/6 female mice (20 g) were obtained from either channel was below two standard deviations from the mean for that the National Cancer Institute. All animals had free access to water and food. channel on that array. For cluster analysis, genes present (not filtered) in at Animal care and experiments were done according to protocols approved least 60% of the samples were included. Each array was normalized using a by the Animal Care and Use Committee of the National Cancer Institute. nonlinear Lowess smoother to provide intensity level–dependent normal- Ischemia-reperfusion model. Regeneration was induced by a modifi- ization.12 The data were analyzed using principal component analysis. cation of the renal warm ischemia method (15). Mice were anesthetized Analysis and curation of pathways. Publicly available literature from with ketamine, xylazine, and acepromazine and placed on a heating table at 1966 to mid-2003 was surveyed using PubMed. The survey was comple- 37jC to maintain body temperature. A left unilateral flank incision was mented by information from publicly available databases, including OMIM, made to allow exposure of the left kidney and renal artery. A nontraumatic Entrez Gene (LocusLink), KEGG, GeneCard, MYC Cancer Gene,13 p53,14 vascular clamp was placed across the renal artery for 50 minutes. The mice Panomics,15 and Gilmore’s Rel/NF-nB transcription factors.16 The survey were kept anesthetized during that time, with temporary closure of the was conducted with the goal of cataloguing genes reported to be expressed abdomen. After the ischemic interval, the kidney was inspected for differentially. HUGO gene names were used for comparisons across restoration of blood flow, and 1 mL of prewarmed (37jC) normal saline was databases. Only genes that were printed on the GEM2 microarray were instilled into the abdominal cavity. The abdomen was closed with wound clips (Roboz Surgical Instrument Co., Inc, RS-9262), and the animals were allowed to recover in a 37jC incubator. After the desired period of 12 http://linus.nci.nih.gov/BRB-ArrayTools.html. reperfusion (6-12 hours or 1, 2, 5, 7, or 14 days), the animals were 13 anesthetized, and both kidneys were rapidly excised by midline abdominal http://www.myc-cancer-gene.org/. 14 http://linkage.rockefeller.edu/p53/. incision. For microarray studies, the kidneys were flash-frozen in liquid 15 http://www.panomics.com/NFkBhuman.cfm. nitrogen and stored at À70jC. Normal and ischemic kidneys were removed, 16 http://people.bu.edu/gilmore/nf-kb/index.html. www.aacrjournals.org 7217 Cancer Res 2006; 66: (14). July 15, 2006

Downloaded from cancerres.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancer Research considered for further analysis. If conflicting reports on gene expression Table 1. Pathway analysis of genes differentially were present in the literature, the genes were labeled ‘‘conflict.’’ expressed in RRR and RCC MatchMiner17 and SOURCE18 were used to translate among different types of identifiers for comparative analyses. The statistical significance of concordance or discordance in relative enrichment of gene subgroups was RRR + RCC RRR + RCC RRR + RCC determined using a m2 test (Table 1; Supplemental Table S7). A 2 Â 2 all genes concordant discordant contingency table is shown below: VHL VHL VHL Hypoxia Hypoxia Hypoxia Concordant Remainder HIF (HRE) HIF (HRE) IGF IGF Hypoxia pathway 35216 MYC MYC Remainder 243 5302 p53 p53 p53 NF-nB NF-nB

The P value for this 2 Â 2 table was calculated using the statistical package R. NOTE: Genes differentially expressed on both RRR and RCC were P Ontology. GoMiner19 and EASE20 analyses were done on the lists of analyzed for significant enrichment ( < 0.05) in genes belonging to n differntially expressed genes (18). Enrichment of categories was determined VHL, hypoxia, HRE, IGF-I, MYC, p53, and NF- B pathways. The RRR using GoMiner (19), and P value thresholds were determined from EASE genes were not filtered by phases of expression (i.e., continuous, early, scores (18). and late; further details are given in Supplemental Table S7).

Results for proliferation marker MiB-1. When that staining peaked at about To understand RRR and its relationship to the gene expression in 48 hours, most of the tubules and at least 50% of the tubular RCC, we established a murine model of warm unilateral renal epithelial cells were positive for MiB-1 (Fig. 2B). After 2 weeks, ischemia and subsequent RRR (Fig. 1B), then we did an extensive most tubules were histologically normal, and there were only rare five-step analysis (Fig. 1A): (a) histopathologic verification of RRR examples of degenerative or regenerative change (Fig. 2B). Those (Fig. 2A-C); (b) gene expression profiling of the regenerating observations are consistent with previous studies of renal injury, kidneys relative to normal kidneys at different time points after regeneration, and recovery (8). ischemia. The resulting RRR gene expression data set served as the Differential gene expression in RRR. Transcript expression foundation for further analysis and comparison with RCC; (c) wasanalyzedusingacDNAmicroarraywith9,596spots biological interpretation of the RRR differential gene expression by (corresponding to 5,796 murine genes) and RNA samples of normal literature mining, gene ontology (GO) analysis, and pathway (day 0), ischemic (50 minutes), and reperfused mouse kidney analysis; (d) comparative analysis of the differential gene harvested 1, 2, 5and 14 days postinjury. Differentially expressed expression patterns of RRR and RCC relative to normal renal microarray spots (1,675; P < 0.05), representing 1,325 genes, tissue, resulting in the identification of concordant and discordant clustered the kidney samples into three groups. The first included genes; and (e) bioinformatic analysis that included pathway samples of normal and ischemic kidney (‘‘baseline’’ and 50 minutes analysis, GO analysis, and literature mining of the concordant ischemic); the second included the samples from the 1st and 2nd and discordant genes. The results are presented in Figs. 1-3 days postinjury (‘‘early’’); the third included the samples from the and Tables 1-3. Additional data (Supplemental Tables S4-9; 5th and 14th days postinjury (‘‘late’’). The average differential Supplemental Fig. S4) and accompanying text are available in the expression (RRR relative to normal and 50-minute ischemic online supplemental materials. kidneys) was calculated for each gene. By principal component The histopathology of RRR. Ischemic injury was induced in the analysis, individual data points were highly reproducible because left kidneys of female mice by restricting blood flow for 50 minutes repeat measurements (4-16 arrays per time point) clustered in the with a vascular clamp (see Materials and Methods for details). same pattern (Fig. 3A). Following reperfusion, the kidneys were allowed to recover for 0.5, Relative to the normal and 50-minute ischemic kidneys, the 1,325 1, 2, 5, 7, and 14 days before harvesting (Fig. 1B). Apoptotic cells RRR genes fell into three groups in their temporal patterns of were observed in the outer medulla within 12 hours of reperfusion, differential expression. The first included 323 genes differentially and the number of apoptotic cells increased for f24 hours (data expressed continuously during RRR [Fig. 3B, ‘‘continuous’’ or (*)]. not shown). Histologic markers of ischemia were monitored, with Included were 189 up-regulated and 134 down-regulated genes. The the results shown in Fig. 2A-C. More than half of the cortical second group included 629 ‘‘early’’ genes (336 up-regulated and 293 tubules stained for hypoxia-inducible factor 1a (HIF1a)-regulated down-regulated) differentially expressed only during the first 2 days glucose transporter-1 (Glut-1/Slc2A1) after 1 day (Fig. 2C). Acute after injury [Fig. 3B, ‘‘early’’ or (A)]. The third included 373 ‘‘late’’ tubular necrosis with complete loss of epithelium within individual genes (227 up-regulated, 96 down-regulated) differentially expressed tubules was observed within the first 12 to 24 hours. Some tubules 5and 14 days after injury [Fig. 3 B,‘‘late’’ or (B)]. A complete list of the had cells with enlarged, reactive, hyperchromatic nuclei and genes differentially expressed during RRR can be found in prominent nucleoli (Fig. 2A and B). Tubular epithelial cells stained Supplemental Table S4. The data were validated by reverse- transcription quantitative PCR analysis of 10 genes (Supplemental Fig. S4) and by mining the literature for an additional 81 genes out 17 http://discover.nci.nih.gov/matchminer/index.jsp. of 91 that were reported by others (Supplemental Table S4). 18 http://source.stanford.edu. 19 http://discover.nci.nih.gov/gominer. Comparison of genes differentially expressed in RRR and 20 http://apps1.niaid.nih.gov/David. RCC. An extensive literature survey of gene expression data for

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Figure 1. Overview of the protocol and analysis. A, schematic flow of the five-step comparison of global gene expression in RRR and RCC. B, renal ischemia reperfusion protocol: 5-week-old C57BL/6 female mice were subjected to 50 minutes of left unilateral warm ischemia, followed by reperfusion. Before the ischemia (normal kidney) or after the desired period of reperfusion (0, 6, or 12 hours or 1, 2, 5, 7, and 14 days) both kidneys were rapidly excised. Histologic studies were carried out for both kidneys. Microarray analysis was carried out using total RNA from the left kidney sampled before or immediately after ischemia or on days 1, 2, 5, and 14 of RRR. C, Venn diagram: 984 genes on the array were previously reported to be differentially expressed in RCC and normal kidney. Comparison with the current microarray study identified 1,325 genes differentially expressed in RCC and normal kidney. Three hundred and sixty-one genes were differentially expressed in both RRR and RCC. Of those, 278 were concordantly expressed, and 83 were discordantly expressed. D, distribution of the 361 genes differentially expressed in both RRR and RCC.

human RCC identified 2,815genes reported to be differentially Pathway and gene ontology analyses of ‘‘concordant’’ and expressed in RCC relative to normal human kidney.21 For 984 of ‘‘discordant’’ genes. We next tested the association between the those genes, a mouse orthologue was present on the microarray concordantly and discordantly expressed genes and pathways used in this study, and 361 of those genes were differentially presumed to be involved in RRR and/or RCC. Concordant genes expressed in both RRR and RCC (Fig. 1C and D; Supplemental were significantly enriched (P < 0.05) in the VHL, MYC, p53, and Table S4). Of those 361 genes, 278 (77%) were up-regulated in RRR NF-nB pathways and the hypoxia-regulated category (Table 1).22 and RCC or down-regulated in both RRR and RCC. Those genes are Discordant genes were significantly enriched in the VHL, hypoxia, referred to here as ‘‘concordant’’ genes. The remaining 83 genes HIF (HRE), insulin-like growth factor (IGF-I), and p53 pathways. (23%) were differentially expressed in opposite directions in RRR The NF-nB pathway was significantly enriched with concordant, and RCC. Those are referred to here as ‘‘discordant’’ (Fig. 1C and D; but not discordant genes. The HIF and IGF-I pathways were Table 1). The probability of observing those percentages by chance significantly enriched with discordant, but not concordant, genes. would be extremely low under the null hypothesis that the RRR and The discordant genes in the IGF-I pathway included CTCG, À RCC phenotypes are unrelated (P value, 2.2 Â 10 16 by Fisher’s CYR61, IGFBP1, IGFBP3, TASCTD2, VEGFA, and COX6C. The exact test; Fig. 1C and D; Table 1). Of the concordant genes, 209 discordant genes in the HIF pathway included HK1, IGFBP1, were up-regulated. Included were VCAM1, ICAM1, and MYC. The IGFBP3, MMP2, PGK1, EGLN1, and VEGFA (Table 1; Supplemental remaining 69 concordant genes were down-regulated (P < 0.001; Table S5b). Fig. 1C and D; Supplemental Table S4). Thirty discordant genes Gene ontology23 categories significantly enriched in concordant were up-regulated in RRR and down-regulated in RCC (e.g., genes are listed in Table 2 and are listed in detail in Supplemental CTGF, THBS1, and SMC1L1;Fig.1C and D; Table 3; Supplemental Tables S5b and S6. Among the gene categories for concordant Table S4). Fifty-three discordant genes were down-regulated in RRR genes, which were mostly up-regulated, are such biological and up-regulated in RCC (e.g., IGFBP1, IGFBP3, PHD2/EGLN1, and processes and functions as immune response, proliferation, cell HK1;Fig.1C and D; Table 3; Supplemental Table S4).

22 http://discover.nci.nih.gov/mim/view.jsp?selection=intro&MIM=hypoxia. 21 J. Riss et al., in preparation. 23 http://www.geneontology.org. www.aacrjournals.org 7219 Cancer Res 2006; 66: (14). July 15, 2006

Downloaded from cancerres.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancer Research growth, translation (ribosome biogenesis), metabolism, and Discussion extracellular matrix structural constituent (Table 2; Supplemental Earlier studies suggested that the complexities of the signaling P Tables S5b and S6). When the same GO analysis method (i.e., < and regulatory pathways involved in cancer present a significant 0.05) was used for the discordant genes, a different set of GO barrier to understanding, preventing, and/or treating cancer (20). categories was found, and among those were IGF binding, heparin However, cancers share many features in common with tissue binding, extracellular space, angiogenesis, regulation of cell growth, regeneration, including immune response, cell proliferation, cell and morphogenesis of renal tissue (Table 2; Supplemental Tables migration, tissue remodeling, and cell death. Our results support S5b and S6). Only a small number of GO categories were enriched the proposed hypothesis that cancer is an aberrancy of the for both concordant and discordant genes (Table 2; Supplemental physiologic processes of wound healing, and reveal for the first Tables S5b and S6). time, two distinct qualitative gene expression signatures, a Based on our earlier pathway analysis of the concordant and concordant signature and a discordant signature that distinguishes discordant genes (Table 1; Supplemental Table S4), we next RCC from RRR. Of the 361 genes that we found to be differentially analyzed the genes in the significant pathways (e.g., the hypoxia expressedinbothRRRandRCC,themajority(77%)were pathway) for enrichment of GO categories (Supplemental Table S9). concordant, and the remaining 23% were discordant. Given those Interestingly, the concordant genes in the hypoxia pathway were numbers, we can confidently reject the null hypothesis that there is enriched for the category of enzyme inhibitor activity, whereas no relationship in differential expression between RRR and RCC À discordant genes in the hypoxia, HIF, and IGF-I pathways were (P,2.2Â 10 16 by Fisher’s exact test). The biological functions of enriched for gene functions related to cell growth. the concordant genes seem to reflect cancer as wounds (e.g., cell Based on the common biological characteristics of cancer, and proliferation and immune response). On the other hand, the extensive analysis of the literature, we also categorized the discordant discordant signature seems to reflect the critical differences genes on a nonprobabilistic, gene-by-gene basis (Table 3; Supple- between malignancies and the processes of tissue repair (e.g., mental Table S8). regulation of cell growth, morphogenesis, and angiogenesis). Those

Figure 2. Histologic analysis of RRR. A, histologic analysis: (i) essentially normal murine renal cortex taken at time 0 (H&E, original magnification, Â400); (ii) acute tubular necrosis 2 days after the ischemic event. About half of the tubules show complete necrosis with loss of epithelium, and the remaining tubules show cells with reactive nuclear changes (hyperchromasia, prominent nucleoli; H&E, original magnification, Â600); (iii) representative renal cortex 14 days after the ischemic event. Most of the tubules seem normal, with few tubules showing degenerative or regenerative changes (original magnification, Â600). B, immunoreactivity for MiB-1 in renal cortex: (i) normal renal cortex at time 0. Only rare tubular cells are positive for MiB-1; (ii) 12 hours after the ischemic event. The number of positive cells is similar to that of normal cortex; (iii) 2 days after the ischemic event. Many tubular epithelial cells now stain positively for MiB-1; (iv) 7 days after the ischemic event. Although scattered tubules still show multiple nuclei positive for MiB-1, most tubules are now negative or show rare individual cells with positive staining (original magnification, Â600). C, immunoreactivity for Glut-1 in renal cortex: (i) normal renal cortex taken at time 0. Positive staining is seen mainly in the distal collecting tubules; (ii) 12 hours after the ischemic event. In addition to distal collecting tubules, some proximal tubules are also staining; (iii) 24 hours after ischemic event. More than half of the cortical tubules now show some degree of staining for Glut-1; (iv) 48 hours after the ischemic event. Most tubules are now negative, and the staining pattern is similar to that seen at time 0 (original magnification, Â400).

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Table 2. Gene ontology analysis of concordant and discordant genes in RRR and RCC

GO system GO term No. of genes GO term average Category up-regulated/down-regulated fold change enrichment

Concordant expression Molecular function Immunoglobulin binding 3/0 1.103 9.7 Structural constituent of ribosome 24/0 0.741 4.7 RNA binding 27/1 0.563 2.7 Extracellular matrix structural constituent 6/0 0.884 3.1 Cellular component Cytosolic ribosome 11/0 0.730 8.1 Proteasome core complex 4/0 0.563 5.6 Collagen 5/0 0.886 4.9 Extracellular matrix 13/1 0.799 1.9 Biological process DNA replication initiation 5/0 0.609 8.6 Regulation of translation 4/2 0.137 4.8 Ribosome biogenesis 10/0 0.752 4.8 Posttranslational membrane targeting 5/2 0.491 3.5 Cytoplasm organization and biogenesis* 20/2 0.747 1.8 Macromolecule biosynthesis 29/3 0.560 1.7 Cell adhesion 19/2 0.672 1.7 Immune response 21/0 0.912 1.7 Cell growth and/or maintenance* 78/25 0.325 1.3 Protein metabolism 60/10 0.466 1.3 Protein-ER targeting 6/2 0.481 3.5 Cell proliferation 33/1 0.517 1.4

Discordant expression Molecular function IGF binding 2/2 0.088 21.5 Organic cation transporter activity 1/2 À0.268 14.9 Heparin binding 4/2 0.253 10.2 Catalytic activity 9/30 À0.333 1.3 Cellular component Extracellular space 12/12 0.085 1.5 Biological process One–carbon compound metabolism 0/3 À0.517 11 Angiogenesis 3/2 0.392 8.7 Regulation of cell growth 2/2 0.088 8.3 Cytoskeleton organization and biogenesis 5/3 0.194 3.2 Cytoplasm organization and biogenesis* 5/4 0.105 2.4 Morphogenesis 8/6 0.286 1.7 Cell growth and/or maintenance* 13/20 À0.127 1.3

NOTE: GO categories enriched in concordant or discordant genes in RRR and RCC are shown. *, Categories enriched for both concordant and

discordant genes. The average log2 change in gene expression for genes associated with each category is shown. Red and green shading indicate up- and down-regulated genes, respectively (the expression direction and values are as in RRR, relative to the normal kidney; further details are given in Supplemental Table S6). gene expression patterns may yield new insight into pathways, epithelial barrier as regeneration of cells relines the denuded functions, and cellular locations of proteins that play multifaceted tubules (23). Our results for the RRR model are in accord with the roles in wound healing and/or carcinogenesis. expected RRR processes and further suggest three distinct temporal patterns of differential gene expression: continuous (days 1, 2, 5, The RRR Model and 14), early (days 1 and 2), and late (days 5and 14; Fig. 3 A and B). Clinical RRR is relatively common, but there is no ethical Our GO analysis of the differential gene expression suggests that possibility of obtaining biopsy specimens at different times during metabolic and catabolic processes, as well as response to injury, are the process. In recent years, mouse (and other) model systems have involved throughout renal recovery, whereas the first 2 days shed new light on the nature and treatment of human RRR. following ischemia are enriched with regeneration processes, and Physiologic, pharmacologic, global gene expression, and gene the late RRR stage is characterized by immune response inactivation studies have been included (21, 22). Therefore, we (Supplemental Tables S5a-b). chose a mouse model (unilateral renal ischemia) to assess changes in gene expression during RRR. The predominant consequences of Comparison of RRR and RCC renal injury in the model include proximal tubule necrosis, as well To compare RRR and RCC, we analyzed differential gene as apoptotic death of a minority of the cells. The reversal of those expression in RRR and compared it with RCC differential gene changes coincides with the reestablishment of the normal renal expression. That analysis required integration of data from different www.aacrjournals.org 7221 Cancer Res 2006; 66: (14). July 15, 2006

Downloaded from cancerres.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancer Research organisms, tissue pathologies, methods, and authors (24). Despite Concordant Genes: Normal RRR Processes Are Found the heterogeneity of cell populations, transcriptional profiling of in RCC bulk tumors and wounds has yielded significant insights, such as Concordant genes comprised the majority (77%) of the 361 genes those in this study (25, 26). we identified as differentially changed in both RRR and RCC. Those The comparison of mouse RRR with human RCC was genes and their pathways reflect the common mechanisms of cell accomplished by using the corresponding normal tissue in each proliferation, growth, metabolism, and defense that are pertinent to original study as a reference point, and thus, the comparison was both RRR and RCC. For example, our GO analysis of the differential indirect (i.e., not RRR versus RCC). To reduce the noise in the study, concordant gene expression suggests, in agreement with the the differential expression was catalogued and compared only literature, a significant enrichment of categories as DNA replication qualitatively (not quantitatively), as expressed up or down from [the highly conserved minichromosome maintenance genes MCM2, normal tissue (Supplemental Table S4). The feasibility of that MCM3, MCM4, and MCM7 and the human mismatch repair gene comparison was supported by the fact that both RCC and RRR are mutS homologue 2 (MSH2), cell adhesion (e.g., ICAM1 and VCAM1), predominantly proximal tubular processes, and proximal tubules and through 21 up-regulated concordant immune response genes make up the bulk of the kidney (11, 27). Moreover, comparative (Supplemental Table S4; ref. 28–30)]. analysis of the literature is supported by a comparison of the RRR literature with our experimental RRR data set. Of the 91 genes Discordant Genes and Biological Processes that appearing in both lists, 89% were differentially expressed in full Differentiate RRR from RCC agreement (up or down), despite the difference in organism Nearly a fourth (23%) of the genes differentially expressed in RRR (human versus mouse) and methods (Supplemental Table S4). and RCC were discordant, i.e., differentially expressed in opposite Further methodologic considerations are addressed in the directions. Although differences in some of those genes may be due supplemental material. to extraneous factors (including different methodologies, species

Table 3. Classification of discordant genes by functional category based on extensive analysis of the RRR and RCC literatures

Category Regeneration RCC Gene symbol

Morphogenesis Up Down CRYM, CTGF, GPC3, CYR61, MYL6, TCF21, THBS1 Down Up FHL1, KDR, PKD1, RTN3, VEGF, GADD45G Extracellular space Up Down APOE, IF, DCN, CTGF, GC, GPC3, CYR61, MMP2, PLAT, SDC1, THBS1, TACSTD2 Down Up BCKDHA, CD59, COX6C, IGFBP1, IGFBP3, KDR, Klk1, LPL, MEP1A, ENPP2, RTN3, VEGF Metabolism Up Down APOE, CTGF/IGFBP8 Down Up BCKDHA, AMACR, ENPP2, MTHFD1, MAT2A, SHMT2, SPTLC1, LPL, SHMT1, PTPRB, SOD2, CPT1A, ACOX1, EGLN1 Glycolysis Up Down Down Up PGK1, HK1 Signal transduction Up Down SAR1, RALBP1, NR2F6, SMC1L1, TACSTD2 Down Up IGFBP1, IGFBP3, ARHE, PCTK3, VEGF, CD59, FRAP1 Angiogenesis Up Down CTGF, CYR61, THBS1 Down Up VEGF, KDR Transcription Up Down TCF21, ZNF144, NR2F6 Down Up GRSF1, NCOA4, PAPOLA, UBE2V1, EIF4A2, MKNK2, SOD2 Transport Up Down GC, SLC1A1, APOE, SAR1, RALBP1 Down Up SCP2, SLC16A7, GJB2, ATP1B1, COX6C, SLC22A1, CPT1A, ACOX1, ARHE Proteolysis Up Down IF, PLAT Down Up Klk1, MEP1A Immune Up Down Down Up CEACAM1, CD59 DNA Up Down SMC1L1, CTGF/IGFBP8 Down Up TOP3B, RRM1, GADD45G, FRAP1 Cell adhesion Up Down THBS1, CTGF/IGFBP8, CYR61/IGFBP10 Down Up PKD1 Cell differentiation Up Down Down Up FHL1, GADD45G De/phosphorylation Up Down PTPRO, PPP2CB; Down Up PTPRB, PCTK3, MKNK2, KDR Ubiquitination Up Down ZNF144 Down Up UBE2V1, EGLN1 Others Up Down TJP2, MT2A, TM4SF3, SDC1, CORO1B, WSB1, MYL6, AKAP2, CRYM, DCN Down Up HARS, C16orf5, RTN3, KIAA1049, HSPH1, KIF21A, ADD3, HSPD1, CAPNS1

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processes involving morphogenesis and glycolysis and the HIF- VHL and the IGF-I pathways. The discordant genes include genes that may play a critical role in those processes and pathways (12, 37, 41, 42). The HIF-VHL pathway. Seventeen HIF-responsive or HIF- associated genes are differentially expressed during RRR (P < 0.05), and seven of those are differentially expressed in the opposite direction during RCC (P < 0.05). Six of the seven discordant HIF-responsive genes have been reported to be hypoxia-induced and are up-regulated in RCC. Their down- regulation in RRR must signify other control mechanisms in normal regeneration that are not operative in RCC. Among the biological functions of those genes are glycolysis (HK1 and PGK1) and the IGF-I pathway (IGFBP1 and IGFBP3; Tables 1 and 2; Supplemental Table S4). Regulation of the HIF1a transcription factor in RCC is complex. For example, FK506 binding protein 12-rapamycin associated protein 1 (FRAP1/MTOR) is down-regulated continuously during RRR but is up-regulated in RCC (Supplemental Table S4; ref. 43), suggesting that mTOR signaling increases the translation of HIF1a in RCC but not in RRR (44). Interestingly, prolyl hydroxylases PHD2/EGLN1 and PHD3/ Figure 3. Temporal patterns of gene expression during RRR. A, principal EGLN3 are up-regulated during RCC (30, 38) and down-regulated component analysis of gene expression data during RRR. The first two principal during RRR, together with PHD1/EGLN2 (Supplemental Table S4; components, PC-1 and PC-2, explain 22.2% and 12.1% of the total variance, PHD1, respectively. B, the RRR gene expression distribution: 23% of the genes were Supplemental Fig. S4). In RRR, the down-regulation of differentially expressed. The differential gene expression is presented here as up PHD2, and PHD3 is likely to prolong the half-life of HIF1a or down in regenerating, as opposed to normal or ischemic kidney. protein in the early hours following ischemia (45). In RCC, the induction of PHD2 and PHD3 is a consequence of a dysfunctional PHD2 PHD3 differences, or chance), the functions of the genes support the negative feedback loop. The and genes are induced a conclusion that many of them do differentiate the RRR and RCC by HIF1 which is continuously up-regulated in RCC. Solid VHL processes from each other. Our GO analysis indicated that 95% tumors are often hypoxic and mutated in the gene. a of the GO categories for the discordant genes are distinctly Therefore, the proline-hydroxylated HIF1 cannot be mediated different from those predicted for the concordant genes (Table 2; for oxygen-dependent ubiquitination. Thus, in RCC, the up- Supplemental Table S5b; Fig. 1A-D). Including categories such as regulation of PHD2 and PHD3 cannot affect the already IGF binding, organic cation transporter activity, heparin binding, dysfunctional VHL-HIF pathway (46–48). Further examples of angiogenesis, regulation of cell growth, organogenesis, and discordant genes involved in the HIF-VHL pathway are given in morphogenesis. Interestingly, alterations in morphogenesis have the supplemental material. been cited as a clear characteristic of cancer (Supplemental Our GO analysis of the discordant genes in the HIF-VHL pathway Table S5b; ref. 31). indicated that they are significantly enriched with biological Another characteristic of RCC are the alterations in glycolysis. process of glycolysis, regulation of cell growth, and IGF binding. Fast-growing tumors consume large amounts of energy in the form Those biological processes are in agreement with the RCC of ATP. In hypoxic tumors, ATP is partially generated by anaerobic literature (Supplemental Table S9; ref. 37, 38). glycolysis, even though that pathway is far less efficient than The IGF-I pathway. Several IGF-I pathway genes were IGFBP1, aerobic glycolysis (32). The glycolytic genes differentially expressed differentially expressed during RRR (e.g., CTGF/IGFBP8, IGFBP3 IGFBP4 in both RRR and RCC are interesting. For example, hexokinase 1 , and ; Table 2; Supplemental Table S5b). In contrast IGFBP1 IGFBP3 (HK1), which carries out the essential first step in the glycolytic to RRR, and are up-regulated during RCC. The pathway, is down-regulated early in RRR and is up-regulated in bioavailability of the IGFs is influenced by the concentrations of RCC (Table 3; Supplemental Table S4). In the kidney, HK1 is specific IGFBPs. In a different physiologic context, IGFBPs could expressed in the proximal renal tubule and is regulated by HIF and either increase or decrease IGF signaling. This complexity is poorly possibly by p53 (33–37). Phosphoglycerate kinase 1 (PGK1)is understood; it could well be that IGFBP3 up-regulation in RCC down-regulated early in RRR and is up-regulated in RCC. PGK1, prolongs the half-lives of the IGFs. Alternatively, IGFBPs may which is expressed in the collecting duct, is regulated by HIF and compete with receptors for free IGFs and IGF-II and thus disrupt possibly by NF-nB and MYC (35, 37, 38). Solute carrier family 16- these pathways (49); or IGFBPs may serve some unknown func- IGFBP8/CTGF member 7 (SLC16A7/MCT2) is up-regulated in RCC and down- tions in RCC (for —see supplemental material). The regulated in RRR. Those observations are consistent with increased discordant genes regulated by the IGF-I pathway were enriched glycolysis in cancer cells that rely to a greater extent on glycolytic with GO categories such as regulation of cell growth, angiogenesis, pathways than do normal cells (39, 40). morphogenesis/organogenesis, heparin binding, and IGF binding (Supplemental Table S9). Discordant Gene Pathways Prospective and future directions. We have identified three Previous studies have implicated altered processes and path- temporally different patterns of differential gene expression in RRR: ways as associated with RCC pathogenesis. Included are early, late, and continuous. RRR can be viewed as a complex, www.aacrjournals.org 7223 Cancer Res 2006; 66: (14). July 15, 2006

Downloaded from cancerres.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancer Research ordered process involving tissue regeneration and repair. Compar- peutic strategies for renal tumors, as well as strategies for ison of the RRR gene expression profile with that of RCC reported improving recovery from renal ischemia without promoting RCC. in the literature reveals two expression signatures that strongly support the proposed hypothesis that cancers bear similarity to wounds: a predominant concordant signature and a lesser Acknowledgments discordant one. The biological functions of the concordant genes Received 1/6/2006; revised 3/29/2006; accepted 5/9/2006. indeed support the view of ‘‘cancer as a wound’’ and include genes Funding: This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. and pathways that are tuned to maintain the regenerative and The costs of publication of this article were defrayed in part by the payment of page repair processes. The discordant signature, however, points to charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. processes, pathways (e.g., HIF and IGF-I), and genes that Microarray analyses were done using BRB ArrayTools developed by Dr. R. Simon differentiate cancer from wounds. Those observations provide a and A. Peng Lam. We gratefully acknowledge Drs. H.F. Dvorak for his comments, L.M. conceptual framework for further efforts to understand the biology Staudt for advice in microarray technology, A.M. Michalowska and R. Simon for help in biostatistics, B.R. Zeeberg for advice in bioinformatics, H. Cao for web site of RCC and RRR. They also provide information for the development, A.R. Kane for graphics support, and L.K. Fleming, S.F. Goldberg, and development of more effective diagnostic biomarkers and thera- M. Sander for editing this manuscript.

References apy for diffuse large-B-cell lymphoma. N Engl J Med analysis by cDNA array hybridization. Kidney Int 2000; 2002;346:1937–47. 57:1452–9. 1. Dvorak HF. Tumors: wounds that do not heal. 18. Hosack DA, Dennis G, Jr., Sherman BT, Lane HC, 36. Hoh J, Jin S, Parrado T, Edington J, Levine AJ, Ott J. Similarities between tumor stroma generation and Lempicki RA. Identifying biological themes within lists The p53MH algorithm and its application in detecting wound healing. N Engl J Med 1986;315:1650–9. of genes with EASE. Genome Biol 2003;4:R70. p53-responsive genes. Proc Natl Acad Sci U S A 2002;99: 2. Haddow A. Molecular repair, wound healing, and 19. Zeeberg BR, Feng W, Wang G, et al. GoMiner: a 8467–72. carcinogenesis: tumor production a possible overheal- resource for biological interpretation of genomic and 37. Semenza GL. Targeting HIF-1 for cancer therapy. Nat ing? Adv Cancer Res 1972;16:181–234. proteomic data. Genome Biol 2003;4:R28. Rev Cancer 2003;3:721–32. 3. Pedersen TX, Leethanakul C, Patel V, et al. Laser 20. Klausner RD. The fabric of cancer cell biology— 38. Boer JM, Huber WK, Sultmann H, et al. Identification capture microdissection-based in vivo genomic profiling weaving together the strands. Cancer Cell 2002;1:3–10. and classification of differentially expressed genes in of wound keratinocytes identifies similarities and 21. Bouchard M. Transcriptional control of kidney renal cell carcinoma by expression profiling on a global differences to squamous cell carcinoma. Oncogene development. Differentiation 2004;72:295–306. human 31,500-element cDNA array. Genome Res 2001; 2003;22:3964–76. 22. Heyman SN, Lieberthal W, Rogiers P, Bonventre JV. 11:1861–70. 4. Chang HY, Sneddon JB, Alizadeh AA, et al. Gene Animal models of acute tubular necrosis. Curr Opin Crit 39. Lin RY, Vera JC, Chaganti RS, Golde DW. Human expression signature of fibroblast serum response Care 2002;8:526–34. monocarboxylate transporter 2 (MCT2) is a high affinity predicts human cancer progression: similarities between 23. Price PM, Megyesi J, Safirstein RL. Cell cycle pyruvate transporter. J Biol Chem 1998;273:28959–65. tumors and wounds. PLoS Biol 2004;2:E7. regulation: repair and regeneration in acute renal 40. Halestrap AP, Price NT. The proton-linked mono- 5. Chang HY, Nuyten DS, Sneddon JB, et al. Robustness, failure. Semin Nephrol 2003;23:449–59. carboxylate transporter (MCT) family: structure, func- scalability, and integration of a wound-response gene 24. Hanash S. Integrated global profiling of cancer. Nat tion and regulation. Biochem J 1999;343:281–99. expression signature in predicting breast cancer surviv- Rev Cancer 2004;4:638–44. 41. Takahashi M, Papavero V, Yuhas J, et al. Altered al. Proc Natl Acad Sci U S A 2005;102:3738–43. 25. Nambiar PR, Boutin SR, Raja R, Rosenberg DW. expression of members of the IGF-axis in clear cell renal 6. Rabb H, Martin JG. An emerging paradigm shift on the Global gene expression profiling: a complement to cell carcinoma. Int J Oncol 2005;26:923–31. role of leukocyte adhesion molecules. J Clin Invest 1997; conventional histopathologic analysis of neoplasia. Vet 42. Unwin RD, Craven RA, Harnden P, et al. Proteomic 100:2937–8. Pathol 2005;42:735–52. changes in renal cancer and co-ordinate demonstration 7. Shoskes DA, Halloran PF. Delayed graft function in 26. EbertBL,GolubTR.Genomicapproachesto of both the glycolytic and mitochondrial aspects of the renal transplantation: etiology, management and long- hematologic malignancies. Blood 2004;104:923–32. Warburg effect. Proteomics 2003;3:1620–32. term significance. J Urol 1996;155:1831–40. 27. Linehan WM, Zbar B. Focus on kidney cancer. 43. Wilhelm M, Veltman JA, Olshen AB, et al. Array-based 8. Sutton TA, Fisher CJ, Molitoris BA. Microvascular Cancer Cell 2004;6:223–8. comparative genomic hybridization for the differential endothelial injury and dysfunction during ischemic 28. Bissell MJ, Radisky D. Putting tumours in context. diagnosis of renal cell cancer. Cancer Res 2002;62: acute renal failure. Kidney Int 2002;62:1539–49. Nat Rev Cancer 2001;1:46–54. 957–60. 9. Jemal A, Tiwari RC, Murray T, et al. Cancer statistics, 29. Vasselli JR, Shih JH, Iyengar SR, et al. Predicting 44. Zhong H, Chiles K, Feldser D, et al. Modulation of 2004. CA Cancer J Clin 2004;54:8–29. survival in patients with metastatic kidney cancer by hypoxia-inducible factor 1a expression by the epidermal 10. Linehan WM, Vasselli J, Srinivasan R, et al. Genetic gene-expression profiling in the primary tumor. Proc growth factor/phosphatidylinositol 3-kinase/PTEN/ basis of cancer of the kidney: disease-specific Natl Acad Sci U S A 2003;100:6958–63. AKT/FRAP pathway in human prostate cancer cells: approaches to therapy. Clin Cancer Res 2004;10:6282–9S. 30. Jiang Y, Zhang W, Kondo K, et al. Gene expression implications for tumor angiogenesis and therapeutics. 11. Motzer RJ, Bander NH, Nanus DM. Renal-cell profiling in a renal cell carcinoma cell line: dissecting Cancer Res 2000;60:1541–5. carcinoma. N Engl J Med 1996;335:865–75. VHL and hypoxia-dependent pathways. Mol Cancer Res 45. Eickelberg O, Seebach F, Riordan M, et al. Functional 12. Pavlovich CP, Schmidt LS. Searching for the hered- 2003;1:453–62. activation of heat shock factor and hypoxia-inducible itary causes of renal-cell carcinoma. Nat Rev Cancer 31. Pienta KJ, Coffey DS. Correlation of nuclear mor- factor in the kidney. J Am Soc Nephrol 2002;13:2094–101. 2004;4:381–93. phometry with progression of breast cancer. Cancer 46. Metzen E, Berchner-Pfannschmidt U, Stengel P, et al. 13. Brennan JF, Stilmant MM, Babayan RK, Siroky MB. 1991;68:2012–6. Intracellular localisation of human HIF-1a hydroxylases: Acquired renal cystic disease: implications for the 32. Frydman B, Bhattacharya S, Sarkar A, et al. implications for oxygen sensing. J Cell Sci 2003;116: urologist. Br J Urol 1991;67:342–8. Macrocyclic polyamines deplete cellular ATP levels 1319–26. 14. Gomez Garcia I, Burgos Revilla FJ, Sanz Mayayo E, and inhibit cell growth in human prostate cancer cells. 47. del Peso L, Castellanos MC, Temes E, et al. The von et al. [Metastasis in renal graft of primary renal adeno- J Med Chem 2004;47:1051–9. Hippel Lindau/hypoxia-inducible factor (HIF) pathway carcinoma]. Actas Urol Esp 2004;28:458–61. 33. Supavekin S, Zhang W, Kucherlapati R, Kaskel FJ, regulates the transcription of the HIF-proline hydroxy- 15. Chiao H, Kohda Y, McLeroy P, Craig L, Housini I, Moore LC, Devarajan P. Differential gene expression lase genes in response to low oxygen. J Biol Chem 2003; Star RA. a-Melanocyte-stimulating hormone protects following early renal ischemia/reperfusion. Kidney Int 278:48690–5. against renal injury after ischemia in mice and rats. 2003;63:1714–24. 48. Marxsen JH, Stengel P, Doege K, et al. Hypoxia- J Clin Invest 1997;99:1165–72. 34. Takenaka M, Imai E, Kaneko T, et al. Isolation of inducible factor-1 (HIF-1) promotes its degradation by 16. Morgan JM, Navabi H, Schmid KW, Jasani B. Possible genes identified in mouse renal proximal tubule by induction of HIF-a-prolyl-4-hydroxylases. Biochem J role of tissue-bound calcium ions in citrate-mediated high- comparing different gene expression profiles. Kidney Int 2004;381:761–7. temperature antigen retrieval. J Pathol 1994;174:301–7. 1998;53:562–72. 49. Pollak MN, Schernhammer ES, Hankinson SE. 17. Rosenwald A, Wright G, Chan WC, et al. The use of 35. Yano N, Endoh M, Fadden K, et al. Comprehensive Insulin-like growth factors and neoplasia. Nat Rev molecular profiling to predict survival after chemother- gene expression profile of the adult human renal cortex: Cancer 2004;4:505–18.

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