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Genome-Wide Profiling of TRACK Kidneys Shows Similarity to the Human Ccrcc Transcriptome

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Genome-Wide Profiling of TRACK Kidneys Shows Similarity to the Human Ccrcc Transcriptome Published OnlineFirst February 25, 2015; DOI: 10.1158/1541-7786.MCR-14-0423 Genomics Molecular Cancer Research Genome-Wide Profiling of TRACK Kidneys Shows Similarity to the Human ccRCC Transcriptome Leiping Fu1,2, Denise R. Minton1,2, Tuo Zhang3, David M. Nanus2,4, and Lorraine J. Gudas1,2 Abstract Renal cell carcinoma (RCC) is the most common cancer arising including increased expression of genes involved in glycolysis and from the kidney in adults, with clear cell RCC (ccRCC) representing the tricarboxylic acid cycle. Some of the transcripts overexpressed in the majority of all RCCs. Expression of a human HIF1a triple- both the TRACK mouse model and human ccRCC include mutant (P402A, P564A, and N803A) construct in the proximal ANKRD37, CA9, EGLN3, HK2, NDUFA4L2, and SLC16A3. These tubule cells of C57BL/6 mice [TRAnsgenic model of Cancer of the data suggest that constitutive activation of HIF1a in kidney prox- Kidney (TRACK); ref. 1] mimics the histologic changes found in imal tubule cells transcriptionally reprograms the regulation of early stage human ccRCC. To better understand the genomic metabolic pathways in the kidney and that HIF1a is a major landscape, a high-throughput sequence analysis was performed contributor to the altered metabolism observed in human ccRCC. with cDNA libraries (RNAseq) derived from TRACK transgenic þ fi positive (TG ) kidney cortex along with human ccRCC transcripts Implications: TRACK (GGT-HIF1aM3) kidney mRNA pro les from the Oncomine and The Cancer Genome Atlas databases. show similarities to human ccRCC transcriptome and pheno- þ Importantly, the expression profiles of TRACK TG kidneys show types associated with the Warburg effect. Mol Cancer Res; 13(5); significant similarities with those observed in human ccRCC, 870–8. Ó2015 AACR. Introduction Loss of expression or mutation of the von Hippel–Lindau (VHL) tumor suppressor gene is found in hereditary and most Renal cell carcinoma (RCC) is the most common primary sporadic ccRCCs (2, 8). This suggests an etiological role for VHL cancer arising from the kidney in adults, with clear cell RCC gene loss in renal carcinogenesis. However, the exact pathway by (ccRCC) representing approximately 75% of all RCCs (2, 3). which loss of VHL leads to ccRCC has not been definitively Histologically, ccRCC cells are characterized by a transparent elucidated. The best studied and likely most important effect of cytoplasm caused by deposition of glycogen, phospholipids, and VHL loss is the resulting increase in expression of the alpha neutral lipids, including cholesterol esters (4, 5). This phenotype subunits of hypoxia-inducible factors 1 (HIF1a) and 2 (HIF2a; suggests that there are metabolic changes in ccRCC cells, resulting refs. 9–11). Increased expression of these two transcription factors in abnormal deposition of glycogen and lipids. Seven genes has been proposed as a key step in ccRCC carcinogenesis (refs. 9, commonly mutated in human kidney cancer, including VHL 10; for review, see ref. 12). We previously generated the murine (NCBI Gene ID: 7428), MET (4233), FLCN (201163), TSC1 TRAnsgenic model of Cancer of the Kidney (TRACK) that (7248), TSC2 (7249), FH (2271), and SDH (6390, 6391, and expresses a triple-mutant (P402A, P564A, and N803A) human 6392), have been identified to date (6). Interestingly, all seven HIF1a construct in murine proximal tubule cells (PTCs) and genes are involved in the regulation of metabolic pathways (6). showed that this model mimics the histologic alterations found These data support the theory that kidney cancer is a metabolic in early stage human ccRCC (1). The cellular histologies displayed disease (6, 7). in TRACK mice are also similar to those observed in the kidneys of individuals with VHL disease, including areas of distorted tubular structure, cells with clear cytoplasm and increased glycogen and 1Department of Pharmacology,Weill Cornell Medical College (WCMC) lipid deposition, multiple renal cysts, and areas of multifocal of Cornell University, New York, New York. 2Weill Cornell Meyer Cancer ccRCC (1). Center, Weill Cornell Medical College (WCMC) of Cornell University, 3 To delineate the gene expression pattern in TRACK transgenic New York, New York. Genomics Resources Core Facility,Weill Cornell þ Medical College (WCMC) of Cornell University, New York, New York. positive (TG ) kidneys, we sequenced the entire transcriptome of þ 4Division of Hematology and Medical Oncology, Department of Med- the TRACK TG kidney cortex by high-throughput sequencing of icine,Weill Cornell Medical College (WCMC) of Cornell University, New cDNA libraries (RNAseq) and compared it with both the gene York, New York. À expression profile in WT/transgenic negative (TG ) kidneys and Note: Supplementary data for this article are available at Molecular Cancer the gene expression profile observed in sporadic human ccRCC Research Online (http://mcr.aacrjournals.org/). using the Oncomine database (Compendia Bioscience) and The Corresponding Author: Lorraine J. Gudas, Weill Cornell Medical College of Cancer Genome Atlas (TCGA) database. We report that the þ Cornell University, 1300 York Avenue, New York, NY 10065. Phone: 212-746- pattern of gene expression in TRACK TG kidneys is similar to 6250; Fax: 212-746-8858; E-mail: [email protected] that of human ccRCC, including expression of transcripts associ- doi: 10.1158/1541-7786.MCR-14-0423 ated with glycolysis/gluconeogenesis, the pentose phosphate Ó2015 American Association for Cancer Research. pathway, and the lipid metabolism pathway. These data provide 870 Mol Cancer Res; 13(5) May 2015 Downloaded from mcr.aacrjournals.org on October 1, 2021. © 2015 American Association for Cancer Research. Published OnlineFirst February 25, 2015; DOI: 10.1158/1541-7786.MCR-14-0423 TRACK (GGT-HIF1aM3) Kidney RNAseq Figure 1. Global plotting of TRACK TGþ versus TGÀ kidney RNAseq result. A scatter plot of the RPKM values between þ À TRACK TG versus TG kidneys (A) and a principal component analysis result (B) are shown. The majority of transcripts show no differences in levels between TRACK TGþ versus TGÀ. There are transcripts that show increased (dots in the bottom right part of A) or decreased (dots in the top þ left part of A) levels in the TRACK TG versus TGÀ kidneys. Principal component analysis shows that there is a clear distinction between TRACK TGþ and TGÀ kidneys (B). evidence that constitutive activation of HIF1a in kidney PTCs Kilobase per Million mapped reads) values were created in R using transcriptionally reprograms the regulation of metabolic path- the heatmap.2 command of the gplots package. ways in a manner similar to that observed in human ccRCC. Human ccRCC data retrieval Materials and Methods Human ccRCC gene expression changes were retrieved from Animals Oncomine (Compendia Bioscience) by combining five different þ À TRACK TG and TG mice were housed five per cage in a 12- datasets of human ccRCC patient samples (17–20). The same five hour light/dark cycle in the Research Animal Resource Center of Oncomine datasets of Cancer versus Normal Analysis of ccRCC þ Weill Cornell Medical College (WCMC). The care and use of that we used in the g-HIF2aM3 TG RNAseq analysis (21) were animals in this study were approved by the Institutional Animal used in this analysis. Care and Use Committee of WCMC. Human ccRCC mRNA data were downloaded from TCGA (http://cancergenome.nih.gov/). Only tumor patient data with matched normal and normal patient data with matched tumor Whole transcriptome RNA sequencing were downloaded. All data satisfying this requirement were Total RNA from one thin, outer slice of kidney cortex per downloaded, including a total of 470 tumor samples and 68 kidney was used for whole transcriptome sequencing. Total normal samples. Differential expression between ccRCC and RNA was extracted using mini-RNAeasy columns (Qiagen). normal kidneys was calculated using the downloaded RPKM The complete transcriptomes of kidney cortices from three t þ values. Statistical analyses were performed by the Student test g-HIF1aM3 TRACK (#43 line) TG and three g-HIF1aM3 q fi À followed by FDR adjustment ( value). Statistical signi cance was TG male C57BL/6 mice (about 13 months old) were sequenced defined as q < 0.05. (51-bp single-end reads) on an Illumina HiSeq2000 Sequencer following standard protocols in the Genomics Resources Core Results Facility at WCMC. Three lanes were used to sequence all 12 samples (4 samples/lane, 2 kidney samples/mouse). The TRACK Expression of a mutated, constitutively active HIF1a in the RNAseq data have been deposited in the GEO database (acces- PTCs of the g-HIF1aM3 TRACK mice results in early stage tumors sion no. GSE54390). morphologically similar to human ccRCC (1). To identify changes in gene expression associated with ccRCC carcinogen- esis, we examined the whole transcriptome from cells in TRACK À Data analysis kidney cortex slices compared with TG controls. At the time of Data analysis was mainly performed with the Tuxedo tools sacrifice (13 months old), about 50% of the proximal tubules software (13). In brief, the RNAseq reads were first aligned to the in TRACK mice show clear cell abnormalities. However, further Mus musculus genome (UCSC version mm10) using Tophat ver- abnormalities, e.g., carcinoma in situ, are not ubiquitously seen sion 2.0.6 (13, 14). The aligned reads were assembled into in the kidney cortex. The average number of reads per sample transcripts, their abundance was estimated, and they were tested was approximately 45.6 million, and approximately 96% of for differential expression using Cufflinks version 2.1.1 (13, 15). reads mapped to the Mus musculus genome (Supplementary þ CummeRbund version 2.0.0 (13) was used to analyze the differ- Table S1). A scatter plot of the RPKM values of TRACK TG À ential expression analysis results. To identify pathways changed in versus TG kidneys shows that the majority of transcripts eval- þ À the TRACK TG versus TG kidneys, functional enrichment uated display no change between these two samples (Fig.
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