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• W2010991736 abstract "•Comprehensive molecular analysis is performed on 66 kidney chromophobe cases•Global molecular patterns provide clues as to this cancer’s cell of origin•mtDNA sequencing reveals loss-of-function mutations in NADH dehydrogenase subunits•Genomic structural rearrangements involving TERT promoter region are assessed We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) on the basis of multidimensional and comprehensive characterization, including mtDNA and whole-genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared with other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT upregulation in cancer distinct from previously observed amplifications and point mutations. We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) on the basis of multidimensional and comprehensive characterization, including mtDNA and whole-genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared with other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT upregulation in cancer distinct from previously observed amplifications and point mutations. Rare diseases can provide insights into the biology of more common pathologies. Using diverse molecular platforms, we deconstructed ChRCC, a tumor characterized by slow but persistent growth and high resistance to conventional cancer therapies. Global molecular patterns provide clues as to this cancer’s cell of origin. mtDNA alterations represent an integral component of the molecular portrait of ChRCC. The observed TERT promoter rearrangements may result from genomic instability in precancerous cells undergoing the crisis stage of immortalization, leading to activated telomerase. These data will facilitate further discovery of driver alterations extending beyond the exome as well as the generation of hypotheses that can advance our molecular understanding of this and other cancers. Rare tumor types offer a unique opportunity to investigate and discover mechanisms of tumorigenesis. Chromophobe renal cell carcinoma (ChRCC) is a subtype of renal cell carcinoma (RCC), representing ∼5% of this heterogeneous group of cancers arising from the nephron (Störkel et al., 1997Störkel S. Eble J.N. Adlakha K. Amin M. Blute M.L. Bostwick D.G. Darson M. Delahunt B. Iczkowski K. Union Internationale Contre le Cancer (UICC) and the American Joint Committee on Cancer (AJCC)Classification of renal cell carcinoma: Workgroup No. 1.Cancer. 1997; 80: 987-989Crossref PubMed Scopus (805) Google Scholar), with 3,000 new cases annually in the United States (Jemal et al., 2013Jemal A. Simard E.P. Dorell C. Noone A.M. Markowitz L.E. Kohler B. Eheman C. Saraiya M. Bandi P. Saslow D. et al.Annual Report to the Nation on the Status of Cancer, 1975-2009, featuring the burden and trends in human papillomavirus(HPV)-associated cancers and HPV vaccination coverage levels.J. Natl. Cancer Inst. 2013; 105: 175-201Crossref PubMed Scopus (805) Google Scholar). Although ChRCC typically exhibits an indolent pattern of local growth, with greater than 90% 10-year cancer-specific survival (Amin et al., 2002Amin M.B. Amin M.B. Tamboli P. Javidan J. Stricker H. de-Peralta Venturina M. Deshpande A. Menon M. Prognostic impact of histologic subtyping of adult renal epithelial neoplasms: an experience of 405 cases.Am. J. Surg. Pathol. 2002; 26: 281-291Crossref PubMed Scopus (596) Google Scholar, Przybycin et al., 2011Przybycin C.G. Cronin A.M. Darvishian F. Gopalan A. Al-Ahmadie H.A. Fine S.W. Chen Y.B. Bernstein M. Russo P. Reuter V.E. Tickoo S.K. Chromophobe renal cell carcinoma: a clinicopathologic study of 203 tumors in 200 patients with primary resection at a single institution.Am. J. Surg. Pathol. 2011; 35: 962-970Crossref PubMed Scopus (100) Google Scholar), aggressive features and metastasis can occur. ChRCC is associated with a distinct aneuploidy pattern (Speicher et al., 1994Speicher M.R. Schoell B. du Manoir S. Schröck E. Ried T. Cremer T. Störkel S. Kovacs A. Kovacs G. Specific loss of chromosomes 1, 2, 6, 10, 13, 17, and 21 in chromophobe renal cell carcinomas revealed by comparative genomic hybridization.Am. J. Pathol. 1994; 145: 356-364PubMed Google Scholar); however, genome-wide evaluation of its somatic mutation spectrum has not been reported. ChRCC is associated with germline mutation of FLCN in the autosomal-dominant cancer predisposition Birt-Hogg-Dubé (BHD) syndrome, in which 34% of BHD-associated kidney tumors are ChRCC (Nickerson et al., 2002Nickerson M.L. Warren M.B. Toro J.R. Matrosova V. Glenn G. Turner M.L. Duray P. Merino M. Choyke P. Pavlovich C.P. et al.Mutations in a novel gene lead to kidney tumors, lung wall defects, and benign tumors of the hair follicle in patients with the Birt-Hogg-Dubé syndrome.Cancer Cell. 2002; 2: 157-164Abstract Full Text Full Text PDF PubMed Scopus (714) Google Scholar, Pavlovich et al., 2002Pavlovich C.P. Walther M.M. Eyler R.A. Hewitt S.M. Zbar B. Linehan W.M. Merino M.J. Renal tumors in the Birt-Hogg-Dubé syndrome.Am. J. Surg. Pathol. 2002; 26: 1542-1552Crossref PubMed Scopus (469) Google Scholar, Schmidt et al., 2001Schmidt L.S. Warren M.B. Nickerson M.L. Weirich G. Matrosova V. Toro J.R. Turner M.L. Duray P. Merino M. Hewitt S. et al.Birt-Hogg-Dubé syndrome, a genodermatosis associated with spontaneous pneumothorax and kidney neoplasia, maps to chromosome 17p11.2.Am. J. Hum. Genet. 2001; 69: 876-882Abstract Full Text Full Text PDF PubMed Scopus (273) Google Scholar), and with germline mutation of PTEN in Cowden syndrome (Shuch et al., 2013Shuch B. Ricketts C.J. Vocke C.D. Komiya T. Middelton L.A. Kauffman E.C. Merino M.J. Metwalli A.R. Dennis P. Linehan W.M. Germline PTEN mutation cowden syndrome: an underappreciated form of hereditary kidney cancer.J. Urol. 2013; 190: 1990-1998Abstract Full Text Full Text PDF PubMed Scopus (69) Google Scholar). Previous studies have suggested a nonglycolytic metabolic profile for ChRCC, using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (Ho et al., 2012Ho C.L. Chen S. Ho K.M. Chan W.K. Leung Y.L. Cheng K.C. Wong K.N. Cheung M.K. Wong K.K. Dual-tracer PET/CT in renal angiomyolipoma and subtypes of renal cell carcinoma.Clin. Nucl. Med. 2012; 37: 1075-1082Crossref PubMed Scopus (36) Google Scholar), and have shown that the genomic profile comprises unique whole-chromosome losses rather than focal events (Speicher et al., 1994Speicher M.R. Schoell B. du Manoir S. Schröck E. Ried T. Cremer T. Störkel S. Kovacs A. Kovacs G. Specific loss of chromosomes 1, 2, 6, 10, 13, 17, and 21 in chromophobe renal cell carcinomas revealed by comparative genomic hybridization.Am. J. Pathol. 1994; 145: 356-364PubMed Google Scholar). Genomic profiling of rare cancers, such as ChRCC, can provide a more complete picture of the disease. Although very large sample numbers (>5,000) may be needed for some disease types in order to detect rare mutational events (Lawrence et al., 2014Lawrence M.S. Stojanov P. Mermel C.H. Robinson J.T. Garraway L.A. Golub T.R. Meyerson M. Gabriel S.B. Lander E.S. Getz G. Discovery and saturation analysis of cancer genes across 21 tumour types.Nature. 2014; 505: 495-501Crossref PubMed Scopus (2100) Google Scholar), in many cases, there remain undiscovered frequent mutations that drive disease. When data integration across multiple platforms is applied, patterns observed in one data type may be reflected in the other data types, building a more conclusive set of findings with regard to revealing driver events. For example, early DNA microarray studies of breast cancer, for example, globally assaying a single data type for 65 tumors (Perou et al., 2000Perou C.M. Sørlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnsen H. Akslen L.A. et al.Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (11710) Google Scholar) and incorporating clinical data, have had an enduring impact on our understanding of breast and other cancers, while PBRM1 mutations were discovered in clear cell kidney cancers from an initial analysis of just 25 tumors (Varela et al., 2011Varela I. Tarpey P. Raine K. Huang D. Ong C.K. Stephens P. Davies H. Jones D. Lin M.L. Teague J. et al.Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma.Nature. 2011; 469: 539-542Crossref PubMed Scopus (981) Google Scholar). Understudied cancers, such as ChRCC, may hold this potential for discovery as well. The Cancer Genome Atlas (TCGA) collected a total of 66 primary ChRCC specimens (Table S1 available online) with matching normal tissue/blood, in order to better characterize the molecular basis of this cancer using multiple data platforms (Table 1; Table S1). Our comprehensive analysis of ChRCC involved a systematic examination by data type, including copy number and whole-exome sequencing (WES). By SNP array analysis, loss of one copy of the entire chromosome, for most or all of chromosomes 1, 2, 6, 10, 13, and 17, was seen in the majority of cases (86%; Figure 1A). Losses of chromosomes 3, 5, 8, 9, 11, 18, and 21 were also noted at significant frequencies (12%–58%). There were no focal copy-number events by GISTIC analysis (Mermel et al., 2011Mermel C.H. Schumacher S.E. Hill B. Meyerson M.L. Beroukhim R. Getz G. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.Genome Biol. 2011; 12: R41Crossref PubMed Scopus (1806) Google Scholar), suggestive of a simpler chromosomal landscape for ChRCC in comparison with that of other cancers, including the more common clear cell type RCC (ccRCC). We subdivided our ChRCC cases according to previously defined histologic categories of “classic” (n = 47), which demonstrate the classical pale cytoplasmic features for which the disease was named, and “eosinophilic” (n = 19), based on abundant, eosinophilic cytoplasm and densely packed mitochondria, by expert consensus pathology review (Brunelli et al., 2005Brunelli M. Eble J.N. Zhang S. Martignoni G. Delahunt B. Cheng L. Eosinophilic and classic chromophobe renal cell carcinomas have similar frequent losses of multiple chromosomes from among chromosomes 1, 2, 6, 10, and 17, and this pattern of genetic abnormality is not present in renal oncocytoma.Mod. Pathol. 2005; 18: 161-169Crossref PubMed Scopus (169) Google Scholar). Although all classic cases showed the characteristic ChRCC copy-number pattern, only about half of the eosinophilic cases (10 of 19) showed the same, with four eosinophilic cases showing no copy-number alterations. This suggests a degree of genomic heterogeneity that distinguishes the histopathology-based classifications.Table 1Summary of Data TypesData TypePlatformsCasesData AccessTCGA core sample set (n = 66 total cases)Whole-exome DNA sequenceIllumina66controlledWhole-genome DNA sequenceIllumina50controlledmtDNA sequenceIllumina (LR-PCRaTo amplify mitochondrial DNA.)61controlledDNA copy number/genotypeAffymetrix SNP 666controlled: CEL filesopen: copy numbermRNA expressionIllumina66controlled: BAM filesopen: expressionmiRNA expressionIllumina66controlled: BAM filesopen: expressionCpG DNA methylationIllumina 450,000 array66openSee also Table S1.a To amplify mitochondrial DNA. Open table in a new tab See also Table S1. WES of 66 ChRCC cases targeted ∼186,260 exons in ∼18,091 genes, achieving 90% target coverage at a minimum of 20× for both tumor and matched normal samples. Overall, ChRCC displayed a low median rate of exonic somatic mutations (∼0.4 per Mb) compared with most tumors (Alexandrov et al., 2013Alexandrov L.B. Nik-Zainal S. Wedge D.C. Aparicio S.A. Behjati S. Biankin A.V. Bignell G.R. Bolli N. Borg A. Børresen-Dale A.L. et al.Australian Pancreatic Cancer Genome InitiativeICGC Breast Cancer ConsortiumICGC MMML-Seq ConsortiumICGC PedBrainSignatures of mutational processes in human cancer.Nature. 2013; 500: 415-421Crossref PubMed Scopus (6272) Google Scholar), approximately 3-fold less than the median number seen in ccRCC (which differences were also observable within strata defined by age or stage), with the one exception showing elevated somatic mutation rate (>10/Mb by WES) and mutation signature of DNA mismatch repair deficiency (Alexandrov et al., 2013Alexandrov L.B. Nik-Zainal S. Wedge D.C. Aparicio S.A. Behjati S. Biankin A.V. Bignell G.R. Bolli N. Borg A. Børresen-Dale A.L. et al.Australian Pancreatic Cancer Genome InitiativeICGC Breast Cancer ConsortiumICGC MMML-Seq ConsortiumICGC PedBrainSignatures of mutational processes in human cancer.Nature. 2013; 500: 415-421Crossref PubMed Scopus (6272) Google Scholar). Using alternative sequencing instrumentation, we validated 60 somatic mutation events for a set of 30 genes both arising from WES and having inferred biologically relevance (Table S2). Although our lower case numbers limited purely data-driven approaches to assigning statistical significance to infrequently mutated genes, we did have sufficient power to identify significant genes with a frequency of ∼10% (Lawrence et al., 2014Lawrence M.S. Stojanov P. Mermel C.H. Robinson J.T. Garraway L.A. Golub T.R. Meyerson M. Gabriel S.B. Lander E.S. Getz G. Discovery and saturation analysis of cancer genes across 21 tumour types.Nature. 2014; 505: 495-501Crossref PubMed Scopus (2100) Google Scholar). Only two significant genes were thus identified (MutSig q < 0.1): TP53 and PTEN. TP53 was frequently mutated in 32% of cases (21 of the 66 profiled), with mutations correlating with decreased expression of p53 transcriptional targets (Figures S1A–S1C). PTEN was the next most frequently mutated, with 9% (6 of 66) nonsilent mutations detected. No other genes were found to be mutated at a frequency higher than 5%, though mutations involving cancer-relevant genes were found at lower frequencies (Figure 1B). Mutations were seen in MTOR (2 cases), NRAS (1 activating mutation), and TSC1 or TSC2 (4 cases), and two homozygous deletions were seen in PTEN, indicating that genomic targeting of the mTOR pathway occurred overall in 15 (23%) of 66 ChRCCs (Figure 1B). Biological significance could be ascribed to infrequently mutated genes, in terms of associated pathways, including the p53 and PTEN pathways (Table S2). The genetic diseases BHD and tuberous sclerosis complex both predispose to the development of ChRCC, and associated mutations converge in activation of the PTEN signaling pathway. Our study focused on sporadic disease, and a surprisingly high percentage (∼47%) of our core cases did not show alterations associated with either PTEN or p53 pathways. Because no additional pathways involving sizable numbers of cases could be implicated from the exome data, our search was extended to mtDNA and structural variant (SV) analysis, as described below. TCGA data platforms allow for comparisons between tumor types (Cancer Genome Atlas Research Network et al., 2013Weinstein J. Collisson E. Mills G. Shaw K. Ozenberger B. Ellrott K. Shmulevich I. Sander C. Stuart J. Cancer Genome Atlas Research NetworkThe Cancer Genome Atlas Pan-Cancer analysis project.Nat. Genet. 2013; 45: 1113-1120Crossref PubMed Scopus (4198) Google Scholar). For example, we observed widespread differences in DNA methylation between ChRCC and ccRCC (Figure 2A), involving over 64,000 loci out of ∼450,000 profiled (p < 0.001, t test using logit-transformed data, beta value difference > 0.1). ChRCC displayed more hypomethylation and fewer hypermethylation events compared with ccRCC. We also observed epigenetic silencing of CDKN2A/p16 in four ChRCC cases (Figure 2B). In principle, differential DNA methylation patterns could involve cancer-relevant pathways but may also reflect the cell of origin of the cancer (Shen and Laird, 2013Shen H. Laird P.W. Interplay between the cancer genome and epigenome.Cell. 2013; 153: 38-55Abstract Full Text Full Text PDF PubMed Scopus (615) Google Scholar). On the basis of immunohistochemical analyses (Prasad et al., 2007Prasad S.R. Narra V.R. Shah R. Humphrey P.A. Jagirdar J. Catena J.R. Dalrymple N.C. Siegel C.L. Segmental disorders of the nephron: histopathological and imaging perspective.Br. J. Radiol. 2007; 80: 593-602Crossref PubMed Scopus (40) Google Scholar), ChRCC has been postulated to arise from intercalated cells in the distal convoluted tubule of the nephron, while ccRCC is thought to arise from cells in the proximal convoluted tubule; however, this issue has remained unresolved. The above DNA methylation patterns were consistent with distinct origins, leading us to further explore these origins using gene expression data. We examined our gene expression data in the context of an external gene expression data set of normal tissue microdissected from various regions of the nephron (Cheval et al., 2012Cheval L. Pierrat F. Rajerison R. Piquemal D. Doucet A. Of mice and men: divergence of gene expression patterns in kidney.PLoS ONE. 2012; 7: e46876Crossref PubMed Scopus (42) Google Scholar). Supervised analysis, globally comparing each TCGA ChRCC or ccRCC tumor expression profile (n = 66 and n = 417, respectively) with that of each sample in the nephron atlas, showed high mRNA expression correlations for ChRCC with distal regions of the nephron. ccRCC gene expression, however, was correlated with patterns associated with the proximal nephron (Figure 2C). These associations were also evident when focusing on the subset of differential genes in ChRCC versus ccRCC associated with inverse DNA methylation changes (Figure 2D). These results put into context many of the widespread molecular differences between these two kidney cancer types, as well as suggesting that cancers may be defined in part by cell of origin in addition to genetic aberrations. In addition to widespread differences in gene expression between ChRCC and ccRCC, and differences from normal kidney (Figure S2A and Table S3), unsupervised clustering of mRNA profiles indicated further molecular heterogeneity within ChRCC, with at least two subsets identified (Figure S2B) as defined by differential gene expression patterns. Cluster analysis of microRNA (miRNA) profiles also indicated heterogeneity (Figure S2C), and we could identify anticorrelations between miRNAs and their predicted mRNA targets (Table S4), including an anticorrelation (false discovery rate [FDR] < 0.01) involving miR-145 (low in ChRCC versus normal) and the complex I-associated NDUFA4 gene (Figure S2D) (Kano et al., 2010Kano M. Seki N. Kikkawa N. Fujimura L. Hoshino I. Akutsu Y. Chiyomaru T. Enokida H. Nakagawa M. Matsubara H. miR-145, miR-133a and miR-133b: Tumor-suppressive miRNAs target FSCN1 in esophageal squamous cell carcinoma.Int. J. Cancer. 2010; 127: 2804-2814Crossref PubMed Scopus (437) Google Scholar). Molecular correlates of patient survival in ChRCC were identifiable at levels of mRNA, miRNA, and DNA methylation (Table S5); many of these correlates were shared with those previously observed for ccRCC (Cancer Genome Atlas Research Network, 2013Cancer Genome Atlas Research NetworkComprehensive molecular characterization of clear cell renal cell carcinoma.Nature. 2013; 499: 43-49Crossref PubMed Scopus (2312) Google Scholar) and included cell cycle genes, but not the “Warburg effect”-like patterns of aggressive ccRCC (Cancer Genome Atlas Research Network, 2013Cancer Genome Atlas Research NetworkComprehensive molecular characterization of clear cell renal cell carcinoma.Nature. 2013; 499: 43-49Crossref PubMed Scopus (2312) Google Scholar). When viewed in the context of mitochondrial function, expression of nuclear-encoded genes in ChRCC, with compared to normal kidney, suggested increased utilization of the Krebs cycle and electron transport chain (ETC) for ATP generation (Figure 3A; Figures S3A and S3B). In ChRCC, nearly all genes encoding enzymes in the Krebs cycle showed increased expression over normal, with the entry of pyruvate into the Krebs cycle via acetyl coenzyme A likely through the pyruvate dehydrogenase complex. Concordantly, all complexes of the ETC demonstrated mRNA increases in at least one gene. These patterns could reflect an increased level of mitochondrial biosynthesis, resulting in greater numbers of mitochondria within each tumor cell; this possibility is supported by both the increased expression of mitochondrial biogenesis regulator PPARGC1A (p < 1 × 10−5, t test using log-transformed data; Table S3) and increased mitochondrial genome copy numbers (four times more on average in ChRCC versus normal kidney; Figure 3B; Figure S3C). These findings interestingly parallel the eosinophilic histology observed in some ChRCC, corresponding to the high uptake of eosin by mitochondria. Eosinophilic ChRCC tumors share many features with the benign variant oncocytoma, which is also characterized by dense accumulations of mitochondria (Amin et al., 2008Amin M.B. Paner G.P. Alvarado-Cabrero I. Young A.N. Stricker H.J. Lyles R.H. Moch H. Chromophobe renal cell carcinoma: histomorphologic characteristics and evaluation of conventional pathologic prognostic parameters in 145 cases.Am. J. Surg. Pathol. 2008; 32: 1822-1834Crossref PubMed Scopus (199) Google Scholar, Tickoo et al., 2000Tickoo S.K. Lee M.W. Eble J.N. Amin M. Christopherson T. Zarbo R.J. Amin M.B. Ultrastructural observations on mitochondria and microvesicles in renal oncocytoma, chromophobe renal cell carcinoma, and eosinophilic variant of conventional (clear cell) renal cell carcinoma.Am. J. Surg. Pathol. 2000; 24: 1247-1256Crossref PubMed Scopus (135) Google Scholar). Furthermore, the gene expression landscape appeared very different from that of ccRCC, in which expression of genes involved in mitochondrial functions is strongly suppressed (Figure S3D) (Cancer Genome Atlas Research Network, 2013Cancer Genome Atlas Research NetworkComprehensive molecular characterization of clear cell renal cell carcinoma.Nature. 2013; 499: 43-49Crossref PubMed Scopus (2312) Google Scholar). These findings suggest that various bioenergetics strategies may support tumor growth and that not all cancers necessarily seek to minimize their reliance upon oxidative phosphorylation (Cancer Genome Atlas Research Network, 2013Cancer Genome Atlas Research NetworkComprehensive molecular characterization of clear cell renal cell carcinoma.Nature. 2013; 499: 43-49Crossref PubMed Scopus (2312) Google Scholar). Given the indicated prevalent role of mitochondria in ChRCC and the likelihood of rapid mitochondrial genome replication (Figure 3B), we sequenced mtDNA from 61 of our 66 ChRCC cases, using a PCR-based amplification approach (Table S6). In all, we identified 142 somatic mutation events (i.e., not present in the normal) at various levels of heteroplasmy (i.e., mixture with other variants), 75 of these residing within the commonly altered D-loop noncoding region (Chatterjee et al., 2006Chatterjee A. Mambo E. Sidransky D. Mitochondrial DNA mutations in human cancer.Oncogene. 2006; 25: 4663-4674Crossref PubMed Scopus (462) Google Scholar). Thirty-five mutation events (involving 27 cases) were present in over 50% of mtDNA copies in the tumor (>50% heteroplasmy) (Figure 4A). Human mtDNA encodes 13 proteins involved in respiration and oxidative phosphorylation (Figure 3A), and we found 15 nonsilent mutations in 12 ChRCC cases involving these genes (>50% heteroplasmy), all of which validated using alternative strategies, including whole-genome sequencing (WGS)-based analysis (Larman et al., 2012Larman T.C. DePalma S.R. Hadjipanayis A.G. Protopopov A. Zhang J. Gabriel S.B. Chin L. Seidman C.E. Kucherlapati R. Seidman J.G. Cancer Genome Atlas Research NetworkSpectrum of somatic mitochondrial mutations in five cancers.Proc. Natl. Acad. Sci. USA. 2012; 109: 14087-14091Crossref PubMed Scopus (171) Google Scholar) (Table S6). On the basis of previous functional studies in oncocytoma (Gasparre et al., 2008Gasparre G. Hervouet E. de Laplanche E. Demont J. Pennisi L.F. Colombel M. Mège-Lechevallier F. Scoazec J.Y. Bonora E. Smeets R. et al.Clonal expansion of mutated mitochondrial DNA is associated with tumor formation and complex I deficiency in the benign renal oncocytoma.Hum. Mol. Genet. 2008; 17: 986-995Crossref PubMed Scopus (124) Google Scholar, Mayr et al., 2008Mayr J.A. Meierhofer D. Zimmermann F. Feichtinger R. Kögler C. Ratschek M. Schmeller N. Sperl W. Kofler B. Loss of complex I due to mitochondrial DNA mutations in renal oncocytoma.Clin. Cancer Res. 2008; 14: 2270-2275Crossref PubMed Scopus (134) Google Scholar, Simonnet et al., 2003Simonnet H. Demont J. Pfeiffer K. Guenaneche L. Bouvier R. Brandt U. Schagger H. Godinot C. Mitochondrial complex I is deficient in renal oncocytomas.Carcinogenesis. 2003; 24: 1461-1466Crossref PubMed Scopus (104) Google Scholar), and because many of our variants represented frameshift substitutions, these mtDNA mutations are thought, in general, to lead to inactivation, rather than activation, of the associated protein. ETC complex I genes were altered in 18% of cases (n = 11; Figures 1B and 3A; Table S3); the most frequently altered gene was MT-ND5, in six cases (all with >70% heteroplasmy), with five of these being histologically classified as eosinophilic ChRCC (p < 0.01, one-sided Fisher’s exact test) and three showing no copy-number abnormalities (p < 0.002). MT-ND5 is essential for the activity of complex I (Chomyn, 2001Chomyn A. Mitochondrial genetic control of assembly and function of complex I in mammalian cells.J. Bioenerg. Biomembr. 2001; 33: 251-257Crossref PubMed Scopus (73) Google Scholar), which is responsible for the transfer of electrons from NADH to ubiquinone. One ChRCC case had a single base insertion at position 12417 that changes the length of an 8-bp homopolymer tract in MT-ND5, which has been observed previously in several other cancer types (Larman et al., 2012Larman T.C. DePalma S.R. Hadjipanayis A.G. Protopopov A. Zhang J. Gabriel S.B. Chin L. Seidman C.E. Kucherlapati R. Seidman J.G. Cancer Genome Atlas Research NetworkSpectrum of somatic mitochondrial mutations in five cancers.Proc. Natl. Acad. Sci. USA. 2012; 109: 14087-14091Crossref PubMed Scopus (171) Google Scholar); another case had an insertion at 12384, at which position a mutation was found elsewhere in oncocytoma and associated with loss of complex I activity (Mayr et al., 2008Mayr J.A. Meierhofer D. Zimmermann F. Feichtinger R. Kögler C. Ratschek M. Schmeller N. Sperl W. Kofler B. Loss of complex I due to mitochondrial DNA mutations in renal oncocytoma.Clin. Cancer Res. 2008; 14: 2270-2275Crossref PubMed Scopus (134) Google Scholar). Two ChRCC cases each had single-base deletions at position 13230 of MT-ND5, but no other mtDNA mutations were recurrent in our cases. We also found MT-ND5-mutated ChRCC cases to have a distinct gene transcription signature (Figure 4B; Figures S4A and S4B; 719 genes with p < 0.001 by t test, FDR < 0.05), which was shared by other eosinophilic cases and not limited to genes in regions of recurrent copy-number abnormality (Figure S4C). Genes with high expression in MT-ND5-mutated cases were enriched for those associated with mitochondria (43 with Gene Ontology term “mitochondrion;” p < 5 × 10−6, one-sided Fisher’s exact test), including several with roles in ETC (SDHB, NDUFS1, ATP5F1, COX10, and COX11; Table S3). Notably, mutations in complex I did not result in expression patterns associated with loss of oxidative phosphorylation (Figure 4C), as might be assumed (Larman et al., 2012Larman T.C. DePalma S.R. Hadjipanayis A.G. Protopopov A. Zhang J. Gabriel S.B. Chin L. Seidman C.E. Kucherlapati R. Seidman J.G. Cancer Genome Atlas Research NetworkSpectrum of somatic mitochondrial mutations in five cancers.Proc. Natl. Acad. Sci. USA. 2012; 109: 14087-14091Crossref PubMed Scopus (171) Google Scholar), suggesting possible alternative roles for complex I alteration in cancer-associated metabolic activity (Figure S4D). The associations made here, involving mtDNA mutations with mitochondrial abundance and differential gene expression patterns (which may be unique to ChRCC and related cancers), could perhaps suggest either a compensatory role for loss of complex I function or selective pressures operating to promote alternative pathways. WGS for 50 of our 66 ChRCC cases was performed (60× and 30× coverage for paired tumor and normal, respectively). The Meerkat algorithm (Yang et al., 2013Yang L. Luquette L.J. Gehlenborg N. Xi R. Haseley P.S. Hsieh C.H. Zhang C. Ren X. Protopopov A. Chin L. et al.Diverse mechanisms of somatic structural variations in human cancer genomes.Cell. 2013; 153: 919-929Abstract Full Text Full Text PDF PubMed Scopus (225) Google Scholar) was applied to detect genomic rearrangements, with an average of 16 found per case (range 0–207; Figure S5A), but without involving recurrent gene-gene fusions. By WGS analysis, a subset of ChRCC manifested kataegis" @default.
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