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The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Christopher J Ricketts et al. Cell Rep. .

Erratum in

  • The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma.
    Ricketts CJ, De Cubas AA, Fan H, Smith CC, Lang M, Reznik E, Bowlby R, Gibb EA, Akbani R, Beroukhim R, Bottaro DP, Choueiri TK, Gibbs RA, Godwin AK, Haake S, Hakimi AA, Henske EP, Hsieh JJ, Ho TH, Kanchi RS, Krishnan B, Kwiatkowski DJ, Lui W, Merino MJ, Mills GB, Myers J, Nickerson ML, Reuter VE, Schmidt LS, Shelley CS, Shen H, Shuch B, Signoretti S, Srinivasan R, Tamboli P, Thomas G, Vincent BG, Vocke CD, Wheeler DA, Yang L, Kim WY, Robertson AG; Cancer Genome Atlas Research Network; Spellman PT, Rathmell WK, Linehan WM. Ricketts CJ, et al. Cell Rep. 2018 Jun 19;23(12):3698. doi: 10.1016/j.celrep.2018.06.032. Cell Rep. 2018. PMID: 29925010 No abstract available.
  • The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma.
    Ricketts CJ, De Cubas AA, Fan H, Smith CC, Lang M, Reznik E, Bowlby R, Gibb EA, Akbani R, Beroukhim R, Bottaro DP, Choueiri TK, Gibbs RA, Godwin AK, Haake S, Hakimi AA, Henske EP, Hsieh JJ, Ho TH, Kanchi RS, Krishnan B, Kwiatkowski DJ, Liu W, Merino MJ, Mills GB, Myers J, Nickerson ML, Reuter VE, Schmidt LS, Shelley CS, Shen H, Shuch B, Signoretti S, Srinivasan R, Tamboli P, Thomas G, Vincent BG, Vocke CD, Wheeler DA, Yang L, Kim WY, Robertson AG; Cancer Genome Atlas Research Network; Spellman PT, Rathmell WK, Linehan WM. Ricketts CJ, et al. Cell Rep. 2024 Apr 23;43(4):113063. doi: 10.1016/j.celrep.2023.113063. Epub 2024 Apr 4. Cell Rep. 2024. PMID: 38578829 No abstract available.

Abstract

Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.

Keywords: CDKN2A; DNA hypermethylation; PanCanAtlas; TCGA; chromatin remodeling; chromophobe renal cell carcinoma; clear cell renal cell carcinoma; immune signature; papillary renal cell carcinoma.

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Conflict of interest statement

DECLARATION OF INTERESTS

Michael Seiler, Peter G. Smith, Ping Zhu, Silvia Buonamici, and Lihua Yu are employees of H3 Biomedicine, Inc. Parts of this work are the subject of a patent application: WO2017040526 titled “Splice variants associated with neomorphic sf3b1 mutants.” Shouyoung Peng, Anant A. Agrawal, James Palacino, and Teng Teng are employees of H3 Biomedicine, Inc. Andrew D. Cherniack, Ashton C. Berger, and Galen F. Gao receive research support from Bayer Pharmaceuticals. Gordon B. Mills serves on the External Scientific Review Board of Astrazeneca. Anil Sood is on the Scientific Advisory Board for Kiyatec and is a shareholder in BioPath. Jonathan S. Serody receives funding from Merck, Inc. Kyle R. Covington is an employee of Castle Biosciences, Inc. Preethi H. Gunaratne is founder, CSO, and shareholder of NextmiRNA Therapeutics. Christina Yau is a part-time employee/consultant at NantOmics. Franz X. Schaub is an employee and shareholder of SEngine Precision Medicine, Inc. Carla Grandori is an employee, founder, and shareholder of SEngine Precision Medicine, Inc. Robert N. Eisenman is a member of the Scientific Advisory Boards and shareholder of Shenogen Pharma and Kronos Bio. Daniel J. Weisenberger is a consultant for Zymo Research Corporation. Joshua M. Stuart is the founder of Five3 Genomics and shareholder of NantOmics. Marc T. Goodman receives research support from Merck, Inc. Andrew J. Gentles is a consultant for Cibermed. Charles M. Perou is an equity stock holder, consultant, and Board of Directors member of BioClassifier and GeneCentric Diagnostics and is also listed as an inventor on patent applications on the Breast PAM50 and Lung Cancer Subtyping assays. Matthew Meyerson receives research support from Bayer Pharmaceuticals; is an equity holder in, consultant for, and Scientific Advisory Board chair for OrigiMed; and is an inventor of a patent for EGFR mutation diagnosis in lung cancer, licensed to LabCorp. Eduard Porta-Pardo is an inventor of a patent for domainXplorer. Han Liang is a shareholder and scientific advisor of Precision Scientific and Eagle Nebula. Da Yang is an inventor on a pending patent application describing the use of antisense oligonucleotides against specific lncRNA sequence as diagnostic and therapeutic tools. Yonghong Xiao was an employee and shareholder of TESARO, Inc. Bin Feng is an employee and shareholder of TESARO, Inc. Carter Van Waes received research funding for the study of IAP inhibitor ASTX660 through a Cooperative Agreement between NIDCD, NIH, and Astex Pharmaceuticals. Raunaq Malhotra is an employee and shareholder of Seven Bridges, Inc. Peter W. Laird serves on the Scientific Advisory Board for AnchorDx. Joel Tepper is a consultant at EMD Serono. Kenneth Wang serves on the Advisory Board for Boston Scientific, Microtech, and Olympus. Andrea Califano is a founder, shareholder, and advisory board member of DarwinHealth, Inc. and a shareholder and advisory board member of Tempus, Inc. Toni K. Choueiri serves as needed on advisory boards for Bristol-Myers Squibb, Merck, and Roche. Lawrence Kwong receives research support from Array BioPharma. Sharon E. Plon is a member of the Scientific Advisory Board for Baylor Genetics Laboratory. Beth Y. Karlan serves on the Advisory Board of Invitae.

Figures

Figure 1
Figure 1. Comparison of RCC Histologic Subtypes
(A) Heatmap representation of chromosomal copy number and RNA expression profiles between the different histologic RCC subtypes. Chromosomal copy number data are ordered by chromosomal arm in descending order (red, gain; blue, loss). The relative RNA expression was assessed for the most variable probes within the complete RCC cohort for either mRNA (n = 500), miRNA (n = 249), or lncRNA (n = 178) (red, increased; blue, decreased). RCC samples were arrayed left to right based on histologic subtype (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; unclassified [Unc.] PRCC, gray; CIMP-RCC, red; ChRCC, purple), then tumor stage (stage I, light green; stage II, yellow; stage III, orange; stage IV, red), and then vital status (alive, white; deceased, black). (B) Percentage of chromosomal copy number alterations between the different histologic RCC subtypes. (C) Differences in patient overall survival between the different histologic RCC subtypes (log-rank p value).
Figure 2
Figure 2. Gene and Pathway Alteration Associates with Survival Predictions in Specific RCC Subtypes
(A) Differences in patient overall survival within histologic RCC subtypes (ccRCC, green; PRCC, blue; ChRCC, purple) dependent upon gene mutation (log-rank p value). (B) Oncoprints for CDKN2A gene deletions, hypermethylation, and mutations for the histologic RCC subtypes (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; Unc. PRCC, gray; CIMP-RCC, red; ChRCC, purple). Mutations were segregated into nonsense (red) and missense (blue). (C) Differences in patient overall survival within the histologic RCC subtypes (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; ChRCC, purple) dependent upon CDKN2A alteration (log-rank p value). (D) Chromatin remodeling pathway mutation frequency within histologic RCC subtypes (ccRCC, green; PRCC, blue; ChRCC, purple). Abbreviations: Me, histone methylation; Ac, histone acetylation; Ub, histone ubiquitination.
Figure 3
Figure 3. Hypermethylation Patterns Associate with Survival Predictions
(A) Heatmap representation of the clustering of 1,532 highly variable DNA methylation probes that were unmethylated in the normal tissues. A methylation b-value R 0.3 was considered hypermethylated. Tumors were annotated for histologic RCC subtype (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; Unc. PRCC, gray; CIMP-RCC, red; ChRCC, purple), tumor stage (stage I, light green; stage II, yellow; stage III, orange; stage IV, red), vital status (alive, white; deceased, black), and DKK1 (cg07684796) and SFRP1 (cg15839448) hypermethylation (hypermethylated, dark green). (B) Differences in patient overall survival within the histologic RCC subtypes (ccRCC, green; PRCC, blue; ChRCC, purple) dependent upon methylation cluster (log-rank p value). (C) Differences in patient overall survival within ccRCC and ChRCC tumors (ccRCC, green; ChRCC, purple) dependent upon hypermethylation of either SFRP1 or DKK1 (log-rank p value).
Figure 4
Figure 4. RCC Histologic Subtypes Associate with Specific mRNA Signatures
(A) Heatmap representation of the comparison of mRNA expression signatures for major cellular processes between the different histologic RCC subtypes (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; Unc. PRCC, gray; CIMP-RCC, red; ChRCC, purple). Tumor stage (stage I, light green; stage II, yellow; stage III, orange; stage IV, red) and vital status (alive, white; deceased, black) are indicated above the heatmap. (B) Heatmap representation showing the relationship between gene expression modules and clinical features. Red heatmap shading indicates a positive correlation between a gene module and a clinical feature and blue heatmap shading represents a negative correlation.
Figure 5
Figure 5. Metabolic Analysis of RCC Histologic Subtypes
(A) Schematic of metabolic pathway genes selected for metabolic analysis. (B) Heatmap representation of the comparison of mRNA expression signatures for the selected metabolic processes between the different histologic RCC subtypes (ccRCC, green; type 1 PRCC, light blue; type 2 PRCC, orange; Unc. PRCC, gray; CIMP-RCC, red; ChRCC, purple). Tumor stage (stage I, light green; stage II, yellow; stage III, orange; stage IV, red) and vital status (alive, white; deceased, black) are indicated above the heatmap. (C) Comparative expression of the ribose sugar metabolism signature between the different histologic RCC (ccRCC, green; ccRCC stage I/II, dark blue; ccRCC stage III/IV, dark red; type 1 PRCC, light blue; type 2 PRCC, orange; Unc. PRCC, gray; CIMP-RCC, red; ChRCC, purple). (D) Differences in patient overall survival within ccRCC dependent upon expression of the ribose sugar metabolism signature (log-rank p value). (E) Comparative expression of the Krebs cycle, ETC Complex III, AMPK, and ribose sugar metabolism gene signatures between ChRCC and metabolically divergent (MD) ChRCC (ChRCC, purple; MD-ChRCC, pink). (F) Differences in patient overall survival between ChRCC and MD-ChRCC (log-rank p value).
Figure 6
Figure 6. Immune Signature Analysis
(A) Supervised clustering of immune gene signature (IGS) expression by individual sample (left) or mean IGS expression (right) for the different histologic RCC subtypes (ccRCC, green; PRCC, blue; ChRCC, purple). (B) Comparative expression of the Th2 gene signature between the histologic RCC subtypes (ccRCC, green; PRCC, blue; type 1 PRCC, light blue; type 2 PRCC, orange; CIMP-RCC, red; unclassified PRCC, gray; ChRCC, purple) (t test). (C) Comparative differences in patient overall survival within the histologic RCC subtypes (ccRCC, green; PRCC, blue; type 2 PRCC, orange; ChRCC, purple) dependent upon the Th2 gene signature (log-rank p value).
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References

    1. Aine M, Eriksson P, Liedberg F, Sjödahl G, Höglund M. Biological determinants of bladder cancer gene expression subtypes. Sci Rep. 2015;5:10957. - PMC - PubMed
    1. Beck AH, Espinosa I, Edris B, Li R, Montgomery K, Zhu S, Varma S, Marinelli RJ, van de Rijn M, West RB. The macrophage colony-stimulating factor 1 response signature in breast carcinoma. Clin Cancer Res. 2009;15:778–787. - PMC - PubMed
    1. Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, Angell H, Fredriksen T, Lafontaine L, Berger A, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39:782–795. - PubMed
    1. Bolotin DA, Shugay M, Mamedov IZ, Putintseva EV, Turchaninova MA, Zvyagin IV, Britanova OV, Chudakov DM. MiTCR: software for T-cell receptor sequencing data analysis. Nat Methods. 2013;10:813–814. - PubMed
    1. Calabrese C, Simone D, Diroma MA, Santorsola M, Guttà C, Gasparre G, Picardi E, Pesole G, Attimonelli M. MToolBox: a highly automated pipeline for heteroplasmy annotation and prioritization analysis of human mitochondrial variants in high-throughput sequencing. Bioinformatics. 2014;30:3115–3117. - PMC - PubMed

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