. 2019 Oct 31;179(4):964-983.e31.

doi: 10.1016/j.cell.2019.10.007.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

David J Clark¹, Saravana M Dhanasekaran², Francesca Petralia³, Jianbo Pan¹, Xiaoyu Song⁴, Yingwei Hu¹, Felipe da Veiga Leprevost², Boris Reva³, Tung-Shing M Lih¹, Hui-Yin Chang², Weiping Ma³, Chen Huang⁵, Christopher J Ricketts⁶, Lijun Chen¹, Azra Krek³, Yize Li⁷, Dmitry Rykunov³, Qing Kay Li¹, Lin S Chen⁸, Umut Ozbek⁴, Suhas Vasaikar⁹, Yige Wu⁷, Seungyeul Yoo³, Shrabanti Chowdhury³, Matthew A Wyczalkowski⁷, Jiayi Ji⁴, Michael Schnaubelt¹, Andy Kong², Sunantha Sethuraman⁷, Dmitry M Avtonomov², Minghui Ao¹, Antonio Colaprico¹⁰, Song Cao⁷, Kyung-Cho Cho¹, Selim Kalayci³, Shiyong Ma¹, Wenke Liu¹¹, Kelly Ruggles¹², Anna Calinawan³, Zeynep H Gümüş³, Daniel Geiszler¹³, Emily Kawaler¹¹, Guo Ci Teo², Bo Wen⁵, Yuping Zhang², Sarah Keegan¹¹, Kai Li⁵, Feng Chen¹⁴, Nathan Edwards¹⁵, Phillip M Pierorazio¹⁶, Xi Steven Chen¹⁷, Christian P Pavlovich¹⁶, A Ari Hakimi¹⁸, Gabriel Brominski¹⁹, James J Hsieh²⁰, Andrzej Antczak¹⁹, Tatiana Omelchenko²¹, Jan Lubinski²², Maciej Wiznerowicz²³, W Marston Linehan⁶, Christopher R Kinsinger²⁴, Mathangi Thiagarajan²⁵, Emily S Boja²⁴, Mehdi Mesri²⁴, Tara Hiltke²⁴, Ana I Robles²⁴, Henry Rodriguez²⁴, Jiang Qian²⁶, David Fenyö¹¹, Bing Zhang²⁷, Li Ding⁷, Eric Schadt²⁸, Arul M Chinnaiyan², Zhen Zhang¹, Gilbert S Omenn²⁹, Marcin Cieslik³⁰, Daniel W Chan³¹, Alexey I Nesvizhskii³², Pei Wang³³, Hui Zhang³⁴; Clinical Proteomic Tumor Analysis Consortium

Collaborators, Affiliations

Collaborators

Clinical Proteomic Tumor Analysis Consortium:
Abdul Samad Hashimi, Alexander R Pico, Alla Karpova, Alyssa Charamut, Amanda G Paulovich, Amy M Perou, Anna Malovannaya, Annette Marrero-Oliveras, Anupriya Agarwal, Barbara Hindenach, Barbara Pruetz, Beom-Jun Kim, Brian J Druker, Chelsea J Newton, Chet Birger, Corbin D Jones, Cristina Tognon, D R Mani, Dana R Valley, Daniel C Rohrer, Daniel C Zhou, Darlene Tansil, David Chesla, David Heiman, David Wheeler, Donghui Tan, Doug Chan, Emek Demir, Ewa Malc, Francesmary Modugno, Gaddy Getz, Galen Hostetter, George D Wilson, Gerald W Hart, Heng Zhu, Hongwei Liu, Houston Culpepper, Hua Sun, Hua Zhou, Jacob Day, James Suh, Jasmine Huang, Jason McDermott, Jeffrey R Whiteaker, Jeffrey W Tyner, Jennifer Eschbacher, Jin Chen, John McGee, Jun Zhu, Karen A Ketchum, Karin D Rodland, Karl Clauser, Karna Robinson, Karsten Krug, Katherine A Hoadley, Ki Sung Um, Kim Elburn, Kimberly Holloway, Liang-Bo Wang, Lili Blumenberg, Linda Hannick, Liqun Qi, Lori J Sokoll, MacIntosh Cornwell, Marc Loriaux, Marcin J Domagalski, Marina A Gritsenko, Matthew Anderson, Matthew E Monroe, Matthew J Ellis, Maureen Dyer, Meenakshi Anurag, Meghan C Burke, Melissa Borucki, Michael A Gillette, Michael J Birrer, Michael Lewis, Michael M Ittmann, Michael Smith, Michael Vernon, Michelle Chaikin, Milan G Chheda, Munziba Khan, Nancy Roche, Nathan J Edwards, Negin Vatanian, Nicole Tignor, Noam Beckmann, Pamela Grady, Patricia Castro, Paul Piehowski, Peter B McGarvey, Piotr Mieczkowski, Pushpa Hariharan, Qingsong Gao, Rajiv Dhir, Ramani Bhupendra Kothadia, Ratna R Thangudu, Rebecca Montgomery, Reyka G Jayasinghe, Richard D Smith, Robert Edwards, Robert Zelt, Ross Bremner, Ruiyang Liu, Runyu Hong, Sailaja Mareedu, Samuel H Payne, Sandra Cottingham, Sanford P Markey, Scott D Jewell, Shalin Patel, Shankha Satpathy, Shannon Richey, Sherri R Davies, Shuang Cai, Simina M Boca, Snehal Patil, Sohini Sengupta, Sonya Carter, Stacey Gabriel, Stefani N Thomas, Stephanie De Young, Stephen E Stein, Steven A Carr, Steven M Foltz, Sue Hilsenbeck, Tanya Krubit, Tao Liu, Tara Skelly, Thomas Westbrook, Uma Borate, Uma Velvulou, Vladislav A Petyuk, William E Bocik, Xi Chen, Yan Shi, Yifat Geffen, Yihao Lu, Ying Wang, Yosef Maruvka, Zhi Li, Zhiao Shi, Zhidong Tu

Affiliations

¹ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.
² Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
³ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁴ Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁵ Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA.
⁶ Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
⁷ Washington University School of Medicine, St. Louis, MO 63110, USA.
⁸ Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
⁹ Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX 77030, USA.
¹⁰ Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
¹¹ Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA.
¹² Department of Medicine, New York University School of Medicine, New York, NY 10016, USA.
¹³ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
¹⁴ Departments of Medicine and Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
¹⁵ Department of Biochemistry and Cellular Biology, Georgetown University, Washington, DC 20007, USA.
¹⁶ Brady Urological Institute and Department of Urology, Johns Hopkins University, Baltimore, MD 21231, USA.
¹⁷ Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
¹⁸ Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
¹⁹ Department of Urology, Poznań University of Medical Sciences, Szwajcarska 3, Poznań 61-285, Poland.
²⁰ Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
²¹ Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
²² Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland.
²³ International Institute for Molecular Oncology, Poznań 60-203, Poland; Poznań University of Medical Sciences, Poznan 60-701, Poland.
²⁴ Office of Cancer Clinical Proteomics Research, National Cancer Institute, Bethesda, MD 20892, USA.
²⁵ Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
²⁶ Department of Ophthalmology, Johns Hopkins University, Baltimore, MD 21231, USA.
²⁷ Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
²⁸ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Sema4, Stamford, CT 06902, USA.
²⁹ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
³⁰ Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: mcieslik@med.mich.edu.
³¹ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA. Electronic address: dchan@jhmi.edu.
³² Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: nesvi@med.umich.edu.
³³ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: pei.wang@mssm.edu.
³⁴ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA. Electronic address: huizhang@jhu.edu.

PMID: 31675502
PMCID: PMC7331093
DOI: 10.1016/j.cell.2019.10.007

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

David J Clark et al. Cell. 2019.

. 2019 Oct 31;179(4):964-983.e31.

doi: 10.1016/j.cell.2019.10.007.

Authors

Collaborators

Clinical Proteomic Tumor Analysis Consortium:
Abdul Samad Hashimi, Alexander R Pico, Alla Karpova, Alyssa Charamut, Amanda G Paulovich, Amy M Perou, Anna Malovannaya, Annette Marrero-Oliveras, Anupriya Agarwal, Barbara Hindenach, Barbara Pruetz, Beom-Jun Kim, Brian J Druker, Chelsea J Newton, Chet Birger, Corbin D Jones, Cristina Tognon, D R Mani, Dana R Valley, Daniel C Rohrer, Daniel C Zhou, Darlene Tansil, David Chesla, David Heiman, David Wheeler, Donghui Tan, Doug Chan, Emek Demir, Ewa Malc, Francesmary Modugno, Gaddy Getz, Galen Hostetter, George D Wilson, Gerald W Hart, Heng Zhu, Hongwei Liu, Houston Culpepper, Hua Sun, Hua Zhou, Jacob Day, James Suh, Jasmine Huang, Jason McDermott, Jeffrey R Whiteaker, Jeffrey W Tyner, Jennifer Eschbacher, Jin Chen, John McGee, Jun Zhu, Karen A Ketchum, Karin D Rodland, Karl Clauser, Karna Robinson, Karsten Krug, Katherine A Hoadley, Ki Sung Um, Kim Elburn, Kimberly Holloway, Liang-Bo Wang, Lili Blumenberg, Linda Hannick, Liqun Qi, Lori J Sokoll, MacIntosh Cornwell, Marc Loriaux, Marcin J Domagalski, Marina A Gritsenko, Matthew Anderson, Matthew E Monroe, Matthew J Ellis, Maureen Dyer, Meenakshi Anurag, Meghan C Burke, Melissa Borucki, Michael A Gillette, Michael J Birrer, Michael Lewis, Michael M Ittmann, Michael Smith, Michael Vernon, Michelle Chaikin, Milan G Chheda, Munziba Khan, Nancy Roche, Nathan J Edwards, Negin Vatanian, Nicole Tignor, Noam Beckmann, Pamela Grady, Patricia Castro, Paul Piehowski, Peter B McGarvey, Piotr Mieczkowski, Pushpa Hariharan, Qingsong Gao, Rajiv Dhir, Ramani Bhupendra Kothadia, Ratna R Thangudu, Rebecca Montgomery, Reyka G Jayasinghe, Richard D Smith, Robert Edwards, Robert Zelt, Ross Bremner, Ruiyang Liu, Runyu Hong, Sailaja Mareedu, Samuel H Payne, Sandra Cottingham, Sanford P Markey, Scott D Jewell, Shalin Patel, Shankha Satpathy, Shannon Richey, Sherri R Davies, Shuang Cai, Simina M Boca, Snehal Patil, Sohini Sengupta, Sonya Carter, Stacey Gabriel, Stefani N Thomas, Stephanie De Young, Stephen E Stein, Steven A Carr, Steven M Foltz, Sue Hilsenbeck, Tanya Krubit, Tao Liu, Tara Skelly, Thomas Westbrook, Uma Borate, Uma Velvulou, Vladislav A Petyuk, William E Bocik, Xi Chen, Yan Shi, Yifat Geffen, Yihao Lu, Ying Wang, Yosef Maruvka, Zhi Li, Zhiao Shi, Zhidong Tu

Affiliations

¹ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.
² Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
³ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁴ Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁵ Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA.
⁶ Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
⁷ Washington University School of Medicine, St. Louis, MO 63110, USA.
⁸ Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
⁹ Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX 77030, USA.
¹⁰ Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
¹¹ Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA.
¹² Department of Medicine, New York University School of Medicine, New York, NY 10016, USA.
¹³ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
¹⁴ Departments of Medicine and Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
¹⁵ Department of Biochemistry and Cellular Biology, Georgetown University, Washington, DC 20007, USA.
¹⁶ Brady Urological Institute and Department of Urology, Johns Hopkins University, Baltimore, MD 21231, USA.
¹⁷ Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
¹⁸ Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
¹⁹ Department of Urology, Poznań University of Medical Sciences, Szwajcarska 3, Poznań 61-285, Poland.
²⁰ Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
²¹ Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
²² Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland.
²³ International Institute for Molecular Oncology, Poznań 60-203, Poland; Poznań University of Medical Sciences, Poznan 60-701, Poland.
²⁴ Office of Cancer Clinical Proteomics Research, National Cancer Institute, Bethesda, MD 20892, USA.
²⁵ Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
²⁶ Department of Ophthalmology, Johns Hopkins University, Baltimore, MD 21231, USA.
²⁷ Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
²⁸ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Sema4, Stamford, CT 06902, USA.
²⁹ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
³⁰ Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: mcieslik@med.mich.edu.
³¹ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA. Electronic address: dchan@jhmi.edu.
³² Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: nesvi@med.umich.edu.
³³ Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: pei.wang@mssm.edu.
³⁴ Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA. Electronic address: huizhang@jhu.edu.

PMID: 31675502
PMCID: PMC7331093
DOI: 10.1016/j.cell.2019.10.007

Erratum in

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.
Clark DJ, Dhanasekaran SM, Petralia F, Pan J, Song X, Hu Y, da Veiga Leprevost F, Reva B, Lih TM, Chang HY, Ma W, Huang C, Ricketts CJ, Chen L, Krek A, Li Y, Rykunov D, Li QK, Chen LS, Ozbek U, Vasaikar S, Wu Y, Yoo S, Chowdhury S, Wyczalkowski MA, Ji J, Schnaubelt M, Kong A, Sethuraman S, Avtonomov DM, Ao M, Colaprico A, Cao S, Cho KC, Kalayci S, Ma S, Liu W, Ruggles K, Calinawan A, Gümüş ZH, Geiszler D, Kawaler E, Teo GC, Wen B, Zhang Y, Keegan S, Li K, Chen F, Edwards N, Pierorazio PM, Chen XS, Pavlovich CP, Hakimi AA, Brominski G, Hsieh JJ, Antczak A, Omelchenko T, Lubinski J, Wiznerowicz M, Linehan WM, Kinsinger CR, Thiagarajan M, Boja ES, Mesri M, Hiltke T, Robles AI, Rodriguez H, Qian J, Fenyö D, Zhang B, Ding L, Schadt E, Chinnaiyan AM, Zhang Z, Omenn GS, Cieslik M, Chan DW, Nesvizhskii AI, Wang P, Zhang H; Clinical Proteomic Tumor Analysis Consortium. Clark DJ, et al. Cell. 2020 Jan 9;180(1):207. doi: 10.1016/j.cell.2019.12.026. Cell. 2020. PMID: 31923397 No abstract available.

Abstract

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Keywords: CPTAC; ccRCC; chromosomal translocation; drug targets; immune infiltration; phosphoproteomics; proteogenomics; proteomics; renal carcinoma; tumor microenvironment.

PubMed Disclaimer

Conflict of interest statement

DECLARATION OF INTERESTS

Dr. Eric Schadt serves as Chief Executive Officer for Sema4 and has an equity interest in this company.

Figures

**Figure 1.. Genomic Alterations and their Associations with mRNA, Protein, and Phosphoprotein Abundances**
(A) Profiling of absolute copy number estimates observed in the CPTAC cohort. Genomically defined non-ccRCC tumors are above ccRCC tumors; translocation event, grade, CpG island methylator phenotype (CIMP) status, genome instability, and CNV loss/gain are indicated by color coding. ccRCC tumors with evidence of 3p loss of heterozygosity (LOH) are indicated by three asterisks (***). (B) Circos plots of translocation events involving chromosomes 3 and either chromosomes 5 (red), 2 (blue), 8 (purple) or all other chromosomes (gray), including chromosomal inversion within chromosome 3 (green). Percentage of involved tumors with re-arrangement for each chromosome is annotated below each plot. (C) Heatmap of multi-omic data for the five key tumor suppressor genes (*VHL, PBRM1, BAP1, SETD2*, and *KDM5C*) (n = 103). Tumor samples were ordered by 3p CNV alteration (loss to neutral). Non-ccRCC tumors are separated (right). CNV event, Z score, CNV loss/gain, translocation status, CpG island methylator phenotype (CIMP) status, genome instability, grade, and gender are indicated by color coding (bottom). See also Figure S1 and Tables S1 and S2.

**Figure 2.. Impact of Copy Number Variation (CNV) on Protein Abundance**
(A) DNA variations (CNV baf, B-allele frequencies; CNV Ir, adjusted log coverage ratios; DNA methylation) with cascading *cis*-association (associations with all types of mRNA, global protein, and phosphopeptide abundances), overlapped with phosphopeptides significantly differentiated by clinical features (tumor versus NAT and tumor grade). Genes in bold are associated with CNV events involving chromosome 5 or 7 gain and 14 loss. (B) The *cis* and *trans* associations of chromosome arms (3p, 5q, 7p, 9p, and 14q) and CpG island methylator phenotype (CIMP). Significant (adjusted p < 0.1) positive (red) and negative (blue) associations for individual chromosomes (left), summed associations (middle), and corresponding enriched upregulated (red) and downregulated (blue) pathways (adjusted p < 0.05) are annotated (right). See also Figure S2 and Table S3.

**Figure 3.. Correlations between Transcriptomic and Proteomic Abundance**
(A) Gene-wise correlations of mRNA and protein expression in tumors (left) and NATs (right). Annotated cellular pathways and corresponding Spearman gene-wise correlation (bottom). (B) Sample-wise correlation of tumors ranked from high to low with corresponding NAT sample-wise correlation (top). Tumors were evenly distributed into three groups: high (blue), middle (gray), and low (gold). BAP1 mutation, chromosome 14 loss status, and tumor grade are annotated (bottom). (C) Boxplots of ribosome and translation factor gene expression and Pol I-associated regulation in tumor samples (left) and corresponding NATs (right) (*p < 0.05). Figure S3 and Tables S1 and S4.

**Figure 4.. Differential Expression of Transcriptomic and Proteomic Profiles between ccRCC Tumors and NAT Protein Expression**
(A) PCA visualization of protein expression in ccRCC tumors and NATs. (B) Analysis of significantly differentially regulated pathways (adjusted p < 0.05) between ccRCC tumors and NATs. (C) Schema of metabolic pathways (glycolysis and electron transport chain [OXPHOS]) with select differential gene expression of mRNA and protein levels between ccRCC tumors and NATs. (D) Scatterplots depicting expression of mRNA (x axis) and protein (y axis). Linear regression of all mRNA-protein pairs (gray dotted line) and OXPHOS mRNA-gene pairs (red dotted line) are shown. Metabolism-related genes are indicated. (E) Boxplot of representative OXPHOS genes from complex I (*NDUFV2*), IV (*COX6C*), and V (*ATP6V1F*) displaying discordant mRNA-protein expression (n.s., not significant, *adjusted p < 0.05). See also Figure S4 and Tables S1, S4, and S5.

**Figure 5.. Phospho-Substrates with Associated Kinases and a Network Module Specific to Phospho-Tumor Data**
(A) Ranked phospho-substrate events of kinases with inhibitors and fold-change at global- and phospho-levels for kinases and substrates, respectively. (B) Pathways based on the selected phospho-substrates and kinases, with relevant drugs shown by targets (red). Current FDA-approved drugs for ccRCC (gray). (C) Pairwise correlation of nodes at multi-omics levels of “cell cycle” co-expression network module. (D) Heatmap of “cell cycle” module expression with grade, BAP1 and chromosome 14 loss, and genome instability distribution annotated. See also Figure S5 and Tables S1 and S6.

**Figure 6.. Immune-Based Subtyping of ccRCC Tumors**
(A) Transcriptome-based deconvolution of mRNA transcript cell signatures in 103 ccRCC tumors and 72 NATs using xCell. (B) Molecular characteristics (transcriptomic, proteomic) stratified tumors into four immune subtypes: CD8⁺ inflamed (red), CD8⁻ inflamed (blue), VEGF immune desert (yellow), metabolic immune desert (green), and NATs into two subtypes (pink and gray). (C) Proportion of *BAP1* mutation, *PBRM1* mutation, chromosome 14 loss, and chromosome 7 gains within each of the immune groups. (D) Proportion of high tumor grade tumors (i.e., grade 3 and grade 4) in each of the immune groups for CPTAC and TCGA datasets. High-grade tumors were significantly enriched in CD8⁺ inflamed group compared to VEGF immune desert group. (E) Density contours of immune and stroma scores of each immune subtype. Pathways upregulated based on RNA-seq and global proteomics data are labeled with “R” or “P,” respectively. See also Figure S6 and Tables S1 and S7.

**Figure 7.. Proteomic Inter-Tumor Heterogeneity of ccRCC and Associated Functional Pathways**
(A) Cellular pathways (right) with positive (red) or negative (blue) associations with grade (adjusted p < 0.05) at protein or mRNA level (left). Heatmap of protein expression associated with high- and low-grade tumors (center) (Benjamini-Hochberg adjusted p < 0.05). (B) Heatmap of global proteomic abundances. For subtype identification, protein features (n = 3,567) were selected based on highest variance. Color indicates Z score of protein in each sample: red is increased, blue is decreased. Clinical and molecular features are indicated above the heatmap. Cluster-derived modules are annotated according to pathway enrichment using Hallmark Gene signature, REACTOME, and KEGG ontologies (adjusted p < 0.05). See also Figure S7 and Tables S1 and S5.

See this image and copyright information in PMC

Comment in

Proteomic signatures of clear cell renal cell carcinoma.
Creighton CJ. Creighton CJ. Nat Rev Nephrol. 2020 Mar;16(3):133-134. doi: 10.1038/s41581-019-0233-5. Nat Rev Nephrol. 2020. PMID: 31780818 No abstract available.

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Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

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Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

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