Skip to main content
Top
Published in: Journal of Experimental & Clinical Cancer Research 1/2017

Open Access 01-12-2017 | Research

Identification and validation of a 44-gene expression signature for the classification of renal cell carcinomas

Authors: Qifeng Wang, Hualei Gan, Chengshu Chen, Yifeng Sun, Jinying Chen, Midie Xu, Weiwei Weng, Liyu Cao, Qinghua Xu, Jian Wang

Published in: Journal of Experimental & Clinical Cancer Research | Issue 1/2017

Login to get access

Abstract

Background

Renal cancers account for more than 3% of all adult malignancies and cause more than 23,400 deaths per year in China alone. The four most common types of kidney tumours include clear cell, papillary, chromophobe and benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. Some kidney tumours can be very difficult to distinguish based on the pathological assessment of morphology and immunohistochemistry.

Methods

Six renal cell carcinoma microarray data sets, including 106 clear cell, 66 papillary, 42 chromophobe, 46 oncocytoma and 35 adjacent normal tissue samples, were subjected to integrative analysis. These data were combined and used as a training set for candidate gene expression signature identification. In addition, two independent cohorts of 1020 RNA-Seq samples from The Cancer Genome Atlas database and 129 qRT-PCR samples from Fudan University Shanghai Cancer Center (FUSCC) were analysed to validate the selected gene expression signature.

Results

A 44-gene expression signature derived from microarray analysis was strongly associated with the histological differentiation of renal tumours and could be used for tumour subtype classification. The signature performance was further validated in 1020 RNA-Seq samples and 129 qRT-PCR samples with overall accuracies of 93.4 and 93.0%, respectively.

Conclusions

A 44-gene expression signature that could accurately discriminate renal tumour subtypes was identified in this study. Our results may prompt further development of this gene expression signature into a molecular assay amenable to routine clinical practice.
Literature
1.
go back to reference Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–32.CrossRefPubMed Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–32.CrossRefPubMed
2.
go back to reference Bray F, Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2014;136:E359–86.PubMed Bray F, Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2014;136:E359–86.PubMed
3.
go back to reference Pang C, Guan Y, Li H, Chen W, Zhu G. Urologic cancer in China. Jpn J Clin Oncol. 2016;46:497–501.CrossRefPubMed Pang C, Guan Y, Li H, Chen W, Zhu G. Urologic cancer in China. Jpn J Clin Oncol. 2016;46:497–501.CrossRefPubMed
4.
go back to reference Moch H, Cubilla AL, Humphrey PA, Reuter VE, Ulbright TM. The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs—Part A: Renal, Penile, and Testicular Tumours. European Urology. 2016;70:93–105. Moch H, Cubilla AL, Humphrey PA, Reuter VE, Ulbright TM. The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs—Part A: Renal, Penile, and Testicular Tumours. European Urology. 2016;70:93–105.
5.
go back to reference Tilki D, Nguyen HG, Dall'Era MA, Bertini R, Carballido JA, Chromecki T, Ciancio G, Daneshmand S, Gontero P, Gonzalez J, Haferkamp A, Hohenfellner M, Huang WC, Koppie TM, Lorentz CA, Mandel P, Martinez-Salamanca JI, Master VA, Matloob R, JM MK, Mlynarczyk CM, Montorsi F, Novara G, Pahernik S, Palou J, Pruthi RS, Ramaswamy K, Rodriguez Faba O, Russo P, Shariat SF, et al. Impact of histologic subtype on cancer-specific survival in patients with renal cell carcinoma and tumor thrombus. Eur Urol. 2014;66:577–83.CrossRefPubMed Tilki D, Nguyen HG, Dall'Era MA, Bertini R, Carballido JA, Chromecki T, Ciancio G, Daneshmand S, Gontero P, Gonzalez J, Haferkamp A, Hohenfellner M, Huang WC, Koppie TM, Lorentz CA, Mandel P, Martinez-Salamanca JI, Master VA, Matloob R, JM MK, Mlynarczyk CM, Montorsi F, Novara G, Pahernik S, Palou J, Pruthi RS, Ramaswamy K, Rodriguez Faba O, Russo P, Shariat SF, et al. Impact of histologic subtype on cancer-specific survival in patients with renal cell carcinoma and tumor thrombus. Eur Urol. 2014;66:577–83.CrossRefPubMed
6.
go back to reference Posadas EM, Limvorasak S, Figlin RA. Targeted therapies for renal cell carcinoma. Nat Rev Nephrol. 2017;13:496–511.CrossRefPubMed Posadas EM, Limvorasak S, Figlin RA. Targeted therapies for renal cell carcinoma. Nat Rev Nephrol. 2017;13:496–511.CrossRefPubMed
7.
go back to reference Schuetz AN, Yin-Goen Q, Amin MB, Moreno CS, Cohen C, Hornsby CD, Yang WL, Petros JA, Issa MM, Pattaras JG, Ogan K, Marshall FF, Young AN. Molecular classification of renal tumors by gene expression profiling. J Mol Diagn. 2005;7:206–18.CrossRefPubMedPubMedCentral Schuetz AN, Yin-Goen Q, Amin MB, Moreno CS, Cohen C, Hornsby CD, Yang WL, Petros JA, Issa MM, Pattaras JG, Ogan K, Marshall FF, Young AN. Molecular classification of renal tumors by gene expression profiling. J Mol Diagn. 2005;7:206–18.CrossRefPubMedPubMedCentral
8.
go back to reference Lawson D, Young AN, Cohen C, Hornsby CD, Picken MM, Amin MB, Yin-Goen Q. Claudin-7 immunohistochemistry in renal tumors: a candidate marker for chromophobe renal cell carcinoma identified by gene expression profiling. Arch Pathol Lab Med. 2007;131:1541–6.PubMed Lawson D, Young AN, Cohen C, Hornsby CD, Picken MM, Amin MB, Yin-Goen Q. Claudin-7 immunohistochemistry in renal tumors: a candidate marker for chromophobe renal cell carcinoma identified by gene expression profiling. Arch Pathol Lab Med. 2007;131:1541–6.PubMed
9.
go back to reference Osunkoya AO, Cohen C, Lawson D, Picken MM, Amin MB, Young AN. Claudin-7 and claudin-8: immunohistochemical markers for the differential diagnosis of chromophobe renal cell carcinoma and renal oncocytoma. Hum Pathol. 2009;40:206–10.CrossRefPubMed Osunkoya AO, Cohen C, Lawson D, Picken MM, Amin MB, Young AN. Claudin-7 and claudin-8: immunohistochemical markers for the differential diagnosis of chromophobe renal cell carcinoma and renal oncocytoma. Hum Pathol. 2009;40:206–10.CrossRefPubMed
10.
go back to reference Chen YT, Tu JJ, Kao J, Zhou XK, Mazumdar M. Messenger RNA expression ratios among four genes predict subtypes of renal cell carcinoma and distinguish oncocytoma from carcinoma. Clin Cancer Res. 2005;11:6558–66.CrossRefPubMed Chen YT, Tu JJ, Kao J, Zhou XK, Mazumdar M. Messenger RNA expression ratios among four genes predict subtypes of renal cell carcinoma and distinguish oncocytoma from carcinoma. Clin Cancer Res. 2005;11:6558–66.CrossRefPubMed
11.
go back to reference Youssef YM, NMA W, Grigull J, Krizova A, Samy C, Mejia-Guerrero S, Evans A, Yousef GM. Accurate molecular classification of kidney cancer subtypes using microRNA signature. Eur Urol. 2011;59:721–30.CrossRefPubMed Youssef YM, NMA W, Grigull J, Krizova A, Samy C, Mejia-Guerrero S, Evans A, Yousef GM. Accurate molecular classification of kidney cancer subtypes using microRNA signature. Eur Urol. 2011;59:721–30.CrossRefPubMed
12.
go back to reference Jones J, Jones J, Otu H, Spentzos D, Kolia S, Inan M, Beecken WD, Fellbaum C, Gu X, Joseph M, Pantuck AJ, Jonas D, Libermann TA. Gene signatures of progression and metastasis in renal cell cancer. Clin Cancer Res. 2005;11:5730–9.CrossRefPubMed Jones J, Jones J, Otu H, Spentzos D, Kolia S, Inan M, Beecken WD, Fellbaum C, Gu X, Joseph M, Pantuck AJ, Jonas D, Libermann TA. Gene signatures of progression and metastasis in renal cell cancer. Clin Cancer Res. 2005;11:5730–9.CrossRefPubMed
13.
go back to reference Beleut M, Zimmermann P, Baudis M, Bruni N, Bühlmann P, Laule O, Luu V-D, Gruissem W, Schraml P, Moch H. Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome. BMC Cancer. 2012;12:310.CrossRefPubMedPubMedCentral Beleut M, Zimmermann P, Baudis M, Bruni N, Bühlmann P, Laule O, Luu V-D, Gruissem W, Schraml P, Moch H. Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome. BMC Cancer. 2012;12:310.CrossRefPubMedPubMedCentral
14.
go back to reference Furge KA, Chen J, Koeman J, Swiatek P, Dykema K, Lucin K, Kahnoski R, Yang XJ, Teh BT. Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma. Cancer Res. 2007;67:3171–6.CrossRefPubMed Furge KA, Chen J, Koeman J, Swiatek P, Dykema K, Lucin K, Kahnoski R, Yang XJ, Teh BT. Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma. Cancer Res. 2007;67:3171–6.CrossRefPubMed
15.
go back to reference Tan M-H, Wong CF, Tan HL, Yang XJ, Ditlev J, Matsuda D, Khoo SK, Sugimura J, Fujioka T, Furge KA, Kort E, Giraud S, Ferlicot S, Vielh P, Amsellem-Ouazana D, Debré B, Flam T, Thiounn N, Zerbib M, Benoît G, Droupy S, Molinié V, Vieillefond A, Tan PH, Richard S, Teh BT. Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma. BMC Cancer. 2010;10:196.CrossRefPubMedPubMedCentral Tan M-H, Wong CF, Tan HL, Yang XJ, Ditlev J, Matsuda D, Khoo SK, Sugimura J, Fujioka T, Furge KA, Kort E, Giraud S, Ferlicot S, Vielh P, Amsellem-Ouazana D, Debré B, Flam T, Thiounn N, Zerbib M, Benoît G, Droupy S, Molinié V, Vieillefond A, Tan PH, Richard S, Teh BT. Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma. BMC Cancer. 2010;10:196.CrossRefPubMedPubMedCentral
16.
go back to reference Gao J, Gao J, Aksoy BA, Aksoy BA, Dogrusoz U, Dogrusoz U, Dresdner G, Dresdner G, Gross B, Gross B, Sumer SO, Sumer SO, Sun Y, Sun Y, Jacobsen A, Jacobsen A, Sinha R, Sinha R, Larsson E, Larsson E, Cerami E, Cerami E, Sander C, Sander C, Schultz N, Schultz N. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6:pl1.CrossRefPubMedPubMedCentral Gao J, Gao J, Aksoy BA, Aksoy BA, Dogrusoz U, Dogrusoz U, Dresdner G, Dresdner G, Gross B, Gross B, Sumer SO, Sumer SO, Sun Y, Sun Y, Jacobsen A, Jacobsen A, Sinha R, Sinha R, Larsson E, Larsson E, Cerami E, Cerami E, Sander C, Sander C, Schultz N, Schultz N. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6:pl1.CrossRefPubMedPubMedCentral
17.
go back to reference Chang C-C, Lin C-J. LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol. 2011;2:1–27.CrossRef Chang C-C, Lin C-J. LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol. 2011;2:1–27.CrossRef
18.
go back to reference Ihaka R, Gentleman R. R: a language for data analysis and graphics. arXiv. 1996;5:299–314. Ihaka R, Gentleman R. R: a language for data analysis and graphics. arXiv. 1996;5:299–314.
19.
go back to reference Reimers M, Carey VJ. Bioconductor: an open source framework for bioinformatics and computational biology. Meth Enzymol. 2006;411:119–34.CrossRefPubMed Reimers M, Carey VJ. Bioconductor: an open source framework for bioinformatics and computational biology. Meth Enzymol. 2006;411:119–34.CrossRefPubMed
20.
go back to reference Piccolo SR, Withers MR, Francis OE, Bild AH, Johnson WE. Multiplatform single-sample estimates of transcriptional activation. Proc Natl Acad Sci U S A. 2013;110:17778–83.CrossRefPubMedPubMedCentral Piccolo SR, Withers MR, Francis OE, Bild AH, Johnson WE. Multiplatform single-sample estimates of transcriptional activation. Proc Natl Acad Sci U S A. 2013;110:17778–83.CrossRefPubMedPubMedCentral
21.
go back to reference Piccolo SR, Sun Y, Campbell JD, Lenburg ME, Bild AH, Johnson WE. A single-sample microarray normalization method to facilitate personalized-medicine workflows. Genomics. 2012;100:337–44.CrossRefPubMedPubMedCentral Piccolo SR, Sun Y, Campbell JD, Lenburg ME, Bild AH, Johnson WE. A single-sample microarray normalization method to facilitate personalized-medicine workflows. Genomics. 2012;100:337–44.CrossRefPubMedPubMedCentral
22.
go back to reference Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, Watson SJ, Meng F. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res. 2005;33:e175.CrossRefPubMedPubMedCentral Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, Watson SJ, Meng F. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res. 2005;33:e175.CrossRefPubMedPubMedCentral
23.
go back to reference Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8:118–27.CrossRefPubMed Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8:118–27.CrossRefPubMed
24.
go back to reference Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. arXiv. 2002;46:389–422. Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. arXiv. 2002;46:389–422.
25.
go back to reference Sulakhe D, Balasubramanian S, Xie B, Feng B, Taylor A, Wang S, Berrocal E, Dave U, Xu J, Börnigen D, Gilliam TC, Maltsev N. Lynx: a database and knowledge extraction engine for integrative medicine. Nucleic Acids Res. 2014;42(Database issue):D1007–12.CrossRefPubMed Sulakhe D, Balasubramanian S, Xie B, Feng B, Taylor A, Wang S, Berrocal E, Dave U, Xu J, Börnigen D, Gilliam TC, Maltsev N. Lynx: a database and knowledge extraction engine for integrative medicine. Nucleic Acids Res. 2014;42(Database issue):D1007–12.CrossRefPubMed
26.
go back to reference Xia J, Benner MJ, Hancock REW. NetworkAnalyst--integrative approaches for protein-protein interaction network analysis and visual exploration. Nucleic Acids Res. 2014;42(Web Server issue):W167–74.CrossRefPubMedPubMedCentral Xia J, Benner MJ, Hancock REW. NetworkAnalyst--integrative approaches for protein-protein interaction network analysis and visual exploration. Nucleic Acids Res. 2014;42(Web Server issue):W167–74.CrossRefPubMedPubMedCentral
27.
go back to reference Xia J, Gill EE, Hancock REW. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc. 2015;10:823–44.CrossRefPubMed Xia J, Gill EE, Hancock REW. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc. 2015;10:823–44.CrossRefPubMed
28.
go back to reference Breuer K, Foroushani AK, Laird MR, Chen C, Sribnaia A, Lo R, Winsor GL, Hancock REW, Brinkman FSL, Lynn DJ. InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation. Nucleic Acids Res. 2013;41(Database issue):D1228–33.CrossRefPubMed Breuer K, Foroushani AK, Laird MR, Chen C, Sribnaia A, Lo R, Winsor GL, Hancock REW, Brinkman FSL, Lynn DJ. InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation. Nucleic Acids Res. 2013;41(Database issue):D1228–33.CrossRefPubMed
29.
go back to reference Shioi K-I, Komiya A, Hattori K, Huang Y, Sano F, Murakami T, Nakaigawa N, Kishida T, Kubota Y, Nagashima Y, Yao M. Vascular cell adhesion molecule 1 predicts cancer-free survival in clear cell renal carcinoma patients. Clin Cancer Res. 2006;12:7339–46.CrossRefPubMed Shioi K-I, Komiya A, Hattori K, Huang Y, Sano F, Murakami T, Nakaigawa N, Kishida T, Kubota Y, Nagashima Y, Yao M. Vascular cell adhesion molecule 1 predicts cancer-free survival in clear cell renal carcinoma patients. Clin Cancer Res. 2006;12:7339–46.CrossRefPubMed
30.
go back to reference Kauffman EC, Barocas DA, Chen YT, Yang XJ, Scherr DS, Tu JJ. Differential expression of KAI1 metastasis suppressor protein in renal cell tumor histological subtypes. J Urol. 2009;181:2305–11.CrossRefPubMed Kauffman EC, Barocas DA, Chen YT, Yang XJ, Scherr DS, Tu JJ. Differential expression of KAI1 metastasis suppressor protein in renal cell tumor histological subtypes. J Urol. 2009;181:2305–11.CrossRefPubMed
31.
go back to reference Chuang S-T, Yang XJ, Chuang ST, Chu P, Chu P, Sugimura J, Sugimura J, Tretiakova MS, Tretiakova MS, Papavero V, Papavero V, Wang K, Wang K, Tan M, Tan MH, Lin F, Lin F, Teh BT, Teh BT, Yang XJ. Overexpression of glutathione S-Transferase a in clear cell renal cell carcinoma. Am J Clin Pathol. 2005;123:421–9.CrossRefPubMed Chuang S-T, Yang XJ, Chuang ST, Chu P, Chu P, Sugimura J, Sugimura J, Tretiakova MS, Tretiakova MS, Papavero V, Papavero V, Wang K, Wang K, Tan M, Tan MH, Lin F, Lin F, Teh BT, Teh BT, Yang XJ. Overexpression of glutathione S-Transferase a in clear cell renal cell carcinoma. Am J Clin Pathol. 2005;123:421–9.CrossRefPubMed
32.
go back to reference Lam JS, Leppert JT, Figlin RA, Belldegrun AS. Role of molecular markers in the diagnosis and therapy of renal cell carcinoma. Urology. 2005;66:1–9.CrossRefPubMed Lam JS, Leppert JT, Figlin RA, Belldegrun AS. Role of molecular markers in the diagnosis and therapy of renal cell carcinoma. Urology. 2005;66:1–9.CrossRefPubMed
33.
go back to reference Tan PH, Cheng L, Rioux-Leclercq N, Merino MJ, Netto G, Reuter VE, Shen SS, Grignon DJ, Montironi R, Egevad L, Srigley JR, Delahunt B, Moch H, ISUP Renal Tumor Panel. Renal tumors: diagnostic and prognostic biomarkers. Am J Surg Pathol. 2013;37:1518–31.CrossRefPubMedPubMedCentral Tan PH, Cheng L, Rioux-Leclercq N, Merino MJ, Netto G, Reuter VE, Shen SS, Grignon DJ, Montironi R, Egevad L, Srigley JR, Delahunt B, Moch H, ISUP Renal Tumor Panel. Renal tumors: diagnostic and prognostic biomarkers. Am J Surg Pathol. 2013;37:1518–31.CrossRefPubMedPubMedCentral
34.
go back to reference Spector Y, Fridman E, Rosenwald S, Zilber S, Huang Y, Barshack I, Zion O, Mitchell H, Sanden M, Meiri E. Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas. Mol Oncol. 2013;7:732–8.CrossRefPubMedPubMedCentral Spector Y, Fridman E, Rosenwald S, Zilber S, Huang Y, Barshack I, Zion O, Mitchell H, Sanden M, Meiri E. Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas. Mol Oncol. 2013;7:732–8.CrossRefPubMedPubMedCentral
35.
go back to reference Allory Y, Bazille C, Vieillefond A, Molinié V, Cochand-Priollet B, Cussenot O, Callard P, Sibony M. Profiling and classification tree applied to renal epithelial tumours. Histopathology. 2008;52:158–66.PubMed Allory Y, Bazille C, Vieillefond A, Molinié V, Cochand-Priollet B, Cussenot O, Callard P, Sibony M. Profiling and classification tree applied to renal epithelial tumours. Histopathology. 2008;52:158–66.PubMed
Metadata
Title
Identification and validation of a 44-gene expression signature for the classification of renal cell carcinomas
Authors
Qifeng Wang
Hualei Gan
Chengshu Chen
Yifeng Sun
Jinying Chen
Midie Xu
Weiwei Weng
Liyu Cao
Qinghua Xu
Jian Wang
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Journal of Experimental & Clinical Cancer Research / Issue 1/2017
Electronic ISSN: 1756-9966
DOI
https://doi.org/10.1186/s13046-017-0651-9

Other articles of this Issue 1/2017

Journal of Experimental & Clinical Cancer Research 1/2017 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine