Comparison of gene expression patterns across twelve tumor types identifies a cancer supercluster characterized by TP53 mutations and cell cycle defects

Transcriptional profile-based subtypes of cancer are often viewed as identifying different diseases from the same tissue origin. Understanding the mechanisms driving the subtypes may be key in development of novel therapeutics but is challenged by lineage-specific expression signals. Using a t-test statistics approach, we compared gene expression subtypes across 12 tumor types, which identified eight transcriptional superclusters characterized by commonly activated disease pathways and similarities in gene expression. One of the largest superclusters was determined by the upregulation of a proliferation signature, significant enrichment in TP53 mutations, genomic loss of CDKN2A (p16ARF), evidence of increased numbers of DNA double strand breaks and high expression of cyclin B1 protein. These correlations suggested that abrogation of the P53-mediated apoptosis response to DNA damage results in activation of cell cycle pathways and represents a common theme in cancer. A second consistent pattern, observed in 9 of 11 solid tumor types, was a subtype related to an activated tumor-associated stroma. The similarity in transcriptional footprints across cancers suggested that tumor subtypes are commonly unified by a limited number of molecular themes.

[1]  The Cancer Genome Atlas Research Network,et al.  Comprehensive molecular characterization of urothelial bladder carcinoma , 2014, Nature.

[2]  R. Tibshirani,et al.  Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Susumu Goto,et al.  Data, information, knowledge and principle: back to metabolism in KEGG , 2013, Nucleic Acids Res..

[4]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of human colon and rectal cancer , 2012, Nature.

[5]  Bas J. Wouters,et al.  Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling , 2009, Haematologica.

[6]  K. Cibulskis,et al.  Prognostically relevant gene signatures of high-grade serous ovarian carcinoma. , 2012, The Journal of clinical investigation.

[7]  Chris Sander,et al.  Emerging landscape of oncogenic signatures across human cancers , 2013, Nature Genetics.

[8]  Christopher R. Cabanski,et al.  Molecular Subtypes in Head and Neck Cancer Exhibit Distinct Patterns of Chromosomal Gain and Loss of Canonical Cancer Genes , 2013, PloS one.

[9]  B. Everitt,et al.  Cluster Analysis: Everitt/Cluster Analysis , 2011 .

[10]  C. Horak,et al.  Nivolumab plus ipilimumab in advanced melanoma. , 2013, The New England journal of medicine.

[11]  A. McKenna,et al.  Absolute quantification of somatic DNA alterations in human cancer , 2012, Nature Biotechnology.

[12]  Kenneth H. Buetow,et al.  PID: the Pathway Interaction Database , 2008, Nucleic Acids Res..

[13]  Aleix Prat Aparicio Comprehensive molecular portraits of human breast tumours , 2012 .

[14]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[15]  Adam A. Margolin,et al.  The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity , 2012, Nature.

[16]  Ben S. Wittner,et al.  Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 , 2009, Nature.

[17]  Yudong D. He,et al.  A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .

[18]  The Cancer Genome Atlas Research Network COMPREHENSIVE MOLECULAR CHARACTERIZATION OF CLEAR CELL RENAL CELL CARCINOMA , 2013, Nature.

[19]  David C. Smith,et al.  Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. , 2012, The New England journal of medicine.

[20]  G. Getz,et al.  Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.

[21]  Benjamin J. Raphael,et al.  Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. , 2013, The New England journal of medicine.

[22]  D. Schadendorf,et al.  Improved survival with ipilimumab in patients with metastatic melanoma. , 2010, The New England journal of medicine.

[23]  Pablo Tamayo,et al.  Metagenes and molecular pattern discovery using matrix factorization , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Henning Hermjakob,et al.  The Reactome pathway Knowledgebase , 2015, Nucleic acids research.

[25]  S. Gabriel,et al.  Pan-cancer patterns of somatic copy-number alteration , 2013, Nature Genetics.

[26]  B. Rosner Percentage Points for a Generalized ESD Many-Outlier Procedure , 1983 .

[27]  Yuan Qi,et al.  Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA , IDH 1 , EGFR , and NF 1 Citation Verhaak , 2010 .

[28]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[29]  D. Haussler,et al.  The Somatic Genomic Landscape of Glioblastoma , 2013, Cell.

[30]  S. Gabriel,et al.  Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. , 2010, Cancer cell.

[31]  S. Reed,et al.  Cyclin-Dependent Kinase-Associated Proteins Cks1 and Cks2 Are Essential during Early Embryogenesis and for Cell Cycle Progression in Somatic Cells , 2008, Molecular and Cellular Biology.

[32]  Nader Sanai,et al.  Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma. , 2010, World neurosurgery.

[33]  Steven J. M. Jones,et al.  Integrated genomic characterization of endometrial carcinoma , 2013, Nature.

[34]  Bin Fang,et al.  Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms , 2013, Molecular systems biology.

[35]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[36]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[37]  Joshua M. Korn,et al.  Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2008, Nature.

[38]  William Stafford Noble,et al.  Support vector machine , 2013 .

[39]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of clear cell renal cell carcinoma , 2013, Nature.

[40]  Joshua M. Stuart,et al.  Subtype and pathway specific responses to anticancer compounds in breast cancer , 2011, Proceedings of the National Academy of Sciences.

[41]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of urothelial bladder carcinoma , 2014, Nature.

[42]  Ken Chen,et al.  A survey of intragenic breakpoints in glioblastoma identifies a distinct subset associated with poor survival. , 2013, Genes & development.

[43]  Brian Everitt,et al.  Cluster analysis , 1974 .

[44]  Steven J. M. Jones,et al.  Comprehensive genomic characterization of squamous cell lung cancers , 2012, Nature.

[45]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Tony Pawson,et al.  Temporal regulation of EGF signaling networks by the scaffold protein Shc1 , 2013, Nature.

[47]  E. Lander,et al.  Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[48]  A. Nobel,et al.  Supervised risk predictor of breast cancer based on intrinsic subtypes. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[49]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[50]  Antoni Ribas,et al.  Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. , 2013, The New England journal of medicine.

[51]  R. Verhaak,et al.  Prognostically useful gene-expression profiles in acute myeloid leukemia. , 2004, The New England journal of medicine.

[52]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumours , 2013 .

[53]  David Haussler,et al.  Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM , 2010, Bioinform..