Discovery of cancer common and specific driver gene sets

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found.

[1]  C. Yeang,et al.  Combinatorial patterns of somatic gene mutations in cancer , 2008, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[2]  Christoph Schmid,et al.  Molecular subtypes of NPM1 mutations have different clinical profiles, specific patterns of accompanying molecular mutations and varying outcomes in intermediate risk acute myeloid leukemia , 2016, Haematologica.

[3]  Muhammad Mustafa,et al.  CTCF negatively regulates HOXA10 expression in breast cancer cells. , 2015, Biochemical and biophysical research communications.

[4]  E. Birney,et al.  Patterns of somatic mutation in human cancer genomes , 2007, Nature.

[5]  Shihua Zhang,et al.  Toward a systematic understanding of cancers: a survey of the pan-cancer study , 2014, Front. Genet..

[6]  Marcel J. T. Reinders,et al.  Identification of Networks of Co-Occurring, Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach , 2010, PLoS Comput. Biol..

[7]  Giovanni Parmigiani,et al.  Patient-oriented gene set analysis for cancer mutation data , 2010, Genome Biology.

[8]  Daniel J Weisdorf,et al.  Acute Myeloid Leukemia. , 2015, The New England journal of medicine.

[9]  Adam J Mead,et al.  The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. , 2008, Blood.

[10]  Caroline Dive,et al.  Inhibition of FGFR2 and FGFR1 increases cisplatin sensitivity in ovarian cancer , 2010, Cancer biology & therapy.

[11]  Benjamin J. Raphael,et al.  Pan-Cancer Network Analysis Identifies Combinations of Rare Somatic Mutations across Pathways and Protein Complexes , 2014, Nature Genetics.

[12]  M. Roizen,et al.  Hallmarks of Cancer: The Next Generation , 2012 .

[13]  Shivendra V. Singh,et al.  Notch2 activation is protective against anticancer effects of zerumbone in human breast cancer cells , 2014, Breast Cancer Research and Treatment.

[14]  G. Parmigiani,et al.  Core Signaling Pathways in Human Pancreatic Cancers Revealed by Global Genomic Analyses , 2008, Science.

[15]  Simo V. Zhang,et al.  A map of human cancer signaling , 2007, Molecular systems biology.

[16]  Y. Kim,et al.  Identification of differentially expressed genes using an annealing control primer system in stage III serous ovarian carcinoma , 2010, BMC Cancer.

[17]  K. Sandvig,et al.  Regulation of ErbB2 localization and function in breast cancer cells by ERM proteins , 2016, Oncotarget.

[18]  D. Hanahan,et al.  The Hallmarks of Cancer , 2000, Cell.

[19]  Shihua Zhang,et al.  Tumor characterization and stratification by integrated molecular profiles reveals essential pan-cancer features , 2015, BMC Genomics.

[20]  Henry W. Long,et al.  Somatic Cell Fusions Reveal Extensive Heterogeneity in Basal-like Breast Cancer. , 2015, Cell reports.

[21]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[22]  Shi-Hua Zhang,et al.  Efficient methods for identifying mutated driver pathways in cancer , 2012, Bioinform..

[23]  M. Hottiger,et al.  Transcription coactivator p300 binds PCNA and may have a role in DNA repair synthesis , 2001, Nature.

[24]  J. Kostic,et al.  Parallel targeted next generation sequencing of childhood and adult acute myeloid leukemia patients reveals uniform genomic profile of the disease , 2016, Tumor Biology.

[25]  Niko Beerenwinkel,et al.  Modeling Mutual Exclusivity of Cancer Mutations , 2014, RECOMB.

[26]  É. Remy,et al.  A Modeling Approach to Explain Mutually Exclusive and Co-Occurring Genetic Alterations in Bladder Tumorigenesis. , 2015, Cancer research.

[27]  K. Tewari,et al.  A review of HER2-targeted therapy in breast and ovarian cancer: lessons from antiquity - CLEOPATRA and PENELOPE. , 2015, Future oncology.

[28]  Andrew M. Gross,et al.  Network-based stratification of tumor mutations , 2013, Nature Methods.

[29]  P. Laird,et al.  Discovery of multi-dimensional modules by integrative analysis of cancer genomic data , 2012, Nucleic acids research.

[30]  Shi-Hua Zhang,et al.  Discovery of co-occurring driver pathways in cancer , 2014, BMC Bioinformatics.

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

[32]  Teresa M. Przytycka,et al.  MEMCover: integrated analysis of mutual exclusivity and functional network reveals dysregulated pathways across multiple cancer types , 2015, Bioinform..

[33]  B. Ponder,et al.  FGFR2 risk SNPs confer breast cancer risk by augmenting oestrogen responsiveness , 2016, Carcinogenesis.

[34]  Yan Zhang,et al.  Comparative serum proteome analysis of human lymph node negative/positive invasive ductal carcinoma of the breast and benign breast disease controls via label-free semiquantitative shotgun technology. , 2009, Omics : a journal of integrative biology.

[35]  A. Cimino-Mathews,et al.  The role of GATA3 in breast carcinomas: a review. , 2016, Human pathology.

[36]  P. Ding,et al.  Clinicopathological significance and potential drug target of CDH1 in breast cancer: a meta-analysis and literature review , 2015, Drug design, development and therapy.

[37]  K. Kinzler,et al.  Cancer genes and the pathways they control , 2004, Nature Medicine.

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

[39]  Ki-Chun Yoo,et al.  Radiation driven epithelial-mesenchymal transition is mediated by Notch signaling in breast cancer , 2016, Oncotarget.

[40]  Gary D Bader,et al.  International network of cancer genome projects , 2010, Nature.

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

[42]  H. Cai,et al.  Roles of LPA receptor signaling in breast cancer , 2016, Expert review of molecular diagnostics.

[43]  C. Sander,et al.  Mutual exclusivity analysis identifies oncogenic network modules. , 2012, Genome research.

[44]  Roded Sharan,et al.  Simultaneous Identification of Multiple Driver Pathways in Cancer , 2013, PLoS Comput. Biol..

[45]  A. Ziogas,et al.  Novel polymorphisms in caspase-8 are associated with breast cancer risk in the California Teachers Study , 2016, BMC Cancer.

[46]  C. Cui,et al.  GNAQ and GNA11 mutations occur in 9.5% of mucosal melanoma and are associated with poor prognosis. , 2016, European journal of cancer.

[47]  P. Elizalde,et al.  ErbB-2 nuclear function in breast cancer growth, metastasis and resistance to therapy. , 2016, Endocrine-related cancer.

[48]  E. Birney,et al.  Patterns of somatic mutation in human cancer genomes , 2007, Nature.

[49]  E. Lander,et al.  Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma , 2007, Proceedings of the National Academy of Sciences.

[50]  Junhua Zhang,et al.  The Discovery of Mutated Driver Pathways in Cancer: Models and Algorithms , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[51]  G. Hardiman,et al.  Amplification of WHSC1L1 regulates expression and estrogen‐independent activation of ERα in SUM‐44 breast cancer cells and is associated with ERα over‐expression in breast cancer , 2016, Molecular oncology.

[52]  Sharon I. Greenblum,et al.  Detecting Cancer Gene Networks Characterized by Recurrent Genomic Alterations in a Population , 2011, PloS one.

[53]  Adam A. Margolin,et al.  Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity , 2018, Nature.

[54]  Nicolò Riggi,et al.  Comprehensive Genetic Landscape of Uveal Melanoma by Whole-Genome Sequencing. , 2016, American journal of human genetics.

[55]  Christopher A. Miller,et al.  Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors , 2011, BMC Medical Genomics.

[56]  Brian H. Dunford-Shore,et al.  Somatic mutations affect key pathways in lung adenocarcinoma , 2008, Nature.

[57]  Tzu-Pin Lu,et al.  Prognostic significance of NPM1 mutation-modulated microRNA−mRNA regulation in acute myeloid leukemia , 2016, Leukemia.

[58]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[59]  Raul Rabadan,et al.  An information theoretic method to identify combinations of genomic alterations that promote glioblastoma. , 2015, Journal of molecular cell biology.

[60]  Eli Upfal,et al.  De Novo Discovery of Mutated Driver Pathways in Cancer , 2011, RECOMB.

[61]  M. Stratton,et al.  The cancer genome , 2009, Nature.

[62]  C. Annunziata,et al.  Caspase 8 expression may determine the survival of women with ovarian cancer , 2016, Cell Death and Disease.

[63]  Benjamin J. Raphael,et al.  Mutational landscape and significance across 12 major cancer types , 2013, Nature.

[64]  Y. Hamamoto,et al.  Phase I trial of sorafenib in combination with interferon-alpha in Japanese patients with unresectable or metastatic renal cell carcinoma , 2009, Investigational new drugs.

[65]  Shi-Hua Zhang,et al.  Identification of mutated core cancer modules by integrating somatic mutation, copy number variation, and gene expression data , 2013, BMC Systems Biology.

[66]  W. Hogan,et al.  Prognostic impact of combined NPM1+/FLT3- genotype in patients with acute myeloid leukemia with intermediate risk cytogenetics stratified by age and treatment modalities. , 2015, Leukemia research.

[67]  J. Vince,et al.  New insights into the regulation of innate immunity by caspase-8 , 2016, Arthritis Research & Therapy.

[68]  B. Dołęgowska,et al.  Lysophosphatidic acid signaling in ovarian cancer , 2015, Journal of receptor and signal transduction research.