DawnRank: discovering personalized driver genes in cancer

Large-scale cancer genomic studies have revealed that the genetic heterogeneity of the same type of cancer is greater than previously thought. A key question in cancer genomics is the identification of driver genes. Although existing methods have identified many common drivers, it remains challenging to predict personalized drivers to assess rare and even patient-specific mutations. We developed a new algorithm called DawnRank to directly prioritize altered genes on a single patient level. Applications to TCGA datasets demonstrated the effectiveness of our method. We believe DawnRank complements existing driver identification methods and will help us discover personalized causal mutations that would otherwise be obscured by tumor heterogeneity. Source code can be accessed at http://bioen-compbio.bioen.illinois.edu/DawnRank/.

[1]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[2]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[3]  L. Serrano,et al.  Engineering stability in gene networks by autoregulation , 2000, Nature.

[4]  Minoru Kanehisa,et al.  The KEGG database. , 2002, Novartis Foundation symposium.

[5]  W. Kolch,et al.  The role of MAPK pathways in the action of chemotherapeutic drugs. , 2002, Carcinogenesis.

[6]  Hao Wu,et al.  Distinct molecular mechanism for initiating TRAF6 signalling , 2002, Nature.

[7]  K. Honda,et al.  Integration of interferon-alpha/beta signalling to p53 responses in tumour suppression and antiviral defence. , 2003, Nature.

[8]  T. Hubbard,et al.  A census of human cancer genes , 2004, Nature Reviews Cancer.

[9]  A. Prescott,et al.  Structural insights into the regulation of PDK1 by phosphoinositides and inositol phosphates , 2004, The EMBO journal.

[10]  G. Dranoff,et al.  Cytokines in cancer pathogenesis and cancer therapy , 2004, Nature Reviews Cancer.

[11]  Desmond J. Higham,et al.  GeneRank: Using search engine technology for the analysis of microarray experiments , 2005, BMC Bioinformatics.

[12]  Wen-Lin Kuo,et al.  A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. , 2006, Cancer cell.

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

[14]  K. Wood,et al.  Centromere-Associated Protein E: A Motor That Puts the Brakes on the Mitotic Checkpoint , 2008, Clinical Cancer Research.

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

[16]  Susmita Datta,et al.  Finding common genes in multiple cancer types through meta-analysis of microarray experiments: a rank aggregation approach. , 2008, Genomics.

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

[18]  F. He,et al.  JAB1 accelerates mitochondrial apoptosis by interaction with proapoptotic BclGs. , 2008, Cellular signalling.

[19]  Azadeh Shakery,et al.  DirichletRank: Solving the zero-one gap problem of PageRank , 2008, TOIS.

[20]  Samuel Leung,et al.  Basal-Like Breast Cancer Defined by Five Biomarkers Has Superior Prognostic Value than Triple-Negative Phenotype , 2008, Clinical Cancer Research.

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

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

[23]  R. Leduc,et al.  Lysosomotropic drugs inhibit maturation of transforming growth factor-beta. , 2008, Canadian journal of physiology and pharmacology.

[24]  R. McLendon,et al.  Glioblastoma proto-oncogene SEC61gamma is required for tumor cell survival and response to endoplasmic reticulum stress. , 2009, Cancer research.

[25]  Pooja Mittal,et al.  A novel signaling pathway impact analysis , 2009, Bioinform..

[26]  J. Komorowski,et al.  Characterization of novel and complex genomic aberrations in glioblastoma using a 32K BAC array. , 2009, Neuro-oncology.

[27]  Leyla Isik,et al.  Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations. , 2009, Cancer research.

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

[29]  J. Uhm Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2009 .

[30]  Eugene A. Mash,et al.  Molecular Pharmacology and Antitumor Activity of PHT-427, a Novel Akt/Phosphatidylinositide-Dependent Protein Kinase 1 Pleckstrin Homology Domain Inhibitor , 2010, Molecular Cancer Therapeutics.

[31]  K. Kinzler,et al.  Genetic inactivation of AKT1, AKT2, and PDPK1 in human colorectal cancer cells clarifies their roles in tumor growth regulation , 2010, Proceedings of the National Academy of Sciences.

[32]  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.

[33]  E. Mardis,et al.  Analysis of next-generation genomic data in cancer: accomplishments and challenges. , 2010, Human molecular genetics.

[34]  Eli Upfal,et al.  Algorithms for Detecting Significantly Mutated Pathways in Cancer , 2010, RECOMB.

[35]  S. Steinberg,et al.  Nuclear factor κB transcription factors are coexpressed and convey a poor outcome in ovarian cancer , 2010, Cancer.

[36]  L. Stein,et al.  A human functional protein interaction network and its application to cancer data analysis , 2010, Genome Biology.

[37]  D. Pe’er,et al.  An Integrated Approach to Uncover Drivers of Cancer , 2010, Cell.

[38]  R. Hruban,et al.  Prioritization of driver mutations in pancreatic cancer using cancer-specific high-throughput annotation of somatic mutations (CHASM) , 2010, Cancer biology & therapy.

[39]  Genetic inactivation of AKT1, AKT2, and PDPK1 in human colorectal cancer cells clarifies their roles in tumor growth regulation (Proceedings of the National Academy of Sciences of the United States of America (2010) 107 (2598-2603) DOI: 10.1073/pnas.0914018107) , 2010 .

[40]  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 .

[41]  Signalling: The calcium connection , 2010, Nature Reviews Cancer.

[42]  C. Sander,et al.  Predicting the functional impact of protein mutations: application to cancer genomics , 2011, Nucleic acids research.

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

[44]  Yang Liu,et al.  Targeting HIF1α eliminates cancer stem cells in hematological malignancies. , 2011, Cell stem cell.

[45]  S. Davis,et al.  Exome sequencing identifies GRIN2A as frequently mutated in melanoma , 2011, Nature Genetics.

[46]  M. Guyer,et al.  Charting a course for genomic medicine from base pairs to bedside , 2011, Nature.

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

[48]  Eli Upfal,et al.  Algorithms for Detecting Significantly Mutated Pathways in Cancer , 2010, RECOMB.

[49]  D. Pe’er,et al.  Principles and Strategies for Developing Network Models in Cancer , 2011, Cell.

[50]  Renato V Iozzo,et al.  Proteoglycans in cancer biology, tumour microenvironment and angiogenesis , 2011, Journal of cellular and molecular medicine.

[51]  Ying Zheng,et al.  Therapeutic Potential of AZD1480 for the Treatment of Human Glioblastoma , 2011, Molecular Cancer Therapeutics.

[52]  K. Tachibana,et al.  FoxO3a Functions as a Key Integrator of Cellular Signals That Control Glioblastoma Stem‐like Cell Differentiation and Tumorigenicity , 2011, Stem cells.

[53]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[54]  Michael Schroeder,et al.  Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes , 2012, PLoS Comput. Biol..

[55]  A. Gonzalez-Perez,et al.  Functional impact bias reveals cancer drivers , 2012, Nucleic acids research.

[56]  Madhu Chetty,et al.  Issues impacting genetic network reverse engineering algorithm validation using small networks. , 2012, Biochimica et biophysica acta.

[57]  Scott M Lippman,et al.  Targeting the MAPK–RAS–RAF signaling pathway in cancer therapy , 2012, Expert opinion on therapeutic targets.

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

[59]  H. Ford,et al.  Molecular Pathways Molecular Pathways : Targeting the TGF-b Pathway for Cancer Therapy , 2012 .

[60]  Benjamin J. Raphael,et al.  De novo discovery of mutated driver pathways in cancer , 2011 .

[61]  F. Bertucci,et al.  A refined molecular taxonomy of breast cancer , 2011, Oncogene.

[62]  K. Watabe,et al.  WNT7A Regulates Tumor Growth and Progression in Ovarian Cancer through the WNT/β-Catenin Pathway , 2012, Molecular Cancer Research.

[63]  Matthew B. Callaway,et al.  MuSiC: Identifying mutational significance in cancer genomes , 2012, Genome research.

[64]  David Haussler,et al.  PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysis , 2012, Bioinform..

[65]  Susumu Goto,et al.  KEGG for integration and interpretation of large-scale molecular data sets , 2011, Nucleic Acids Res..

[66]  Matteo D'Antonio,et al.  Integrated analysis of recurrent properties of cancer genes to identify novel drivers , 2012, Genome Biology.

[67]  Peng Zhang,et al.  Tumor-Associated Microglia/Macrophages Enhance the Invasion of Glioma Stem-like Cells via TGF-β1 Signaling Pathway , 2012, The Journal of Immunology.

[68]  Nicholas T. Ingolia,et al.  The translational landscape of mTOR signalling steers cancer initiation and metastasis , 2012, Nature.

[69]  A. Bashashati,et al.  DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer , 2012, Genome Biology.

[70]  Todd R. Golub,et al.  PAK1 is a breast cancer oncogene that coordinately activates MAPK and MET signaling , 2011, Oncogene.

[71]  A. Sivachenko,et al.  Sequence analysis of mutations and translocations across breast cancer subtypes , 2012, Nature.

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

[73]  M. Stratton Journeys into the genome of cancer cells , 2013, EMBO molecular medicine.

[74]  Gabor T. Marth,et al.  Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics , 2013, Science.

[75]  Sridhar Ramaswamy,et al.  Identification of a pharmacologically tractable Fra-1/ADORA2B axis promoting breast cancer metastasis , 2013, Proceedings of the National Academy of Sciences.

[76]  Xuegong Zhang,et al.  Identifying potential cancer driver genes by genomic data integration , 2013, Scientific Reports.

[77]  Kevin C. Chu,et al.  Amplification of FRS2 and activation of FGFR/FRS2 signaling pathway in high-grade liposarcoma. , 2013, Cancer research.

[78]  K. Kinzler,et al.  Cancer Genome Landscapes , 2013, Science.

[79]  David Haussler,et al.  Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Events (TieDIE) , 2013, Bioinform..

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

[81]  Hannah Carter,et al.  CRAVAT: cancer-related analysis of variants toolkit , 2013, Bioinform..

[82]  Li Fan,et al.  TRAF6 upregulates expression of HIF-1α and promotes tumor angiogenesis. , 2013, Cancer research.

[83]  Ophir D Klein,et al.  Lgr5-expressing cells are sufficient and necessary for postnatal mammary gland organogenesis. , 2013, Cell reports.

[84]  Gary D Bader,et al.  Comprehensive identification of mutational cancer driver genes across 12 tumor types , 2013, Scientific Reports.

[85]  Gary D Bader,et al.  Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers , 2013 .

[86]  Jian Ma,et al.  A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression , 2014, BMC Bioinformatics.

[87]  Peilin Jia,et al.  VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data , 2014, PLoS Comput. Biol..

[88]  Dima Suki,et al.  Extent of resection of glioblastoma revisited: personalized survival modeling facilitates more accurate survival prediction and supports a maximum-safe-resection approach to surgery. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[89]  S. Gabriel,et al.  Discovery and saturation analysis of cancer genes across 21 tumor types , 2014, Nature.

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