VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

PLoS Computational Biology

Volumn 10, Issue 2, 2014, Pages

  Jia, Peilin ^a,b   Zhao, Zhongming ^a,b  

^a VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DISEASES; NEXT GENERATION NETWORKS; PROTEINS;

'CURRENT; CANCER GENES; INTERACTORS; LARGE VOLUMES; LARGE-SCALES; MUTATED GENES; MUTATION FREQUENCY; NEXT-GENERATION SEQUENCING; NOVEL MUTATIONS; POWER;

GENES;

ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; DATA ANALYSIS SOFTWARE; GENE INTERACTION; GENE SEQUENCE; GENETIC ALGORITHM; GENETIC DATABASE; GENETIC VARIABILITY; GENOME ANALYSIS; HUMAN; LUNG ADENOCARCINOMA; MELANOMA; MUTATIONAL ANALYSIS; NEXT GENERATION SEQUENCING; PROCESS DEVELOPMENT; PROTEIN PROTEIN INTERACTION; TUMOR GENE; ADENOCARCINOMA; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; CONSENSUS SEQUENCE; GENE FREQUENCY; GENE REGULATORY NETWORK; GENETICS; HIGH THROUGHPUT SEQUENCING; LUNG TUMOR; MOLECULAR GENETICS; MUTATION; NEOPLASM; NUCLEOTIDE SEQUENCE; ONCOGENE; STATISTICS AND NUMERICAL DATA; VALIDATION STUDY;

DNA;

ADENOCARCINOMA; ALGORITHMS; COMPUTATIONAL BIOLOGY; CONSENSUS SEQUENCE; DATABASES, GENETIC; DNA MUTATIONAL ANALYSIS; DNA, NEOPLASM; GENE FREQUENCY; GENE REGULATORY NETWORKS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; LUNG NEOPLASMS; MELANOMA; MODELS, GENETIC; MOLECULAR SEQUENCE ANNOTATION; MUTATION; NEOPLASMS; ONCOGENES;

EID: 84895774260     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003460     Document Type: Article

References (44)

1. Wei X, Walia V, Lin JC, Teer JK, Prickett TD, et al. (2011) Exome sequencing identifies GRIN2A as frequently mutated in melanoma. Nat Genet 43: 442-446.
2. Lovly CM, Dahlman KB, Fohn LE, Su Z, Dias-Santagata D, et al. (2012) Routine multiplex mutational profiling of melanomas enables enrollment in genotype-driven therapeutic trials. PLoS One 7: e35309.
3. Gonzalez-Perez A, Mustonen V, Reva B, Ritchie GR, Creixell P, et al. (2013) Computational approaches to identify functional genetic variants in cancer genomes. Nat Methods 10: 723-729.
4. Moreau Y, Tranchevent LC, (2012) Computational tools for prioritizing candidate genes: boosting disease gene discovery. Nat Rev Genet 13: 523-536.
5. Rubin AF, Green P, (2007) Comment on "The consensus coding sequences of human breast and colorectal cancers". Science 317: 1500.
6. Getz G, Hofling H, Mesirov JP, Golub TR, Meyerson M, et al. (2007) Comment on "The consensus coding sequences of human breast and colorectal cancers". Science 317: 1500.
7. Forrest WF, Cavet G, (2007) Comment on "The consensus coding sequences of human breast and colorectal cancers". Science 317: 1500 author reply 1500.
8. Ju YS, Kim JI, Kim S, Hong D, Park H, et al. (2011) Extensive genomic and transcriptional diversity identified through massively parallel DNA and RNA sequencing of eighteen Korean individuals. Nat Genet 43: 745-752.
9. Ding L, Getz G, Wheeler DA, Mardis ER, McLellan MD, et al. (2008) Somatic mutations affect key pathways in lung adenocarcinoma. Nature 455: 1069-1075.
10. Yeang CH, McCormick F, Levine A, (2008) Combinatorial patterns of somatic gene mutations in cancer. FASEB J 22: 2605-2622.
11. Vandin F, Clay P, Upfal E, Raphael BJ, (2012) Discovery of mutated subnetworks associated with clinical data in cancer. Pac Symp Biocomput pp. 55-66.
12. Vandin F, Upfal E, Raphael BJ, (2012) De novo discovery of mutated driver pathways in cancer. Genome Res 22: 375-385.
13. Masica DL, Karchin R, (2011) Correlation of somatic mutation and expression identifies genes important in human glioblastoma progression and survival. Cancer Res 71: 4550-4561.
14. Kim JG, Takeshima H, Niwa T, Rehnberg E, Shigematsu Y, et al. (2013) Comprehensive DNA methylation and extensive mutation analyses reveal an association between the CpG island methylator phenotype and oncogenic mutations in gastric cancers. Cancer Lett 330: 33-40.
15. Imielinski M, Berger AH, Hammerman PS, Hernandez B, Pugh TJ, et al. (2012) Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell 150: 1107-1120.
16. Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, et al. (2012) A landscape of driver mutations in melanoma. Cell 150: 251-263.
17. Kohler S, Bauer S, Horn D, Robinson PN, (2008) Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet 82: 949-958.
18. Li Y, Patra JC, (2010) Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network. Bioinformatics 26: 1219-1224.
19. Cancer Gene Census (CGC) website http://www.sanger.ac.uk/genetics/CGP/Census/.
20. Barabasi AL, Gulbahce N, Loscalzo J, (2011) Network medicine: a network-based approach to human disease. Nat Rev Genet 12: 56-68.
21. Li MX, Kwan JS, Sham PC, (2012) HYST: a hybrid set-based test for genome-wide association studies, with application to protein-protein interaction-based association analysis. Am J Hum Genet 91: 478-488.
22. Manning G, Whyte DB, Martinez R, Hunter T, Sudarsanam S, (2002) The protein kinase complement of the human genome. Science 298: 1912-1934.
23. Huang da W, Sherman BT, Lempicki RA, (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37: 1-13.
24. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M, (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38: D355-D360.
25. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25: 25-29.
26. Bonitsis N, Batistatou A, Karantima S, Charalabopoulos K, (2006) The role of cadherin/catenin complex in malignant melanoma. Exp Oncol 28: 187-193.
27. Berx G, van Roy F, (2009) Involvement of members of the cadherin superfamily in cancer. Cold Spring Harb Perspect Biol 1: a003129.
28. Guldener U, Munsterkotter M, Oesterheld M, Pagel P, Ruepp A, et al. (2006) MPact: the MIPS protein interaction resource on yeast. Nucleic Acids Res 34: D436-441.
29. Kerrien S, Alam-Faruque Y, Aranda B, Bancarz I, Bridge A, et al. (2007) IntAct-open source resource for molecular interaction data. Nucleic Acids Res 35: D561-565.
30. Licata L, Briganti L, Peluso D, Perfetto L, Iannuccelli M, et al. (2012) MINT, the molecular interaction database: 2012 update. Nucleic Acids Res 40: D857-D861.
31. Mewes HW, Ruepp A, Theis F, Rattei T, Walter M, et al. (2011) MIPS: curated databases and comprehensive secondary data resources in 2010. Nucleic Acids Res 39: D220-D224.
32. Kan Z, Jaiswal BS, Stinson J, Janakiraman V, Bhatt D, et al. (2010) Diverse somatic mutation patterns and pathway alterations in human cancers. Nature 466: 869-873.
33. Wang K, Li M, Hakonarson H, (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38: e164.
34. Kumar P, Henikoff S, Ng PC, (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4: 1073-1081.
35. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, et al. (2010) A method and server for predicting damaging missense mutations. Nat Methods 7: 248-249.
36. Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, et al. (2009) Human Protein Reference Database-2009 update. Nucleic Acids Res 37: D767-772.
37. CCDS http://www.ncbi.nlm.nih.gov/CCDS.
38. Li Y, Li J, (2012) Disease gene identification by random walk on multigraphs merging heterogeneous genomic and phenotype data. BMC Genomics 13 Suppl 7: S27.
39. Zhu J, Qin Y, Liu T, Wang J, Zheng X, (2013) Prioritization of candidate disease genes by topological similarity between disease and protein diffusion profiles. BMC Bioinformatics 14 Suppl 5: S5.
40. Fouss F, Francoisse K, Yen L, Pirotte A, Saerens M, (2012) An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. Neural Netw 31: 53-72.
41. Nakaoka H, Cui T, Tajima A, Oka A, Mitsunaga S, et al. (2011) A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis. PLoS One 6: e25389.
42. Milo R, Kashtan N, Itzkovitz S, Newman MEJ, Alon U, (2003) On the uniform generation of random graphs with prescribed degree sequences. eprint arXiv cond-mat/0312028.
43. Murray S, Dahabreh IJ, Linardou H, Manoloukos M, Bafaloukos D, et al. (2008) Somatic mutations of the tyrosine kinase domain of epidermal growth factor receptor and tyrosine kinase inhibitor response to TKIs in non-small cell lung cancer: an analytical database. J Thorac Oncol 3: 832-839.
44. Chen J, Bardes EE, Aronow BJ, Jegga AG, (2009) ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res 37: W305-311.