title: MutComFocal: an integrative approach to identifying recurrent and focal genomic alterations in tumor samples.
abstract: BACKGROUND
  Most tumors are the result of accumulated genomic alterations in somatic cells. The emerging spectrum of alterations in tumors is complex and the identification of relevant genes and pathways remains a challenge. Furthermore, key cancer genes are usually found amplified or deleted in chromosomal regions containing many other genes. Point mutations, on the other hand, provide exquisite information about amino acid changes that could be implicated in the oncogenic process. Current large-scale genomic projects provide high throughput genomic data in a large number of well-characterized tumor samples.
  
  
  METHODS
  We define a Bayesian approach designed to identify candidate cancer genes by integrating copy number and point mutation information. Our method exploits the concept that small and recurrent alterations in tumors are more informative in the search for cancer genes. Thus, the algorithm (Mutations with Common Focal Alterations, or MutComFocal) seeks focal copy number alterations and recurrent point mutations within high throughput data from large panels of tumor samples.
  
  
  RESULTS
  We apply MutComFocal to Diffuse Large B-cell Lymphoma (DLBCL) data from four different high throughput studies, totaling 78 samples assessed for copy number alterations by single nucleotide polymorphism (SNP) array analysis and 65 samples assayed for protein changing point mutations by whole exome/whole transcriptome sequencing. In addition to recapitulating known alterations, MutComFocal identifies ARID1B, ROBO2 and MRS1 as candidate tumor suppressors and KLHL6, IL31 and LRP1 as putative oncogenes in DLBCL.
  
  
  CONCLUSIONS
  We present a Bayesian approach for the identification of candidate cancer genes by integrating data collected in large number of cancer patients, across different studies. When trained on a well-studied dataset, MutComFocal is able to identify most of the reported characterized alterations. The application of MutComFocal to large-scale cancer data provides the opportunity to pinpoint the key functional genomic alterations in tumors.
authors.affiliation: Department of Biomedical Informatics, New York, NY 10032, USA. vt2184@c2b2.columbia.edu
authors.forename: Vladimir
authors.initials: V
authors.lastname: Trifonov
authors.forename: Laura
authors.initials: L
authors.lastname: Pasqualucci
authors.forename: Riccardo
authors.initials: R
authors.lastname: Dalla Favera
authors.forename: Raul
authors.initials: R
authors.lastname: Rabadan
mesh_terms: D001499:Bayes Theorem; D002352:Carrier Proteins / Q000235:genetics; D004268:DNA-Binding Proteins / Q000235:genetics; D018628:Gene Dosage / Q000235:genetics*; D052138:Genes, Neoplasm / Q000235:genetics*; D056726:Genetic Association Studies / Q000379:methods; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D007378:Interleukins / Q000235:genetics; D026503:Low Density Lipoprotein Receptor-Related Protein-1 / Q000235:genetics; D016403:Lymphoma, Large B-Cell, Diffuse / Q000235:genetics*; D008957:Models, Genetic; D017354:Point Mutation / Q000235:genetics*; D011971:Receptors, Immunologic / Q000235:genetics; D049490:Systems Biology / Q000379:methods; D014157:Transcription Factors / Q000235:genetics; D000097905:Roundabout Proteins
chemical_list: D002352:Carrier Proteins; D004268:DNA-Binding Proteins; D007378:Interleukins; D026503:Low Density Lipoprotein Receptor-Related Protein-1; D011971:Receptors, Immunologic; D014157:Transcription Factors; C497837:ARID1B protein, human; C502187:IL31 protein, human; C473356:KLHL6 protein, human; C475476:LRP1 protein, human; C498890:ROBO2 protein, human; D000097905:Roundabout Proteins