CanDriS: posterior profiling of cancer-driving sites based on two-component evolutionary model.

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  • Additional Information
    • Source:
      Publisher: Oxford University Press Country of Publication: England NLM ID: 100912837 Publication Model: Print Cited Medium: Internet ISSN: 1477-4054 (Electronic) Linking ISSN: 14675463 NLM ISO Abbreviation: Brief Bioinform Subsets: MEDLINE
    • Publication Information:
      Publication: Oxford : Oxford University Press
      Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000-
    • Subject Terms:
      Algorithms* ; Databases, Genetic* ; Models, Genetic* ; Mutation*; Computational Biology/*methods ; Neoplasms/*genetics; Bayes Theorem ; Benchmarking/methods ; Genomics/methods ; Humans ; Internet ; User-Computer Interface
    • Abstract:
      Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations. Then, we implemented an empirical Bayesian procedure to calculate the posterior probability of a site being cancer-driven. Based on these, we developed a software CanDriS (Cancer Driver Sites) to profile the potential cancer-driving sites for thousands of tumor samples from the Cancer Genome Atlas and International Cancer Genome Consortium across tumor types and pan-cancer level. As a result, we identified that approximately 1% of the sites have posterior probabilities larger than 0.90 and listed potential cancer-wide and cancer-specific driver mutations. By comprehensively profiling all potential cancer-driving sites, CanDriS greatly enhances our ability to refine our knowledge of the genetic basis of cancer and might guide clinical medication in the upcoming era of precision medicine. The results were displayed in a database CandrisDB (http://biopharm.zju.edu.cn/candrisdb/).
      (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].)
    • Contributed Indexing:
      Keywords: CanDriS; cancer somatic mutations; cancer-driving sites; two-component model
    • Publication Date:
      Date Created: 20210420 Date Completed: 20211122 Latest Revision: 20211122
    • Publication Date:
      20250114
    • Accession Number:
      10.1093/bib/bbab131
    • Accession Number:
      33876217