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Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins. | LitMetric

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins.

Sci Rep

Machine Learning for Healthcare and Life Sciences, IBM Research - Haifa, Mount Carmel Campus, Israel.

Published: December 2016

AI Article Synopsis

  • Compiling a thorough list of cancer driver genes is crucial for improving cancer diagnostics and drug development, but many rare drivers go undetected due to small sample sizes.
  • The research presents a new method called CARNAF, which combines tumor genomics with various gene characteristics to uncover novel driver genes that previous studies missed.
  • The findings underscore that a significant number of known and potential tumor suppressor genes are found among the small fraction of genes responsible for large, chromatin-regulating proteins, stressing the importance of investigating these large epigenetic regulators in cancer research.

Article Abstract

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180091PMC
http://dx.doi.org/10.1038/srep38988DOI Listing

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