Analysis on GENIE reveals novel recurrent variants that affect molecular diagnosis of sizable number of cancer patients View Full Text


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Article Info

DATE

2019-02-01

AUTHORS

Takahiko Koyama, Kahn Rhrissorrakrai, Laxmi Parida

ABSTRACT

BackgroundSignificant numbers of variants detected in cancer patients are often left labeled only as variants of unknown significance (VUS). In order to expand precision medicine to a wider population, we need to extend our knowledge of pathogenicity and drug response in the context of VUS’s.MethodsIn this study, we analyzed variants from AACR Project GENIE Consortium APG (Cancer Discov 7:818-831, 2017) and compared them to the COSMIC database Forbes et al. (Nucleic Acids Res 43:D805-811, 2015) to identify recurrent variants that would merit further study. We filtered out known hotspot variants, inactivating variants in tumor suppressors, and likely benign variants by comparing with COSMIC and ExAC Lee et al. (Science 337:967-971, 2012).ResultsWe have identified 45,933 novel variants with unknown significance unique to GENIE. In our analysis, we found on average six variants per patient where two could be considered as pathogenic or likely pathogenic and the majority are VUS’s. More importantly, we have discovered 730 recurrent variants that appear more than 3 times in GENIE but less than 3 in COSMIC. If we combine the recurrences of GENIE and COSMIC for all variants, 2586 are newly identified as occurring more than 3 times than when using COSMIC alone.ConclusionsAlthough it would be inappropriate to blindly accept these recurrent variants as pathogenic, they may warrant higher priority than other observed VUS’s. These newly identified recurrent variants might affect the molecular profiles of approximately 1 in 6 patients. Further analysis and characterization of these variants in both research and clinical contexts will improve patient treatments and the development of new therapeutics. More... »

PAGES

114

References to SciGraph publications

  • 2011-03-07. Metabolism unhinged: IDH mutations in cancer in NATURE MEDICINE
  • 2016-06-13. Protein-structure-guided discovery of functional mutations across 19 cancer types in NATURE GENETICS
  • 2012-08-15. Tumour suppressor RNF43 is a stem-cell E3 ligase that induces endocytosis of Wnt receptors in NATURE
  • 2014-07-09. Comprehensive molecular profiling of lung adenocarcinoma in NATURE
  • 2016-07-26. G protein pathway suppressor 2 (GPS2) acts as a tumor suppressor in liposarcoma in TUMOR BIOLOGY
  • 2015-04-23. Regulation of RAF protein kinases in ERK signalling in NATURE REVIEWS MOLECULAR CELL BIOLOGY
  • 2015-09-14. The histone lysine methyltransferase KMT2D sustains a gene expression program that represses B cell lymphoma development in NATURE MEDICINE
  • 2009-08-30. Analysis of the tyrosine kinome in melanoma reveals recurrent mutations in ERBB4 in NATURE GENETICS
  • 2016-08-11. AKT1E17K mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection in BMC CANCER
  • 2009-06-01. GATA3 inhibits breast cancer growth and pulmonary breast cancer metastasis in ONCOGENE
  • 2014-05-22. Role of Fbxw7 in the maintenance of normal stem cells and cancer-initiating cells in BRITISH JOURNAL OF CANCER
  • 2016-06-27. Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks in NATURE COMMUNICATIONS
  • 2013-08-14. Signatures of mutational processes in human cancer in NATURE
  • 2015-11-20. PDCD2 and NCoR1 as putative tumor suppressors in gastric gastrointestinal stromal tumors in CELLULAR ONCOLOGY
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