4.8 Article

mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers

Journal

NUCLEIC ACIDS RESEARCH
Volume 45, Issue W1, Pages W215-W221

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx400

Keywords

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Funding

  1. Y S and Christabel Lung Postgraduate Scholarship from the University of Hong Kong
  2. Talent Excellence Program from Tianjin Medical University
  3. Research Grants Council, Hong Kong SAR, China [17121414M]
  4. Mayo Clinic (Mayo Clinic Arizona and Center for Individualized Medicine)
  5. National Institute of Health [5R01CA170357, 2P30CA015083, 1U54CA210180]

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Cancer therapies have experienced rapid progress in recent years, with a number of novel smallmolecule kinase inhibitors and monoclonal antibodies now being widely used to treat various types of human cancers. During cancer treatments, mutations can have important effects on drug sensitivity. However, the relationship between tumor genomic profiles and the effectiveness of cancer drugs remains elusive. We introduce Mutation To Cancer Therapy Scan (mTCTScan) web server (http://jjwanglab.org/mTCTScan) that can systematically analyze mutations affecting cancer drug sensitivity based on individual genomic profiles. The platform was developed by leveraging the latest knowledge on mutation-cancer drug sensitivity associations and the results from large-scale chemical screening using human cancer cell lines. Using an evidence-based scoring scheme based on current integrative evidences, mTCTScan is able to prioritize mutations according to their associations with cancer drugs and preclinical compounds. It can also show related drugs/compounds with sensitivity classification by considering the context of the entire genomic profile. In addition, mTCTScan incorporates comprehensive filtering functions and cancer-related annotations to better interpretmutation effects and their association with cancer drugs. This platform will greatly benefit both researchers and clinicians for interrogating mechanisms of mutation-dependent drug response, which will have a significant impact on cancer precision medicine.

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