An increasing number of targeted cancer therapies, such as small-molecule kinase inhibitors and monoclonal antibodies, have been widely applied to the treatment of various types of human cancers. During the course of treatment, many somatic mutations have demonstrated their importance in affecting drug sensitivity. However, the relationship between tumor genomic profiles and effectiveness of targeted cancer drugs remains to be fully determined. According to current treatment guidelines, only a small proportion of cancer genomic alterations are confirmed actionable with approved targeted therapies, which significantly limit the scope of cancer precision medicine. Recent large-scale clinical trials of mutation-dependent treatment on cancer patients (like NCI-Molecular Analysis for Therapy Choice [NCI-MATCH)]) and chemical screens on human cancer cell lines (like Cancer Cell Line Encyclopedia [CCLE], Cancer Therapeutics Response Portal [CTRP], and Genomics of Drug Sensitivity in Cancer [GDSC]) revealed many emerging associations between somatic mutation and drug/compound sensitivity.

mTCTScan ( is designed to analyze mutation-dependent response of targeted cancer drugs/compounds by integrating conclusion level of mutation associations for 495 drugs/compounds (FDA-approved and those in the clinical trial stage) from literatures and other public resources, such as Clinical Interpretations Of Variants In Cancer ( and Gene Drug Knowledge Database (!Synapse:syn2370773), as well as cell line level evidence of association between mutated genes and drug responses from large-scale pharmacogenomics screens. This web server accepts human cancer genomic profile (such as VCF) and filters the mutation by different criteria, such as mutation type, known allele frequency and cancer type. It uses an evidence-based scoring strategy to filter and prioritize the mutations associated with drug sensitivity. In addition, mTCTScan provides comprehensive annotations of mutations, including recurrence rate (from TCGA, ICGC and COSMIC), disease relevance (ClinVar), functional predictions (nonsynonymous, splicing and non-coding functional prediction) and base-wise conservation. Furthermore, it incorporates several visualization functions to display the mutation position in protein functional domains and integrate drug information from public databases such as Drug Bank (

mTCTScan was developed by Center for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong. If you have new information on mutation-targeted cancer drug response and would like to contribute to this platform, please contact us through or or

news: 13/04/2017 mTCTScan now introduces new help pages and supports result downloads.
28/02/2017 mTCTScan now supports drug classification according to entire genomic profile input.
29/12/2016 mTCTScan now supports direct query of single mutation through an independent web page.
26/12/2016 mTCTScan now introduces functional prediction annotations including Nonsynonymous Functional Prediction, Splicing Functional Prediction, Non-coding Functional Prediction and Conservation Score, each category contains many scores from different algorithms.
21/12/2016 mTCTScan is released.