Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns.
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ABSTRACT:
SUBMITTER: Mateo L
PROVIDER: S-EPMC7488324 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
Publications
Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns.
Mateo Lidia L Duran-Frigola Miquel M Gris-Oliver Albert A Palafox Marta M Scaltriti Maurizio M Razavi Pedram P Chandarlapaty Sarat S Arribas Joaquin J Bellet Meritxell M Serra Violeta V Aloy Patrick P
Genome medicine 20200909 1
Identification of actionable genomic vulnerabilities is key to precision oncology. Utilizing a large-scale drug screening in patient-derived xenografts, we uncover driver gene alteration connections, derive driver co-occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug-response predictors attains an average balanced accuracy of 58% in a cross-validation setting, rising to 66% for a subset of high-confidence predictions. We experimentally validated 12 out of ...[more]
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