Deciphering the Complexity of MEK Mutations in the Clinic
- PMID: 33008803
- DOI: 10.1158/0008-5472.CAN-20-2611
Deciphering the Complexity of MEK Mutations in the Clinic
Abstract
Significant advances in tumor sequencing have led to an explosion in our knowledge of the genetic complexity of cancer. For many cancers, the selection of a targetable alteration is not readily apparent, especially when confronted with mutational variants of unknown significance. The complex clinical landscape of MEK mutations illustrates the need for improved methods to identify those patients, independent of tumor histology, who would benefit from treatment with a MAP kinase pathway inhibitor. In this issue of Cancer Research, Hanrahan and colleagues adopt an in silico platform to attempt to distinguish benign MEK mutations from those that are functional and, therefore, most likely to be therapeutically actionable.See related article by Hanrahan et al., p. 4233.
©2020 American Association for Cancer Research.
Comment in
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Leveraging Systematic Functional Analysis to Benchmark an In Silico Framework Distinguishes Driver from Passenger MEK Mutants in Cancer.Cancer Res. 2020 Oct 1;80(19):4233-4243. doi: 10.1158/0008-5472.CAN-20-0865. Epub 2020 Jul 8. Cancer Res. 2020. PMID: 32641410 Free PMC article.
Comment on
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Leveraging Systematic Functional Analysis to Benchmark an In Silico Framework Distinguishes Driver from Passenger MEK Mutants in Cancer.Cancer Res. 2020 Oct 1;80(19):4233-4243. doi: 10.1158/0008-5472.CAN-20-0865. Epub 2020 Jul 8. Cancer Res. 2020. PMID: 32641410 Free PMC article.
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