Predicting and affecting response to cancer therapy based on pathway-level biomarkers.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 32620799.
- Also identified by DOI 10.1038/s41467-020-17090-y and PMC identifier 7335104.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Identifying robust, patient-specific, and predictive biomarkers presents a major obstacle in precision oncology. To optimize patient-specific therapeutic strategies, here we couple pathway knowledge with large-scale drug sensitivity, RNAi, and CRISPR-Cas9 screening data from 460 cell lines. Pathway activity levels are found to be strong predictive biomarkers for the essentiality of 15 proteins, including the essentiality of MAD2L1 in breast cancer patients with high BRCA-pathway activity. We also find strong predictive biomarkers for the sensitivity to 31 compounds, including BCL2 and microtubule inhibitors (MTIs). Lastly, we show that Bcl-xL inhibition can modulate the activity of a predictive biomarker pathway and re-sensitize lung cancer cells and tumors to MTI therapy. Overall, our results support the use of pathways in helping to achieve the goal of precision medicine by uncovering dozens of predictive biomarkers.
Medical subject headings
- Biomarkers, Tumor
- Gene Expression Profiling
- Gene Expression Regulation, Neoplastic
- Neoplasms
- Signal Transduction