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- W3039349546 abstract "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." @default.
- W3039349546 created "2020-07-10" @default.
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- W3039349546 date "2020-07-03" @default.
- W3039349546 modified "2023-10-10" @default.
- W3039349546 title "Predicting and affecting response to cancer therapy based on pathway-level biomarkers" @default.
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- W3039349546 doi "https://doi.org/10.1038/s41467-020-17090-y" @default.
- W3039349546 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7335104" @default.
- W3039349546 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32620799" @default.
- W3039349546 hasPublicationYear "2020" @default.
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