Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning.

ABSTRACT: Cancer is a group of complex diseases, with tumor heterogeneity, durable drug efficacy, emerging resistance, and host toxicity presenting major challenges to the development of effective cancer therapeutics. While traditionally used methods have remained limited in their capacity to overcome these challenges in cancer drug development, efforts have been made in recent years toward applying "big data" to cancer research and precision oncology. By curating, standardizing, and integrating data from various databases, we developed deep learning architectures that use perturbation and baseline transcriptional signatures to predict efficacious small molecule compounds and genetic dependencies in cancer. A series of internal validations followed by prospective validation in prostate cancer cell l

SUBMITTER: Ocasio BA 

PROVIDER: S-EPMC11601385 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature