Preclinical-to-clinical Anti-cancer Drug Response Prediction and Biomarker Identification Using TINDL.

ABSTRACT: Prediction of the response of cancer patients to different treatments and identification of biomarkers of drug response are two major goals of individualized medicine. Here, we developed a deep learning framework called TINDL, completely trained on preclinical cancer cell lines (CCLs), to predict the response of cancer patients to different treatments. TINDL utilizes a tissue-informed normalization to account for the tissue type and cancer type of the tumors and to reduce the statistical discrepancies between CCLs and patient tumors. Moreover, by making the deep learning black box interpretable, this model identifies a small set of genes whose expression levels are predictive of drug response in the trained model, enabling identification of biomarkers of drug response. Using data from two

SUBMITTER: Hostallero DE 

PROVIDER: S-EPMC10787192 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature