Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network Characteristics.

ABSTRACT: Prostate cancer (PRAD) is a major cause of cancer-related deaths. Current monotherapies show limited efficacy due to often rapidly emerging resistance. Combination therapies could provide an alternative solution to address this problem with enhanced therapeutic effect, reduced cytotoxicity, and delayed the appearance of drug resistance. However, it is prohibitively cost and labor-intensive for the experimental approaches to pick out synergistic combinations from the millions of possibilities. Thus, it is highly desired to explore other efficient strategies to assist experimental researches. Inspired by the challenge, we construct the transcriptomics-based and network-based prediction models to quickly screen the potential drug combination for Prostate cancer, and further assess their perfo

SUBMITTER: Li S 

PROVIDER: S-EPMC8112211 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature