A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

Abstract

SUMMARYThe Columbia Cancer Target Discovery and Development (CTD2) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection of dose-response curves and perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, developed to study tumor-specific drug mechanism of action, was instrumental in hosting a DREAM Challenge to assess computational models for de novo drug polypharmacology prediction. Dose-response and perturbational profiles for 32 kinase inhibitors were provided to 21 participating teams, who did not know the identity or nature of the compounds, and they were asked to predict high-affinity binding among ~1,300 possible protein targets. Best performing methods leveraged both gene expression profile similarity analysis, and deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessment of context-specific drug mechanism of action.

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal

“…The single drug sensitivity is characterized as a dose-response curve with its IC50 and RI (relative inhibition) values. RI is the normalized area under the log 10 -transformed dose-response curves, which has shown enhanced robustness to characterize drug sensitivity ( 35 ). Moreover, RI can be interpreted as percentage inhibition, summarizing the overall drug inhibition effects relative to positive controls.…”

Network-based identification and pharmacological targeting of host cell master regulators induced by SARS-CoV-2 infection

“…We have shown that drug MoA—as represented by differentially active proteins in response to the drug and measured by VIPER analysis of drug perturbation profiles in lineage-matched cells—is well recapitulated in vivo and in explants when the activity of their MR proteins is conserved(21, 32). Among the 25 cell lines for which perturbational profiles had been generated in the PANACEA database (PANcancer Analysis of Chemical Entity Activity)(33), 2 cell lines, LoVo and NCI-H1973, are the closest lineage-matched representative models of the GI epithelial and lung epithelial cells, respectively. However, while LoVo (human colon cell line) showed significant conservation of MR proteins with a colon adenocarcinoma cell line susceptible to SARS-CoV-2 infection (Caco-2(34), Supplementary Fig.…”

SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets

“…To facilitate the interpretation of mechanisms of action of drug combinations, it would therefore be beneficial to provide data integration tools for effective annotation and accurate matching to public databases such that more comprehensive features used for synergy predictions can be obtained. Efforts regarding annotating and harmonizing existing drug screening data, such as DrugComb 24,29 and DrugCombDB 30 , have significantly contributed to the development of data-driven pharmacological modelling [31][32][33] . For newly generated drug screening datasets, we have developed the SynergyFinder Plus portal further as a companion tool for retrieving publicly available information in a more automated fashion.…”