ICBcDrug: An online resource and tool for screening and predicting immunotherapy combination drugs

Combining small molecules with immune checkpoint blockade (ICB) therapy is an effective strategy for improving therapeutic efficacy. However, the systematic identification of small molecules that effectively potentiate ICB remains a significant challenge.

We curated 276 literature-supported compounds known to enhance the efficacy of ICB. For each compound, we calculated its Core and Minor gene set score (CM-score), a quantitative metric defined by the CM-Drug method. The median CM-score of these compounds was then established as the reference standard. We subsequently used the CM-Drug framework to screen 2036 candidate drugs from the Library of Integrated Network-based Cellular Signatures (LINCS) database against this reference to identify potential ICB enhancers.

We developed ICBcDrug, a resource that integrates 2311 reported or predicted compounds across 18 cancer types. With respect to the reported drugs, ICBcDrug displays compounds with similar chemical structures or transcriptomic profiles, and for the predicted drugs, they are prioritized for further validation across various cancer types. A "Search" module allows users to retrieve compounds using customizable filters. Furthermore, ICBcDrug offers an "Analysis" module to predict the ICB combination efficacy of novel compounds on the basis of user-provided expression data. Using these modules, we identified promising candidate drugs and accurately predicted both the efficacy and potential mechanisms of the known ICB enhancer entinostat.

ICBcDrug (https://guolab.wchscu.cn/ICBcDrug) is a freely accessible and valuable resource for advancing ICB combination therapy. These findings will facilitate the discovery and development of novel ICB-enhancing drugs, contributing to the improvement of cancer immunotherapy.