Response Marker Enrichment Analysis informs the impact of pharmacological and genetic perturbagens on cancer cells

Abstract Omics data encode information on biological processes dysregulated in disease, thus providing insights that are critical for advancing precision oncology approaches. Enrichment analysis is fundamental for interpreting omics data, yet most approaches disregard whether genes positively or negatively regulate pathways despite this being an essential aspect of understanding cellular responses. To address this, we developed Response Marker Enrichment Analysis (ReMEA), a computational framework that uses quantitative proteomics to infer functional gene involvement with directionally informed enrichment scores. ReMEA is based on a database of proteomic signatures from 2220 genetic perturbations and 286 pharmacological agents, encompassing 37,874 signatures and 13,176 proteins. The method integrates the ratio of positively and negatively associated protein markers of response (namely, antiproliferative impact) for each perturbagen. Validation revealed strong agreement between ReMEA scores and the antiproliferative impact of genetic and drug perturbations. In acute myeloid leukemia (AML), ReMEA identified increased PI3K pathway dependency following LSD1 inhibition and such scores reflected drug responses in independent primary cancer proteomic datasets. By incorporating regulatory directionality, ReMEA broadens enrichment analysis capabilities and advances drug discovery for precision oncology. ReMEA is implemented in a freely available R package.