Q-omics provides the Selisistat response profile across cancer cell-line models in the CCLE and GDSC pharmacogenomic screens. Selisistat, a SIRT1 inhibitor, shows drug-response associations across 11 molecular data types, most extensively with RNA-expression features, with the highest sampling consensus in OVARY. OVARY shows the largest number of associated molecular features, while functional-dependency data highlight URINARY_TRACT as a cancer context with signals that can be tested experimentally.
Each association is evaluated using two consensus scores. Sampling consensus shows how consistently a biomarker separates sensitive and resistant cell lines across repeated analysis settings. Lineage consensus shows how widely the same biomarker–response association appears across cancer lineages, distinguishing broadly shared signals from lineage-specific ones.
Cross-omics associations
This table summarizes molecular features associated with Selisistat sensitivity in cancer cell lines. Drug sensitivity data from CCLE and GDSC were compared with RNA expression, mutation, CRISPR, and shRNA dependency data. The Strength column shows the number of significant associated features for each molecular layer, and the Lineage column indicates the cancer lineage where the largest associated feature set is observed. The response to Selisistat is most broadly linked to RNA-expression features, especially in OVARY. CRISPR and shRNA dependency results also highlight experimentally testable signals in URINARY_TRACT.