Q-omics provides the Sunitinib response profile across cancer cell-line models in the CCLE and GDSC pharmacogenomic screens. Sunitinib, a PDGFR / KIT / VEGFR inhibitor, shows drug-response associations across 12 molecular data types, most extensively with RNA-expression features, with the highest sampling consensus in BREAST. BREAST shows the largest number of associated molecular features, while functional-dependency data highlight LUNG_NSCLC_LUAD 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 Sunitinib 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 Sunitinib is most broadly linked to RNA-expression features, especially in BREAST. CRISPR and shRNA dependency results also highlight experimentally testable signals in LUNG_NSCLC_LUAD.