Q-omics provides the consensus-scored CAPG profile across patient tissues and cancer cell-line models. CAPG expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CAPG is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, CAPG protein abundance shows 23,657 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, COAD, and LSCC as cancer lineages where CAPG shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for CAPG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CAPG survival associations across molecular data types. CAPG RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CAPG RNA expression–survival associations across cancer types. High CAPG expression shows unfavorable associations in ACC, LGG and LIHC, but favorable associations in DLBC, ESCA and COAD. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify ACC as the clearest survival context for CAPG RNA expression.
This table summarizes CAPG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CAPG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CAPG shows higher tumor expression in COAD, HNSC, BLCA, LIHC, STAD and BRCA. The COAD box plot shows higher CAPG RNA expression in tumor versus normal tissue (log2 FC = +1.186, t-test p < 0.001).
This table shows molecular features associated with CAPG in patient tissues and cancer cell lines. In patient samples, CAPG shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CAPG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
