Q-omics provides the consensus-scored GAPDH profile across patient tissues and cancer cell-line models. GAPDH expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, GAPDH is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, GAPDH protein abundance shows 35,787 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight LUAD, KIRC, and HNSC as cancer lineages where GAPDH 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 GAPDH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GAPDH survival associations across molecular data types. GAPDH RNA expression shows survival associations in the most cancer types (27), followed by mutation status (6) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GAPDH RNA expression–survival associations across cancer types. High GAPDH expression shows unfavorable associations in LUAD, MESO, KICH, KIRP, LIHC and UCS. The LUAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LUAD as the clearest survival context for GAPDH RNA expression.
This table summarizes GAPDH 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 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GAPDH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GAPDH shows higher tumor expression in KIRC, HNSC, LUAD, KIRP, COAD and LUSC. The KIRC box plot shows higher GAPDH RNA expression in tumor versus normal tissue (log2 FC = +2.226, t-test p < 0.001).
This table shows molecular features associated with GAPDH in patient tissues and cancer cell lines. In patient samples, GAPDH shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, GAPDH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SOFT_TISSUE.
