Q-omics provides the consensus-scored G6PD profile across patient tissues and cancer cell-line models. G6PD expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, G6PD is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, G6PD protein abundance shows 18,511 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, KIRP, and GBM as cancer lineages where G6PD 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 G6PD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes G6PD survival associations across molecular data types. G6PD RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 G6PD RNA expression–survival associations across cancer types. High G6PD expression shows unfavorable associations in LIHC, LGG, UCS, KIRP and LAML, but favorable associations in SCLC. The LIHC 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 LIHC as the clearest survival context for G6PD RNA expression.
This table summarizes G6PD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for G6PD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. G6PD shows higher tumor expression in KIRP, COAD, HNSC, LIHC, KIRC and STAD. The KIRP box plot shows higher G6PD RNA expression in tumor versus normal tissue (log2 FC = +2.478, t-test p < 0.001).
This table shows molecular features associated with G6PD in patient tissues and cancer cell lines. In patient samples, G6PD shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, G6PD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
