Q-omics provides the consensus-scored GPX5 profile across patient tissues and cancer cell-line models. GPX5 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, GPX5 is differentially expressed in 6, with the highest sampling consensus in LUAD. Additionally, GPX5 RNA expression shows 6,688 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KICH, LUAD, and STAD as cancer lineages where GPX5 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 GPX5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPX5 survival associations across molecular data types. GPX5 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GPX5 RNA expression–survival associations across cancer types. High GPX5 expression shows unfavorable associations in KICH, CESC, BLCA, LGG, PAAD and ESCA. The KICH 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 KICH as the clearest survival context for GPX5 RNA expression.
This table summarizes GPX5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for GPX5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPX5 shows lower tumor expression in LUAD and LUSC and higher tumor expression in UCEC, BLCA, KIRC and LIHC. The LUAD box plot shows higher GPX5 RNA expression in normal versus tumor tissue (log2 FC = −0.032, t-test p = .015).
This table shows molecular features associated with GPX5 in patient tissues and cancer cell lines. In patient samples, GPX5 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, GPX5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LIVER.
