Q-omics provides the consensus-scored GPX4 profile across patient tissues and cancer cell-line models. GPX4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, GPX4 is differentially expressed in 12, with the highest sampling consensus in KIRP. Additionally, GPX4 protein abundance shows 24,101 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, KIRP, and GBM as cancer lineages where GPX4 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 GPX4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPX4 survival associations across molecular data types. GPX4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GPX4 RNA expression–survival associations across cancer types. High GPX4 expression shows unfavorable associations in UCS, UVM, KICH, ACC and LAML, but favorable associations in UCEC. The UCS Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify UCS as the clearest survival context for GPX4 RNA expression.
This table summarizes GPX4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GPX4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPX4 shows higher tumor expression in KIRP, KIRC, COAD, THCA, LIHC and UCEC. The KIRP box plot shows higher GPX4 RNA expression in tumor versus normal tissue (log2 FC = +0.859, t-test p < 0.001).
This table shows molecular features associated with GPX4 in patient tissues and cancer cell lines. In patient samples, GPX4 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, GPX4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
