Q-omics provides the consensus-scored PLA2G4D profile across patient tissues and cancer cell-line models. PLA2G4D expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PLA2G4D is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PLA2G4D RNA expression shows 13,205 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SKCM, KIRC, and ACC as cancer lineages where PLA2G4D 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 PLA2G4D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLA2G4D survival associations across molecular data types. PLA2G4D RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLA2G4D RNA expression–survival associations across cancer types. High PLA2G4D expression shows unfavorable associations in SKCM, KIRC, LIHC and KIRP, but favorable associations in LUAD and PRAD. The SKCM 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 SKCM as the clearest survival context for PLA2G4D RNA expression.
This table summarizes PLA2G4D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PLA2G4D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLA2G4D shows lower tumor expression in PRAD and higher tumor expression in KIRC, LUAD, BRCA, LUSC and COAD. The KIRC box plot shows higher PLA2G4D RNA expression in tumor versus normal tissue (log2 FC = +0.291, t-test p < 0.001).
This table shows molecular features associated with PLA2G4D in patient tissues and cancer cell lines. In patient samples, PLA2G4D shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PLA2G4D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
