Q-omics provides the consensus-scored PLA2G2A profile across patient tissues and cancer cell-line models. PLA2G2A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PLA2G2A is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PLA2G2A protein abundance shows 16,432 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, HNSC, and BRCA as cancer lineages where PLA2G2A 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 PLA2G2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLA2G2A survival associations across molecular data types. PLA2G2A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLA2G2A RNA expression–survival associations across cancer types. High PLA2G2A expression shows unfavorable associations in KIRC, ACC, LGG, KIRP and KICH, but favorable associations in SKCM. The KIRC 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 KIRC as the clearest survival context for PLA2G2A RNA expression.
This table summarizes PLA2G2A 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 HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PLA2G2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLA2G2A shows lower tumor expression in HNSC, BLCA, UCEC, BRCA, LUSC and LIHC. The HNSC box plot shows higher PLA2G2A RNA expression in normal versus tumor tissue (log2 FC = −4.120, t-test p < 0.001).
This table shows molecular features associated with PLA2G2A in patient tissues and cancer cell lines. In patient samples, PLA2G2A shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, PLA2G2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
