Q-omics provides the consensus-scored PPP2R2A profile across patient tissues and cancer cell-line models. PPP2R2A expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPP2R2A is differentially expressed in 10, with the highest sampling consensus in CHOL. Additionally, PPP2R2A protein abundance shows 19,574 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, CHOL, and PDAC as cancer lineages where PPP2R2A 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 PPP2R2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP2R2A survival associations across molecular data types. PPP2R2A RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP2R2A RNA expression–survival associations across cancer types. High PPP2R2A expression shows unfavorable associations in ACC, PAAD, KIRP and LIHC, but favorable associations in KIRC and COAD. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify ACC as the clearest survival context for PPP2R2A RNA expression.
This table summarizes PPP2R2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in READ for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPP2R2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP2R2A shows lower tumor expression in KICH and higher tumor expression in CHOL, READ, COAD, LUAD and STAD. The CHOL box plot shows higher PPP2R2A RNA expression in tumor versus normal tissue (log2 FC = +1.385, t-test p < 0.001).
This table shows molecular features associated with PPP2R2A in patient tissues and cancer cell lines. In patient samples, PPP2R2A shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP2R2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BONE.
