Q-omics provides the consensus-scored PPP1R3A profile across patient tissues and cancer cell-line models. PPP1R3A expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PPP1R3A is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, PPP1R3A mutation status shows 7,138 significant gene co-expression associations, with the highest sampling consensus in UCEC. Together, these results highlight KIRP, HNSC, and UCEC as cancer lineages where PPP1R3A 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 PPP1R3A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R3A survival associations across molecular data types. PPP1R3A RNA expression shows survival associations in the most cancer types (14), followed by mutation status (11) 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 PPP1R3A RNA expression–survival associations across cancer types. High PPP1R3A expression shows unfavorable associations in KIRP, HNSC, UCS, LUAD and MESO, but favorable associations in CESC. The KIRP 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 KIRP as the clearest survival context for PPP1R3A RNA expression.
This table summarizes PPP1R3A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R3A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R3A shows lower tumor expression in HNSC, LUSC, LUAD, ESCA and STAD. The HNSC box plot shows higher PPP1R3A RNA expression in normal versus tumor tissue (log2 FC = −1.595, t-test p = .001).
This table shows molecular features associated with PPP1R3A in patient tissues and cancer cell lines. In patient samples, PPP1R3A shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R3A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
