Q-omics provides the consensus-scored PPP4R3A profile across patient tissues and cancer cell-line models. PPP4R3A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPP4R3A is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PPP4R3A protein abundance shows 23,483 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PPP4R3A 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 PPP4R3A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP4R3A survival associations across molecular data types. PPP4R3A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 PPP4R3A RNA expression–survival associations across cancer types. High PPP4R3A expression shows unfavorable associations in ACC, UVM and HNSC, but favorable associations in KIRC, UCS and THYM. The ACC 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 ACC as the clearest survival context for PPP4R3A RNA expression.
This table summarizes PPP4R3A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPP4R3A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP4R3A shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, LIHC, STAD and CHOL. The HNSC box plot shows higher PPP4R3A RNA expression in tumor versus normal tissue (log2 FC = +0.481, t-test p < 0.001).
This table shows molecular features associated with PPP4R3A in patient tissues and cancer cell lines. In patient samples, PPP4R3A 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, PPP4R3A 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 BLOOD_Leukemia and LARGE_INTESTINE.
