Q-omics provides the consensus-scored PPP1CA profile across patient tissues and cancer cell-line models. PPP1CA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPP1CA is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PPP1CA RNA expression shows 19,209 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where PPP1CA 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 PPP1CA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1CA survival associations across molecular data types. PPP1CA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) 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 PPP1CA RNA expression–survival associations across cancer types. High PPP1CA expression shows unfavorable associations in ACC, KICH, HNSC, LGG and UVM, but favorable associations in SCLC. 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 PPP1CA RNA expression.
This table summarizes PPP1CA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PPP1CA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1CA shows higher tumor expression in HNSC, LIHC, BLCA, LUSC, KIRC and LUAD. The HNSC box plot shows higher PPP1CA RNA expression in tumor versus normal tissue (log2 FC = +0.709, t-test p < 0.001).
This table shows molecular features associated with PPP1CA in patient tissues and cancer cell lines. In patient samples, PPP1CA 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, PPP1CA 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 PANCREAS and BLOOD_Leukemia.
