Q-omics provides the consensus-scored PPP1R1C profile across patient tissues and cancer cell-line models. PPP1R1C expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, PPP1R1C is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PPP1R1C RNA expression shows 13,631 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight STAD, HNSC, and THYM as cancer lineages where PPP1R1C 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 PPP1R1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R1C survival associations across molecular data types. PPP1R1C RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R1C RNA expression–survival associations across cancer types. High PPP1R1C expression shows unfavorable associations in STAD, BLCA, LGG, COAD and LUAD, but favorable associations in THYM. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify STAD as the clearest survival context for PPP1R1C RNA expression.
This table summarizes PPP1R1C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PPP1R1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R1C shows lower tumor expression in KIRC and LIHC and higher tumor expression in HNSC, BLCA, THCA and BRCA. The HNSC box plot shows higher PPP1R1C RNA expression in tumor versus normal tissue (log2 FC = +1.023, t-test p < 0.001).
This table shows molecular features associated with PPP1R1C in patient tissues and cancer cell lines. In patient samples, PPP1R1C shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R1C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
