Q-omics provides the consensus-scored PPP1R2C profile across patient tissues and cancer cell-line models. PPP1R2C expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PPP1R2C is differentially expressed in 2, with the highest sampling consensus in THCA. Additionally, PPP1R2C RNA expression shows 7,675 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SKCM, THCA, and TGCT as cancer lineages where PPP1R2C 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 PPP1R2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R2C survival associations across molecular data types. PPP1R2C RNA expression shows survival associations in the most cancer types (17), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R2C RNA expression–survival associations across cancer types. High PPP1R2C expression shows unfavorable associations in HNSC, UCS and ACC, but favorable associations in SKCM, CESC and STAD. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for PPP1R2C RNA expression.
This table summarizes PPP1R2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R2C shows lower tumor expression in THCA and UCEC. The THCA box plot shows higher PPP1R2C RNA expression in normal versus tumor tissue (log2 FC = −0.106, t-test p = .019).
This table shows molecular features associated with PPP1R2C in patient tissues and cancer cell lines. In patient samples, PPP1R2C shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
