Q-omics provides the consensus-scored PPP2R2C profile across patient tissues and cancer cell-line models. PPP2R2C expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PPP2R2C is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PPP2R2C RNA expression shows 21,700 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where PPP2R2C 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 PPP2R2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP2R2C survival associations across molecular data types. PPP2R2C RNA expression shows survival associations in the most cancer types (20), followed by mutation status (9) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP2R2C RNA expression–survival associations across cancer types. High PPP2R2C expression shows unfavorable associations in KIRC, LUAD, LIHC and UVM, but favorable associations in UCEC and ACC. The KIRC 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 KIRC as the clearest survival context for PPP2R2C RNA expression.
This table summarizes PPP2R2C 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 HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPP2R2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP2R2C shows higher tumor expression in HNSC, LUAD, LUSC, KIRP, BRCA and LIHC. The HNSC box plot shows higher PPP2R2C RNA expression in tumor versus normal tissue (log2 FC = +1.227, t-test p < 0.001).
This table shows molecular features associated with PPP2R2C in patient tissues and cancer cell lines. In patient samples, PPP2R2C 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, PPP2R2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
