Q-omics provides the consensus-scored PPP1R12C profile across patient tissues and cancer cell-line models. PPP1R12C expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPP1R12C is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, PPP1R12C protein abundance shows 38,542 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, LIHC, and LSCC as cancer lineages where PPP1R12C 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 PPP1R12C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R12C survival associations across molecular data types. PPP1R12C RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R12C RNA expression–survival associations across cancer types. High PPP1R12C expression shows unfavorable associations in ACC, MESO, LIHC, LGG and LAML, but favorable associations in PAAD. 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 PPP1R12C RNA expression.
This table summarizes PPP1R12C 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 10. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R12C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R12C shows lower tumor expression in BLCA, LUAD, COAD and UCEC and higher tumor expression in LIHC and HNSC. The LIHC box plot shows higher PPP1R12C RNA expression in tumor versus normal tissue (log2 FC = +1.186, t-test p < 0.001).
This table shows molecular features associated with PPP1R12C in patient tissues and cancer cell lines. In patient samples, PPP1R12C shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R12C 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 SOFT_TISSUE and LARGE_INTESTINE.
