Q-omics provides the consensus-scored PPP1R14C profile across patient tissues and cancer cell-line models. PPP1R14C expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PPP1R14C is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PPP1R14C RNA expression shows 17,793 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UVM, HNSC, and KIRP as cancer lineages where PPP1R14C 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 PPP1R14C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R14C survival associations across molecular data types. PPP1R14C RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R14C RNA expression–survival associations across cancer types. High PPP1R14C expression shows unfavorable associations in UVM, ACC, BRCA, HNSC and LIHC, but favorable associations in THCA. The UVM 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 UVM as the clearest survival context for PPP1R14C RNA expression.
This table summarizes PPP1R14C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R14C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R14C shows lower tumor expression in KICH, LUAD and THCA and higher tumor expression in HNSC, BLCA and KIRP. The HNSC box plot shows higher PPP1R14C RNA expression in tumor versus normal tissue (log2 FC = +2.239, t-test p < 0.001).
This table shows molecular features associated with PPP1R14C in patient tissues and cancer cell lines. In patient samples, PPP1R14C shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R14C 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 OESOPHAGUS and LUNG_NSCLC_LUAD.
