Q-omics provides the consensus-scored PPP1R14D profile across patient tissues and cancer cell-line models. PPP1R14D expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PPP1R14D is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, PPP1R14D RNA expression shows 13,715 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, COAD, and ESCA as cancer lineages where PPP1R14D 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 PPP1R14D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R14D survival associations across molecular data types. PPP1R14D RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 PPP1R14D RNA expression–survival associations across cancer types. High PPP1R14D expression shows unfavorable associations in UVM, DLBC and PAAD, but favorable associations in KIRC, HNSC and THCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for PPP1R14D RNA expression.
This table summarizes PPP1R14D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R14D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R14D shows lower tumor expression in COAD and KIRP and higher tumor expression in KIRC, LUAD, BLCA and LIHC. The COAD box plot shows higher PPP1R14D RNA expression in normal versus tumor tissue (log2 FC = −2.135, t-test p < 0.001).
This table shows molecular features associated with PPP1R14D in patient tissues and cancer cell lines. In patient samples, PPP1R14D shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R14D 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 BONE and LARGE_INTESTINE.
