Q-omics provides the consensus-scored PPP1R10 profile across patient tissues and cancer cell-line models. PPP1R10 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PPP1R10 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, PPP1R10 protein abundance shows 29,516 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, THCA, and LSCC as cancer lineages where PPP1R10 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 PPP1R10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R10 survival associations across molecular data types. PPP1R10 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 PPP1R10 RNA expression–survival associations across cancer types. High PPP1R10 expression shows unfavorable associations in UVM and ACC, but favorable associations in KIRC, SCLC, READ and PAAD. The KIRC 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 KIRC as the clearest survival context for PPP1R10 RNA expression.
This table summarizes PPP1R10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R10 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, STAD and BRCA. The THCA box plot shows higher PPP1R10 RNA expression in normal versus tumor tissue (log2 FC = −0.864, t-test p < 0.001).
This table shows molecular features associated with PPP1R10 in patient tissues and cancer cell lines. In patient samples, PPP1R10 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, PPP1R10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
