Q-omics provides the consensus-scored PPP1R3D profile across patient tissues and cancer cell-line models. PPP1R3D 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, PPP1R3D is differentially expressed in 10, with the highest sampling consensus in LUSC. Additionally, PPP1R3D RNA expression shows 19,994 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LUSC, and UVM as cancer lineages where PPP1R3D 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 PPP1R3D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R3D survival associations across molecular data types. PPP1R3D RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R3D RNA expression–survival associations across cancer types. High PPP1R3D expression shows unfavorable associations in UVM and LGG, but favorable associations in KIRC, HNSC, CESC and LUSC. 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 PPP1R3D RNA expression.
This table summarizes PPP1R3D 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 3. The strongest signals are observed in LUSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R3D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R3D shows lower tumor expression in UCEC and THCA and higher tumor expression in LUSC, BRCA, LIHC and BLCA. The LUSC box plot shows higher PPP1R3D RNA expression in tumor versus normal tissue (log2 FC = +0.926, t-test p < 0.001).
This table shows molecular features associated with PPP1R3D in patient tissues and cancer cell lines. In patient samples, PPP1R3D shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R3D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
