Q-omics provides the consensus-scored PPP2R3C profile across patient tissues and cancer cell-line models. PPP2R3C expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPP2R3C is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, PPP2R3C RNA expression shows 19,171 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where PPP2R3C 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 PPP2R3C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP2R3C survival associations across molecular data types. PPP2R3C RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP2R3C RNA expression–survival associations across cancer types. High PPP2R3C expression shows unfavorable associations in ACC, STAD, LIHC and UVM, but favorable associations in UCEC and LUAD. 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 PPP2R3C RNA expression.
This table summarizes PPP2R3C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPP2R3C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP2R3C shows lower tumor expression in LUSC, THCA and COAD and higher tumor expression in LIHC, HNSC and CHOL. The LIHC box plot shows higher PPP2R3C RNA expression in tumor versus normal tissue (log2 FC = +0.800, t-test p < 0.001).
This table shows molecular features associated with PPP2R3C in patient tissues and cancer cell lines. In patient samples, PPP2R3C shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP2R3C 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
