Q-omics provides the consensus-scored PPP4R3C profile across patient tissues and cancer cell-line models. PPP4R3C expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PPP4R3C is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, PPP4R3C RNA expression shows 7,888 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, LIHC, and TGCT as cancer lineages where PPP4R3C 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 PPP4R3C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP4R3C survival associations across molecular data types. PPP4R3C RNA expression shows survival associations in the most cancer types (16), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP4R3C RNA expression–survival associations across cancer types. High PPP4R3C expression shows unfavorable associations in KIRC, THCA, KICH, READ, UCS and KIRP. The KIRC 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 KIRC as the clearest survival context for PPP4R3C RNA expression.
This table summarizes PPP4R3C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PPP4R3C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP4R3C shows higher tumor expression in LIHC, LUSC, HNSC, BRCA and LUAD. The LIHC box plot shows higher PPP4R3C RNA expression in tumor versus normal tissue (log2 FC = +0.829, t-test p < 0.001).
This table shows molecular features associated with PPP4R3C in patient tissues and cancer cell lines. In patient samples, PPP4R3C shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP4R3C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma.
