Q-omics provides the consensus-scored PPP3CC profile across patient tissues and cancer cell-line models. PPP3CC expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PPP3CC is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, PPP3CC protein abundance shows 24,694 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, BLCA, and GBM as cancer lineages where PPP3CC 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 PPP3CC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP3CC survival associations across molecular data types. PPP3CC RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) 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 PPP3CC RNA expression–survival associations across cancer types. High PPP3CC expression shows unfavorable associations in SCLC, ACC and KICH, but favorable associations in SKCM, KIRC and LUAD. The SKCM 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 SKCM as the clearest survival context for PPP3CC RNA expression.
This table summarizes PPP3CC 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 4. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPP3CC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP3CC shows lower tumor expression in BLCA, LUAD, THCA, LUSC and BRCA and higher tumor expression in KIRC. The BLCA box plot shows higher PPP3CC RNA expression in normal versus tumor tissue (log2 FC = −0.573, t-test p < 0.001).
This table shows molecular features associated with PPP3CC in patient tissues and cancer cell lines. In patient samples, PPP3CC shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP3CC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
