Q-omics provides the consensus-scored PC profile across patient tissues and cancer cell-line models. PC expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, PC is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, PC RNA expression shows 19,438 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight OV, KICH, and ACC as cancer lineages where PC 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 PC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PC survival associations across molecular data types. PC RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) 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 PC RNA expression–survival associations across cancer types. High PC expression shows unfavorable associations in OV, MESO and ACC, but favorable associations in UVM, THCA and LGG. The OV 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 OV as the clearest survival context for PC RNA expression.
This table summarizes PC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PC shows lower tumor expression in KICH and COAD and higher tumor expression in LUAD, THCA, HNSC and LUSC. The KICH box plot shows higher PC RNA expression in normal versus tumor tissue (log2 FC = −2.612, t-test p < 0.001).
This table shows molecular features associated with PC in patient tissues and cancer cell lines. In patient samples, PC 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, PC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
