Q-omics provides the consensus-scored PCP2 profile across patient tissues and cancer cell-line models. PCP2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PCP2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PCP2 RNA expression shows 16,489 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, KIRC, and THYM as cancer lineages where PCP2 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 PCP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCP2 survival associations across molecular data types. PCP2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCP2 RNA expression–survival associations across cancer types. High PCP2 expression shows unfavorable associations in UCS and COAD, but favorable associations in HNSC, BRCA, LUAD and BLCA. The HNSC 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 HNSC as the clearest survival context for PCP2 RNA expression.
This table summarizes PCP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PCP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCP2 shows lower tumor expression in KIRC and KIRP and higher tumor expression in COAD, BRCA, BLCA and STAD. The KIRC box plot shows higher PCP2 RNA expression in normal versus tumor tissue (log2 FC = −0.814, t-test p < 0.001).
This table shows molecular features associated with PCP2 in patient tissues and cancer cell lines. In patient samples, PCP2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PCP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
