Q-omics provides the consensus-scored PCDHA9 profile across patient tissues and cancer cell-line models. PCDHA9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, PCDHA9 is differentially expressed in 5, with the highest sampling consensus in CHOL. Additionally, PCDHA9 RNA expression shows 11,535 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UCS, CHOL, and TGCT as cancer lineages where PCDHA9 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 PCDHA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCDHA9 survival associations across molecular data types. PCDHA9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (13) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCDHA9 RNA expression–survival associations across cancer types. High PCDHA9 expression shows unfavorable associations in UCEC, LUSC, HNSC, ESCA and BRCA, but favorable associations in UCS. The UCS 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 UCS as the clearest survival context for PCDHA9 RNA expression.
This table summarizes PCDHA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 1. The strongest signals are observed in CHOL for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PCDHA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCDHA9 shows lower tumor expression in LUSC and higher tumor expression in CHOL, LUAD, PAAD and PRAD. The CHOL box plot shows higher PCDHA9 RNA expression in tumor versus normal tissue (log2 FC = +0.053, t-test p = .032).
This table shows molecular features associated with PCDHA9 in patient tissues and cancer cell lines. In patient samples, PCDHA9 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, PCDHA9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
