Q-omics provides the consensus-scored PCDHB9 profile across patient tissues and cancer cell-line models. PCDHB9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PCDHB9 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PCDHB9 RNA expression shows 14,670 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, HNSC, and TGCT as cancer lineages where PCDHB9 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 PCDHB9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCDHB9 survival associations across molecular data types. PCDHB9 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCDHB9 RNA expression–survival associations across cancer types. High PCDHB9 expression shows unfavorable associations in BRCA, BLCA, MESO and THYM, but favorable associations in UVM and DLBC. The UVM 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 UVM as the clearest survival context for PCDHB9 RNA expression.
This table summarizes PCDHB9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PCDHB9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCDHB9 shows higher tumor expression in HNSC, KIRC, COAD, KIRP, STAD and LUSC. The HNSC box plot shows higher PCDHB9 RNA expression in tumor versus normal tissue (log2 FC = +0.830, t-test p < 0.001).
This table shows molecular features associated with PCDHB9 in patient tissues and cancer cell lines. In patient samples, PCDHB9 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, PCDHB9 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.
