Q-omics provides the consensus-scored PCDHGB4 profile across patient tissues and cancer cell-line models. PCDHGB4 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, PCDHGB4 is differentially expressed in 10, with the highest sampling consensus in UCEC. Additionally, PCDHGB4 RNA expression shows 15,910 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUSC, UCEC, and THYM as cancer lineages where PCDHGB4 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 PCDHGB4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCDHGB4 survival associations across molecular data types. PCDHGB4 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCDHGB4 RNA expression–survival associations across cancer types. High PCDHGB4 expression shows unfavorable associations in LUSC, CESC, HNSC and BLCA, but favorable associations in KIRC and DLBC. The LUSC 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 LUSC as the clearest survival context for PCDHGB4 RNA expression.
This table summarizes PCDHGB4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for PCDHGB4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCDHGB4 shows lower tumor expression in UCEC, KICH, LUSC, KIRC, BRCA and STAD. The UCEC box plot shows higher PCDHGB4 RNA expression in normal versus tumor tissue (log2 FC = −0.881, t-test p < 0.001).
This table shows molecular features associated with PCDHGB4 in patient tissues and cancer cell lines. In patient samples, PCDHGB4 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, PCDHGB4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in SKIN.
