Q-omics provides the consensus-scored PCDHGA3 profile across patient tissues and cancer cell-line models. PCDHGA3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, PCDHGA3 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PCDHGA3 RNA expression shows 16,270 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight BLCA, KIRC, and THYM as cancer lineages where PCDHGA3 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 PCDHGA3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCDHGA3 survival associations across molecular data types. PCDHGA3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (11) 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 PCDHGA3 RNA expression–survival associations across cancer types. High PCDHGA3 expression shows unfavorable associations in BLCA, STAD and READ, but favorable associations in UCS, ESCA and SKCM. The BLCA 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 BLCA as the clearest survival context for PCDHGA3 RNA expression.
This table summarizes PCDHGA3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PCDHGA3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCDHGA3 shows lower tumor expression in KIRC, UCEC, LUSC, BLCA, KIRP and BRCA. The KIRC box plot shows higher PCDHGA3 RNA expression in normal versus tumor tissue (log2 FC = −0.508, t-test p < 0.001).
This table shows molecular features associated with PCDHGA3 in patient tissues and cancer cell lines. In patient samples, PCDHGA3 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, PCDHGA3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
