gap junction protein alpha 9Genealiases: CX58 · CX59 · GJA10
Q-omics provides the consensus-scored GJA9 profile across patient tissues and cancer cell-line models. GJA9 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in THCA. Among the 18 cancer types available for tumor–normal comparison, GJA9 is differentially expressed in 7, with the highest sampling consensus in STAD. Additionally, GJA9 RNA expression shows 14,325 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight THCA, STAD, and UVM as cancer lineages where GJA9 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 GJA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GJA9 survival associations across molecular data types. GJA9 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GJA9 RNA expression–survival associations across cancer types. High GJA9 expression shows unfavorable associations in THCA, UVM, COAD, LGG, KICH and DLBC. The THCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify THCA as the clearest survival context for GJA9 RNA expression.
This table summarizes GJA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in STAD for RNA.
This table ranks reproducible tumor–normal expression differences for GJA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GJA9 shows lower tumor expression in PAAD and READ and higher tumor expression in STAD, CHOL, PRAD and LIHC. The STAD box plot shows higher GJA9 RNA expression in tumor versus normal tissue (log2 FC = +0.065, t-test p = .001).
This table shows molecular features associated with GJA9 in patient tissues and cancer cell lines. In patient samples, GJA9 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GJA9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and UPPER_AERODIGESTIVE_TRACT.
