Q-omics provides the consensus-scored GJA4 profile across patient tissues and cancer cell-line models. GJA4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GJA4 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, GJA4 RNA expression shows 16,626 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where GJA4 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 GJA4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GJA4 survival associations across molecular data types. GJA4 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 GJA4 RNA expression–survival associations across cancer types. High GJA4 expression shows unfavorable associations in UVM, KIRP, BLCA and COAD, but favorable associations in KIRC and LIHC. The KIRC 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 KIRC as the clearest survival context for GJA4 RNA expression.
This table summarizes GJA4 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for GJA4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GJA4 shows lower tumor expression in KICH, LUSC, LUAD and KIRP and higher tumor expression in KIRC and COAD. The KIRC box plot shows higher GJA4 RNA expression in tumor versus normal tissue (log2 FC = +1.687, t-test p < 0.001).
This table shows molecular features associated with GJA4 in patient tissues and cancer cell lines. In patient samples, GJA4 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, GJA4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Myeloma.
