gap junction protein beta 6Genealiases: CX30 · DFNA3 · DFNA3B · DFNB1B · ECTD2 · ED2
Q-omics provides the consensus-scored GJB6 profile across patient tissues and cancer cell-line models. GJB6 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GJB6 is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, GJB6 RNA expression shows 16,850 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, THCA, and GBM as cancer lineages where GJB6 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 GJB6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GJB6 survival associations across molecular data types. GJB6 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GJB6 RNA expression–survival associations across cancer types. High GJB6 expression shows unfavorable associations in KIRC, COAD, ACC and OV, but favorable associations in THYM and LAML. The KIRC 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 KIRC as the clearest survival context for GJB6 RNA expression.
This table summarizes GJB6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for GJB6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GJB6 shows lower tumor expression in THCA and KICH and higher tumor expression in LUSC, BLCA, LUAD and READ. The THCA box plot shows higher GJB6 RNA expression in normal versus tumor tissue (log2 FC = −2.935, t-test p < 0.001).
This table shows molecular features associated with GJB6 in patient tissues and cancer cell lines. In patient samples, GJB6 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, GJB6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BONE and URINARY_TRACT.
