Q-omics provides the consensus-scored B4GALT6 profile across patient tissues and cancer cell-line models. B4GALT6 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, B4GALT6 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, B4GALT6 RNA expression shows 19,442 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LUAD, KIRC, and UVM as cancer lineages where B4GALT6 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 B4GALT6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes B4GALT6 survival associations across molecular data types. B4GALT6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible B4GALT6 RNA expression–survival associations across cancer types. High B4GALT6 expression shows unfavorable associations in LUAD, LIHC and UVM, but favorable associations in UCS, PAAD and COAD. The LUAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify LUAD as the clearest survival context for B4GALT6 RNA expression.
This table summarizes B4GALT6 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 LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for B4GALT6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. B4GALT6 shows lower tumor expression in KIRC, BRCA and KIRP and higher tumor expression in LIHC, THCA and KICH. The KIRC box plot shows higher B4GALT6 RNA expression in normal versus tumor tissue (log2 FC = −0.673, t-test p < 0.001).
This table shows molecular features associated with B4GALT6 in patient tissues and cancer cell lines. In patient samples, B4GALT6 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, B4GALT6 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 URINARY_TRACT and BLOOD_Leukemia.
