Q-omics provides the consensus-scored B4GAT1 profile across patient tissues and cancer cell-line models. B4GAT1 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, B4GAT1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, B4GAT1 RNA expression shows 19,401 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where B4GAT1 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 B4GAT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes B4GAT1 survival associations across molecular data types. B4GAT1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible B4GAT1 RNA expression–survival associations across cancer types. High B4GAT1 expression shows unfavorable associations in KICH, BLCA and COAD, but favorable associations in KIRC, MESO and PAAD. 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 B4GAT1 RNA expression.
This table summarizes B4GAT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for B4GAT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. B4GAT1 shows lower tumor expression in LUAD, KICH and LUSC and higher tumor expression in KIRC, LIHC and HNSC. The KIRC box plot shows higher B4GAT1 RNA expression in tumor versus normal tissue (log2 FC = +0.571, t-test p < 0.001).
This table shows molecular features associated with B4GAT1 in patient tissues and cancer cell lines. In patient samples, B4GAT1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, B4GAT1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
