Q-omics provides the consensus-scored B3GLCT profile across patient tissues and cancer cell-line models. B3GLCT expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, B3GLCT is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, B3GLCT protein abundance shows 20,266 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where B3GLCT 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 B3GLCT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes B3GLCT survival associations across molecular data types. B3GLCT RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible B3GLCT RNA expression–survival associations across cancer types. High B3GLCT expression shows unfavorable associations in UVM, PAAD, ACC and MESO, but favorable associations in KIRC and COAD. 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 B3GLCT RNA expression.
This table summarizes B3GLCT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for B3GLCT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. B3GLCT shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, LIHC, COAD and CHOL. The HNSC box plot shows higher B3GLCT RNA expression in tumor versus normal tissue (log2 FC = +1.273, t-test p < 0.001).
This table shows molecular features associated with B3GLCT in patient tissues and cancer cell lines. In patient samples, B3GLCT shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, B3GLCT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
