Q-omics provides the consensus-scored B4GALNT2 profile across patient tissues and cancer cell-line models. B4GALNT2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, B4GALNT2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, B4GALNT2 RNA expression shows 11,937 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UCEC, KIRC, and KIRP as cancer lineages where B4GALNT2 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 B4GALNT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes B4GALNT2 survival associations across molecular data types. B4GALNT2 RNA expression shows survival associations in the most cancer types (22), 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 B4GALNT2 RNA expression–survival associations across cancer types. High B4GALNT2 expression shows unfavorable associations in UCEC, SKCM, LUAD, STAD, DLBC and LGG. The UCEC 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 UCEC as the clearest survival context for B4GALNT2 RNA expression.
This table summarizes B4GALNT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for B4GALNT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. B4GALNT2 shows lower tumor expression in KIRC, COAD, THCA and KIRP and higher tumor expression in LUAD and LIHC. The KIRC box plot shows higher B4GALNT2 RNA expression in normal versus tumor tissue (log2 FC = −2.683, t-test p < 0.001).
This table shows molecular features associated with B4GALNT2 in patient tissues and cancer cell lines. In patient samples, B4GALNT2 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, B4GALNT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
