Q-omics provides the consensus-scored LGALS3BP profile across patient tissues and cancer cell-line models. LGALS3BP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, LGALS3BP is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, LGALS3BP protein abundance shows 17,668 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, HNSC, and BRCA as cancer lineages where LGALS3BP 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 LGALS3BP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LGALS3BP survival associations across molecular data types. LGALS3BP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LGALS3BP RNA expression–survival associations across cancer types. High LGALS3BP expression shows unfavorable associations in KIRC, KIRP, LGG and HNSC, but favorable associations in ACC and MESO. 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 LGALS3BP RNA expression.
This table summarizes LGALS3BP 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 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for LGALS3BP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LGALS3BP shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRP, KIRC, STAD and LUAD. The HNSC box plot shows higher LGALS3BP RNA expression in tumor versus normal tissue (log2 FC = +1.982, t-test p < 0.001).
This table shows molecular features associated with LGALS3BP in patient tissues and cancer cell lines. In patient samples, LGALS3BP shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, LGALS3BP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
