Q-omics provides the consensus-scored BVES profile across patient tissues and cancer cell-line models. BVES expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, BVES is differentially expressed in 16, with the highest sampling consensus in KICH. Additionally, BVES RNA expression shows 18,800 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BLCA, KICH, and UVM as cancer lineages where BVES 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 BVES — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BVES survival associations across molecular data types. BVES RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BVES RNA expression–survival associations across cancer types. High BVES expression shows unfavorable associations in BLCA, ACC, LGG, OV and LAML, but favorable associations in KIRC. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify BLCA as the clearest survival context for BVES RNA expression.
This table summarizes BVES tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for BVES. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BVES shows lower tumor expression in KICH, BLCA, COAD, KIRC, THCA and UCEC. The KICH box plot shows higher BVES RNA expression in normal versus tumor tissue (log2 FC = −1.747, t-test p < 0.001).
This table shows molecular features associated with BVES in patient tissues and cancer cell lines. In patient samples, BVES 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, BVES 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 PANCREAS and SOFT_TISSUE.
