Q-omics provides the consensus-scored BIVM profile across patient tissues and cancer cell-line models. BIVM expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, BIVM is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, BIVM RNA expression shows 19,582 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ESCA, KIRC, and UVM as cancer lineages where BIVM 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 BIVM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BIVM survival associations across molecular data types. BIVM RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BIVM RNA expression–survival associations across cancer types. High BIVM expression shows unfavorable associations in ESCA, UVM, HNSC and STAD, but favorable associations in KIRP and LGG. The ESCA 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 ESCA as the clearest survival context for BIVM RNA expression.
This table summarizes BIVM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for BIVM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BIVM shows lower tumor expression in KICH, THCA and UCEC and higher tumor expression in KIRC, KIRP and HNSC. The KIRC box plot shows higher BIVM RNA expression in tumor versus normal tissue (log2 FC = +0.996, t-test p < 0.001).
This table shows molecular features associated with BIVM in patient tissues and cancer cell lines. In patient samples, BIVM 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, BIVM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
