Q-omics provides the consensus-scored BORA profile across patient tissues and cancer cell-line models. BORA expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, BORA is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, BORA RNA expression shows 19,964 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where BORA 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 BORA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BORA survival associations across molecular data types. BORA RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BORA RNA expression–survival associations across cancer types. High BORA expression shows unfavorable associations in ACC, LIHC, KIRP, KICH and LGG, but favorable associations in UCS. The ACC 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 ACC as the clearest survival context for BORA RNA expression.
This table summarizes BORA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for BORA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BORA shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, KIRC, COAD and STAD. The HNSC box plot shows higher BORA RNA expression in tumor versus normal tissue (log2 FC = +1.595, t-test p < 0.001).
This table shows molecular features associated with BORA in patient tissues and cancer cell lines. In patient samples, BORA 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, BORA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SOFT_TISSUE.
