Q-omics provides the consensus-scored BRD3 profile across patient tissues and cancer cell-line models. BRD3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, BRD3 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, BRD3 protein abundance shows 22,031 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where BRD3 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 BRD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BRD3 survival associations across molecular data types. BRD3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) 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 BRD3 RNA expression–survival associations across cancer types. High BRD3 expression shows unfavorable associations in ACC and COAD, but favorable associations in KIRC, HNSC, UCS and LGG. 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 BRD3 RNA expression.
This table summarizes BRD3 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 4. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for BRD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BRD3 shows lower tumor expression in THCA and KIRC and higher tumor expression in HNSC, COAD, LIHC and BRCA. The HNSC box plot shows higher BRD3 RNA expression in tumor versus normal tissue (log2 FC = +1.034, t-test p < 0.001).
This table shows molecular features associated with BRD3 in patient tissues and cancer cell lines. In patient samples, BRD3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, BRD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
