Q-omics provides the consensus-scored BRCC3 profile across patient tissues and cancer cell-line models. BRCC3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, BRCC3 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, BRCC3 RNA expression shows 19,735 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where BRCC3 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 BRCC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BRCC3 survival associations across molecular data types. BRCC3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BRCC3 RNA expression–survival associations across cancer types. High BRCC3 expression shows unfavorable associations in PAAD, LGG and LIHC, but favorable associations in KIRC, SKCM and BRCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for BRCC3 RNA expression.
This table summarizes BRCC3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for BRCC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BRCC3 shows lower tumor expression in KIRC and THCA and higher tumor expression in LUAD, COAD, LIHC and UCEC. The KIRC box plot shows higher BRCC3 RNA expression in normal versus tumor tissue (log2 FC = −1.098, t-test p < 0.001).
This table shows molecular features associated with BRCC3 in patient tissues and cancer cell lines. In patient samples, BRCC3 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, BRCC3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Lymphoma.
