Q-omics provides the consensus-scored NRBF2 profile across patient tissues and cancer cell-line models. NRBF2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, NRBF2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, NRBF2 protein abundance shows 24,378 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, and HNSC as cancer lineages where NRBF2 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 NRBF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NRBF2 survival associations across molecular data types. NRBF2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NRBF2 RNA expression–survival associations across cancer types. High NRBF2 expression shows unfavorable associations in UVM, BLCA, ACC, CESC and KIRP, but favorable associations in KIRC. The UVM 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 UVM as the clearest survival context for NRBF2 RNA expression.
This table summarizes NRBF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NRBF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NRBF2 shows lower tumor expression in THCA and BRCA and higher tumor expression in HNSC, KIRC, STAD and BLCA. The HNSC box plot shows higher NRBF2 RNA expression in tumor versus normal tissue (log2 FC = +1.336, t-test p < 0.001).
This table shows molecular features associated with NRBF2 in patient tissues and cancer cell lines. In patient samples, NRBF2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, NRBF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
