Q-omics provides the consensus-scored UBTF profile across patient tissues and cancer cell-line models. UBTF expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, UBTF is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, UBTF protein abundance shows 29,970 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BRCA, HNSC, and GBM as cancer lineages where UBTF 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 UBTF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBTF survival associations across molecular data types. UBTF RNA expression shows survival associations in the most cancer types (20), followed by mutation status (8) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UBTF RNA expression–survival associations across cancer types. High UBTF expression shows unfavorable associations in ACC and LIHC, but favorable associations in BRCA, KIRC, THYM and HNSC. The BRCA 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 BRCA as the clearest survival context for UBTF RNA expression.
This table summarizes UBTF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for UBTF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBTF shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, LIHC, STAD and LUSC. The HNSC box plot shows higher UBTF RNA expression in tumor versus normal tissue (log2 FC = +0.697, t-test p < 0.001).
This table shows molecular features associated with UBTF in patient tissues and cancer cell lines. In patient samples, UBTF 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, UBTF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
