Q-omics provides the consensus-scored UBE2F-SCLY profile across patient tissues and cancer cell-line models. UBE2F-SCLY expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, UBE2F-SCLY is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, UBE2F-SCLY RNA expression shows 14,722 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LIHC, and UVM as cancer lineages where UBE2F-SCLY 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 UBE2F-SCLY — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBE2F-SCLY survival associations across molecular data types. UBE2F-SCLY RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UBE2F-SCLY RNA expression–survival associations across cancer types. High UBE2F-SCLY expression shows unfavorable associations in KIRC, KICH, OV, ACC, LUSC and LGG. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for UBE2F-SCLY RNA expression.
This table summarizes UBE2F-SCLY tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for UBE2F-SCLY. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBE2F-SCLY shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, HNSC, BRCA and CHOL. The LIHC box plot shows higher UBE2F-SCLY RNA expression in tumor versus normal tissue (log2 FC = +0.032, t-test p < 0.001).
This table shows molecular features associated with UBE2F-SCLY in patient tissues and cancer cell lines. In patient samples, UBE2F-SCLY 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, UBE2F-SCLY RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE.
