Q-omics provides the consensus-scored UBE2T profile across patient tissues and cancer cell-line models. UBE2T 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, UBE2T is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, UBE2T protein abundance shows 32,259 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where UBE2T 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 UBE2T — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBE2T survival associations across molecular data types. UBE2T RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UBE2T RNA expression–survival associations across cancer types. High UBE2T expression shows unfavorable associations in ACC, KIRP, KIRC, MESO, KICH and LUAD. 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 UBE2T RNA expression.
This table summarizes UBE2T tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for UBE2T. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBE2T shows higher tumor expression in HNSC, LUAD, KIRP, BLCA, COAD and KIRC. The HNSC box plot shows higher UBE2T RNA expression in tumor versus normal tissue (log2 FC = +2.285, t-test p < 0.001).
This table shows molecular features associated with UBE2T in patient tissues and cancer cell lines. In patient samples, UBE2T shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, UBE2T RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
