Q-omics provides the consensus-scored UBE2Q1 profile across patient tissues and cancer cell-line models. UBE2Q1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, UBE2Q1 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, UBE2Q1 RNA expression shows 18,772 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where UBE2Q1 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 UBE2Q1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBE2Q1 survival associations across molecular data types. UBE2Q1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 UBE2Q1 RNA expression–survival associations across cancer types. High UBE2Q1 expression shows unfavorable associations in KIRP, ACC, LIHC, LAML, HNSC and ESCA. The KIRP 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 KIRP as the clearest survival context for UBE2Q1 RNA expression.
This table summarizes UBE2Q1 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for UBE2Q1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBE2Q1 shows higher tumor expression in HNSC, KIRC, BLCA, LIHC, STAD and LUAD. The HNSC box plot shows higher UBE2Q1 RNA expression in tumor versus normal tissue (log2 FC = +1.074, t-test p < 0.001).
This table shows molecular features associated with UBE2Q1 in patient tissues and cancer cell lines. In patient samples, UBE2Q1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, UBE2Q1 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 LUNG_SCLC and BLOOD_Leukemia.
