Q-omics provides the consensus-scored UGT2B10 profile across patient tissues and cancer cell-line models. UGT2B10 expression is associated with patient survival in 12 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, UGT2B10 is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, UGT2B10 RNA expression shows 8,780 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight COAD, LIHC, and TGCT as cancer lineages where UGT2B10 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 UGT2B10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UGT2B10 survival associations across molecular data types. UGT2B10 RNA expression shows survival associations in the most cancer types (12), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UGT2B10 RNA expression–survival associations across cancer types. High UGT2B10 expression shows unfavorable associations in CHOL and LGG, but favorable associations in COAD, LIHC, READ and BLCA. The COAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify COAD as the clearest survival context for UGT2B10 RNA expression.
This table summarizes UGT2B10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for UGT2B10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UGT2B10 shows lower tumor expression in LIHC, CHOL, COAD and KICH and higher tumor expression in LUAD. The LIHC box plot shows higher UGT2B10 RNA expression in normal versus tumor tissue (log2 FC = −2.239, t-test p < 0.001).
This table shows molecular features associated with UGT2B10 in patient tissues and cancer cell lines. In patient samples, UGT2B10 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, UGT2B10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
