Q-omics provides the consensus-scored UGT2A2 profile across patient tissues and cancer cell-line models. UGT2A2 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in COAD. Additionally, UGT2A2 RNA expression shows 3,873 significant gene co-expression associations, with the highest sampling consensus in HNSC. Together, these results highlight COAD, and HNSC as cancer lineages where UGT2A2 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 UGT2A2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UGT2A2 survival associations across molecular data types. UGT2A2 RNA expression shows survival associations in the most cancer types (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UGT2A2 RNA expression–survival associations across cancer types. High UGT2A2 expression shows unfavorable associations in COAD, STAD, TGCT, KICH, LIHC and THCA. The COAD 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 COAD as the clearest survival context for UGT2A2 RNA expression.
This table shows molecular features associated with UGT2A2 in patient tissues and cancer cell lines. In patient samples, UGT2A2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, UGT2A2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC.
