AU RNA binding methylglutaconyl-CoA hydrataseGenealiases: []
Q-omics provides the consensus-scored AUH profile across patient tissues and cancer cell-line models. AUH expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AUH is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, AUH protein abundance shows 26,028 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where AUH 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 AUH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AUH survival associations across molecular data types. AUH RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AUH RNA expression–survival associations across cancer types. High AUH expression shows unfavorable associations in LGG and UVM, but favorable associations in KIRC, KIRP, MESO and SKCM. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for AUH RNA expression.
This table summarizes AUH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AUH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AUH shows lower tumor expression in KIRC, KIRP, THCA, COAD, BRCA and LUAD. The KIRC box plot shows higher AUH RNA expression in normal versus tumor tissue (log2 FC = −1.236, t-test p < 0.001).
This table shows molecular features associated with AUH in patient tissues and cancer cell lines. In patient samples, AUH shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, AUH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
