Q-omics provides the consensus-scored ADH1A profile across patient tissues and cancer cell-line models. ADH1A expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ADH1A is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, ADH1A protein abundance shows 16,883 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight MESO, KIRC, and UCEC as cancer lineages where ADH1A 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 ADH1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADH1A survival associations across molecular data types. ADH1A RNA expression shows survival associations in the most cancer types (21), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ADH1A RNA expression–survival associations across cancer types. High ADH1A expression shows unfavorable associations in CHOL and LGG, but favorable associations in MESO, PAAD, LUAD and BRCA. The MESO 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 MESO as the clearest survival context for ADH1A RNA expression.
This table summarizes ADH1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, 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 ADH1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADH1A shows lower tumor expression in KIRC, LUAD, THCA, KIRP, LIHC and BRCA. The KIRC box plot shows higher ADH1A RNA expression in normal versus tumor tissue (log2 FC = −0.274, t-test p < 0.001).
This table shows molecular features associated with ADH1A in patient tissues and cancer cell lines. In patient samples, ADH1A shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, ADH1A 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_Myeloma and SKIN.
