Q-omics provides the consensus-scored ADH1B profile across patient tissues and cancer cell-line models. ADH1B expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ADH1B is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, ADH1B protein abundance shows 27,753 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight MESO, COAD, and LUAD as cancer lineages where ADH1B 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 ADH1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADH1B survival associations across molecular data types. ADH1B RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ADH1B RNA expression–survival associations across cancer types. High ADH1B expression shows unfavorable associations in OV, KIRP and BLCA, but favorable associations in MESO, LIHC 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 ADH1B RNA expression.
This table summarizes ADH1B 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ADH1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADH1B shows lower tumor expression in COAD, KIRC, HNSC, BLCA, LUAD and KICH. The COAD box plot shows higher ADH1B RNA expression in normal versus tumor tissue (log2 FC = −4.748, t-test p < 0.001).
This table shows molecular features associated with ADH1B in patient tissues and cancer cell lines. In patient samples, ADH1B shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ADH1B 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_Leukemia and SOFT_TISSUE.
