Q-omics provides the consensus-scored ADAL profile across patient tissues and cancer cell-line models. ADAL expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ADAL is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ADAL RNA expression shows 20,407 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where ADAL 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 ADAL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADAL survival associations across molecular data types. ADAL RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) 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 ADAL RNA expression–survival associations across cancer types. High ADAL expression shows unfavorable associations in BLCA, STAD, KICH and LGG, but favorable associations in KIRC and UCS. 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 ADAL RNA expression.
This table summarizes ADAL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ADAL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADAL shows lower tumor expression in THCA, KIRC, KIRP and COAD and higher tumor expression in LIHC and LUSC. The THCA box plot shows higher ADAL RNA expression in normal versus tumor tissue (log2 FC = −1.355, t-test p < 0.001).
This table shows molecular features associated with ADAL in patient tissues and cancer cell lines. In patient samples, ADAL shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ADAL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
