Q-omics provides the consensus-scored ADA profile across patient tissues and cancer cell-line models. ADA expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ADA is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ADA RNA expression shows 17,137 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where ADA 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 ADA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADA survival associations across molecular data types. ADA RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 ADA RNA expression–survival associations across cancer types. High ADA expression shows unfavorable associations in KIRP, UCEC, LIHC, KIRC, LUAD and ACC. The KIRP 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 KIRP as the clearest survival context for ADA RNA expression.
This table summarizes ADA 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 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ADA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADA shows higher tumor expression in HNSC, KIRC, KIRP, COAD, LIHC and LUSC. The HNSC box plot shows higher ADA RNA expression in tumor versus normal tissue (log2 FC = +2.015, t-test p < 0.001).
This table shows molecular features associated with ADA in patient tissues and cancer cell lines. In patient samples, ADA 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, ADA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
