Q-omics provides the consensus-scored AATK profile across patient tissues and cancer cell-line models. AATK expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, AATK is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, AATK RNA expression shows 19,214 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where AATK 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 AATK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AATK survival associations across molecular data types. AATK RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AATK RNA expression–survival associations across cancer types. High AATK expression shows unfavorable associations in KIRP, ACC, UVM and UCEC, but favorable associations in STAD and HNSC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for AATK RNA expression.
This table summarizes AATK 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 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AATK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AATK shows lower tumor expression in LUAD, KICH and LUSC and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher AATK RNA expression in tumor versus normal tissue (log2 FC = +0.611, t-test p < 0.001).
This table shows molecular features associated with AATK in patient tissues and cancer cell lines. In patient samples, AATK 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, AATK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BONE.
