Q-omics provides the consensus-scored ATIC profile across patient tissues and cancer cell-line models. ATIC expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ATIC is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, ATIC protein abundance shows 19,777 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, COAD, and PDAC as cancer lineages where ATIC 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 ATIC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATIC survival associations across molecular data types. ATIC RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) 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 ATIC RNA expression–survival associations across cancer types. High ATIC expression shows unfavorable associations in ACC, UVM, LIHC, KIRP, LUAD and PAAD. The ACC 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 ACC as the clearest survival context for ATIC RNA expression.
This table summarizes ATIC 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 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATIC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATIC shows higher tumor expression in COAD, HNSC, LUAD, THCA, KIRP and STAD. The COAD box plot shows higher ATIC RNA expression in tumor versus normal tissue (log2 FC = +1.407, t-test p < 0.001).
This table shows molecular features associated with ATIC in patient tissues and cancer cell lines. In patient samples, ATIC shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATIC 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 BONE.
