Q-omics provides the consensus-scored ATE1 profile across patient tissues and cancer cell-line models. ATE1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATE1 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, ATE1 protein abundance shows 23,379 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, KICH, and BRCA as cancer lineages where ATE1 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 ATE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATE1 survival associations across molecular data types. ATE1 RNA expression shows survival associations in the most cancer types (27), 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 ATE1 RNA expression–survival associations across cancer types. High ATE1 expression shows unfavorable associations in ACC, UVM and DLBC, but favorable associations in KIRC, HNSC and LGG. 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 ATE1 RNA expression.
This table summarizes ATE1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATE1 shows lower tumor expression in KICH, BLCA, THCA and KIRC and higher tumor expression in LIHC and STAD. The KICH box plot shows higher ATE1 RNA expression in normal versus tumor tissue (log2 FC = −1.575, t-test p < 0.001).
This table shows molecular features associated with ATE1 in patient tissues and cancer cell lines. In patient samples, ATE1 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, ATE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
