Q-omics provides the consensus-scored ATL2 profile across patient tissues and cancer cell-line models. ATL2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ATL2 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, ATL2 protein abundance shows 24,730 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, LIHC, and PDAC as cancer lineages where ATL2 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 ATL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATL2 survival associations across molecular data types. ATL2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) 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 ATL2 RNA expression–survival associations across cancer types. High ATL2 expression shows unfavorable associations in ACC, KIRP, BLCA and UCEC, but favorable associations in LUAD and KIRC. 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 ATL2 RNA expression.
This table summarizes ATL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 9. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ATL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATL2 shows lower tumor expression in BRCA and UCEC and higher tumor expression in LIHC, LUAD, LUSC and CHOL. The LIHC box plot shows higher ATL2 RNA expression in tumor versus normal tissue (log2 FC = +0.717, t-test p < 0.001).
This table shows molecular features associated with ATL2 in patient tissues and cancer cell lines. In patient samples, ATL2 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, ATL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
