Q-omics provides the consensus-scored ATL3 profile across patient tissues and cancer cell-line models. ATL3 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, ATL3 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, ATL3 protein abundance shows 23,192 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ESCA, HNSC, and GBM as cancer lineages where ATL3 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 ATL3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATL3 survival associations across molecular data types. ATL3 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (7) 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 ATL3 RNA expression–survival associations across cancer types. High ATL3 expression shows unfavorable associations in ACC, LGG, PAAD and KICH, but favorable associations in ESCA and KIRC. The ESCA 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 ESCA as the clearest survival context for ATL3 RNA expression.
This table summarizes ATL3 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATL3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATL3 shows lower tumor expression in THCA and UCEC and higher tumor expression in HNSC, KIRC, LIHC and CHOL. The HNSC box plot shows higher ATL3 RNA expression in tumor versus normal tissue (log2 FC = +1.395, t-test p < 0.001).
This table shows molecular features associated with ATL3 in patient tissues and cancer cell lines. In patient samples, ATL3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATL3 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 LUNG_NSCLC_LUSC and LARGE_INTESTINE.
