Q-omics provides the consensus-scored ATN1 profile across patient tissues and cancer cell-line models. ATN1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, ATN1 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, ATN1 protein abundance shows 20,328 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, HNSC, and GBM as cancer lineages where ATN1 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 ATN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATN1 survival associations across molecular data types. ATN1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATN1 RNA expression–survival associations across cancer types. High ATN1 expression shows unfavorable associations in COAD, LIHC and ACC, but favorable associations in SCLC, UVM and HNSC. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify SCLC as the clearest survival context for ATN1 RNA expression.
This table summarizes ATN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, 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 ATN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATN1 shows lower tumor expression in THCA, LUAD and BRCA and higher tumor expression in HNSC, LIHC and CHOL. The HNSC box plot shows higher ATN1 RNA expression in tumor versus normal tissue (log2 FC = +0.743, t-test p < 0.001).
This table shows molecular features associated with ATN1 in patient tissues and cancer cell lines. In patient samples, ATN1 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, ATN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
