Q-omics provides the consensus-scored ATXN1 profile across patient tissues and cancer cell-line models. ATXN1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATXN1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ATXN1 RNA expression shows 20,427 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where ATXN1 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 ATXN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATXN1 survival associations across molecular data types. ATXN1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (9) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATXN1 RNA expression–survival associations across cancer types. High ATXN1 expression shows unfavorable associations in ACC, UVM and BLCA, but favorable associations in KIRC, LUAD and HNSC. 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 ATXN1 RNA expression.
This table summarizes ATXN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATXN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATXN1 shows lower tumor expression in KICH and THCA and higher tumor expression in KIRC, HNSC, LIHC and BRCA. The KIRC box plot shows higher ATXN1 RNA expression in tumor versus normal tissue (log2 FC = +0.618, t-test p < 0.001).
This table shows molecular features associated with ATXN1 in patient tissues and cancer cell lines. In patient samples, ATXN1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATXN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
