Q-omics provides the consensus-scored ATXN3L profile across patient tissues and cancer cell-line models. ATXN3L expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in STAD. Additionally, ATXN3L protein abundance shows 16,394 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight STAD, and PDAC as cancer lineages where ATXN3L 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 ATXN3L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATXN3L survival associations across molecular data types. ATXN3L RNA expression shows survival associations in the most cancer types (8), followed by mutation status (4) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATXN3L RNA expression–survival associations across cancer types. High ATXN3L expression shows unfavorable associations in STAD, ESCA, UCS, UCEC, PCPG and GBM. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify STAD as the clearest survival context for ATXN3L RNA expression.
This table shows molecular features associated with ATXN3L in patient tissues and cancer cell lines. In patient samples, ATXN3L 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, ATXN3L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
