Q-omics provides the consensus-scored ATP1A4 profile across patient tissues and cancer cell-line models. ATP1A4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, ATP1A4 is differentially expressed in 9, with the highest sampling consensus in BRCA. Additionally, ATP1A4 RNA expression shows 13,880 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight LUAD, and BRCA as cancer lineages where ATP1A4 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 ATP1A4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP1A4 survival associations across molecular data types. ATP1A4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP1A4 RNA expression–survival associations across cancer types. High ATP1A4 expression shows favorable associations in LUAD, BLCA, UCS, DLBC, HNSC and ESCA. The LUAD 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 LUAD as the clearest survival context for ATP1A4 RNA expression.
This table summarizes ATP1A4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for ATP1A4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP1A4 shows lower tumor expression in HNSC, PRAD and READ and higher tumor expression in BRCA, UCEC and LIHC. The BRCA box plot shows higher ATP1A4 RNA expression in tumor versus normal tissue (log2 FC = +0.399, t-test p = .006).
This table shows molecular features associated with ATP1A4 in patient tissues and cancer cell lines. In patient samples, ATP1A4 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP1A4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
