ATPase Na+/K+ transporting family member beta 4Genealiases: []
Q-omics provides the consensus-scored ATP1B4 profile across patient tissues and cancer cell-line models. ATP1B4 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ATP1B4 is differentially expressed in 3, with the highest sampling consensus in HNSC. Additionally, ATP1B4 RNA expression shows 8,568 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight HNSC as cancer lineages where ATP1B4 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 ATP1B4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP1B4 survival associations across molecular data types. ATP1B4 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP1B4 RNA expression–survival associations across cancer types. High ATP1B4 expression shows unfavorable associations in HNSC, DLBC, BLCA and KIRP, but favorable associations in SKCM and SCLC. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for ATP1B4 RNA expression.
This table summarizes ATP1B4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ATP1B4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP1B4 shows lower tumor expression in HNSC and higher tumor expression in KICH and STAD. The HNSC box plot shows higher ATP1B4 RNA expression in normal versus tumor tissue (log2 FC = −0.767, t-test p = .044).
This table shows molecular features associated with ATP1B4 in patient tissues and cancer cell lines. In patient samples, ATP1B4 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP1B4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and LARGE_INTESTINE.
