Q-omics provides the consensus-scored ATP4B profile across patient tissues and cancer cell-line models. ATP4B expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, ATP4B is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, ATP4B RNA expression shows 12,986 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUSC, KIRP, and THYM as cancer lineages where ATP4B 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 ATP4B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP4B survival associations across molecular data types. ATP4B RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP4B RNA expression–survival associations across cancer types. High ATP4B expression shows unfavorable associations in LUSC, READ and LGG, but favorable associations in HNSC, LUAD and UVM. The LUSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .012). Together, the overview and detailed table identify LUSC as the clearest survival context for ATP4B RNA expression.
This table summarizes ATP4B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for ATP4B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP4B shows lower tumor expression in KIRP, KICH, KIRC, THCA and STAD and higher tumor expression in BRCA. The KIRP box plot shows higher ATP4B RNA expression in normal versus tumor tissue (log2 FC = −1.028, t-test p < 0.001).
This table shows molecular features associated with ATP4B in patient tissues and cancer cell lines. In patient samples, ATP4B shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP4B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LUNG_SCLC.
