Q-omics provides the consensus-scored ATP4A profile across patient tissues and cancer cell-line models. ATP4A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, ATP4A is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, ATP4A protein abundance shows 23,519 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, THCA, and LSCC as cancer lineages where ATP4A 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 ATP4A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP4A survival associations across molecular data types. ATP4A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP4A RNA expression–survival associations across cancer types. High ATP4A expression shows unfavorable associations in LIHC, KIRC, ACC and COAD, but favorable associations in HNSC and UVM. The LIHC 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 LIHC as the clearest survival context for ATP4A RNA expression.
This table summarizes ATP4A 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 8. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP4A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP4A shows lower tumor expression in THCA, STAD and BRCA and higher tumor expression in KICH, UCEC and LUSC. The THCA box plot shows higher ATP4A RNA expression in normal versus tumor tissue (log2 FC = −0.994, t-test p < 0.001).
This table shows molecular features associated with ATP4A in patient tissues and cancer cell lines. In patient samples, ATP4A shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP4A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
