Q-omics provides the consensus-scored ATP6AP1 profile across patient tissues and cancer cell-line models. ATP6AP1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATP6AP1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, ATP6AP1 RNA expression shows 19,428 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where ATP6AP1 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 ATP6AP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6AP1 survival associations across molecular data types. ATP6AP1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP6AP1 RNA expression–survival associations across cancer types. High ATP6AP1 expression shows unfavorable associations in HNSC, LUSC, COAD and LGG, but favorable associations in KIRC and SCLC. The KIRC 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 KIRC as the clearest survival context for ATP6AP1 RNA expression.
This table summarizes ATP6AP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ATP6AP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6AP1 shows higher tumor expression in HNSC, COAD, LIHC, BRCA, BLCA and STAD. The HNSC box plot shows higher ATP6AP1 RNA expression in tumor versus normal tissue (log2 FC = +0.776, t-test p < 0.001).
This table shows molecular features associated with ATP6AP1 in patient tissues and cancer cell lines. In patient samples, ATP6AP1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP6AP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and CNS.
