Q-omics provides the consensus-scored ATP6AP1L profile across patient tissues and cancer cell-line models. ATP6AP1L expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ATP6AP1L is differentially expressed in 7, with the highest sampling consensus in KIRP. Additionally, ATP6AP1L RNA expression shows 19,536 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, KIRP, and UVM as cancer lineages where ATP6AP1L 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 ATP6AP1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6AP1L survival associations across molecular data types. ATP6AP1L RNA expression shows survival associations in the most cancer types (22), 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 ATP6AP1L RNA expression–survival associations across cancer types. High ATP6AP1L expression shows unfavorable associations in KICH, KIRC and BLCA, but favorable associations in SKCM, READ and BRCA. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for ATP6AP1L RNA expression.
This table summarizes ATP6AP1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for ATP6AP1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6AP1L shows lower tumor expression in LUSC and KICH and higher tumor expression in KIRP, LIHC, KIRC and CHOL. The KIRP box plot shows higher ATP6AP1L RNA expression in tumor versus normal tissue (log2 FC = +0.540, t-test p = .003).
This table shows molecular features associated with ATP6AP1L in patient tissues and cancer cell lines. In patient samples, ATP6AP1L shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP6AP1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SKIN.
