Q-omics provides the consensus-scored ATP6V1E1P1 profile across patient tissues and cancer cell-line models. ATP6V1E1P1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, ATP6V1E1P1 is differentially expressed in 4, with the highest sampling consensus in COAD. Additionally, ATP6V1E1P1 RNA expression shows 11,521 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight STAD, COAD, and UVM as cancer lineages where ATP6V1E1P1 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 ATP6V1E1P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6V1E1P1 survival associations across molecular data types. ATP6V1E1P1 RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP6V1E1P1 RNA expression–survival associations across cancer types. High ATP6V1E1P1 expression shows unfavorable associations in STAD and LIHC, but favorable associations in LUSC, PRAD, UCS and THYM. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify STAD as the clearest survival context for ATP6V1E1P1 RNA expression.
This table summarizes ATP6V1E1P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for ATP6V1E1P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6V1E1P1 shows higher tumor expression in COAD, HNSC, LIHC and STAD. The COAD box plot shows higher ATP6V1E1P1 RNA expression in tumor versus normal tissue (log2 FC = +0.370, t-test p < 0.001).
This table shows molecular features associated with ATP6V1E1P1 in patient tissues and cancer cell lines. In patient samples, ATP6V1E1P1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
