Q-omics provides the consensus-scored ATP6V0E1P2 profile across patient tissues and cancer cell-line models. ATP6V0E1P2 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATP6V0E1P2 is differentially expressed in 7, with the highest sampling consensus in LUAD. Additionally, ATP6V0E1P2 RNA expression shows 7,210 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, LUAD, and PDAC as cancer lineages where ATP6V0E1P2 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 ATP6V0E1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6V0E1P2 survival associations across molecular data types. ATP6V0E1P2 RNA expression shows survival associations in the most cancer types (15). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP6V0E1P2 RNA expression–survival associations across cancer types. High ATP6V0E1P2 expression shows unfavorable associations in KIRC, UCEC and MESO, but favorable associations in CESC, BRCA and STAD. The KIRC 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 KIRC as the clearest survival context for ATP6V0E1P2 RNA expression.
This table summarizes ATP6V0E1P2 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 LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for ATP6V0E1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6V0E1P2 shows lower tumor expression in LUAD, PAAD and LUSC and higher tumor expression in HNSC, ESCA and COAD. The LUAD box plot shows higher ATP6V0E1P2 RNA expression in normal versus tumor tissue (log2 FC = −0.290, t-test p = .007).
This table shows molecular features associated with ATP6V0E1P2 in patient tissues and cancer cell lines. In patient samples, ATP6V0E1P2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set.
