Q-omics provides the consensus-scored ATP6V0A4 profile across patient tissues and cancer cell-line models. ATP6V0A4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, ATP6V0A4 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ATP6V0A4 protein abundance shows 20,922 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight COAD, KIRC, and UCEC as cancer lineages where ATP6V0A4 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 ATP6V0A4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6V0A4 survival associations across molecular data types. ATP6V0A4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (8) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP6V0A4 RNA expression–survival associations across cancer types. High ATP6V0A4 expression shows unfavorable associations in COAD, MESO, SCLC, KIRP, LIHC and UVM. The COAD 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 COAD as the clearest survival context for ATP6V0A4 RNA expression.
This table summarizes ATP6V0A4 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP6V0A4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6V0A4 shows lower tumor expression in KIRC, HNSC and KIRP and higher tumor expression in UCEC, THCA and KICH. The KIRC box plot shows higher ATP6V0A4 RNA expression in normal versus tumor tissue (log2 FC = −6.683, t-test p < 0.001).
This table shows molecular features associated with ATP6V0A4 in patient tissues and cancer cell lines. In patient samples, ATP6V0A4 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP6V0A4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
