Q-omics provides the consensus-scored ATP6V1D profile across patient tissues and cancer cell-line models. ATP6V1D expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATP6V1D is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, ATP6V1D protein abundance shows 32,362 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where ATP6V1D 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 ATP6V1D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP6V1D survival associations across molecular data types. ATP6V1D RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP6V1D RNA expression–survival associations across cancer types. High ATP6V1D expression shows unfavorable associations in HNSC, BLCA, SCLC and SKCM, but favorable associations in KIRC and UCEC. 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 ATP6V1D RNA expression.
This table summarizes ATP6V1D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP6V1D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP6V1D shows lower tumor expression in KIRC, COAD and THCA and higher tumor expression in LIHC, BRCA and HNSC. The KIRC box plot shows higher ATP6V1D RNA expression in normal versus tumor tissue (log2 FC = −0.756, t-test p < 0.001).
This table shows molecular features associated with ATP6V1D in patient tissues and cancer cell lines. In patient samples, ATP6V1D shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP6V1D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Lymphoma.
