Q-omics provides the consensus-scored ATP5PD profile across patient tissues and cancer cell-line models. ATP5PD expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ATP5PD is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, ATP5PD protein abundance shows 24,311 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LIHC, and GBM as cancer lineages where ATP5PD 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 ATP5PD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP5PD survival associations across molecular data types. ATP5PD RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP5PD RNA expression–survival associations across cancer types. High ATP5PD expression shows unfavorable associations in UVM, KICH, HNSC, UCS, ACC and LIHC. The UVM 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 UVM as the clearest survival context for ATP5PD RNA expression.
This table summarizes ATP5PD 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 LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP5PD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP5PD shows higher tumor expression in LIHC, LUAD, LUSC, BRCA, CHOL and BLCA. The LIHC box plot shows higher ATP5PD RNA expression in tumor versus normal tissue (log2 FC = +0.956, t-test p < 0.001).
This table shows molecular features associated with ATP5PD in patient tissues and cancer cell lines. In patient samples, ATP5PD 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, ATP5PD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in CNS and SOFT_TISSUE.
