aminopeptidase O (putative)Genealiases: AP-O · APO · C90RF3 · C9orf3 · DYT31 · ONPEP
Q-omics provides the consensus-scored AOPEP profile across patient tissues and cancer cell-line models. AOPEP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AOPEP is differentially expressed in 12, with the highest sampling consensus in KIRP. Additionally, AOPEP RNA expression shows 21,049 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRP, and UVM as cancer lineages where AOPEP 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 AOPEP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AOPEP survival associations across molecular data types. AOPEP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AOPEP RNA expression–survival associations across cancer types. High AOPEP expression shows unfavorable associations in ACC, UVM and LGG, but favorable associations in KIRC, UCS and HNSC. The ACC 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 ACC as the clearest survival context for AOPEP RNA expression.
This table summarizes AOPEP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for AOPEP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AOPEP shows lower tumor expression in KIRP, KICH, BLCA, UCEC and KIRC and higher tumor expression in LIHC. The KIRP box plot shows higher AOPEP RNA expression in normal versus tumor tissue (log2 FC = −0.841, t-test p < 0.001).
This table shows molecular features associated with AOPEP in patient tissues and cancer cell lines. In patient samples, AOPEP shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, AOPEP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
