Q-omics provides the consensus-scored ANPEP profile across patient tissues and cancer cell-line models. ANPEP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ANPEP is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, ANPEP RNA expression shows 20,447 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, COAD, and GBM as cancer lineages where ANPEP 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 ANPEP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ANPEP survival associations across molecular data types. ANPEP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ANPEP RNA expression–survival associations across cancer types. High ANPEP expression shows unfavorable associations in UVM, ACC and LGG, but favorable associations in KIRP, KIRC and READ. 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 ANPEP RNA expression.
This table summarizes ANPEP 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 3. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ANPEP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ANPEP shows lower tumor expression in COAD, KICH, LUSC, BRCA and LUAD and higher tumor expression in UCEC. The COAD box plot shows higher ANPEP RNA expression in normal versus tumor tissue (log2 FC = −5.181, t-test p < 0.001).
This table shows molecular features associated with ANPEP in patient tissues and cancer cell lines. In patient samples, ANPEP 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, ANPEP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and SOFT_TISSUE.
