Q-omics provides the consensus-scored PTGES profile across patient tissues and cancer cell-line models. PTGES expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, PTGES is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, PTGES protein abundance shows 16,231 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight PAAD, KIRC, and PDAC as cancer lineages where PTGES 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 PTGES — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTGES survival associations across molecular data types. PTGES RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) 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 PTGES RNA expression–survival associations across cancer types. High PTGES expression shows unfavorable associations in PAAD, UVM, KIRC, LUAD and GBM, but favorable associations in BRCA. The PAAD 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 PAAD as the clearest survival context for PTGES RNA expression.
This table summarizes PTGES tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PTGES. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTGES shows lower tumor expression in KIRC and higher tumor expression in COAD, LUAD, LUSC, LIHC and CHOL. The KIRC box plot shows higher PTGES RNA expression in normal versus tumor tissue (log2 FC = −1.911, t-test p < 0.001).
This table shows molecular features associated with PTGES in patient tissues and cancer cell lines. In patient samples, PTGES shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PTGES 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 LUNG_NSCLC_LUSC and BLOOD_Leukemia.
