Q-omics provides the consensus-scored PTGDS profile across patient tissues and cancer cell-line models. PTGDS expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PTGDS is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, PTGDS RNA expression shows 23,940 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRP, and LSCC as cancer lineages where PTGDS 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 PTGDS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTGDS survival associations across molecular data types. PTGDS RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTGDS RNA expression–survival associations across cancer types. High PTGDS expression shows unfavorable associations in KIRC, but favorable associations in HNSC, LUAD, ESCA, UCEC and CESC. The HNSC 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 HNSC as the clearest survival context for PTGDS RNA expression.
This table summarizes PTGDS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PTGDS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTGDS shows lower tumor expression in KIRP, BLCA, LUSC, LUAD, KIRC and COAD. The KIRP box plot shows higher PTGDS RNA expression in normal versus tumor tissue (log2 FC = −4.478, t-test p < 0.001).
This table shows molecular features associated with PTGDS in patient tissues and cancer cell lines. In patient samples, PTGDS shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PTGDS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and OVARY.
