Q-omics provides the consensus-scored PTGS2 profile across patient tissues and cancer cell-line models. PTGS2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PTGS2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PTGS2 protein abundance shows 25,130 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, and HNSC as cancer lineages where PTGS2 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 PTGS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTGS2 survival associations across molecular data types. PTGS2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTGS2 RNA expression–survival associations across cancer types. High PTGS2 expression shows unfavorable associations in UVM, ACC, THCA, KIRC and STAD, but favorable associations in BLCA. 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 PTGS2 RNA expression.
This table summarizes PTGS2 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 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PTGS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTGS2 shows lower tumor expression in KIRP, KIRC, LIHC, BRCA and LUSC and higher tumor expression in HNSC. The HNSC box plot shows higher PTGS2 RNA expression in tumor versus normal tissue (log2 FC = +1.994, t-test p < 0.001).
This table shows molecular features associated with PTGS2 in patient tissues and cancer cell lines. In patient samples, PTGS2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, PTGS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
