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Updated: Feb 8, 2026

Visualization and Quantification of Mesenchymal Cell Adipogenic Differentiation Potential with a Lineage Specific Marker
Published on: March 31, 2018
The prostanoid pathway contains potential prognostic markers for glioblastoma
Alexandros Theodoros Panagopoulos1, Renata Nascimento Gomes2, Fernando Gonçalves Almeida3
1Department of Neurosurgery, Santa Casa Hospital, São Paulo, Brazil.
Abstract:
Prostanoids derived from the activity of cyclooxygenases and their respective synthases contribute to both active inflammation and immune response in the tumor microenvironment. Their synthesis, deactivation and role in glioma biology have not yet been fully explored and require further study. Using quantitative real time PCR, gas chromatography/ electron impact mass spectrometry and liquid chromatography/ electrospray ionization tandem mass spectrometry, we have further characterized the prostanoid pathway in grade IV glioblastoma (GBM). We observed significant correlations between high mRNA expression levels and poor patient survival for microsomal PGE synthase 1 (mPGES1) and prostaglandin reductase 1 (PTGR1). Conversely, high mRNA expression levels for 15-hydroxyprostaglandin dehydrogenase (15-HPGD) were correlated with better patient survival. GBMs had a higher quantity of the prostanoid precursor, arachidonic acid, versus grade II/III tumors and in GBMs a significant positive correlation was found between arachidonic acid and PGE2 content. GBMs also had higher concentrations of TXB2, PGD2, PGE2 and PGF2α versus grade II/III tumors. A significant decrease in survival was detected for high versus low PGE2, PGE2 + PGE2 deactivation products (PGEMs) and PGF2α in GBM patients. Our data show the potential importance of prostanoid metabolism in the progression towards GBM and provide evidence that higher PGE2 and PGF2α concentrations in the tumor are correlated with poorer patient survival. Our findings highlight the potential importance of the enzymes 15-HPGD and PTGR1 as prognostic biomarkers which could be used to predict survival outcome of patients with GBM.
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