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Prognostic value of prostaglandin I2 synthase and its correlation with tumor-infiltrating immune cells in lung cancer, ovarian cancer, and gastric cancer

Background: Prostaglandin I2 synthase (PTGIS) is a crucial gene for the synthesis of prostaglandin I2, which has multiple roles in inflammation and immune modulation. However, studies on the prognostic value of PTGIS and its correlation with tumor-infiltrating immune cells in multiple cancers are st...

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Detalles Bibliográficos
Autores principales: Dai, Danian, Chen, Bo, Feng, Yanling, Wang, Weizhong, Jiang, Yanhui, Huang, He, Liu, Jihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288932/
https://www.ncbi.nlm.nih.gov/pubmed/32463792
http://dx.doi.org/10.18632/aging.103235
Descripción
Sumario:Background: Prostaglandin I2 synthase (PTGIS) is a crucial gene for the synthesis of prostaglandin I2, which has multiple roles in inflammation and immune modulation. However, studies on the prognostic value of PTGIS and its correlation with tumor-infiltrating immune cells in multiple cancers are still rare. Results: Multiple datasets of the Oncomine database showed that PTGIS was expressed at low levels in lung cancer and ovarian cancer compared to the levels in normal tissues. Kaplan-Meier plotter showed that high PTGIS was associated with poor overall survival and progression-free survival in lung, ovarian, and gastric cancers. Moreover, PTGIS expression was significantly positively correlated with infiltrating levels of macrophages and was strongly associated with a variety of immune markers, especially tumor-associated macrophages (TAMs) and T-regulatory cells (Tregs). Conclusions: High expression of PTGIS could promote the infiltration of TAMs and Tregs in the tumor microenvironment and deteriorate outcomes of patients with lung, ovarian, and gastric cancers. These findings suggest that PTGIS could be taken as a potential biomarker of prognosis and tumor-infiltrating immune cells. Methods: PTGIS expression was investigated in different datasets of the Oncomine database, and its expression levels in various tumors and corresponding normal tissues were analyzed by the Tumor Immune Estimation Resource (TIMER). Then, the clinical prognostic value of PTGIS was assessed with online public databases. In addition, we initially explored the correlation between PTGIS and tumor-infiltrating immune cells by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA).