(untitled) (Annals of Medical Research, 2023)
Aim: To analyze the expression of PTGIS in colon adenocarcinoma and its relationship with clinical prognosis using multiple databases. Materials and Methods: By mining the data of Timer and GEPIA databases on PTGIS studies, the changes of its expression level in colon adenocarcinoma were analyzed. The GEPIA database was used to analyze the relationship between PTGIS expression levels and survival prognosis of colon adenocarcinoma patients. the Linked Omics database was used to analyze the correlation between PTGIS gene expression and clinicopathological features of colon adenocarcinoma. The Genecards database was used to collect proteins related to PTGIS gene, and the STRING data platform was used to construct protein interactions network of PTGIS-related proteins and analyze the physiological process of protein enrichment. Results: The study of Timer database and GEPIA database regarding the differential expression of PTGIS genes in colon adenocarcinoma and normal tissues of colon glands showed that the expression of PTGIS genes in colon adenocarcinoma tissues was significantly lower than that in normal tissues of colon glands (P < 0.05). The overall survival rate of patients with low PTGIS gene expression was significantly higher than that of patients with high PTGIS gene expression, and the prognosis of patients with low PTGIS gene expression was better (P < 0.05), according to the survival analysis of the GEPIA database. PTGIS gene expression levels were lower in colon adenocarcinoma stages I and IV and higher in colon adenocarcinoma stages II and III. Twenty-five proteins related to PTGIS were collected through Genecards database, including LSS, SIGMAR1,FDFT1,etc. The results of their related protein enrichment analysis showed that they were mainly enriched in Cholesterol biosynthetic process,B cell chemotaxis and other biological processes. Conclusion: PTGIS gene is lowly expressed in colon adenocarcinoma and its expression level correlates with survival prognosis. PTGIS gene can provide bioinformatics guidance for the later laboratory experiments.