LPCAT1 is a Prognostic Biomarker and Correlated with Tumor Microenvironment in Endometrial Cancer

Abstract Background: Endometrial cancer (EC) is one of the three malignant reproductive tumors threatening women’s life and health. Glycerophospholipids (GPLs) are important bioactive lipids involved in various physiological and pathological processes including cancer. Immune-infiltration of the tumor microenvironment (TME) is positively associated with the overall survival in EC. Exploring GPLs-related factors associated with TME in endometrial cancer can aid in the prognosis of patients and provide new therapy targets. Methods: Differentially expressed GPLs-related genes were identified from TCGA-UCEC datasets and Molecular Signatures Database (MSigDB). Univariate Cox regression analysis was used to select GPLs-related genes with prognostic values. Random forest algorithm, LASSO algorithm and PPI network were used to identify critical genes. ESTIMATEScore was calculated to find out genes associated with TME. Then, differentiation analysis and survival analysis of LPCAT1 were performed based on TCGA datasets. GSE17025 and immunohistochemistry (IHC) verified the results of differentiation analysis. GO and KEGG enrichment analyses were performed to explore the underlying mechanism. In addition, we used ssGSEA algorithm to explore the correlation between LPCAT1 and cancer immune infiltrates. Results: Twenty-three differentially expressed GPLs-related genes were identified and eleven prognostic genes were selected by Univariate Cox regression analysis. Four significant genes were found out by two different algorithms and PPI network. Only LPCAT1 was significantly correlated with tumor microenvironment. Then, we found that LPCAT1 was highly expressed in tumors samples compared with normal tissues, and lower survival rates was along with high expression groups of LPCAT1. Moreover, the expression of LPCAT1 was positively correlated with histologic grades and types. ROC curve indicated LPCAT1 had good accuracy of prognostic value. Receptor ligand activity, pattern specification process, regionalization, anterior/posterior pattern specification and salivary secretion pathways were enriched as potential targets of LPCAT1. By using ssGSEA algorithm, fifteen kinds of tumor infiltrating cells (TICs) were found correlated with LPCAT1 expression. Conclusion: These findings suggested that LPCAT1 was a valuable prognostic biomarker and correlated with immune infiltrates in endometrial cancer, which may provide novel therapy options and improved treatment of EC.