BCHE as a Prognostic Biomarker in Endometrial Cancer and Its Correlation with Immunity

Abstract

Background: In developed countries, the most common gynecologic malignancy is endometrial carcinoma (EC), making the identification of EC biomarkers extremely essential. As a natural enzyme, butyrylcholinesterase (BCHE) is found in hepatocytes and plasma. There is a strong correlation between BCHE gene mutations and cancers and other diseases. The aim of this study was to analyze the role of BCHE in patients with EC.

Methods: A variety of analyses were conducted on The Cancer Genome Atlas (TCGA) data, including differential expression analysis, enrichment analysis, immunity, clinicopathology, and survival analysis. The Gene Expression Omnibus (GEO) database was used to validate outcomes. Using R tools, Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) analyses revealed the potential mechanisms of BCHE in EC. Sangerbox tools were used to delve into the relations between BCHE expression and tumor microenvironment, including microsatellite instability (MSI), tumor neoantigen count (TNC), and tumor mutation burden (TMB). BCHE's genetic alteration analysis was conducted by cBioPortal. In addition, the Human Protein Atlas (HPA) was used to validate the outcomes by immunohistochemistry, and an analysis of the protein-protein interaction network (PPI) was performed with the help of the STRING database.

Results: Based on our results, BCHE was a significant independent prognostic factor for patients with EC. The prognosis with EC was affected by age, stage, grade, histological type, and BCHE. GSEA showed that BCHE was closely related to pathways regulating immune response, including transforming growth factor-β (TGF-β) signaling pathways and cancer immunotherapy through PD1 blockade pathways. The immune analysis revealed that CD4+ regulatory T cells (Tregs) were negatively correlated with BCHE expression and the immune checkpoint molecules CD28, ADORA2A, BTNL2, and TNFRSF18 were all significantly related to BCHE. BCHE expression was also associated with TMB by genetic alteration analysis.

Conclusions: Identifying BCHE as a biomarker for EC might help predict its prognosis and could have important implications for immunotherapy.

Figure 1

BCHE expression analysis. (a) BCHE expression in normal and tumor tissues in TCGA and GTEx pan-cancer data. (b) BCHE expression in unpaired EC samples. (c) BCHE expression in paired EC samples. (d) BCHE expression in GSE63678. (e) BCHE expression in GSE17025. (f, g) Representative images of immunohistochemistry showing BCHE expression in endometrial carcinoma tissues. (h, i) Representative images of immunohistochemistry showing BCHE expression in normal endometrial tissues.

Figure 2

Differential BCHE expression in various clinicopathological parameters. Expression of BCHE was significantly different in (a) histological grade, (b) histological type, (c) age, and (d) clinical stage (^∗∗∗p < 0.001; ^∗∗p < 0.01; ^∗p < 0.05).

Figure 3

Survival analysis of BCHE expression. (a) Multivariate Cox analysis of BCHE expression and other clinicopathological variables. (b) BCHE expression distribution and survival status (0 = alive; 1 = death). (c) Levels of BCHE mRNA expression and overall survival. (d) ROC curves of BCHE.

Figure 4

Nomogram construction and evaluation. (a) Nomogram construction based on BCHE and clinicopathological variables. (b) ROC curves of BCHE. (c) Calibration curves of 1 year. (d) Calibration curves of 3 years. (e) Calibration curves of 5 years.

Figure 5

Function and pathway enrichment analyses of BCHE in EC. (a–c) Significant Gene Ontology terms associated with BCHE, including biological processes (BP), cell component (CC), and molecular function (MF). (d–g) Significant GSEA results associated with BCHE, including (d) KEGG pathways, (e) REACTOME pathways, (f) PID pathways, and (g) WP pathways.

Figure 6

BCHE expression associated with the immune system and tumor microenvironment. (a) Correlations between BCHE expression and immune infiltration levels. (b) The varied proportions of 24 subtypes of immune cells in high and low BCHE expression groups in tumor samples. (c) Heatmap of 24 immune infiltration cells in tumor samples. (d) Relationships between BCHE and the immune microenvironment in EC. (e) Coexpression analysis of BCHE and immune checkpoint molecules in EC.

Figure 7

Mutation feature of BCHE in EC from TCGA cohort using the cBioPortal tool. (a) The alteration frequency with mutation type of BCHE in EC from TCGA cohorts. (b) K-M survival analysis of OS with or without BCHE alteration. (c) Mutation sites of BCHE in EC. (d) The relationship between the TGF-β signaling pathway and BCHE mutation.

Figure 8

Relationships between BCHE and PPI, TNC, MSI, and TMB in EC. (a) PPI network. (b) Relationships between BCHE and TNC. (c) Relationships between BCHE and MSI. (d) Relationships between BCHE and TMB.