A Novel Porphyromonas gingivalis Infection-Related Inflammatory Response-Related Genes Signature Predicts the Prognosis of Esophageal Squamous Cell Carcinoma

Abstract

Background: Our previous research showed that Porphyromonas gingivalis (P. gingivalis) infection can activate the inflammatory signaling pathway and promotes the malignancy development of esophageal squamous cell carcinoma (ESCC). However, the prognostic significance of inflammatory response-related genes (IRRGs) in P. gingivalis-infected ESCC requires further elucidation. Hence, our study constructed a prognostic signature based on P. gingivalis and IRRGs to forecast the survival of patients with ESCC, which may provide insight into new treatment options for ESCC patients. Methods: Differentially expressed genes (DEGs) were identified in P.gingivalis-infected and P.gingivalis-uninfected ESCC cell by RNA sequencing. A risk model was constructed and validated using the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database by using univariate Cox regression analysis, LASSO, and the multivariate Cox regression analysis. Kaplan-Meier analysis was carried out to compare the overall survival (OS) between high-risk and low-risk groups. Single-sample gene set enrichment analysis was used to analyze the immune cell infiltration. The Genomics of Drug Sensitivity in Cancer database was used to predict drug sensitivity. Results: There were 365 DEGs between the P.gingivalis-infected and P.gingivalis-uninfected groups. Four genes including DKK1, ESRRB, EREG, and RELN were identified to construct the prognostic risk model (P =.012, C-index = 0.73). In both the training and validation sets, patients had a considerably shorter OS in the high-risk group than those in the low-risk group (P