Development and validation of a risk prognostic model based on the H. pylori infection phenotype for stomach adenocarcinoma

• Published in: Heliyon 2024-09, Vol.10 (17), p.e36882, Article e36882
• Main Authors: Zhou, Jing, Guo, Li, Wang, Yuzhen, Li, Lina, Guo, Yahuan, Duan, Lian, Jiao, Mi, Xi, Pan, Wang, Pei
• Format: Article
• Language: English
• Subjects: H. pylori infection phenotype; RiskScore; Single cell RNA-Seq profile; ssGSEA; Stomach adenocarcinoma (STAD); WGCNA
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e36882

Stomach adenocarcinoma (STAD) is one of the most common malignancies. Infection of helicobacter pylori (H. pylori) is a major risk factor that leads to the development of STAD. This study constructed a risk model based on the H. pylori-related macrophages for predicting STAD prognosis. The single-cell RNA sequencing (scRNA-seq) dataset and the clinic information and RNA-seq datasets of STAD patients were collected for establishing a prognostic model and for validation. The “Seurat” and “harmony” packages were used to process the scRNA-seq data. Key gene modules were sectioned using the “limma” package and the “WGCNA” package. Kaplan-Meier (KM) and Receiver Operating Characteristic Curve (ROC) analyses were performed with “survminer” package. The “GSVA” package was employed for single sample gene set enrichment analysis (ssGSEA). Cell migration and invasion were measured by carrying out wound healing and trans-well assays. A total of 17397 were screened and classified into 8 cell type clusters, among which the macrophage cluster was closely associated with the H. pylori infection. Macrophages were further categorized into four subtypes (including C1, C2, C3, and C4), and highly variable genes of macrophage subtype C4 could serve as an indicator of the prognosis of STAD. Subsequently, we developed a RiskScore model based on six H. pylori -associated genes (TNFRSF1B, CTLA4, ABCA1, IKBIP, AKAP5, and NPC2) and observed that the high-risk patients exhibited poor prognosis, higher suppressive immune infiltration, and were closely associated with cancer activation-related pathways. Furthermore, a nomogram combining the RiskScore was developed to accurately predict the survival of STAD patients. ABCA1 in the RiskScore model significantly affected the migration and invasion of tumor cells. The gene expression profile served as an indicator of the survival for patients with STAD and addressed the clinical significance of using H. pylori-associated genes to treat STAD. The current findings provided novel understandings for the clinical evaluation and management of STAD.