Integrated bioinformatics and machine-learning screening for immune-related genes in diagnosing non-alcoholic fatty liver disease with ischemic stroke and RRS1 pan-cancer analysis

Frontiers in Immunology

Immunology

Lidong Liu¹  Huayan Bao¹  Danke Su¹  Boyang Zhang¹  Ju Huang¹  Jianwen Li² 

[1] Department of Medical Imaging Center; Guangxi Key Clinical Specialty (Medical Imaging Department); Dominant Cultivation Discipline of Guangxi Medical University Cancer Hospital (Medical Imaging Department), Guangxi Medical University Cancer Hospital, Nanning, China;Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, China;

关键词: non-alcoholic fatty liver disease;    ischemic stroke;    machine learning;    diagnosis;    immune infiltration;    pan-cancer;   

DOI  :  10.3389/fimmu.2023.1113634

 received in 2022-12-01, accepted in 2023-03-27,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundThe occurrence of ischemic stroke (IS) is associated with nonalcoholic fatty liver disease (NAFLD). The cancer burden of NAFLD complicated by IS also warrants attention. This study aimed to identify candidate immune biomarkers linked to NAFLD and IS and analyze their association with cancer.MethodsTwo of each of the NAFLD and IS datasets were downloaded, differentially expressed genes (DEGs) were identified, and module genes were screened via weighted gene coexpression network analysis (WGCNA). Subsequently, utilizing machine learning (least absolute shrinkage and selection operator regression, random forest and support vector machine-recursive feature elimination) and immune cell infiltration analysis, immune-related candidate biomarkers for NAFLD with IS were determined. Simultaneously, a nomogram was established, the diagnostic efficacy was assessed, and the role of candidate biomarkers in cancer was ascertained through pan-cancer analyses.ResultsIn this study, 117 and 98 DEGs were identified from the combined NAFLD and IS datasets, respectively, and 279 genes were obtained from the most significant modules of NAFLD. NAFLD module genes and IS DEGs were intersected to obtain nine genes, which were enriched in the inflammatory response and immune regulation. After overlapping the results of the three machine learning algorithms, six candidate genes were obtained, based on which a nomogram was constructed. The calibration curve demonstrated good accuracy, and the candidate genes had high diagnostic values. The genes were found to be related to the immune dysregulation of stroke, and RRS1 was strongly associated with the prognosis, immune cell infiltration, microsatellite instability (MSI), and tumor mutation burden (TMB).ConclusionSix common candidate immune-related genes (PTGS2, FCGR1A, MMP9, VNN3, S100A12, and RRS1) of NAFLD and IS were identified, and a nomogram for diagnosing NAFLD with IS was established. RRS1 may serve as a candidate gene for predicting the prognosis of patients with cancer who have NAFLD complicated by IS, which could aid in their diagnosis and treatment.

【 授权许可】

Unknown   
Copyright © 2023 Bao, Li, Zhang, Huang, Su and Liu