文献类型：期刊文献

英文题名：Single-cell RNA-sequencing and genome-wide Mendelian randomisation along with abundant machine learning methods identify a novel B cells signature in gastric cancer

作者：Ma, Qi[1];Gao, Jie[2];Hui, Yuan[1];Zhang, Zhi-Ming[1];Qiao, Yu-Jie[1];Yang, Bin-Feng[1];Gong, Ting[1];Zhao, Duo-Ming[1];Huang, Bang-Rong[1]

第一作者：Ma, Qi

通信作者：Huang, BR[1]

机构：[1]Gansu Prov Hosp Tradit Chinese Med, Lanzhou 730050, Peoples R China;[2]Gansu Univ Tradit Chinese Med, Lanzhou, Peoples R China

第一机构：Gansu Prov Hosp Tradit Chinese Med, Lanzhou 730050, Peoples R China

通信机构：[1]corresponding author), Gansu Prov Hosp Tradit Chinese Med, Lanzhou 730050, Peoples R China.

年份：2025

卷号：16

期号：1

外文期刊名：DISCOVER ONCOLOGY

收录：;Scopus(收录号：2-s2.0-85214357172);WOS:【SCI-EXPANDED(收录号:WOS:001391728500003)】；

基金：The study was supported by fundings from Gansu Provincial Natural Science Joint Fund General Programme (NO.24JRRA901); Provincial Regional Chinese Medicine (Special) Diagnostic and Treatment Project: Tumour Multidisciplinary Diagnostic and Treatment Centre.

语种：英文

外文关键词：Gastric cancer; Single-cell RNA sequencing; Diagnostic biomarker; Machine learning; Bioinformatics

摘要：BackgroundGastric cancer (GC) has a poor prognosis, considerable cellular heterogeneity, and ranks fifth among malignant tumours. Understanding the tumour microenvironment (TME) and intra-tumor heterogeneity (ITH) may lead to the development of novel GC treatments.MethodsThe single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Gene Expression Omnibus (GEO) database, where diverse immune cells were isolated and re-annotated based on cell markers established in the original study to ascertain their individual characteristics. We conducted a weighted gene co-expression network analysis (WGCNA) to identify genes with a significant correlation to GC. Utilising bulk RNA sequencing data, we employed machine learning integration methods to train specific biomarkers for the development of novel diagnostic combinations. A two-sample Mendelian randomisation study was performed to investigate the causal effect of biomarkers on gastric cancer (GC). Ultimately, we utilised the DSigDB database to acquire associations between signature genes and pharmaceuticals.ResultsThe 18 genes that made up the signature were as follows: ZFAND2A, PBX4, RAMP2, NNMT, RNASE1, CD93, CDH5, NFKBIE, VWF, DAB2, FAAH2, VAT1, MRAS, TSPAN4, EPAS1, AFAP1L1, DNM3. Patients were categorised into high-risk and low-risk groups according to their risk scores. Individuals in the high-risk cohort exhibited a dismal outlook. The Mendelian randomisation study demonstrated that individuals with a genetic predisposition for elevated NFKBIE levels exhibited a heightened likelihood of acquiring GC. Molecular docking indicates that gemcitabine and chloropyramine may serve as effective therapeutics against NFKBIE.ConclusionsWe developed and validated a signature utilising scRNA-seq and bulk sequencing data from gastric cancer patients. NFKBIE may function as a novel biomarker and therapeutic target for GC.