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加权基因共表达网络分析鉴定胃癌中与中性粒细胞相关的分子亚型及其临床意义
Authors Chen C, Shao Y, Ye C, Yu X, Hu M, Yan J , Ye G
Received 10 October 2024
Accepted for publication 22 February 2025
Published 28 February 2025 Volume 2025:17 Pages 397—418
DOI http://doi.org/10.2147/CMAR.S500215
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Seema Singh
Chujia Chen,1,2,* Yongfu Shao,1,* Chengyuan Ye,2 Xuan Yu,2 Meng Hu,2 Jianing Yan,1 Guoliang Ye1
1Department of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, People’s Republic of China; 2Health Science Center, Ningbo University, Ningbo, 315211, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yongfu Shao; Guoliang Ye, Department of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, People’s Republic of China, Tel +86-574-87035171, Fax +86-574-87380487, Email fyshaoyongfu@nbu.edu.cn, shaoyongfu1173@163.com; yeguoliang@nbu.edu.cn, ndfyygl@126.com
Background: Gastric cancer (GC) is among the most lethal malignancies worldwide. Due to the substantial heterogeneity of GC, more accurate molecular typing systems are desperately required to enhance the prognosis of GC patients.
Methods: The major immune cell subclusters in GC were identified by a single-cell RNA sequencing (scRNA-seq) dataset. High-dimensional weighted gene coexpression network analysis (hdWGCNA) and multiple bioinformatics methods were utilized to classify the molecular subtypes of GC and further investigate the differences among the subtypes. Based on the module genes and differentially expressed genes (DEGs), random survival forest analysis was applied to identify the key prognostic genes for GC, and the roles and functional mechanisms of the key genes in GC were explored by clinical samples and cellular experiments.
Results: Two distinct GC molecular subtypes (C1 and C2) associated with neutrophils were identified, with C1 associated with better prognosis. Compared with C2 subtype, C1 subtype has significant differences in immune infiltration, immune checkpoint expression, signaling pathway regulation, tumor mutation burden, and immunotherapy and chemotherapeutic drug sensitivity. Three new key genes (VIM, RBMS1 and RGS2) were revealed to be highly correlated with the prognosis of GC patients. In addition, the expression and cellular functions of key genes RBMS1 and RGS2 in gastric carcinogenesis were verified.
Conclusion: We identified two neutrophil-related molecular GC subtypes with different prognostic outcomes and clinical significance. VIM, RBMS1 and RGS2 were identified as potential prognostic markers and therapeutic targets for GC. These findings provide a new perspective for the molecular typing and personalized treatment of GC.
Keywords: gastric cancer, neutrophils, molecular subtypes, single-cell RNA sequencing, weighted gene co-expression network analysis