研究动态
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机器学习和单细胞测序揭示了胃癌进展过程中线粒体自噬的潜在调控因子。

Machine learning and single-cell sequencing reveal the potential regulatory factors of mitochondrial autophagy in the progression of gastric cancer.

发表日期:2023 Aug 31
作者: Chen Wei, Yichao Ma, Fei Wang, Yuji Chen, Yiqun Liao, Bin Zhao, Qi Zhao, Dong Tang
来源: GENES & DEVELOPMENT

摘要:

线粒体自噬作为一种重要的调节机制,以清除受损线粒体和维持内外环境平衡为目标,在癌症的发展和治疗中起着关键作用(Onishi EMBO J 40(3): e104705, 2021)。本研究旨在通过RNA测序(RNA-seq)和单细胞RNA测序(scRNA-seq),全面分析线粒体自噬相关基因在胃癌(GC)发展中的作用。GSE26942、GSE54129、GSE66229、GSE183904等数据集通过GEO数据库获取到。分别采用支持向量机递归特征消除(SVM-RVF)算法和随机森林算法,获得与胃癌相关的线粒体自噬相关基因。之后,构建模型并分析炎症因子、免疫评分和免疫细胞浸润。此外,根据13个GC样本中28,836个细胞的scRNA-seq数据,利用scRNA-seq分析鉴定出18个细胞簇和7个细胞类型。通过细胞通讯分析验证相关基因的表达水平和信号通路。最后,通过SCENIC分析细胞的调控网络。通过机器学习算法,鉴定出MAP1LC3B、PGAW5、PINK1、TOMM40和UBC作为关键基因。在肿瘤环境中,CXCL12-CXCR4、LGALS9-CD44、LGALS9-CD45以及MIF (CD74 + CD44) 通路可能在具有较高T细胞和单核细胞评分的内皮细胞中发挥重要作用。在GC细胞簇中,识别出CEBPB、ETS1、GATA2、MATB、SPl1和XBP1作为具有特定调控表达的候选转录因子。本研究结果为研究GC中线粒体自噬的机制、诊断和治疗提供了启示。© 2023. 作者(们)在Springer-Verlag GmbH Germany的独家许可下,属于Springer Nature。
As an important regulatory mechanism to remove damaged mitochondria and maintain the balance between internal and external cells, mitochondrial autophagy plays a key role in the progression and treatment of cancer Onishi (EMBO J 40(3): e104705, 2021). The purpose of this study is to comprehensively analyze the role of mitochondrial autophagy-related genes in the progression of gastric cancer (GC) by RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq).GSE26942, GSE54129,GSE66229,GSE183904 and other data sets were obtained by GEO databases. Using support vector machine recursive feature elimination (SVM-RVF) algorithm and random forest algorithm, the mitochondrial autophagy-related genes related to gastric cancer were obtained, respectively. After that, the model was constructed and the inflammatory factors, immune score and immune cell infiltration were analyzed. Furthermore, according to the scRNA-seq data of 28,836 cells from 13 GC samples, 18 cell clusters and 7 cell types were identified by scRNA-seq analysis. The expression level and signal pathway of related genes were verified by cell communication analysis. Finally, the regulatory network of cells was analyzed by SCENIC.MAP1LC3B, PGAW5, PINK1, TOMM40 and UBC are identified as key genes through machine learning algorithms. CXCL12-CXCR4, LGALS9-CD44, LGALS9-CD45 and MIF (CD74 + CD44) pathways may play an important role in endothelial cells with high score scores of T cells and monocytes in tumor environment. CEBPB, ETS1, GATA2, MATB, SPl1 and XBP1 were identified as candidate TF with specific regulatory expression in the GC cell cluster.The results of this study will provide implications for the study of the mechanism, diagnosis and treatment of mitochondrial autophagy in GC.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.