The Second Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China; Lanzhou University Second Hospital, Lanzhou, Gansu, China; Key Laboratory of Digestive System Tumors of Gansu Province, Lanzhou, Gansu, China.
The Second Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China; Lanzhou University Second Hospital, Lanzhou, Gansu, China; Key Laboratory of Digestive System Tumors of Gansu Province, Lanzhou, Gansu, China.
Clin Chim Acta. 2022 Jun 1;531:25-35. doi: 10.1016/j.cca.2022.03.010. Epub 2022 Mar 14.
To explore the differentially expressed microRNAs (DEMs) in serum exosomes between gastric cancer (GC) patients and healthy people to provide new targets for GC diagnosis and treatment.
DEMs in serum exosomes were screened by microarray analysis and verified by RT-qPCR. The target genes of DEMs were predicted using Targetscan and miRTarBase databases and then overlapped with the DEGs of STAD in TCGA database to obtain the common target genes. Biological function and pathway enrichment were analyzed using enrichr database, and a PPI network was constructed using STRING database. The potential target genes of DEMs were identified using the MCODE and cytoHubba plug-ins of Cytoscape software. Survival analysis were conducted using KMP and TCGA databases. The DEMs -target genes-pathways network was established using Cytoscape software. A Cox proportional hazards regression model formed by optimal target genes was used to access the reliability of this prediction process.
Three serum exosomal microRNAs (exo-miRNAs, has-miR-1273 g-3p, has-miR-4793-3p, has-miR-619-5p) were identified to be highly expressed in GC patients and performed excellent diagnostic ability. A total of 179 common target genes related to GC were predicted. They were mainly involved in 79 GO functional annotations and 6 KEGG pathways. The prognostic model formed by eight optimal target genes (TIMELESS, DNA2, MELK, CHAF1B, DBF4, PAICS, CHEK1 and NCAPG2), which were low-risk genes of GC, also performed perfect prognostic ability.
Serum exosomal has-miR-1273 g-3p, has-miR-4793-3p and has-miR-619-5p can be used as new diagnostic biomarkers for GC. Among them, serum exosomal hsa-miR-1273 g-3p / hsa-miR-4793-3p targets MELK and hsa-miR-619-5p targets NCAPG2 were identified as novel mechanisms involved in the development of GC. It provides new targets for the diagnosis and treatment of GC by exo-miRNAs.
探索胃癌（GC）患者与健康人血清外泌体中差异表达的 microRNAs（DEMs），为 GC 的诊断和治疗提供新的靶点。
通过微阵列分析筛选血清外泌体中的 DEMs，并通过 RT-qPCR 进行验证。使用 Targetscan 和 miRTarBase 数据库预测 DEMs 的靶基因，然后与 TCGA 数据库中 STAD 的 DEGs 重叠，获得共同靶基因。使用 enrichr 数据库进行生物功能和通路富集分析，使用 STRING 数据库构建 PPI 网络。使用 Cytoscape 软件的 MCODE 和 cytoHubba 插件识别潜在的 DEMs 靶基因。使用 KMP 和 TCGA 数据库进行生存分析。使用 Cytoscape 软件建立 DEMs-靶基因-通路网络。使用 Cox 比例风险回归模型构建由最优靶基因组成的预测模型，以评估该预测过程的可靠性。
鉴定出三种在 GC 患者血清外泌体中高表达的微小 RNA（exo-miRNA，has-miR-1273 g-3p、has-miR-4793-3p 和 has-miR-619-5p），具有出色的诊断能力。预测到 179 个与 GC 相关的共同靶基因。它们主要参与 79 个 GO 功能注释和 6 个 KEGG 通路。由 8 个最优靶基因（TIMELSS、DNA2、MELK、CHAF1B、DBF4、PAICS、CHEK1 和 NCAPG2）组成的预后模型（这些基因是 GC 的低风险基因）也具有完美的预后能力。
血清外泌体中的 has-miR-1273 g-3p、has-miR-4793-3p 和 has-miR-619-5p 可用作 GC 的新型诊断生物标志物。其中，血清外泌体 hsa-miR-1273 g-3p/hsa-miR-4793-3p 靶向 MELK 和 hsa-miR-619-5p 靶向 NCAPG2 被确定为参与 GC 发生的新机制。通过 exo-miRNA 为 GC 的诊断和治疗提供了新的靶点。
