鉴定与复发性妊娠失败中细胞凋亡相关的生物标志物和机制。

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xiaofeng Zhao, Yunhong Yang, Qiuyue Xie, Jiahan Qiu, Xiaofeng Sun
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引用次数: 0

摘要

在这项研究中,我们采用生物信息学技术来鉴定与复发性妊娠丢失(RPL)中细胞凋亡相关的基因。我们从基因表达总库(Gene Expression Omnibus,GEO)数据库中检索了RPL表达谱数据集GSE165004和GSE73025。我们还从京都基因和基因组百科全书(KEGG)凋亡途径(hsa04210)中获取数据,以确定与凋亡相关的基因。此外,我们还进行了好友分析,以探索差异凋亡基因与功能通路中其他基因之间的相互作用。我们发现了6个与细胞凋亡相关的差异表达基因,包括CTSZ、BCL2、PIK3CD、KRAS、GADD45G和CASP8,其中GADD45G是表达最多的基因。功能生育分析显示,差异表达基因主要调控蛋白质稳定性、细胞数量稳态、髓样细胞稳态、造血祖细胞分化、溶酶体和溶酶体功能、空泡膜和溶酶体膜、跨膜转运体结合、蛋白质结构域特异性结合、G蛋白β亚基结合、磷脂结合,并参与Rap1信号转导、肌动蛋白细胞骨架调控和NOD样受体信号转导等通路。在与 RPL 相关的癌症 CESC 中,KRAS 的突变率最高。差异表达基因还与 B 细胞记忆、CD4 记忆静息 T 细胞、滤泡辅助 T 细胞、幼稚 B 细胞和静息树突状细胞呈正相关。我们发现了 6 个与 RPL 细胞凋亡有关的差异表达基因,其中 GADD45G 是最重要的基因。NOD样受体信号通路和肌动蛋白细胞骨架调控可能是RPL的治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Biomarkers and Mechanisms Associated with Apoptosis in Recurrent Pregnancy Loss.

In this study, we employed bioinformatics techniques to identify genes associated with apoptosis in recurrent pregnancy loss (RPL). We retrieved the RPL expression profile datasets GSE165004 and GSE73025 from the Gene Expression Omnibus (GEO) database. We also obtained data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway of Apoptosis (hsa04210) to identify apoptosis-related genes. In addition, we performed Friends analysis to explore the interactions between differential apoptosis genes and other genes in the functional pathway. We identified six differentially expressed genes related to apoptosis, including CTSZ, BCL2, PIK3CD, KRAS, GADD45G, and CASP8, with GADD45G as the most gene. Functional fertility analysis revealed that differentially expressed genes primarily regulated protein stability, cell number homeostasis, myeloid cell homeostasis, hematopoietic progenitor cell differentiation, lytic vacuole and lysosome functions, vacuolar and lysosomal membranes, transmembrane transporter binding, protein domain-specific binding, G-protein beta-subunit binding, phospholipid binding, and were involved in pathways such as Rap1 signaling, regulation of actin cytoskeleton, and NOD-like receptor signaling. KRAS exhibited the highest mutation rate in RPL-related cancer CESC. There was also a positive correlation between differentially expressed genes and B cell memory, CD4 memory resting T cells, follicular helper T cells, naïve B cells, and resting dendritic cells. We identified six differentially expressed genes related to apoptosis in RPL, with GADD45G as the most important. NOD-like receptor signaling pathway and regulation of actin cytoskeleton could be therapeutic targets for RPL.

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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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