利用生物信息学探索多囊卵巢综合征细胞粘附相关的生物标志物并进行实验验证。

IF 2.1 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
International Journal of General Medicine Pub Date : 2025-03-29 eCollection Date: 2025-01-01 DOI:10.2147/IJGM.S509651
Jiani Zhu, Xinyue Qi, Zhenyu Zhang, Qun Zhou, Ran Gu, Xiaorong Wu, Lanping Zhong
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引用次数: 0

摘要

目的:相关研究指出细胞粘附可能在治疗多囊卵巢综合征(PCOS)中发挥重要作用。本研究旨在鉴定和分析与细胞粘附相关基因(CRGs)治疗多囊卵巢综合征相关的生物标志物及其生物学机制。患者和方法:本研究采用GSE80432基因,通过差异表达分析鉴定PCOS组与对照组的差异表达基因(DEGs)。然后,将deg与1531个crg重叠,得到杂交基因。随后,利用支持向量机-递归特征消除结合最小绝对收缩算子和选择算子获得候选基因,并将AUC大于0.7且在两个数据集中表达趋势一致的基因定义为生物标志物。最后构建模态图,分别进行富集分析、调控网络、药物预测、生物标志物与PCOS的关联以及反转录定量PCR (RT-qPCR)。结果:共鉴定出10个交叉基因,从中筛选出DSG2和TH11 2个生物标志物。RT-qPCR分析显示,THBS1在PCOS样本中表达升高,而DSG2在PCOS样本中表达无显著差异。此外,富集分析表明DSG2和THBS1在b细胞受体信号通路中均富集。然后,基于这两种生物标志物,分别构建lncRNA-miRNA-mRNA(81个节点和135条边)和tf生物标志物网络(38个节点和38条边),如MIR17HG'-has-miR-7-5p'-THBS1, TFDP1-DSG2。通过预测靶向生物标志物的药物,预测61种药物靶向DSG2, 133种药物靶向THBS1。此外,THBS1与PCOS之间存在较强的相关性(推理分数= 27.15)。结论:本研究鉴定出2种生物标志物(DSG2和THBS1),为PCOS的治疗提供了潜在的理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring Biomarkers Related to Cell Adhesion in Polycystic Ovary Syndrome Using Bioinformatics and Conducting Experimental Validation.

Purpose: Related studies have pointed out that cell adhesion may play an important role for treating Polycystic Ovary Syndrome (PCOS). This study aimed to identify and analyze the biomarkers associated with cell adhesion-related genes (CRGs) for treating PCOS and their biological mechanisms.

Patients and methods: In this study, GSE80432 was used to identify differentially expressed genes (DEGs) (PCOS vs control group) through differential expression analysis. Then, the DEGs were overlapped with 1531 CRGs to obtain the cross - genes. Subsequently, the Support Vector Machine-Recursive Feature Elimination combined with the least absolute shrinkage and selection operator was utilized to obtain candidate genes, and the genes with AUC greater than 0.7 and consistent expression trends in the two datasets were defined as biomarkers. Finally, a nomogram was constructed, and enrichment analysis, regulatory network, drug prediction, the association between biomarkers and PCOS, and reverse transcription quantitative PCR (RT-qPCR) were carried out respectively.

Results: A total of 10 cross-genes were identified, and 2 biomarkers (DSG2 and TH11) were screened out from them. RT-qPCR analysis showed that the expression of THBS1 was increased in PCOS samples, while there was no significant difference in DSG2. In addition, enrichment analysis indicated that both DSG2 and THBS1 were enriched in the B-cell receptor signaling pathway. Then, based on these two biomarkers, lncRNA-miRNA-mRNA (81 nodes and 135 edges) and TFs biomarker networks (38 nodes and 38 edges), such as MIR17HG'-has-miR-7-5p'-THBS1, TFDP1-DSG2, were constructed respectively. By predicting drugs targeting biomarkers, 61 drugs were predicted to target DSG2, while 133 drugs were predicted to target THBS1. Moreover, a stronger association between THBS1 and PCOS was detected (inference score = 27.15).

Conclusion: In this study, 2 biomarkers (DSG2 and THBS1) were identified, providing a potential theoretical basis for PCOS treatment.

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来源期刊
International Journal of General Medicine
International Journal of General Medicine Medicine-General Medicine
自引率
0.00%
发文量
1113
审稿时长
16 weeks
期刊介绍: The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas. A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal. As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.
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