利用生物信息学探索多囊卵巢综合征中与细胞粘附相关的生物标志物并进行实验验证。
Exploring Biomarkers Related to Cell Adhesion in Polycystic Ovary Syndrome Using Bioinformatics and Conducting Experimental Validation.
作者信息
Zhu Jiani, Qi Xinyue, Zhang Zhenyu, Zhou Qun, Gu Ran, Wu Xiaorong, Zhong Lanping
机构信息
Department of Clinical Nutrition, The First People's Hospital of Yunnan Province, Kunming, Yunnan, People's Republic of China.
Department of Clinical Nutrition, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, People's Republic of China.
出版信息
Int J Gen Med. 2025 Mar 29;18:1777-1794. doi: 10.2147/IJGM.S509651. eCollection 2025.
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.
目的
相关研究指出，细胞黏附可能在多囊卵巢综合征（PCOS）的治疗中发挥重要作用。本研究旨在鉴定和分析与治疗PCOS的细胞黏附相关基因（CRGs）相关的生物标志物及其生物学机制。
患者与方法
在本研究中，通过差异表达分析，利用GSE80432鉴定差异表达基因（DEGs）（PCOS组与对照组）。然后，将DEGs与1531个CRGs进行重叠以获得交叉基因。随后，利用支持向量机递归特征消除结合最小绝对收缩和选择算子来获得候选基因，将在两个数据集中AUC大于0.7且表达趋势一致的基因定义为生物标志物。最后，构建列线图，并分别进行富集分析、调控网络分析、药物预测、生物标志物与PCOS之间的关联分析以及逆转录定量PCR（RT-qPCR）。
结果
共鉴定出10个交叉基因，并从中筛选出2个生物标志物（DSG2和TH11）。RT-qPCR分析表明，PCOS样本中THBS1的表达增加，而DSG2无显著差异。此外，富集分析表明DSG2和THBS1均富集于B细胞受体信号通路。然后，基于这两个生物标志物，分别构建了lncRNA-miRNA-mRNA（81个节点和135条边）和转录因子生物标志物网络（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，预测有61种药物靶向DSG2，而有133种药物靶向THBS1。此外，检测到THBS1与PCOS之间的关联更强（推断得分=27.15）。
结论
本研究鉴定出2个生物标志物（DSG2和THBS1），为PCOS的治疗提供了潜在的理论基础。
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