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生物信息学结合生物学实验以确定2型糖尿病与乳腺癌的发病机制联系。

Bioinformatics Combined With Biological Experiments to Identify the Pathogenetic Link of Type 2 Diabetes for Breast Cancer.

作者信息

Bao Xin, Zeng Zhirui, Tang Wenjing, Li Dahuan, Fan Xianrui, Chen Kang, Wang Yongkang, Ai Weijie, Yang Qian, Liu Shu, Chen Tengxiang

机构信息

Engineering Research Center of Chronic Disease Diagnosis and Treatment, School of Basic Medicine, Guizhou Medical University, Guiyang, China.

School of Imaging, Guizhou Medical University, Guiyang, China.

出版信息

Cancer Med. 2025 Apr;14(7):e70759. doi: 10.1002/cam4.70759.

Abstract

BACKGROUND

Type 2 diabetes mellitus (T2DM) constitutes a significant risk factor for breast cancer (BC), with affected women exhibiting a two- to three-fold increased likelihood of developing BC. Furthermore, women diagnosed with both BC and T2DM tend to experience poorer prognoses and exhibit greater resistance to various treatments compared to their non-diabetic counterparts. Consequently, elucidating the comorbidities associated with T2DM and BC is instrumental in enhancing the diagnostic and therapeutic strategies for BC.

METHODS

A series of bioinformatics methods including weighted gene co-expression network analysis (WGCNA), differentially expressed gene (DEG) analysis, machine learning, and single-cell sequencing analysis were used to identify the pathogenetic molecules of T2DM for BC. Biological experiments including CCK-8, colony formation, wound healing, transwell assay, immunohistochemistry, and immunofluorescence were performed to determine the molecule effect.

RESULTS

By conducting WGCNA and DEG analysis on the profiles of T2DM (GSE25724 and GSE20966) and the TCGA cohort of BC, we identified a total of 27 common hub genes shared between T2DM and BC. These genes were significantly enriched in pathways related to cell differentiation, cellular developmental processes, focal adhesion, and the MAPK signaling pathway. Notably, among these 27 genes, CCNB2, XRCC2, and CENPI were associated with poor prognosis in BC. Moreover, single-cell RNA sequencing analysis revealed that CCNB2, XRCC2, and CENPI are enriched in cancer cells within BC tissues. Additionally, we observed that CCNB2, XRCC2, and CENPI were elevated in BC tissues provided by patients with a diabetes history and associated with KI67 expression. Hyperglycemia treatment elevated the expression levels of CCNB2, XRCC2, and CENPI in BC cells, which correlated with increased cell proliferation and mobility. Conversely, the knockdown of these genes partially mitigated the pro-proliferative and pro-migratory effects induced by hyperglycemia in BC cells.

CONCLUSION

Our findings suggested that CCNB2, XRCC2, and CENPI may serve as key pathogenic mediators linking T2DM and BC. Targeting these molecules could potentially attenuate the adverse impacts of T2DM on BC progression.

摘要

背景

2型糖尿病(T2DM)是乳腺癌(BC)的一个重要危险因素,患T2DM的女性患BC的可能性增加两到三倍。此外,与未患糖尿病的女性相比,同时被诊断为BC和T2DM的女性往往预后较差,并且对各种治疗的耐药性更强。因此,阐明与T2DM和BC相关的合并症有助于提高BC的诊断和治疗策略。

方法

使用一系列生物信息学方法,包括加权基因共表达网络分析(WGCNA)、差异表达基因(DEG)分析、机器学习和单细胞测序分析,来鉴定T2DM合并BC的致病分子。进行了包括CCK-8、集落形成、伤口愈合、Transwell实验、免疫组织化学和免疫荧光在内的生物学实验,以确定该分子的作用。

结果

通过对T2DM(GSE25724和GSE20966)的图谱以及BC的TCGA队列进行WGCNA和DEG分析,我们总共鉴定出T2DM和BC之间共有的27个常见枢纽基因。这些基因在与细胞分化、细胞发育过程、粘着斑和MAPK信号通路相关的途径中显著富集。值得注意的是,在这27个基因中,CCNB2、XRCC2和CENPI与BC的不良预后相关。此外,单细胞RNA测序分析表明,CCNB2、XRCC2和CENPI在BC组织内的癌细胞中富集。此外,我们观察到CCNB2、XRCC2和CENPI在有糖尿病病史患者提供的BC组织中升高,并与KI67表达相关。高血糖治疗可提高BC细胞中CCNB2、XRCC2和CENPI的表达水平,这与细胞增殖和迁移增加相关。相反,敲低这些基因可部分减轻高血糖对BC细胞诱导的促增殖和促迁移作用。

结论

我们的研究结果表明,CCNB2、XRCC2和CENPI可能是连接T2DM和BC的关键致病介质。靶向这些分子可能会减轻T2DM对BC进展的不利影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0eff/11979791/e6ed590dc368/CAM4-14-e70759-g002.jpg

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