Identify critical genes of breast cancer and corresponding leading natural product compounds of potential therapeutic targets

被引:0
|
作者
Fan, Xiaokai [1 ,2 ,3 ]
Xin, Le [1 ]
Yu, Xuan [2 ]
Liu, Maoxuan [2 ]
Shim, Joong Sup [4 ]
Yang, Gui [1 ]
Chen, Liang [2 ]
机构
[1] Longgang Cent Hosp, Dept Gen Surg Otolaryngol, Shenzhen, Peoples R China
[2] Chinese Acad Sci, Shenzhen Inst Adv Technol, Inst Biomed & Biotechnol, Shenzhen Lab Tumor Cell Biol, Shenzhen, Peoples R China
[3] Fudan Univ, Ctr Intelligent Med Res, Greater Bay Area Inst Precis Med Guangzhou, Sch Life Sci, Shanghai, Peoples R China
[4] Univ Macau, Fac Hlth Sci, Canc Ctr, Ave Univ, Taipa, Macau, Peoples R China
关键词
Breast cancer; Hub genes; Leading compounds; Targeted therapy; SINGLE-CELL; CHOLESTEROL; STRATEGIES;
D O I
10.1007/s11030-024-11035-z
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Breast cancer is a leading cause of cancer mortality among women globally, with over 2.26 million new cases annually, according to GLOBOCAN 2020. This accounts for approximately 25% of all new female cancers and 15.5% of female cancer deaths. To address this critical public health challenge, we conducted a multi-omics study aimed at identifying hub genes, therapeutic targets, and potential natural product-based therapies. We employed weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis to pinpoint hub genes in breast cancer. Regulatory networks for these genes were constructed by re-analyzing chromatin immunoprecipitation sequencing (ChIP-seq) data from breast cancer cell lines. Additionally, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were utilized to characterize hub gene expression profiles and their relationships with immune cell clusters and tumor microenvironments. Survival analysis based on mRNA and protein expression levels identified prognostic factors and potential therapeutic targets. Lastly, large-scale virtual screening of natural product compounds revealed leading compounds that target squalene epoxidase (SQLE). Our multi-omics analysis paves the way for more effective clinical treatments for breast cancer.
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收藏
页数:14
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