与乳腺癌预后相关的8种组蛋白甲基化修饰调节因子的鉴定

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Yan-Ni Cao, Xiao-Hui Li, Xing-Jie Chen, Kang-Cheng Xu, Jun-Yuan Zhang, Hao Lin, Yu-Xian Liu
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引用次数: 0

摘要

组蛋白甲基化是一种重要的表观遗传修饰过程,由组蛋白甲基转移酶、组蛋白去甲基化酶和组蛋白甲基化解读蛋白协同作用,在癌症的发生发展中起着关键作用。本研究围绕组蛋白甲基化修饰调控因子构建风险评分模型,并进行多维度综合分析,揭示其在乳腺癌预后和药物敏感性中的潜在作用。首先,对144个组蛋白甲基化修饰调节因子(HMMRs)进行差异分析和单因素Cox回归分析,筛选出9个与生存相关的差异表达HMMRs。其次,采用LASSO回归算法构建由8个hmmr组成的风险评分模型,在训练队列和验证队列中表现出独立的预测值。然后,免疫分析显示,按照风险评分模型划分的高危组患者免疫反应减弱。此外,通过对高危组和低危组差异表达基因(differential expression genes, DEGs)的功能分析,我们证实差异表达基因主要影响核质和肿瘤微环境。最后,药物敏感性分析表明,我们的模型可以用于药物筛选和确定治疗BRCA患者的潜在药物。综上所述,这8种HMMRs可能是影响BRCA患者预后和药物敏感性的关键因素。
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 Eight Histone Methylation Modification Regulators Associated With Breast Cancer Prognosis

Identification of Eight Histone Methylation Modification Regulators Associated With Breast Cancer Prognosis

Histone methylation is an important epigenetic modification process coordinated by histone methyltransferases, histone demethylases and histone methylation reader proteins and plays a key role in the occurrence and development of cancer. This study constructed a risk scoring model around histone methylation modification regulators and conducted a multidimensional comprehensive analysis to reveal its potential role in breast cancer prognosis and drug sensitivity. First, 144 histone methylation modification regulators (HMMRs) were subjected to differential analysis and univariate Cox regression analysis, and nine differentially expressed HMMRs associated with survival were screened out. Next, a risk scoring model consisting of eight HMMRs was constructed using the LASSO regression algorithm, exhibiting independent predictive values in training and validation cohorts. Then, immune analysis shows that patients in the high-risk group divided by the risk scoring model has weakened the immune response. In addition, through functional analysis of differentially expressed genes (DEGs) between high-risk and low-risk groups, we confirmed that the DEGs mainly affected the nucleoplasm and tumour microenvironment. Finally, drug sensitivity analysis demonstrated that our model could be useful for drug screening and identify potential drugs for treating BRCA patients. In conclusion, these eight HMMRs may be key factors in the prognosis and drug sensitivity of BRCA patients.

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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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