|本期目录/Table of Contents|

[1]赵一凡,胡一诺,陈维琳,等.乳腺癌个体特异的差异甲基化基因识别*[J].生物医学工程研究,2022,03:293-300.
 ZHAO Yifan,HU Yinuo,CHEN Weilin,et al.Individual differential methylation gene recognition in breast cancer[J].Journal of Biomedical Engineering Research,2022,03:293-300.
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乳腺癌个体特异的差异甲基化基因识别*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2022年03期
页码:
293-300
栏目:
出版日期:
2022-09-25

文章信息/Info

Title:
Individual differential methylation gene recognition in breast cancer
文章编号:
1672-6278 (2022)03-0293-08
作者:
赵一凡 胡一诺 陈维琳陈园园△
南京农业大学 理学院,南京 210095
Author(s):
ZHAO Yifan HU Yinuo CHEN Weilin CHEN Yuanyuan
College of Science, Nanjing Agricultural University, Nanjing 210095, China
关键词:
DNA甲基化甲基化异常基因Grubbs算法个体特异分析Kaplan-Meier生存曲线生存预测
Keywords:
DNA methylation Abnormal methylation genes Grubbs algorithm Individual specific analysis Kaplan Meier survival curve Survival prediction
分类号:
R318;R737.9
DOI:
10.19529/j.cnki.1672-6278.2022.03.11
文献标识码:
A
摘要:
针对癌症个体之间明显的异质性,本研究提出一种个体特异的差异甲基化基因识别方法并构建乳腺癌预后模型,在个体水平分析乳腺癌的发生发展。基于TCGA数据库中的乳腺癌甲基化数据,利用差异分析法和Grubbs离群值检测法识别个体特异的差异甲基化基因,通过基因富集分析得到12条与乳腺癌相关的生物通路。利用Cox回归模型和Lasso回归模型,筛选出47个和乳腺癌生存预后显著相关的预后基因。基于基因甲基化值构建乳腺癌生存预后模型,对乳腺癌患者进行生存预后分析。结果显示,构建的生存预后模型能成功区分乳腺癌患者的高风险组和低风险组。研究结果表明,本研究方法不仅能鉴定出乳腺癌共有的异常甲基化基因,同时能够识别出个体特异的差异甲基化基因;构建的生存预后模型可以稳健地预测乳腺癌患者的生存预后状态,有利于从个体基因甲基化的层面更好地理解乳腺癌的发生发展机制,促进精准医疗的发展。
Abstract:
In view of significant heterogeneity between individuals with cancer, we proposed an individual-specific differential methylation gene identification method and constructed a prognostic model for breast cancer to analyze the occurrence and development of breast cancer at the individual level. Based on the data of breast cancer methylation in TCGA database, the individual-specific differential methylation genes were identified by difference analysis method and Grubbs outlier detection method. Gene enrichment analysis revealed 12 biological pathways related to breast cancer. Prognostic genes were screened by univariate Cox proportional risk regression and Lasso regression. Forty-seven prognostic genes were significantly associated with survival and prognosis of breast cancer. We constructed the survival prognostic model of breast cancer based on gene methylation value and analyzed the survival and prognosis of breast cancer patients. The final survival prognosis model was able to successfully distinguish between the high-risk group and low-risk group. Based on the individual-specific differential methylation gene identification method could identified not only the common abnormal methylation genes in breast cancer, but also the individual-specific differential methylation genes. In addition, the survival prognostic model constructed based on individual specific differential methylation genes could robustly predict the survival prognostic status of breast cancer patients. It is conducive to better understand the occurrence and development mechanism of breast cancer from the perspective of individual gene methylation, promote the development of precision medicine.

参考文献/References

备注/Memo

备注/Memo:
(收稿日期:2022-03-30)第65批中国博士后科学基金项目(2019M651658);南京农业大学校级大学生创新训练项目(202123XX10)。△通信作者Email: chenyuanyuan@njau.edu.cn
更新日期/Last Update: 2022-11-08