Discovery of gene module acting on ubiquitin-mediated proteolysis pathway by co-expression network analysis for endometriosis,Reproductive BioMedicine Online

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Discovery of gene module acting on ubiquitin-mediated proteolysis pathway by co-expression network analysis for endometriosis
Reproductive BioMedicine Online ( IF 3.7 ) Pub Date : 2020-10-14 , DOI: 10.1016/j.rbmo.2020.10.005
Bohan Li ₁ , Sha Wang ₁ , Hua Duan ₁ , Yiyi Wang ₁ , Zhengchen Guo ₁

Affiliation

Research question

Is abnormal gene module expression in the eutopic endometrium related to the occurrence of endometriosis?

Design

Nine datasets of normal and eutopic endometrium were searched and collected through the National Center for Biotechnology Information Gene Expression Omnibus, which included genome-wide expression studies of 71 normal cases and 142 endometriosis cases. Surrogate variable analysis was used for dataset integration. The network module and hub genes were selected by weighted gene co-expression network analysis. Machine learning was used to establish a diagnostic model of endometriosis.

Results

A gene module that was most relevant to endometriosis was selected through weighted gene co-expression network analysis. After further analysis of this module, four hub genes that represent the function of this module were selected: SCAF11, KRAS, MDM2 and KIF3A. Kyoto Encyclopedia of Genes and Genomes enrichment analysis of the four hub genes revealed that all of them were most highly correlated with genes enriched in the ubiquitin-mediated proteolysis pathway. Moreover, in the correlation analysis between hub genes and Jab1, SCAF11 was found to be closely related to Jab1. Furthermore, hub genes were effective indicators for clinical diagnosis. The deep machine learning diagnostic model based on hub genes was highly sensitive.

Conclusions

The gene module identified is highly correlated with endometriosis. The four hub genes in this module degrade p27^kip1 through the ubiquitin-mediated proteolysis pathway to regulate the endometrium cell cycle and affect the development of endometriosis. The hub genes and the deep learning model based on them are valuable for clinical diagnosis.

中文翻译：

通过共表达网络分析发现作用于泛素介导的蛋白水解途径的基因模块用于子宫内膜异位症

研究问题

在位子宫内膜基因模块表达异常与子宫内膜异位症的发生有关吗？

设计

通过国家生物技术信息基因表达综合中心搜索和收集了9个正常和在位子宫内膜数据集，其中包括71例正常病例和142例子宫内膜异位症病例的全基因组表达研究。替代变量分析用于数据集整合。通过加权基因共表达网络分析选择网络模块和枢纽基因。机器学习用于建立子宫内膜异位症的诊断模型。

结果

通过加权基因共表达网络分析选择与子宫内膜异位症最相关的基因模块。经过对该模块的进一步分析，选出了代表该模块功能的四个中枢基因：SCAF11、KRAS、MDM2和KIF3A。京都基因和基因组百科全书对四个枢纽基因的富集分析表明，它们都与泛素介导的蛋白水解途径中富集的基因高度相关。此外，在轮毂的基因和Jab1蛋白之间的相关性分析，SCAF11发现密切相关Jab1蛋白。此外，hub基因是临床诊断的有效指标。基于hub基因的深度机器学习诊断模型高度敏感。