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苯诱导的血液毒性中与氧化应激途径相关的关键基因的鉴定

Identification of critical genes associated with oxidative stress pathways in benzene-induced hematotoxicity.

作者信息

He Jin, Peng Cheng, Yang XiaoHan, Li Peng, Bai Jin, Jia Qiang, Bo Cunxiang

机构信息

Shandong Academy of Occupational Health and Occupational Medicine & Shandong Provincial Occupational Diseases Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Shandong, China.

Queensland Alliance for Environmental Health Sciences, University of Queensland, Brisbane, Queensland, 4029, Australia.

出版信息

Heliyon. 2024 Aug 3;10(15):e35427. doi: 10.1016/j.heliyon.2024.e35427. eCollection 2024 Aug 15.

DOI:10.1016/j.heliyon.2024.e35427
PMID:39170214
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11336642/
Abstract

BACKGROUND AND AIMS

Bone marrow failure (BMF) is chronic benzene-induced hematotoxicity, which is associated with differential gene expression abnormality. Benzene-induced BMF is characterized by irreversible bone marrow depression. Despite extensive studies have been conducted, there is a lack of reliable, useful and simple diagnostic method for BMF. Previous studies have shown that the aberrant gene expression changes and reactive oxygen species production in bone marrow cells related to the development of BMF. Early detection of differentially expressed genes (DEGs) as potential biomarkers is important for diagnosis and treatment. However, the validation of effective biomarker through DEGs analysis in benzene-induced BMF still deserve to be clarified. This study aimed to identify target genes as potential biomarkers with benzene-induced BMF based on DEGs analysis.

METHODS

First, we developed a benzene-induced BMF mouse model and obtained the DEGs in bone marrow cells of benzene-exposed CD1 mice. Next, after obtaining the DEGs via RNA-Sequencing (RNA-seq) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also used, key genes associated with benzene-induced BMF were identified. Additionally, the key markers for benzene poisoning was evaluated using qRT-PCR technique.

RESULTS

We identified DEGs for further KEGG functional analysis. Ten statistically significantly (up or down) regulated genes, namely Mapk11, Foxo1, Lefty1, Ren1, Bank1, Fgf3, Cdc42ep2, Rasgrf1, P2rx7, and Shank3 were found mainly associated with mitogen-activated protein kinases (MAPK) oxidative stress Further analysis using qRT-PCR identified that eight statistically significant DEGs associated with signaling pathways such as MAPK. We found that the level of mRNA expression of Mapk11, Foxo1, Bank1, Lefty1, Ren1, P2rx7, and Fgf3 genes were increased and Cdc42ep2 gene was decreased in BMF mice compared to control mice. Additionally, we validated the eight candidate genes for potential biomarkers in peripheral blood mononuclear cells of benzene poisoning patients by qRT-PCR.

CONCLUSION

Our results indicated that Mapk11 and Fgf3 were predominantly candidate genes linked to novel biomarkers for benzene hematotoxicity in human beings. Our study will provide new candidate genes as useful biomarkers involved in benzene-induced hematotoxicity.

摘要

背景与目的

骨髓衰竭(BMF)是慢性苯诱导的血液毒性,与基因表达差异异常有关。苯诱导的BMF的特征是不可逆的骨髓抑制。尽管已经进行了广泛的研究,但仍缺乏可靠、实用且简单的BMF诊断方法。先前的研究表明,骨髓细胞中异常的基因表达变化和活性氧生成与BMF的发生发展有关。早期检测差异表达基因(DEGs)作为潜在生物标志物对于诊断和治疗很重要。然而,通过DEGs分析在苯诱导的BMF中验证有效生物标志物仍有待阐明。本研究旨在基于DEGs分析鉴定作为苯诱导BMF潜在生物标志物的靶基因。

方法

首先,我们建立了苯诱导的BMF小鼠模型,并获得了苯暴露的CD1小鼠骨髓细胞中的DEGs。接下来,通过RNA测序(RNA-seq)分析获得DEGs后,还使用了京都基因与基因组百科全书(KEGG)通路分析,鉴定了与苯诱导的BMF相关的关键基因。此外,使用qRT-PCR技术评估苯中毒的关键标志物。

结果

我们鉴定了用于进一步KEGG功能分析的DEGs。发现10个具有统计学显著(上调或下调)调节的基因,即Mapk11、Foxo1、Lefty1、Ren1、Bank1、Fgf3、Cdc42ep2、Rasgrf1、P2rx7和Shank3,主要与丝裂原活化蛋白激酶(MAPK)氧化应激相关。使用qRT-PCR进一步分析确定了8个与MAPK等信号通路相关的具有统计学显著意义的DEGs。我们发现,与对照小鼠相比,BMF小鼠中Mapk11、Foxo1、Bank1、Lefty1、Ren1、P2rx7和Fgf3基因的mRNA表达水平升高,而Cdc42ep2基因的表达水平降低。此外,我们通过qRT-PCR验证了苯中毒患者外周血单个核细胞中8个潜在生物标志物候选基因。

结论

我们的结果表明,Mapk11和Fgf3是与人类苯血液毒性新生物标志物相关的主要候选基因。我们的研究将提供新的候选基因作为参与苯诱导血液毒性的有用生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/ab2c3b0fec1e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/bb9e6c5601d1/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/816f1d1912b7/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/68f6cb98a7b5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/d5554acde188/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/f3a022b94d4d/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/653fdf322b07/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/ab2c3b0fec1e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/bb9e6c5601d1/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/816f1d1912b7/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/68f6cb98a7b5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/d5554acde188/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/f3a022b94d4d/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/653fdf322b07/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32af/11336642/ab2c3b0fec1e/gr6.jpg

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