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通过动态网络生物标志物测定 PM 有机提取物诱导恶性转化过程中的临界点。

Determination of tipping point in course of PM organic extracts-induced malignant transformation by dynamic network biomarkers.

机构信息

Department of Toxicology, School of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou 510080, China.

Department of Toxicology, School of Public Health, Qingdao University, Qingdao 266021, China.

出版信息

J Hazard Mater. 2022 Mar 15;426:128089. doi: 10.1016/j.jhazmat.2021.128089. Epub 2021 Dec 16.

DOI:10.1016/j.jhazmat.2021.128089
PMID:34933256
Abstract

The dynamic network biomarkers (DNBs) are designed to identify the tipping point and specific molecules in initiation of PM-induced lung cancers. To discover early-warning signals, we analyzed time-series gene expression datasets over a course of PM organic extraction-induced human bronchial epithelial (HBE) cell transformation (0~16 week). A composition index of DNB (CI) was calculated to determine correlations and fluctuations in molecule clusters at each timepoint. We identified a group of genes with the highest CI at the 10 week, implicating a tipping point and corresponding DNBs. Functional experiments revealed that manipulating respective DNB genes at the tipping point led to remarkable changes in malignant phenotypes, including four promoters (GAB2, NCF1, MMP25, LAPTM5) and three suppressors (BATF2, DOK3, DAP3). Notably, co-altered expression of seven core DNB genes resulted in an enhanced activity of malignant transformation compared to effects of single-gene manipulation. Perturbation of pathways (EMT, HMGB1, STAT3, NF-κB, PTEN) appeared in HBE cells at the tipping point. The core DNB genes were involved in regulating lung cancer cell growth and associated with poor survival, indicating their synergistic effects in initiation and development of lung cancers. These findings provided novel insights into the mechanism of dynamic networks attributable to PM-induced cell transformation.

摘要

动态网络生物标志物(DNB)旨在识别 PM 诱导肺癌起始时的转折点和特定分子。为了发现预警信号,我们分析了 PM 有机提取物诱导人支气管上皮(HBE)细胞转化(0~16 周)过程中的时间序列基因表达数据集。计算了 DNB 的组成指数(CI),以确定每个时间点分子簇的相关性和波动。我们确定了一组在第 10 周具有最高 CI 的基因,表明存在一个转折点和相应的 DNB。功能实验表明,在转折点操纵各自的 DNB 基因会导致恶性表型的显著变化,包括四个启动子(GAB2、NCF1、MMP25、LAPTM5)和三个抑制子(BATF2、DOK3、DAP3)。值得注意的是,与单基因操作相比,七个核心 DNB 基因的共同改变表达导致恶性转化活性增强。EMT、HMGB1、STAT3、NF-κB 和 PTEN 等途径在 HBE 细胞中的转折点发生改变。核心 DNB 基因参与调节肺癌细胞生长,并与不良生存相关,表明它们在肺癌起始和发展中的协同作用。这些发现为 PM 诱导的细胞转化归因于动态网络的机制提供了新的见解。

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