Assessment of TGx-DDI genes for genotoxicity in a comprehensive panel of chemicals.

IF 3.2 4区医学 Q1 Pharmacology, Toxicology and Pharmaceutics

Toxicology Mechanisms and Methods Pub Date : 2024-09-01 Epub Date: 2024-04-15 DOI:10.1080/15376516.2024.2335966

A Rasim Barutcu

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引用次数: 0

Abstract

Background: The TGx-DDI biomarker identifies transcripts specifically induced by primary DNA damage. Profiling similarity of TGx-DDI signatures can allow clustering compounds by genotoxic mechanism. This transcriptomics-based approach complements conventional toxicology testing by enhancing mechanistic resolution.

Methods: Unsupervised hierarchical clustering and t-distributed stochastic neighbor embedding (tSNE) were utilized to assess similarity of publicly-available per- and polyfluoroalkyl substances (PFAS) and ToxCast chemicals based on TGx-DDI modulation. TempO-seq transcriptomic data after highest chemical concentrations were analyzed.

Results: Clustering discriminated between genotoxic and non-genotoxic compounds while drawing similarity among chemicals with shared mechanisms. PFAS largely clustered distinctly from classical mutagens. However, dynamic range across PFAS types and durations indicated variable potential for DNA damage. tSNE visualization reinforced phenotypic groupings, with genotoxins clustering separately from non-DNA damaging agents.

Discussion: Unsupervised learning approaches applied to TGx-DDI profiles effectively categorizes chemical genotoxicity potential, aiding elucidation of biological response pathways. This transcriptomics-based strategy gives further insight into the role and effect of individual TGx-DDI biomarker genes and complements existing assays by enhancing mechanistic resolution. Overall, TGx-DDI biomarker profiling holds promise for predictive safety screening.

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评估综合化学品组中 TGx-DDI 基因的遗传毒性。

背景TGx-DDI 生物标志物可识别原发性 DNA 损伤特异性诱导的转录本。通过分析 TGx-DDI 特征的相似性，可以按基因毒性机制对化合物进行分类。这种基于转录组学的方法可提高机理分辨率，是对传统毒理学测试的补充：方法：利用无监督分层聚类和 t 分布随机邻域嵌入（tSNE）来评估公开的全氟和多氟烷基物质（PFAS）与基于 TGx-DDI 调节的 ToxCast 化学品的相似性。对最高化学浓度后的 TempO-seq 转录组数据进行了分析：结果：聚类区分了基因毒性和非基因毒性化合物，同时得出了具有共同机制的化学品之间的相似性。全氟辛烷磺酸在很大程度上有别于传统的诱变剂。tSNE 可视化强化了表型分组，将基因毒性物质与非 DNA 损伤物质分开聚类：讨论：应用于 TGx-DDI 图谱的无监督学习方法有效地对化学物质的潜在遗传毒性进行了分类，有助于阐明生物反应途径。这种基于转录组学的策略可进一步深入了解单个 TGx-DDI 生物标记基因的作用和影响，并通过提高机理分辨率对现有检测方法进行补充。总之，TGx-DDI 生物标志物分析有望用于预测性安全性筛选。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Toxicology Mechanisms and Methods 医学-毒理学

CiteScore

6.60

自引率

3.10%

发文量

审稿时长

6-12 weeks

期刊介绍： Toxicology Mechanisms and Methods is a peer-reviewed journal whose aim is twofold. Firstly, the journal contains original research on subjects dealing with the mechanisms by which foreign chemicals cause toxic tissue injury. Chemical substances of interest include industrial compounds, environmental pollutants, hazardous wastes, drugs, pesticides, and chemical warfare agents. The scope of the journal spans from molecular and cellular mechanisms of action to the consideration of mechanistic evidence in establishing regulatory policy. Secondly, the journal addresses aspects of the development, validation, and application of new and existing laboratory methods, techniques, and equipment. A variety of research methods are discussed, including: In vivo studies with standard and alternative species In vitro studies and alternative methodologies Molecular, biochemical, and cellular techniques Pharmacokinetics and pharmacodynamics Mathematical modeling and computer programs Forensic analyses Risk assessment Data collection and analysis.