Stiehl Daniel P, Tritto Elaine, Chibout Salah-Dine, Cordier André, Moulin Pierre
Translational Medicine at the Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland. Translational Medicine at the Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland. Translational Medicine at the Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland. Translational Medicine at the Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland. Translational Medicine at the Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
ILAR J. 2017 Jul 1;58(1):69-79. doi: 10.1093/ilar/ilx016.
Originally conceptualized as an integrated approach combining conventional toxicology methods with genome-wide expression profiling, toxicogenomics has promised to provide unequivocal relationships between the molecular changes elicited by a compound or a target pathway and the lesions that appear subsequently in the tissues. However, the discipline has only partially delivered on this promise, and the number of publications and submissions related to toxicogenomics is stagnating. The purpose of this article is to outline key factors contributing to a successful implementation of toxicogenomics in the drug discovery and development process. Paradigms and methods of toxicogenomics are briefly reviewed, and the prominence of biostatistics and its limitations in the particular context of nonclinical toxicology studies are discussed. We present specific approaches for pathophysiological contextualization of gene expression data derived from tissues with lesions at variable incidence and severity: "unmixing" (deconvolution) of molecular expression profiles from complex tissues, the invaluable contribution of reference data, the role of establishing causation between expression signals and pathologic changes (phenotypic anchoring), and especially molecular localization. These approaches compensate for the limitations of biostatistical analysis, which in turn, derive from tissue heterogeneity. Finally, impactful applications of toxicogenomics along the drug discovery and development process are exemplified, from the evaluation of potential target toxicities to the selection of candidate compounds and elucidation of the molecular and cellular mechanisms leading to chronic toxicity.
毒理基因组学最初被概念化为一种将传统毒理学方法与全基因组表达谱分析相结合的综合方法，有望在化合物或目标途径引发的分子变化与随后在组织中出现的病变之间提供明确的关联。然而，该学科仅部分兑现了这一承诺，与毒理基因组学相关的出版物和投稿数量正趋于停滞。本文旨在概述在药物发现和开发过程中成功实施毒理基因组学的关键因素。简要回顾了毒理基因组学的范式和方法，并讨论了生物统计学在非临床毒理学研究特定背景下的重要性及其局限性。我们提出了针对从发病率和严重程度各异的病变组织中获取的基因表达数据进行病理生理背景分析的具体方法：对复杂组织的分子表达谱进行“解混”（去卷积）、参考数据的宝贵贡献、在表达信号与病理变化之间建立因果关系（表型锚定）的作用，尤其是分子定位。这些方法弥补了生物统计学分析的局限性，而生物统计学分析的局限性又源于组织异质性。最后，举例说明了毒理基因组学在药物发现和开发过程中的重要应用，从评估潜在靶点毒性到选择候选化合物以及阐明导致慢性毒性的分子和细胞机制。
