Molecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer (WHO), Lyon, France.
Basic Clin Pharmacol Toxicol. 2017 Sep;121 Suppl 3:16-22. doi: 10.1111/bcpt.12690. Epub 2017 Feb 3.
Mutation spectra in cancer genomes provide information on the disease aetiology and the causality underlying the evolution and progression of cancer. Genome-wide mutation patterns reflect the effects of mutagenic insults and can thus reveal past carcinogen-specific exposures and inform hypotheses on the causative factors for specific cancer types. To identify mutation profiles in human cancers, single-gene studies were first employed, focusing mainly on the tumour suppressor gene TP53. Furthermore, experimental studies had been developed in model organisms. They allowed the characterization of the mutation patterns specific to known human carcinogens, such as polycyclic aromatic hydrocarbons or ultraviolet light. With the advent of massively parallel sequencing, mutation landscapes become revealed on a large scale, in human primary tumours and in experimental models, enabling deeper investigations of the functional and structural impact of mutations on the genome, including exposure-specific base-change fingerprints known as mutational signatures. These studies can now accelerate the identification of aetiological factors, contribute to carcinogen evaluation and classification and ultimately inform cancer prevention measures.
癌症基因组中的突变谱提供了有关疾病病因以及癌症演变和进展背后因果关系的信息。全基因组突变模式反映了诱变因素的影响,因此可以揭示过去特定致癌剂的暴露情况,并为特定癌症类型的致病因素提供假设。为了确定人类癌症中的突变特征,首先采用了单基因研究,主要集中在肿瘤抑制基因 TP53 上。此外,还在模式生物中开展了实验研究。它们允许对已知人类致癌剂(如多环芳烃或紫外线)特有的突变模式进行特征描述。随着大规模平行测序的出现,突变景观在人类原发性肿瘤和实验模型中大规模揭示,使我们能够更深入地研究突变对基因组的功能和结构影响,包括已知的暴露特异性碱基变化指纹,称为突变特征。这些研究现在可以加速病因因素的确定,有助于致癌剂的评估和分类,并最终为癌症预防措施提供信息。