Institute of Community Medicine, University of Tromsø, 9037 Tromsø, Norway.
Med Hypotheses. 2011 Aug;77(2):195-8. doi: 10.1016/j.mehy.2011.04.009. Epub 2011 May 6.
The understanding of general models of carcinogenesis have not advanced substantially over the last years despite a rapidly increasing amount of detailed knowledge in molecular biology, genetics and epidemiology, and it has been difficult to come up with specific hypotheses in order to test existing models. Current multistage models consider mutations per se as the driving forces of carcinogenesis. In contrast, novel knowledge in epidemiology and basic research combined with upcoming large scale technologies of transcriptomics and epigenetics offers a new model--the exposure driven functional model. In this model exposures to carcinogenic substances are the determinants of the carcinogenesis leading to functional changes in gene regulation and to mutations. The diversity of exposures and functional changes could give not one, but many different cancer phenotypes. Under this novel model, cessation of exposure could arrest or reverse the carcinogenic process. To test hypotheses based on this novel model, studies with valid exposures measurements, biological material suitable for all "-omics" analyses, and a design that takes into account the time order principle of causality are a prerequisite. In epidemiology, such designs have been proposed, while in basic genetic research most designs only comply with some, but not all of these conditions. The strength of the exposure driven functional model is the potential for testing specific hypothesis of the effect of many exposures on different stages or mutations. An example of such design would be the testing of the effect of continuing or stopping exposures in relation to the last stage of carcinogenesis in a prospective or globolomic design. If successful the exposure driven carcinogenic model and the use of functional genomics could improve the understanding of carcinogenesis and concomitantly the assessment of causality as part of systems epidemiology.
尽管近年来分子生物学、遗传学和流行病学方面的详细知识迅速增加，但对一般致癌模型的理解并没有实质性的进展，也很难提出具体的假设来检验现有的模型。目前的多阶段模型将突变本身视为致癌作用的驱动力。相比之下，流行病学和基础研究方面的新知识与即将出现的转录组学和表观遗传学大规模技术相结合，提供了一种新的模型——暴露驱动的功能模型。在这个模型中，致癌物质的暴露是导致基因调控和突变的致癌作用的决定因素。暴露的多样性和功能变化可能导致的不是一种，而是多种不同的癌症表型。在这种新模型下，停止暴露可以阻止或逆转致癌过程。为了检验基于这一新模型的假设，需要进行有有效暴露测量的研究、适合所有“组学”分析的生物材料以及考虑因果关系时间顺序原则的设计。在流行病学中已经提出了这种设计，而在基础遗传研究中，大多数设计只符合其中一些条件，而不是所有条件。暴露驱动的功能模型的优势在于可以检验许多暴露对不同阶段或突变的影响的具体假设。这种设计的一个例子是，在前瞻性或全基因组设计中，测试继续或停止暴露与致癌作用的最后阶段的关系，以检验暴露的效果。如果成功，暴露驱动的致癌模型和功能基因组学的应用可以提高对致癌作用的理解，同时提高因果关系评估作为系统流行病学的一部分。
