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Towards a more functional concept of causality in cancer research

机译:在癌症研究中寻求因果关系的更实用概念

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摘要

Advances in molecular technologies challenge the different concepts of causality in biology, epidemiology and multistage mathematical models. The lack of integration of the different aspects of causality into a common framework could postpone our attempts to build a human causal model of carcinogenesis. We present here some aspects of differences in methodology, terminology and traditions between the scientific disciplines and propose a research strategy using functional analyses of the transcriptome and epigenetics to illuminate causality in complex biological systems. Overcoming the challenges of biological material collection suitable for such analyses into a prospective design, this could give unique opportunities for verification of mechanistic information from basic biological research in a human model system. The ultimate goal is to obtain a dynamic causal description of the different carcinogenesis stages. The success of this novel approach depends on the biological relationship between the gene expression of the somatic driver mutations or co-expressed genes in tumours and the gene expressions mirrored in peripheral blood along the different stages of carcinogenesis. The use of gene expression profiles and epigenetics could produce a functional concept of causality to explain the human multistage carcinogenic process.
机译:分子技术的发展挑战了生物学,流行病学和多阶段数学模型中因果关系的不同概念。将因果关系的不同方面整合到一个通用框架中的缺乏可能会推迟我们建立人类致癌因果模型的尝试。我们在这里介绍了科学学科之间在方法,术语和传统上的差异的某些方面,并提出了一种利用转录组和表观遗传学的功能分析来阐明复杂生物系统中因果关系的研究策略。克服了适合进行此类分析的生物材料收集挑战,使其成为前瞻性设计,这可以为验证来自人类模型系统中基础生物学研究的机械信息提供独特的机会。最终目标是获得不同致癌阶段的动态因果关系描述。这种新方法的成功取决于肿瘤中体细胞驱动突变或共表达基因的基因表达与癌变不同阶段外周血中反映的基因表达之间的生物学关系。基因表达谱和表观遗传学的使用可以产生因果关系的功能性概念,以解释人类多阶段致癌过程。

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