Laboratory of Molecular Medicine, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Department of Surgery, Kyushu University Beppu Hospital, Beppu, Japan.
J Hum Genet. 2021 Sep;66(9):869-878. doi: 10.1038/s10038-021-00930-0. Epub 2021 May 13.
Understanding cancer evolution provides a clue to tackle therapeutic difficulties in colorectal cancer. In this review, together with related works, we will introduce a series of our studies, in which we constructed an evolutionary model of colorectal cancer by combining genomic analysis and mathematical modeling. In our model, multiple subclones were generated by driver mutation acquisition and subsequent clonal expansion in early-stage tumors. Among the subclones, the one obtaining driver copy number alterations is endowed with malignant potentials to constitute a late-stage tumor in which extensive intratumor heterogeneity is generated by the accumulation of neutral mutations. We will also discuss how to translate our understanding of cancer evolution to a solution to the problem related to therapeutic resistance: mathematical modeling suggests that relapse caused by acquired resistance could be suppressed by utilizing clonal competition between sensitive and resistant clones. Considering the current rate of technological development, modeling cancer evolution by combining genomic analysis and mathematical modeling will be an increasingly important approach for understanding and overcoming cancer.
了解癌症进化为解决结直肠癌治疗中的困难提供了线索。在这篇综述中,我们将结合相关工作,介绍一系列研究成果,通过整合基因组分析和数学建模,构建了结直肠癌的进化模型。在我们的模型中,早期肿瘤中驱动突变的获得和随后的克隆扩张产生了多个亚克隆。在这些亚克隆中,获得驱动拷贝数改变的亚克隆具有恶性潜能,构成晚期肿瘤,其中大量的肿瘤内异质性是由中性突变的积累产生的。我们还将讨论如何将我们对癌症进化的理解转化为解决治疗耐药性相关问题的方法:数学模型表明,利用敏感和耐药克隆之间的克隆竞争,可以抑制获得性耐药引起的复发。考虑到当前技术发展的速度,通过整合基因组分析和数学建模来模拟癌症进化将成为理解和克服癌症的一种越来越重要的方法。