Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
Evolutionary Dynamics Group, Centre for Cancer Genomics & Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Nat Commun. 2020 Feb 25;11(1):1035. doi: 10.1038/s41467-020-14844-6.
Both normal tissue development and cancer growth are driven by a branching process of cell division and mutation accumulation that leads to intra-tissue genetic heterogeneity. However, quantifying somatic evolution in humans remains challenging. Here, we show that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions. We present a new theoretical framework that, applied to whole-genome sequencing data of healthy tissue and cancer, allows inferring the mutation rate and the cell survival/death rate per division. On average, we found that cells accumulate 1.14 mutations per cell division in healthy haematopoiesis and 1.37 mutations per division in brain development. In both tissues, cell survival was maximal during early development. Analysis of 131 biopsies from 16 tumours showed 4 to 100 times increased mutation rates compared to healthy development and substantial inter-patient variation of cell survival/death rates.
正常组织的发育和癌症的生长都受到细胞分裂和突变积累的分支过程的驱动，这导致了组织内的遗传异质性。然而，量化人类的体细胞进化仍然具有挑战性。在这里，我们表明，来自正常组织和癌症组织的单一时间点的多样本基因组数据包含关于单细胞分裂的信息。我们提出了一个新的理论框架，将其应用于健康组织和癌症的全基因组测序数据，可以推断出每个分裂的突变率和细胞存活/死亡率。平均而言，我们发现健康造血过程中每个细胞分裂积累 1.14 个突变，大脑发育过程中每个细胞分裂积累 1.37 个突变。在这两种组织中，细胞在早期发育过程中的存活率最高。对来自 16 个肿瘤的 131 个活检的分析表明，与健康发育相比，突变率增加了 4 到 100 倍，并且细胞存活/死亡率的个体间差异很大。
