Abstract: Tumor is generally believed to originate from a single cell, which develops into a genetically heterogeneous population after continuous cell divisions under the principle of “survival of the fittest”. Tumor evolution is a dynamic process, and reconstruction of the disappeared history is challenging but crucial for both understanding the mechanism and personalized therapy. Genetic alterations can be used as molecular clues to tumor evolution, with somatic mutations as a key tracer. Although bulk-level sequencing of a large number of tumor specimens has provided useful information on the mutational landscape, it is not easy to utilize such data for evolutionary history study. This is because bulk-level mutation prevalence may be confounded by various factors, such as tumor purity, copy number alterations, and more severely, the overlapping of prevalence ranges for mutations from similarly sized subclones. Single-cell mutational profiling overcomes such challenges, enabling precise identification of co-mutation groups and tumor subclones. This further enables successful reconstruction of tumor evolution, even for a solid tumor sample collected at a single time point. Technical and analytical advancements in single-cell profiling, such as mutation calling from single-cell RNA-Seq or spatial transcriptomic data, will provide further insights into tumor evolution and cancer treatment.

Key words: tumor evolution, intratumoral heterogeneity, subclone, somatic mutations, single-cell sequencing

摘要： 一般认为肿瘤起源于单个细胞，根据“适者生存”的原则，经过持续分裂发展成遗传异质性的细胞群体。肿瘤演化是一个动态过程，重建消失的历史虽具挑战性，但对理解肿瘤发生机制和个性化治疗至关重要。遗传变异可以为肿瘤演化提供线索，而体细胞突变是关键示踪物。对大量肿瘤样本进行细胞群体水平测序可提供有用的突变景观信息，但利用此类数据进行肿瘤演化研究并不容易。这是因为细胞群体水平的突变发生频率可能受到多种因素干扰，如肿瘤纯度、拷贝数变化、以及来自大小相似肿瘤亚克隆的突变发生频率范围重叠。单细胞突变分析克服了这些挑战，可以精准鉴定共突变分组和肿瘤亚克隆。这使重构肿瘤演化历史成为可能，即使是面对单一时间点采集的实体肿瘤样本。单细胞分析的技术和方法进展，例如从单细胞RNA测序或空间转录组数据鉴定突变，将为肿瘤演化和癌症治疗提供更多见解。

关键词: 肿瘤演化，肿瘤异质性，亚克隆，体细胞突变，单细胞测序