Cancer represents an evolutionary process through which growing malignant populations genetically diversify, leading to tumour progression, relapse and resistance to therapy. In addition to genetic diversity, the cell-to-cell variation that fuels evolutionary selection also manifests in cellular states, epigenetic profiles, spatial distributions and interactions with the microenvironment. Therefore, the study of cancer requires the integration of multiple heritable dimensions at the resolution of the single cell — the atomic unit of somatic evolution. In this Review, we discuss emerging analytic and experimental technologies for single-cell multi-omics that enable the capture and integration of multiple data modalities to inform the study of cancer evolution. These data show that cancer results from a complex interplay between genetic and non-genetic determinants of somatic evolution.

癌症代表了一个进化过程，通过该过程，不断增长的恶性人群遗传多样化，导致肿瘤进展、复发和对治疗的抵抗。除了遗传多样性之外，推动进化选择的细胞间变异还体现在细胞状态、表观遗传谱、空间分布和与微环境的相互作用中。因此，对癌症的研究需要在单细胞——体细胞进化的原子单位——的分辨率下整合多个可遗传的维度。在这篇综述中，我们讨论了单细胞多组学的新兴分析和实验技术，这些技术能够捕获和整合多种数据模式，为癌症进化研究提供信息。