Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
University College London Great Ormond Street Institute of Child Health, London, UK.
Commun Biol. 2022 Sep 7;5(1):884. doi: 10.1038/s42003-022-03808-9.
A fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data.
肿瘤单细胞 mRNA 分析的一个基本步骤是分离癌症和非癌细胞。我们表明，常用的分离方法，即利用平均表达的变化，可能导致错误的生物学结论。相比之下，代表拷贝数变化的等位基因失衡直接检测癌症基因型，并能准确地区分癌症细胞和非癌症细胞。我们的研究结果为从单细胞 mRNA 测序数据中鉴定癌症细胞提供了一种明确的方法。
