Precise identification of cancer cells from allelic imbalances in single cell transcriptomes

Abstract

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.

Haplotype-enhanced inference of somatic copy number profiles from single-cell transcriptomes

“…Precisely distinguishing the malignant cells within heterogeneous cell mixtures is a well-established problem 6,9 . Since the non-malignant cells do not share aberrations with the tumor, the tumor population should be isolated as a distinct clade in the reconstructed clonal phylogeny (Figure 3c).…”

“…Expression-based methods infer the presence of CNVs based on a general expectation that local amplifications or deletions will on average result in up- or down-regulation of genes within the affected region of the genome, respectively. Such approach can produce false-positive results due to local variations in expression unrelated to genomic copy numbers 9 . Allele-based approaches examine deviations of the relative allele frequency (“B-allele frequency” or BAF) caused by CNVs, and are less affected by sample or cell type variations 5,8 .…”