Integrated single-cell whole genome sequencing and spatial transcriptomics reveal latent intra-tumoral heterogeneity in ovarian cancer

Abstract

The mortality rate of ovarian cancer remains disproportionately high compared to its incidence. This is partly due to a high level of intra-tumoral heterogeneity that promotes disease recurrence and treatment failure. In this study, we describe degrees of heterogeneity revealed by single-cell whole genome sequencing and spatial transcriptomics of five epithelial ovarian carcinomas. At the cellular level, we describe pseudo-diploid cells that match the malignant cell population in both somatic variant and copy number patterns. At the clonal and subclonal levels, we describe diversification associated with copy number gains and whole genome doubling. In multi-clonal samples, we infer evolutionary relationships from single cell copy number, loss of heterozygosity analysis, and somatic variant detection, and correlate these with tissue histology and gene expression programs. In one sample, we identify functionally consequential copy number alterations that contribute to molecular diversity, cell proliferation, and inflammation in a minor clone that persisted without major expansion alongside a more complex major clone. In another, we describe a complex evolutionary history including a spontaneous reversion of a driver mutation in a secondary clone, which correlated with a switch in oncogenic expression programs.