GSE163210
Cancer phylogenetics using single-cell RNA-seq data
To test if scRNA-seq contains sufficient phylogenetic information to reconstruct a population history of cancer, immunosuppressed NU/J mice were injected with human cancer cells (MDA-MB-231-LM2). The tumors that develop are derived from the same population and thus share a common ancestor, but evolved independently in each mouse and should form separate clades on reconstructed phylogenetic trees when analysed together. We explore and compare results of phylogenetic analyses based on both expression levels and SNVs called from our scRNA-seq data. Both techniques are shown to be useful for reconstructing phylogenetic relationships between cells, refecting the clonal composition of a tumor. Without an explicit error model, standardized expression values appears to be more powerful and informative than the SNV values at a lower computational cost, due to being a by-product of standard expression analysis. Our results suggest that scRNA-seq can be a competitive alternative or useful addition to conventional scDNA-seq phylogenetic reconstruction. Our results open up a new direction of somatic phylogenetics based on scRNA-seq data. Further research is required to refne and improve these approaches to capture the full picture of somatic evolutionary dynamics in cancer. Overall design: Phylogenetic analysis of 5 tumour samples from 3 individual mice seeded with human cancer cells derived from a single cell line.