Single-cell RNA Sequencing to Elucidate Tumor and Tumor Subclone-Specific Cancer Phenotypes
Year: 2020
Type: article
Abstract: Massively parallel DNA/RNA sequencing has empowered detailed maps of clonal variation in human cancer, both through an inference of clonal substructure by analysis of variant allele frequencies in bulk tumor cell populations and direct sequencing of single cells. Bulk cell DNA-sequencing collected at multiple time points can be used to estimate the mutational, copy number, and subclone population evolution of a tumor over time or in response to treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) are providing opportunities to evaluate decouple the transcriptional behavior of tumor and normal cells and explore the cellular diversity within the tumor. Here we present a methodology to evaluate the transcriptional effects of somatic genome alterations in cancer cells, and to explore the cellular diversity across subclonal cell subpopulations within an individual tumor, by linking single cells from scRNA-seq data to genetic variant profiles and subclone populations inferred using bulk (whole-genome or whole-exome) DNA-sequencing. This workflow, implemented in our scBayes tool, consists of the following steps: (1) identification of somatically acquired mutations (either point mutations or copy number changes such as deletions/amplifications); (2) reconstruction of subclone structure within either one or a series of tumor biopsies from the patient; (3) extraction of subclone-defining “characters” i.e. somatic mutations or copy number events (deletions / amplifications); (4) genotyping of such subclone-defining characters in single cells, based on the single-cell RNA-Seq data; (5) the assignment of each cell to a subclone; (6) characterization of subclone-specific phenotypes based on the expression profiles / cell states of the single cells assigned to each subclone. We present the application of this methodology to study subclone-specific evolution of transcriptional behavior across disease progression in metastatic breast cancer and chronically.
Source: PubMed Central
Author: Gábor Marth
Institution: University of Utah
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3081153345