Inferring Copy Number from Triple-Negative Breast Cancer Patient Derived Xenograft scRNAseq Data Using scCNA.

Abstract

Cancer can develop from an accumulation of alterations, some of which cause a nonmalignant cell to transform to a malignant state exhibiting increased rate of cell growth and evasion of growth suppressive mechanisms, eventually leading to tissue invasion and metastatic disease. Triple-negative breast cancers (TNBC) are heterogeneous and are clinically characterized by the lack of expression of hormone receptors and human epidermal growth factor receptor 2 (HER2), which limits its treatment options. Since tumor evolution is driven by diverse cancer cell populations and their microenvironment, it is imperative to map TNBC at single-cell resolution. Here, we describe an experimental procedure for isolating a single-cell suspension from a TNBC patient-derived xenograft, subjecting it to single-cell RNA sequencing using droplet-based technology from 10× Genomics and analyzing the transcriptomic data at single-cell resolution to obtain inferred copy number aberration profiles, using scCNA. Data obtained using this single-cell RNA sequencing experimental and analytical methodology should enhance our understanding of intratumor heterogeneity which is key for identifying genetic vulnerabilities and developing effective therapies.