Human breast tumors have been shown to exhibit extensive inter- and intra-tumor heterogeneity. While recent advances in genomic technologies have allowed us to deconvolute this heterogeneity, few studies have addressed the functional consequences of diversity within tumor populations. We performed single cell RNA and exome sequencing of treatment resistant breast tumor derived xenografts (PDX) to identify population structure. Genes differentially expressed between these subpopulations are involved in proliferation and differentiation. Microfluidic whole genome amplification followed by whole exome capture of single cells, identified driver mutations as well as a number of sub-clonal mutations that are being investigated further. Loss of heterozygocity was observed in 16 TCGA cancer driver genes and novel mutations in 7 known cancer driver genes. Careful comparison of the exome sequencing data allowed the association of driver gene mutation prevalence with tumor progression. These findings are important in our understanding the functional consequences of intra-tumor heterogeneity with respect to clinically important phenotypes such as invasion, metastasis and drug-resistance.

Learning Objectives:

• Develop an understanding of the technology behind single cell genomics 
• Understand the data analysis and quality control processes for single cell data
• Understand single cell expression profiling approaches using high throughput quantitative PCR
• Understand the relevance of single cell genomics in the development of personalized medicine approaches