Description

Single-cell epigenomic variability reveals functional cancer heterogeneity

Ulrike M. Litzenburger¹, Jason D. Buenrostro^4,5, William J. Greenleaf ^1,2,3 and Howard Y. Chang¹

¹Center for Personal Dynamic Regulomes, Stanford University; ² Department of Genetics, Stanford University; ³Department of Applied Physics, Stanford University; ⁴Broad Institute of MIT and Harvard; ⁵Harvard Society of Fellows, Harvard University

Cell-to-cell heterogeneity is a major driver of cancer evolution, progression, and emergence of drug resistance. Epigenomic variation at the single-cell level can rapidly create cancer heterogeneity but is difficult to detect and assess functionally. Data generated from single-cell techniques are purely descriptive and require downstream functional validation to link observed heterogeneity to functional subpopulations, such as those with metastatic capabilities or stem cell-like properties. However, it is difficult to combine single-cell approaches with functional cellular assays unless single cells can be identified and sorted using cell surface markers. Yet, cell surface markers linked to an epigenomic state are often unknown.

We developed a strategy to bridge the gap between measurement and function in single-cell epigenomics. Using single-cell chromatin accessibility and RNA-seq data in K562 leukemic cells, we identify the cell surface marker CD24 as co-varying with chromatin accessibility changes linked to GATA transcription factors in single cells. Cell sorting of CD24 high versus low cells isolated GATA1 and GATA2 high versus low cells. GATA high versus low cells display differential gene regulatory networks, differential drug sensitivity, and differential self-renewal capacity. Lineage tracing experiments show that GATA/CD24^hi cells have the capability to rapidly reconstitute the heterogeneity within the entire starting population, suggesting that GATA expression levels drive a phenotypically relevant source of epigenomic plasticity.

Concluding, our strategy can guide prospective characterization of cancer heterogeneity. Identified epigenomic subpopulations impact drug sensitivity and the clonal dynamics of cancer evolution.