As these GEITP pages have often discussed, in order to understand the contribution of genes and other factors to any selected phenotype (trait, such as schizophrenia, obesity, response to a drug, or response to an environmental toxicant) — assays have been developed for gene-scanning and some epigenetics effects. Epigenetics includes DNA methylation, RNA interference (e.g. microRNAs), histone modifications, and chromatin remodeling; there are available assays and kits and procedures for the first two, whereas the latter two still require much more research before assays/procedures become available. An additional challenge is realizing that virtually all tissues and organs comprise many different types of cells, whose epigenomes will differ from one another. ☹
Epigenetic heterogeneity plays a pivotal role in enabling genetically identical cells to take on remarkably heterogeneous states and fates — not only in development (e.g. a heart muscle cell carries out different functions from a lung bronchial epithelial cell; a leaf cell of an oak tree has different functions than a root cell), but also in disease processes such as cancer. Epigenetically “permissive states” have been proposed to potentially predispose rare subpopulations of cancer cells to drug resistance (when challenged with a chemotherapeutic agent). How can we identify and characterize such rare subpopulations — on a genome-wide scale? Recently, methods have been developed for quantifying molecular heterogeneity in single cells. For example, single-cell RNA-seq measures transcriptional heterogeneity, and single-cell ATAC–seq measures relative chromatin accessibility. Needless to say, it has been particularly challenging to develop methods that directly interrogate histone modifications — and interactions between transcription factors and DNA — in single cells.
Authors [see attached first article] present a new method (single-cell chromatin-immunoprecipitation expression analysis; scChIP–seq) for genome-wide profiling of abundant histone modifications in single cells. Using this new method, authors have achieved a 10-fold gain in coverage per cell — as compared with that of previous methods, while profiling thousands of cells in a single experiment..!!! Using this method, authors [see attached second article] profiled patient-derived tumor xenografts (in this case, surgical grafts of human breast tumor grown on another species, in this case, mouse) and observed intriguing epigenetic heterogeneity within drug-sensitive and drug-resistant tumors.
Authors [see attached second article] used patient-derived xenograft models of acquired resistance to chemotherapy and targeted therapy in breast cancer, and they discovered that a subset of cells within the untreated drug-sensitive tumors share a common chromatin signature with resistant cells. This finding could not happen using bulk (i.e. whole-tissue) approaches. Both cells from untreated tumors, and cells from resistant tumors, were found to have lost chromatin marks, specifically in H3K27me3 (trimethylation at lysine-27 of histone H3, a downstream target of the polycomb repressive complex 2 (PRC2), which has histone methlyltransferase activity). H3K27me3 is associated with stable transcriptional repression — for genes known to promote resistance to treatment.
Authors corroborated their findings by comparison to previous single-cell gene expression data, and they show their new method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone. This scChIP–seq approach paves the way to examine the role of chromatin heterogeneity, not just in cancer, but in other diseases and healthy systems, especially during studies of developmental biology and cellular differentiation. 😊
DwN
Nat Biotechnol 2o15; 33: 1165-1172 & Nat Genet June 2o19; 51: 1060-1066 and News’N’Views editorial pp 931-932