Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Abstract

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

Spatial transcriptomics technology in cancer research

“…Through spot deconvolution and prior cell marker genes, researchers can estimate the cell composition of spots and further divide the ST sections into several spatially different areas i.e., tumor area, tumor leading-edge area and paratumor area. Several pilot studies have shown ST-based pathological annotations displayed comparable or even higher accuracy than that from pathologists (38,82,110,112,123) (Table 2). Moreover, ST can distinguish cancer subtypes as well (108).…”

“…It is very important to predict the response of cancer patients for specific cancer therapy clinically. However, it is quite difficult due to complex tumor heterogeneity (2,123). ScRNA-seq has revealed specific cell components could influence treatment response in diverse cancers (127).…”

“…A gene signature usually consists of tens to hundreds of genes, which can serve as a prognostic factor as well. For instance, in PC, Taavitsainen et al proposed a gene signature called PROSGenesis score and further demonstrated high PROSGenesis score was associated with good prognosis (123). In HCC, Wu et al proposed high TLS-50 signature score was associated with good prognosis (16).…”

Microfluidic single‐cell multiomics analysis

“…Microfluidics‐based single‐cell sequencing methods are reliable tools to elucidate tumor growth, development, metastasis, and drug resistance 90 . So far, a variety of cancers, such as lung cancer, 91 ] [ 92 breast cancer, 93 ] [ 94 ] [ 95 prostate cancer, 96 ] [ 97 ] [ 98 ] [ 99 , liver cancer 100 , epithelial ovarian cancer (EOC) 101 , and so on have been explored at the single‐cell level, providing critical insight for cancer monitoring, diagnosis, and treatment.…”

scATACpipe: A nextflow pipeline for comprehensive and reproducible analyses of single cell ATAC-seq data

“…An in-depth analysis of scATAC-seq data can reveal distinct cell populations, roles of key transcription factor, gene regulatory programs underlying cell heterogeneity, and trajectories of cell lineage differentiation (Baek and Lee, 2020;Granja et al, 2021). So far, scATAC-seq has been used for investigating epigenetic heterogeneity in complex tissues during normal development and diseases, such as an array of adult tissues (Cusanovich et al, 2018;Liu et al, 2019;Zhang K. et al, 2021;Chen et al, 2021;Fang et al, 2021), developing tissues and embryos (Preissl et al, 2018;Pijuan-Sala et al, 2020), immune cell development (Buenrostro et al, 2018;Satpathy et al, 2019), spermatogenesis (Wu et al, 2021), and tumor progression (LaFave et al, 2020;Taavitsainen et al, 2021).…”