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

• Published in: Nature communications Vol. 12; no. 1; p. 5307
• Main Authors: Taavitsainen, S., Engedal, N., Cao, S., Handle, F., Erickson, A., Prekovic, S., Wetterskog, D., Tolonen, T., Vuorinen, E. M., Kiviaho, A., Nätkin, R., Häkkinen, T., Devlies, W., Henttinen, S., Kaarijärvi, R., Lahnalampi, M., Kaljunen, H., Nowakowska, K., Syvälä, H., Bläuer, M., Cremaschi, P., Claessens, F., Visakorpi, T., Tammela, T. L. J., Murtola, T., Granberg, K. J., Lamb, A. D., Ketola, K., Mills, I. G., Attard, G., Wang, W., Nykter, M., Urbanucci, A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 06-09-2021; Nature Publishing Group; Nature Portfolio
• Subjects: 13; 38/91; 45/22; 49/39; 631/114/2401; 631/67/589/466; 692/4028/67/589/466; Antineoplastic Agents - therapeutic use; Benzamides - therapeutic use; Cell culture; Cell Line, Tumor; Chromatin; Chromatin - chemistry; Chromatin - metabolism; Decision analysis; Decision making; DNA, Neoplasm - genetics; DNA, Neoplasm - metabolism; Drug Resistance, Neoplasm - genetics; Exome Sequencing; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene sequencing; Humanities and Social Sciences; Humans; Male; Molecular modelling; multidisciplinary; Neoplasm Proteins - genetics; Neoplasm Proteins - metabolism; Nitriles - therapeutic use; Patients; Phenylthiohydantoin - therapeutic use; Prostate - metabolism; Prostate - pathology; Prostate cancer; Prostatic Neoplasms - drug therapy; Prostatic Neoplasms - genetics; Prostatic Neoplasms - mortality; Prostatic Neoplasms - pathology; Quorum sensing; Ribonucleic acid; RNA; Science; Science (multidisciplinary); Sequence Analysis, RNA - methods; Single-Cell Analysis - methods; Subpopulations; Survival Analysis; Transcription; Transcriptome; Transposase
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-25624-1

Prostate cancer is heterogeneous and patients would benefit from methods that stratify those who are likely to respond to systemic therapy. Here, we employ single-cell assays for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identify pre-existing and treatment-persistent cell subpopulations that possess regenerative potential when subjected to treatment. We find distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent cells are 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 as yet unrecognized molecular predictors of treatment response. This suggests that the application of single-cell methods with high analytical resolution in pre-clinical models may powerfully inform clinical decision-making.
Identifying the molecular mechanisms of response to systemic therapy in prostate cancer remains crucial. Here, the authors apply single cell-ATAC and RNAseq to models of early treatment response and resistance to enzalutamide and identify chromatin and gene expression patterns that can predict treatment response.