Nature CommunicationsCancer BiologyPeer-reviewed journal article
Epigenetic reprogramming shapes the cellular landscape of schwannoma
S. J. Liu, T. Casey-Clyde, N. W. Cho, J. Swinderman, M. Pekmezci, M. C. Dougherty, K. Foster, W. C. Chen, J. E. Villanueva-Meyer, D. L. Swaney, H. N. Vasudevan, A. Choudhury, J. D. Breshears, U. E. Lang, C. D. Eaton, K. J. Hiam-Galvez, E. Stevenson, K.-H. Chen, B. V. Lien, D. Wu, S. E. Braunstein, P. K. Sneed, S. T. Magill, D. A. Lim, M. W. McDermott, , D. R. Raleigh
Abstract
Cell state evolution underlies tumor development and response to therapy1, but mechanisms specifying cancer cell states and intratumor heterogeneity are incompletely understood. Schwannomas are the most common tumors of the peripheral nervous system and are treated with surgery and ionizing radiation2-5. Schwannomas can oscillate in size for many years after radiotherapy6,7, suggesting treatment may reprogram schwannoma cells or the tumor microenvironment. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas. We find schwannomas are comprised of 2 molecular groups distinguished by reactivation of neural crest development pathways or misactivation of nerve injury mechanisms that specify cancer cell states and the architecture of the tumor immune microenvironment. Schwannoma molecular groups can arise independently, but ionizing radiation is sufficient for epigenetic reprogramming of neural crest to immune-enriched schwannoma by remodeling chromatin accessibility, gene expression, and metabolism to drive schwannoma cell state evolution and immune cell infiltration. To define functional genomic mechanisms underlying epigenetic reprograming of schwannomas, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of cancer evolution and establish a paradigm of epigenetic reprograming of cancer in response to radiotherapy.
- organism: human
- assay: scRNA-seq
- assay: ATAC-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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