RESUMEN
We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating sub-5-kb resolution 3D genome maps by in situ Hi-C. Contact maps at sub-5-kb resolution allow identification of individual DNA loops, domain organization, and large-scale genome compartmentalization. We observed differences in looping architectures among GSCs from different patients, suggesting that 3D genome architecture is a further layer of inter-patient heterogeneity for glioblastoma. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including the convergence of multiple super enhancers to individual stemness genes within individual cells. We show that the number of loops contacting a gene correlates with elevated transcription. These results indicate that stemness genes are hubs of interaction between multiple regulatory regions, likely to ensure their sustained expression. Regions of open chromatin common among the GSCs tested were poised for expression of immune-related genes, including CD276 We demonstrate that this gene is co-expressed with stemness genes in GSCs and that CD276 can be targeted with an antibody-drug conjugate to eliminate self-renewing cells. Our results demonstrate that integrated structural genomics data sets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.
Asunto(s)
Neoplasias Encefálicas/genética , Cromatina/ultraestructura , Mapeo Cromosómico/métodos , Regulación Neoplásica de la Expresión Génica , Glioblastoma/genética , Proteínas de Neoplasias/genética , Antígenos B7/antagonistas & inhibidores , Antígenos B7/genética , Antígenos B7/metabolismo , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/patología , Proliferación Celular , Cromatina/química , Elementos de Facilitación Genéticos , Perfilación de la Expresión Génica , Heterogeneidad Genética , Genoma Humano , Genómica/métodos , Glioblastoma/metabolismo , Glioblastoma/patología , Humanos , Terapia Molecular Dirigida , Proteínas de Neoplasias/clasificación , Proteínas de Neoplasias/metabolismo , Células Madre Neoplásicas/metabolismo , Células Madre Neoplásicas/patología , Cultivo Primario de Células , ARN Interferente Pequeño/genética , ARN Interferente Pequeño/metabolismo , Transcripción GenéticaRESUMEN
BACKGROUND: Diffuse invasion of glioblastoma cells through normal brain tissue is a key contributor to tumor aggressiveness, resistance to conventional therapies, and dismal prognosis in patients. A deeper understanding of how components of the tumor microenvironment (TME) contribute to overall tumor organization and to programs of invasion may reveal opportunities for improved therapeutic strategies. RESULTS: Towards this goal, we apply a novel computational workflow to a spatiotemporally profiled GBM xenograft cohort, leveraging the ability to distinguish human tumor from mouse TME to overcome previous limitations in the analysis of diffuse invasion. Our analytic approach, based on unsupervised deconvolution, performs reference-free discovery of cell types and cell activities within the complete GBM ecosystem. We present a comprehensive catalogue of 15 tumor cell programs set within the spatiotemporal context of 90 mouse brain and TME cell types, cell activities, and anatomic structures. Distinct tumor programs related to invasion align with routes of perivascular, white matter, and parenchymal invasion. Furthermore, sub-modules of genes serving as program network hubs are highly prognostic in GBM patients. CONCLUSION: The compendium of programs presented here provides a basis for rational targeting of tumor and/or TME components. We anticipate that our approach will facilitate an ecosystem-level understanding of the immediate and long-term consequences of such perturbations, including the identification of compensatory programs that will inform improved combinatorial therapies.