RT Journal
A1 Johnston, Michael
A1 Nikolic, Ana
A1 Ninkovic, Nicoletta
A1 Guilhamon, Paul
A1 Cavalli, Florence
A1 Seaman, Steven
A1 Zemp, Franz
A1 Lee, John
A1 Abdelkareem, Aly
A1 Ellestad, Katrina
A1 Murison, Alex
A1 Kushida, Michelle
A1 Coutinho, Fiona
A1 Ma, Yussanne
A1 Mungall, Andrew
A1 Moore, Richard
A1 Marra, Marco
A1 Taylor, Michael
A1 Dirks, Peter
A1 Pugh, Trevor
A1 Morrissy, Sorana
A1 St Croix, Bradley
A1 Mahoney, Douglas
A1 Lupien, Mathieu
A1 Gallo, Marco
T1 High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma
JF Genome Research 
JO Genome Research 
YR 2019 
FD June 27 
DO 10.1101/gr.246520.118 
SP gr.246520.118 
UL http://genome.cshlp.org/content/early/2019/06/27/gr.246520.118.abstract 
AB 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 datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.