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Spatiotemporal genomic architecture informs precision oncology in glioblastoma

Cited 186 time in Web of Science Cited 191 time in Scopus
Authors

Lee, Jin-Ku; Wang, Jiguang; Sa, Jason K.; Ladewig, Erik; Lee, Hae-Ock; Lee, In-Hee; Kang, Hyun Ju; Rosenbloom, Daniel S.; Camara, Pablo G.; Liu, Zhaoqi; van Nieuwenhuizen, Patrick; Jung, Sang Won; Choi, Seung Won; Kim, Junhyung; Chen, Andrew; Kim, Kyu-Tae; Shin, Sang; Seo, Yun Jee; Oh, Jin-Mi; Shin, Yong Jae; Park, Chul-Kee; Kong, Doo-Sik; Seol, Ho Jun; Blumberg, Andrew; Lee, Jung-Il; Iavarone, Antonio; Park, Woong-Yang; Rabadan, Raul; Nam, Do-Hyun

Issue Date
2017-04
Publisher
Nature Publishing Group
Citation
Nature Genetics, Vol.49 No.4, pp.594-599
Abstract
Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies1-5. However, this proposition is complicated by spatial and temporal heterogeneity6-14. Here we study genomic and expression profiles across 127 multisector or longitudinal specimens from 52 individuals with glioblastoma (GBM). Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, whereas geographically separated, multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated with genetic similarity, and multifocal tumors that are enriched with PIK3CA mutations have a heterogeneous drug-response pattern. We show that targeting truncal events is more efficacious than targeting private events in reducing the tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multisector biopsies can inform targeted therapeutic interventions for patients with GBM.
ISSN
1061-4036
URI
https://hdl.handle.net/10371/191549
DOI
https://doi.org/10.1038/ng.3806
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  • Department of Medicine
Research Area 3D drug screening, Cancer Organoid, Precision Oncologuy

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