GRCh38 · COSMIC v98


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Spatiotemporal genomic architecture informs precision oncology in glioblastoma.
Paper ID
Lee JK, Wang J, Sa JK, Ladewig E, Lee HO, Lee IH, Kang HJ, Rosenbloom DS, Camara PG, Liu Z, van Nieuwenhuizen P, Jung SW, Choi SW, Kim J, Chen A, Kim KT, Shin S, Seo YJ, Oh JM, Shin YJ, Park CK, Kong DS, Seol HJ, Blumberg A, Lee JI, Iavarone A, Park WY, Rabadan R and Nam DH
Institute for Refractory Cancer Research, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Nature genetics, 2017
ISSN: 1546-1718
PMID: 28263318 (view at PubMed or Europe PMC)
Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. However, this proposition is complicated by spatial and temporal heterogeneity. 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.
Paper Status