Spatiotemporal genomic architecture informs precision oncology in glioblastoma

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

Research output: Contribution to journalArticlepeer-review

119 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)594-599
Number of pages6
JournalNature Genetics
Volume49
Issue number4
DOIs
Publication statusPublished - 2017 Mar 30
Externally publishedYes

ASJC Scopus subject areas

  • Genetics

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