Jin-Ku Lee1,2,13, Jiguang Wang3.5,13, Jason K Sa1,2,6,13, Erik Ladewig3,4,13, Hae-Ock Lee7, In-Hee Lee1,2, Hyun Ju Kang1,2, Daniel S Rosenbloom3,4, Pablo G Camara3,4, Zhaoqi Liu3,4, Patrick van Nieuwenhuizen3,4, Sang Won Jung1,2,6, Seung Won Choi1,2,6, Junhyung Kim1,2, Andrew Chen3,4, Kyu-Tae Kim7, Sang Shin1,2,6, Yun Jee Seo1,2, Jin-Mi Oh1,2, Yong Jae Shin1,2,7, Chul-Kee Park8, Doo-Sik Kong2, Ho Jun Seol2, Andrew Blumberg9, Jung-Il Lee2, Antonio Iavarone10.12, Woong-Yang Park6,7,*, Raul Rabadan3,4,* & Do-Hyun Nam1,2,6,*
1Institute for Refractory Cancer Research, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 2Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 3Department of Systems Biology, Columbia University, New York, New York, USA. 4Department of Biomedical Informatics, Columbia University, New York, New York, USA. 5Divisions of Life Science and Biomedical Engineering, Hong Kong University of Science and Technology, Hong Kong. 6Department of Health Science and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul, Republic of Korea. 7Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 8Department of Neurosurgery, College of Medicine, Seoul National University and Seoul National University Hospital, Seoul, Republic of Korea. 9Department of Mathematics, University of Texas, Austin, Texas, USA. 10Institute for Cancer Genetics, Columbia University, New York, New York, USA. 11Department of Neurology, Columbia University, New York, New York, USA. 12Department of Pathology, Columbia University, New York, New York, USA.13These authors contributed equally to this work.
*Correspondence to : Raul Rabadan or Woong-Yang Park or Do-Hyun Nam
Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies1, 2, 3, 4, 5. However, this proposition is complicated by spatial and temporal heterogeneity6, 7, 8, 9, 10, 11, 12, 13, 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.