Spatiotemporal genomic architecture informs precision oncology in glioblastoma

Nature Genetics 49, 594 (2017). doi:10.1038/ng.3806 Authors: 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 Shin, Chul-Kee Park, Doo-Sik Kong, Ho Jun Seol, Andrew Blumberg, Jung-Il Lee, Antonio Iavarone, Woong-Yang Park, Raul Rabadan & Do-Hyun Nam 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 in...
Source: Nature Genetics - Category: Genetics & Stem Cells Authors: Tags: Letter Source Type: research