- Meeting abstract
- Open Access
Integrated genomics elucidates relative spatial homogeneity of embryonal brain tumors
© Remke et al. 2015
- Published: 1 July 2015
- Renal Cell Carcinoma
- Copy Number Alteration
- Intratumor Heterogeneity
- Copy Number Analysis
Genome-wide profiling and next-generation based sequencing studies have dramatically improved our understanding of embryonal brain tumor (EBT) biology in the recent years. However, the vast majority of these studies are based on the assumption that single biopsies are representative for the entire primary tumor. Intratumor heterogeneity constitutes a common phenomenon previously described in renal cell carcinoma (RCC) and high-grade glioma (HGG). Highly disparate molecular profiles of spatially separated tumor areas within the same tumor may preclude development of molecularly targeted therapies based on single tumor biopsies.
To address this issue, we conducted multiregion whole exome sequencing, high-resolution DNA copy number analysis (Cytoscan HD), and transcriptional profiling on 39 distinct pediatric and adult tumors with a median of six spatially distant biopsies per tumor (range 4-11). Histological entities included AT/RT (n = 2), HGG (n = 17), medulloblastoma (n = 9), medulloepithelioma (n = 1), and RCC (n = 10). We assessed the degree of intratumor heterogeneity and subgroup affiliation using integrated genomics approaches.
Embryonal brain tumors demonstrated highly spatially homogenous transcriptomes. In contrast to adult glioblastoma, we showed that subgroup affiliation was stable in multiregion biopsies from the same medulloblastoma patient. Furthermore, EBT displayed highly similar focal and broad DNA copy number alterations compared to HGG and RCC. Multiregion sequencing further reinforced the relatively higher degree of intratumor homogeneity in EBT. Compared to HGG or RCC, somatic mutations in EBT were much more likely to be ubiquitous throughout the tumor.
The relative spatial homogeneity of EBT suggests that limited biopsies are representative of the tumor genomics landscape, which has important implications for biological classification and development of targeted therapies for these tumors.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.