Abstract

Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM) primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient’s tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.

Highlights

  • The discovery of cancer specific somatic DNA mutations has led to the development of highly effective therapies targeting the corresponding altered protein via monoclonal antibodies or specific inhibitors

  • We first assessed the quality of the resulting calls by analyzing germline single nucleotide variants (SNV) comparing the results of sequencing and microarray genotyping at 62,550 positions investigated by the two methods

  • We estimated that,90% of the germline SNVs identified are present in dbSNP(132) (Table S3), which is slightly lower than expected (95%) for Caucasian patients [32]

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Summary

Introduction

The discovery of cancer specific somatic DNA mutations has led to the development of highly effective therapies targeting the corresponding altered protein via monoclonal antibodies or specific inhibitors. These therapies have enhanced activity with a reduced toxicity for the patient in comparison to cytotoxic agents. The specific alterations affect different genes in these pathways through various somatic events such as point mutations, copy number aberrations or transcriptional deregulation. These molecular profiles led to a classification of GBM tumors which have already proven useful in designing more rationalized targeted therapies. Current clinical trials in GBM targeting EGFR, VEGF, PDGFRA are all leveraging recent molecular genetic information of GBM [11]

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