Comprehensive genomic analysis of young adult glioblastomas reveals four subclasses with distinct driver events Ovarian Cancer and Us OVARIAN CANCER and US Ovarian Cancer and Us

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Tuesday, November 08, 2016

Comprehensive genomic analysis of young adult glioblastomas reveals four subclasses with distinct driver events



abstract
COMPREHENSIVE GENOMIC ANALYSIS OF YOUNG ADULT GLIOBLASTOMAS REVEALS FOUR SUBCLASSES WITH DISTINCT DRIVER EVENTS 

 Glioblastoma (GBM) is the most common primary malignant brain tumor in adults; however, recent studies have shown that GBM is comprised of biologically and genetically distinct diseases which share a common morphologic appearance. In this study, we demonstrate that young adult GBMs (yaGBM, 18-40 years) comprise genomically distinct subclasses with unique collections of driver events. DNA was extracted from 271 yaGBM (female 110, male 161, median age 34 years) samples and comprehensive genomic profiling was performed using hybridization-capture, adaptor ligation-based libraries for 315 cancer-related genes including selected introns from 31 genes frequently rearranged in cancer. The most commonly altered genes were TP53 (65.3%), IDH1 (40.6%), ATRX (40.6%), CDKN2A/B (39.1%/33.6%), PTEN (24.0%), TERT (20.3%), NF1 (18.1%), PIK3CA (17.3%), CDK4 (15.5%), EGFR (14.0%), H3F3A (12.5%), PDGFRA (11.4%), and RB1 (11.4%). Genomic rearrangements included FGFR1-TACC1 (n=2), FGFR2-GKAP1 (n=1), FGFR3-TACC3 (n=2), and BRAF-KIAA1549 (n=1). Unsupervised latent class analysis revealed four distinct classes of yaGBM largely defined as (1) IDH1/TP53 mutant (2) IDH1/TP53 mutant with PDGFRA amplification, (3) H3F3A/TP53 mutant, and (4) PI3K activation (PTEN/EGFR mutant, TP53 wild type). The median tumor mutation burden (TMB) was 3.6 mutations/Mb (range <1 to 666 mutations/Mb). Samples with TMBs ≥ 10 mutations/Mb (n=39, 10.7%) were enriched for genomic alterations involving DNA repair/mismatch repair genes including MSH6 (23.9%), MLH1 (21.7%), ATM (19.6%), MLL2 (15.2%), and MSH2 (13.0%). Taken together these findings demonstrate that yaGBMs can be subdivided into four genetically distinct subclasses each with unique driver events. Furthermore, these findings highlight clinically actionable alterations for which targeted agents are available including IDH1, PIK3CA, PDGFRA, or EGFR inhibitors while a subpopulation of patients with hypermutated GBMs may benefit from immunotherapy agents.

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