Comprehensive Genomic Profiling of 282 Pediatric Low‐ and High‐Grade Gliomas Reveals Genomic Drivers, Tumor Mutational Burden, and Hypermutation Signatures. (4th December 2017)

• Record Type: Journal Article
• Authors: Johnson, Adrienne; Severson, Eric; Gay, Laurie; Vergilio, Jo‐Anne; Elvin, Julia; Suh, James; Daniel, Sugganth; Covert, Mandy; Frampton, Garrett M.; Hsu, Sigmund; Lesser, Glenn J.; Stogner‐Underwood, Kimberly; Mott, Ryan T.; Rush, Sarah Z.; Stanke, Jennifer J.; Dahiya, Sonika; Sun, James; Reddy, Prasanth; Chalmers, Zachary R.; Erlich, Rachel; Chudnovsky, Yakov; Fabrizio, David; Schrock, Alexa B.; Ali, Siraj; Miller, Vincent; Stephens, Philip J.; Ross, Jeffrey; Crawford, John R.; Ramkissoon, Shakti H.
• Is Part Of: Oncologist. Volume 22:Number 12(2017)
• Page Start: 1478
• Page End: 1490
• Publication Date: 2017-12-04
• Subjects: Pediatric neuro‐oncology -- Glioma -- Precision medicine -- Immunotherapy -- Clinical sequencing; Oncology -- Periodicals; Tumors -- Periodicals; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Oncology; Tumors; Neoplasms; Electronic journals; Periodicals; Periodicals; 616.994
• DOI: 10.1634/theoncologist.2017-0242
• Languages: English
• ISSNs: 1083-7159

Abstract

Abstract: Background: Pediatric brain tumors are the leading cause of death for children with cancer in the U.S. Incorporating next‐generation sequencing data for both pediatric low‐grade (pLGGs) and high‐grade gliomas (pHGGs) can inform diagnostic, prognostic, and therapeutic decision‐making. Materials and Methods: We performed comprehensive genomic profiling on 282 pediatric gliomas (157 pHGGs, 125 pLGGs), sequencing 315 cancer‐related genes and calculating the tumor mutational burden (TMB; mutations per megabase [Mb]). Results: In pLGGs, we detected genomic alterations (GA) in 95.2% (119/125) of tumors. BRAF was most frequently altered (48%; 60/125), and FGFR1 missense (17.6%; 22/125), NF1 loss of function (8.8%; 11/125), and TP53 (5.6%; 7/125) mutations were also detected. Rearrangements were identified in 35% of pLGGs, including KIAA1549‐BRAF, QKI‐RAF1, FGFR3‐TACC3, CEP85L‐ROS1, and GOPC‐ROS1 fusions. Among pHGGs, GA were identified in 96.8% (152/157). The genes most frequently mutated were TP53 (49%; 77/157), H3F3A (37.6%; 59/157), ATRX (24.2%; 38/157), NF1 (22.2%; 35/157), and PDGFRA (21.7%; 34/157). Interestingly, most H3F3A mutations (81.4%; 35/43) were the variant K28M. Midline tumor analysis revealed H3F3A mutations (40%; 40/100) consisted solely of the K28M variant. Pediatric high‐grade gliomas harbored oncogenic EML4‐ALK, DGKB‐ETV1, ATG7‐RAF1, and EWSR1‐PATZ1 fusions. Six percent (9/157) of pHGGs were hypermutated (TMB >20 mutations per Mb; range 43–581 mutations per Mb), harboring mutations deleterious for DNA repair in MSH6, MSH2, MLH1, PMS2, POLE, and POLD1 genes (78% of cases). Conclusion: Comprehensive genomic profiling of pediatric gliomas provides objective data that promote diagnostic accuracy and enhance clinical decision‐making. Additionally, TMB could be a biomarker to identify pediatric glioblastoma (GBM) patients who may benefit from immunotherapy. Abstract : This study highlights the value of comprehensive genomic profiling in the largest known cohort of pediatric glioma patients and explores the most common alterations across diagnosis and anatomic location. Tumor mutational burden and associated genetic factors that may predispose patients to developing a hypermutator phenotype are also discussed.