Whole-genome sequencing identifies genetic alterations in pediatric low-grade gliomas

The most common pediatric brain tumors are low-grade gliomas (LGGs). We used whole-genome sequencing to identify multiple new genetic alterations involving BRAF, RAF1, FGFR1, MYB, MYBL1 and genes with histone-related functions, including H3F3A and ATRX, in 39 LGGs and low-grade glioneuronal tumors (LGGNTs). Only a single non-silent somatic alteration was detected in 24 of 39 (62%) tumors. Intragenic duplications of the portion of FGFR1 encoding the tyrosine kinase domain (TKD) and rearrangements of MYB were recurrent and mutually exclusive in 53% of grade II diffuse LGGs. Transplantation of Trp53-null neonatal astrocytes expressing FGFR1 with the duplication involving the TKD into the brains of nude mice generated high-grade astrocytomas with short latency and 100% penetrance. FGFR1 with the duplication induced FGFR1 autophosphorylation and upregulation of the MAPK/ERK and PI3K pathways, which could be blocked by specific inhibitors. Focusing on the therapeutically challenging diffuse LGGs, our study of 151 tumors has discovered genetic alterations and potential therapeutic targets across the entire range of pediatric LGGs and LGGNTs.Jinghui Zhang, Gang Wu, Claudia P Miller, Ruth G Tatevossian, James D Dalton, Bo Tang, Wilda Orisme, Chandanamali Punchihewa, Matthew Parker, Ibrahim Qaddoumi, Fredrick A Boop, Charles Lu, Cyriac Kandoth, Li Ding, Ryan Lee, Robert Huether, Xiang Chen, Erin Hedlund, Panduka Nagahawatte, Michael Rusch, Kristy Boggs, Jinjun Cheng, Jared Becksfort, Jing Ma, Guangchun Song, Yongjin Li, Lei Wei, Jianmin Wang, Sheila Shurtleff, John Easton, David Zhao, Robert S Fulton, Lucinda L Fulton, David J Dooling, Bhavin Vadodaria, Heather L Mulder, Chunlao Tang, Kerri Ochoa, Charles G Mullighan, Amar Gajjar, Richard Kriwacki, Denise Sheer, Richard J Gilbertson, Elaine R Mardis, Richard K Wilson, James R Downing, Suzanne J Baker and David W Elliso

Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives: At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community. Methods: Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media. Results: Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minori

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology