Genome-Wide Genetic And Epigenetic Assessment Of Group 4 Medulloblastoma For Improved, Biomarker Driven, Prognostication And Riskstratification

NEURO-ONCOLOGY(2021)

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Abstract Introduction Medulloblastoma (MB) is the most common malignant brain tumour in children. The most frequent molecular subgroup, Group 4 (MBGrp4) accounts for ~35/40% of cases, however it has the least understood underlying biology. Clinical outcomes are heterogeneous in MBGrp4 and are not accounted for by established clinico-pathological risk factors. There is now a requirement for a comprehensive study of MBGrp4, considering established clinico-pathological features and novel molecular biomarkers to enhance risk-stratification and identify novel therapeutic targets. Methods A clinically-annotated, retrospective MBGrp4 discovery cohort (n = 420) was generated from UK CCLG institutions, collaborating European centres and SIOP-UKCCSG-PNET3 and HIT-SIOP-PNET4 clinical trials. Contemporary, multi-omics profiling was performed. Focal and arm level copy number aberrations (CNAs) were determined from molecular inversion probe (MIP) or DNA methylation array which additionally provided next generation non-WNT/non-SHH (Grp3/Grp4) subtype classifications. Targeted next-generation DNA sequencing was performed to overlay the mutational landscape. Survival modelling was carried out with patients >3 years old who received craniospinal irradiation. Results MBGrp4 subtypes were assigned to 88% of tumours with available data. Subtype VIII was strongly associated with i17q (p<0.0001). The favourable-risk cytogenetic signature (2 or 3 of; chromosome 7 gain, chromosome 8 loss and/or chromosome 11 loss) associated with both subtypes VI and VII (p<0.0001). MYCN amplifications were strongly associated with subtype V (p<0.0001) in addition to 16q loss (p<0.0001). The high-risk CNA group was enriched for mutations in genes involved in chromatin remodelling (p<0.0001). Risk factors were identified from multivariate survival modelling. Subtype and CNA groups contributed to improved risk-stratification models that outperformed current clinical schemes. Conclusion Comprehensive genetic and epigenetic profiling in this large retrospective cohort has improved our understanding of the molecular and clinical heterogeneity within MBGrp4. Incorporation of molecular biomarkers improved risk-stratification for MBGrp4.
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