Cytogenetic prognostication within medulloblastoma subgroups - Shih, David J H; Northcott, Paul A; Remke, Marc; Korshunov, Andrey; Ramaswamy, Vijay; Kool, Marcel; Luu, Betty; Yao, Yuan; Wang, Xin; Dubuc, Adrian M; Garzia, Livia; Peacock, John; et al. (Journal of clinical oncology, 2014)
PURPOSE: Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. PATIENTS AND METHODS: Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. RESULTS: Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. CONCLUSION: Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.
Keywords: reprodukovatelnost výsledků; Gene Expression Regulation, Neoplastic; mužské pohlaví; Male; Nuclear Proteins; prediktivní hodnota testů; proteiny Wnt; Reproducibility of Results; Female; Humans; Prognosis; kojenec; jaderné proteiny; hybridizace in situ fluorescenční; lidé; proporcionální rizikové modely; Risk Assessment; stanovení celkové genové exprese; Biomarkers, Tumor; In Situ Hybridization, Fluorescence; ženské pohlaví; nádorové biomarkery; Wnt Proteins; Infant; Cytogenetics; Kruppel-Like Transcription Factors; meduloblastom; mladiství; Tissue Array Analysis; prognóza; rizikové faktory; čipová analýza tkání; Young Adult; cytogenetika; Child; dítě; Adolescent; Predictive Value of Tests; protoonkogenní proteiny c-myc; mladý dospělý; Chromosomes, Human, Pair 14; Risk Factors; Chromosomes, Human, Pair 11; Child, Preschool; Proportional Hazards Models; Proto-Oncogene Proteins c-myc; Gene Expression Profiling; Hedgehog Proteins; lidské chromozomy, pár 14; lidské chromozomy, pár 11; transkripční faktory Krüppel-like; Medulloblastoma; proteiny hedgehog; předškolní dítě; regulace genové exprese u nádorů; hodnocení rizik