Daniel Antunes Moreno1, Luciane Sussuchi da Silva1, Maicon Fernando Zanon2, Murilo Bonatelli2, Flávia Escremim de Paula2, Marcus de Medeiros Matsushita3, Gustavo Ramos Teixeira3,4, Iara Viana Vidigal Santana3, Fabiano Saggioro5, Luciano Neder5, João N Stavale6, Suzana Maria Fleury Malheiros6, Matheus Lima7, Glaucia Noeli Maroso Hajj7, Hernan Garcia-Rivello8, Silvia Christiansen8, Susana Nunes9, Maria João Gil da Costa9, Maria José Soares10, Jorge Pinheiro11, Carlos Almeida Junior12, Bruna Minniti Mançano1,12, Rui Manuel Reis13,14,15,16. 1. Molecular Oncology Research Center Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. 2. Molecular Diagnosis Laboratory Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. 3. Pathology Department Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. 4. Barretos School of Health Sciences Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. 5. Department of Pathology and Forensic Medicine, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil. 6. Federal University of São Paulo (UNIFESP), São Paulo, Brazil. 7. AC Camargo Hospital, São Paulo, Brazil. 8. Pathology Department, Italian Hospital of Buenos Aires, Buenos Aires, Argentina. 9. Pediatric Oncology Department, Hospital São João, Porto, Portugal. 10. Clinical Hematology Department, Hospital São João, Porto, Portugal. 11. Department of Pathology, Hospital São João, Porto, Portugal. 12. Pediatric Oncology Department, Pediatric Neurosurgery Department, Barretos Cancer Hospital, Barretos, Brazil. 13. Molecular Oncology Research Center Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. ruireis.hcb@gmail.com. 14. Molecular Diagnosis Laboratory Dr. Paulo Prata, Barretos Cancer Hospital, Barretos, Brazil. ruireis.hcb@gmail.com. 15. ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal. ruireis.hcb@gmail.com. 16. School of Medicine, Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal. ruireis.hcb@gmail.com.
Abstract
PURPOSE: Medulloblastoma is the most frequent pediatric malignant brain tumor, and is divided into four main subgroups: WNT, SHH, group 3, and group 4. MYCN amplification is an important medulloblastoma prognostic biomarker. We aimed to molecular classify and predict MYCN amplification in a single assay. METHODS: It was included 209 medulloblastomas from 205 patients (Brazil, Argentina, and Portugal), divided into training (n = 50) and validation (n = 159) sets. A nCounter assay was carried out using a custom panel for molecular classification, with additional genes, including MYCN. nSolver 4.0 software and the R environment were used for profiling and MYCN mRNA analysis. MYCN amplification by FISH was performed in 64 cases. RESULTS: The 205 medulloblastomas were classified in SHH (44.9%), WNT (15.6%), group 3 (18.1%) and group 4 (21.4%). In the training set, MYCN amplification was detected in three SHH medulloblastomas by FISH, which showed significantly higher MYCN mRNA counts than non-FISH amplified cases, and a cutoff for MYCN amplification was established ([Formula: see text] + 4σ = 11,124.3). Applying this threshold value in the validation set, we identified MYCN mRNA counts above the cutoff in three cases, which were FISH validated. CONCLUSION: We successfully stratified medulloblastoma molecular subgroups and predicted MYCN amplification using a single nCounter assay without the requirement of additional biological tissue, costs, or bench time.
PURPOSE: Medulloblastoma is the most frequent pediatric malignant brain tumor, and is divided into four main subgroups: WNT, SHH, group 3, and group 4. MYCN amplification is an important medulloblastoma prognostic biomarker. We aimed to molecular classify and predict MYCN amplification in a single assay. METHODS: It was included 209 medulloblastomas from 205 patients (Brazil, Argentina, and Portugal), divided into training (n = 50) and validation (n = 159) sets. A nCounter assay was carried out using a custom panel for molecular classification, with additional genes, including MYCN. nSolver 4.0 software and the R environment were used for profiling and MYCN mRNA analysis. MYCN amplification by FISH was performed in 64 cases. RESULTS: The 205 medulloblastomas were classified in SHH (44.9%), WNT (15.6%), group 3 (18.1%) and group 4 (21.4%). In the training set, MYCN amplification was detected in three SHH medulloblastomas by FISH, which showed significantly higher MYCN mRNA counts than non-FISH amplified cases, and a cutoff for MYCN amplification was established ([Formula: see text] + 4σ = 11,124.3). Applying this threshold value in the validation set, we identified MYCN mRNA counts above the cutoff in three cases, which were FISH validated. CONCLUSION: We successfully stratified medulloblastoma molecular subgroups and predicted MYCN amplification using a single nCounter assay without the requirement of additional biological tissue, costs, or bench time.
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