A simplified approach using Taqman low-density array for medulloblastoma subgrouping

Acta Neuropathologica Communications

Ana Luiza Seidinger¹  José Andrés Yunes¹  Vanessa da Silva Silveira²  Taciani de Almeida Magalhães²  Carlos Alberto Oliveira de Biagi Jr²  Mirella Baroni Milan²  Suely Marie Kazue Nagahashi³  Sueli Mieko Oba-Shinjo³  Martin Baumgartner⁴  Fabiano Pinto Saggioro⁵  Rosane Gomes de Paula Queiroz⁶  Paulo Henrique dos Santos Klinger⁶  Elvis Terci Valera⁶  Gustavo Alencastro Veiga Cruzeiro⁶  Carlos Alberto Scrideli⁶  Régia Caroline Peixoto Lira⁶  Karina Bezerra Salomão⁶  Luiz Gonzaga Tone⁶  Ricardo Santos de Oliveira⁷  Dominik Sturm⁸ 

[1] Boldrini Centre of Children, University of Campinas-UNICAMP;Department of Genetics, Ribeirão Preto Medical School, University of São Paulo;Department of Neurology, Faculty of Medicine, University of São Paulo;Department of Oncology, Children’s Research Center, Neuro-Oncology group, University Children’s Hospital Zürich;Department of Pathology, University of São Paulo;Department of Pediatrics Ribeirão Preto Medical School, Hospital das Clínicas, University of São Paulo;Division of Pediatric Neurosurgery, Department of Surgery and Anatomy, Ribeirão Preto Medical School, Hospital das Clínicas, University of São Paulo;Pediatric Glioma Research Group, Hopp Children’s Cancer Center at the NCT Heidelberg (KiTZ) and German Cancer Research Center (DKFZ);

关键词: Medulloblastoma;    Molecular subgroups;    Brazilian cohort;    Real-time PCR;   

DOI  :  10.1186/s40478-019-0681-y

来源: DOAJ

【 摘 要 】

Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making.

【 授权许可】

Unknown