Back to Search Start Over

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

Authors :
Gustavo Alencastro Veiga Cruzeiro
Karina Bezerra Salomão
Carlos Alberto Oliveira de Biagi Jr
Martin Baumgartner
Dominik Sturm
Régia Caroline Peixoto Lira
Taciani de Almeida Magalhães
Mirella Baroni Milan
Vanessa da Silva Silveira
Fabiano Pinto Saggioro
Ricardo Santos de Oliveira
Paulo Henrique dos Santos Klinger
Ana Luiza Seidinger
José Andrés Yunes
Rosane Gomes de Paula Queiroz
Sueli Mieko Oba-Shinjo
Carlos Alberto Scrideli
Suely Marie Kazue Nagahashi
Luiz Gonzaga Tone
Elvis Terci Valera
Source :
Acta Neuropathologica Communications, Vol 7, Iss 1, Pp 1-10 (2019)
Publication Year :
2019
Publisher :
BMC, 2019.

Abstract

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.

Details

Language :
English
ISSN :
20515960
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Acta Neuropathologica Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.6cfc7ec6ce483ebbb41923ea82f3dc
Document Type :
article
Full Text :
https://doi.org/10.1186/s40478-019-0681-y