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

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.

Keywords: Brazilian cohort; Medulloblastoma; Molecular subgroups; Real-time PCR.

Fig. 1

a Clinical characteristics of MB patients (n = 90). Classification Molecular classification: WNT subgroup, SHH subgroup, Group 3 and Group 4 of patients. Gender (female and male). Age at diagnosis (below or above 3 years). Metastasis presence of metastasis at diagnosis (yes, no); Relapse presence of postoperative disease relapse (yes, no). Tumor resection (gross-total resection GTR; non-gross total resection non-GTR). Treatment treatment protocol (craniospinal radiotherapy plus carboplatin, ifosfamide, vincristine, etoposide; craniospinal radiotherapy plus CCNU (1-(2-chloroethyl)-3-cyclohexyl-1-nitrosourea), cisplatin, vincristine; Baby POG – Pediatric Oncology Group). Death if patient died (yes, no). Institution institute where patients received treatment, Monosomy of chromosome 6 if patient bears this feature (yes, no), GLI2 Amplification if patients bears feature (yes, no), Isochromosome (17q) if patient bears feature (yes, no), Methylation Array 450 K Molecular assignment by methylation array of WNT (6), SHH (2), Group 3 (2) and Group 4 (1) samples. b Hierarchical unsupervised clustering of 92 primary MB into four molecular subgroups: SHH (green), WNT (purple), Group 3 (red) and Group 4 (blue). Pearson distance as Metric and average linkage as algorithm clustering. L1, L2, L3, L4 and L5 are represented as UW473, DAOY, UW402, UW228 and ONS-76 MB cell lines and “na” as samples tumors with unavailable data. c Copy number profile of sample 4 WNT subgroup (monosomy 6) (d) Copy number profile of sample 26 SHH Subgroup (Amplification of GLI2) (e) Copy number profile of sample 55 Group 3 (Isochromosome 17q)

Fig. 2

a Two-dimensional representation of pairwise sample correlations of twenty TaqMan expression assay probes (Additional file: Table S1) in 92 MB Brazilian samples by t-Distributed Stochastic Neighbor Embedding. b Two-dimensional representation of pairwise sample correlation of the same gene set represented in (a) using Microarray probes in 763 MB samples from GSE85217 by t-Distributed Stochastic Neighbor Embedding

Fig. 3

Hierarchical unsupervised clustering of previously classified 763 primary MB in GSE85217 study: SHH (blue), WNT (orange), Group 3 (red) and Group 4 (purple) Pearson distance as Metric was utilized in both heatmaps. a Clustering using the Ward.D2 algorithm. b Clustering using the Average linkage algorithm

Fig. 4

Hierarchical unsupervised clustering using HHIP, EYA1, SFRP1, EMX2, DKK2, WIFI1 a 92 MB samples from Brazilian cohort and b 763 MB samples from GSE85217. SHH (blue), WNT (orange), Group 3 (red) and Group 4 (purple)

Fig. 5

a Two-dimensional representation of pairwise sample correlations of 6 TaqMan expression assay probes (SFRP1, HHIP, EYA1, WIFI1, EMX2 and DKK2) in 92 MB Brazilian samples by t-Distributed Stochastic Neighbor Embedding. b Two- dimensional representation of pairwise sample correlation of the same gene set represented in (a), although using Microarray probes of 763 MB samples from GSE85217 by t-Distributed Stochastic Neighbor Embedding