Clinical Prognostic Implications of Wnt Hub Genes Expression in Medulloblastoma.

Medulloblastoma is the most common type of pediatric malignant primary brain tumor, and about one-third of patients die due to disease recurrence and most survivors suffer from long-term side effects. MB is clinically, genetically, and epigenetically heterogeneous and subdivided into at least four molecular subgroups: WNT, SHH, Group 3, and Group 4. We evaluated common differentially expressed genes between a Brazilian RNA-seq GSE181293 dataset and microarray GSE85217 dataset cohort of pediatric MB samples using bioinformatics methodology in order to identify hub genes of the molecular subgroups based on PPI network construction, survival and functional analysis. The main finding was the identification of five hub genes from the WNT subgroup that are tumor suppressors, and whose lower expression is related to a worse prognosis for MB patients. Furthermore, the common genes correlated with the five tumor suppressors participate in important pathways and processes for tumor initiation and progression, as well as development and differentiation, and some of them control cell stemness and pluripotency. These genes have not yet been studied within the context of MB, representing new important elements for investigation in the search for therapeutic targets, prognostic markers or for understanding of MB biology.

Single nCounter assay for prediction of MYCN amplification and molecular classification of medulloblastomas: a multicentric study.

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.

A coordinated approach for the assessment of molecular subgroups in pediatric ependymomas using low-cost methods.

Although ependymoma (EPN) molecular subgroups have been well established by integrated high-throughput platforms, low- and middle-income countries still need low-cost techniques to promptly classify these molecular subtypes. Here, we applied low-cost methods to classify EPNs from a Brazilian cohort with 60 pediatric EPN patients. Fusion transcripts (C11orf95-RELA, YAP1-MAMLD1, and YAP1-FAM118B) were investigated in supratentorial EPN (ST-EPNs) samples through RT-PCR/Sanger sequencing and immunohistochemistry (IHC) for p65/L1CAM. qRT-PCR and IHC were used to evaluate expression profiling of CXorf67, LAMA2, NELL2, and H3K27me3 in posterior fossa EPN (PF-EPNs) samples. In silico analysis was performed using public microarray data to validate the molecular assignment PF-EPNs with LAMA2/NELL2 markers. RELA cases and YAP1-MAMLD1 fusions were identified in nine and four ST-EPNs, respectively. An additional RELA case was identified by IHC. Of note, LAMA2 and NELL2 gene expression and immunoprofiling were less accurate for classifying PF-EPNs, which were confirmed by in silico analysis. Yet, H3K27me3 staining was sufficient to classify PF-EPN subgroups. Our results emphasize the feasibility of a simplified strategy to molecularly classify EPNs in the vast majority of cases (49/60; 81.7%). A coordinated combination of simple methods can be effective to screen pediatric EPN with the available laboratory resources at most low-/mid-income countries, giving support for clinical practice in pediatric EPN. KEY MESSAGES: Low- and middle-income countries need effective low-cost approaches to promptly distinguish between EPN molecular subgroups. RT-PCR plus Sanger sequencing is able to recognize the most common types of RELA and YAP1 fusion transcripts in ST-EPNs. Genetic and protein expressions of LAMA2 and NELL2 are of limited value to accurately stratify PF-EPNs. Immunohistochemical staining for H3K27me3 may be used as a robust method to accurately diagnose PF-EPNs subgroups. A coordinated flow diagram based on these validated low-cost methods is proposed to help clinical-decision making and to reduce costs with NGS assessment outside research protocols.

Lack of KBTBD4 Mutations in Molecularly Classified Brazilian Medulloblastomas.

Medulloblastoma is the most frequent malignant brain tumor in children, representing 20% of all childhood brain tumors. Currently, medulloblastomas are molecularly classified in 4 subgroups that are associated with distinctive clinicopathological features. KBTBD4 mutations were recently described in a subset of MBGRP3 and MBGRP4 medulloblastomas subgroups. However, no other studies reported KBTBD4 mutations in medulloblastomas. Thus, our aim was to investigate KBTBD4 mutations in a Brazilian series of medulloblastoma. We evaluated 128 medulloblastoma patients molecularly classified from 4 Brazilian reference centers. DNA from formalin-fixed, paraffin-embedded samples was screened for KBTBD4 hotspot mutations by Sanger sequencing. Most of the patients were male, average age was 16.5 years old and average overall survival was 55.9 months. The predominant histological subtype was the classic subtype, followed by nodular/desmoplastic, and the predominant medulloblastoma molecular subtype was the MBSHH subgroup (46%), followed by MBGRP3 and MBGRP4 (19%/each), and MBWNT (16%). Among the 128 samples, 111 were successfully sequenced. No KBTBD4 mutations were identified in 111 samples. Our findings suggest that KBTBD4 mutations are uncommon in Brazilian MBGRP3 and MBGRP4 medulloblastomas subgroups. Further studies in a larger series of MBGRP3 and MBGRP4 medulloblastomas are warranted to better assess role of KBTBD4 mutations.

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

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.

Reproducibility of the NanoString 22-gene molecular subgroup assay for improved prognostic prediction of medulloblastoma.

Medulloblastoma is the most frequent malignant brain tumor in children. Four medulloblastoma molecular subgroups, MBSHH , MBWNT , MBGRP3 and MBGRP4 , have been identified by integrated high-throughput platforms. Recently, a 22-gene panel NanoString-based assay was developed for medulloblastoma molecular subgrouping, but the robustness of this assay has not been widely evaluated. Mutations in the gene for human telomerase reverse transcriptase (hTERT) have been found in medulloblastomas and are associated with distinct molecular subtypes. This study aimed to implement the 22-gene panel in a Brazilian context, and to associate the molecular profile with patients' clinical-pathological features. Formalin-fixed, paraffin-embedded (FFPE) medulloblastoma samples (n = 104) from three Brazilian centers were evaluated. Expression profiling of the 22-gene panel was performed by NanoString and a Canadian series (n = 240) was applied for training phase. hTERT mutations were analyzed by PCR followed by direct Sanger sequencing and the molecular profile was associated with patients' clinicopathological features. Overall, 65% of the patients were male, average age at diagnosis was 18 years and 7% of the patients presented metastasis at diagnosis. The molecular classification was attained in 100% of the cases, with the following frequencies: MBSHH (n = 51), MBWNT (n = 19), MBGRP4 (n = 19) and MBGRP3 (n = 15). The MBSHH and MBGRP3 subgroups were associated with older and younger patients, respectively. The MBGRP4 subgroup exhibited the lowest 5-year cancer-specific overall survival (OS), yet in the multivariate analysis, only metastasis at diagnosis and surgical resection were associated with OS. hTERT mutations were detected in 29% of the cases and were associated with older patients, increased hTERT expression and MBSHH subgroup. The 22-gene panel provides a reproducible assay for molecular subgrouping of medulloblastoma FFPE samples in a routine setting and is well-suited for future clinical trials.