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, 3 (8), e3088

Integrated Genomics Identifies Five Medulloblastoma Subtypes With Distinct Genetic Profiles, Pathway Signatures and Clinicopathological Features


Integrated Genomics Identifies Five Medulloblastoma Subtypes With Distinct Genetic Profiles, Pathway Signatures and Clinicopathological Features

Marcel Kool et al. PLoS One.


Background: Medulloblastoma is the most common malignant brain tumor in children. Despite recent improvements in cure rates, prediction of disease outcome remains a major challenge and survivors suffer from serious therapy-related side-effects. Recent data showed that patients with WNT-activated tumors have a favorable prognosis, suggesting that these patients could be treated less intensively, thereby reducing the side-effects. This illustrates the potential benefits of a robust classification of medulloblastoma patients and a detailed knowledge of associated biological mechanisms.

Methods and findings: To get a better insight into the molecular biology of medulloblastoma we established mRNA expression profiles of 62 medulloblastomas and analyzed 52 of them also by comparative genomic hybridization (CGH) arrays. Five molecular subtypes were identified, characterized by WNT signaling (A; 9 cases), SHH signaling (B; 15 cases), expression of neuronal differentiation genes (C and D; 16 and 11 cases, respectively) or photoreceptor genes (D and E; both 11 cases). Mutations in beta-catenin were identified in all 9 type A tumors, but not in any other tumor. PTCH1 mutations were exclusively identified in type B tumors. CGH analysis identified several fully or partly subtype-specific chromosomal aberrations. Monosomy of chromosome 6 occurred only in type A tumors, loss of 9q mostly occurred in type B tumors, whereas chromosome 17 aberrations, most common in medulloblastoma, were strongly associated with type C or D tumors. Loss of the inactivated X-chromosome was highly specific for female cases of type C, D and E tumors. Gene expression levels faithfully reflected the chromosomal copy number changes. Clinicopathological features significantly different between the 5 subtypes included metastatic disease and age at diagnosis and histology. Metastatic disease at diagnosis was significantly associated with subtypes C and D and most strongly with subtype E. Patients below 3 yrs of age had type B, D, or E tumors. Type B included most desmoplastic cases. We validated and confirmed the molecular subtypes and their associated clinicopathological features with expression data from a second independent series of 46 medulloblastomas.

Conclusions: The new medulloblastoma classification presented in this study will greatly enhance the understanding of this heterogeneous disease. It will enable a better selection and evaluation of patients in clinical trials, and it will support the development of new molecular targeted therapies. Ultimately, our results may lead to more individualized therapies with improved cure rates and a better quality of life.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. Identification of molecular subtypes in medulloblastoma.
A. Unsupervised two-way hierarchical cluster analysis of 62 medulloblastoma samples and expression data of 1300 most differentially expressed genes identified 5 distinct clusters indicated as A, B, C, D, and E. Clinical annotations are at the bottom. Histology: grey = desmoplastic, orange = large cell/anaplastic, white = classic; sex: pink = female, white = male; Metastatic disease at diagnosis indicated with M stage: yellow = M1, orange = ≥M2, white = M0; Age: purple = age ≤3 yrs, white = age >3 yrs; β-catenin mutations: brown = mutations, white = wild type; PTCH1 mutations: blue = mutations, white = wild type. A cross means not analyzed. B. Schematic pentagram showing the correlations between the 5 molecular subtypes of medulloblastoma. Numbers at the outside near each subtype indicate number of genes that are significantly differently expressed between that subtype and all other subtypes (P<0.001). Numbers at connecting lines indicate number of genes that are significantly differently expressed between medulloblastoma subtypes.
Figure 2
Figure 2. Schematic overview of the 5 molecular subtypes of medulloblastoma and their molecular, genetic, and clinical characteristics described in this paper.
Figure 3
Figure 3. Examples of marker genes.
For each medulloblastoma subtype A, B, C, D, and E, the expression data (vertical axes) are shown in each tumor (indicated with colored circles) for 2 markers that are specifically expressed or upregulated in that subtype, and 2 markers that are not expressed or only at very low levels in that subtype. A. Type A markers; B. Type B markers; C. In 2C markers are shown that are expressed either in subtype A and B together or in subtype C, D, and E together; D. Type C and/or CD markers; E. Type DE markers; F. Type E markers.
Figure 4
Figure 4. Cluster analysis of genetic aberrations in the different molecular subtypes identified with array CGH.
Array probes were grouped together according to their position in distinct cytobands. Cytobands were then scored in each tumor as gained (+1, red), lost (−1, green), or unchanged (0, white), based on the array CGH data for all probes in a particular cytoband region. Subsequently, these cytoband data for gain, loss or no change were clustered using an unsupervised one-way hierarchical clustering. This was done for each molecular subtype separately.
Figure 5
Figure 5. CGH analysis of sex chromosomes.
A. One copy of chromosome X is lost in most female cases of clusters C, D, and E. The plot shows array CGH data for the X and Y chromosome in males and females of the different subtypes. The plotted data represent the average logratio for probes on chromosome X vs chromosome Y after normalization on the median of autosomes (see methods). The error-bars represent the standard error of the mean. Open circles represent male patients, closed circles are for female patients. Colors correspond to the colors for the different subtypes as indicated in Figure 1. B. XIST expression (vertical axis) is shown for 21 female cases (indicated with colored circles) in the MB62 series. 17 of them were analyzed by CGH arrays (Figure 5A). XIST expression is lost or strongly reduced in most type C, D, or E tumors, but not in type A or B tumors.
Figure 6
Figure 6. Genetic aberrations affect gene expression.
A. Expression data suggest loss of chromosome 6 in all 9 tumors of cluster A. A one-way unsupervised hierarchical clustering of 62 medulloblastoma samples is shown for all expressed genes on chromosome 6. Colors on top correspond with the colors of the different subtypes as shown in Figure 1. Genes on the vertical axis are not clustered and are placed next to each other according to their position on the chromosome. B. Example of how DNA alterations affect gene expression. Chromosome 9 array CGH data (green) and expression data (Z-scores, red), both plotted on the Y-axis, are shown for two samples. MB0313 has no DNA alterations for chromosome 9, and MB0270 has lost the telomeric part of 9q. C. Overall analysis shows how genetic aberrations affect gene expression. Cytoband regions for all tumors analyzed by array CGH were marked as ‘−1’ for loss, ‘0’ for no change, and ‘+1’ for gain. Then the average expression (average Z-scores) of all expressed genes in these regions was calculated for each tumor and plotted on the Y-axis for each category. Results show that genes in regions with loss are on average expressed at lower levels (green box) and genes in regions with gain at higher levels (red box), compared to regions with no changes (blue box). Numbers at the X-axis between brackets represent the number of probe sets that were taken into account per category.
Figure 7
Figure 7. Unsupervised two-way hierarchical cluster analysis of 46 medulloblastoma samples and expression data of 1500 most differentially expressed genes from Thompson data series .
The clustering identified 4 distinct clusters indicated as A, B, C, and DE. Clusters D and E could not be separated in this series. Clinical annotations are at the bottom. Thompson subtypes as indicated in their paper: yellow = Thompson subtype A, light pink = Thompson subtype B, blue = Thompson subtype C, green = Thompson subtype D, dark pink = Thompson subtype E; Histology: grey = desmoplastic, orange = large cell/anaplastic, white = classic; sex: pink = female, white = male; M stage: yellow = M1, orange = ≥M2, white = M0; Age: purple = age ≤3 yrs, white = age >3 yrs; β-catenin mutations: brown = mutations, white = wild type; PTCH1/SUFU mutations: light blue = PTCH1 mutations, dark blue = SUFU mutation, white = wild type; 17p deletions: dark red = yes, white = no. A cross means not analyzed.

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    1. Giangaspero F, Eberhart CG, Haapasalo H, Pietsch T, Wiestler OD, et al. Medulloblastoma. In: Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, editors. WHO classification of tumours of the central nervous system. Lyon: IARC Press; 2007. pp. 132–140.
    1. Bayani J, Zielenska M, Marrano P, Kwan Ng Y, Taylor MD, et al. Molecular cytogenetic analysis of medulloblastomas and supratentorial primitive neuroectodermal tumors by using conventional banding, comparative genomic hybridization, and spectral karyotyping. J Neurosurg. 2000;93:437–448. - PubMed
    1. Michiels EM, Weiss MM, Hoovers JM, Baak JP, Voute PA, et al. Genetic alterations in childhood medulloblastoma analyzed by comparative genomic hybridization. J Pediatr Hematol Oncol. 2002;24:205–210. - PubMed
    1. Hui AB, Takano H, Lo KW, Kuo WL, Lam CN, et al. Identification of a novel homozygous deletion region at 6q23.1 in medulloblastomas using high-resolution array comparative genomic hybridization analysis. Clin Cancer Res. 2005;11:4707–4716. - PubMed
    1. Pan E, Pellarin M, Holmes E, Smirnov I, Misra A, et al. Isochromosome 17q is a negative prognostic factor in poor-risk childhood medulloblastoma patients. Clin Cancer Res. 2005;11:4733–4740. - PubMed

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