SUMMARY Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated “CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)”, “CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)”, “CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)”, and “CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)”, will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

Medulloblastoma is the most frequent malignant paediatric brain tumour. The activation of the Wnt/beta-catenin pathway occurs in 10-15% of medulloblastomas and has been recently described as a marker for favourable patient outcome. We report a series of 72 paediatric medulloblastomas evaluated for beta-catenin protein expression, CTNNB1 mutations, and comparative genomic hybridization. Gene expression profiles were also available in a subset of 40 cases. Immunostaining of beta-catenin showed extensive nuclear staining (>50% of the tumour cells) in six cases and focal nuclear staining (<10% of cells) in three cases. The other cases either exhibited a signal strictly limited to the cytoplasm (58 cases) or were negative (five cases). CTNNB1 mutations were detected in all beta-catenin extensively nucleopositive cases. The expression profiles of these cases documented strong activation of the Wnt/beta-catenin pathway. Remarkably, five out of these six tumours showed a complete loss of chromosome 6. In contrast, cases with focal nuclear beta-catenin staining, as well as tumours with negative or cytoplasmic staining, never demonstrated CTNNB1 mutation, Wnt/beta-catenin pathway activation or chromosome 6 loss. Patients with extensive nuclear staining were significantly older at diagnosis and were in continuous complete remission after a mean follow-up of 75.7 months (range 27.5-121.2 months) from diagnosis. All three patients with focal nuclear staining of beta-catenin died within 36 months from diagnosis. Altogether, these data confirm and extend previous observations that CTNNB1-mutated tumours represent a distinct molecular subgroup of medulloblastomas with favourable outcome, indicating that therapy de-escalation should be considered. International consensus on the definition criteria of this distinct medulloblastoma subgroup should be achieved.

No abstract

Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to 3 or more sets of variables. RGCCA is a component-based approach which aims to study the relationships between several sets of variables. The quality and interpretability of the RGCCA components are likely to be affected by the usefulness and relevance of the variables in each block. Therefore, it is an important issue to identify within each block which subsets of significant variables are active in the relationships between blocks. In this paper, RGCCA is extended to address the issue of variable selection. Specifically, sparse generalized canonical correlation analysis (SGCCA) is proposed to combine RGCCA with an [Formula: see text]-penalty in a unified framework. Within this framework, blocks are not necessarily fully connected, which makes SGCCA a flexible method for analyzing a wide variety of practical problems. Finally, the versatility and usefulness of SGCCA are illustrated on a simulated dataset and on a 3-block dataset which combine gene expression, comparative genomic hybridization, and a qualitative phenotype measured on a set of 53 children with glioma. SGCCA is available on CRAN as part of the RGCCA package.