Molecular subgroups of adult medulloblastoma: a long-term single-institution study

Abstract

Background: Recent transcriptomic approaches have demonstrated that there are at least 4 distinct subgroups in medulloblastoma (MB); however, survival studies of molecular subgroups in adult MB have been inconclusive because of small sample sizes. The aim of this study is to investigate the molecular subgroups in adult MB and identify their clinical and prognostic implications in a large, single-institution cohort.

Methods: We determined gene expression profiles for 13 primary adult MBs. Bioinformatics tools were used to establish distinct molecular subgroups based on the most informative genes in the dataset. Immunohistochemistry with subgroup-specific antibodies was then used for validation within an independent cohort of 201 formalin-fixed MB tumors, in conjunction with a systematic analysis of clinical and histological characteristics.

Results: Three distinct molecular variants of adult MB were identified: the SHH, WNT, and group 4 subgroups. Validation of these subgroups in the 201-tumor cohort by immunohistochemistry identified significant differences in subgroup-specific demographics, histology, and metastatic status. The SHH subgroup accounted for the majority of the tumors (62%), followed by the group 4 subgroup (28%) and the WNT subgroup (10%). Group 4 tumors had significantly worse progression-free and overall survival compared with tumors of the other molecular subtypes.

Conclusions: We have identified 3 subgroups of adult MB, characterized by distinct expression profiles, clinical features, pathological features, and prognosis. Clinical variables incorporated with molecular subgroup are more significantly informative for predicting adult patient outcome.

Keywords: adult medulloblastoma; histology; molecular subgroup; prognosis; survival.

Fig. 1.

Gene expression profiles for 13 primary adult MBs display 3 subgroups with distinct demographics and histology. (A) Unsupervised hierarchical clustering of 13 adult medulloblastomas based on 1300 transcripts with high standard deviation. Hierarchical clustering is performed using average linkage and dissimilarity based on the Pearson correlation metric. Clinical features of the study population are indicated below the dendrogram: sex (male, black; female, white), age at diagnosis (18–20 y, red; 20–40 y, white; >40 y, black), histology (C, white; DN, black; LC/A, red), M stage (M0, white; M+, black), risk (low, white; high, black), and progression and death (no event, white; event, black). (B) Application of consensus non-negative matrix factorization (NMF), an unsupervised bioinformatics tool for determining the number of independent classes within an expression dataset, strongly supports the existence of 3 adult medulloblastoma subgroups.

Fig. 2.

Kaplan–Meier plots of estimated OS (left side) and PFS (right side) time distributions for the 201-tumor cohort of adult MB according to: (A, B) risk staging: average risk vs high risk, (C, D) histology: classic vs desmoplastic/nodular vs anaplastic vs large cell, and (E, F) molecular subgroup: WNT vs SHH vs group 4. Survival differences are calculated using continuous log-rank tests.

Fig. 2.

Kaplan–Meier plots of estimated OS (left side) and PFS (right side) time distributions for the 201-tumor cohort of adult MB according to: (A, B) risk staging: average risk vs high risk, (C, D) histology: classic vs desmoplastic/nodular vs anaplastic vs large cell, and (E, F) molecular subgroup: WNT vs SHH vs group 4. Survival differences are calculated using continuous log-rank tests.