The meta-analysis presented here represents the largest series of biology data on medulloblastoma reported so far. The data clearly demonstrate that medulloblastoma is not a single disease. The four major subgroups (WNT, SHH, Group 3, and Group 4) differ in many aspects. They are transcriptionally, genetically, demographically, clinically, and prognostically distinct, confirming earlier reports in smaller series [
1,
3,
9,
15,
19,
25]. Most likely, they will also have different cellular origins, as has already been shown for the WNT and SHH subgroups [
7,
8,
23,
26]. The cellular origin of Group 3 and 4 medulloblastomas is still unknown. Several of the earlier profiling studies showed that there might even be five or six subgroups of medulloblastoma [
1,
9,
25], with further subdivisions of Group 3 and Group 4. An analysis performed on the combined GEP cohorts under the assumption that there were five or six subgroups showed that there are indeed subsets present within these subgroups with transcriptional and genetic differences, but demographically they were not different (data not shown). Collectively, these data demonstrate that there are only four core disease subgroups of medulloblastoma, with a yet unknown number of subsets within each subgroup. Subsets also exist within the SHH subgroup as we and others recently demonstrated [
14,
18]. These subsets show transcriptional and genetic differences and seem to be associated with the different age groups (infants vs. adults; [
14]) that exist within the SHH subgroup and with the presence of
P53 mutations [
18]. Potentially, they could actually represent different disease variants with different cellular origins, which might explain the bimodal age distribution of SHH medulloblastomas. The meta-analysis data also show that prognostic factors like metastatic stage, histology,
MYC and
MYCN amplifications, 10q loss, 17p loss, and 17q gain, previously reported for medulloblastoma as a single disease [
11,
12,
17], remain prognostic in these combined series of all patients. However, our data now show for the first time how they all perform in the context of different subgroups. For instance, the observation that medulloblastomas with chromosome 17 aberrations have an adverse outcome is due to the fact that they are most frequent in Group 3 and Group 4 medulloblastomas, which fare worse than the WNT and SHH subgroups. However, even within these subgroups, loss of 17p and/or gain of 17q remain independent prognostic factors for SHH, Group 3 and 4. Other factors, which are clearly prognostic for the entire medulloblastoma cohort, such as histology or metastasis, are barely prognostic in specific subgroups and most of them do not hold up in the multivariate analysis. Only for the SHH subgroup does histology remain an independent prognostic factor, and we have identified gain of 3q as a novel independent prognostic factor for this subgroup.
MYC and
MYCN amplifications also predict an unfavourable outcome in the entire cohort (Fig.
4a), in line with previous publications [
3,
11,
17,
22]. However,
MYC amplification, most frequent in Group 3 medulloblastomas, is not prognostic within this subgroup (Fig.
4c). In contrast,
MYCN amplification, mostly occurring in SHH or Group 4 medulloblastomas, is still prognostic in both of these subgroups (Fig.
4b, d), but did not hold up in the multivariate analyses (Table
1). Only after correcting for age (excluding infants)
MYCN amplification remains prognostic within the SHH subgroups (Table S3). Therefore, medulloblastoma subgrouping is by far the best factor in terms of prognostication identified to date, but there is now a need for identifying better prognostic markers within each of the subgroups. A good example of such a subgroup-specific biomarker is the recently identified FSTL5 protein [
19]. Immunopositivity of FSTL5 identified a large group of patients at high risk across all medulloblastomas, but more importantly, also within Group 3 and 4 patients.
One drawback in the survival analyses performed in this meta-analysis is the fact that the patients contained in each of the different GEP cohorts come from different studies, and have been treated in multiple centers according to different protocols. This is also demonstrated by the overall survival of the four subgroups in the GEP cohort in comparison with that in the TMA cohort. All tumors in the TMA cohort come from patients treated in a single institute according to standardized therapeutic protocols of the German HIT study group. Interestingly, in this TMA cohort, patients with SHH medulloblastomas had a much better outcome compared to the SHH medulloblastomas in the combined GEP cohort, whereas especially patients with Group 3 medulloblastomas had a much worse prognosis. Furthermore, WNT medulloblastomas, reported in several studies as having a very good outcome [
2‐
4,
15,
17], which is confirmed in the meta-analyses of the GEP cohorts, do not have such a good outcome in adults of the TMA cohort. One of the reasons explaining these differences in overall survival for the different subgroups between the GEP and TMA cohorts could be that in general medulloblastoma patients represented on the TMA cohort received less intensive therapies compared to most other patients present in the GEP cohorts. As illustrated in another paper in this issue [
10], even
MYCN amplified cases in the SHH subgroup have a better outcome when receiving less intensive therapies. These data suggest that most, if not all SHH medulloblastoma patients may benefit from a less intensive protocol, but other subgroups, and in particular Group 3 tumors, may not. Prospective studies targeting specific subgroups should aim to resolve this question. Future clinical trials will require reliable and reproducible methods to subgroup clinical medulloblastoma samples in a fast way. For this, the recently developed NanoString assay can be used, which predicts the tumor specific subgroup with high accuracy, based on the expression level of 22 subgroup-specific signature genes [
16]. Alternatively, a panel of immunohistochemistry-based markers can be assessed, as demonstrated in previous publications [
3,
15,
19]. As yet, the most reliable method to attribute patients to the four subgroups has still to be decided, but efforts are ongoing to address this question.
In summary, we consistently find four core molecular subgroups of medulloblastoma across all published datasets which are as distinct as different tumor entities and, therefore, should be regarded as such. Thus, future studies of medulloblastoma should accommodate this new clinically useful knowledge for optimizing trial design and treatment protocols.