Multidisciplinary Management of Medulloblastoma: Consensus, Challenges, and Controversies

Transcriptome analysis stratifies second-generation non-WNT/non-SHH medulloblastoma subgroups into clinically tractable subtypes

Medulloblastoma (MB), one of the most common malignant pediatric brain tumor, is a heterogenous disease comprised of four distinct molecular groups (WNT, SHH, Group 3, Group 4). Each of these groups can be further subdivided into second-generation MB (SGS MB) molecular subgroups, each with distinct genetic and clinical characteristics. For instance, non-WNT/non-SHH MB (Group 3/4) can be subdivided molecularly into eight distinct and clinically relevant tumor subgroups. A further molecular stratification/summarization of these SGS MB would allow for the assignment of patients to risk-associated treatment protocols. Here, we performed DNA- and RNA-based analysis of 574 non-WNT/non-SHH MB and analyzed the clinical significance of various molecular patterns within the entire cohort and the eight SGS MB, with the aim to develop an optimal risk stratification of these tumors. Multigene analysis disclosed several survival-associated genes highly specific for each molecular subgroup within this non-WNT/non-SHH MB cohort with minimal inter-subgroup overlap. These subgroup-specific and prognostically relevant genes were associated with pathways that could underlie SGS MB clinical-molecular diversity and tumor-driving mechanisms. By combining survival-associated genes within each SGS MB, distinct metagene sets being appropriate for their optimal risk stratification were identified. Defined subgroup-specific metagene sets were independent variables in the multivariate models generated for each SGS MB and their prognostic value was confirmed in a completely non-overlapping validation cohort of non-WNT/non-SHH MB (n = 377). In summary, the current results indicate that the integration of transcriptome data in risk stratification models may improve outcome prediction for each non-WNT/non-SHH SGS MB. Identified subgroup-specific gene expression signatures could be relevant for clinical implementation and survival-associated metagene sets could be adopted for further SGS MB risk stratification. Future studies should aim at validating the prognostic role of these transcriptome-based SGS MB subtypes in prospective clinical trials.

Effects of metformin on Sonic hedgehog subgroup medulloblastoma progression: In vitro and in vivo studies

Metformin is a first-line drug for type 2 diabetes, and its anticancer effects have also been widely studied in recent years. The Sonic hedgehog (Shh) signaling pathway is involved in the initiation and progression of medulloblastoma. In order to develop a new treatment strategy for medulloblastoma (MB), this study investigated the inhibitory effect of metformin on MB and the underlying mechanism of metformin on the Shh signaling pathway. The effect of metformin on proliferation was evaluated by the cell counting kit-8 (CCK-8) test and colony formation experiment. The effect of metformin on metastasis was assessed by the scratch-wound assay and transwell invasion assay. Cell cycle and apoptosis were evaluated by flow cytometry, and the associated proteins were examined by western blotting. The mRNA and protein expression levels related to the Shh pathway were measured by quantitative PCR, western blotting, and immunofluorescence staining. The xenograft murine model was carried out to evaluate the anticancer effect of metformin on medulloblastoma in vivo. Metformin inhibited proliferation and metastasis of the Shh subgroup MB cell line, and the inhibitory effect on proliferation was related to apoptosis and the block of the cell cycle at the G0/G1 phase. Animal experiments showed that metformin inhibits medulloblastoma growth in vivo. Moreover, metformin decreased mRNA and protein expression levels of the Shh pathway, and this effect was reversed by the AMP-activated protein kinase (AMPK) siRNA. Furthermore, the pro-apoptotic and cell cycle arrest effects of metformin on Daoy cells could be reversed by the Shh pathway activators. Our findings demonstrated that metformin could inhibit medulloblastoma progression in vitro and in vivo, and this effect was associated with AMPK-mediated inhibition of the Shh signaling pathway in vitro studies.

Gene expression profiling of Group 3 medulloblastomas defines a clinically tractable stratification based on KIRREL2 expression

Medulloblastomas (MB) molecularly designated as Group 3 (Grp 3) MB represent a more clinically aggressive tumor variant which, as a group, displays heterogeneous molecular characteristics and disease outcomes. Reliable risk stratification of Grp 3 MB would allow for appropriate assignment of patients to aggressive treatment protocols and, vice versa, for sparing adverse effects of high-dose radio-chemotherapy in patients with standard or low-risk tumors. Here we performed RNA-based analysis on an international cohort of 179 molecularly designated Grp 3 MB treated with HIT protocols. We analyzed the clinical significance of differentially expressed genes, thereby developing optimal prognostic subdivision of this MB molecular group. We compared the transcriptome profiles of two Grp 3 MB subsets with various outcomes (76 died within the first 60 months vs. 103 survived this period) and identified 224 differentially expressed genes (DEG) between these two clinical groups (Limma R algorithm, adjusted p-value < 0.05). We selected the top six DEG overexpressed in the unfavorable cohort for further survival analysis and found that expression of all six genes strongly correlated with poor outcomes. However, only high expression of KIRREL2 was identified as an independent molecular prognostic indicator of poor patients' survival. Based on clinical and molecular patterns, four risk categories were outlined for Grp 3 MB patients: i. low-risk: M0-1/MYC non-amplified/KIRREL2 low (n = 48; 5-year OS-95%); ii. standard-risk: M0-1/MYC non-amplified/KIRREL2 high or M2-3/MYC non-amplified/KIRREL2 low (n = 65; 5-year OS-70%); iii. high-risk: M2-3/MYC non-amplified/KIRREL2 high (n = 36; 5-year OS-30%); iv. very high risk-all MYC amplified tumors (n = 30; 5-year OS-0%). Cross-validated survival models incorporating KIRREL2 expression with clinical features allowed for the reclassification of up to 50% of Grp 3 MB patients into a more appropriate risk category. Finally, KIRREL2 immunopositivity was also identified as a predictive indicator of Grp 3 MB poor survival, thus suggesting its application as a possible prognostic marker in routine clinical settings. Our results indicate that integration of KIRREL2 expression in risk stratification models may improve Grp 3 MB outcome prediction. Therefore, simple gene and/or protein expression analyses for this molecular marker could be easily adopted for Grp 3 MB prognostication and may help in assigning patients to optimal therapeutic approaches in prospective clinical trials.