Risk Factors for Survival in Patients With Medulloblastoma: A Systematic Review and Meta-Analysis

A Prognostic Methylation-Driven Two-Gene Signature in Medulloblastoma

Medulloblastoma (MB) is one of the most common pediatric brain tumors and it is estimated that one-third of patients will not achieve long-term survival. Conventional prognostic parameters have limited and unreliable correlations with MB outcome, presenting a major challenge for patients' clinical improvement. Acknowledging this issue, our aim was to build a gene signature and evaluate its potential as a new prognostic model for patients with the disease. In this study, we used six datasets totaling 1679 samples including RNA gene expression and DNA methylation data from primary MB as well as control samples from healthy cerebellum. We identified methylation-driven genes (MDGs) in MB, genes whose expression is correlated with their methylation. We employed LASSO regression, incorporating the MDGs as a parameter to develop the prognostic model. Through this approach, we derived a two-gene signature (GS-2) of candidate prognostic biomarkers for MB (CEMIP and NCBP3). Using a risk score model, we confirmed the GS-2 impact on overall survival (OS) with Kaplan-Meier analysis. We evaluated its robustness and accuracy with receiver operating characteristic curves predicting OS at 1, 3, and 5 years in multiple independent datasets. The GS-2 showed highly significant results as an independent prognostic biomarker compared to traditional MB markers. The methylation-regulated GS-2 risk score model can effectively classify patients with MB into high and low-risk, reinforcing the importance of this epigenetic modification in the disease. Such genes stand out as promising prognostic biomarkers with potential application for MB treatment.

Human-Level Differentiation of Medulloblastoma from Pilocytic Astrocytoma: A Real-World Multicenter Pilot Study

Medulloblastoma and pilocytic astrocytoma are the two most common pediatric brain tumors with overlapping imaging features. In this proof-of-concept study, we investigated using a deep learning classifier trained on a multicenter data set to differentiate these tumor types. We developed a patch-based 3D-DenseNet classifier, utilizing automated tumor segmentation. Given the heterogeneity of imaging data (and available sequences), we used all individually available preoperative imaging sequences to make the model robust to varying input. We compared the classifier to diagnostic assessments by five readers with varying experience in pediatric brain tumors. Overall, we included 195 preoperative MRIs from children with medulloblastoma (n = 69) or pilocytic astrocytoma (n = 126) across six university hospitals. In the 64-patient test set, the DenseNet classifier achieved a high AUC of 0.986, correctly predicting 62/64 (97%) diagnoses. It misclassified one case of each tumor type. Human reader accuracy ranged from 100% (expert neuroradiologist) to 80% (resident). The classifier performed significantly better than relatively inexperienced readers (p < 0.05) and was on par with pediatric neuro-oncology experts. Our proof-of-concept study demonstrates a deep learning model based on automated tumor segmentation that can reliably preoperatively differentiate between medulloblastoma and pilocytic astrocytoma, even in heterogeneous data.

Integrin-αvβ3 is a Therapeutically Targetable Fundamental Factor in Medulloblastoma Tumorigenicity and Radioresistance

Medulloblastoma is one of the most prevalent solid tumors found in children, occurring in the brain's posterior fossa. The standard treatment protocol involves maximal resection surgery followed by craniospinal irradiation and chemotherapy. Despite a long-term survival rate of 70%, wide disparities among patients have been observed. The identification of pertinent targets for both initial and recurrent medulloblastoma cases is imperative. Both primary and recurrent medulloblastoma are marked by their aggressive infiltration into surrounding brain tissue, robust angiogenesis, and resistance to radiotherapy. While the significant role of integrin-αvβ3 in driving these characteristics has been extensively documented in glioblastoma, its impact in the context of medulloblastoma remains largely unexplored. Integrin-αvβ3 was found to be expressed in a subset of patients with medulloblastoma. We investigated the role of integrin-αvβ3 using medulloblastoma-derived cell lines with β3-subunit depletion or overexpression both in vitro and in vivo settings. By generating radioresistant medulloblastoma cell lines, we uncovered an increased integrin-αvβ3 expression, which correlated with increased susceptibility to pharmacologic integrin-αvβ3 inhibition with cilengitide, a competitive ligand mimetic. Finally, we conducted single-photon emission computed tomography (SPECT)/MRI studies on orthotopic models using a radiolabeled integrin-αvβ3 ligand (99mTc-RAFT-RGD). This innovative approach presents the potential for a novel predictive imaging technique in the realm of medulloblastoma. Altogether, our findings lay the foundation for employing SPECT/MRI to identify a specific subset of patients with medulloblastoma eligible for integrin-αvβ3-directed therapies. This breakthrough offers a pathway toward more targeted and effective interventions in the treatment of medulloblastoma.

SIGNIFICANCE

This study demonstrates integrin-αvβ3's fundamental role in medulloblastoma tumorigenicity and radioresistance and the effect of its expression on cilengitide functional activity.

Global trends, gaps, and future agenda in medulloblastoma research: a bibliometric analysis

BACKGROUND

Medulloblastoma is the most common malignant primary pediatric brain tumor. Over the years, an increase in published research has been observed on this topic. However, there is a lack of analysis on the characteristics and trends and the socioeconomic indicators associated with medulloblastoma research productivity and impact.

METHODS

The Scopus database was used to search all articles from inception to 2020. Bibliometric information was obtained from Scopus, and bibliometrics diagrams were created using VOSviewer software. Statistical analysis was performed using the GraphPad Prism software version 7.

RESULTS

A total of 4058 research articles on medulloblastoma research worldwide were included in this study. There has been an increase in published articles, with a steep increase observed in the last decade. The country with the most publications is the USA, with St. Jude Children's Research Hospital as the most productive institution in medulloblastoma research. The articles mainly focused on molecular biology, diagnosis, treatment, prognostic factors for medulloblastoma, and research on other pediatric tumors. The number of collaborations with other countries showed the strongest positive correlation with scientific productivity.

CONCLUSION

This analysis showed the trend and characteristics of published articles. The results of this study emphasized the need to increase funding for research, support for researchers and physicians, and promote more collaborations with countries and institutions engaged in medulloblastoma research.

A nomogram for predicting post-operative hydrocephalus in children with medulloblastoma

Post-operative hydrocephalus is common among children with medulloblastoma after initial tumor resection. This study aimed to establish a novel model for predicting the development of post-operative hydrocephalus in children with medulloblastoma. Only pediatric patients who received initial medulloblastoma resection at Beijing Tiantan Hospital between January 2018 and May 2021 were included in this study. The potential risk factors associated with post-operative hydrocephalus were identified based on multivariate logistic regression and the nomogram. Receiver operating characteristic (ROC) curve were used to evaluate the performance of the nomogram model based on an independent cohort of medulloblastoma patients who underwent surgery from June 2021 to March 2022. A total of 105 patients were included in the primary cohort. Superior invasion (P = 0.007), caudal invasion (P = 0.025), and intraventricular blood ≥ 5 mm (P = 0.045) were significantly related to the development of post-operative hydrocephalus and thus were assembled into the nomogram model. The model accurately predicted post-operative hydrocephalus based on the calibration curve. The area under the ROC curves for the primary and validation cohorts was 0.849 and 0.855, respectively. In total, the nomogram we developed may aid clinicians in assessing the potential risk of pediatric patients with MB developing post-operative hydrocephalus, especially those who would otherwise not have received a diversionary procedure at presentation.

Clinical, Histological, and Molecular Prognostic Factors in Childhood Medulloblastoma: Where Do We Stand?

Medulloblastomas, highly aggressive neoplasms of the central nervous system (CNS) that present significant heterogeneity in clinical presentation, disease course, and treatment outcomes, are common in childhood. Moreover, patients who survive may be diagnosed with subsequent malignancies during their life or could develop treatment-related medical conditions. Genetic and transcriptomic studies have classified MBs into four subgroups: wingless type (WNT), Sonic Hedgehog (SHH), Group 3, and Group 4, with distinct histological and molecular profiles. However, recent molecular findings resulted in the WHO updating their guidelines and stratifying medulloblastomas into further molecular subgroups, changing the clinical stratification and treatment management. In this review, we discuss most of the histological, clinical, and molecular prognostic factors, as well the feasibility of their application, for better characterization, prognostication, and treatment of medulloblastomas.