Genetic screening algorithm for children with medulloblastoma: a scoring system for stratifying the risk of hereditary variants

Abstract

Introduction . Medulloblastoma is the most common malignant central nervous system tumor in children, representing a molecularly heterogeneous group of neoplasms (SHH, WNT, Group 3, Group 4 subtypes). Germline mutations in predisposition genes (PTCH1, SUFU, TP53, APC, BRCA2, PALB2, ELP1, GPR161) are identified in 5–15 % of patients, predominantly in SHH and WNT subtypes. The purpose of the study – to develop a screening algorithm with a risk stratification scoring system for hereditary medulloblastoma variants to rationally select patients for genetic testing. Materials and methods . The study included a cohort of 26 patients with medulloblastoma aged 0 to 18 years who received chemotherapy in 2024–2025 at V.F. Voyno-Yasenetsky Scientific and Practical Center of Specialized Medical Care for Children. Molecular subgroup determination was performed using NanoString technology or DNA methylation profiling. Genetic counseling was provided to all patients. Germline mutations in DNA extracted from peripheral blood were analyzed in 11 patients using parallel sequencing (whole exome sequencing) and Sanger sequencing. Results . Molecular classification was performed in 20 patients: SHH – 38 %, WNT – 5 %, Group 3 – 24 %, Group 4 – 29 %. Genetic testing was conducted in 11 patients, with pathogenic germline variants identified in 6 (55 %): Gorlin syndrome (n = 2), Li–Fraumeni syndrome (n = 1), Turcot syndrome type 2 (n = 1), Fanconi anemia/PALB2 (n = 1), ELP1 mutation (n = 1). Hereditary forms were exclusively found in SHH/WNT subtypes (100 %). Patients with pathogenic variants scored ³ 4 points. No pathogenic variants were identified in Group 3 and Group 4 cases. Conclusions . Genetic counseling with testing should be considered a standard procedure in the management of patients with SHH- and WNT-subtype medulloblastomas. The developed scoring system enables detection of 90–95% of hereditary forms while testing only 30–40 % of patients, improving diagnostic efficiency and optimizing resource utilization.