Clinicomorphological and molecular analysis of medulloblastoma and association with survival: A single tertiary care center experience

Abstract

ABSTRACTS Background: Medulloblastoma (MB) is a heterogeneous disease, displaying distinct genetic profiles, with specific molecular subgroups. Various clinical, pathological and molecular variables have been associated with disease outcome and therefore utilised in risk stratification of patients. Objectives: To perform molecular classification of medulloblastoma using surrogate immunohistochemistry (IHC) and associate molecular subgroups, histopathological types, and available clinicopathological parameters with overall survival (OS) of MB patients. Results: This study included 65 medulloblastoma patients. Immunohistochemical staining, using β-catenin YAP1 and GRB2-Associated Binding Protein 1 (GAB1) antibodies was used to classify MB cases into wingless signalling (WNT) activated, sonic hedgehog (SHH) activated, and non-WNT/non-SHH molecular subgroups. The relevant statistical analysis was done using GraphPad Prism version 9.3.0. Histological patterns included classic (40 cases, 62%), desmoplastic nodular (D/N) (14 cases, 22%), large cell/anaplastic (LC/A) (9 cases, 13%), medulloblastoma with extensive nodularity (MBEN) (1 case, 1.5%) and one special subtype, i.e., medulloblastoma with myogenic and melanotic differentiation. Molecular subgroups included WNT (4 cases, 6%), SHH (34 cases, 52%), and non-WNT/non-SHH (27 cases, 42%) subgroups. Histopathological types differed significantly according to tumor location, degree of anaplasia and molecular subgroups. Molecular subgroups differed significantly in age distribution and tumor location. The probability of survival was 78% and 68% after 1 and 2 years, respectively. Infants (<3 years of age), LC/A pattern, and TP53-mutant status among SHH subgroup conferred poor prognosis in our study. At the end of the study (at 65 months of maximum follow-up period) probability of survival was 51%. Conclusions: Immunohistochemical analysis helps in molecular classification of medulloblastoma in majority of the cases as well as helps in predicting prognosis and treatment response.