MIF-CD74 signaling drives immune modulation in medulloblastoma
Menée à l'aide de modèles murins, d'un algorithme et de données de séquençage d'ARN portant sur 140 patients atteints d'un médulloblastome, cette étude met en évidence un mécanisme par lequel des interactions entre le facteur d’inhibition de la migration des macrophages MIF et l'antigène CD74 régulent l'immunité antitumorale
Background : Relapsed medulloblastoma remains a significant therapeutic challenge as it is near universally fatal. The tumor microenvironment of medulloblastoma plays a critical role in tumor progression, influencing tumor growth, immune evasion, and therapeutic resistance. We hypothesised that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets.
Methods : We analysed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the tumor microenvironment. To identify key tumor–immune interactions, we developed a novel algorithm to detect receptor–ligand pairs using single cell RNA-sequencing data. These interactions were validated across RNA and proteomic datasets. Their functional significance was empirically demonstrated in newly developed immunocompetent models of recurrent medulloblastoma that closely recapitulate the human disease.
Results : We observed a shift in toward a heightened immunosuppressive tumor microenvironment at relapse. Using our algorithm, we identified biologically significant receptor-ligand interactions, most notably MIF-CD74, constitutively expressed at RNA and protein levels across medulloblastoma subgroups, at diagnosis and relapse. Disrupting MIF-CD74 interactions led to significant alterations in the tumor microenvironment, highlighting its functional significance.
Conclusions : Our multifaceted approach identified key tumor-immune interactions in medulloblastoma. Among these, MIF-CD74 was validated as a targetable interaction, demonstrating the utility of our integrative approach for identifying novel therapeutic targets across multiple tumor types.
Neuro-Oncology , résumé, 2026