Jacques, Thomas S.

Abstract 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 hypothesized that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets. Methods We analyzed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the TME. 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 toward a heightened immunosuppressive TME 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.

Abstract Genome-wide DNA methylation signatures correlate with and distinguish central nervous system (CNS) tumor types. Since the publication of the initial CNS tumor DNA methylation classifier in 2018, this platform has been increasingly used as a diagnostic tool for CNS tumors, with multiple studies showing the value and utility of DNA methylation-based classification of CNS tumors. A Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) Working Group was therefore convened to describe the current state of the field and to provide advice based on lessons learned to date. Here, we provide recommendations for the use of DNA methylation-based classification in CNS tumor diagnostics, emphasizing the attributes and limitations of the modality. We emphasize that the methylation classifier is one diagnostic tool to be used alongside previously established diagnostic tools in a fully integrated fashion. In addition, we provide examples of the inclusion of DNA methylation data within the layered diagnostic reporting format endorsed by the World Health Organization (WHO) and the International Collaboration on Cancer Reporting. We emphasize the need for backward compatibility of future platforms to enable accumulated data to be compatible with new versions of the array. Finally, we outline the specific connections between methylation classes and CNS WHO tumor types to aid in the interpretation of classifier results. It is hoped that this update will assist the neuro-oncology community in the interpretation of DNA methylation classifier results to facilitate the accurate diagnosis of CNS tumors and thereby help guide patient management.

Abstract Objective Focal cortical dysplasia (FCD) is a major cause of difficult‐to‐treat epilepsy in children and young adults, and the diagnosis is currently based on microscopic review of surgical brain tissue using the International League Against Epilepsy classification scheme of 2011. We developed an iterative histopathological agreement trial with genetic testing to identify areas of diagnostic challenges in this widely used classification scheme. Methods Four web‐based digital pathology trials were completed by 20 neuropathologists from 15 countries using a consecutive series of 196 surgical tissue blocks obtained from 22 epilepsy patients at a single center. Five independent genetic laboratories performed screening or validation sequencing of FCD‐relevant genes in paired brain and blood samples from the same 22 epilepsy patients. Results Histopathology agreement based solely on hematoxylin and eosin stainings was low in Round 1, and gradually increased by adding a panel of immunostainings in Round 2 and the Delphi consensus method in Round 3. Interobserver agreement was good in Round 4 (kappa = .65), when the results of genetic tests were disclosed, namely, MTOR , AKT3 , and SLC35A2 brain somatic mutations in five cases and germline mutations in DEPDC5 and NPRL3 in two cases. Significance The diagnoses of FCD 1 and 3 subtypes remained most challenging and were often difficult to differentiate from a normal homotypic or heterotypic cortical architecture. Immunohistochemistry was helpful, however, to confirm the diagnosis of FCD or no lesion. We observed a genotype–phenotype association for brain somatic mutations in SLC35A2 in two cases with mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy. Our results suggest that the current FCD classification should recognize a panel of immunohistochemical stainings for a better histopathological workup and definition of FCD subtypes. We also propose adding the level of genetic findings to obtain a comprehensive, reliable, and integrative genotype–phenotype diagnosis in the near future.