Proteomics and Multi-Omics Approaches to Brain Tumors and Multiple Sclerosis: Linking Neuroinflammation and Neurodegeneration

Neurological diseases, from brain tumors to neurodegenerative and neuroinflammatory disorders, are among the most difficult to diagnose and treat. Conditions like gliomas, medulloblastomas, multiple sclerosis, Alzheimer’s disease, ALS, and other central nervous system disorders are marked by complex molecular and cellular diversity. Traditional single-omic methods often miss the interactions between genetics, epigenetics, protein function, metabolism, and the surrounding environment. New precision proteomics and multi-omics technologies have transformed the field. By studying proteins, their modifications, metabolic changes, and how different molecular layers interact, these tools provide insights that DNA and RNA analysis alone cannot offer. This deeper understanding can lead to more accurate diagnoses, improved methods for categorising diseases, enhanced predictions of disease progression and therapeutic response, and the development of personalised treatment strategies for neuro-oncology, neurodegenerative, and neuroinflammatory disorders.

This Research Topic seeks submissions that investigate the role of precision proteomics and multi-omics in advancing the understanding of neurological diseases, including brain tumors, neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, and ALS, neuroinflammatory conditions such as multiple sclerosis (MS), and other central nervous system (CNS) disorders. Studies utilizing human samples, animal models, organoids, induced pluripotent stem cell (iPSC)-derived systems, and other innovative disease models are encouraged. Acceptable submission types include original research, reviews, methodological papers, and meta-analyses that integrate proteomic, metabolomic, genomic, transcriptomic, spatial, or single-cell data. Relevant topics encompass biomarker discovery and validation, early detection, molecular subtyping, treatment response, therapy resistance, microenvironmental dynamics, immune interactions, and systems biology or network-based approaches. Submissions spanning basic, translational, and clinical research are welcome. By integrating diverse methodologies and model systems, this collection aims to broaden the application of precision medicine in neuro-oncology and neurological disease.

The objective of this Research Topic is to highlight innovative research employing proteomics and integrative multi-omics approaches to improve the diagnosis, stratification, and treatment of brain tumors, neurodegenerative diseases, and neuroinflammatory disorders. Despite extensive research, patients with conditions such as glioblastoma, multiple sclerosis, and ALS continue to face poor prognoses, emphasizing the need for molecular insights that can inform effective therapies. Integrating proteomic and metabolomic data with genomic, transcriptomic, epigenomic, and spatial information enables the identification of predictive biomarkers, therapeutic targets, mechanisms underlying disease progression or treatment resistance, and disease-specific molecular signatures.

This Research Topic is designed to establish a multidisciplinary platform for researchers, clinicians, computational biologists, and industry scientists to disseminate findings and foster collaborative networks. Discovery-driven and translational studies utilizing human patient samples, longitudinal cohorts, animal models, organoids, and other advanced systems are encouraged. Relevant topics include biomarker validation, pathway mapping, cell-type-specific analyses, microenvironmental and immune interactions, and multi-omic integration methodologies. By uniting diverse research strategies across neuro-oncology and neurological disease, this collection aims to promote innovation and expedite the translation of multi-omic discoveries into precision medicine interventions that enhance patient outcomes.
Please note: Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.