Metabolomic analysis of SH-SY5Y and U87MG cell lines: effects of differentiation with retinoic acid and cannabinoid treatment

Gabriel Borges Ravaglia1, Murilo de Carvalho2, Alessandra Sussulini1

1. UNICAMP, Universidade Estadual de Campinas; Cidade Universitária Zeferino Vaz - Barão Geraldo, Campinas - SP, 13083-970
2. CNPEM, Centro Nacional de Pesquisa em Energia e Materiais; Polo II de Alta Tecnologia - R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas - SP, 13083-100

Cell lines are essential tools in biomedical research, particularly for the study of complex pathologies such as glioblastoma and neuroblastoma, which are characterized by poor prognoses and have significant therapeutic challenges. The U87MG (glioblastoma) and SH-SY5Y (neuroblastoma) cell lines are widely used to investigate the molecular mechanisms underlying neurodegenerative diseases and to assess neurotoxicity or neuroprotection induced by exposure to various compounds, including cannabinoids. Recent studies have demonstrated that cannabinoids interact with CB1 and CB2 receptors, modulating pathways involved in cell proliferation, inflammation, energy metabolism, and other processes. In this context, metabolomics emerges as a powerful analytical strategy to map metabolic alterations associated with cannabinoid exposure, providing detailed insights into cellular responses to treatment. In this context, the present study aims to analyze the metabolic changes in U87MG and SH-SY5Y cell lines in response to treatment with full-spectrum cannabis oil using an untargeted metabolomics approach based on mass spectrometry. The cell cultures will be subjected to various experimental conditions, including retinoic acidinduced differentiation and exposure to different concentrations of cannabis oil, with defined levels of cannabidiol (CBD) and tetrahydrocannabinol (THC). The main goal is to elucidate the affected metabolic pathways and contribute to the development of novel therapeutic strategies for brain tumors and neurodegenerative diseases.

Agradecimentos: FAPESP; CAPES; FINEP; CNPq