Abstract LB332: Spatial transcriptomic and proteomic analysis of the treatment resistant slow cycling micro environment in GBM

Abstract Within the Glioblastoma (GBM) microenvironment, there are micro-niches originating from independent lineages of cancer stem cells with distinct metabolic requirements that are characterized by Fast cycling cells (FCCs) and Slow cycling cells (SCC). The FCCs employ aerobic glycolysis for energy, while the treatment-resistant SCCs primarily rely on lipid metabolism. Our study allows for the molecular and spatial decoding of the heterogeneity within the GBM microenvironment, with a specific focus on decoding the dichotomy of the immune infiltrates and studying the interactions between the SCCs and the immune compartment in human GBM patients. Our research reveals a new paradigm of interaction within the tumor microenvironment (TME) of glioblastoma (GBM) patients, in which SCCs are instrumental in altering the tumor milieu to favor immune suppression. These SCCs actively recruit and harness sub-population of immune cells of myeloid origin that promote tumor growth and simultaneously provide metabolic aid to these treatment-resistant cells. Our research maps out the intricate metabolic dialogues within GBM and evaluates the potential therapeutic effect of disrupting this interaction to open up new treatment avenues. The findings based on our spatial transcriptomic and proteomic study on brain biopsies from human patients provide a deeper understanding of the critical links among the tumor's local environment, cellular metabolism, anti-tumor immunity, and potential treatment vulnerabilities. In summary, our investigation offers novel insights into how metabolic exchanges contribute to the evolution of GBM leading to the development of drug and immune resistant GBM. Our data is suggestive that therapies aimed at these metabolic interactions, especially those between SCCs and metabolically supporting immunosuppressive myeloid originating immune cells, hold potential as effective therapeutic strategy for GBM. Citation Format: Avirup Chakraborty, Diana Feier, Aryeh Silver, Changlin Yang, Miruna Anica, Avinash Pittu, Olusegun Sobanjo, Ethan Hodge, Mia Engelbart, Christina Von Roemeling, Maryam Rahman, Matthew Sarkisian, Jianping Huang, Jeffrey Harrison, Duane Mitchell, Loic Deleyrolle. Spatial transcriptomic and proteomic analysis of the treatment resistant slow cycling micro environment in GBM abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (7Suppl): Abstract nr LB332.