PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 5, 2026Cancer Research0 citations

Abstract 3879: SPP1-driven immunometabolic reprogramming of tumor-associated neutrophils in glioblastoma.

View Full Paper
MAMatthew AbikenariJCJohn ChoiRMRavi Medikonda

Key Points

  • This research aims to characterize the states of tumor-associated neutrophils in glioblastoma and identify mechanisms driving their pro-tumoral functions.
  • Reanalyzed public single-cell RNA sequencing datasets of neutrophils.
  • Applied standard workflows for quality control, integration, and clustering of data.
  • Used differential expression analyses to identify key neutrophil states and pathways.
  • Conducted network analysis to explore functional relationships among genes.
  • Identified six distinct tumor-associated neutrophil states beyond classical models.
  • Highlighted a specific SPP1+ population associated with lipid processing and immune signaling genes.
  • Found SPP1+ neutrophils exhibiting metabolic reprogramming and reduced cytotoxicity.
  • Revealed connections between lipid remodeling and chemokine signaling through key metabolic stress genes.

Abstract

Abstract Introduction: Tumor-associated neutrophils (TANs) in glioblastoma (GBM) are heterogeneous and poorly captured by the classical N1/N2 dichotomy. We characterized TAN states relative to peripheral blood neutrophils (PBNs) and wondered if a discrete, targetable program drives their pro-tumoral phenotype. Methods: Public scRNA-seq datasets were reanalyzed (GSM8380727, GSM8380728: TANs 15,000 cells; PBNs 10,000 cells; 36,601 genes). Standard Seurat workflow was applied (stringent QC; SCTransform; integration; PCA/UMAP; shared-nearest-neighbor clustering). Differential expression used Wilcoxon rank-sum with Bonferroni FDR (adj. p0.05, |log2FC|0.25). Module scoring examined prespecified programs: antigen presentation/co-stimulation, interferon/cytotoxicity, lipid/stress adaptation. Functional enrichment and protein-protein networks were assessed via GSEA and STRING. Results: Integration revealed six tumor-associated Neutrophil states beyond the classical N1/N2 paradigm. Among them, an SPP1+(osteopontin-high) (avg log2FC ∼10.7; adj. p≈0) population was particularly transcriptionally associated with lipid processing genes (APOE, APOC1, APOC2) and chemokine master regulators (CCL3, CCL4) of immune cell recruitment and metabolic reprogramming. SPP1+ TANs featured repression of cytotoxicity pathways and induction of oxidative and lipid metabolism modules, pointing toward a shift from antimicrobial to tissue-remodeling and tumor-supporting activities. Network analysis revealed two large hubs: SPP1-APOE/APOC (lipid remodeling) and CCL3/CCL4 (immune signaling) that are bridged by metabolic stress genes (CTSB, EIF1B) into a cohesive immunometabolic circuit. Conclusion: Single-cell analysis characterizes GBM TAN heterogeneity and implicates an SPP1-centered, APC-like neutrophil axis bridging lipid regulation (APOE/APOCs) and chemokine signaling (CCL3/CCL4). This osteopontin-driven axis establishes a mechanistic basis for TAN-mediated tumor support and nominates SPP1 and its lipid-chemokine network as actionable targets to reprogram TANs for anti-tumor activity.This is among the first studies to define an osteopontin-driven immunometabolic axis in pro-tumoral neutrophils, establishing a mechanistic framework for future neutrophil-targeted immunotherapies in glioblastoma. Citation Format: Matthew Alexander Abikenari, John Hyunkuk Choi, Ravi Medikonda, Lily Kim, Rohit Verma, Justin Liu, Adam Sjoholm, George Nageeb, Brandon Hwa-Lin Bergsneider, Caren Yu-Ju Wu, Kwang Bog Cho, Andrew Tran, David Bakalov, Matei Banu, Michael Lim. SPP1-driven immunometabolic reprogramming of tumor-associated neutrophils in glioblastoma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3879.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Abikenari et al. (2026) studied this question.

synapsesocial.com/papers/69d1fdf7a79560c99a0a46a9https://doi.org/10.1158/1538-7445.am2026-3879
Ask AI
Helpful
Bookmark
Share
View Full Paper