Cancer-myeloid cell invasive program in pediatric-type diffuse high-grade glioma

2026/01/25 by Cristian Ruiz Moreno, Raphaël Collot, Thijs J M van den Broek +16 · 1 voice
Medicine · Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · #Glioma Diagnosis and Treatment #Single-cell and spatial transcriptomics #Immune cells in cancer

paper · doi:10.64898/2026.01.23.701142

openalex publication_date 2026/01/25 · openalex created_date 2026/01/26 · openalex updated_date 2026/07/22

Abstract

SUMMARY Pediatric-type diffuse high-grade gliomas (pHGGs) are aggressive, heterogeneous brain tumors shaped by intricate cancer-microenvironment cell-cell interactions. Here, we present an integrative multimodal pHGGmap, encompassing over 800,000 cells from 136 patients profiled across transcriptomic, epigenomic, and spatial modalities. Its analysis delineated robust cancer-myeloid cell programs that structured the tumor ecosystem and identified ten distinct cancer cell states, including previously unrecognized developmental and context-responsive programs. Among these, radial glial-like (RG-like) cells exhibited dual stress-adapted and infiltrative phenotypes. Tumor-associated monocyte-derived macrophages and resident microglia engaged in four distinct immunomodulatory programs aligned with specific cancer states. Three conserved multicellular communities were maintained across treatment, including a stable, spatially and transcriptionally linked RG-like/complement-macrophage niche, indicative of cellular co-option and adaptation to support invasion. Longitudinal profiling of a metastatic diffuse midline glioma case showed that RG-like cells predominate during dissemination and remain associated with complement-enriched macrophages, whose reprogramming restores immune activation. pHGGmap establishes a landmark resource for translational discovery. Graphical abstract

Citations

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Discussions

• I’m excited to finally share our research on pediatric high-grade gliomas (pHGG), the result of years of effort integrating single-cell and spatial datasets to offer a fresh perspective on their organ [bsky, 3 points, 1 comments]

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