{
  "abstract": "ObjectiveTo define clinically relevant glioma ecosystem states (recurrent spatial configurations of malignant programs and microenvironmental niches) and identify immune-niche-dependent therapeutic vulnerabilities using single-nucleus, spatial, tissue, and machine-learning analyses.MethodsPublic multi-omics datasets were integrated with institutional single-nucleus RNA sequencing from 12 tumors, spatial transcriptomics from 6 IDH-wildtype glioblastomas, multiplex immunofluorescence in 138 FFPE cases, and glioma–macrophage co-culture assays.ResultsThree ecosystem states were identified. The hypoxic myeloid-mesenchymal state showed the highest MES-like, hypoxia, SPP1/APOE myeloid, and temozolomide-resistance scores, the lowest CD8+ T-cell density, and the shortest tumor–myeloid distance. In 96 IDH-wildtype glioblastomas, this state independently predicted shorter progression-free survival (HR 2.19, 95% CI 1.22–3.92) and overall survival (HR 2.07, 95% CI 1.12–3.81) after adjustment for major clinical and molecular covariates. Defactinib plus temozolomide reduced viability, colony formation, and migration by 56.0%, 61.3%, and 57.8%, respectively, under macrophage-conditioned culture.ConclusionSpatially organized tumor–immune ecosystems provide prognostic information and highlight potentially actionable SPP1–CD44/FAK–SRC signaling in glioblastoma as a candidate target for individualized therapeutic stratification approaches.",
  "abstract_shown": true,
  "affiliations": [
    "Senior Department of Neurosurgery, The First Medical Center of PLA General Hospital, Beijing, China",
    "Department of Neurosurgery, The Third Medical Center of Chinese PLA General Hospital, Beijing, China",
    "School of Science and Technology, Hong Kong Metropolitan University, Kowloon, China",
    "Department of Critical Care Medicine, The Third Medical Center of Chinese PLA General Hospital, Beijing, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zhizhen Qin"
    },
    {
      "affs": [
        1
      ],
      "name": "Zhizhen Qin"
    },
    {
      "affs": [
        0
      ],
      "name": "Yibo Zhang"
    },
    {
      "affs": [
        2
      ],
      "name": "Bo Wen"
    },
    {
      "affs": [
        0
      ],
      "name": "Jiaxin Li"
    },
    {
      "affs": [
        3
      ],
      "name": "Zhenzhen Chen"
    },
    {
      "affs": [
        0
      ],
      "name": "Xin Li"
    },
    {
      "affs": [
        1
      ],
      "name": "Xin Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Dongsheng Kong"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7jf5n77phw27v.bib",
  "cited_by": 0,
  "doi": "10.3389/fcell.2026.1943227",
  "fulltext_url": "https://www.frontiersin.org/articles/10.3389/fcell.2026.1943227/full",
  "id": "7jf5n77phw27v",
  "issns": [
    "2296-634X"
  ],
  "landing_url": "https://doi.org/10.3389/fcell.2026.1943227",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "QH301-705.5"
    ],
    [
      "openalex",
      "2716|Glioma Diagnosis and Treatment"
    ]
  ],
  "openalex": "W7223367660",
  "pdf_url": "https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2026.1943227/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-23",
  "publisher": "Frontiers Media S.A.",
  "ris": "https://research.draconitic.com/paper/7jf5n77phw27v.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:43:48Z",
      "native_id": "e41b073f176143508306aa2f150c392f",
      "source": "doaj",
      "url": "https://doi.org/10.3389/fcell.2026.1943227"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2716|Glioma Diagnosis and Treatment",
      "subfield": "human-genetics"
    }
  ],
  "title": "Defining glioma ecosystem states with AI-driven single-cell and spatial multi-omics: immune-niche reprogramming and therapeutic vulnerabilities",
  "title_text": "Defining glioma ecosystem states with AI-driven single-cell and spatial multi-omics: immune-niche reprogramming and therapeutic vulnerabilities",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:43:48Z",
  "url": "https://research.draconitic.com/paper/7jf5n77phw27v",
  "venue": "Frontiers in Cell and Developmental Biology",
  "versions": []
}