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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Genetics
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1477617
This article is part of the Research Topic Genomics and Epigenomics of Cancer Immunotherapy: Challenges and Clinical Implications View all 22 articles
Multi-Omics Approach Reveals the Impact of Prognosis Model-Related Genes on the Tumor Microenvironment in Medulloblastoma
Provisionally accepted- 1 College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- 2 BGI Research, Shenzhen 518083, China
- 3 College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- 4 Department of Neurosurgery, Beijing TianTan Hospital, Capital Medical University, Beijing 100050, China
- 5 Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
The tumor microenvironment (TME) significantly impacts the progression and prognosis of medulloblastoma (MB). This study aimed to develop a TME-associated risk score(TMErisk) model using RNA sequencing data to predict patient outcomes and elucidate biological mechanisms.Methods: RNA sequencing data from 322 Tiantan and 763 GSE85217 MB samples were analyzed. Key gene modules related to immune and stromal components were identified using Weighted Gene Co-expression Network Analysis (WGCNA). Significant genes were screened using LASSO-COX and COX regression models. Single-cell RNA sequencing (scRNA-seq), single-cell ATAC sequencing (scATAC-seq), and spatial RNA analyses validated the findings.Results: Differential expression analysis identified 731 upregulated and 15 downregulated genes in high vs. low immune score MB patients, and 686 upregulated and 43 downregulated genes in high vs. low stromal score patients. Eight key genes (CEBPB, OLFML2B, GGTA1, GZMA, TCIM, OLFML3, NAT1, and CD1C) were included in the TMErisk model, which demonstrated strong prognostic power.High TMErisk scores correlated with poorer survival, distinct immune cell infiltration patterns, and lower tumor cell stemness. Single-cell analyses revealed the expression dynamics of TMErisk genes across cell types, including macrophages, T cells, and NK cells, and identified key regulatory transcription factors. Spatial transcriptomics showed significant clustering of TMErisk genes in tumor regions, highlighting spatial heterogeneity and the formation of immune hubs.The TMErisk model enhances our understanding of the MB tumor microenvironment, serving as a robust prognostic tool and suggesting new avenues for targeted therapy.
Keywords: Tumor microenvironment (TME), Medulloblastoma (MB), TMErisk Model, single-cell RNA sequencing (scRNA-seq), Spatial transcriptomics
Received: 08 Aug 2024; Accepted: 28 Jan 2025.
Copyright: © 2025 Han, Xuan, Wang, Jin, Li and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Dongming Han, College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Tao Jiang, Department of Neurosurgery, Beijing TianTan Hospital, Capital Medical University, Beijing 100050, China
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