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Open Access Green as soon as Postprint is submitted to ZB.
Neuro-immuno-stromal context in colorectal cancer: An enteric glial cell-driven prognostic model via machine learning predicts survival, recurrence, and therapy response.
Exp. Cell Res. 452:114733 (2025)
BACKGROUND: Enteric glial cells (EGCs) have been implicated in colorectal cancer (CRC) progression. This study aimed to develop and validate a prognostic model integrating EGC- and CRC-associated gene expression to predict patient survival, recurrence, metastasis, and therapy response. METHODS: Bulk and single-cell RNA sequencing data were analyzed, and a machine learning-based model was constructed using the RSF random forest algorithm. The model's prognostic value was evaluated through survival analysis, pathway enrichment, immune profiling, and therapy response predictions. RESULTS: The model effectively stratified patients into high- and low-risk groups, with high-risk patients exhibiting significantly worse overall survival (OS) and an increased likelihood of recurrence and metastasis. Gene Set Enrichment Analysis (GSEA) identified key pathways associated with tumor progression, immune regulation, and microenvironmental interactions. The model was significantly correlated with immune cell infiltration and chemokine signaling. High-risk patients exhibited reduced immune therapy efficacy and distinct drug sensitivity profiles, suggesting its potential to guide personalized treatment strategies. CONCLUSION: This model serves as a valuable tool for CRC prognosis and treatment stratification, with potential clinical applications pending further validation.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Colorectal Cancer ; Enteric Glial Cells ; Neurogastroenterology; Nervous-system; Map1b
ISSN (print) / ISBN
1090-2422
e-ISSN
0014-4827
Journal
Experimental Cell Research
Quellenangaben
Volume: 452,
Issue: 1,
Article Number: 114733
Publisher
Academic Press
Publishing Place
Orlando, Fla.
Reviewing status
Peer reviewed
Institute(s)
Institute of Diabetes and Cancer (IDC)
Grants
Science Foundation of Peking University Cancer Hospital
National Natural Science Foundation of China
Boxi Youth Natural Science Foundation
Young Elite Scientists Sponsorship Program by CAST
National Natural Science Foundation of China
Boxi Youth Natural Science Foundation
Young Elite Scientists Sponsorship Program by CAST