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Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.
- Source :
-
CNS neuroscience & therapeutics [CNS Neurosci Ther] 2024 Jul; Vol. 30 (7), pp. e14816. - Publication Year :
- 2024
-
Abstract
- Aim: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas.<br />Methods: Based on the unsupervised clustering algorithm, we identified novel TRP channel clusters and investigated their biological function, immune microenvironment, and genomic heterogeneity. In vitro and in vivo experiments revealed the association between TRPV2 and macrophages. Subsequently, based on 96 machine learning algorithms and six independent glioma cohorts, we constructed a machine learning-based TRP channel signature (MLTS). The performance of the MLTS in predicting prognosis, immunotherapy response, and drug sensitivity was evaluated.<br />Results: Patients with high expression levels of TRP channel genes had worse prognoses, higher tumor mutation burden, and more activated immunosuppressive microenvironment. Meanwhile, TRPV2 was identified as the most essential regulator in TRP channels. TRPV2 activation could promote macrophages migration toward malignant cells and alleviate glioma prognosis. Furthermore, MLTS could work independently of common clinical features and present stable and superior prediction performance.<br />Conclusion: This study investigated the comprehensive effect of TRP channel genes in gliomas and provided a promising tool for designing effective, precise treatment strategies.<br /> (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)
- Subjects :
- Humans
Animals
TRPV Cation Channels genetics
TRPV Cation Channels metabolism
Mice
Male
Female
Glioma genetics
Glioma immunology
Machine Learning
Tumor Microenvironment physiology
Brain Neoplasms genetics
Brain Neoplasms immunology
Transient Receptor Potential Channels genetics
Transient Receptor Potential Channels metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 1755-5949
- Volume :
- 30
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- CNS neuroscience & therapeutics
- Publication Type :
- Academic Journal
- Accession number :
- 38948951
- Full Text :
- https://doi.org/10.1111/cns.14816