Identification of CRF-related molecular subtypes and a prognostic CRRS model in glioma: insights into immunotherapy response prediction and candidate biomarkers
Year: 2026
Type: article
Abstract: Background Cancer-related fatigue (CRF) is a common symptom in glioma patients, significantly affecting their quality of life. The underlying mechanisms of fatigue in these patients are not fully understood. Methods Using CRF-associated genes (CAGs), we identified two CRF-related subtypes in glioma patients. We evaluated differences in clinicopathological features, immune characteristics, and prognostic stratification between these subtypes. A CRF-associated risk score (CRRS) model was developed using LASSO Cox regression analysis. Its predictive performance in immunotherapy was validated using multiple datasets. A nomogram was created to facilitate clinical use. Expression assessment of CAGs was conducted utilizing tissue microarray (TMA) and single-cell sequencing data. Potential small-molecule compounds for treating glioma and its associated fatigue were screened through molecular docking (MD) and molecular dynamics simulation (MDS) analysis and subsequently validated by in vitro experiments. Results We identified two CRF-related clusters and constructed a CRRS model based on 10 key CAGs. CRRS was significantly associated with age, WHO grade, IDH mutation status, and 1p/19q codeletion status. High-risk and low-risk groups differed in prognosis, immune cell infiltration, expression of immune checkpoint inhibitors, major histocompatibility complex and T-cell stimulators, immunotherapy response, and drug sensitivity. TMA analysis revealed upregulated expression of IRF7 in glioma. MD, MDS, and in vitro drug experiments have identified two potential compounds for glioma treatment: Docetaxel and SNX-2112. Conclusion CRRS represents a reliable prognostic marker for glioma, demonstrating a relation with the manifestation of CRF symptoms in patients. IRF7 serves as a biomarker for glioma. Docetaxel and SNX-2112 show promise as effective treatments for glioma and its associated fatigue symptoms.
Source: Scientific Reports
Authors: Jihao Xue, Jianguo Xu, Qijia Yin, Ming Wang
Language: English
Subfield: Genetics (clinical)
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: Southwest Medical University
OpenAlex ID: W7205015482
