Background: Malignant behavior and radioresistance, which severely limits the efficacy of radiation therapy (RT) in nasopharyngeal carcinoma (NPC), are associated with tumor progression and poor prognosis. Mesenchymal stem cells (MSCs) are used as a therapeutic tool in a variety of tumors. The aim of this study was to reveal the effect of tumor suppressor microRNA-34c-5p (miR-34c) on NPC development and radioresistance, as well as to confirm that exosomes derived from MSCs overexpressing miR-34c restore the sensitivity to radiotherapy in NPCs. Methods: Potentially active microRNAs were screened by cell sequencing, Gene Expression Omnibus (GEO) database analysis, and analysis of clinical serum samples from 70 patients. The expression of genes and proteins was detected by Western blotting, quantitative reverse transcription PCR (qRT-PCR), and immunohistochemistry (IHC). Proliferation, apoptosis, invasion, migration and radioresistance of NPC were detected. Luciferase reporter assays were used to verify the interactions of microRNAs with their downstream targets. MSCs exosomes were isolated by ultrafiltration and verified by electron microscopy and nanoparticle tracking technology. Results: The expression of miR-34c was associated with the occurrence and radiation resistance of NPC. In vitro and in vivo experiments indicated that overexpression of miR-34c inhibit malignant behavior such as invasion, migration, proliferation and epithelial-mesenchymal transition (EMT) in NPCs by targeting β-Catenin. In addition, we found alleviated radioresistance upon miR-34c overexpression or β-catenin knockdown in NPCs. Exosomes derived from miR-34c-transfected MSCs attenuated NPC invasion, migration, proliferation and EMT. Moreover, miR-34c-overexpressing exosomes drastically increased radiation-induced apoptosis in NPC cells. Conclusion: miR-34c is a tumor suppressor miR in NPC, which inhibits malignant behavior as well as radioresistance of tumor. Therefore, exogenous delivery of miR-34c to NPCs via MSC exosomes inhibits tumor progression and increases the efficiency of RT. Combination IR with miR-34c-overexpressing exosomes may be effective treatment for radioresistant NPCs.

Increasing evidence highlights the role of aberrant circadian rhythm gene expression in glioblastoma (GBM) progression, but the impact of the circadian rhythm gene network on GBM molecular profiles and prognosis remains unclear. A total of 1042 GBM samples from six public datasets, TCGA and CGGA, were analyzed, with GBM samples stratified into three circadian core-gene patterns using unsupervised clustering based on the expression profiles of 17 circadian rhythm genes. The Limma R package identified differentially expressed genes (DEGs) among the three patterns, and a secondary clustering system, termed circadian-related gene pattern, was established based on DEGs. A circadian risk score was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, and the efficiency of these patterns and the circadian risk score in distinguishing molecular profiles and predicting prognosis was systematically analyzed. The relationship between the circadian risk score and response to immune or targeted therapy was examined using the GSE78200 and IMvigor210 datasets. The results showed that GBM patients were clustered into three circadian core-gene patterns based on the expression profiles of 17 core circadian genes, with distinct molecular profiles, malignant characteristics, and patient prognoses among the patterns. Thirty-two DEGs among these patterns were identified and termed circadian-related genes, and secondary clustering based on these 32 DEGs classified GBM samples into two circadian-related gene patterns, which also predicted molecular profiles and prognosis. A circadian risk scoring system was established, allowing the calculation of individual risk scores based on the expression of 10 genes, where GBM patients with lower circadian risk scores had prolonged overall survival and less aggressive molecular subtypes, while higher circadian risk scores correlated with better responses to MAPK-targeted therapy. In conclusion, this study established two clustering patterns based on 17 circadian rhythm genes or 32 circadian-related genes, enabling the rapid classification of GBM patients with distinct molecular profiles and prognoses, while the circadian risk scoring system effectively predicted survival, molecular profiles, and therapeutic responses for individual GBM patients, demonstrating that the circadian rhythm gene network can distinguish molecular profiles and prognosis in GBM.