Zeyu Wang1, Guanhua Su1,2, Ziyu Dai1, Ming Meng1, Hao Zhang1, Fan Fan1, Zhengzheng Liu3, Longbo Zhang1,4, Nathaniel Weygant5,6, Fengqiong He1,7, Ning Fang8, Liyang Zhang1,7,9, Quan Cheng1,7,9,10. 1. Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. 2. Clinic Medicine of 5-year Program, Xiangya School of Medicine, Central South University, Changsha, China. 3. Department of Oncology, Xiangya Hospital, Central South University, Changsha, China. 4. Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA. 5. Academy of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China. 6. Fujian Key Laboratory of Integrative Medicine in Geriatrics, Fujian University of Traditional Chinese Medicine, Fujian, China. 7. Clinical Diagnosis and Therapy Center for Glioma of Xiangya Hospital, Central South University, Changsha, China. 8. Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China. 9. National Clinical Research Center for Geriatric Disorders, Changsha, China. 10. Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China.
Abstract
OBJECTIVES: Circadian rhythm controls complicated physiological activities in organisms. Circadian clock genes have been related to tumour progression, but its role in glioma is unknown. Therefore, we explored the relationship between dysregulated circadian clock genes and glioma progression. MATERIALS AND METHODS: Samples were divided into different groups based on circadian clock gene expression in training dataset (n = 672) and we verified the results in other four validating datasets (n = 1570). The GO and GSEA enrichment analysis were conducted to explore potential mechanism of how circadian clock genes affected glioma progression. The single-cell RNA-Seq analysis was conducted to verified previous results. The immune landscape was evaluated by the ssGSEA and CIBERSORT algorithm. Cell proliferation and viability were confirmed by the CCK8 assay, colony-forming assay and flow cytometry. RESULTS: The cluster and risk model based on circadian clock gene expression can predict survival outcome. Samples were scoring by the least absolute shrinkage and selection operator regression analysis, and high scoring tumour was associated with worse survival outcome. Samples in high-risk group manifested higher activation of immune pathway and cell cycle. Tumour immune landscape suggested high-risk tumour infiltrated more immunocytes and more sensitivity to immunotherapy. Interfering TIMELESS expression affected circadian clock gene expression, inhibited tumour cell proliferation and arrested cell cycle at the G0/G1 phase. CONCLUSIONS: Dysregulated circadian clock gene expression can affect glioma progression by affecting tumour immune landscape and cell cycle. The risk model can predict glioma survival outcome, and this model can also be applied to pan-cancer.
OBJECTIVES: Circadian rhythm controls complicated physiological activities in organisms. Circadian clock genes have been related to tumour progression, but its role in glioma is unknown. Therefore, we explored the relationship between dysregulated circadian clock genes and glioma progression. MATERIALS AND METHODS: Samples were divided into different groups based on circadian clock gene expression in training dataset (n = 672) and we verified the results in other four validating datasets (n = 1570). The GO and GSEA enrichment analysis were conducted to explore potential mechanism of how circadian clock genes affected glioma progression. The single-cell RNA-Seq analysis was conducted to verified previous results. The immune landscape was evaluated by the ssGSEA and CIBERSORT algorithm. Cell proliferation and viability were confirmed by the CCK8 assay, colony-forming assay and flow cytometry. RESULTS: The cluster and risk model based on circadian clock gene expression can predict survival outcome. Samples were scoring by the least absolute shrinkage and selection operator regression analysis, and high scoring tumour was associated with worse survival outcome. Samples in high-risk group manifested higher activation of immune pathway and cell cycle. Tumour immune landscape suggested high-risk tumour infiltrated more immunocytes and more sensitivity to immunotherapy. Interfering TIMELESS expression affected circadian clock gene expression, inhibited tumour cell proliferation and arrested cell cycle at the G0/G1 phase. CONCLUSIONS: Dysregulated circadian clock gene expression can affect glioma progression by affecting tumour immune landscape and cell cycle. The risk model can predict glioma survival outcome, and this model can also be applied to pan-cancer.
Authors: Ruihuan Chai; Min Liao; Ling Ou; Qian Tang; Youfang Liang; Nan Li; Wei Huang; Xiao Wang; Kai Zheng; Shaoxiang Wang Journal: Biomed Res Int Date: 2022-07-04 Impact factor: 3.246
Authors: Wenjing Xuan; Fatima Khan; Charles David James; Amy B Heimberger; Maciej S Lesniak; Peiwen Chen Journal: Trends Cell Biol Date: 2021-07-13 Impact factor: 20.808