Circadian Clock Genes Act as Diagnostic and Prognostic Biomarkers of Glioma: Clinic Implications for Chronotherapy

Author:

Chai Ruihuan1ORCID,Liao Min1ORCID,Ou Ling23ORCID,Tang Qian4ORCID,Liang Youfang1ORCID,Li Nan1ORCID,Huang Wei23ORCID,Wang Xiao5ORCID,Zheng Kai1ORCID,Wang Shaoxiang1ORCID

Affiliation:

1. School of Pharmaceutical Sciences, Shenzhen University Health Science Center, Shenzhen 518000, China

2. Bacteriology & Antibacterial Resistance Surveillance Laboratory, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, Shenzhen 518020, China

3. The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen 518020, China

4. School of Pharmacy, Jinan University, Guangzhou 510630, China

5. Department of Pharmacy, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, Shenzhen 518020, China

Abstract

Gliomas are the most common primary intracranial tumors and closely related to circadian clock. Due to the high mortality and morbidity of gliomas, exploring novel diagnostic and early prognostic markers is necessary. Circadian clock genes (CCGs) play important roles in regulating the daily oscillation of biological processes and the development of tumor. Therefore, we explored the influences that the oscillations of circadian clock genes (CCGs) on diagnosis and prognosis of gliomas using bioinformatics. In this work, we systematically analyzed the rhythmic expression of CCGs in brain and found that some CCGs had strong rhythmic expression; the expression levels were significantly different between day and night. Four CCGs (ARNTL, NPAS2, CRY2, and DBP) with rhythmic expression were not only identified as differentially expressed genes but also had significant independent prognostic ability in the overall survival of glioma patients and were highly correlated with glioma prognosis in COX analysis. Besides, we found that CCG-based predictive model demonstrated higher predictive accuracy than that of the traditional grade-based model; this new prediction model can greatly improve the accuracy of glioma prognosis. Importantly, based on the four CCGs’ circadian oscillations, we revealed that patients sampled at night had higher predictive ability. This may help detect glioma as early as possible, leading to early cancer intervention. In addition, we explored the mechanism of CCGs affecting the prognosis of glioma. CCGs regulated the cell cycle, DNA damage, Wnt, mTOR, and MAPK signaling pathways. In addition, it also affects prognosis through gene coexpression and immune infiltration. Importantly, ARNTL can rhythmically modulated the cellular sensitivity to clinic drugs, temozolomide. The optimal point of temozolomide administration should be when ARNTL expression is highest, that is, the effect is better at night. In summary, our study provided a basis for optimizing clinical dosing regimens and chronotherapy for glioma. The four key CCGs can serve as potential diagnostic and prognostic biomarkers for glioma patients, and ARNTL also has obvious advantages in the direction of glioma chronotherapy.

Funder

SZU Medical Young Scientists Program

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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