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.
Methods
Samples were divided into different groups based on circadian clock gene expression in training dataset (n = 672) and we verified the
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.