High-risk early-stage lung adenocarcinoma patients are identified by an immune-related circadian clock gene signature

BACKGROUND: Twenty-four-hour oscillations of circadian rhythms control comprehensive biological processes in the human body. In lung adenocarcinoma (LUAD), chronic circadian rhythm disruption is positively associated with tumorigenesis. However, few studies focus on circadian clock gene signatures (CGSs) for prognosis evaluation of patients with early-stage LUAD. METHODS: In this study, we aimed to construct a robust prognostic circadian rhythm-related biomarker from multiple public databases, including the Gene Expression Omnibus database and The Cancer Genome Atlas database. The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression model was performed to select optimal circadian clock gene pairs. Bioinformatic analyses were performed to estimate the abundance of different immune cells and immunohistochemical analyses were conducted to validate the differential proportion of tumor-infiltrating lymphocytes in different groups. RESULTS: Results demonstrated that the CGS could accurately identify patients with early-stage LUAD at a high risk in the training dataset [hazard ratio (HR) =3.06; 95% confidence interval (CI): 2.47–3.78; P<0.001], testing dataset (HR =2.44; 95% CI: 1.74–3.43; P<0.001), and validation dataset (HR =2.09, 95% CI: 1.09–4.00; P=0.023). Bioinformatic and immunohistochemical analyses demonstrated that the abundance of tumor-infiltrating CD4(+) T cells was higher in the low-CGS groups. Integration of the CGS and clinical characteristics improved the accuracy of the CGS in predicting overall survival (OS) of patients with early-stage LUAD. CONCLUSIONS: In conclusion, the CGS was an independent immune-related circadian biomarker that could identify early-stage LUAD patients with different OS.