Affiliations: [a] Department of Thoracic Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China | [b] Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201112, China
Correspondence:
[*]
Corresponding author: Chunxiao Wu, Department of Thoracic Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, South Wanping Road 725, Shanghai, 20032, China. E-mail:[email protected]
Note: [1] The authors contributed equally.
Abstract: BACKGROUND: Current staging methods are lack of precision in
predicting prognosis of early-stage lung adenocarcinomas. OBJECTIVE: We aimed to develop a gene expression signature to
identify high- and low-risk groups of patients. METHODS: We used the Bayesian Model Averaging algorithm to analyze
the DNA microarray data from 442 lung adenocarcinoma patients from three
independent cohorts, one of which was used for training. RESULTS: The patients were assigned to either high- or low-risk
groups based on the calculated risk scores based on the identified 25-gene
signature. The prognostic power was evaluated using Kaplan-Meier analysis
and the log-rank test. The testing sets were divided into two distinct
groups with log-rank test p-values of 0.00601 and 0.0274 respectively. CONCLUSIONS: Our results show that the prognostic models could
successfully predict patients' outcome and serve as biomarkers for
early-stage lung adenocarcinoma overall survival analysis.
Keywords: Lung adenocarcinoma, prognosis, gene expression, Bayesian Model Averaging
