Abstract
Objective: Lung cancer is the most prevalent cancer in the world, and lung adenocarcinoma is the most common lung cancer subtype. Identification and determination of relevant prognostic markers are the key steps to personalized cancer management.
Methods: We collected the gene expression profiles from 265 tumor tissues of stage I patients from The Cancer Genome Atlas (TCGA) databases. Using Cox regression model, we evaluated the association between gene expression and the overall survival time of patients adjusting for gender and age at initial pathologic diagnosis.
Results: Age at initial pathologic diagnosis was identified to be associated with the survival, while gender was not. We identified that 15 genes were significantly associated with overall survival time of patients (FDR < 0.1). The 15-mRNA signature- based risk score was helpful to distinguish patients of high-risk group from patients of low-risk group.
Conclusion: Our findings reveal novel genes associated with lung adenocarcinoma survival and extend our understanding of how gene expression contributes to lung adenocarcinoma survival. These results are helpful for the prediction of the prognosis and personalized cancer management.
Keywords: Lung adenocarcinoma, gene, prognosis, cancer management, lung cancer, markers.
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