Identifying Common Genes Related to Platelet and Immunity for Lung Adenocarcinoma Prognosis Prediction - Zhou, Chengmao; Wang, Ying; Lei, Lei; Ji, Mu-Huo; Yang, Jian-Jun; Xia, Hongping (Frontiers in Molecular Biosciences, 2020)
Background: Although thousands of immune-related and platelet receptor-related genes have been identified in lung adenocarcinoma, their role in prognosis prediction remains unclear. Methods: We downloaded mRNA data from TCGA, and GSE68465 or GSE14814 datasets from the GEO database. Results: The high-risk group’s overall survival time was lower than that of the low-risk group’s in TCGA (P=1.15e−03). Additionally, the risk score was an independent prognostic survival factor for lung adenocarcinoma patients in TCGA (HR = 2.136，95％CI = 1.553−2.937，P<0.001). The model’s prognostic performance was verified with two independent GEO cohorts (GSE68465 and GSE14814). We also developed a nomogram and provided free webpage prediction tools (https://zcmnewnomogram.shinyapps.io/zcmnewRiskscore/). The mechanism of the high-risk group in this risk score may be have been related to somatic mutations and copy number changes. In addition, this risk score can distinguish the prognosis of the other two cancers (ACC, P<0.001 and KIRP, P<0.001). Also, among the other 7 cancers, the OS prognosis for high and low risk groups show wide variation (P<0.05). Conclusion: Our research demonstrates that CCNA2 and TGFB2 are potential diagnostic and prognostic biomarkers, as well as therapeutic targets in LUAD. We also determined a novel and reliable prognostic score for lung adenocarcinoma prognosis. The online nomogram prediction tool that contains this risk score may also help clinical medical staff.