Identifying Common Genes Related to Platelet and Immunity for Lung Adenocarcinoma Prognosis Prediction

  • Chengmao Zhou
  • , Ying Wang
  • , Lei Lei
  • , Mu Huo Ji
  • , Jian Jun Yang
  • , Hongping Xia

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Background: Although 1000s 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 the Cancer Genome Atlas Dataset (TCGA), and GSE68465 or GSE14814 data sets from the Gene Expression Omnibus (GEO) database. Results: The high-risk group’s overall survival (OS) 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.1 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 seven 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 lung adenocarcinoma (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.

Original languageEnglish
Article number563142
JournalFrontiers in Molecular Biosciences
Volume7
DOIs
StatePublished - 29 Oct 2020

Keywords

  • immune
  • lung adenocarcinoma
  • nomogram
  • platelet
  • TCGA

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