Research Paper Volume 13, Issue 6 pp 8706—8719
Predicting lung adenocarcinoma prognosis with a novel risk scoring based on platelet-related gene expression
- 1 Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
- 2 Department of Pathology, School of Basic Medical Sciences & Key Laboratory of Antibody Technique of National Health Commission & Jiangsu Antibody Drug Engineering Research Center, Nanjing Medical University, Nanjing 211166, China
- 3 Department of Respiratory Medicine, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China
- 4 Jiangsu Cancer Hospital, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Institute of Cancer Research, Nanjing 210009, China
- 5 School of Medicine, Southeast University, Nanjing 210009, China
- 6 Sir Run Run Hospital, Nanjing Medical University, Nanjing 211166, China
Received: May 6, 2020 Accepted: February 1, 2021 Published: February 22, 2021
https://doi.org/10.18632/aging.202682How to Cite
Copyright: © 2021 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Lung adenocarcinoma is the most common subtype of non-small cell lung cancer, and platelet receptor-related genes are related to its occurrence and progression. A new prognostic indicator based on platelet receptor-related genes was developed with multivariate COX analysis. Prognostic markers based on platelet-related risk score perform moderately in prognosis prediction. The functional annotation of this risk model in high-risk patients shows that the pathways related to cell cycle, glycolysis and platelet-derived related factors are rich. It is worth noting that somatic mutation analysis shows that TTN and MUC16 have higher mutation burdens in high-risk patients. Moreover, the differential genes of high- and low-risk groups are regulated by copy number variation and miRNA. And we provide a free online nomogram web tool based on clinical factors and the risk score (