Development and validation of a novel mRNA signature for predicting early relapse in non-small cell lung cancer

Autor: Jingping Lin, Jieping Huang, Cuibo Lin, Jinsen Weng, Shaofeng Lin, Shen Zhang, Haizhou Ji, Chunxia Zhang, Xi Ke, Chuanpeng Dong
Rok vydání: 2021
Předmět:
Zdroj: Japanese Journal of Clinical Oncology. 51:1277-1286
ISSN: 1465-3621
Popis: Background Recurrence after initial primary resection is still a major and ultimate cause of death for non-small cell lung cancer patients. We attempted to build an early recurrence associated gene signature to improve prognostic prediction of non-small cell lung cancer. Methods Propensity score matching was conducted between patients in early relapse group and long-term survival group from The Cancer Genome Atlas training series (N = 579) and patients were matched 1:1. Global transcriptome analysis was then performed between the paired groups to identify tumour-specific mRNAs. Finally, using LASSO Cox regression model, we built a multi-gene early relapse classifier incorporating 40 mRNAs. The prognostic and predictive accuracy of the signature was internally validated in The Cancer Genome Atlas patients. Results A total of 40 mRNAs were finally identified to build an early relapse classifier. With specific risk score formula, patients were classified into a high-risk group and a low-risk group. Relapse-free survival was significantly different between the two groups in both discovery (HR: 3.244, 95% CI: 2.338-4.500, P Conclusions We successfully established a reliable signature for predicting early relapse in stage I–III non-small cell lung cancer.
Databáze: OpenAIRE