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

Abstract

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 < 0.001) and internal validation series (HR 1.970, 95% CI 1.181-3.289, P = 0.009). Further analysis revealed that the prognostic value of this signature was independent of tumour stage, histotype and epidermal growth factor receptor mutation (P < 0.05). Time-dependent receiver operating characteristic analysis showed that the area under receiver operating characteristic curve of this signature was higher than TNM stage alone (0.771 vs 0.686, P < 0.05). Further, decision curve analysis curves analysis at 1 year revealed the considerable clinical utility of this signature in predicting early relapse. Conclusions We successfully established a reliable signature for predicting early relapse in stage I–III non-small cell lung cancer.

Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity

“…Chiba et al found that CLEC7A could promote natural killer cells to secrete cytotoxic factors and thus fight lung cancer through cell-to-cell contact ( Chiba et al, 2014 ). In this study, CLEC7A had a positive effect on the prognosis of LUAD patients, which was consistent with the findings of previous studies ( Zou et al, 2020 ; Zhou et al, 2021b ; Lin et al, 2021 ).…”