Identification of 17 mRNAs and a miRNA as an integrated prognostic signature for lung squamous cell carcinoma

Background Gene signatures for predicting the outcome of lung squamous cell carcinoma (LUSC) have been employed for many years. However, various signatures have been applied in clinical practice. Therefore, in the present study, we aimed to filter out an effective LUSC prognostic gene signature by simultaneously integrating mRNA and microRNA (miRNA). Methods First, based on data from the Cancer Genome Atlas (TCGA) (https://www.cancer.gov/tcga), mRNAs and miRNAs that were related to overall survival of LUSC were obtained by the least absolute shrinkage and selection operator method. Subsequently, the predicting effect was tested by time-dependent receiver operating characteristic curve analysis and Kaplan-Meier survival analysis. Next, related clinical indices were added to evaluate the efficiency of the selected gene signatures. Finally, validation and comparison using three independent gene signatures were performed using data from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo). Results Our data showed that the prognostic index (PI) contained 17 mRNAs and one miRNA. According to the best normalized cut-off of PI (0.0247), the hazard ratio of the PI was 3.40 (95% confidence interval = 2.33-4.96). Moreover, when clinical factors were introduced, the PI was still the most significant index. In addition, only two Gene Ontology terms with p < 0.05 were reported. Furthermore, validation implied that, using our 18-gene signature, only hazard ratio = 1.36 (95% confidence interval = 1.01-1.83) was significant compared to the other three groups of gene biomarkers. Conclusions The 18-gene signature selected based on data from the TCGA database had an effective prognostic value for LUSC patients.