Identification of a Prognostic Signature Composed of GPI, IL22RA1, CCT6A and SPOCK1 for Lung Adenocarcinoma Based on Bioinformatic Analysis of lncRNA-Mediated ceRNA Network and Sample Validation.

Abstract

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high morbidity and mortality in China and worldwide. Long non-coding RNAs (lncRNAs) as the competing endogenous RNA (ceRNA) play an essential role in the occurrence and development of LUAD. However, identifying lncRNA-related biomarkers to improve the accuracy of LUAD prognosis remains to be determined. This study downloaded RNA sequence data from The Cancer Genome Atlas (TCGA) database and identified the differential RNAs by bioinformatics. A total of 214 lncRNA, 198 miRNA and 2989 mRNA were differentially identified between LUAD and adjacent nontumor samples. According to the ceRNA hypothesis, we constructed a lncRNA-miRNA-mRNA network including 95 protein-coding mRNAs, 7 lncRNAs and 15 miRNAs, and found 24 node genes in this network were significantly associated with the overall survival of LUAD patients. Subsequently, through LASSO regression and multivariate Cox regression analyses, a four-gene prognostic signature composed of GPI, IL22RA1, CCT6A and SPOCK1 was developed based on the node genes of the lncRNA-mediated ceRNA network, demonstrating high performance in predicting the survival and chemotherapeutic responses of low- and high-risk LUAD patients. Finally, independent prognostic factors were further analyzed and combined into a well-executed nomogram that showed strong potential for clinical applications. In summary, the data from the current study suggested that the four-gene signature obtained from analysis of lncRNA-mediated ceRNA could serve as a reliable biomarker for LUAD prognosis and evaluation of chemotherapeutic response.