Identification and Validation of a Novel Six-lncRNA-Based Prognostic Model for Lung Adenocarcinoma - Yang, Lingge; Wu, Yuan; Xu, Huan; Zhang, Jingnan; Zheng, Xinjie; Zhang, Long; Wang, Yongfang; Chen, Weiyu; Wang, Kai (Frontiers in Oncology, 2022)
Objective: To establish a lncRNAs based model for predicting overall survival (OS) in patients with lung adenocarcinoma (LUAD). Methods: Original RNA-seq data of LUAD samples was extracted from The Cancer Genome Atlas (TCGA) database. Univariate Cox survival analysis was performed to select lncRNAs associated with OS. The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox analysis were performed for building OS-associated lncRNA prognostic model. Moreover, receiver operating characteristic (ROC) curves were generated to assess predictive values of the hub lncRNAs. Consequently, qRT PCR was conducted to validate its prognostic value. The potential roles of these lncRNAs in immunotherapy and anti-angiogenic therapy were also investigated. Results: lncRNA-associated risk score of OS (LARSO) was established based on the LASSO coefficient of six individual lncRNA, including CTD-2124B20.2, CTD-2168K21.1, DEPDC1-AS1, RP1-290I10.3, RP11-454K7.3, and RP11-95M5.1. Kaplan-Meier analysis revealed that LUAD patients with higher LARSO values had a shorter OS. Furthermore, a new risk score (NRS), including LARSO, stage, and N stage, could better predict the prognosis of LUAD patients compared to LARSO alone. Evaluation of the prognostic model in our cohort demonstrated that patients with higher scores had a worse prognosis. In addition, correlation analysis between these six lncRNAs and immune checkpoints or anti-angiogenic targets suggested that LUAD patients with high LARSO might not be sensitive to immunotherapy or anti-angiogenic therapy. Conclusions: This robust six-lncRNA prognostic signature may be used as a novel and powerful prognostic biomarker for lung adenocarcinoma.