Litcius/Paper detail

Identification and validation of an autophagy-related long non-coding RNA signature as a prognostic biomarker for patients with lung adenocarcinoma

Aimin Jiang, Na Liu, Shuheng Bai, Jingjing Wang, Huan Gao, Xiaoqiang Zheng, Xiao Fu, Mengdi Ren, Xiaoni Zhang, Tao Tian, Zhiping Ruan, Xuan Liang, Yu Yao

2021Journal of Thoracic Disease21 citationsDOIOpen Access PDF

Abstract

BACKGROUND: Lung adenocarcinoma (LUAD) is the most predominant pathological subtype of lung cancer, accounting for 40-70% of all lung cancer cases. Although significant improvements have been made in the screening, diagnosis, and precise management in recent years, the prognosis of LUAD remains bleak. This study aimed to investigate the prognostic significance of autophagy-related long non-coding RNAs (lncRNAs) and construct an autophagy-related lncRNA prognostic model in LUAD. METHODS: The gene expression data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) database. All autophagy-related genes were downloaded from the Human Autophagy Database (HADb). Spearman's correlation test was exploited to identify potential autophagy-related lncRNAs. The multivariate Cox regression analysis was used to construct the prognostic signature, which divided LUAD patients into high-risk and low-risk groups. Subsequently, the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of this prognostic model for overall survival (OS) in these individuals. Then, the Gene set enrichment analysis (GSEA) was conducted to execute pathway enrichment analysis. Finally, a multidimensional validation was exploited to verify our findings. RESULTS: | >0.4 and P≤0.001). Ultimately, a 16 autophagy-related lncRNAs prognostic model was constructed, and the area under the ROC curve (AUC) was 0.775. The results of GSEA enrichment analysis showed that the genes in the high-risk group were mainly enriched in cell cycle and p53 signaling pathways. The results of the multidimensional database validation indicated that the expression level of BIRC5 was significantly correlated with the expression level of TMPO-AS1. Furthermore, both TMPO-AS1 and BIRC5 had a higher expression level in LUAD samples. LUAD patients with high expression levels of TMPO-AS1 and BIRC5 were correlated with advanced disease stage and poor OS. CONCLUSIONS: In summary, our results suggested that the prognostic signature of the 16 autophagy-related lncRNAs has significant prognostic value for LUAD patients. Furthermore, TMPO-AS1 and BIRC5 are potential predictors and therapeutic targets in these individuals.

Topics & Concepts

MedicineBiomarkerLong non-coding RNAAutophagyAdenocarcinomaIdentification (biology)Signature (topology)Coding (social sciences)MALAT1Computational biologyLungLung cancerOncologyRNABioinformaticsPathologyInternal medicineCancerBiologyGeneGeneticsStatisticsApoptosisBotanyMathematicsGeometryCancer-related molecular mechanisms researchAutophagy in Disease and TherapyFerroptosis and cancer prognosis