Deciphering N6-Methyladenosine-Related Genes Signature to Predict Survival in Lung Adenocarcinoma

• Main Authors: Jie Zhu, Min Wang, Daixing Hu
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2020/2514230

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N6-methyladenosine (m6A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m6A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m6A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m6A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m6A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m6A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p<0.05), M stages (p<0.05), T stages (p < 0.05), gender (p=0.04), and survival outcome (p=0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m6A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.