Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas.

Sijin Sun,Zhenlin Yang,Guochao Zhang,Yibo Gao,Jie Wang,Qi Xue,Jie He,Wei Guo,Yannan Yang,Kailun Fei,Juhong Wang

doi:10.3389/fgene.2020.617174

Sijin Sun, Zhenlin Yang + Show 9 more

Open Access

https://doi.org/10.3389/fgene.2020.617174

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Abstract

For lung adenocarcinoma (LUAD), patients of different stages have strong heterogeneity, and their overall prognosis varies greatly. Thus, exploration of novel biomarkers to better clarify the characteristics of LUAD is urgent. Multi-omics information of LUAD patients were collected form TCGA. Three independent LUAD cohorts were obtained from gene expression omnibus (GEO). A multi-omics correlation analysis of METTL5 was performed in TCGA dataset. To build a METTL5-associated prognostic score (MAPS). Spathial and random forest methods were first applied for feature selection. Then, LASSO was implemented to develop the model in TCGA cohort. The prognostic value of MAPS was validated in three independent GEO datasets. Finally, functional annotation was conducted using gene set enrichment analysis (GSEA) and the abundances of infiltrated immune cells were estimated by ImmuCellAI algorithm. A total of 901 LUAD patients were included. The expression of METTL5 in LUAD was significantly higher than that in normal lung tissue. And high expression of METTL5 indicated poor prognosis in all different stages (P < 0.001, HR = 1.81). Five genes (RAC1, C11of24, METTL5, RCCD1, and SLC7A5) were used to construct MAPS and MAPS was significantly correlated with poor prognosis (P < 0.001, HR = 2.15). Furthermore, multivariate Cox regression analysis suggested MAPS as an independent prognostic factor. Functional enrichment revealed significant association between MAPS and several immune components and pathways. This study provides insights into the potential significance of METTL5 in LUAD and MAPS can serve as a promising biomarker for LUAD.

Highlights

MATERIALS AND METHODSAs the world’s highest incidence and highest mortality, lung cancer causes more than 700,000 deaths each year (Bray et al, 2018)
METTL5 expression and copy number variation (CNV) was found in lung adenocarcinoma (LUAD) (Figure 2E)
The clinical and prognostic effects of METTL5 was analyzed in LUAD based on the the Cancer Genome Atlas (TCGA) database, and further we developed a METTL5-based signature METTL5-associated prognostic score (MAPS), which could effectively predict the prognosis of patients with LUAD

Summary

MATERIALS AND METHODS

As the world’s highest incidence and highest mortality, lung cancer causes more than 700,000 deaths each year (Bray et al, 2018). The multi-omics LUAD dataset including mRNA expression profile, DNA methylation, gene mutation and copy number variation (CNV) data was retrieved from the Cancer Genome Atlas (TCGA) Data Portal (1May, 2020). To validate the predictive value of MAPS, Cox regression and Kaplan–Meier survival analysis were performed in three independent cohorts (GSE3141, GSE13213, and GSE31210) (Bild et al, 2006; Tomida et al, 2009; Okayama et al, 2012). In order to understand the potential biological relevance of MAPS, gene set enrichment analysis (GESA) was conducted based on the R package clusterProfiler between different risk groups (Yu et al, 2012). A m6Aprognostic signature reported by Li et al were extracted and risk score was calculated for each sample according to the provided formula in all included cohorts except GSE13213 due to lack of gene probes. A P value less than 0.05 was considered statistically significant

RESULTS

DISCUSSION

DATA AVAILABILITY STATEMENT