Comprehensive analysis of gene expression and DNA methylation data identifies potential biomarkers and functional epigenetic modules for lung adenocarcinoma.

Xiaocong Wang,Fangzheng Zhou,Jie Chen,Yanmei Li,Dongsheng Zhang,Huihua Hu

doi:10.1590/1678-4685-gmb-2019-0164

Xiaocong Wang, Fangzheng Zhou + Show 4 more

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https://doi.org/10.1590/1678-4685-gmb-2019-0164

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Abstract

Lung cancer has one of the highest mortality rates of malignant neoplasms. Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer. DNA methylation is more stable than gene expression and could be used as a biomarker for early tumor diagnosis. This study is aimed to screen potential DNA methylation signatures to facilitate the diagnosis and prognosis of LUAD and integrate gene expression and DNA methylation data of LUAD to identify functional epigenetic modules. We systematically integrated gene expression and DNA methylation data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), bioinformatic models and algorithms were implemented to identify signatures and functional modules for LUAD. Three promising diagnostic and five potential prognostic signatures for LUAD were screened by rigorous filtration, and our tumor-normal classifier and prognostic model were validated in two separate data sets. Additionally, we identified functional epigenetic modules in the TCGA LUAD dataset and GEO independent validation data set. Interestingly, the MUC1 module was identified in both datasets. The potential biomarkers for the diagnosis and prognosis of LUAD are expected to be further verified in clinical practice to aid in the diagnosis and treatment of LUAD.

Highlights

Lung cancer has one of the highest incidence and mortality rates of neoplasms and can be classified into small cell lung cancer and non-small cell lung cancer (NSCLC), NSCLC consists of adenocarcinoma, squamous cell carcinoma, large cell carcinoma and other types (Travis, 2011)
The unsupervised cluster map of the DNA methylation level of these 3 probes could clearly distinguish tumor samples from normal samples (Figure 2b), indicating that the selected three probes can be used as potential biomarkers for the diagnosis of lung adenocarcinoma (LUAD)
DNA methylation changes have been reported to occur early in carcinogenesis (Teschendorff et al, 2016), and DNA methylation analysis seems to be a promising strategy in cancer diagnosis

Summary

Introduction

Lung cancer has one of the highest incidence and mortality rates of neoplasms and can be classified into small cell lung cancer and non-small cell lung cancer (NSCLC), NSCLC consists of adenocarcinoma, squamous cell carcinoma, large cell carcinoma and other types (Travis, 2011). Despite treatment with surgery followed by radiotherapy or chemotherapy, many patients still have poor clinical outcomes (Perez et al, 2014; Ramnath et al, 2013; Verdecchia et al, 2007). Early diagnosis and treatment are the key to reducing the mortality of lung cancer. No widely used DNA methylation markers have been identified for the early diagnosis and prognosis of lung adenocarcinoma (LUAD). According to a previous study, alterations in DNA methylation (DNAm) appear to mark preneoplastic normal cells that later transform and become enriched in tumors (Teschendorff et al, 2016), which indicates that DNAm could act as biomarkers for the diagnosis of early cancer

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