Abstract

Esophageal squamous cell carcinoma (ESCC) is a common malignancy with poor prognosis and survival rate. To identify meaningful long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) modules related to the ESCC prognosis, The Cancer Genome Atlas-ESCC was downloaded and processed, and then, a weighted gene co-expression network analysis was applied to construct lncRNA co-expression networks, miRNA co-expression networks, and mRNA co-expression networks. Twenty-one hub lncRNAs, seven hub miRNAs, and eight hub mRNAs were clarified. Additionally, a competitive endogenous RNAs network was constructed, and the emerging role of the network involved in head and neck squamous cell carcinoma (HNSCC) was also analyzed using several webtools. The expression levels of eight hub genes (TBC1D2, ATP6V0E1, SPI1, RNASE6, C1QB, C1QC, CSF1R, and C1QA) were different between normal esophageal tissues and HNSCC tissues. The expression levels of TBC1D2 and ATP6V0E1 were related to the survival time of HNSCC. The competitive endogenous RNAs network might provide common mechanisms involving in ESCC and HNSCC. More importantly, useful clues were provided for clinical treatments of both diseases based on novel molecular advances.

Highlights

  • Esophageal squamous cell carcinoma (ESCC) is the globally predominant pathological type of esophageal cancer [1]

  • The results showed that TBC1D2 and ATP6V0E1 were significantly downregulated in ESCC, while SPI1, RNASE6, C1QB, C1QC, CSF1R, and C1QA are significantly downregulated (Figure 5)

  • The common mechanisms and molecular targets between ESCC and head and neck squamous cell carcinoma (HNSCC) were explored by bioinformatics analysis for the first time

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Summary

Introduction

Esophageal squamous cell carcinoma (ESCC) is the globally predominant pathological type of esophageal cancer [1]. For the lack of effective biomarkers, most patients with ESCC are diagnosed at a late stage, which leads to the poor prognosis of ESCC, with a 5-year survival rate of

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