Comprehensive analysis of differential co-expression patterns reveal transcriptional dysregulation mechanism and identify novel prognostic lncRNAs in esophageal squamous cell carcinoma

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies worldwide and occurs at a relatively high frequency in People’s Republic of China. However, the molecular mechanism underlying ESCC is still unclear. In this study, the mRNA and long non-coding RNA (lncRNA) expression profiles of ESCC were downloaded from the Gene Expression Omnibus database, and then differential co-expression analysis was used to reveal the altered co-expression relationship of gene pairs in ESCC tumors. A total of 3,709 mRNAs and 923 lncRNAs were differentially co-expressed between normal and tumor tissues, and we found that most of the gene pairs lost associations in the tumor tissues. The differential regulatory networking approach deciphered that transcriptional dysregulation was ubiquitous in ESCC, and most of the differentially regulated links were modulated by 37 TFs. Our study also found that two novel lncRNAs (ADAMTS9-AS1 and AP000696.2) might be essential in the development of ectoderm and epithelial cells, which could significantly stratify ESCC patients into high-risk and low-risk groups, and were much better than traditional clinical tumor markers. Further inspection of two risk groups showed that the changes in TF-target regulation in the high-risk patients were significantly higher than those in the low-risk patients. In addition, four signal transduction-related DCmRNAs (ERBB3, ENSA, KCNK7, MFSD5), which were differentially co-expressed with the two lncRNAs, might also have the predictive capacity. Our findings will enhance the understanding of ESCC transcriptional dysregulation from a view of cross-link of lncRNA and mRNA, and the two-lncRNA combination may serve as a novel prognostic biomarker for clinical applications of ESCC.

Keywords:

• ESCC
• differential co-expression analysis
• differential regulation analysis
• dysregulation
• lncRNA
• prognostic biomarker

Acknowledgments

This work was supported by the National High Technology Research and Development Program of China (2015AA020104, 2015AA020108), the National Key Research and Development Program on Precision Medicine (2016YFC0901700, 2016YFC0901900, 2016YFC0901600), the National Key Technology Support Program (2013BAI101B09), the National Grand Program on Key Infectious Diseases (2015ZX10004801) and the Youth Innovation Promotion Association CAS.

Author contributions

ZL, ZW and YXL conceived the concept for this work; ZL performed the analyses and wrote the manuscript; ZL, QLY and ZW discussed the analyses; and ZW, SJZ and YW carried out the review. All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.