Literature DB >> 30505479

Gene set enrichment analysis and meta-analysis to identify six key genes regulating and controlling the prognosis of esophageal squamous cell carcinoma.

Wenwu He1, Linxin Chen2, Kun Yuan3, Qiuxi Zhou4, Lin Peng1, Yongtao Han1.   

Abstract

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a common malignancy with high mortality. Because of the lack of clarity in the relevant genes and mechanisms involved, and the current difficulty for oncotherapy in providing therapeutic solutions, there is an urgent need to study this matter. While gene probe studies have been used to select the most virulent genes and pathways, paucity of case controls during gene screening and lack of conclusive results to expound the etiology and pathogenesis of the disease, have reduced study reliability.
METHODS: We chose six datasets from independent studies in the Gene Expression Omnibus (GEO) database and used gene set enrichment analysis and meta-analysis to select key genes and pathways.
RESULTS: We found four down-regulated and four up-regulated pathways through gene set enrichment analysis, and 406 differential genes through meta-analysis. Based on The Cancer Genome Atlas (TCGA), 995 differentially expressed genes were screened out. Comparing the 406 gene set with the 995 gene set, we found 19 common genes, of which 6 had a common pathway and were screened out as key genes regulating and controlling the prognosis of ESCC.
CONCLUSIONS: Among the 19 genes, we found three genes that affect the chemotherapy of ESCC: BUB1B, BUB1, and TTK. Another three genes NDC1, NUP107, and NUP155 on the RNA transport pathway were also found. Altogether, these six genes are not only crucial in the development of ESCC, but also determine the prognosis of patients. The key genes and pathways identified in the present study will be used for the next stage in our study, which will involve gene elimination and other experimentation methods.

Entities:  

Keywords:  Esophageal squamous cell carcinoma (ESCC); gene set enrichment analysis (GSEA); key gene; meta-analysis; pathway

Year:  2018        PMID: 30505479      PMCID: PMC6236198          DOI: 10.21037/jtd.2018.09.55

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN: 2072-1439            Impact factor:   2.895


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