Network-Based Differential Analysis to Identify Molecular Features of Tumorigenesis for Esophageal Squamous Carcinoma

Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry
Suxia JiangLinqiang Pan

Abstract

Esophageal cancer has a poor prognosis and high mortality rate across the world. The diagnosis and treatment of esophageal cancer are hindered by the limited knowledge about the pathogenesis mechanisms of esophageal cancer. Esophageal cancer has two major subtypes, squamous and adenocarcinoma. In this work, we proposed a method to select candidate biomarkers of esophageal squamous carcinoma based on the topological differential analysis between the gene-gene interaction networks for esophageal squamous carcinoma and normal cells. We established the gene-gene interaction networks for esophageal squamous carcinoma and normal based on the correlation of genes. For each gene, we firstly calculated and compared five centrality measures, which could reflect the topological property of a network. According to five centrality measures, the genes with large differences between the two networks were regarded as candidate biomarkers for esophageal squamous carcinoma. A total of 21 candidate biomarkers were identified for esophageal squamous carcinoma, and seven of them have been confirmed to be biomarkers of esophageal-12 squamous carcinoma by previous research. In addition, six genes (RBPMS2, PDK4, IGK, SBSN, IFIT3 and HSPB6) were likely...Continue Reading

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Citations

Jan 23, 2021·The Journal of Investigative Dermatology·Jason ThomsonJun Wang
Jan 23, 2021·Genes·Miroslav PribylIva Kubikova

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Datasets Mentioned

BETA
GSE23400

Methods Mentioned

BETA
X-ray

Software Mentioned

Microarray Suite 5 Mas5
Cytoscape

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