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. 2020 Jan 13;11(6):1393-1402.
doi: 10.7150/jca.30699. eCollection 2020.

Identification of key genes and pathways associated with esophageal squamous cell carcinoma development based on weighted gene correlation network analysis

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Identification of key genes and pathways associated with esophageal squamous cell carcinoma development based on weighted gene correlation network analysis

Mingrui Shao et al. J Cancer. .

Abstract

Background: As one of the most aggressive malignancies, esophageal squamous cell carcinoma(ESCC) remains one of the leading causes of cancer related death worldwide. The majority of ESCCs are diagnosed at advanced stages with poor five-year survival rate, making it urgent to identify specific genes and pathways associated with its initiation and prognosis. Materials and Methods: The differentially expressed genes in TCGA were analysed to construct a co-expression network by WGCNA. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were performed for the selected genes. Module-clinical trait relationships were analyzed to explore the genes and pathways that associated with clinicopathological parameters of ESCC. Log-rank tests and COX regression were used to identify the prognosis-related genes. Results: The brown module containing 716 genes which most significantly contributed to ESCC. GO analysis suggested enrichment of adaptive immune response, cyclin-dependent protein serine, regeneration and mRNA metabolic process. KEGG analysis indicated pathways including Cellular senescence, Ribosome biogenesis, Proteasome, Base excision repair and p53 signaling pathway. Clinical stage was associated with cyan module; clinical M was associated with grey60 module; clinical T was associated with darkturquoise module; while clinical N, histological type and cancer location were associated with turquoise module. Key genes of TCP1, COQ3, PTMA and MAPRE1 might be potential prognostic markers for ESCC. Discussion: Differentially expressed genes and key modules contributing to initiation and progression in ESCC were identified by WGCNA. These findings provide novel insights into the mechanisms underlying the initiation, prognosis and treatment of ESCC.

Keywords: esophageal squamous cell carcinoma; prognosis.; risk; weighted gene correlation network analysis.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
The connectivity analysis of critical genes in different module
Figure 2
Figure 2
The protein-protein interaction network of the genes in the risk-related brown module of ESCC.
Figure 3
Figure 3
Gene Ontology analysis and KEGG pathway enrichment analysis for genes in the risk-related brown module of ESCC.
Figure 4
Figure 4
The correlation between the expression levels of key genes of risk-associated brown module and the survival of ESCC patients.
Figure 5
Figure 5
The module-clinical trait relationships of genes involved in ESCC.

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