J Cancer 2018; 9(24):4568-4577. doi:10.7150/jca.27655

Research Paper

Systematic Analysis of Gene Expression Alteration and Co-Expression Network of Eukaryotic Initiation Factor 4A-3 in Cancer

Yan Lin1*, Jinyan Zhang1*, Junying Cai2*, Rong Liang1, Guoying Chen3, Gang Qin3, Xueqiong Han3, Chunling Yuan1, Zhihui Liu1, Yongqiang Li1, Donghua Zou3✉, Yingwei Mao4✉

1. Department of Medical Oncology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi 530021, People's Republic of China
2. Maternal and Child Health Hospital and Obstetrics and Gynecology Hospital of Guangxi Zhuang Autonomous Region, Guangxi 530003, People's Republic of China
3. The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530022, People's Republic of China
4. Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA
*These authors contributed equally to this work.

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Citation:
Lin Y, Zhang J, Cai J, Liang R, Chen G, Qin G, Han X, Yuan C, Liu Z, Li Y, Zou D, Mao Y. Systematic Analysis of Gene Expression Alteration and Co-Expression Network of Eukaryotic Initiation Factor 4A-3 in Cancer. J Cancer 2018; 9(24):4568-4577. doi:10.7150/jca.27655. Available from http://www.jcancer.org/v09p4568.htm

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Abstract

Purpose: Eukaryotic initiation factor 4A-3 (EIF4A3) is an RNA-binding protein (RBP) that is a core component of the exon junction complex (EJC). It has been identified as an important player in post-transcriptional regulation processes. Recently, investigations have focused on EIF4A3 dysfunction in carcinogenesis. The present study aims to determine whether EIF4A3 can serve as a prognostic marker and potential regulatory mechanism in human cancers.

Materials and methods: EIF4A3 expression in various cancers was assessed using Oncomine. The Correlation between EIF4A3 expression and patient survival was evaluated using PrognoScan. EIF4A3 mutations in various cancers were investigated using cBioPortal. EIF4A3 co-expression networks in various cancers were established using Coexpedia. Finally, we analyzed potential functional roles of EIF4A3 using Gene Ontology and pathway enrichment analyses by FunRich V3.

Results: EIF4A3 was overexpressed in common malignancies at the transcription levels. High incidences of the breast, lung, and urinary cancers were closely related to the prognostic index for survival. The most prevalent mutation in EIF4A3 was E59K/Q. The tumor necrosis factor-α (TNF-α)/nuclear factor-κB (NF-κB) signaling pathway was affected by these mutations. Co-expression networks showed that EIF4A3 regulates apoptosis and cell cycle via several cancer-related signal pathways, and promotes tumor cell migration, invasion and drug resistance.

Conclusion: Our results suggest the potential role for EIF4A3 to serve as a diagnostic marker or therapeutic target for certain types of cancers.

Keywords: EIF4A3, cancer, prognosis, co-expression analysis