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05 April 2019 : Laboratory Research  

Identification of Key Genes and Circular RNAs in Human Gastric Cancer

Shuhong Hao1CEF, Junfeng Lv2B, Qiwei Yang3D, Ao Wang4F, Zhaoyan Li4E, Yuchen Guo5AG, Guizhen Zhang34AG*

DOI: 10.12659/MSM.915382

Med Sci Monit 2019; 25:2488-2504

Abstract

BACKGROUND: Globally, gastric cancer (GC) is the third most common source of cancer-associated mortality. The aim of this study was to identify key genes and circular RNAs (circRNAs) in GC diagnosis, prognosis, and therapy and to further explore the potential molecular mechanisms of GC.

MATERIAL AND METHODS: Differentially expressed genes (DEGs) and circRNAs (DE circRNAs) between GC tissues and adjacent non-tumor tissues were identified from 3 mRNA and 3 circRNA expression profiles. Functional analyses were performed, and protein–protein interaction (PPI) networks were constructed. The significant modules and key genes in the PPI networks were identified. Kaplan-Meier analysis was performed to evaluate the prognostic value of these key genes. Potential miRNA-binding sites of the DE circRNAs and target genes of these miRNAs were predicted and used to construct DE circRNA–miRNA–mRNA networks.

RESULTS: A total of 196 upregulated and 311 downregulated genes were identified in GC. The results of functional analysis showed that these DEGs were significantly enriched in a variety of functions and pathways, including extracellular matrix-related pathways. Ten hub genes (COL1A1, COL3A1, COL1A2, COL5A2, FN1, THBS1, COL5A1, SPARC, COL18A1, and COL11A1) were identified via PPI network analysis. Kaplan-Meier analysis revealed that 7 of these were associated with a poor overall survival in GC patients. Furthermore, we identified 2 DE circRNAs, hsa_circ_0000332 and hsa_circ_0021087. To reveal the potential molecular mechanisms of circRNAs in GC, DE circRNA–microRNA–mRNA networks were constructed.

CONCLUSIONS: Key candidate genes and circRNAs were identified, and novel PPI and circRNA–microRNA–mRNA networks in GC were constructed. These may provide useful information for the exploration of potential biomarkers and targets for the diagnosis, prognosis, and therapy of GC.

Keywords: Diagnosis, Gene Expression Profiling, Computational Biology, Gene Regulatory Networks, Oligonucleotide Array Sequence Analysis, Protein Interaction Mapping, Protein Interaction Maps, RNA, RNA, Circular, RNA, Messenger

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750