Han-Xi Ding1,2, Qian Xu1,2, Ben-Gang Wang1,2,3, Zhi Lv1,2, Yuan Yuan4,5. 1. Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University, Shenyang, China. 2. Key Laboratory of Cancer Etiology and Prevention in Liaoning Education Department, The First Hospital of China Medical University, Shenyang, China. 3. Hepatobiliary Surgery Department of General Surgery Institute, The First Hospital of China Medical University, Shenyang, China. 4. Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University, Shenyang, China. yuanyuan@cmu.edu.cn. 5. Key Laboratory of Cancer Etiology and Prevention in Liaoning Education Department, The First Hospital of China Medical University, Shenyang, China. yuanyuan@cmu.edu.cn.
Abstract
BACKGROUND: Circular RNAs (circRNAs) could play carcinogenic roles in gastric cancer (GC) and have potential to be biomarkers for GC early diagnosis, which needs to be further excavated and supported by more evidence. AIMS: The study aims to identify more authentic circRNA expression profiles that could function as potential biomarkers in GC. METHODS: circRNA expression data in three microarrays were downloaded from Gene Expression Omnibus datasets. A systematic meta-analysis based on an integrated dataset pre-processed from the three microarrays was conducted to identify a panel of differentially expressed circRNAs (DEcircs) by using the metaDE package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes term enrichment were used to note the corresponding functions of DEcircs. Quantitative real-time polymerase chain reaction was applied to verify the DEcircs expression in cancer tissues and adjacent paracancerous tissues. A GC risk-related circRNAs-miRNAs-mRNAs network was further constructed and analyzed. RESULTS: MetaDE analysis suggested 64 DEcircs between cancer tissues and adjacent normal tissues. GO and KEGG analysis showed that the parental genes of these DEcircs were mainly associated with histone methylation, Wnt signalosome and histone methylation activity. Hsa_circ_0005927 and hsa_circ_0067934 were verified in GC tissues, and a GC risk-related network was constructed. CONCLUSION: MetaDE-based circRNA expression profiles revealed a series of potential biomarkers involved in GC. Two circRNAs, hsa_circ_0005927 and hsa_circ_0067934, could be more authentic biomarkers for GC screening. The GC risk-related network of hsa_circ_0005927/hsa_circ_0067934 and their downstream targets will provide new genetic insights for GC research.
BACKGROUND: Circular RNAs (circRNAs) could play carcinogenic roles in gastric cancer (GC) and have potential to be biomarkers for GC early diagnosis, which needs to be further excavated and supported by more evidence. AIMS: The study aims to identify more authentic circRNA expression profiles that could function as potential biomarkers in GC. METHODS: circRNA expression data in three microarrays were downloaded from Gene Expression Omnibus datasets. A systematic meta-analysis based on an integrated dataset pre-processed from the three microarrays was conducted to identify a panel of differentially expressed circRNAs (DEcircs) by using the metaDE package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes term enrichment were used to note the corresponding functions of DEcircs. Quantitative real-time polymerase chain reaction was applied to verify the DEcircs expression in cancer tissues and adjacent paracancerous tissues. A GC risk-related circRNAs-miRNAs-mRNAs network was further constructed and analyzed. RESULTS: MetaDE analysis suggested 64 DEcircs between cancer tissues and adjacent normal tissues. GO and KEGG analysis showed that the parental genes of these DEcircs were mainly associated with histone methylation, Wnt signalosome and histone methylation activity. Hsa_circ_0005927 and hsa_circ_0067934 were verified in GC tissues, and a GC risk-related network was constructed. CONCLUSION: MetaDE-based circRNA expression profiles revealed a series of potential biomarkers involved in GC. Two circRNAs, hsa_circ_0005927 and hsa_circ_0067934, could be more authentic biomarkers for GC screening. The GC risk-related network of hsa_circ_0005927/hsa_circ_0067934 and their downstream targets will provide new genetic insights for GC research.