Identification of circRNA Biomarker for Gastric Cancer through Integrated Analysis

Md Tofazzal Hossain; Song Li; Md Selim Reza; Shengzhong Feng; Xiaojing Zhang; Zhe Jin; Yanjie Wei; Yin Peng

doi:10.3389/fmolb.2022.857320

Identification of circRNA Biomarker for Gastric Cancer through Integrated Analysis

Front Mol Biosci. 2022 Mar 10:9:857320. doi: 10.3389/fmolb.2022.857320. eCollection 2022.

Authors

Md Tofazzal Hossain^{1

2

3}, Song Li⁴, Md Selim Reza^{1

2}, Shengzhong Feng², Xiaojing Zhang⁵, Zhe Jin⁵, Yanjie Wei², Yin Peng⁵

Affiliations

¹ University of Chinese Academy of Sciences, Beijing, China.
² Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
³ Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
⁴ Shenzhen Science & Technology Development Exchange Center, Shenzhen Science and Technology Building, Shenzhen, China.
⁵ Guangdong Provincial Key Laboratory for Genome Stability & Disease Prevention and Regional Immunity and Diseases, Department of Pathology, Shenzhen University School of Medicine, Shenzhen, China.

Abstract

Gastric cancer (GC) is one of the most common malignant tumors and ranks third in cancer mortality globally. Although, a lot of advancements have been made in diagnosis and treatment of gastric cancer, there is still lack of ideal biomarker for the diagnosis and treatment of gastric cancer. Due to the poor prognosis, the survival rate is not improved much. Circular RNAs (circRNAs) are single-stranded RNAs with a covalently closed loop structure that don't have the 5'-3' polarity and a 3' polyA tail. Because of their circular structure, circRNAs are more stable than linear RNAs. Previous studies have found that circRNAs are involved in several biological processes like cell cycle, proliferation, apoptosis, autophagy, migration and invasion in different cancers, and participate in some molecular mechanisms including sponging microRNAs (miRNAs), protein translation and binding to RNA-binding proteins. Several studies have reported that circRNAs play crucial role in the occurrence and development of different types of cancers. Although, some studies have reported several circRNAs in gastric cancer, more studies are needed in searching new biomarkers for gastric cancer diagnosis and treatment. Here, we investigated potential circRNA biomarkers for GC using next-generation sequencing (NGS) data collected from 5 paired GC samples. A total of 45,783 circRNAs were identified in all samples and among them 478 were differentially expressed (DE). The gene ontology (GO) analysis of the host genes of the DE circRNAs showed that some genes were enriched in several important biological processes, molecular functions and cellular components. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that some host genes were enriched in several GC related pathways. The circRNA-miRNA-gene interaction network analysis showed that two circRNAs circCEACAM5 and circCOL1A1 were interacted with gastric cancer related miRNAs, and their host genes were also the important therapeutic and prognostic biomarkers for GC. The experimental results also validated that these two circRNAs were DE in GC compared to adjacent normal tissues. Overall, our findings suggest that these two circRNAs circCEACAM5 and circCOL1A1 might be the potential biomarkers for the diagnosis and treatment of GC.

Keywords: circRNA biomarker; circRNA-miRNA-gene interaction; circular RNA; computational approach; gastric cancer.

Grants and funding

This work was partly supported by the National Key Research and Development Program of China under Grant No. 2018YFB0204403; Strategic Priority CAS Project XDB38050100; National Science Foundation of China under grant no. U1813203; the Shenzhen Basic Research Fund under grant nos JCYJ20200109114818703, RCYX20200714114734194, and JSGG20201102163800001; CAS Key Lab under grant no. 2011DP173015 (YW). We would also like to thank the funding support from the Youth Innovation Promotion Association, CAS to YW. This work is also supported by the National Foundation of Science (82172946) to ZJ; the National Foundation of Science (82173290) to XZ; Shenzhen Basic Research Fund (JCYJ20190808163801777) to YP.