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INTERNATIONAL CONGRESS OF

CancerGenetics

• A computational approach to identify the biomarker based on the RNA sequencing data analysis for colorectal cancer

• Atena Vaghf,^1,* Nayereh Abdali,² Shahram Tahmasebian,³
  1. Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
  2. Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
  3. Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran
  
  
  
• Introduction: Colorectal cancer (CRC) remains one of the most common cancers in the world. Previous studies have shown that some genetic changes are closely associated with the occurrence of CRC. RNA sequencing (RNA-seq) is one effective approach to finding the heterogeneous gene expressions of diseases that helps discover new functional genes as prognostic biomarkers. Besides, It is well-known that microRNA (miRNAs) biomarkers have emerged as a powerful screening tool, as they are highly expressed in CRC patients and easily detectable in several biological samples. The bioinformatics method is cost-effective and time-saving when studying the role of miRNAs-mRNA. Therefore, in this study computational models were used to identify colon cancer-related biomarker by RNA-seq analysis.
• Methods: The RNA sequencing of 20 colorectal tumor samples with 20 matched adjacent normal colorectal tissue under the accession code GSE142279 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). The differentially expressed genes (DEGs) between CRC and normal tissues were obtained by using GEO2R. The 1000 top up regulated genes were imported into the STRING (version 12.0, http://string-db.org) database to identify the interactive association between the proteins. Then, the all interactions with a significant combined score >0.9 were selected for further analysis. The appropriate gene with the highest degrees of connectivity were selected as hub genes. The targetSacn database is a specialized collection of microRNA-mRNA targeting relationships. These databases were used to obtain hub gene-associated miRNA.
• Results: This study identified 4250 genes with |log2FC|>1 and P-value <0.01 as DEGs: 2009 upregulated and 2241 downregulated genes. BYSL, Bystin like, was identified as one of the best hub gene in STRING which hsa-miR-138-5p can suppressed the BYSL expression in CRC. BYSL plays a role in a variety of cancers, and mutations in the BYSL gene will significantly increase tumourigenesis and progression. BYSL was characterized as an important gene for cell proliferation, migration and invasion in human carcinoma. Down-regulation of miR-138-5p has also been reported in various cancers. This miRNA have been categorized as a tumor suppressor. Of note, this bioinformatic results confirmed that targeting BYSL is an important mechanism of the tumor-suppressive function of miR-138-5p in CRC. Moreover, TargetScan indicating that the seed region of miR-138-5p contains 1 complementary sites within position 2293-2299 of BYSL 3' UTR.
• Conclusion: Taken together, our findings from RNA sequencing analysis provide the first clues regarding the role of miR-138-5p as a tumor suppressor in CRC by inhibiting BYSL translation. The results also provide valuable insights into the regulation of miR-138-5p and BYSL for future research and therapeutic development.
• Keywords: Colorectal cancer; RNA sequencing; miRNA; miR-138-5p; BYSL