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INTERNATIONAL CONGRESS OF

CancerGenetics

• microRNAs prediction analysis based on computational biology in liver cancer

• Nayereh Abdali,^1,* Atena Vaghf,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
  
  
  
• Introduction: Liver cancer ranks fourth globally in terms of frequency of occurrence and is the leading cause of mortality worldwide, accounting for 800,000 deaths annually. Chronic viral hepatitis, excessive alcohol use, and non-alcoholic fatty liver disease are the main causes of this illness. Small non-coding RNAs found naturally in the body called microRNAs (miRNAs) are involved in the control of gene expression. Strong evidence has shown that dysregulated miRNA expression occurs in human cancer through a variety of pathways, such as aberrant transcriptional regulation of miRNAs, amplification or deletion of miRNA genes, dysregulated epigenetic modifications, and flaws in the machinery of miRNA biogenesis. Under some circumstances, miRNAs can act as tumor suppressors or oncogenes.
• Methods: This study found candidate medications based on differential gene expression profiles of liver cancer obtained from RNA sequencing data by using a computational drug repurposing process. Using accession code GSE142987 from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), the transcriptional sample of plasma was compared. Only 34 liver cancer patients' plasma samples and 10 healthy people's plasma samples were examined because some samples were not accessible through the dataset. Using GEO2R, differentially expressed genes (DEGs) between plasma samples from patients with liver cancer and plasma samples from healthy participants were identified. Then, the expression difference obtained from the genes was entered into the String(https://string-db.org/) online platform, and finally the gene network was drawn. The desired hub gene was entered in the TargetScan (https://www.targetscan.org/vert_80/) online platform, and it suggests the desired rates for the main gene obtained in this data for liver cancer.
• Results: It was shown that the ACRBP gene is one of the most important genes involved in the development of liver cancer, and further investigations show that microRNAs hsa-miR-4322, hsa-miR-6747-5p and hsa-miR-6737-5p are among the most important miRNAs that play a role in the suppression of ACRBP-causing liver cancer, and their induction can be effective in the process of suppressing liver cancer.
• Conclusion: Methods that can increase and induce suppressive miRNAs in genes and proteins that cause liver cancer can be effective in cancer treatment.
• Keywords: RNA sequencing; Liver cancer; miRNAs