مقالات پذیرفته شده در هشتمین کنگره بین المللی زیست پزشکی
Gene expression analysis and microRNA prediction in gastric cancer using RNA sequencing data
Gene expression analysis and microRNA prediction in gastric cancer using RNA sequencing data
Mobina Bahadorani,1,*
1. Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord , Iran
Introduction: Gastric cancer is the fourth leading cause of cancer-related deaths worldwide. Despite significant advances in medical science, a definitive treatment for this disease remains elusive, posing a major challenge for healthcare professionals and researchers. MicroRNAs (miRNAs), which play crucial roles in regulating gene expression, have gained considerable attention in recent years. By binding to target mRNAs, miRNAs can suppress gene expression and regulate critical cellular processes such as apoptosis, differentiation, and proliferation. Various studies have shown that some miRNAs exhibit oncogenic properties, promoting cancer progression, while others function as tumor suppressors, inhibiting cancer development.
Given the critical role of specific genes involved in gastric cancer, this study aims to propose miRNAs that could potentially suppress one such gene, offering a promising strategy for improving disease management.
Methods: The study utilized the GSE122796 dataset from the GEO database, which includes RNA sequencing data from three gastric cancer tissue samples and three adjacent non-cancerous tissues. Differential gene expression analysis was conducted using the GEO2R tool, identifying differentially expressed genes (DEGs). The identified DEGs were further analyzed using the STRING database to explore protein-protein interactions (PPI), ultimately revealing key genes involved in gastric cancer.
One gene was targeted for further analysis. To predict miRNAs with the potential to suppress it, we employed the miRDB database.
Results: Our analysis identified 20,113 DEGs, of which 1,620 were upregulated and 1,405 were downregulated. Through the PPI analysis, FN1 was identified as one of the key upregulated genes involved in gastric cancer. Using miRDB, 133 miRNAs were predicted to target FN1, with scores ranging from 97 to 50. The highest scores were assigned to hsa-miR-144-3p and hsa-miR-3124-3p.
Conclusion: Gene expression profile analysis based on RNA sequencing data provides valuable insights into the molecular mechanisms underlying gastric cancer and can aid in the development of targeted therapies. This study suggests that the proposed miRNAs may have inhibitory effects on the identified gene, which acts as one of the main genes in gastric cancer. This approach could be considered as one possible strategy for managing the condition, but it is important to note that ultimate success will require further research and clinical validation.