Identification and Analysis of Crucial Genes Underlying pancreatic cancer via Bioinformatics Techniques

Pancreatic cancer (PC) represents a highly aggressive neoplasm within the digestive system, and its global burden has more than doubled over the past ۲۵ years. The highest incidence regions for pancreatic cancer include North America, Europe and Australia, and although much of this increase is due to ageing worldwide population . Pancreatic cancer is a fatal malignancies which is predominantly seen in men and at advanced age (۴۰-۸۵ years) and has an aggressive course. Its frequency is gradually increasing over the past years. It accounts for ۲% of all cancers and ۵% of cancer-related deaths. Pancreatic cancer takes the first place among asymptomatic cancers. Ninety percent of cases are adenocarcinomas. Ten percent of the patients have a familial disposition. The disease is very difficult to detect as it has no early signs and spreads rapidly to surrounding organs is one of the most deadly types of cancer. Numerous studies have indicated that various microRNAs, particularly miRNA-۲۱, play a significant role in predicting survival and regulating apoptosis. Recently, advancements in microarray and sequencing technologies, coupled with the availability of multi-omics databases, have enabled researchers to not only identify alterations in the expression of specific genes but also to compare these changes between groups of cancer patients and healthy individuals. Methods: One dataset comprising ۵۲ samples was sourced from the GEO database, with each dataset undergoing a quality assessment via Principal Component Analysis (PCA). Following this, the LIMMA package was applied to detect genes that displayed differential expression. A Venn diagram was utilized to ascertain the common differentially expressed genes (DEGs). Additionally, the RNA-seq results from TCGA were used to corroborate our findings. Finally, the association between the DEGs and disease survival time was evaluated using the Kaplan-Meier plotter. Result: Three genes (FN۱, EGF, POSTN) were recognized as hub genes. It was observed that the biological process categories associated with these common genes were significantly enriched in various domains, including extracellular matrix organization and tissue development. Conclusion: This research facilitated the identification of three genes exhibiting differential expression profiles in pancreatic cancer, which may hold potential for early disease detection.

کلیدواژه ها:

Pancreatic cancer ، biomarker ، microarray