Bioinformatics Analysis Reveals Potential Biomarkers for Esophageal Cancer

Esophageal cancer primarily occurs in two forms: esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC).[۱] While ESCC is more prevalent in developing countries, EAC is commonly observed in developed nations. Due to the high incidence of esophageal cancer as one of the most common malignancies of the gastrointestinal tract and the lack of early awareness, it ranks as the sixth leading cause of cancer-related deaths worldwide. Preventative measures such as maintaining a healthy diet, utilizing chemoradiotherapy, and identifying reliable biomarkers are crucial for improving treatment outcomes.[۲] The EGFR gene, encoding a critical protein involved in cell growth and survival, plays a significant role in cancer development. Mutations in this gene result in uncontrolled cell proliferation, contributing to cancers such as esophageal, lung, and gastric cancers. Based on this background, the present study aims to identify potential biomarkers for the early detection of esophageal cancer, facilitating timely and effective interventions. Materials and Methods: First, raw data from GSE۱۶۱۵۳۳ was downloaded from the Gene Expression Omnibus (GEO) database. In-depth analysis of differentially expressed genes (DEGs) was performed using RStudio. The selected gene was then searched in the KEGG database by its gene symbol to ensure its presence in the dataset. Upon confirmation, further research was conducted on the selected gene. For gene expression analysis, relevant microRNAs were identified using the miRWalk database. Additionally, the interaction between microRNAs (miRNAs) and single nucleotide polymorphisms (SNPs) was examined through the miRNASNP database. Lastly, the desired long non-coding RNAs (lncRNAs) were identified using the lncRRlsearch database. Results: Based on the data obtained from GSE۱۵۱۶۳۳, the EGFR gene was identified as a key indicator in esophageal cancer. Through the miRWalk database, miRNAs associated with the EGFR gene were analyzed, and hsa-let-۷a-۵p was selected due to its strong interaction quality. The relevant SNP, rs۱۳۶۲۹۷۵۱۳۶, was chosen based on its interaction strength, as determined by the miRENASNP database. Additionally, using the lncRRlsearch database, the long non-coding RNA EGFR-AS۱ was identified as a significant lncRNA related to the EGFR gene. Conclusion: Based on the bioinformatics analysis conducted in this study, the EGFR gene, hsa-let-۷a-۵p miRNA, rs۱۳۶۲۹۷۵۱۳۶ SNP, and EGFR-AS۱ lncRNA have been identified as potential biomarkers for esophageal cancer. These biomarkers could play a crucial role in the early diagnosis and treatment of this disease, offering valuable insights for future therapeutic strategies. References: [۱] He, S., Xu, J., Liu, X., & Zhen, Y. (۲۰۲۱). Advances and challenges in the treatment of esophageal cancer. Acta Pharmaceutica Sinica B, ۱۱(۱۱), ۳۳۷۹-۳۳۹۲. [۲] Hou, X., Wen, J., Ren, Z., & Zhang, G. (۲۰۱۷). Non-coding RNAs: new biomarkers and therapeutic targets for esophageal cancer. Oncotarget, ۸(۲۶), ۴۳۵۷۱.

کلیدواژه ها:

Esophageal cancer ، EGFR ، hsa-let-۷a-۵p ، rs۱۳۶۲۹۷۵۱۳۶ ، EGFR-A