Identification of informative Genes in Lung Cancer Stem Cells via Bioinformatics Analysis
- سال انتشار: 1403
- محل انتشار: دومین کنگره بین المللی کنسرژنومیکس
- کد COI اختصاصی: ICGCS02_143
- زبان مقاله: انگلیسی
- تعداد مشاهده: 92
نویسندگان
Department of Molecular and Cellular Sciences, Faculty of Advanced Science and Technology, Tehran Medical Science, Islamic Azad University, Tehran, Iran
Department of Molecular and Cellular Sciences, Faculty of Advanced Science and Technology, Tehran Medical Science, Islamic Azad University, Tehran, Iran
Vira Pioneers of Modern Science (VIPOMS), Tehran, Iran
چکیده
Background. Lung cancer (LC) is the leading cause of cancer-related deaths globally, primarily affecting individuals over ۶۵. Smoking is the most significant risk factor, responsible for over ۸۰% of cases. LC is classified into small-cell lung carcinoma (۱۵%) and non-small cell lung carcinoma (۸۵%), the latter including adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Early detection significantly improves survival rates, yet many cases are diagnosed at advanced stages. Metastasis occurs via circulating tumor cells spreading to organs like the lymph nodes, liver, and brain. Cancer stem cells (CSCs) play a critical role in LC initiation and recurrence due to their resistance to conventional treatments. Research focuses on identifying key genes and pathways associated with CSCs to develop targeted therapies. Methods. We used the GSE۱۳۴۷۸۸, GSE۸۹۲۲۹, and GSE۵۰۶۲۷ datasets, which include LCSC samples and normal control samples, to perform this work. The microarray datasets were obtained from the GEO database, and differentially expressed genes (DEGs) were discovered using the limma package analysis in R software, with p-values < ۰> ۱| as screening criteria. The DEGs of these five datasets were shared by Venn Diagram. Results. A total of ۲۲۱ DEGs that were common to at least three datasets were selected. The Gene Ontology and WikiPathways analysis were performed using the EnrichR website, and the construction of protein-protein interaction (PPI) networks and the screening of the hub gene module were performed using STRING and Cytoscape. We identified ten hub genes related to LCSC, including FOS, NFKBIA, CDKN۱A, E۲F۱, CEBPB, RAC۲, INSR, NCK۲, PRKCA, and CCNE. These genes are significantly enriched in the signaling pathways of lung cancer and are strongly associated with pathogenesis, growth, and malignancy pathways. Conclusions. We identified ten hub genes in LCSC which increase our comprehension of the molecular signature and the function of these stem cells. This achievment provides key regulatory components and identifiy novel actionable therapeutic targets that should be validated through experimental approaches.کلیدواژه ها
lung cancer, microarray, bioinformatics, gene ontology, hub geneمقالات مرتبط جدید
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