Differential genes expression and co-expression network analysis in colorectal cancer: A new approach to identify therapeutic targets
- سال انتشار: 1403
- محل انتشار: دومین کنگره بین المللی کنسرژنومیکس
- کد COI اختصاصی: ICGCS02_459
- زبان مقاله: انگلیسی
- تعداد مشاهده: 87
نویسندگان
Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran
Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran
چکیده
Colorectal cancer is the third most common cancer and the fourth cause of death in the world. It is very helpful to understand this disease with genetic factors by using systems biology and co-expression network approaches. Many studies have used these approaches to determine the prognosis and treatment of this disease. methods This study was conducted in the bioinformatics phase. First, the RNA sequencing data related to CRC and normal were downloaded from the GEO under accession number GSE۲۲۳۱۱۹. After examining the differential expression of genes with the DESeq۲ package, the co-expression network was reconstructed by the WGCNA package. Key genes involved in the pathogenesis of CRC were finally identified from the shared genes obtained from the stage of differential expression of genes and co-expression network and functional analysis of enrichment through GSEA and EnrichR pathways. Results Examining the differential expression of genes showed that ۵۴۹۸ genes with filters of |log۲FC|> ۱ and adjusted p-value < ۰.۰۵ had expression changes. In co-expression network analysis, the bisque۴ module was selected as the key module in CRC incidence with a correlation of ۰.۹ and p-value = ۱e-۱۴. Finally, several genes and lncRNAs were chosen as key genes from the commonalities between differential expression analysis of genes and co-expression network and investigation of functional enrichment pathways. Some of the genes we have reached in this study can be mentioned as TLX۱NB, HOTAIR, VPS۹D۱-AS۱, GOLGA۶L۲۵, SPMIP۱, CD۳۰۰LD, MRPL۲۳-AS۱, LOC۱۰۰۱۳۴۸۶۸, LINC۰۲۴۱۸, TROAP, TONSL-AS۱, SMKR۱, and LNCOC۱. Conclusion Using advanced data analysis methods, we identified several important genes that play an essential role in the disease process. These genes are known as effective factors in cancer progression and can also be considered as new therapeutic targets. Our findings can have significant clinical implications, especially in the field of developing target-based therapies and improving treatment outcomes for patients with colorectal cancer.کلیدواژه ها
Colorectal cancer, WGCNA ,Biomarkers, Systems biologyمقالات مرتبط جدید
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