Differencial expression genes and ceRNA network by microarray analysis in the breast cancer samples
Differencial expression genes and ceRNA network by microarray analysis in the breast cancer samples
Mehrnoush Rishehri,1Mohammad rezaei,2Mansoureh Azadeh,3,*
1. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran 2. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran 3. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
Introduction: Colorectal cancer (CRC) is the third most common cancer, influencing both colon and rectum (large intestine) through aberrant cell proliferation. (Rad et al., 2020). Therefore, this study aimed to identify potential diagnostic markers for CRC (Xie et al.,2021). Among them aberrant expressions of lncRNAs, miRNAs showe the close correlations in occurrence, development of CRC (Tang et al., 2019).
Methods: Rawdata of GSE113513 dataset from NCBI Gene Expression Omnibus (GEO) was normalayzed via limma and affy packages of R programming and figures from up and down expression (DEGs) were drawn by pheatmap (Fig.1), ggplot2 (Fig.2) and gplots (Fig.3) packages in the micoarray analysis. In addition, mRNA has been chosen as differencial expression gene. Finally, mRNA can to establish a ceRNA network with microRNA and lncRNA using miRWalk2.0, LncRRIsearch-rtools V.1.00 and DIANA-LncBase V.2 databases.
Results: the GSE113513 microarray dataset was used to identify differentially expressed genes (DEGs) between fourteen pairs CRC tissues and noncancerous tissues based on GEO. SFN gene chose as differentially expressed gene, which can to establish a novel ceRNA network (LINC00319 - SFN - hsa-miR-661), that hsa-miR-661 and LINC00319 targeting SFN gene, and LINC00319 has interaction with hsa-miR-661.
Conclusion: In summary,this findings could be suggested a novel interactions among lncRNAs, miRNAs and mRNA for the candidate diagnostic and prognostic markers associated with CRC by bioinformatics analysis.