1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Identification of genes with significant differential expression in breast cancer patients using transcriptome data analysis
Paper ID : 1079-ICB10
Authors:
pegah mahbobnia1, Mostafa Rafiepour1, Reza Mahdian2, Farinaz Behfarjam *1
1Department of Genetics, Faculty of Science, Danesh Alborz University, Qazvin, Iran
2Molecular Medicine Department, Biotechnology Research Center, Pasteur Institute of Iran
Abstract:
Abstract
Background: Breast cancer is a common cancer that starts in the breast tissue. This disease is the most common cancer in women worldwide with a poor prognosis due to its aggressive biological behaviour and lack of therapeutic targets [1, 2]. Therefore, identifying the key genes involved in potential initiation and progression mechanisms of breast cancer can be useful in the diagnosis, prognosis and treatment of this disease [3]. Accordingly, the aim of the present study was to identify some novel genes with significant differential expression affecting breast cancer patients through bioinformatics analysis.
Materials and Methods: Illumina-sequenced transcript data from three samples with breast cancer and four healthy individuals as control were collected from the NCBI database, and after controlling the quality of the readings with FastQC program [4], the reads alignment were performed with reference genomes by STAR software [5]. Then, data features were evaluated using featureCounts program. DESeq2 software [6] was used to identify the genes with differential expression between breast cancer samples and healthy individuals as control. Finally, Volcano graph, bar plot and point diagrams were traced to determine genes with significant differential expression.
Results: RNA sequencing data analysis between patients with breast cancer and healthy individuals showed valuable results. The results of these study were identified 11 downregulated differentially expressed genes (DEGs) and 20 upregulated DEGs. Among the key genes of this study can be noticed RNF223, ETV3L, CACNA1S, UPS34, NEURL3, CRYBG3 and FABP4 and other important genes such as CCL20, CXCL5, CEP295 and FLG2 that significantly associated with breast cancer pathogenesis.
Conclusion: In this study, we found some key genes with important roles in the pathways and molecular mechanisms involved in the pathogenesis of breast cancer that can be candidate targets for diagnostic, therapeutic and preventive purposes.
Keywords:
Keywords: Breast cancer; Differential gene expression; Transcriptome; Bioinformatics; NCBI.
Status : Paper Accepted (Poster Presentation)