Integrative computational approach for gene expression profiling of metastatic breast cancer

Background: Breast cancer (BC) is one of the most common cancers in women worldwide, including an estimated 570,000 deaths in 2015. More than 1.5 million women (25% of all women with cancer) are diagnosed with BC every year worldwide. BC is a metastatic cancer and usually spreads to distant organs such as bone, liver, lungs and the brain. Early detection of the disease can lead to better prognosis and higher survival rates. After genome sequencing, DNA microarray analysis has become the most widely used source of genome scale data in life sciences. Microarray's definition studies produce a large number of genetic expression and other genomics performance data, which promises to provide key information on genetic functioning and interaction within and within metabolic pathways. Aim: Prediction and functional enrichment of significant genes expressed in Breast Cancer. Materials and Methods: Microarray data for this study were downloaded from NCBI gene expression omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo), with accession number of GSE157737. It includes four different kind sets of samples, i.e., healthy control neutrophils, healthy donor monocytes, metastatic BC patient G-myeloid-derived suppressor cell (G-MDSCs) and sepsis patient G-MDSCs. The statistical method was applied to identify the differentially expressed gene (DEGs) using Limma package and significant analysis of microarray (SAM) test. Results: The top ten DEGs were identified between different sample sets using Limma package. Out of 32,321 genes, 93 genes were identified to be the significant genes through SAM test. The functional annotation of significant genes was done using different databases such as gene ontology, Kyoto Encyclopedia of Genes and Genomes and Database for Annotation, Visualisation and Integrated Discovery. Significant genes were found to be enriched in haematopoietic cell lineage pathway and the cancer-causing pathway. Conclusions: This research identifies the important genes that have function in BC and regulation of such genes and pathway can be a potential treatment for the BC and prevent the tumour growth.