Ductal carcinoma in situ and invasive breast cancer-based differential gene expression study for therapeutic development

Abstract

Objective: Breast cancer is the second most common cancer in women globally. Multiple inherited mutations in genes are predominantly associated with breast cancer. The gene expression profiling of breast tumors generated by DNA microarray analysis provides molecular phenotyping that determines and characterizes the classifications of these tumors. Methods: In this work, we used gene expression profiling of breast cancer samples from Gene Expression Omnibus (GEO) database. The dataset GSE41194, retrieved from GEO, was used to investigate differential gene expression in ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC). The dataset contains 26 DCIS and 24 IBC samples. The data were analyzed in R and Bioconductor. To normalize the data Robust Multiarray Average (RMA) method was applied, limma software was used to identify the differentially expressed genes (DEGs) in DCIS and IBC; an adjusted p value ≤0.05 was used to filter differentially expressed probe sets, and a fold change (FC) ≥ 2 to identify upregulated and ≤−2 for downregulated genes. The DEGs retrieved were clustered and annotated using Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources with an EASE score ≤0.1 and count 2. Results: The analysis obtained 72 DEGs with a p≤0.05. The FC≥2 identified 38 upregulated probesets and FC≤−2 identified 34 downregulated probe sets. The up and downregulated genes obtained in various comparisons were characterized based on gene ontology (GO) and pathway analyses in DAVID, which retrieved six genes that had principal pathways targeting breast cancer. Conclusion: Identification of these genes and pathways enhances the knowledge and progression of DCIS to IBC; paving a novel way for developing new therapies for treating patients with breast cancer.