Comprehensive integrated analysis of gene expression datasets identifies key anti-cancer targets in different stages of breast cancer

Abstract

Breast cancer is one of the primary threats to women's health worldwide. However, the molecular mechanisms underlying the development of breast cancer remain to be fully elucidated. The present study aimed to investigate specific target gene expression profiles in breast cancer tissues in general and in different breast cancer stages, as well as to explore their functions in tumor development. For integrated analysis, a total of 5 gene expression profiling datasets for 3 different stages of breast cancer (stages I-III) were downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information. Pre-processing of these datasets was performed using the Robust Multi-array Average algorithm and global renormalization was performed for all studies. Differentially expressed genes between breast cancer patients and controls were estimated using the empirical Bayes algorithm. The Database for Annotation, Visualization and Integrated Discovery web server was used for analyzing the enrichment of the differentially expressed genes in Gene Ontology terms of the category biological process and in Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, breast cancer target genes were downloaded from the Thomson Reuters Integrity Database. We merged these target genes with the genes in breast cancer datasets. Analysis of anti-breast cancer gene networks was performed using the Genome-scale Integrated Analysis of Gene Networks in Tissues web server. The results demonstrated that the normal functions of the cell cycle, cell migration and cell adhesion were altered in all stages of breast cancer. Furthermore, 12 anti-breast cancer genes were identified to be dysregulated in at least one of the three stages. Among all of these genes, ribonucleotide reductase regulatory subunit M2 (RRM2) exhibited the highest degree of interaction with other interacting genes. Analysis of the network interactions revealed that the transcription factor of RRM2 is crucial for cancer development. Other genes, including mucin 1, progesterone receptor and cyclin-dependent kinase 5 regulatory subunit associated protein 3, also exhibited a high degree of interaction with the associated genes. In conclusion, several key anti-breast cancer genes identified in the present study are mainly associated with the regulation of the cell cycle, cell migration, cell adhesion and other cancer-associated cell functions, particularly RRM2.

Keywords: breast cancer; gene expression; network; ribonucleotide reductase regulatory subunit M2; target genes.

Figure 1.

Venn Diagram of enriched Gene Ontology terms in the category Biological Process in breast cancer. The four groups (unstaged cohort, stage I–III) are represented by red, blue, cyan and orange color, respectively. The unstaged cohort contained 1 stage IV sample and 23 samples without stage information.

Figure 2.

Gene expression profiles of enriched KEGG pathways in breast cancer. The 15 enriched KEGG pathways are represented by different colors. The red bars represent the upregulated genes and the blue bars represent the downregulated genes. KEGG, Kyoto Encyclopedia of Genes and Genomes; ECM, extracellular matrix; PPAR, peroxisome proliferator activated receptor. The unstaged cohort contained 1 stage IV sample and 23 samples without stage information.

Figure 3.

LogFC bar graph of mapped breast cancer-associated genes. (A) LogFC in the unstaged cohort. (B) LogFC in different stage groups. The horizontal dashed lines represent the logFC cut-off for the up- and downregulated genes. *False discovery rate-adjusted P<0.05. FC, fold change.

Figure 4.

Genome-scale integrated analysis of gene networks in breast cancer. (A) The gene interaction network of breast cancer-associated target genes (query genes) and associated genes (other genes). (B) Top 15 Gene Ontology terms in the category biological process among the breast cancer-associated genes in the network. FDR, false discovery rate.