E-H Sun1, Q Zhou, K-S Liu, W Wei, C-M Wang, X-F Liu, C Lu, D-Y Ma. 1. State key Laboratory of Reproductive Medicine, Department of Breast, Nanjing Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Nanjing, China. wanglmeill@hotmail.com.
Abstract
AIM: The aim of this study was to screen miRNAs related to different subtypes of breast cancer and their target genes to identify new markers of tumor subtype. MATERIALS AND METHODS: The miRNA expression profiles of breast cancer GSE38867 including 7 ductal carcinoma in situ breast (DCIS) cancer samples, 7 invasive breast cancer samples, 7 metastatic breast cancer samples, and 7 normal breast samples) were downloaded from Gene Expression Omnibus (GEO) database. Limma package in R software was applied to identify specific differentially expressed miRNAs of different subtypes of breast cancer. MicroRNA.org database source was used to predict the target genes of the identified differentially expressed miRNAs. We integrated the target genes and their interacted genes (predicted by STRING) into DAVID to perform the GO function and KEGG pathway analyses. RESULTS: Compared to the normal control, a total of 21, 47, and 107 differentially expressed miRNAs were screened in DCIS, invasive and metastatic breast cancer, respectively. Specific differentially expressed miRNAs of the three subtypes were identified, including hsa-miR-99a and hsa-miR-151-3p for DCIS breast cancer, hsa-miR-145 and hsa-miR-210 for invasive breast cancer, and has-miR-205 and has-miR-361-5p metastatic breast cancer. Furthermore, 220, 43, 446, 307, 587 and 328 interaction pairs of the specific miRNA targets were predicted. Multiple GO functions and KEGG pathways were enriched with the miRNA targets and their interacted genes. CONCLUSIONS: We screened the most representative miRNAs of the three different subtypes of breast cancer, which may act as the putative markers in the diagnosis of different subtypes of breast cancer.
AIM: The aim of this study was to screen miRNAs related to different subtypes of breast cancer and their target genes to identify new markers of tumor subtype. MATERIALS AND METHODS: The miRNA expression profiles of breast cancer GSE38867 including 7 ductal carcinoma in situ breast (DCIS) cancer samples, 7 invasive breast cancer samples, 7 metastatic breast cancer samples, and 7 normal breast samples) were downloaded from Gene Expression Omnibus (GEO) database. Limma package in R software was applied to identify specific differentially expressed miRNAs of different subtypes of breast cancer. MicroRNA.org database source was used to predict the target genes of the identified differentially expressed miRNAs. We integrated the target genes and their interacted genes (predicted by STRING) into DAVID to perform the GO function and KEGG pathway analyses. RESULTS: Compared to the normal control, a total of 21, 47, and 107 differentially expressed miRNAs were screened in DCIS, invasive and metastatic breast cancer, respectively. Specific differentially expressed miRNAs of the three subtypes were identified, including hsa-miR-99a and hsa-miR-151-3p for DCIS breast cancer, hsa-miR-145 and hsa-miR-210 for invasive breast cancer, and has-miR-205 and has-miR-361-5p metastatic breast cancer. Furthermore, 220, 43, 446, 307, 587 and 328 interaction pairs of the specific miRNA targets were predicted. Multiple GO functions and KEGG pathways were enriched with the miRNA targets and their interacted genes. CONCLUSIONS: We screened the most representative miRNAs of the three different subtypes of breast cancer, which may act as the putative markers in the diagnosis of different subtypes of breast cancer.