Sun E-H, Zhou Q, Liu K-S, Wei W, Wang C-M, Liu X-F, Lu C, Ma D-Y
State key Laboratory of Reproductive Medicine, Department of Breast, Nanjing Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Nanjing, China.
Eur Rev Med Pharmacol Sci. 2014 Oct;18(19):2783-8.
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.
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.
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.
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.
本研究旨在筛选与乳腺癌不同亚型相关的微小RNA（miRNA）及其靶基因，以鉴定肿瘤亚型的新标志物。
从基因表达综合数据库（GEO）下载乳腺癌GSE38867的miRNA表达谱，包括7例原位导管癌样本、7例浸润性乳腺癌样本、7例转移性乳腺癌样本和7例正常乳腺样本。应用R软件中的Limma软件包鉴定乳腺癌不同亚型的特异性差异表达miRNA。使用MicroRNA.org数据库来源预测鉴定出的差异表达miRNA的靶基因。我们将靶基因及其相互作用基因（由STRING预测）整合到DAVID中进行基因本体（GO）功能和京都基因与基因组百科全书（KEGG）通路分析。
与正常对照相比，在原位导管癌、浸润性和转移性乳腺癌中分别筛选出21、47和107个差异表达的miRNA。鉴定出三种亚型的特异性差异表达miRNA，原位导管癌的hsa-miR-99a和hsa-miR-151-3p，浸润性乳腺癌的hsa-miR-145和hsa-miR-210，以及转移性乳腺癌的has-miR-205和has-miR-361-5p。此外，预测了特异性miRNA靶标的220、43、446、307、587和328个相互作用对。多个GO功能和KEGG通路在miRNA靶标及其相互作用基因中富集。
我们筛选出了三种不同亚型乳腺癌中最具代表性的miRNA，它们可能作为不同亚型乳腺癌诊断的推定标志物。
