Abstract 1545: Identification of microRNA targets in triple-negative breast cancer
Authors: Mandeep Gill, Bruna Sugita, Silma R. Pereira, Catalin Marian, Xi Li, Yuriy Gusev, Enilze MSF Ribeiro, Iglenir J. Cavalli, Luciane R. Cavalli
Journal: Cancer Research (2014)

Abstract Introduction: Triple negative breast cancers (TNBC) are clinically aggressive tumors that lack the expression of ER, PR and HER2 receptors, and therefore do not respond effectively to the available target therapies. The study of the molecular alterations that are present in these tumors can lead to the identification of potential therapeutic targets that can improve patient's outcome. MicroRNAs (miRNAs) are short non-coding sequences that play a role in breast tumorigenesis regulating the expression of cancer-associated genes. In the present study, we investigated miRNAs expression profile in TNBC and non-TNBC tumors and integrated the data with DNA copy number changes (array-CGH) obtained from the same samples, to obtain the most relevant miRNA targets that may be involved in the pathogenesis of TNBC. Methods: Formalin-fixed paraffin-embedded samples from 43 TNBC and 16 non-TNBC cases were profiled for miRNA using the Nanostring system. Significant differentially expressed miRNAs (with at least 2 fold differences and p≤0.05) between the lesions were calculated by the comparative Ct method (ΔΔCt). DNA copy number analysis from the same samples was performed using an Agilent array-CGH platform. The miRNA data was directly integrated with the array-CGH data from the same cases. Combinatorial target predicted algorithms in conjunction with functional and pathway annotation enrichment systems (Ingenuity Pathway, Pathway Studio) were performed to identify predicted target functions. Results: The miRNA profiling revealed 89 miRNAs significant differentially expressed between the TNBC and non-TNBC lesions. Using miRBase and MiRDB target prediction databases we identified 3,378 target genes of upregulated miRNAs and 823 for downregulated miRNAs. A number of 15 miRNAs (out of the 89) presented concomintant genomic gains or losses and miRNA increase or decrease expression, respectively. This direct integration of the data reduced the number of miRNA targets to 1,242. Ingenuity pathway analysis on these predicted targets function, identified canonical pathways, including p53, IL-8 and Rac signaling. Gene expression profiling analysis is underway to confirm the regulatory effect of the selected miRNAs on the targets identified. Conclusions: We have observed significant differentially expressed miRNAs in the analysis of TNBC cases in comparison with non-TNBC cases. The integration analysis with DNA copy number data let us to select the miRNAs with concomitant changes in copy number and gene expression and predicted target algorithms identified key pathways that may be related to the TNBC phenotype. The functional validation of these targets, by in vitro and in vivo experimental models, through the assessment of miRNA-mRNA interaction and/or modulation of miRNA expression will allow us to identify the most relevant miRNAs that are mechanistically involved in the pathogenesis of TNBC. Note: This abstract was not presented at the meeting. Citation Format: Mandeep Gill, Bruna Sugita, Silma R. Pereira, Catalin Marian, Xi Li, Yuriy Gusev, Enilze MSF Ribeiro, Iglenir J. Cavalli, Luciane R. Cavalli. Identification of microRNA targets in triple-negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1545. doi:10.1158/1538-7445.AM2014-1545