Abstract P5-10-12: Differences in microRNA expression patterns in breast cancer and triple negative tumors.
Authors: Romero-Cordoba SL , Rebollar-Vega RG , Quintanar-Jurado V , Rodriguez-Cuevas S , Bautista-Pina V , Maffuz-Aziz A , Hidalgo-Miranda A 
Published: August 2014

Abstract
Heterogeneity of breast cancer can be classified according to different molecular signatures, including gene expression profiles that differentiate breast cancer into 5 clinically relevant subtypes: luminal A, luminal B, Her2-like, basal-like and claudin-low. Additionally the expression patterns of gene expression regulators like microRNAs can separate normal tissue from breast tumors, however there is currently limited information about the potential differences in microRNA expression profiles between the different tumor subtypes defined by gene expression. In order to determine microRNA expression profiles in breast tumors, and explore differences in the expression patterns of these molecules between different cancer subtypes, we analyzed the expression of 664 microRNAs with the TaqMan low-density array platform in 40 breast tumors from different subtypes. Tumor sub-typing was carried out with the PAM50 algorithm in expression data obtained with the Affymetrix Human Gene ST 1.0 array, obtaining 8 Luminal A tumors, 9 luminal B, 8 Her2-like and 3 Triple negative basal-like tumors, along with a set of microRNAs that distinguish each tumor subtype. Bioinformatic analysis of mRNA targets of the differentially expressed miRNAs, identified oncogenes like ERBB2, YY1, several MAP kinases, and known tumor-suppressors like FOXA1 and SMAD4. Pathway analysis identified that some biological process that are important in breast carcinogenesis are affected by the altered miRNA expression, including signaling through MAP kinases, RAS, programmed cell death and ERBB2-ERBB3 signaling. Given the clinical importance of the triple negative tumors, we included 48 additional triple-negative tumors defined by immunohistochemistry, to analyze the intra-heterogeneity of these phenotype based in the microRNA expression profiles. After the bioinformatics analysis with the algorithm Consensus Clustering we determined 6 sub-groups of triple negative tumors with different molecular, inmunophenotypical and clinical issues. We also compared the microRNA expression patterns between triple negative and other inmunophenotype (ER+, PR+, Her2+) tumors, detecting 56 differentially expressed microRNAs. Transcriptional targets of these microRNAs include genes involved in the carcinogenesis of triple negative tumors, like PARP1, or in the microRNA biogenesis machinery, like Dicer. Enrichment ontology analysis of the microRNAs differentially expressed in the triple negative tumors, detected pathways like p53 and focal adhesion whose role in cancer development, invasion and metastasis might be crucial; and MAPK, which has been related to recurrence of TN tumors. Immunochemistry analysis on the microRNA biogenesis machinery including Dicer and Argonaute2 revels a down-regulation (approximately 20% less) of both proteins, mainly in TN tumors. Our data identified the altered expression of microRNAs whose aberrant expression might have an important impact on cancer-related cellular pathways and whose role in breast cancer has not been previously described. microRNAs expression is also capable to discriminate between different tumor subtypes and to determine microRNAs that classifies triple negative tumors into different subgroups.
Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-10-12.