Unknown,Transcriptomics,Genomics,Proteomics

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Identification of miRNA differential expression patterns in a new model of acquired letrozole resistance

ABSTRACT: Since differential miRNA expression patterns associated with acquired AI resistance have been poorly investigated, the aim of this study was to delineate the deregulation of miRNA expression associated with letrozole response failure in a new model of letrozole resistance. For this purpose, we generated and characterized a novel cellular model of acquired resistance to letrozole (Res-Let cells) and performed microarray experiments to identify miRNAs whose expression was either deregulated between control (MCF-7aro) and resistant cells (Res-Let) or differentially expressed between the two cell lines under letrozole exposure. With the aim to select relevant miRNAs, two independent cell culture replicates were performed for each experimental condition. MCF-7aro and Res-Let cells were grown in the presence of androstenedione (AD) combined or not with letrozole. Two independent cell culture replicates for each experimental condition were used to generate total RNA. Total RNA was extracted from cell culture using a Qiagen RNA extraction kit and RNA quality was assessed using the BioAnalyzer 2100M-bM-^DM-" (Agilent Technologies). Complex probes were produced from these RNA, then hybridized to GeneChipM-BM-. miRNA 3.0 array according to the manufacturer's recommendations (Affymetrix).

ORGANISM(S): Homo sapiens

SUBMITTER: Julie Vendrell

PROVIDER: E-GEOD-43766 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Resistance to endocrine therapy agents has presented a clinical obstacle in the treatment of hormone-dependent breast cancer. Our laboratory has initiated a study of microRNA regulation of signaling pathways that may result in breast cancer progression on aromatase inhibitors (AI). Microarray analysis of microRNA expression identified 115 significantly regulated microRNAs, of which 49 microRNAs were believed to be hormone-responsive. Within the AI-resistant cells, microRNAs were differentially expressed between the steroidal and non-steroidal AI-resistant lines. Also, a group of microRNAs were inversely expressed in the AI-resistant lines versus LTEDaro and tamoxifen-resistant. We focused our work on hsa-miR-128a which was hormone-responsive and up-regulated in the letrozole-resistant cell lines. Human miR-128a was shown to negatively target TGFBRI protein expression by binding to the 3âUTR region of the gene. Loss of TGFBRI resulted in compromised sensitivity to the growth inhibitory effects of TGFB in the letrozole-resistant lines. Inhibition of endogenous miR-128a resulted in re-sensitization of the letrozole-resistant lines to TGFB growth inhibitory effects. This data suggests that the hormone-responsive miR-128a can modulate TGFB signaling and survival of the letrozole-resistant cell lines. To our knowledge, this is the first study to address the role of microRNA regulation as well as TGFB signaling in AI-resistant breast cancer cell lines. We believe that in addition to estrogen-modulation of gene expression, hormone-regulated microRNAs may provide an additional level of post-transcriptional regulation of signaling pathways critically involved in breast cancer progression and AI-resistance. To look at microRNA expression profiles of breast cancer cell lines derived from MCF-7 cells that are resistant to endocrine therapy agents. MCF-7 cells that overexpress aromatase (MCF-7aro) were cultured long-term in the presence of endocrine therapy agents until cells acquired resistance. Three different aromatase inhibitors (letrozole, anastrozole or exemestane) were used, as well as the ER antagonist tamoxifen, or the hormone-free long-term estrogen deprived cells (LTED). Three replicates of the control cells (MCF-7aro) and all resistant cells were used for microarray experiments. Total of 23 samples were analyzed by microarray.

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Identification of miRNA differential expression patterns in a new model of acquired letrozole resistance

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