4.6 Article

Specific Alterations of MicroRNA Transcriptome and Global Network Structure in Colorectal Carcinoma after Cetuximab Treatment

Journal

MOLECULAR CANCER THERAPEUTICS
Volume 9, Issue 12, Pages 3396-3409

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1535-7163.MCT-10-0137

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  1. Ministero dell'Universita e della Ricerca Scientifica e Tecnologica

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The relationship between therapeutic response and modifications of microRNA (miRNA) transcriptome in colorectal cancer (CRC) remains unknown. We investigated this issue by profiling the expression of 667 miRNAs in 2 human CRC cell lines, one sensitive and the other resistant to cetuximab (Caco-2 and HCT-116, respectively), through TaqMan real-time PCR. Caco-2 and HCT-116 expressed different sets of miRNAs after treatment. Specifically, 21 and 22 miRNAs were differentially expressed in Caco-2 or HCT-116, respectively (t test, P < 0.01). By testing the expression of differentially expressed miRNAs in CRC patients, we found that miR-146b-3p and miR-486-5p are more abundant in K-ras-mutated samples with respect to wild-type ones (Wilcoxon test, P < 0.05). Sixty-seven percent of differentially expressed miRNAs were involved in cancer, including CRC, whereas 19 miRNA targets had been previously reported to be involved in the cetuximab pathway and CRC. We identified 25 transcription factors putatively controlling these miRNAs, 11 of which have been already reported to be involved in CRC. On the basis of these data, we suggest that the downregulation of let-7b and let-7e (targeting K-ras) and the upregulation of miR-17* (a CRC marker) could be considered as candidate molecular markers of cetuximab resistance. Global network functional analysis (based on miRNA targets) showed a significant overrepresentation of cancer-related biological processes and networks centered on critical nodes involved in epidermal growth factor receptor internalization and ubiquitin-mediated degradation. The identification of miRNAs, whose expression is linked to the efficacy of therapy, should allow the ability to predict the response of patients to treatment and possibly lead to a better understanding of the molecular mechanisms of drug response. Mol Cancer Ther; 9(12); 3396-409. (C) 2010 AACR.

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