MicroRNA-mediated drug resistance in breast cancer

Chemoresistance is one of the major hurdles to overcome for the successful treatment of breast cancer. At present, there are several mechanisms proposed to explain drug resistance to chemotherapeutic agents, including decreased intracellular drug concentrations, mediated by drug transporters and metabolic enzymes; impaired cellular responses that affect cell cycle arrest, apoptosis, and DNA repair; the induction of signaling pathways that promote the progression of cancer cell populations; perturbations in DNA methylation and histone modifications; and alterations in the availability of drug targets. Both genetic and epigenetic theories have been put forward to explain the mechanisms of drug resistance. Recently, a small non-coding class of RNAs, known as microRNAs, has been identified as master regulators of key genes implicated in mechanisms of chemoresistance. This article reviews the role of microRNAs in regulating chemoresistance and highlights potential therapeutic targets for reversing miRNA-mediated drug resistance. In the future, microRNA-based treatments, in combination with traditional chemotherapy, may be a new strategy for the clinical management of drug-resistant breast cancers

A mammalian microRNA expression atlas based on small RNA library sequencing.

MicroRNAs (miRNAs) are small noncoding regulatory RNAs that reduce stability and/or translation of fully or partially sequence-complementary target mRNAs. In order to identify miRNAs and to assess their expression patterns, we sequenced over 250 small RNA libraries from 26 different organ systems and cell types of human and rodents that were enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences in miRNA profiles between cell lineages and tissues. This broad survey also provides detailed and accurate information about mature sequences, precursors, genome locations, maturation processes, inferred transcriptional units, and conservation patterns. We also propose a subclassification scheme for miRNAs for assisting future experimental and computational functional analyses