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Discovery of novel human breast cancer microRNAs from deep sequencing data by analysis of pri-microRNA secondary structures.

ABSTRACT: MicroRNAs (miRNAs) are key regulators of gene expression and contribute to a variety of biological processes. Abnormal miRNA expression has been reported in various diseases including pathophysiology of breast cancer, where they regulate protumorigenic processes including vascular invasiveness, estrogen receptor status, chemotherapy resistance, invasion and metastasis. The miRBase sequence database, a public repository for newly discovered miRNAs, has grown rapidly with approximately >10,000 entries to date. Despite this rapid growth, many miRNAs have not yet been validated, and several others are yet to be identified. A lack of a full complement of miRNAs has imposed limitations on recognizing their important roles in cancer, including breast cancer. Using deep sequencing technology, we have identified 189 candidate novel microRNAs in human breast cancer cell lines with diverse tumorigenic potential. We further show that analysis of 500-nucleotide pri-microRNA secondary structure constitutes a reliable method to predict bona fide miRNAs as judged by experimental validation. Candidate novel breast cancer miRNAs with stem lengths of greater than 30 bp resulted in the generation of precursor and mature sequences in vivo. On the other hand, candidates with stem length less than 30 bp were less efficient in producing mature miRNA. This approach may be used to predict which candidate novel miRNA would qualify as bona fide miRNAs from deep sequencing data with approximately 90% accuracy.

SUBMITTER: Ryu S

PROVIDER: S-EPMC3035615 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Discovery of novel human breast cancer microRNAs from deep sequencing data by analysis of pri-microRNA secondary structures.

Ryu Seongho S Joshi Natasha N McDonnell Kevin K Woo Jongchan J Choi Hyejin H Gao Dingcheng D McCombie William R WR Mittal Vivek V

PloS one 20110208 2

MicroRNAs (miRNAs) are key regulators of gene expression and contribute to a variety of biological processes. Abnormal miRNA expression has been reported in various diseases including pathophysiology of breast cancer, where they regulate protumorigenic processes including vascular invasiveness, estrogen receptor status, chemotherapy resistance, invasion and metastasis. The miRBase sequence database, a public repository for newly discovered miRNAs, has grown rapidly with approximately >10,000 ent ...[more]

PMID: 21346806

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Project description:MicroRNAs (miRNAs) regulate many genes critical for tumorigenesis. We profiled miRNAs from 11 normal breast tissues, 17 non-invasive, 151 invasive breast carcinomas, and 6 cell lines by in-house-developed barcoded Solexa sequencing. miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed-sequence-dependent miRNA-target regulation. Unsupervised clustering of samples by miRNA sequence families best reflected the clustering based on mRNA expression available for this sample set. Clustering and comparative analysis of miRNA read frequencies showed that normal breast samples were separated from most non-invasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families (including mir-98/let-7), with most miRNA changes apparent already in the non-invasive carcinomas. In addition, patients that went on to develop metastasis demonstrated increased expression of mir-423, and triple negative breast carcinomas were most distinct from other tumor subtypes due to up-regulation of the mir-17~92 cluster. However, absolute miRNA levels between normal breast and carcinomas did not reveal any significant differences. We also discovered two polymorphic nucleotide variations among the more abundant miRNAs miR-181a (T19G) and miR-185 (T16G), but we did not identify nucleotide variations expected for classical tumor suppressor function associated with miRNAs. The differentiation of tumor subtypes and prediction of metastasis based on miRNA levels is statistically possible, but is not driven by deregulation of abundant miRNAs, implicating far fewer miRNAs in tumorigenic processes than previously suggested. 21 barcoded sequencing runs, including 185 unique samples and 54 samples in replicate (6 in triplicate and the remaining in duplicate). The details of each sample can be found in Supplementary Tables S1 and S2.

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Discovery of novel human breast cancer microRNAs from deep sequencing data by analysis of pri-microRNA secondary structures.

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Discovery of novel human breast cancer microRNAs from deep sequencing data by analysis of pri-microRNA secondary structures.

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