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OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer.

ABSTRACT: BACKGROUND: Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists. There is therefore an unmet need in generating bioinformatic platforms to speed the identification of novel therapeutic targets. DESCRIPTION: We describe here OncomiRdbB, a comprehensive database of oncomiRs mined from different existing databases for mouse and humans along with novel oncomiRs that we have validated in human breast cancer samples. The database also lists their respective predicted targets, identified using miRanda, along with their IDs, sequences, chromosome location and detailed description. This database facilitates querying by search strings including microRNA name, sequence, accession number, target genes and organisms. The microRNA networks and their hubs with respective targets at 3'UTR, 5'UTR and exons of different pathway genes were also deciphered using the 'R' algorithm. CONCLUSION: OncomiRdbB is a comprehensive and integrated database of oncomiRs and their targets in breast cancer with multiple query options which will help enhance both understanding of the biology of breast cancer and the development of new and innovative microRNA based diagnostic tools and targets of therapeutic significance. OncomiRdbB is freely available for download through the URL link http://tdb.ccmb.res.in/OncomiRdbB/index.htm.

SUBMITTER: Khurana R

PROVIDER: S-EPMC3926854 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer.

Khurana Rimpi R Verma Vinod Kumar VK Rawoof Abdul A Tiwari Shrish S Nair Rekha A RA Mahidhara Ganesh G Idris Mohammed M MM Clarke Alan R AR Kumar Lekha Dinesh LD

BMC bioinformatics 20140115

<h4>Background</h4>Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists. There is therefore an unmet ne ...[more]

PMID: 24428888

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Project description:Introduction: microRNAs (miRNAs) are short non-coding RNAs that negatively regulate gene expression and may play a causal role in invasive breast cancer. Since many genetic aberrations of invasive disease are detectable in earlier stages, we hypothesized that miRNA expression dysregulation and the predicted changes in gene expression would also be found in early breast neoplasias. Methods: Expression profiling of 365 miRNAs by RT-qPCR was combined with laser-capture microdissection to obtain an epithelial specific miRNA expression signature of normal breast epithelium (n=9) and of paired samples of histologically normal epithelium (HN) and ductal carcinoma in situ (DCIS) (n=16). To determine how miRNAs may control the expression of co-dysregulated mRNAs we also performed gene expression microarray analysis in the same paired HN and DCIS samples and integrated this with miRNA-target prediction. We further validated several target pairs by modulating the expression levels of miRNAs in MCF7 cells and measured the expression of target mRNAs and proteins. Results: Thirty-five miRNAs were aberrantly expressed between RM, HN and DCIS. Twenty-nine miRNAs and 420 mRNAs were aberrantly expressed between HN and DCIS. Combining these two datasets with miRNA-target prediction we identified two established target pairs (miR-195:CCND1 and miR-21:NFIB) and tested several novel miRNA:mRNA target pairs. Over-expression of the putative tumor-suppressor miR-125b, under-expressed in DCIS, repressed the expression of MEMO1, which is required for ErbB2-driven cell motility (also a target of miR-125b); and NRIP1/RIP140, which modulates the transcriptional activity of the estrogen receptor. Knockdown of the putative oncogenic miRNAs miR-182 and miR-183, both highly over-expressed in DCIS, increased the expression of CBX7 (which regulates E-cadherin expression), DOK4, NMT2, and EGR1. Augmentation of CBX7 by knockdown of miR-182 expression, in turn, positively regulated the expression of E-cadherin, a key protein involved in maintaining normal epithelial cell morphology which is commonly lost during neoplastic progression. Conclusions: These data provide the first miRNA expression profile of normal breast epithelium and of pre-invasive breast carcinoma. Further, we demonstrate that altered miRNA expression can modulate gene expression changes that characterize these early cancers. We conclude that miRNA dysregulation likely plays a substantial role in early breast cancer development. Two total samples were analyzed via Affymetrix U133A. Case numbers correspond to individual patients. Each sample is identified by case number, histologic lesion and corresponding microarray ID.

Project description:Breast cancer is one of the primary threats to women's health worldwide. However, the molecular mechanisms underlying the development of breast cancer remain to be fully elucidated. The present study aimed to investigate specific target gene expression profiles in breast cancer tissues in general and in different breast cancer stages, as well as to explore their functions in tumor development. For integrated analysis, a total of 5 gene expression profiling datasets for 3 different stages of breast cancer (stages I-III) were downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information. Pre-processing of these datasets was performed using the Robust Multi-array Average algorithm and global renormalization was performed for all studies. Differentially expressed genes between breast cancer patients and controls were estimated using the empirical Bayes algorithm. The Database for Annotation, Visualization and Integrated Discovery web server was used for analyzing the enrichment of the differentially expressed genes in Gene Ontology terms of the category biological process and in Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, breast cancer target genes were downloaded from the Thomson Reuters Integrity Database. We merged these target genes with the genes in breast cancer datasets. Analysis of anti-breast cancer gene networks was performed using the Genome-scale Integrated Analysis of Gene Networks in Tissues web server. The results demonstrated that the normal functions of the cell cycle, cell migration and cell adhesion were altered in all stages of breast cancer. Furthermore, 12 anti-breast cancer genes were identified to be dysregulated in at least one of the three stages. Among all of these genes, ribonucleotide reductase regulatory subunit M2 (RRM2) exhibited the highest degree of interaction with other interacting genes. Analysis of the network interactions revealed that the transcription factor of RRM2 is crucial for cancer development. Other genes, including mucin 1, progesterone receptor and cyclin-dependent kinase 5 regulatory subunit associated protein 3, also exhibited a high degree of interaction with the associated genes. In conclusion, several key anti-breast cancer genes identified in the present study are mainly associated with the regulation of the cell cycle, cell migration, cell adhesion and other cancer-associated cell functions, particularly RRM2.

Dataset Information

OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer.

Publications

OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer.

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