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

Khurana R, Verma VK, Rawoof A, Tiwari S, Nair RA, Mahidhara G, Idris MM, Clarke AR, Kumar LD - BMC Bioinformatics (2014)

Bottom Line: 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 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Cancer Biology, Centre for Cellular & Molecular Biology, Council of scientific and Industrial Research, Hyderabad, A,P, India. lekha@ccmb.res.in

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.

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MiRNA target identification at various energy levels in different pathways. a. Target identification of microRNAs at 3 different energy levels was performed on the retrieved sequences from different oncogenic signaling pathways using miRanda. b. shows the percentage cooperation of different microRNA targets of these pathways involved in the development of breast cancer.
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Figure 4: MiRNA target identification at various energy levels in different pathways. a. Target identification of microRNAs at 3 different energy levels was performed on the retrieved sequences from different oncogenic signaling pathways using miRanda. b. shows the percentage cooperation of different microRNA targets of these pathways involved in the development of breast cancer.

Mentions: The miRanda program was used to predict microRNA targets in the various oncogenic signaling pathways. This algorithm was run at energy level EL-15 and 711 genes in human and 490 in mice were identified. The stringency level was increased by decreasing the energy levels to EL-20 and EL-25, in order to increase the accuracy and to identify fewer targets with increased specificity (Figure 4a). By computing the ratio of miRNA targets with the total number of genes in the respective pathways, the percentage cooperation among different pathways including the Notch, VEGF, Wnt, MAPK, Apoptotic and JAK-STAT pathways was deciphered and thus their potential involvement in breast cancer development. Notch signaling pathway was found to have the highest (~50%) percentage of cooperativity between the novel miRNAs and their signaling molecules compared to other pathways analyzed in both murine and human hosts (Figure 4b).


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

Khurana R, Verma VK, Rawoof A, Tiwari S, Nair RA, Mahidhara G, Idris MM, Clarke AR, Kumar LD - BMC Bioinformatics (2014)

MiRNA target identification at various energy levels in different pathways. a. Target identification of microRNAs at 3 different energy levels was performed on the retrieved sequences from different oncogenic signaling pathways using miRanda. b. shows the percentage cooperation of different microRNA targets of these pathways involved in the development of breast cancer.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3926854&req=5

Figure 4: MiRNA target identification at various energy levels in different pathways. a. Target identification of microRNAs at 3 different energy levels was performed on the retrieved sequences from different oncogenic signaling pathways using miRanda. b. shows the percentage cooperation of different microRNA targets of these pathways involved in the development of breast cancer.
Mentions: The miRanda program was used to predict microRNA targets in the various oncogenic signaling pathways. This algorithm was run at energy level EL-15 and 711 genes in human and 490 in mice were identified. The stringency level was increased by decreasing the energy levels to EL-20 and EL-25, in order to increase the accuracy and to identify fewer targets with increased specificity (Figure 4a). By computing the ratio of miRNA targets with the total number of genes in the respective pathways, the percentage cooperation among different pathways including the Notch, VEGF, Wnt, MAPK, Apoptotic and JAK-STAT pathways was deciphered and thus their potential involvement in breast cancer development. Notch signaling pathway was found to have the highest (~50%) percentage of cooperativity between the novel miRNAs and their signaling molecules compared to other pathways analyzed in both murine and human hosts (Figure 4b).

Bottom Line: 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 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Cancer Biology, Centre for Cellular & Molecular Biology, Council of scientific and Industrial Research, Hyderabad, A,P, India. lekha@ccmb.res.in

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.

Show MeSH
Related in: MedlinePlus