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Establishing reliable miRNA-cancer association network based on text-mining method.

Li L, Hu X, Yang Z, Jia Z, Fang M, Zhang L, Zhou Y - Comput Math Methods Med (2014)

Bottom Line: Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies.In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers.Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.

View Article: PubMed Central - PubMed

Affiliation: Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China ; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.

ABSTRACT
Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies. In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers. We further prioritized cancer-related miRNAs at the network level with the random-walk algorithm, achieving a relatively higher performance than previous miRNA disease networks. Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.

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Related in: MedlinePlus

Network illustrated significant associations of miRNAs and cancers. Red circles and green squares represent cancers and miRNAs, respectively, with different sizes according to the number of corresponding annotated papers (logarithmic). Each link represents a miRNA-cancer association with colour and width according to the strength of relationship.
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fig1: Network illustrated significant associations of miRNAs and cancers. Red circles and green squares represent cancers and miRNAs, respectively, with different sizes according to the number of corresponding annotated papers (logarithmic). Each link represents a miRNA-cancer association with colour and width according to the strength of relationship.

Mentions: To reveal the roles of miRNA in different cancers, we constructed a bipartite network with the top 5% associations based on Fisher's exact test P values in miCancerna, consisting of 40 miRNA families and 13 types of cancers (Figure 1). In this bipartite network, miRNAs are only connected to cancers and cancers are only connected to miRNAs. The miRNA-cancer network was visualized with Pajek (http://vlado.fmf.uni-lj.si/pub/networks/pajek/). It is interesting to find that almost all these cancers (except the stomach cancer) can be connected via miRNAs, which indicated that different cancers might share common pathogenic components regulated by  these interconnected miRNAs, while stomach cancer may be different with others.


Establishing reliable miRNA-cancer association network based on text-mining method.

Li L, Hu X, Yang Z, Jia Z, Fang M, Zhang L, Zhou Y - Comput Math Methods Med (2014)

Network illustrated significant associations of miRNAs and cancers. Red circles and green squares represent cancers and miRNAs, respectively, with different sizes according to the number of corresponding annotated papers (logarithmic). Each link represents a miRNA-cancer association with colour and width according to the strength of relationship.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016856&req=5

fig1: Network illustrated significant associations of miRNAs and cancers. Red circles and green squares represent cancers and miRNAs, respectively, with different sizes according to the number of corresponding annotated papers (logarithmic). Each link represents a miRNA-cancer association with colour and width according to the strength of relationship.
Mentions: To reveal the roles of miRNA in different cancers, we constructed a bipartite network with the top 5% associations based on Fisher's exact test P values in miCancerna, consisting of 40 miRNA families and 13 types of cancers (Figure 1). In this bipartite network, miRNAs are only connected to cancers and cancers are only connected to miRNAs. The miRNA-cancer network was visualized with Pajek (http://vlado.fmf.uni-lj.si/pub/networks/pajek/). It is interesting to find that almost all these cancers (except the stomach cancer) can be connected via miRNAs, which indicated that different cancers might share common pathogenic components regulated by  these interconnected miRNAs, while stomach cancer may be different with others.

Bottom Line: Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies.In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers.Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.

View Article: PubMed Central - PubMed

Affiliation: Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China ; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.

ABSTRACT
Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies. In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers. We further prioritized cancer-related miRNAs at the network level with the random-walk algorithm, achieving a relatively higher performance than previous miRNA disease networks. Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.

Show MeSH
Related in: MedlinePlus