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OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs

OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs Vol. 30 no. 15 2014, pages 2237–2238 BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btu155 Databases and ontologies Advance Access publication March 20, 2014 OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs Dongfang Wang, Jin Gu , Ting Wang and Zijian Ding MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China Associate Editor: Ivo Hofacker regulate different hallmarks of cancer by targeting a large set of ABSTRACT oncogenic and tumor-suppressive genes. These miRNAs are usu- Summary: MicroRNAs (miRNAs), a class of small regulatory RNAs, ally called onco-miRNAs (oncomiRs) (Esquela-Kerscher and play important roles in cancer initiation, progression and therapy. Slack, 2006; Lujambio and Lowe, 2012). MiRNAs are found to regulate diverse cancer-related processes by To facilitate the study on miRNA functions and regulatory targeting a large set of oncogenic and tumor-suppressive genes. To networks in cancer, there is a great need to establish a reference establish a high-confidence reference resource for studying the database for annotating the oncomiRs regulating different cellu- miRNA-regulated target genes and cellular processes in cancer, we lar processes and target genes in different types of cancers. There manually curated 2259 entries of cancer-related miRNA regulations are a few existing databases aiming at annotating the cancer- with direct experimental evidence from 9000 abstracts, covering related miRNAs, such as miRCancer (Xie et al., 2013), more than 300 miRNAs and 829 target genes across 25 cancer tis- PhenomiR (Ruepp et al., 2010), miR2Disease (Jiang et al., sues. A web-based portal named oncomiRDB, which provides both 2009), HMDD (Lu et al., 2008) and somamiR (Bhattacharya graphical and text-based interfaces, was developed for easily brows- et al., 2013), but they mainly collect the differentially expressed ing and searching all the annotations. It should be a useful resource miRNAs or the miRNA-associated genetic mutations in cancer for both the computational analysis and experimental study on miRNA without direct functional evidence (miR2Disease and HMDD regulatory networks and functions in cancer. include some experimentally verified entries, but the number of Availability and implementation: http://bioinfo.au.tsinghua.edu.cn/ entries is relatively small). oncomirdb/ According to the PubMed records as of March 2013, there are Contact: [email protected] 9000 publications studying the cancer-related miRNAs. This Supplementary information: Supplementary data are available at literature provides extensive information for the oncomiR func- Bioinformatics online. tions and target genes. We manually reviewed the abstracts and Received on October 1, 2013; revised on March 14, 2014; accepted curated 2259 entries of experimentally verified oncomiRs, which on March 17, 2014 either regulate one or more cancer-related cellular processes or directly target at least one gene in cancer-related processes. The miRNA expression patterns, their upstream regulators and the 1 INTRODUCTION corresponding experimental conditions are also collected from MicroRNAs (miRNAs) are a class of 22-nt endogenous small the abstracts. Then, we developed a Web-based portal regulatory RNAs, which can repress the expressions and/or oncomiRDB for storing and displaying all the curated data translations of hundreds of target genes by binding to the entries. With the graphical and text-based interfaces, users can 3 -UTRs of target gene mRNA transcripts (Bartel, 2004, easily browse and search all the entries for the oncomiRs related 2009).Till now, there are more than 2500 human miRNAs col- to different cancer types, different regulated cellular processes or lected in the latest miRBase database release (Griffiths-Jones, different target genes. OncomiRDB should be a valuable re- 2004; Kozomara and Griffiths-Jones, 2011). More than half of source for both the computational analysis and the experimental the protein-coding genes are potentially regulated by one or mul- study of miRNA functions and regulatory networks in cancer. tiple miRNAs according to the genome-wide computational pre- dictions and high-throughput experimental screens (Chi et al., 2 DATABASE CONTENT AND STATISTICS 2009; Krek et al., 2005; Lewis et al., 2005). Extensive evidence shows that miRNAs play important roles in nearly all essential To annotate the experimentally verified oncomiRs, firstly we cellular processes, such as cell proliferation, migration, differen- retrieved the abstracts studying the miRNA regulations in tiation, apoptosis and senescence. cancer from PubMed (about 9000 abstracts for the current data- Cancer, which is one of the leading causes of death worldwide, base release; the query details are provided in the Supplementary involves significant changes of chromatin structures and molecu- Material). We carefully reviewed all the abstracts and curated the lar regulatory networks. As their impacts on mRNA stability detailed information of the oncomiRs with direct experimental and translation efficiency are extensive, miRNAs are found to evidence: the miRNAs regulate at least one cancer-related cellu- lar process confirmed by perturbing their activities, such as over- *To whom correspondence should be addressed. expression using miRNA mimics or repression using antagomirs The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected] 2237 D.Wang et al. in cancer cell lines, and/or the miRNAs directly target at least 4 DISCUSSION one gene in cancer-related processes validated by luciferase re- OncomiRDB is a unique resource for annotating the experimen- porter assay (when the validation method was not described tally verified cancer-related miRNAs with direct functional evi- clearly, we further checked it within the full text). In the database dence. By comparing with several existing miRNA target content, besides the information of miRNA-regulated cellular databases, oncomiRDB can provide many new miRNA–target processes and target genes, the miRNA expression patterns, annotations validated by luciferase assay, although it focuses on the miRNA upstream regulators, the cancer types and the cor- collecting cancer-related miRNA targets (the comparison result responding experimental conditions were also collected if they is presented in Supplementary Table S1, and the detailed list can provided in the abstracts. Because of the complexity of cancer be downloaded from the database Web site). Except for the types, the detailed cancer types were grouped into 25 different direct targets, oncomiRB also collects the corresponding cancer tissues: for example, ‘non-small cell lung cancer’, ‘small miRNA cellular functions and experimental conditions from cell lung cancer’ and ‘lung adenocarcinoma’ were grouped into the literature. The graphical interface, a unique feature of ‘lung’ tissue. The latest database release contains 2259 entries oncomiRDB, can achieve better database browsing and search covering more than 300 miRNAs and 829 target genes in 25 result visualization. In summary, oncomiRDB is a high-confi- cancer tissues. To maintain the data quality, each entry was dence reference resource for studying the miRNA-regulated double-checked by at least two different curators. target genes and cellular processes in cancer. For the latest release of oncomiRDB, breast, liver, colorectum, Funding: National Basic Research Program of China lung and stomach are the most annotated cancer tissues; miR-21, [2012CB316503]; National Natural Science Foundation of let-7a, miR-34a and miR-145 are the most common oncomiRs annotated across more than 15 cancer tissues. A few others are China [61005040, 61370035, 61105003]; Tsinghua National only studied in specific cancer tissues, such as miR-122 in liver Laboratory for Information Science and Technology Cross-dis- cancer (specifically expressed in liver tissues) (Chang et al., 2004; cipline Foundation. Jopling et al., 2005). The cancer tissues and their related Conflict of Interest: none declared. miRNAs form a complex network. A set of oncogenes such as CCND1, IGF1R, CDK6, MET and BCL2 is strongly regulated by multiple tumor-suppressive miRNAs. These oncogenes are frequently overexpressed in cancer tissues, consistent with the REFERENCES global reduction of miRNA expressions (Lu et al., 2005). Bartel,D.P. (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Several chromatin modifiers, such as EZH2 and BMI1, are Cell, 116, 281–297. Bartel,D.P. (2009) MicroRNAs: target recognition and regulatory functions. Cell, also extensively regulated by several miRNAs, which suggests 136, 215–233. that miRNAs play important roles in regulating the chromatin Bhattacharya,A. et al. (2013) SomamiR: a database for somatic mutations impact- structure changes during the cancer initiation and progression. ing microRNA function in cancer. Nucleic Acids Res., 41,D977–D982. Chang,J. et al. (2004) miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and may downregulate the high affinity cationic amino acid transporter CAT-1. RNA Biol., 1, 106–113. Chi,S.W. et al. (2009) Argonaute HITS-CLIP decodes microRNA-mRNA inter- 3 USER INTERFACES action maps. Nature, 460, 479–486. Esquela-Kerscher,A. and Slack,F.J. (2006) Oncomirs—microRNAs with a role in To facilitate the database browsing and searching, we built a cancer. Nat. Rev. Cancer, 6, 259–269. Web-based portal providing both graphical and text-based inter- Griffiths-Jones,S. (2004) The microRNA registry. Nucleic Acids Res., 32, faces. The graphical interface for the ‘cancer tissue–miRNA’ net- D109–D111. Jiang,Q. et al. (2009) miR2Disease: a manually curated database for microRNA work is provided on the database main page, while the ‘miRNA– deregulation in human disease. Nucleic Acids Res., 37, D98–D104. target’ network can be generated according to any search result. Jopling,C.L. et al. (2005) Modulation of hepatitis C virus RNA abundance by a All the graphical interfaces are developed based on the liver-specific MicroRNA. Science, 309, 1577–1581. Cytoscape Web utility (Lopes et al., 2010). Kozomara,A. and Griffiths-Jones,S. (2011) miRBase: integrating microRNA anno- For the text-based interface, users can specify one or multiple tation and deep-sequencing data. Nucleic Acids Res., 39, D152–D157. Krek,A. et al. (2005) Combinatorial microRNA target predictions. Nat. Genet., 37, query conditions in the left navigation column: (i) ‘MicroRNA’: 495–500. the users can input the exact miRNA name (such as miR-21) or Lewis,B.P. et al. (2005) Conserved seed pairing, often flanked by adenosines, indi- add ‘%’ for a fuzzy search (such as miR-200% for miR-200a, cates that thousands of human genes are microRNA targets. Cell, 120, 15–20. miR-200b and miR-200c); (ii) ‘MiRNA_ID’: the users can select Lopes,C.T. et al. (2010) Cytoscape Web: an interactive web-based network browser. Bioinformatics, 26, 2347–2348. any interested miRNA with an official symbol; (iii) ‘Tissue’: spe- Lu,J. et al. (2005) MicroRNA expression profiles classify human cancers. Nature, cify one of the 25 cancer tissues; (iv) ‘Tumor’: specify any inter- 435, 834–838. ested cancer subtype; (v) ‘Target’: specify any interest target Lu,M. et al. (2008) An analysis of human microRNA and disease associations. gene; (vi) ‘Function’: specify one of the six most annotated PLoS One, 3,e3420. cancer-related cellular functions. After submitting the query, all Lujambio,A. and Lowe,S.W. (2012) The microcosmos of cancer. Nature, 482, 347–355. the matched entries will be listed. Then, the users can either Ruepp,A. et al. (2010) PhenomiR: a knowledgebase for microRNA expression in generate the miRNA–target network or download the detailed diseases and biological processes. Genome Biol., 11,R6. annotations for listed entries. A more detailed user guide can be Xie,B. et al. (2013) miRCancer: a microRNA-cancer association database con- found in the Supplementary Material. structed by text mining on literature. Bioinformatics, 29, 638–644. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bioinformatics Oxford University Press

OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs

Wang, Dongfang; Gu, Jin; Wang, Ting; Ding, Zijian
Bioinformatics , Volume 30 (15): 2 – Mar 20, 2014
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Oxford University Press
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© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected]
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1367-4803
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DOI
10.1093/bioinformatics/btu155
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24651967
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Abstract

Vol. 30 no. 15 2014, pages 2237–2238 BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btu155 Databases and ontologies Advance Access publication March 20, 2014 OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs Dongfang Wang, Jin Gu , Ting Wang and Zijian Ding MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China Associate Editor: Ivo Hofacker regulate different hallmarks of cancer by targeting a large set of ABSTRACT oncogenic and tumor-suppressive genes. These miRNAs are usu- Summary: MicroRNAs (miRNAs), a class of small regulatory RNAs, ally called onco-miRNAs (oncomiRs) (Esquela-Kerscher and play important roles in cancer initiation, progression and therapy. Slack, 2006; Lujambio and Lowe, 2012). MiRNAs are found to regulate diverse cancer-related processes by To facilitate the study on miRNA functions and regulatory targeting a large set of oncogenic and tumor-suppressive genes. To networks in cancer, there is a great need to establish a reference establish a high-confidence reference resource for studying the database for annotating the oncomiRs regulating different cellu- miRNA-regulated target genes and cellular processes in cancer, we lar processes and target genes in different types of cancers. There manually curated 2259 entries of cancer-related miRNA regulations are a few existing databases aiming at annotating the cancer- with direct experimental evidence from 9000 abstracts, covering related miRNAs, such as miRCancer (Xie et al., 2013), more than 300 miRNAs and 829 target genes across 25 cancer tis- PhenomiR (Ruepp et al., 2010), miR2Disease (Jiang et al., sues. A web-based portal named oncomiRDB, which provides both 2009), HMDD (Lu et al., 2008) and somamiR (Bhattacharya graphical and text-based interfaces, was developed for easily brows- et al., 2013), but they mainly collect the differentially expressed ing and searching all the annotations. It should be a useful resource miRNAs or the miRNA-associated genetic mutations in cancer for both the computational analysis and experimental study on miRNA without direct functional evidence (miR2Disease and HMDD regulatory networks and functions in cancer. include some experimentally verified entries, but the number of Availability and implementation: http://bioinfo.au.tsinghua.edu.cn/ entries is relatively small). oncomirdb/ According to the PubMed records as of March 2013, there are Contact: [email protected] 9000 publications studying the cancer-related miRNAs. This Supplementary information: Supplementary data are available at literature provides extensive information for the oncomiR func- Bioinformatics online. tions and target genes. We manually reviewed the abstracts and Received on October 1, 2013; revised on March 14, 2014; accepted curated 2259 entries of experimentally verified oncomiRs, which on March 17, 2014 either regulate one or more cancer-related cellular processes or directly target at least one gene in cancer-related processes. The miRNA expression patterns, their upstream regulators and the 1 INTRODUCTION corresponding experimental conditions are also collected from MicroRNAs (miRNAs) are a class of 22-nt endogenous small the abstracts. Then, we developed a Web-based portal regulatory RNAs, which can repress the expressions and/or oncomiRDB for storing and displaying all the curated data translations of hundreds of target genes by binding to the entries. With the graphical and text-based interfaces, users can 3 -UTRs of target gene mRNA transcripts (Bartel, 2004, easily browse and search all the entries for the oncomiRs related 2009).Till now, there are more than 2500 human miRNAs col- to different cancer types, different regulated cellular processes or lected in the latest miRBase database release (Griffiths-Jones, different target genes. OncomiRDB should be a valuable re- 2004; Kozomara and Griffiths-Jones, 2011). More than half of source for both the computational analysis and the experimental the protein-coding genes are potentially regulated by one or mul- study of miRNA functions and regulatory networks in cancer. tiple miRNAs according to the genome-wide computational pre- dictions and high-throughput experimental screens (Chi et al., 2 DATABASE CONTENT AND STATISTICS 2009; Krek et al., 2005; Lewis et al., 2005). Extensive evidence shows that miRNAs play important roles in nearly all essential To annotate the experimentally verified oncomiRs, firstly we cellular processes, such as cell proliferation, migration, differen- retrieved the abstracts studying the miRNA regulations in tiation, apoptosis and senescence. cancer from PubMed (about 9000 abstracts for the current data- Cancer, which is one of the leading causes of death worldwide, base release; the query details are provided in the Supplementary involves significant changes of chromatin structures and molecu- Material). We carefully reviewed all the abstracts and curated the lar regulatory networks. As their impacts on mRNA stability detailed information of the oncomiRs with direct experimental and translation efficiency are extensive, miRNAs are found to evidence: the miRNAs regulate at least one cancer-related cellu- lar process confirmed by perturbing their activities, such as over- *To whom correspondence should be addressed. expression using miRNA mimics or repression using antagomirs The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected] 2237 D.Wang et al. in cancer cell lines, and/or the miRNAs directly target at least 4 DISCUSSION one gene in cancer-related processes validated by luciferase re- OncomiRDB is a unique resource for annotating the experimen- porter assay (when the validation method was not described tally verified cancer-related miRNAs with direct functional evi- clearly, we further checked it within the full text). In the database dence. By comparing with several existing miRNA target content, besides the information of miRNA-regulated cellular databases, oncomiRDB can provide many new miRNA–target processes and target genes, the miRNA expression patterns, annotations validated by luciferase assay, although it focuses on the miRNA upstream regulators, the cancer types and the cor- collecting cancer-related miRNA targets (the comparison result responding experimental conditions were also collected if they is presented in Supplementary Table S1, and the detailed list can provided in the abstracts. Because of the complexity of cancer be downloaded from the database Web site). Except for the types, the detailed cancer types were grouped into 25 different direct targets, oncomiRB also collects the corresponding cancer tissues: for example, ‘non-small cell lung cancer’, ‘small miRNA cellular functions and experimental conditions from cell lung cancer’ and ‘lung adenocarcinoma’ were grouped into the literature. The graphical interface, a unique feature of ‘lung’ tissue. The latest database release contains 2259 entries oncomiRDB, can achieve better database browsing and search covering more than 300 miRNAs and 829 target genes in 25 result visualization. In summary, oncomiRDB is a high-confi- cancer tissues. To maintain the data quality, each entry was dence reference resource for studying the miRNA-regulated double-checked by at least two different curators. target genes and cellular processes in cancer. For the latest release of oncomiRDB, breast, liver, colorectum, Funding: National Basic Research Program of China lung and stomach are the most annotated cancer tissues; miR-21, [2012CB316503]; National Natural Science Foundation of let-7a, miR-34a and miR-145 are the most common oncomiRs annotated across more than 15 cancer tissues. A few others are China [61005040, 61370035, 61105003]; Tsinghua National only studied in specific cancer tissues, such as miR-122 in liver Laboratory for Information Science and Technology Cross-dis- cancer (specifically expressed in liver tissues) (Chang et al., 2004; cipline Foundation. Jopling et al., 2005). The cancer tissues and their related Conflict of Interest: none declared. miRNAs form a complex network. A set of oncogenes such as CCND1, IGF1R, CDK6, MET and BCL2 is strongly regulated by multiple tumor-suppressive miRNAs. These oncogenes are frequently overexpressed in cancer tissues, consistent with the REFERENCES global reduction of miRNA expressions (Lu et al., 2005). Bartel,D.P. (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Several chromatin modifiers, such as EZH2 and BMI1, are Cell, 116, 281–297. Bartel,D.P. (2009) MicroRNAs: target recognition and regulatory functions. Cell, also extensively regulated by several miRNAs, which suggests 136, 215–233. that miRNAs play important roles in regulating the chromatin Bhattacharya,A. et al. (2013) SomamiR: a database for somatic mutations impact- structure changes during the cancer initiation and progression. ing microRNA function in cancer. Nucleic Acids Res., 41,D977–D982. Chang,J. et al. (2004) miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and may downregulate the high affinity cationic amino acid transporter CAT-1. RNA Biol., 1, 106–113. Chi,S.W. et al. (2009) Argonaute HITS-CLIP decodes microRNA-mRNA inter- 3 USER INTERFACES action maps. Nature, 460, 479–486. Esquela-Kerscher,A. and Slack,F.J. (2006) Oncomirs—microRNAs with a role in To facilitate the database browsing and searching, we built a cancer. Nat. Rev. Cancer, 6, 259–269. Web-based portal providing both graphical and text-based inter- Griffiths-Jones,S. (2004) The microRNA registry. Nucleic Acids Res., 32, faces. The graphical interface for the ‘cancer tissue–miRNA’ net- D109–D111. Jiang,Q. et al. (2009) miR2Disease: a manually curated database for microRNA work is provided on the database main page, while the ‘miRNA– deregulation in human disease. Nucleic Acids Res., 37, D98–D104. target’ network can be generated according to any search result. Jopling,C.L. et al. (2005) Modulation of hepatitis C virus RNA abundance by a All the graphical interfaces are developed based on the liver-specific MicroRNA. Science, 309, 1577–1581. Cytoscape Web utility (Lopes et al., 2010). Kozomara,A. and Griffiths-Jones,S. (2011) miRBase: integrating microRNA anno- For the text-based interface, users can specify one or multiple tation and deep-sequencing data. Nucleic Acids Res., 39, D152–D157. Krek,A. et al. (2005) Combinatorial microRNA target predictions. Nat. Genet., 37, query conditions in the left navigation column: (i) ‘MicroRNA’: 495–500. the users can input the exact miRNA name (such as miR-21) or Lewis,B.P. et al. (2005) Conserved seed pairing, often flanked by adenosines, indi- add ‘%’ for a fuzzy search (such as miR-200% for miR-200a, cates that thousands of human genes are microRNA targets. Cell, 120, 15–20. miR-200b and miR-200c); (ii) ‘MiRNA_ID’: the users can select Lopes,C.T. et al. (2010) Cytoscape Web: an interactive web-based network browser. Bioinformatics, 26, 2347–2348. any interested miRNA with an official symbol; (iii) ‘Tissue’: spe- Lu,J. et al. (2005) MicroRNA expression profiles classify human cancers. Nature, cify one of the 25 cancer tissues; (iv) ‘Tumor’: specify any inter- 435, 834–838. ested cancer subtype; (v) ‘Target’: specify any interest target Lu,M. et al. (2008) An analysis of human microRNA and disease associations. gene; (vi) ‘Function’: specify one of the six most annotated PLoS One, 3,e3420. cancer-related cellular functions. After submitting the query, all Lujambio,A. and Lowe,S.W. (2012) The microcosmos of cancer. Nature, 482, 347–355. the matched entries will be listed. Then, the users can either Ruepp,A. et al. (2010) PhenomiR: a knowledgebase for microRNA expression in generate the miRNA–target network or download the detailed diseases and biological processes. Genome Biol., 11,R6. annotations for listed entries. A more detailed user guide can be Xie,B. et al. (2013) miRCancer: a microRNA-cancer association database con- found in the Supplementary Material. structed by text mining on literature. Bioinformatics, 29, 638–644.

Journal

Bioinformatics – Oxford University Press

Published: Mar 20, 2014

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