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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Using microRNA Networks to Understand Cancer

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Autor(es):
Dragomir, Mihnea [1, 2, 3] ; Mafra, Ana Carolina P. [4, 5, 1] ; Dias, Sandra M. G. [4, 5] ; Vasilescu, Catalin [2] ; Calin, George A. [1, 6]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Texas MD Anderson Canc Ctr, Dept Expt Therapeut, 1515 Holcombe Blvd Unit 1950, Houston, TX 77030 - USA
[2] Univ Med & Pharm Carol Davila, Dept Surg, Fundeni Hosp, Sos Fundeni 258, Sect 2, Bucharest 022328 - Romania
[3] Univ Med & Pharm Iuliu Hatieganu, Res Ctr Funct Genom Biomed & Translat Med, Str Gh Marinescu 23, Cluj Napoca 400012 - Romania
[4] Brazilian Ctr Res Energy & Mat CNPEM, Brazilian Biosci Natl Lab LNBio, Rua Giuseppe Maximo Scolfaro 10000, BR-13083970 Campinas, SP - Brazil
[5] Univ Campinas UNICAMP, Inst Biol, Dept Genet Evolut & Bioagents, POB 6109, BR-13083970 Campinas, SP - Brazil
[6] Univ Texas MD Anderson Canc Ctr, Ctr RNA Inference & Noncoding RNAs, 1515 Holcombe Blvd Unit 1950, Houston, TX 77030 - USA
Número total de Afiliações: 6
Tipo de documento: Artigo de Revisão
Fonte: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES; v. 19, n. 7 JUL 2018.
Citações Web of Science: 15
Resumo

Human cancers are characterized by deregulated expression of multiple microRNAs (miRNAs), involved in essential pathways that confer the malignant cells their tumorigenic potential. Each miRNA can regulate hundreds of messenger RNAs (mRNAs), while various miRNAs can control the same mRNA. Additionally, many miRNAs regulate and are regulated by other species of non-coding RNAs, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs). For this reason, it is extremely difficult to predict, study, and analyze the precise role of a single miRNA involved in human cancer, considering the complexity of its connections. Focusing on a single miRNA molecule represents a limited approach. Additional information could come from network analysis, which has become a common tool in the biological field to better understand molecular interactions. In this review, we focus on the main types of networks (monopartite, association networks and bipartite) used for analyzing biological data related to miRNA function. We briefly present the important steps to take when generating networks, illustrating the theory with published examples and with future perspectives of how this approach can help to better select miRNAs that can be therapeutically targeted in cancer. (AU)

Processo FAPESP: 15/25832-4 - Controle genético e epigenético comandado pelo metabolismo celular
Beneficiário:Sandra Martha Gomes Dias
Linha de fomento: Auxílio à Pesquisa - Regular