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Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using text-mining Approach

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Big Data mining and Analytics 2024年第1期7卷 107-130页

作者： Nadezhda Yu.Biziukova Sergey M.Ivanov Oga A.Tarasova Department of Bioinformatics Institute of Biomedical ChemistryMoscow 119121Russia Department of Bioinformatics Pirogov Russian National Research Medical UniversityMoscow 117997Russia

Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches.One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development.Systematic accumulation of various types of biological data,including interactions between proteins,regulation of genes transcription,proteomics,and metabolomics experiments results,allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets.The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components,as well as for identifying their roles in the development of various types of tumors.We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database.For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach,while for all other proteins and genes machine learning method is used.For association extraction,we develop a set of semantic rules.We complete the results of the text analysis with the gene set enrichment analysis.The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.

关键词： text-mining data mining Hedgehog pathway neoplastic processes enrichment analysis pathology molecularmechanisms

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Kaphta:text mining web tool to extract information on the anticancer activity of polyphenols

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Journal of Polyphenols 2022年第2期4卷 87-100页

作者： Ramon Gustavo Teodoro Marques da Silva Samuel Lucas Santos Gomes Paulo Muniz deÁvila Gustavo Joséda Silva Ana Lucia Fachin Edilson Carlos Caritá Mozart Marins Biotechnology Unit University of Ribeirão PretoAv.Costábile Romano 2201Ribeirão PretoSP 14096-900Brazil Federal Institute of Education Science and Technology of South of Minas Gerais–IFSULDEMINASPouso AlegreMG 37550-000Brazil Medicine School University of Ribeirão PretoRibeirão PretoSP 14096-900Brazil Centro de Ciências Exatas Naturais e TecnológicasUniversidade de Ribeirão PretoRibeirão Preto SP 14096-900Brazil

In this paper,we describe the application of Kaphta architecture,a resource for text mining of the anticancer activity of polyphenols.The anticancer activity of these compounds against different types of cancer has been widely reported in the literature and they are one of the most promising molecules for the development of anticancer drugs.The architecture,which comprises four sequential and well-defined steps,uses a hybrid approach composed of a dictionary,rules and machine learning to identify abstracts containing sentences with associations between polyphenol,cancer and gene entities.The application of the architecture on 23826 PubMed abstracts generated a knowledge base of indexed abstracts with 172169 sentences containing,polyphenol-cancer and polyphenol-gene associations.A Web tool was implemented that allowed the user to search for information on 2006 polyphenols,240 cancers and 3121 genes entities,and 11750 polyphenol-cancer and 9160 polyphenol-gene associations indexed in the knowledge base.A ranking algorithm calculates scores for each indexed abstract considering the number and type of sentences with entities and rules recognized.A test with users demonstrated that the visualization resources on the web tool contributes to the understanding of the association between polyphenols,genes and cancers,in comparison with the PubMed Tool.The Kaphta architecture and web tool permits to extract knowledge on the anticancer activity of polyphenols and can thus contribute to the exploration of these molecules in the development of anticancer therapies.

关键词： polyphenols cancer text-mining

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Melatonin modifies SOX2^+ cell proliferation in dentate gyrus and modulates SIRT1 and MECP2 in long-term sleep deprivation

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Neural Regeneration Research 2019年第10期14卷 1787-1795页

作者： Alan Hinojosa-Godínez Luis F. Jave-Suarez Mario Flores-Soto Alma Y. Gálvez-Contreras Sonia Luquín Edith Oregon-Romero Oscar González-Pérez Rocio E. González-Castaneda Laboratorio de Microscopía de Alta Resolución Departamento de NeurocienciasCentro Universitario de Ciencias de la SaludUniversidad de GuadalajaraGuadalajaraMéxico Laboratorio de Neurociencias Facultad de PsicologíaUniversidad de ColimaColimaMéxico División de Inmunología Centro de Investigación Biomédica de OccidenteInstituto Mexicano del Seguro SocialGuadalajaraMéxico División de Neurociencias Centro de Investigación Biomédica de OccidenteInstituto Mexicano del Seguro SocialGuadalajaraMéxico Instituto de Investigación en Ciencias Biomédicas (IICB) Departamento de Biología Molecular y GenómicaCentro Universitario de Ciencias de la SaludUniversidad de GuadalajaraGuadalajaraMéxico Unidad de Atención en Neurociencias Departamento de Neurociencias. Centro Universitario de Ciencias de la SaludUniversidad de GuadalajaraGuadalajaraMéxico

Melatonin is a pleiotropic molecule that,after a short-term sleep deprivation,promotes the proliferation of neural stem cells in the adult hippocampus.However,this effect has not been observed in long-term sleep deprivation.The precise mechanism exerted by melatonin on the modulation of neural stem cells is not entirely elucidated,but evidence indicates that epigenetic regulators may be involved in this process.In this study,we investigated the effect of melatonin treatment during a 96-hour sleep deprivation and analyzed the expression of epigenetic modulators predicted by computational text mining and keyword clusterization.Our results showed that the administration of melatonin under sleep-deprived conditions increased the MECP2 expression and reduced the SIRT1 expression in the dentate gyrus.We observed that let-7 b,mir-132,and mir-124 were highly expressed in the dentate gyrus after melatonin administration,but they were not modified by sleep deprivation.In addition,we found more Sox2^+/5-bromo-2’-deoxyuridine(BrdU)^+cells in the subgranular zone of the sleep-deprived group treated with melatonin than in the untreated group.These findings may support the notion that melatonin modifies the expression of epigenetic mediators that,in turn,regulate the proliferation of neural progenitor cells in the adult dentate gyrus under long-term sleep-deprived conditions.All procedures performed in this study were approved by the Animal Ethics Committee of the University of Guadalajara,Mexico(approval No.CI-16610)on January 2,2016.

关键词： sleep-deprivation melatonin microRNA neurogenesis Sirtuin 1 SIRT1 methyl-CpG-binding protein 2 MECP2 epigenetic text-mining mir-9 let-7b

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