Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods

Detalhes bibliográficos
Autor(a) principal: Martins, Sofia
Data de Publicação: 2023
Outros Autores: Coletti, Roberta, Lopes, Marta B.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164089
Resumo: Publisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature.
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spelling Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methodsBiomarkersGliomaJoint graphical lassoRobust sparse K-means clusteringSparse networksTranscriptomicsBiochemistryMolecular BiologyGeneticsComputer Science ApplicationsComputational Theory and MathematicsComputational MathematicsSDG 3 - Good Health and Well-beingPublisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature.Gliomas are primary malignant brain tumors with poor survival and high resistance to available treatments. Improving the molecular understanding of glioma and disclosing novel biomarkers of tumor development and progression could help to find novel targeted therapies for this type of cancer. Public databases such as The Cancer Genome Atlas (TCGA) provide an invaluable source of molecular information on cancer tissues. Machine learning tools show promise in dealing with the high dimension of omics data and extracting relevant information from it. In this work, network inference and clustering methods, namely Joint Graphical lasso and Robust Sparse K-means Clustering, were applied to RNA-sequencing data from TCGA glioma patients to identify shared and distinct gene networks among different types of glioma (glioblastoma, astrocytoma, and oligodendroglioma) and disclose new patient groups and the relevant genes behind groups’ separation. The results obtained suggest that astrocytoma and oligodendroglioma have more similarities compared with glioblastoma, highlighting the molecular differences between glioblastoma and the others glioma subtypes. After a comprehensive literature search on the relevant genes pointed our from our analysis, we identified potential candidates for biomarkers of glioma. Further molecular validation of these genes is encouraged to understand their potential role in diagnosis and in the design of novel therapies.DI - Departamento de InformáticaCMA - Centro de Matemática e AplicaçõesNOVALincsUNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e IndustrialDEMI - Departamento de Engenharia Mecânica e IndustrialRUNMartins, SofiaColetti, RobertaLopes, Marta B.2024-02-24T00:22:08Z2023-122023-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16application/pdfhttp://hdl.handle.net/10362/164089eng1756-0381PURE: 83893760https://doi.org/10.1186/s13040-023-00341-1info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:50:46Zoai:run.unl.pt:10362/164089Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:00:02.833026Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
title Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
spellingShingle Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
Martins, Sofia
Biomarkers
Glioma
Joint graphical lasso
Robust sparse K-means clustering
Sparse networks
Transcriptomics
Biochemistry
Molecular Biology
Genetics
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics
SDG 3 - Good Health and Well-being
title_short Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
title_full Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
title_fullStr Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
title_full_unstemmed Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
title_sort Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
author Martins, Sofia
author_facet Martins, Sofia
Coletti, Roberta
Lopes, Marta B.
author_role author
author2 Coletti, Roberta
Lopes, Marta B.
author2_role author
author
dc.contributor.none.fl_str_mv DI - Departamento de Informática
CMA - Centro de Matemática e Aplicações
NOVALincs
UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial
DEMI - Departamento de Engenharia Mecânica e Industrial
RUN
dc.contributor.author.fl_str_mv Martins, Sofia
Coletti, Roberta
Lopes, Marta B.
dc.subject.por.fl_str_mv Biomarkers
Glioma
Joint graphical lasso
Robust sparse K-means clustering
Sparse networks
Transcriptomics
Biochemistry
Molecular Biology
Genetics
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics
SDG 3 - Good Health and Well-being
topic Biomarkers
Glioma
Joint graphical lasso
Robust sparse K-means clustering
Sparse networks
Transcriptomics
Biochemistry
Molecular Biology
Genetics
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics
SDG 3 - Good Health and Well-being
description Publisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature.
publishDate 2023
dc.date.none.fl_str_mv 2023-12
2023-12-01T00:00:00Z
2024-02-24T00:22:08Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/164089
url http://hdl.handle.net/10362/164089
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1756-0381
PURE: 83893760
https://doi.org/10.1186/s13040-023-00341-1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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