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

2023-12Artigo científico Acesso aberto
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dc.contributor.authorMartins, Sofia
dc.contributor.authorColetti, Roberta
dc.contributor.authorLopes, Marta B.
dc.contributor.institutionDI - Departamento de Informática
dc.contributor.institutionCMA - Centro de Matemática e Aplicações
dc.contributor.institutionNOVALincs
dc.contributor.institutionUNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial
dc.contributor.institutionDEMI - Departamento de Engenharia Mecânica e Industrial
dc.contributor.pblBioMed Central (BMC)
dc.date.accessioned2024-02-24T00:22:08Z
dc.date.available2024-02-24T00:22:08Z
dc.date.issued2023-12
dc.descriptionPublisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature.
dc.description.abstractGliomas 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.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent16
dc.format.extent1383928
dc.identifier.doi10.1186/s13040-023-00341-1
dc.identifier.otherPURE: 83893760
dc.identifier.otherPURE UUID: f2eefea3-28bc-44f3-a365-0f120b92b0e3
dc.identifier.otherScopus: 85172236984
dc.identifier.otherWOS: 001073849400001
dc.identifier.otherPubMed: 37752578
dc.identifier.otherPubMedCentral: PMC10523751
dc.identifier.otherORCID: /0000-0002-4135-1857/work/153923166
dc.identifier.urihttp://hdl.handle.net/10362/164089
dc.identifier.urlhttps://www.scopus.com/pages/publications/85172236984
dc.language.isoeng
dc.peerreviewedyes
dc.relationFunding Information: info:eu-repo/grantAgreement/FCT/CEEC INST 2018/CEECINST%2F00102%2F2018%2FCP1567%2FCT0001/PT
dc.relationinfo:eu-repo/grantAgreement/FCT/CEEC INST 2ed/CEECINST%2F00042%2F2021%2FCP1773%2FCT0001/PT
dc.relationNot Available
dc.relationCenter for Mathematics and Applications
dc.relationCenter for Mathematics and Applications
dc.relationNOVA Laboratory for Computer Science and Informatics
dc.relationResearch and Development Unit for Mechanical and Industrial Engineering
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00667%2F2020/PT
dc.relationinfo:eu-repo/grantAgreement/FCT/Concurso para Financiamento de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Todos os Domínios Científicos - 2020/PTDC%2FCCI-BIO%2F4180%2F2020/PT
dc.subjectBiomarkers
dc.subjectGlioma
dc.subjectJoint graphical lasso
dc.subjectRobust sparse K-means clustering
dc.subjectSparse networks
dc.subjectTranscriptomics
dc.subjectBiochemistry
dc.subjectMolecular Biology
dc.subjectGenetics
dc.subjectComputer Science Applications
dc.subjectComputational Theory and Mathematics
dc.subjectComputational Mathematics
dc.subjectSDG 3 - Good Health and Well-being
dc.titleDisclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methodsen
dc.typejournal article
degois.publication.issue1
degois.publication.titleBioData Mining
degois.publication.volume16
dspace.entity.typePublication
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oaire.awardTitleNot Available
oaire.awardTitleCenter for Mathematics and Applications
oaire.awardTitleCenter for Mathematics and Applications
oaire.awardTitleNOVA Laboratory for Computer Science and Informatics
oaire.awardTitleResearch and Development Unit for Mechanical and Industrial Engineering
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC INST 2ed/CEECINST%2F00042%2F2021%2FCP1773%2FCT0001/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00297%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00297%2F2020/PT
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oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Concurso para Financiamento de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Todos os Domínios Científicos - 2020/PTDC%2FCCI-BIO%2F4180%2F2020/PT
oaire.fundingStreamCEEC INST 2ed
oaire.fundingStream6817 - DCRRNI ID
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oaire.fundingStreamConcurso para Financiamento de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Todos os Domínios Científicos - 2020
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