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dc.contributor.authorHernández Martínez, Ana
dc.contributor.authorMadurga Lacalle, Rodrigo 
dc.contributor.authorGarcía Romero, Noemí 
dc.contributor.authorAyuso Sacido, Ángel 
dc.date.accessioned2022-05-06T11:28:21Z
dc.date.available2022-05-06T11:28:21Z
dc.date.issued2022
dc.identifier.issn0304-3835spa
dc.identifier.urihttp://hdl.handle.net/10641/2966
dc.description.abstractGlioblastoma (GBM) is the most invasive and deadliest brain cancer in adults. Its inherent heterogeneity has been designated as the main cause of treatment failure. Thus, a deeper understanding of the diversity that shapes GBM pathobiology is of utmost importance. Single-cell RNA sequencing (scRNA-seq) technologies have begun to uncover the hidden composition of complex tumor ecosystems. Herein, a semi-systematic search of reference literature databases provided all existing publications using scRNA-seq for the investigation of human GBM. We compared and discussed findings from these works to build a more robust and unified knowledge base. All aspects ranging from inter-patient heterogeneity to intra-tumoral organization, cancer stem cell diversity, clonal mosaicism, and the tumor microenvironment (TME) are comprehensively covered in this report. Tumor composition not only differs across patients but also involves a great extent of heterogeneity within itself. Spatial and cellular heterogeneity can reveal tumor evolution dynamics. In addition, the discovery of distinct cell phenotypes might lead to the development of targeted treatment approaches. In conclusion, scRNA-seq expands our knowledge of GBM heterogeneity and helps to unravel putative therapeutic targets.spa
dc.language.isoengspa
dc.publisherCancer Lettersspa
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectGlioblastomaspa
dc.subjectSingle-cell analysisspa
dc.subjectscRNA-seqspa
dc.subjectIntra-tumoral heterogeneityspa
dc.subjectTumor microenvironment (TME)spa
dc.titleUnravelling glioblastoma heterogeneity by means of single-cell RNA sequencing.spa
dc.typejournal articlespa
dc.type.hasVersionAMspa
dc.rights.accessRightsopen accessspa
dc.description.extent4967 KBspa
dc.identifier.doi10.1016/j.canlet.2021.12.008spa
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0304383521006157?via%3Dihubspa


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