Publikation: Global mapping of cancers : The Cancer Genome Atlas and beyond
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
GANINI, Carlo, Ivano AMELIO, Riccardo BERTOLO, Pierluigi BOVE, Oreste Claudio BUONOMO, Eleonora CANDI, Chiara CIPRIANI, Nicola DI DANIELE, Hartmut JUHL, Gerry MELINO, 2021. Global mapping of cancers : The Cancer Genome Atlas and beyond. In: Molecular oncology. Wiley. 2021, 15(11), pp. 2823-2840. ISSN 1574-7891. eISSN 1878-0261. Available under: doi: 10.1002/1878-0261.13056BibTex
@article{Ganini2021Globa-56540, year={2021}, doi={10.1002/1878-0261.13056}, title={Global mapping of cancers : The Cancer Genome Atlas and beyond}, number={11}, volume={15}, issn={1574-7891}, journal={Molecular oncology}, pages={2823--2840}, author={Ganini, Carlo and Amelio, Ivano and Bertolo, Riccardo and Bove, Pierluigi and Buonomo, Oreste Claudio and Candi, Eleonora and Cipriani, Chiara and Di Daniele, Nicola and Juhl, Hartmut and Melino, Gerry} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/56540"> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/56540/3/Amelio_2-1ayz0kyd5c6rr9.pdf"/> <dc:creator>Bertolo, Riccardo</dc:creator> <dc:contributor>Di Daniele, Nicola</dc:contributor> <dc:contributor>Juhl, Hartmut</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/> <dc:contributor>Bove, Pierluigi</dc:contributor> <dc:contributor>Cipriani, Chiara</dc:contributor> <dc:language>eng</dc:language> <dc:creator>Buonomo, Oreste Claudio</dc:creator> <dc:creator>Cipriani, Chiara</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dcterms:title>Global mapping of cancers : The Cancer Genome Atlas and beyond</dcterms:title> <dc:contributor>Melino, Gerry</dc:contributor> <dc:contributor>Ganini, Carlo</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-02-14T11:25:27Z</dc:date> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Amelio, Ivano</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-02-14T11:25:27Z</dcterms:available> <dc:contributor>Amelio, Ivano</dc:contributor> <dc:contributor>Candi, Eleonora</dc:contributor> <dc:creator>Melino, Gerry</dc:creator> <dc:creator>Di Daniele, Nicola</dc:creator> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/56540/3/Amelio_2-1ayz0kyd5c6rr9.pdf"/> <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/> <dc:creator>Candi, Eleonora</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/56540"/> <dc:contributor>Bertolo, Riccardo</dc:contributor> <dc:creator>Ganini, Carlo</dc:creator> <dc:creator>Bove, Pierluigi</dc:creator> <dc:rights>Attribution 4.0 International</dc:rights> <dcterms:issued>2021</dcterms:issued> <dcterms:abstract xml:lang="eng">Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.</dcterms:abstract> <dc:contributor>Buonomo, Oreste Claudio</dc:contributor> <dc:creator>Juhl, Hartmut</dc:creator> </rdf:Description> </rdf:RDF>