Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling

[EN]Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumo...

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Autores: Martinez-Romero, Jorge, Bueno Fortes, Santiago, Martín-Merino Acera, Manuel, Ramírez de Molina, Ana, Rivas Sanz, Javier de las
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/146462
Acceso en línea:http://hdl.handle.net/10366/146462
Access Level:acceso abierto
Palabra clave:Cancer
Colorectal cancer
Colon
Survival
Kaplan-Meier analysis
Gene marker
Bioinformatics
Transcriptomics
Gene Expression
Kaplan-Meier Estimate
Colorectal Neoplasms
3201.01 Oncología
estimación de Kaplan-Meier
colon
neoplasias colorrectales
síntomas de cáncer
id ES_edba34e46e5880adc14d2ff1be6bef76
oai_identifier_str oai:gredos.usal.es:10366/146462
network_acronym_str ES
network_name_str España
repository_id_str
spelling Survival marker genes of colorectal cancer derived from consistent transcriptomic profilingMartinez-Romero, JorgeBueno Fortes, SantiagoMartín-Merino Acera, ManuelRamírez de Molina, AnaRivas Sanz, Javier de lasCancerColorectal cancerColonSurvivalKaplan-Meier analysisGene markerBioinformaticsTranscriptomicsGene ExpressionColonKaplan-Meier EstimateColorectal Neoplasms3201.01 Oncologíaestimación de Kaplan-Meiercolonneoplasias colorrectalessíntomas de cáncer[EN]Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors.We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis.Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis.Springer202120212018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10366/146462reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)InglésAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1464622026-06-07T06:28:51Z
dc.title.none.fl_str_mv Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
title Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
spellingShingle Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
Martinez-Romero, Jorge
Cancer
Colorectal cancer
Colon
Survival
Kaplan-Meier analysis
Gene marker
Bioinformatics
Transcriptomics
Gene Expression
Colon
Kaplan-Meier Estimate
Colorectal Neoplasms
3201.01 Oncología
estimación de Kaplan-Meier
colon
neoplasias colorrectales
síntomas de cáncer
title_short Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
title_full Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
title_fullStr Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
title_full_unstemmed Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
title_sort Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
dc.creator.none.fl_str_mv Martinez-Romero, Jorge
Bueno Fortes, Santiago
Martín-Merino Acera, Manuel
Ramírez de Molina, Ana
Rivas Sanz, Javier de las
author Martinez-Romero, Jorge
author_facet Martinez-Romero, Jorge
Bueno Fortes, Santiago
Martín-Merino Acera, Manuel
Ramírez de Molina, Ana
Rivas Sanz, Javier de las
author_role author
author2 Bueno Fortes, Santiago
Martín-Merino Acera, Manuel
Ramírez de Molina, Ana
Rivas Sanz, Javier de las
author2_role author
author
author
author
dc.subject.none.fl_str_mv Cancer
Colorectal cancer
Colon
Survival
Kaplan-Meier analysis
Gene marker
Bioinformatics
Transcriptomics
Gene Expression
Colon
Kaplan-Meier Estimate
Colorectal Neoplasms
3201.01 Oncología
estimación de Kaplan-Meier
colon
neoplasias colorrectales
síntomas de cáncer
topic Cancer
Colorectal cancer
Colon
Survival
Kaplan-Meier analysis
Gene marker
Bioinformatics
Transcriptomics
Gene Expression
Colon
Kaplan-Meier Estimate
Colorectal Neoplasms
3201.01 Oncología
estimación de Kaplan-Meier
colon
neoplasias colorrectales
síntomas de cáncer
description [EN]Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors.We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis.Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis.
publishDate 2018
dc.date.none.fl_str_mv 2018
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/146462
url http://hdl.handle.net/10366/146462
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869423530199744512
score 15.301603

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