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Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock

Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguis...

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Autores principales: Martínez-Paz, Pedro, Aragón-Camino, Marta, Gómez-Sánchez, Esther, Lorenzo-López, Mario, Gómez-Pesquera, Estefanía, López-Herrero, Rocío, Sánchez-Quirós, Belén, de la Varga, Olga, Tamayo-Velasco, Álvaro, Ortega-Loubon, Christian, García-Morán, Emilio, Gonzalo-Benito, Hugo, Heredia-Rodríguez, María, Tamayo, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287660/
https://www.ncbi.nlm.nih.gov/pubmed/32354167
http://dx.doi.org/10.3390/jcm9051276
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author Martínez-Paz, Pedro
Aragón-Camino, Marta
Gómez-Sánchez, Esther
Lorenzo-López, Mario
Gómez-Pesquera, Estefanía
López-Herrero, Rocío
Sánchez-Quirós, Belén
de la Varga, Olga
Tamayo-Velasco, Álvaro
Ortega-Loubon, Christian
García-Morán, Emilio
Gonzalo-Benito, Hugo
Heredia-Rodríguez, María
Tamayo, Eduardo
author_facet Martínez-Paz, Pedro
Aragón-Camino, Marta
Gómez-Sánchez, Esther
Lorenzo-López, Mario
Gómez-Pesquera, Estefanía
López-Herrero, Rocío
Sánchez-Quirós, Belén
de la Varga, Olga
Tamayo-Velasco, Álvaro
Ortega-Loubon, Christian
García-Morán, Emilio
Gonzalo-Benito, Hugo
Heredia-Rodríguez, María
Tamayo, Eduardo
author_sort Martínez-Paz, Pedro
collection PubMed
description Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores.
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spelling pubmed-72876602020-06-15 Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock Martínez-Paz, Pedro Aragón-Camino, Marta Gómez-Sánchez, Esther Lorenzo-López, Mario Gómez-Pesquera, Estefanía López-Herrero, Rocío Sánchez-Quirós, Belén de la Varga, Olga Tamayo-Velasco, Álvaro Ortega-Loubon, Christian García-Morán, Emilio Gonzalo-Benito, Hugo Heredia-Rodríguez, María Tamayo, Eduardo J Clin Med Article Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores. MDPI 2020-04-28 /pmc/articles/PMC7287660/ /pubmed/32354167 http://dx.doi.org/10.3390/jcm9051276 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Martínez-Paz, Pedro
Aragón-Camino, Marta
Gómez-Sánchez, Esther
Lorenzo-López, Mario
Gómez-Pesquera, Estefanía
López-Herrero, Rocío
Sánchez-Quirós, Belén
de la Varga, Olga
Tamayo-Velasco, Álvaro
Ortega-Loubon, Christian
García-Morán, Emilio
Gonzalo-Benito, Hugo
Heredia-Rodríguez, María
Tamayo, Eduardo
Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title_full Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title_fullStr Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title_full_unstemmed Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title_short Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock
title_sort gene expression patterns distinguish mortality risk in patients with postsurgical shock
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287660/
https://www.ncbi.nlm.nih.gov/pubmed/32354167
http://dx.doi.org/10.3390/jcm9051276
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