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Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling

BACKGROUND: Improvement of patient quality of life is the ultimate goal of biomedical research, particularly when dealing with complex, chronic and debilitating conditions such as inflammatory bowel disease (IBD). This is largely dependent on receiving an accurate and rapid diagnose, an effective tr...

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Autores principales: Montero-Meléndez, Trinidad, Llor, Xavier, García-Planella, Esther, Perretti, Mauro, Suárez, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3796518/
https://www.ncbi.nlm.nih.gov/pubmed/24155895
http://dx.doi.org/10.1371/journal.pone.0076235
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author Montero-Meléndez, Trinidad
Llor, Xavier
García-Planella, Esther
Perretti, Mauro
Suárez, Antonio
author_facet Montero-Meléndez, Trinidad
Llor, Xavier
García-Planella, Esther
Perretti, Mauro
Suárez, Antonio
author_sort Montero-Meléndez, Trinidad
collection PubMed
description BACKGROUND: Improvement of patient quality of life is the ultimate goal of biomedical research, particularly when dealing with complex, chronic and debilitating conditions such as inflammatory bowel disease (IBD). This is largely dependent on receiving an accurate and rapid diagnose, an effective treatment and in the prediction and prevention of side effects and complications. The low sensitivity and specificity of current markers burden their general use in the clinical practice. New biomarkers with accurate predictive ability are needed to achieve a personalized approach that take the inter-individual differences into consideration. METHODS: We performed a high throughput approach using microarray gene expression profiling of colon pinch biopsies from IBD patients to identify predictive transcriptional signatures associated with intestinal inflammation, differential diagnosis (Crohn’s disease or ulcerative colitis), response to glucocorticoids (resistance and dependence) or prognosis (need for surgery). Class prediction was performed with self-validating Prophet software package. RESULTS: Transcriptional profiling divided patients in two subgroups that associated with degree of inflammation. Class predictors were identified with predictive accuracy ranging from 67 to 100%. The expression accuracy was confirmed by real time-PCR quantification. Functional analysis of the predictor genes showed that they play a role in immune responses to bacteria (PTN, OLFM4 and LILRA2), autophagy and endocytocis processes (ATG16L1, DNAJC6, VPS26B, RABGEF1, ITSN1 and TMEM127) and glucocorticoid receptor degradation (STS and MMD2). CONCLUSIONS: We conclude that using analytical algorithms for class prediction discovery can be useful to uncover gene expression profiles and identify classifier genes with potential stratification utility of IBD patients, a major step towards personalized therapy.
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spelling pubmed-37965182013-10-23 Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling Montero-Meléndez, Trinidad Llor, Xavier García-Planella, Esther Perretti, Mauro Suárez, Antonio PLoS One Research Article BACKGROUND: Improvement of patient quality of life is the ultimate goal of biomedical research, particularly when dealing with complex, chronic and debilitating conditions such as inflammatory bowel disease (IBD). This is largely dependent on receiving an accurate and rapid diagnose, an effective treatment and in the prediction and prevention of side effects and complications. The low sensitivity and specificity of current markers burden their general use in the clinical practice. New biomarkers with accurate predictive ability are needed to achieve a personalized approach that take the inter-individual differences into consideration. METHODS: We performed a high throughput approach using microarray gene expression profiling of colon pinch biopsies from IBD patients to identify predictive transcriptional signatures associated with intestinal inflammation, differential diagnosis (Crohn’s disease or ulcerative colitis), response to glucocorticoids (resistance and dependence) or prognosis (need for surgery). Class prediction was performed with self-validating Prophet software package. RESULTS: Transcriptional profiling divided patients in two subgroups that associated with degree of inflammation. Class predictors were identified with predictive accuracy ranging from 67 to 100%. The expression accuracy was confirmed by real time-PCR quantification. Functional analysis of the predictor genes showed that they play a role in immune responses to bacteria (PTN, OLFM4 and LILRA2), autophagy and endocytocis processes (ATG16L1, DNAJC6, VPS26B, RABGEF1, ITSN1 and TMEM127) and glucocorticoid receptor degradation (STS and MMD2). CONCLUSIONS: We conclude that using analytical algorithms for class prediction discovery can be useful to uncover gene expression profiles and identify classifier genes with potential stratification utility of IBD patients, a major step towards personalized therapy. Public Library of Science 2013-10-14 /pmc/articles/PMC3796518/ /pubmed/24155895 http://dx.doi.org/10.1371/journal.pone.0076235 Text en © 2013 Montero-Meléndez et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Montero-Meléndez, Trinidad
Llor, Xavier
García-Planella, Esther
Perretti, Mauro
Suárez, Antonio
Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title_full Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title_fullStr Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title_full_unstemmed Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title_short Identification of Novel Predictor Classifiers for Inflammatory Bowel Disease by Gene Expression Profiling
title_sort identification of novel predictor classifiers for inflammatory bowel disease by gene expression profiling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3796518/
https://www.ncbi.nlm.nih.gov/pubmed/24155895
http://dx.doi.org/10.1371/journal.pone.0076235
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