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Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures

There is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery and thereby determine the optimal time point of liver resection, specifically as current markers are often expensive, time consuming, and invasive. Emerging evidence suggests that micr...

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Autores principales: Starlinger, Patrick, Hackl, Hubert, Pereyra, David, Skalicky, Susanna, Geiger, Elisabeth, Finsterbusch, Michaela, Tamandl, Dietmar, Brostjan, Christine, Grünberger, Thomas, Hackl, Matthias, Assinger, Alice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593830/
https://www.ncbi.nlm.nih.gov/pubmed/30779441
http://dx.doi.org/10.1002/hep.30572
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author Starlinger, Patrick
Hackl, Hubert
Pereyra, David
Skalicky, Susanna
Geiger, Elisabeth
Finsterbusch, Michaela
Tamandl, Dietmar
Brostjan, Christine
Grünberger, Thomas
Hackl, Matthias
Assinger, Alice
author_facet Starlinger, Patrick
Hackl, Hubert
Pereyra, David
Skalicky, Susanna
Geiger, Elisabeth
Finsterbusch, Michaela
Tamandl, Dietmar
Brostjan, Christine
Grünberger, Thomas
Hackl, Matthias
Assinger, Alice
author_sort Starlinger, Patrick
collection PubMed
description There is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery and thereby determine the optimal time point of liver resection, specifically as current markers are often expensive, time consuming, and invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic, and treatment‐response biomarkers for several diseases. Using next‐generation sequencing as an unbiased systematic approach, 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative liver dysfunction (LD) after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature—consisting of miRNAs 151a‐5p, 192‐5p, and 122‐5p—that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real‐time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a‐5p to 192‐5p and 122‐5p to 151a‐5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stays, and even mortality before an operation with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Our data demonstrate the clinical utility of an miRNA‐based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in individualized patient treatment. Thereby, our data might help to tailor surgical strategies to the specific risk profile of patients.
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spelling pubmed-65938302019-07-10 Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures Starlinger, Patrick Hackl, Hubert Pereyra, David Skalicky, Susanna Geiger, Elisabeth Finsterbusch, Michaela Tamandl, Dietmar Brostjan, Christine Grünberger, Thomas Hackl, Matthias Assinger, Alice Hepatology Original Articles There is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery and thereby determine the optimal time point of liver resection, specifically as current markers are often expensive, time consuming, and invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic, and treatment‐response biomarkers for several diseases. Using next‐generation sequencing as an unbiased systematic approach, 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative liver dysfunction (LD) after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature—consisting of miRNAs 151a‐5p, 192‐5p, and 122‐5p—that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real‐time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a‐5p to 192‐5p and 122‐5p to 151a‐5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stays, and even mortality before an operation with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Our data demonstrate the clinical utility of an miRNA‐based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in individualized patient treatment. Thereby, our data might help to tailor surgical strategies to the specific risk profile of patients. John Wiley and Sons Inc. 2019-04-10 2019-06 /pmc/articles/PMC6593830/ /pubmed/30779441 http://dx.doi.org/10.1002/hep.30572 Text en © 2019 The Authors. Hepatology published by Wiley Periodicals, Inc., on behalf of American Association for the Study of Liver Diseases. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Starlinger, Patrick
Hackl, Hubert
Pereyra, David
Skalicky, Susanna
Geiger, Elisabeth
Finsterbusch, Michaela
Tamandl, Dietmar
Brostjan, Christine
Grünberger, Thomas
Hackl, Matthias
Assinger, Alice
Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title_full Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title_fullStr Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title_full_unstemmed Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title_short Predicting Postoperative Liver Dysfunction Based on Blood‐Derived MicroRNA Signatures
title_sort predicting postoperative liver dysfunction based on blood‐derived microrna signatures
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593830/
https://www.ncbi.nlm.nih.gov/pubmed/30779441
http://dx.doi.org/10.1002/hep.30572
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