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Predicting liver regeneration following major resection
Breakdown of synthesis, excretion and detoxification defines liver failure. Post-hepatectomy liver failure (PHLF) is specific for liver resection and a rightfully feared complication due to high lethality and limited therapeutic success. Individual cytokine and growth factor profiles may represent p...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352754/ https://www.ncbi.nlm.nih.gov/pubmed/35927556 http://dx.doi.org/10.1038/s41598-022-16968-9 |
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author | Dehlke, Karolin Krause, Linda Tyufekchieva, Silvana Murtha-Lemekhova, Anastasia Mayer, Philipp Vlasov, Artyom Klingmüller, Ursula Mueller, Nikola S. Hoffmann, Katrin |
author_facet | Dehlke, Karolin Krause, Linda Tyufekchieva, Silvana Murtha-Lemekhova, Anastasia Mayer, Philipp Vlasov, Artyom Klingmüller, Ursula Mueller, Nikola S. Hoffmann, Katrin |
author_sort | Dehlke, Karolin |
collection | PubMed |
description | Breakdown of synthesis, excretion and detoxification defines liver failure. Post-hepatectomy liver failure (PHLF) is specific for liver resection and a rightfully feared complication due to high lethality and limited therapeutic success. Individual cytokine and growth factor profiles may represent potent predictive markers for recovery of liver function. We aimed to investigate these profiles in post-hepatectomy regeneration. This study combined a time-dependent cytokine and growth factor profiling dataset of a training (30 patients) and a validation (14 patients) cohorts undergoing major liver resection with statistical and predictive models identifying individual pathway signatures. 2319 associations were tested. Primary hepatocytes isolated from patient tissue samples were stimulated and their proliferation was analysed through DNA content assay. Common expression trajectories of cytokines and growth factors with strong correlation to PHLF, morbidity and mortality were identified despite highly individual perioperative dynamics. Especially, dynamics of EGF, HGF, and PLGF were associated with mortality. PLGF was additionally associated with PHLF and complications. A global association-network was calculated and validated to investigate interdependence of cytokines and growth factors with clinical attributes. Preoperative cytokine and growth factor signatures were identified allowing prediction of mortality following major liver resection by regression modelling. Proliferation analysis of corresponding primary human hepatocytes showed associations of individual regenerative potential with clinical outcome. Prediction of PHLF was possible on as early as first postoperative day (POD1) with AUC above 0.75. Prediction of PHLF and mortality is possible on POD1 with liquid-biopsy based risk profiling. Further utilization of these models would allow tailoring of interventional strategies according to individual profiles. |
format | Online Article Text |
id | pubmed-9352754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93527542022-08-06 Predicting liver regeneration following major resection Dehlke, Karolin Krause, Linda Tyufekchieva, Silvana Murtha-Lemekhova, Anastasia Mayer, Philipp Vlasov, Artyom Klingmüller, Ursula Mueller, Nikola S. Hoffmann, Katrin Sci Rep Article Breakdown of synthesis, excretion and detoxification defines liver failure. Post-hepatectomy liver failure (PHLF) is specific for liver resection and a rightfully feared complication due to high lethality and limited therapeutic success. Individual cytokine and growth factor profiles may represent potent predictive markers for recovery of liver function. We aimed to investigate these profiles in post-hepatectomy regeneration. This study combined a time-dependent cytokine and growth factor profiling dataset of a training (30 patients) and a validation (14 patients) cohorts undergoing major liver resection with statistical and predictive models identifying individual pathway signatures. 2319 associations were tested. Primary hepatocytes isolated from patient tissue samples were stimulated and their proliferation was analysed through DNA content assay. Common expression trajectories of cytokines and growth factors with strong correlation to PHLF, morbidity and mortality were identified despite highly individual perioperative dynamics. Especially, dynamics of EGF, HGF, and PLGF were associated with mortality. PLGF was additionally associated with PHLF and complications. A global association-network was calculated and validated to investigate interdependence of cytokines and growth factors with clinical attributes. Preoperative cytokine and growth factor signatures were identified allowing prediction of mortality following major liver resection by regression modelling. Proliferation analysis of corresponding primary human hepatocytes showed associations of individual regenerative potential with clinical outcome. Prediction of PHLF was possible on as early as first postoperative day (POD1) with AUC above 0.75. Prediction of PHLF and mortality is possible on POD1 with liquid-biopsy based risk profiling. Further utilization of these models would allow tailoring of interventional strategies according to individual profiles. Nature Publishing Group UK 2022-08-04 /pmc/articles/PMC9352754/ /pubmed/35927556 http://dx.doi.org/10.1038/s41598-022-16968-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dehlke, Karolin Krause, Linda Tyufekchieva, Silvana Murtha-Lemekhova, Anastasia Mayer, Philipp Vlasov, Artyom Klingmüller, Ursula Mueller, Nikola S. Hoffmann, Katrin Predicting liver regeneration following major resection |
title | Predicting liver regeneration following major resection |
title_full | Predicting liver regeneration following major resection |
title_fullStr | Predicting liver regeneration following major resection |
title_full_unstemmed | Predicting liver regeneration following major resection |
title_short | Predicting liver regeneration following major resection |
title_sort | predicting liver regeneration following major resection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352754/ https://www.ncbi.nlm.nih.gov/pubmed/35927556 http://dx.doi.org/10.1038/s41598-022-16968-9 |
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