Cargando…
Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma
BACKGROUND: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is one of the most dismal of all cancers and the median survival of PDAC patients is only 6–8 months after diagnosis. While decades of research effort have been focused on early diagnosis and understanding of molecular mechanisms,...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896775/ https://www.ncbi.nlm.nih.gov/pubmed/36737824 http://dx.doi.org/10.1186/s13045-023-01404-w |
_version_ | 1784882119642710016 |
---|---|
author | Han, Yi Drobisch, Pascal Krüger, Alexander William, Doreen Grützmann, Konrad Böthig, Lukas Polster, Heike Seifert, Lena Seifert, Adrian M. Distler, Marius Pecqueux, Mathieu Riediger, Carina Plodeck, Verena Nebelung, Heiner Weber, Georg F. Pilarsky, Christian Kahlert, Ulf Hinz, Ulf Roth, Susanne Hackert, Thilo Weitz, Jürgen Wong, Fang Cheng Kahlert, Christoph |
author_facet | Han, Yi Drobisch, Pascal Krüger, Alexander William, Doreen Grützmann, Konrad Böthig, Lukas Polster, Heike Seifert, Lena Seifert, Adrian M. Distler, Marius Pecqueux, Mathieu Riediger, Carina Plodeck, Verena Nebelung, Heiner Weber, Georg F. Pilarsky, Christian Kahlert, Ulf Hinz, Ulf Roth, Susanne Hackert, Thilo Weitz, Jürgen Wong, Fang Cheng Kahlert, Christoph |
author_sort | Han, Yi |
collection | PubMed |
description | BACKGROUND: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is one of the most dismal of all cancers and the median survival of PDAC patients is only 6–8 months after diagnosis. While decades of research effort have been focused on early diagnosis and understanding of molecular mechanisms, few clinically useful markers have been universally applied. To improve the treatment and management of PDAC, it is equally relevant to identify prognostic factors for optimal therapeutic decision-making and patient survival. Compelling evidence have suggested the potential use of extracellular vesicles (EVs) as non-invasive biomarkers for PDAC. The aim of this study was thus to identify non-invasive plasma-based EV biomarkers for the prediction of PDAC patient survival after surgery. METHODS: Plasma EVs were isolated from a total of 258 PDAC patients divided into three independent cohorts (discovery, training and validation). RNA sequencing was first employed to identify differentially-expressed EV mRNA candidates from the discovery cohort (n = 65) by DESeq2 tool. The candidates were tested in a training cohort (n = 91) by digital droplet polymerase chain reaction (ddPCR). Cox regression models and Kaplan–Meier analyses were used to build an EV signature which was subsequently validated on a multicenter cohort (n = 83) by ddPCR. RESULTS: Transcriptomic profiling of plasma EVs revealed differentially-expressed mRNAs between long-term and short-term PDAC survivors, which led to 10 of the top-ranked candidate EV mRNAs being tested on an independent training cohort with ddPCR. The results of ddPCR enabled an establishment of a novel prognostic EV mRNA signature consisting of PPP1R12A, SCN7A and SGCD for risk stratification of PDAC patients. Based on the EV mRNA signature, PDAC patients with high risk displayed reduced overall survival (OS) rates compared to those with low risk in the training cohort (p = 0.014), which was successfully validated on another independent cohort (p = 0.024). Interestingly, the combination of our signature and tumour stage yielded a superior prognostic performance (p = 0.008) over the signature (p = 0.022) or tumour stage (p = 0.016) alone. It is noteworthy that the EV mRNA signature was demonstrated to be an independent unfavourable predictor for PDAC prognosis. CONCLUSION: This study provides a novel and non-invasive prognostic EV mRNA signature for risk stratification and survival prediction of PDAC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-023-01404-w. |
format | Online Article Text |
id | pubmed-9896775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98967752023-02-04 Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma Han, Yi Drobisch, Pascal Krüger, Alexander William, Doreen Grützmann, Konrad Böthig, Lukas Polster, Heike Seifert, Lena Seifert, Adrian M. Distler, Marius Pecqueux, Mathieu Riediger, Carina Plodeck, Verena Nebelung, Heiner Weber, Georg F. Pilarsky, Christian Kahlert, Ulf Hinz, Ulf Roth, Susanne Hackert, Thilo Weitz, Jürgen Wong, Fang Cheng Kahlert, Christoph J Hematol Oncol Research BACKGROUND: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is one of the most dismal of all cancers and the median survival of PDAC patients is only 6–8 months after diagnosis. While decades of research effort have been focused on early diagnosis and understanding of molecular mechanisms, few clinically useful markers have been universally applied. To improve the treatment and management of PDAC, it is equally relevant to identify prognostic factors for optimal therapeutic decision-making and patient survival. Compelling evidence have suggested the potential use of extracellular vesicles (EVs) as non-invasive biomarkers for PDAC. The aim of this study was thus to identify non-invasive plasma-based EV biomarkers for the prediction of PDAC patient survival after surgery. METHODS: Plasma EVs were isolated from a total of 258 PDAC patients divided into three independent cohorts (discovery, training and validation). RNA sequencing was first employed to identify differentially-expressed EV mRNA candidates from the discovery cohort (n = 65) by DESeq2 tool. The candidates were tested in a training cohort (n = 91) by digital droplet polymerase chain reaction (ddPCR). Cox regression models and Kaplan–Meier analyses were used to build an EV signature which was subsequently validated on a multicenter cohort (n = 83) by ddPCR. RESULTS: Transcriptomic profiling of plasma EVs revealed differentially-expressed mRNAs between long-term and short-term PDAC survivors, which led to 10 of the top-ranked candidate EV mRNAs being tested on an independent training cohort with ddPCR. The results of ddPCR enabled an establishment of a novel prognostic EV mRNA signature consisting of PPP1R12A, SCN7A and SGCD for risk stratification of PDAC patients. Based on the EV mRNA signature, PDAC patients with high risk displayed reduced overall survival (OS) rates compared to those with low risk in the training cohort (p = 0.014), which was successfully validated on another independent cohort (p = 0.024). Interestingly, the combination of our signature and tumour stage yielded a superior prognostic performance (p = 0.008) over the signature (p = 0.022) or tumour stage (p = 0.016) alone. It is noteworthy that the EV mRNA signature was demonstrated to be an independent unfavourable predictor for PDAC prognosis. CONCLUSION: This study provides a novel and non-invasive prognostic EV mRNA signature for risk stratification and survival prediction of PDAC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-023-01404-w. BioMed Central 2023-02-03 /pmc/articles/PMC9896775/ /pubmed/36737824 http://dx.doi.org/10.1186/s13045-023-01404-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Han, Yi Drobisch, Pascal Krüger, Alexander William, Doreen Grützmann, Konrad Böthig, Lukas Polster, Heike Seifert, Lena Seifert, Adrian M. Distler, Marius Pecqueux, Mathieu Riediger, Carina Plodeck, Verena Nebelung, Heiner Weber, Georg F. Pilarsky, Christian Kahlert, Ulf Hinz, Ulf Roth, Susanne Hackert, Thilo Weitz, Jürgen Wong, Fang Cheng Kahlert, Christoph Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title | Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title_full | Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title_fullStr | Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title_full_unstemmed | Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title_short | Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
title_sort | plasma extracellular vesicle messenger rna profiling identifies prognostic ev signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896775/ https://www.ncbi.nlm.nih.gov/pubmed/36737824 http://dx.doi.org/10.1186/s13045-023-01404-w |
work_keys_str_mv | AT hanyi plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT drobischpascal plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT krugeralexander plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT williamdoreen plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT grutzmannkonrad plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT bothiglukas plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT polsterheike plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT seifertlena plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT seifertadrianm plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT distlermarius plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT pecqueuxmathieu plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT riedigercarina plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT plodeckverena plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT nebelungheiner plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT webergeorgf plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT pilarskychristian plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT kahlertulf plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT hinzulf plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT rothsusanne plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT hackertthilo plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT weitzjurgen plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT wongfangcheng plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma AT kahlertchristoph plasmaextracellularvesiclemessengerrnaprofilingidentifiesprognosticevsignaturefornoninvasiveriskstratificationforsurvivalpredictionofpatientswithpancreaticductaladenocarcinoma |