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,...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
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