Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma
Abstract 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 mech...
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Language: | English |
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BMC
2023-02-01
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Series: | Journal of Hematology & Oncology |
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Online Access: | https://doi.org/10.1186/s13045-023-01404-w |
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author | Yi Han Pascal Drobisch Alexander Krüger Doreen William Konrad Grützmann Lukas Böthig Heike Polster Lena Seifert Adrian M. Seifert Marius Distler Mathieu Pecqueux Carina Riediger Verena Plodeck Heiner Nebelung Georg F. Weber Christian Pilarsky Ulf Kahlert Ulf Hinz Susanne Roth Thilo Hackert Jürgen Weitz Fang Cheng Wong Christoph Kahlert |
author_facet | Yi Han Pascal Drobisch Alexander Krüger Doreen William Konrad Grützmann Lukas Böthig Heike Polster Lena Seifert Adrian M. Seifert Marius Distler Mathieu Pecqueux Carina Riediger Verena Plodeck Heiner Nebelung Georg F. Weber Christian Pilarsky Ulf Kahlert Ulf Hinz Susanne Roth Thilo Hackert Jürgen Weitz Fang Cheng Wong Christoph Kahlert |
author_sort | Yi Han |
collection | DOAJ |
description | Abstract 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. |
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issn | 1756-8722 |
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spelling | doaj.art-79bb2f022f07438e98c676caf4fc57692023-02-05T12:21:26ZengBMCJournal of Hematology & Oncology1756-87222023-02-0116111910.1186/s13045-023-01404-wPlasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinomaYi Han0Pascal Drobisch1Alexander Krüger2Doreen William3Konrad Grützmann4Lukas Böthig5Heike Polster6Lena Seifert7Adrian M. Seifert8Marius Distler9Mathieu Pecqueux10Carina Riediger11Verena Plodeck12Heiner Nebelung13Georg F. Weber14Christian Pilarsky15Ulf Kahlert16Ulf Hinz17Susanne Roth18Thilo Hackert19Jürgen Weitz20Fang Cheng Wong21Christoph Kahlert22Department of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenCore Unit for Molecular Tumour Diagnostics, National Center for Tumour DiseasesCore Unit for Molecular Tumour Diagnostics, National Center for Tumour DiseasesCore Unit for Molecular Tumour Diagnostics, National Center for Tumour DiseasesDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Diagnostic and Interventional Radiology, Carl Gustav Carus University Hospital DresdenDepartment of Diagnostic and Interventional Radiology, Carl Gustav Carus University Hospital DresdenDepartment of Surgery, Universitätsklinikum ErlangenDepartment of Surgery, Universitätsklinikum ErlangenMolecular and Experimental Surgery, University Clinic for General-, Visceral-, Vascular- and Transplantation Surgery, Medical Faculty University Hospital MagdeburgDepartment of General, Visceral and Transplantation Surgery, Heidelberg University HospitalDepartment of General, Visceral and Transplantation Surgery, Heidelberg University HospitalDepartment of General, Visceral and Transplantation Surgery, Heidelberg University HospitalDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität DresdenAbstract 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.https://doi.org/10.1186/s13045-023-01404-wExtracellular vesiclesPancreatic ductal adenocarcinomaPrognosisPlasma extracellular vesiclemRNA biomarkers |
spellingShingle | Yi Han Pascal Drobisch Alexander Krüger Doreen William Konrad Grützmann Lukas Böthig Heike Polster Lena Seifert Adrian M. Seifert Marius Distler Mathieu Pecqueux Carina Riediger Verena Plodeck Heiner Nebelung Georg F. Weber Christian Pilarsky Ulf Kahlert Ulf Hinz Susanne Roth Thilo Hackert Jürgen Weitz Fang Cheng Wong Christoph Kahlert Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma Journal of Hematology & Oncology Extracellular vesicles Pancreatic ductal adenocarcinoma Prognosis Plasma extracellular vesicle mRNA biomarkers |
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 | Extracellular vesicles Pancreatic ductal adenocarcinoma Prognosis Plasma extracellular vesicle mRNA biomarkers |
url | https://doi.org/10.1186/s13045-023-01404-w |
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