Phenotypic profiling of pancreatic ductal adenocarcinoma plasma-derived small extracellular vesicles for cancer diagnosis and cancer stage prediction: a proof-of-concept study
Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biome...
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Published in | Analytical methods Vol. 14; no. 23; pp. 2255 - 2265 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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England
Royal Society of Chemistry
16.06.2022
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Abstract | Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biomedical research because the sEVs reflect some key features (
e.g.
genetic and phenotypic status) related to the organs from which they originate. For example, the surface membrane proteins and their expression level on sEVs were reported to be related to the presence and progression of PDAC. However, difficulty in sEVs isolation and lack of ultrasensitive assays for simultaneous analysis of multiple protein biomarkers on patient plasma-derived sEVs hinder their application in the clinic. In our previous study, we have demonstrated the application of magnetic beads (MBs) and surface-enhanced Raman scattering (SERS) assay for phenotypic analysis of cancer cells-derived sEVs using different cell lines. To further demonstrate the clinical application of the proposed assay, we have profiled the sEVs' phenotypes (relative expression of biomarker Glypican 1, EpCAM and CD44V6) of healthy donors and PDAC patients to enable simultaneous detection of multiple surface membrane proteins on plasma-derived sEVs. We discovered that the PDAC sEVs' phenotype signatures had high accuracy for PDAC diagnosis (100%) and showed strong correlation with cancer stages, which were further validated by the imaging techniques (
e.g.
computerized tomography and magnetic resonance imaging) and also the correlation of cancer stages with CA19-9 (gold standard biomarker) and the sEVs' phenotype signatures. The present proof-of-concept study thus provides an initial investigation of using the proposed SERS assay for PDAC diagnosis and early cancer stage prediction in the clinic.
Phenotype profiling of plasma-derived sEVs using SERS based assay for PDAC diagnosis and cancer stage prediction. |
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AbstractList | Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biomedical research because the sEVs reflect some key features (e.g. genetic and phenotypic status) related to the organs from which they originate. For example, the surface membrane proteins and their expression level on sEVs were reported to be related to the presence and progression of PDAC. However, difficulty in sEVs isolation and lack of ultrasensitive assays for simultaneous analysis of multiple protein biomarkers on patient plasma-derived sEVs hinder their application in the clinic. In our previous study, we have demonstrated the application of magnetic beads (MBs) and surface-enhanced Raman scattering (SERS) assay for phenotypic analysis of cancer cells-derived sEVs using different cell lines. To further demonstrate the clinical application of the proposed assay, we have profiled the sEVs' phenotypes (relative expression of biomarker Glypican 1, EpCAM and CD44V6) of healthy donors and PDAC patients to enable simultaneous detection of multiple surface membrane proteins on plasma-derived sEVs. We discovered that the PDAC sEVs' phenotype signatures had high accuracy for PDAC diagnosis (100%) and showed strong correlation with cancer stages, which were further validated by the imaging techniques (e.g. computerized tomography and magnetic resonance imaging) and also the correlation of cancer stages with CA19-9 (gold standard biomarker) and the sEVs' phenotype signatures. The present proof-of-concept study thus provides an initial investigation of using the proposed SERS assay for PDAC diagnosis and early cancer stage prediction in the clinic. Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biomedical research because the sEVs reflect some key features ( e.g. genetic and phenotypic status) related to the organs from which they originate. For example, the surface membrane proteins and their expression level on sEVs were reported to be related to the presence and progression of PDAC. However, difficulty in sEVs isolation and lack of ultrasensitive assays for simultaneous analysis of multiple protein biomarkers on patient plasma-derived sEVs hinder their application in the clinic. In our previous study, we have demonstrated the application of magnetic beads (MBs) and surface-enhanced Raman scattering (SERS) assay for phenotypic analysis of cancer cells-derived sEVs using different cell lines. To further demonstrate the clinical application of the proposed assay, we have profiled the sEVs' phenotypes (relative expression of biomarker Glypican 1, EpCAM and CD44V6) of healthy donors and PDAC patients to enable simultaneous detection of multiple surface membrane proteins on plasma-derived sEVs. We discovered that the PDAC sEVs' phenotype signatures had high accuracy for PDAC diagnosis (100%) and showed strong correlation with cancer stages, which were further validated by the imaging techniques ( e.g. computerized tomography and magnetic resonance imaging) and also the correlation of cancer stages with CA19-9 (gold standard biomarker) and the sEVs' phenotype signatures. The present proof-of-concept study thus provides an initial investigation of using the proposed SERS assay for PDAC diagnosis and early cancer stage prediction in the clinic. Phenotype profiling of plasma-derived sEVs using SERS based assay for PDAC diagnosis and cancer stage prediction. Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biomedical research because the sEVs reflect some key features ( genetic and phenotypic status) related to the organs from which they originate. For example, the surface membrane proteins and their expression level on sEVs were reported to be related to the presence and progression of PDAC. However, difficulty in sEVs isolation and lack of ultrasensitive assays for simultaneous analysis of multiple protein biomarkers on patient plasma-derived sEVs hinder their application in the clinic. In our previous study, we have demonstrated the application of magnetic beads (MBs) and surface-enhanced Raman scattering (SERS) assay for phenotypic analysis of cancer cells-derived sEVs using different cell lines. To further demonstrate the clinical application of the proposed assay, we have profiled the sEVs' phenotypes (relative expression of biomarker Glypican 1, EpCAM and CD44V6) of healthy donors and PDAC patients to enable simultaneous detection of multiple surface membrane proteins on plasma-derived sEVs. We discovered that the PDAC sEVs' phenotype signatures had high accuracy for PDAC diagnosis (100%) and showed strong correlation with cancer stages, which were further validated by the imaging techniques ( computerized tomography and magnetic resonance imaging) and also the correlation of cancer stages with CA19-9 (gold standard biomarker) and the sEVs' phenotype signatures. The present proof-of-concept study thus provides an initial investigation of using the proposed SERS assay for PDAC diagnosis and early cancer stage prediction in the clinic. Circulating pancreatic ductal adenocarcinoma (PDAC) derived small extracellular vesicles (sEVs) are nano-sized membranous vesicles secreted from PDAC cells and released into surrounding body fluids, such as blood. The use of plasma-derived sEVs for cancer diagnosis is particularly appealing in biomedical research because the sEVs reflect some key features ( e.g. genetic and phenotypic status) related to the organs from which they originate. For example, the surface membrane proteins and their expression level on sEVs were reported to be related to the presence and progression of PDAC. However, difficulty in sEVs isolation and lack of ultrasensitive assays for simultaneous analysis of multiple protein biomarkers on patient plasma-derived sEVs hinder their application in the clinic. In our previous study, we have demonstrated the application of magnetic beads (MBs) and surface-enhanced Raman scattering (SERS) assay for phenotypic analysis of cancer cells-derived sEVs using different cell lines. To further demonstrate the clinical application of the proposed assay, we have profiled the sEVs' phenotypes (relative expression of biomarker Glypican 1, EpCAM and CD44V6) of healthy donors and PDAC patients to enable simultaneous detection of multiple surface membrane proteins on plasma-derived sEVs. We discovered that the PDAC sEVs' phenotype signatures had high accuracy for PDAC diagnosis (100%) and showed strong correlation with cancer stages, which were further validated by the imaging techniques ( e.g. computerized tomography and magnetic resonance imaging) and also the correlation of cancer stages with CA19-9 (gold standard biomarker) and the sEVs' phenotype signatures. The present proof-of-concept study thus provides an initial investigation of using the proposed SERS assay for PDAC diagnosis and early cancer stage prediction in the clinic. |
Author | Li, Dan Campbell, Douglas H Packer, Nicolle H Wang, Erkang Wang, Yuling Zhang, Wei Dong, Qing Walsh, Bradley J Wang, Ling |
AuthorAffiliation | Changchun Institute of Applied Chemistry Chinese Academy of Sciences Department of Gynecology and Obstetrics State Key Laboratory of Electroanalytical Chemistry Macquarie University Faculty of Science and Engineering Minomic International Ltd School of Natural Sciences ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP) The Second Hospital of Jilin University |
AuthorAffiliation_xml | – name: The Second Hospital of Jilin University – name: School of Natural Sciences – name: Department of Gynecology and Obstetrics – name: ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP) – name: Macquarie University – name: Faculty of Science and Engineering – name: Changchun Institute of Applied Chemistry – name: Chinese Academy of Sciences – name: Minomic International Ltd – name: State Key Laboratory of Electroanalytical Chemistry |
Author_xml | – sequence: 1 givenname: Wei surname: Zhang fullname: Zhang, Wei – sequence: 2 givenname: Ling surname: Wang fullname: Wang, Ling – sequence: 3 givenname: Dan surname: Li fullname: Li, Dan – sequence: 4 givenname: Douglas H surname: Campbell fullname: Campbell, Douglas H – sequence: 5 givenname: Bradley J surname: Walsh fullname: Walsh, Bradley J – sequence: 6 givenname: Nicolle H surname: Packer fullname: Packer, Nicolle H – sequence: 7 givenname: Qing surname: Dong fullname: Dong, Qing – sequence: 8 givenname: Erkang surname: Wang fullname: Wang, Erkang – sequence: 9 givenname: Yuling surname: Wang fullname: Wang, Yuling |
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SubjectTerms | Adenocarcinoma Assaying Biomarkers Biomarkers, Tumor Body fluids Cancer Carcinoma, Pancreatic Ductal - diagnosis Carcinoma, Pancreatic Ductal - genetics Carcinoma, Pancreatic Ductal - pathology Computed tomography Diagnosis Extracellular vesicles Extracellular Vesicles - genetics Extracellular Vesicles - pathology Heparan sulfate proteoglycans Humans Imaging techniques Magnetic resonance imaging Medical diagnosis Medical imaging Medical research Membrane proteins Membrane Proteins - genetics Membranes Organs Pancreas Pancreatic Neoplasms Pancreatic Neoplasms - diagnosis Pancreatic Neoplasms - genetics Pancreatic Neoplasms - pathology Patients Phenotype Phenotypes Plasma Proteins Raman spectra Vesicles |
Title | Phenotypic profiling of pancreatic ductal adenocarcinoma plasma-derived small extracellular vesicles for cancer diagnosis and cancer stage prediction: a proof-of-concept study |
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