Plasma extracellular vesicle long RNA profiling identifies a diagnostic signature for the detection of pancreatic ductal adenocarcinoma
ObjectivePancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) prof...
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| Vydané v: | Gut Ročník 69; číslo 3; s. 540 - 550 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
BMJ Publishing Group Ltd and British Society of Gastroenterology
01.03.2020
BMJ Publishing Group LTD |
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| ISSN: | 0017-5749, 1468-3288, 1468-3288 |
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| Abstract | ObjectivePancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling.DesignWe conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178).ResultsWe developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028).ConclusionThis study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window. |
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| AbstractList | ObjectivePancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling.DesignWe conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178).ResultsWe developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028).ConclusionThis study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window. Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling.OBJECTIVEPancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling.We conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178).DESIGNWe conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178).We developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028).RESULTSWe developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028).This study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window.CONCLUSIONThis study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window. Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling. We conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178). We developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028). This study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window. |
| Author | Wang, Peng Li, Yuchen Qian, Ling Wang, Zheng Wang, Zhen Huang, Shenglin Chen, Kun Kang, Bin Zhao, Jingjing Liao, Zhuan He, Xianghuo Zou, Wen-Bin Chen, Zhen Li, Yan Meng, Zhiqiang Yu, Shulin Zong, Huajie |
| Author_xml | – sequence: 1 givenname: Shulin surname: Yu fullname: Yu, Shulin organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China – sequence: 2 givenname: Yuchen surname: Li fullname: Li, Yuchen organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 3 givenname: Zhuan orcidid: 0000-0001-8506-8159 surname: Liao fullname: Liao, Zhuan organization: Department of Gastroenterology, Digestive Endoscopy Center, Changhai Hospital, the Second Military Medical University, Shanghai, China – sequence: 4 givenname: Zheng orcidid: 0000-0002-0490-466X surname: Wang fullname: Wang, Zheng organization: Department of Hepatobiliary Surgery, First Affiliated Hospital, Xi’an Jiaotong University, Xi’an, China – sequence: 5 givenname: Zhen surname: Wang fullname: Wang, Zhen organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 6 givenname: Yan surname: Li fullname: Li, Yan organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 7 givenname: Ling surname: Qian fullname: Qian, Ling organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China – sequence: 8 givenname: Jingjing surname: Zhao fullname: Zhao, Jingjing organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 9 givenname: Huajie surname: Zong fullname: Zong, Huajie organization: Department of General Surgery, Huashan Hospital, Fudan University, Fudan University, Shanghai, China – sequence: 10 givenname: Bin surname: Kang fullname: Kang, Bin organization: Fudan University Shanghai Cancer Center - InstitutMerieux Laboratory, Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China – sequence: 11 givenname: Wen-Bin surname: Zou fullname: Zou, Wen-Bin organization: Department of Gastroenterology, Digestive Endoscopy Center, Changhai Hospital, the Second Military Medical University, Shanghai, China – sequence: 12 givenname: Kun surname: Chen fullname: Chen, Kun organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China – sequence: 13 givenname: Xianghuo orcidid: 0000-0001-8872-668X surname: He fullname: He, Xianghuo organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 14 givenname: Zhiqiang surname: Meng fullname: Meng, Zhiqiang organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China – sequence: 15 givenname: Zhen surname: Chen fullname: Chen, Zhen email: zchenzl@fudan.edu.cn organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China – sequence: 16 givenname: Shenglin orcidid: 0000-0001-9424-5073 surname: Huang fullname: Huang, Shenglin email: slhuang@fudan.edu.cn organization: Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China – sequence: 17 givenname: Peng orcidid: 0000-0003-0569-9001 surname: Wang fullname: Wang, Peng email: wangp413@163.com organization: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31562239$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ. 2020 Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ. |
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| DOI | 10.1136/gutjnl-2019-318860 |
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| ISSN | 0017-5749 1468-3288 |
| IngestDate | Fri Sep 05 10:37:17 EDT 2025 Tue Oct 07 07:24:32 EDT 2025 Wed Feb 19 02:31:16 EST 2025 Tue Nov 18 22:19:32 EST 2025 Sat Nov 29 04:04:18 EST 2025 Thu Apr 24 22:53:42 EDT 2025 Thu Apr 24 22:50:17 EDT 2025 |
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| Issue | 3 |
| Keywords | diagnosis long RNA extracellular vesicle pancreatic ductal adenocarcinoma |
| Language | English |
| License | Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ. |
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| PublicationTitle | Gut |
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receptor signaling in cancer publication-title: Cell doi: 10.1016/j.cell.2017.06.031 – volume: 17 start-page: 754 year: 2017 article-title: Pancreatic cancer screening: still a delusion? publication-title: Pancreatology doi: 10.1016/j.pan.2017.07.001 – volume: 8 start-page: 11683 year: 2015 article-title: Tumor markers CA19-9, CA242 and CEA in the diagnosis of pancreatic cancer: a meta-analysis publication-title: Int J Clin Exp Med – volume: 29 start-page: 653 year: 2016 article-title: Exosome-Transmitted lncARSR promotes sunitinib resistance in renal cancer by acting as a competing endogenous RNA publication-title: Cancer Cell doi: 10.1016/j.ccell.2016.03.004 – volume: 523 start-page: 177 year: 2015 article-title: Glypican-1 identifies cancer exosomes and detects early pancreatic cancer publication-title: Nature doi: 10.1038/nature14581 – volume: 17 year: 2018 article-title: The decade of exosomal long RNA species: an emerging cancer antagonist publication-title: Mol Cancer doi: 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diagnostic and prognostic biomarkers for pancreatic adenocarcinoma publication-title: Pancreas doi: 10.1097/MPA.0b013e31825e354d – volume: 379 start-page: 958 year: 2018 article-title: Circulating extracellular vesicles in human disease publication-title: N Engl J Med doi: 10.1056/NEJMra1704286 – volume: 37 start-page: 481 year: 2016 article-title: Pancreatic cancer: associations of inflammatory potential of diet, cigarette smoking and long-standing diabetes publication-title: Carcinogenesis doi: 10.1093/carcin/bgw022 – volume: 8 year: 2017 article-title: Knockout of MARCH2 inhibits the growth of HCT116 colon cancer cells by inducing endoplasmic reticulum stress publication-title: Cell Death Dis doi: 10.1038/cddis.2017.347 – volume: 19 start-page: 213 year: 2018 article-title: Shedding light on the cell biology of extracellular vesicles publication-title: Nat Rev Mol Cell Biol doi: 10.1038/nrm.2017.125 – volume: 9 year: 2017 article-title: Multiparametric plasma eV profiling 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| Snippet | ObjectivePancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs)... Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain... |
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| SubjectTerms | Accuracy Adenocarcinoma Adolescent Adult Aged Aged, 80 and over Alpha-Globulins - genetics Antigens Area Under Curve Biomarkers CA-19-9 Antigen - blood Cancer therapies Carbohydrates Carcinoma, Pancreatic Ductal - blood Carcinoma, Pancreatic Ductal - diagnosis Carcinoma, Pancreatic Ductal - genetics Case-Control Studies Chemotherapy Child Claudin-1 - genetics diagnosis extracellular vesicle Extracellular Vesicles - metabolism Female Fibrinogen - genetics Gene expression Genomes Humans Keratin-19 - genetics Library collections long RNA Male Membrane Proteins - genetics Middle Aged Myelin and Lymphocyte-Associated Proteolipid Proteins - genetics Pancreas Pancreatic cancer pancreatic ductal adenocarcinoma Pancreatic Neoplasms - blood Pancreatic Neoplasms - diagnosis Pancreatic Neoplasms - genetics Pancreatitis Pancreatitis, Chronic - blood Patients Proteins Ribonucleic acid RNA RNA - blood RNA, Circular - blood RNA, Long Noncoding - blood RNA, Messenger - blood ROC Curve Sequence Analysis, RNA Studies Support Vector Machine Tissue inhibitor of metalloproteinase 1 Tissue Inhibitor of Metalloproteinase-1 - genetics Tumors Ubiquitin-Protein Ligases - genetics Young Adult |
| Title | Plasma extracellular vesicle long RNA profiling identifies a diagnostic signature for the detection of pancreatic ductal adenocarcinoma |
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