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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Veröffentlicht in:	Gut Jg. 69; H. 3; S. 540 - 550
Hauptverfasser:	Yu, Shulin, Li, Yuchen, Liao, Zhuan, Wang, Zheng, Wang, Zhen, Li, Yan, Qian, Ling, Zhao, Jingjing, Zong, Huajie, Kang, Bin, Zou, Wen-Bin, Chen, Kun, He, Xianghuo, Meng, Zhiqiang, Chen, Zhen, Huang, Shenglin, Wang, Peng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England BMJ Publishing Group Ltd and British Society of Gastroenterology 01.03.2020 BMJ Publishing Group LTD
Schlagworte:	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 California United States > US Massachusetts China Germany diagnosis long RNA extracellular vesicle pancreatic ductal adenocarcinoma
ISSN:	0017-5749, 1468-3288, 1468-3288
Online-Zugang:	Volltext
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Zusammenfassung:	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.
Bibliographie:	Original research ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Undefined-3
ISSN:	0017-5749 1468-3288 1468-3288
DOI:	10.1136/gutjnl-2019-318860