Cyst Fluid Biosignature to Predict Intraductal Papillary Mucinous Neoplasms of the Pancreas with High Malignant Potential.
Journal
Journal of the American College of Surgeons
ISSN: 1879-1190
Titre abrégé: J Am Coll Surg
Pays: United States
ID NLM: 9431305
Informations de publication
Date de publication:
05 2019
05 2019
Historique:
received:
31
12
2018
revised:
01
02
2019
accepted:
02
02
2019
pubmed:
23
2
2019
medline:
24
4
2020
entrez:
23
2
2019
Statut:
ppublish
Résumé
Current standard-of-care technologies, such as imaging and cyst fluid analysis, are unable to consistently distinguish intraductal papillary mucinous neoplasms (IPMNs) of the pancreas at high risk of pancreatic cancer from low-risk IPMNs. The objective was to create a single-platform assay to identify IPMNs that are at high risk for malignant progression. Building on the Verona International Consensus Conference branch duct IPMN biomarker review, additional protein, cytokine, mucin, DNA, and microRNA cyst fluid targets were identified for creation of a quantitative polymerase chain reaction-based assay. This included messenger RNA markers: ERBB2, GNAS, interleukin 1β, KRAS, MUCs1, 2, 4, 5AC, 7, prostaglandin E2R, PTGER2, prostaglandin E synthase 2, prostaglandin E synthase 1, TP63; microRNA targets: miRs 101, 106b, 10a, 142, 155, 17, 18a, 21, 217, 24, 30a, 342, 532, 92a, and 99b; and GNAS and KRAS mutational analysis. A multi-institutional international collaborative contributed IPMN cyst fluid samples to validate this platform. Cyst fluid gene expression levels were normalized, z-transformed, and used in classification and regression analysis by a support vector machine training algorithm. From cyst fluids of 59 IPMN patients, principal component analysis confirmed no institutional bias/clustering. Lasso (least absolute shrinkage and selection operator)-penalized logistic regression with binary classification and 5-fold cross-validation used area under the curve as the evaluation criterion to create the optimal signature to discriminate IPMNs as low risk (low/moderate dysplasia) or high risk (high-grade dysplasia/invasive cancer). The most predictive signature was achieved with interleukin 1β, MUC4, and prostaglandin E synthase 2 to accurately discriminate high-risk cysts from low-risk cysts with an area under the curve of up to 0.86 (p = 0.002). We have identified a single-platform polymerase chain reaction-based assay of cyst fluid to accurately predict IPMNs with high malignant potential for additional studies.
Sections du résumé
BACKGROUND
Current standard-of-care technologies, such as imaging and cyst fluid analysis, are unable to consistently distinguish intraductal papillary mucinous neoplasms (IPMNs) of the pancreas at high risk of pancreatic cancer from low-risk IPMNs. The objective was to create a single-platform assay to identify IPMNs that are at high risk for malignant progression.
STUDY DESIGN
Building on the Verona International Consensus Conference branch duct IPMN biomarker review, additional protein, cytokine, mucin, DNA, and microRNA cyst fluid targets were identified for creation of a quantitative polymerase chain reaction-based assay. This included messenger RNA markers: ERBB2, GNAS, interleukin 1β, KRAS, MUCs1, 2, 4, 5AC, 7, prostaglandin E2R, PTGER2, prostaglandin E synthase 2, prostaglandin E synthase 1, TP63; microRNA targets: miRs 101, 106b, 10a, 142, 155, 17, 18a, 21, 217, 24, 30a, 342, 532, 92a, and 99b; and GNAS and KRAS mutational analysis. A multi-institutional international collaborative contributed IPMN cyst fluid samples to validate this platform. Cyst fluid gene expression levels were normalized, z-transformed, and used in classification and regression analysis by a support vector machine training algorithm.
RESULTS
From cyst fluids of 59 IPMN patients, principal component analysis confirmed no institutional bias/clustering. Lasso (least absolute shrinkage and selection operator)-penalized logistic regression with binary classification and 5-fold cross-validation used area under the curve as the evaluation criterion to create the optimal signature to discriminate IPMNs as low risk (low/moderate dysplasia) or high risk (high-grade dysplasia/invasive cancer). The most predictive signature was achieved with interleukin 1β, MUC4, and prostaglandin E synthase 2 to accurately discriminate high-risk cysts from low-risk cysts with an area under the curve of up to 0.86 (p = 0.002).
CONCLUSIONS
We have identified a single-platform polymerase chain reaction-based assay of cyst fluid to accurately predict IPMNs with high malignant potential for additional studies.
Identifiants
pubmed: 30794864
pii: S1072-7515(19)30149-8
doi: 10.1016/j.jamcollsurg.2019.02.040
pmc: PMC6487216
mid: NIHMS1522102
pii:
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Multicenter Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
721-729Subventions
Organisme : NCI NIH HHS
ID : K08 CA190855
Pays : United States
Informations de copyright
Copyright © 2019 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
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