Browsing by Author "Feng, Ziding"

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    A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer
    (Oxford University Press, 2019-04-01) Fahrmann, Johannes F.; Bantis, Leonidas E.; Capello, Michela; Scelo, Ghislaine; Dennison, Jennifer B.; Patel, Nikul; Murage, Eunice; Vykoukal, Jody; Kundnani, Deepali L.; Foretova, Lenka; Fabianova, Eleonora; Holcatova, Ivana; Janout, Vladimir; Feng, Ziding; Yip-Schneider, Michele; Zhang, Jianjun; Brand, Randall; Taguchi, Ayumu; Maitra, Anirban; Brennan, Paul; Max Schmidt, C.; Hanash, Samir; Surgery, School of Medicine
    BACKGROUND: We applied a training and testing approach to develop and validate a plasma metabolite panel for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC) alone and in combination with a previously validated protein panel for early-stage PDAC. METHODS: A comprehensive metabolomics platform was initially applied to plasmas collected from 20 PDAC cases and 80 controls. Candidate markers were filtered based on a second independent cohort that included nine invasive intraductal papillary mucinous neoplasm cases and 51 benign pancreatic cysts. Blinded validation of the resulting metabolite panel was performed in an independent test cohort consisting of 39 resectable PDAC cases and 82 matched healthy controls. The additive value of combining the metabolite panel with a previously validated protein panel was evaluated. RESULTS: Five metabolites (acetylspermidine, diacetylspermine, an indole-derivative, and two lysophosphatidylcholines) were selected as a panel based on filtering criteria. A combination rule was developed for distinguishing between PDAC and healthy controls using the Training Set. In the blinded validation study with early-stage PDAC samples and controls, the five metabolites yielded areas under the curve (AUCs) ranging from 0.726 to 0.842, and the combined metabolite model yielded an AUC of 0.892 (95% confidence interval [CI] = 0.828 to 0.956). Performance was further statistically significantly improved by combining the metabolite panel with a previously validated protein marker panel consisting of CA 19-9, LRG1, and TIMP1 (AUC = 0.924, 95% CI = 0.864 to 0.983, comparison DeLong test one-sided P= .02). CONCLUSIONS: A metabolite panel in combination with CA19-9, TIMP1, and LRG1 exhibited substantially improved performance in the detection of early-stage PDAC compared with a protein panel alone.
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    PROspective Evaluation of Chronic Pancreatitis for EpidEmiologic and Translational StuDies: Rationale and Study Design for PROCEED From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer
    (Wolters Kluwer, 2018-11) Yadav, Dhiraj; Park, Walter G.; Fogel, Evan L.; Li, Liang; Chari, Suresh T.; Feng, Ziding; Fisher, William E.; Forsmark, Christopher E.; Jeon, Christie Y.; Habtezion, Aida; Hart, Phil A.; Hughes, Steven J.; Othman, Mohamed O.; Rinaudo, Jo Ann; Pandol, Stephen J.; Tirkes, Temel; Serrano, Jose; Srivastava, Sudhir; Van Den Eeden, Stephen K.; Whitcomb, David C.; Topazian, Mark; Conwell, Darwin L.; Medicine, School of Medicine
    Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED) is the first prospective, observational cohort study of chronic pancreatitis (CP) in the United States. The primary goals of PROCEED are to define disease progression, test the predictive capability of candidate biomarkers, and develop a platform to conduct translational and mechanistic studies in CP. Using objective and consensus-driven criteria, PROCEED will enroll adults at different stages of CP-controls, suspected CP, and definite CP. In addition to collecting detailed information using structured case report forms and protocol-mandated evaluations at baseline and during follow-up, PROCEED will establish a linked biorepository of blood, urine, saliva, stool, pancreatic fluid, and pancreatic tissue. Enrollment for PROCEED began in June 2017. As of July 1, 2018, nine clinical centers of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer are enrolling, and 350 subjects have completed baseline evaluation. In conclusion, PROCEED will provide the most accurate and reliable estimates to date on progression of CP. The established cohort and biorepository will facilitate numerous analyses, leading to new strategies for diagnosis, methods to monitor disease progression, and treatment of CP.
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    A Prospective Study to Establish a New-Onset Diabetes Cohort: From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer
    (Wolters Kluwer, 2018-11) Maitra, Anirban; Sharma, Ayush; Brand, Randall E.; Van Den Eeden, Stephen K.; Fisher, William E.; Hart, Phil A.; Hughes, Steven J.; Mather, Kieren J.; Pandol, Stephen J.; Park, Walter G.; Feng, Ziding; Serrano, Jose; Rinaudo, Jo Ann; Srivastava, Sudhir; Chari, Suresh T.; Medicine, School of Medicine
    The National Cancer Institute and the National Institute for Diabetes and Digestive and Kidney Diseases initiated the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC) in 2015 (the CPDPC's origin, structure, governance, and research objectives are described in another article in this journal). One of the key objectives of CPDPC is to assemble a cohort of 10,000 subjects 50 years or older with new-onset diabetes, called the NOD cohort. Using a define, enrich, and find early detection approach, the aims of the NOD study are to (a) estimate the 3-year probability of pancreatic ductal adenocarcinoma (PDAC) in NOD (define), (b) establish a biobank of clinically annotated biospecimens from presymptomatic PDAC and control new-onset type 2 diabetes mellitus subjects, (c) conduct phase 3 validation studies of promising biomarkers for identification of incident PDAC in NOD patients (enrich), and (d) provide a platform for development of a future interventional screening protocol for early detection of PDAC in patients with NOD that incorporates imaging studies and/or clinical algorithms (find). It is expected that 85 to 100 incidences of PDAC will be diagnosed during the study period in this cohort of 10,000 patients.