Literature DB >> 25780901

Proteomics analysis of bodily fluids in pancreatic cancer.

Sheng Pan1, Teresa A Brentnall1, Ru Chen1.   

Abstract

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biomedicine; Bodily fluids; Mass spectrometry; Pancreatic cancer; Pancreatic ductal adenocarcinoma; Proteomics

Mesh:

Substances:

Year:  2015        PMID: 25780901      PMCID: PMC4526406          DOI: 10.1002/pmic.201400476

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  129 in total

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3.  Comparison of pancreas juice proteins from cancer versus pancreatitis using quantitative proteomic analysis.

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Journal:  Pancreas       Date:  2007-01       Impact factor: 3.327

4.  Proteomics-based identification of DEAD-box protein 48 as a novel autoantigen, a prospective serum marker for pancreatic cancer.

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Authors:  Caridad Rosette; Richard B Roth; Paul Oeth; Andreas Braun; Stefan Kammerer; Jonas Ekblom; Mikhail F Denissenko
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6.  Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group.

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7.  Proteomic analyses of pancreatic cyst fluids.

Authors:  Eileen Ke; Bhavinkumar B Patel; Tiffany Liu; Xin-Ming Li; Oleh Haluszka; John P Hoffman; Hormoz Ehya; Nancy A Young; James C Watson; David S Weinberg; Minhhuyen T Nguyen; Steven J Cohen; Neal J Meropol; Samuel Litwin; Jeffrey L Tokar; Anthony T Yeung
Journal:  Pancreas       Date:  2009-03       Impact factor: 3.327

Review 8.  Proteomics of pancreatic cancer.

Authors:  Ilona Gräntzdörffer; Stacy Carl-McGrath; Matthias P Ebert; Christoph Röcken
Journal:  Pancreas       Date:  2008-05       Impact factor: 3.327

9.  Comparative proteomic analysis of human pancreatic juice: methodological study.

Authors:  Lu Zhou; ZhaoHui Lu; AiMing Yang; RuiXue Deng; CanRong Mai; XinTing Sang; Klaas Nico Faber; XingHua Lu
Journal:  Proteomics       Date:  2007-04       Impact factor: 3.984

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Review 1.  Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.

Authors:  Yan V Sun; Yi-Juan Hu
Journal:  Adv Genet       Date:  2016-01-25       Impact factor: 1.944

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Review 4.  [Cystic pancreatic tumors: diagnostics and new biomarkers].

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Review 7.  Glycoproteins and glycoproteomics in pancreatic cancer.

Authors:  Sheng Pan; Teresa A Brentnall; Ru Chen
Journal:  World J Gastroenterol       Date:  2016-11-14       Impact factor: 5.742

8.  Highly Sensitive Plasmonic Detection of the Pancreatic Cancer Biomarker CA 19-9.

Authors:  Zaynab A R Jawad; Ioannis G Theodorou; Long R Jiao; Fang Xie
Journal:  Sci Rep       Date:  2017-10-30       Impact factor: 4.379

Review 9.  Proteomic biomarkers in body fluids associated with pancreatic cancer.

Authors:  Cristina Jimenez-Luna; Carolina Torres; Raul Ortiz; Carmelo Dieguez; Joaquina Martinez-Galan; Consolacion Melguizo; Jose C Prados; Octavio Caba
Journal:  Oncotarget       Date:  2018-03-27

10.  Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19-9 in Early-Stage Pancreatic Cancer Using a Combination of Antibody-Based and LC-MS/MS-Based Proteomics.

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