OBJECTIVE: Early detection is the only promising approach to significantly improve the survival of patients with pancreatic cancer (PCa). Noninvasive tools for the diagnosis, prognosis, and monitoring of this disease are of urgent need. The purpose of this study was to identify and validate new biomarkers in PCa patient serum samples. METHODS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has been applied to analyze serum protein alterations associated with PCa and to identify sets of potential biomarkers indicative for this disease. A cohort of 96 serum samples from patients undergoing PCa surgery was compared with sera from 96 healthy volunteers as controls. The sera were fractionated by anion exchange chromatography, and 3 of 6 fractions were analyzed onto 2 different chromatographic arrays. RESULTS: Data analysis revealed 24 differentially expressed protein peaks (P < 0.001), of which 21 were downregulated in the PCa samples. The best single marker can predict 92% of the controls and 89% of the cancer samples correctly. In addition, multivariate pattern analysis was performed. The best pattern model using a set of 3 markers was obtained using fraction 6 on immobilized metal affinity capture, loaded with Cu-Cu arrays. With this pattern model, a sensitivity of 100% and a specificity of 98% for the training data set and a sensitivity of 83% and specificity of 77% for the test data set were achieved with the PCa group set as true positive. Several of protein peaks, including the best single marker at 17.27 kd and other proteins from the pattern models, were purified and identified by peptide mapping and postsource decay-matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Apolipoprotein A-II, transthyretin, and apolipoprotein A-I were identified as markers, and these identified proteins were decreased at least 2-fold in PCa serum when compared with the control group. CONCLUSIONS: PCa is associated with a specific decrease of distinct serum proteins, which allows a reliable differentiation between pancreatic cancer and healthy controls.
OBJECTIVE: Early detection is the only promising approach to significantly improve the survival of patients with pancreatic cancer (PCa). Noninvasive tools for the diagnosis, prognosis, and monitoring of this disease are of urgent need. The purpose of this study was to identify and validate new biomarkers in PCa patient serum samples. METHODS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has been applied to analyze serum protein alterations associated with PCa and to identify sets of potential biomarkers indicative for this disease. A cohort of 96 serum samples from patients undergoing PCa surgery was compared with sera from 96 healthy volunteers as controls. The sera were fractionated by anion exchange chromatography, and 3 of 6 fractions were analyzed onto 2 different chromatographic arrays. RESULTS: Data analysis revealed 24 differentially expressed protein peaks (P < 0.001), of which 21 were downregulated in the PCa samples. The best single marker can predict 92% of the controls and 89% of the cancer samples correctly. In addition, multivariate pattern analysis was performed. The best pattern model using a set of 3 markers was obtained using fraction 6 on immobilized metal affinity capture, loaded with Cu-Cu arrays. With this pattern model, a sensitivity of 100% and a specificity of 98% for the training data set and a sensitivity of 83% and specificity of 77% for the test data set were achieved with the PCa group set as true positive. Several of protein peaks, including the best single marker at 17.27 kd and other proteins from the pattern models, were purified and identified by peptide mapping and postsource decay-matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Apolipoprotein A-II, transthyretin, and apolipoprotein A-I were identified as markers, and these identified proteins were decreased at least 2-fold in PCa serum when compared with the control group. CONCLUSIONS: PCa is associated with a specific decrease of distinct serum proteins, which allows a reliable differentiation between pancreatic cancer and healthy controls.
Authors: Rachel A Egler; Yiting Li; Tu Anh T Dang; Tricia L Peters; Eastwood Leung; Shixia Huang; Heidi V Russell; Hao Liu; Tsz-Kwong Man Journal: Proteomics Clin Appl Date: 2011-09-07 Impact factor: 3.494
Authors: L Giusti; P Iacconi; F Ciregia; G Giannaccini; F Basolo; G Donatini; P Miccoli; A Lucacchini Journal: J Endocrinol Invest Date: 2007-11 Impact factor: 4.256
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Authors: Berit Velstra; Bert A Bonsing; Bart J Mertens; Yuri E M van der Burgt; Anouck Huijbers; Hans Vasen; Wilma E Mesker; André M Deelder; Rob A E M Tollenaar Journal: HPB (Oxford) Date: 2012-11-30 Impact factor: 3.647
Authors: P Kelly; V Appleyard; K Murray; F Paulin; D Lamont; L Baker; S Suttie; D Exon; A Thompson Journal: Br J Cancer Date: 2010-06-15 Impact factor: 7.640
Authors: A Xue; C J Scarlett; L Chung; G Butturini; A Scarpa; R Gandy; S R Wilson; R C Baxter; R C Smith Journal: Br J Cancer Date: 2010-06-29 Impact factor: 7.640
Authors: Gillian Higgins; Katherine M Roper; Irene J Watson; Fiona H Blackhall; William N Rom; Harvey I Pass; Justin F X Ainscough; Dawn Coverley Journal: Proc Natl Acad Sci U S A Date: 2012-10-16 Impact factor: 11.205