PURPOSE: Pancreatitis is an inflammatory state of the pancreas, for which high-performing serological biomarkers are lacking. The aim of the present study was to evaluate the use of affinity proteomics for identifying potential markers of disease and stratifying pancreatitis subtypes. EXPERIMENTAL DESIGN: High-content, recombinant antibody microarrays were applied for serum protein expression profiling of 113 serum samples from patients with chronic, acute, and autoimmune pancreatitis, as well as healthy controls. The sample groups were compared using supervised classification based on support vector machine analysis. RESULTS: This discovery study showed that pancreatitis subtypes could be discriminated with high accuracy. Using unfiltered data, the individual subtypes, as well as the combined pancreatitis cohort, were distinguished from healthy controls with high AUC values (0.96-1.00). Moreover, characteristic protein patterns and AUC values in the range of 0.69-0.95 were observed for the individual pancreatitis entities when compared to each other, and to all other samples combined. CONCLUSIONS AND CLINICAL RELEVANCE: This study demonstrated the potential of the antibody microarray approach for stratification of pancreatitis. Distinct candidate multiplex serum biomarker signatures for chronic, acute, and autoimmune pancreatitis were defined, which could enhance our fundamental knowledge of the underlying molecular mechanisms, and potentially lead to improved diagnosis.
PURPOSE:Pancreatitis is an inflammatory state of the pancreas, for which high-performing serological biomarkers are lacking. The aim of the present study was to evaluate the use of affinity proteomics for identifying potential markers of disease and stratifying pancreatitis subtypes. EXPERIMENTAL DESIGN: High-content, recombinant antibody microarrays were applied for serum protein expression profiling of 113 serum samples from patients with chronic, acute, and autoimmune pancreatitis, as well as healthy controls. The sample groups were compared using supervised classification based on support vector machine analysis. RESULTS: This discovery study showed that pancreatitis subtypes could be discriminated with high accuracy. Using unfiltered data, the individual subtypes, as well as the combined pancreatitis cohort, were distinguished from healthy controls with high AUC values (0.96-1.00). Moreover, characteristic protein patterns and AUC values in the range of 0.69-0.95 were observed for the individual pancreatitis entities when compared to each other, and to all other samples combined. CONCLUSIONS AND CLINICAL RELEVANCE: This study demonstrated the potential of the antibody microarray approach for stratification of pancreatitis. Distinct candidate multiplex serum biomarker signatures for chronic, acute, and autoimmune pancreatitis were defined, which could enhance our fundamental knowledge of the underlying molecular mechanisms, and potentially lead to improved diagnosis.
Authors: Pedro Silva-Vaz; Ana Margarida Abrantes; Miguel Castelo-Branco; António Gouveia; Maria Filomena Botelho; José Guilherme Tralhão Journal: Int J Mol Sci Date: 2020-01-04 Impact factor: 5.923
Authors: Linda D Mellby; Andreas P Nyberg; Julia S Johansen; Christer Wingren; Børge G Nordestgaard; Stig E Bojesen; Breeana L Mitchell; Brett C Sheppard; Rosalie C Sears; Carl A K Borrebaeck Journal: J Clin Oncol Date: 2018-08-14 Impact factor: 44.544
Authors: Zobeida Cruz-Monserrate; Kristyn Gumpper; Valentina Pita; Phil A Hart; Christopher Forsmark; David C Whitcomb; Dhiraj Yadav; Richard T Waldron; Stephen Pandol; Hanno Steen; Vincent Anani; Natasha Kanwar; Santhi Swaroop Vege; Savi Appana; Liang Li; Jose Serrano; Jo Ann S Rinaudo; Mark Topazian; Darwin L Conwell Journal: Pancreatology Date: 2021-01-22 Impact factor: 3.996
Authors: Petter Skoog; Mattias Ohlsson; Mårten Fernö; Lisa Rydén; Carl A K Borrebaeck; Christer Wingren Journal: PLoS One Date: 2017-06-26 Impact factor: 3.240
Authors: Anna S Gerdtsson; Núria Malats; Anna Säll; Francisco X Real; Miquel Porta; Petter Skoog; Helena Persson; Christer Wingren; Carl A K Borrebaeck Journal: Int J Proteomics Date: 2015-10-26