"BACKGROUND: There is an urgent need to discover more sensitive and specific biomarkers to improve early diagnosis and screen high-risk patients for pancreatic ductal adenocarcinoma (PDAC). Pancreatic juice is an ideal specimen for PDAC biomarkers discovery, because it is an exceptionally rich source of proteins released from pancreatic cancer cells.

"ABSTRACT: BACKGROUND: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer.

"BACKGROUND: The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease.

"BACKGROUND: The proteome varies with physiologic and disease states. Few studies have been reported that differentiate the proteome of those with pancreatic cancer. AIM: To apply proteomic-based technologies to body fluids. To differentiate pancreatic neoplasia from nonneoplastic pancreatic disease. METHODS: Samples from 50 patients (15 healthy (H), 24 cancer (Ca), 11 chronic pancreatitis (CP)) were prospectively collected and underwent analysis.

"The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects.

"Serum is a difficult matrix for the identification of biomarkers by mass spectrometry (MS). This is due to high-abundance proteins and their complex processing by a multitude of endogenous proteases making rigorous standardisation difficult. Here, we have investigated the use of defined exogenous reporter peptides as substrates for disease-specific proteases with respect to improved standardisation and disease classification accuracy.

ABSTRACT: BACKGROUND: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer.

BACKGROUND: The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease.

Serum is a difficult matrix for the identification of biomarkers by mass spectrometry (MS). This is due to high-abundance proteins and their complex processing by a multitude of endogenous proteases making rigorous standardisation difficult. Here, we have investigated the use of defined exogenous reporter peptides as substrates for disease-specific proteases with respect to improved standardisation and disease classification accuracy.