Jaroslav Tumas1, Inga Baskirova2, Tomas Petrenas2, Jolita Norkuniene3, Kestutis Strupas4, Audrius Sileikis4. 1. Clinic of Gastroenterology, Nephrourology and Surgery, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania jaroslav.tumas@santa.lt. 2. Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania. 3. Department of Mathematical Statistics, Vilnius Gediminas Technical University, Vilnius, Lithuania. 4. Clinic of Gastroenterology, Nephrourology and Surgery, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Abstract
BACKGROUND/AIM: Body fluid biomarkers may provide means for early pancreatic cancer diagnosis, patient stratification, application of personalized approaches and, finally, improved outcomes. Amino acids are the most frequently distinguished metabolite class in the metabolomics of pancreatic cancer patients. They have been identified as pre-diagnostic and diagnostic markers and associated with pancreatic cancer risk factors. MATERIALS AND METHODS: Deep phenotyping and quantitative amino acid analysis were performed in patients scheduled for pancreatic surgery due to pancreatic tumors (n=75). RESULTS: Significant differences in plasma amino acid concentrations were observed between diagnostic categories (malignant vs. benign lesions and histological cancer types) and pancreatic ductal adenocarcinoma stages. Characteristic patterns of plasma amino acid concentration dynamics according to cancer stage were identified. CONCLUSION: Standardization of metabolomics methods and deep phenotyping may provide means for improved patient stratification and effective personalized approaches in pancreatic cancer prevention, early diagnosis and treatment. Copyright
BACKGROUND/AIM: Body fluid biomarkers may provide means for early pancreatic cancer diagnosis, patient stratification, application of personalized approaches and, finally, improved outcomes. Amino acids are the most frequently distinguished metabolite class in the metabolomics of pancreatic cancerpatients. They have been identified as pre-diagnostic and diagnostic markers and associated with pancreatic cancer risk factors. MATERIALS AND METHODS: Deep phenotyping and quantitative amino acid analysis were performed in patients scheduled for pancreatic surgery due to pancreatic tumors (n=75). RESULTS: Significant differences in plasma amino acid concentrations were observed between diagnostic categories (malignant vs. benign lesions and histological cancer types) and pancreatic ductal adenocarcinoma stages. Characteristic patterns of plasma amino acid concentration dynamics according to cancer stage were identified. CONCLUSION: Standardization of metabolomics methods and deep phenotyping may provide means for improved patient stratification and effective personalized approaches in pancreatic cancer prevention, early diagnosis and treatment. Copyright
Authors: Tabassum A Khan; Tyler J Loftus; Amanda C Filiberto; Tezcan Ozrazgat-Baslanti; Matthew M Ruppert; Sabyasachi Bandyopadhyay; Evagelia C Laiakis; Dean J Arnaoutakis; Azra Bihorac Journal: Ann Surg Date: 2021-02-01 Impact factor: 13.787
Authors: Tiago M A Carvalho; Daria Di Molfetta; Maria Raffaella Greco; Tomas Koltai; Khalid O Alfarouk; Stephan J Reshkin; Rosa A Cardone Journal: Cancers (Basel) Date: 2021-12-06 Impact factor: 6.639