Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis

Mahajan, Ujjwal M.; Oehrle, Bettina; Sirtl, Simon; Alnatsha, Ahmed; Goni, Elisabetta; Regel, Ivonne; Beyer, Georg; Vornhuelz, Marlies; Vielhauer, Jakob; Chromik, Ansgar; Bahra, Markus; Klein, Fritz; Uhl, Waldemar; Fahlbusch, Tim; Distler, Marius; Weitz, Juergen; Gruetzmann, Robert; Pilarsky, Christian; Weiss, Frank Ulrich; Adam, M. Gordian; Neoptolemos, John P.; Kalthoff, Holger; Rad, Roland; Christiansen, Nicole; Bethan, Bianca; Kamlage, Beate; Lerch, Markus M. und Mayerle, Julia (2022): Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis. In: Gastroenterology, Bd. 163, Nr. 5: S. 1407-1422

Abstract

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly lethal malignancy requiring efficient detection when the primary tumor is still resectable. We previously developed the MxPancreasScore comprising 9 analytes and serum carbohydrate antigen 19-9 (CA19-9), achieving an accuracy of 90.6%. The necessity for 5 different analytical platforms and multiple analytical runs, however, hindered clinical applicability. We therefore aimed to develop a simpler single-analytical run, single-platform diagnostic signature. METHODS: We evaluated 941 patients (PDAC, 356;chronic pancreatitis [CP], 304;nonpancreatic disease, 281) in 3 multicenter independent tests, and identification (ID) and validation cohort 1 (VD1) and 2 (VD2) were evaluated. Targeted quantitative plasma metabolite analysis was performed on a liquid chromatography-tandem mass spectrometry platform. A machine learning-aided algorithm identified an improved (i-Metabolic) and minimalistic metabolic (m-Metabolic) signatures, and compared them for performance. RESULTS: The i-Metabolic Signature, (12 analytes plus CA19-9) distinguished PDAC from CP with area under the curve (95% confidence interval) of 97.2% (97.1%-97.3%), 93.5% (93.4%93.7%), and 92.2% (92.1%-92.3%) in the ID, VD1, and VD2 cohorts, respectively. In the VD2 cohort, the m-Metabolic signature (4 analytes plus CA19-9) discriminated PDAC from CP with a sensitivity of 77.3% and specificity of 89.6%, with an overall accuracy of 82.4%. For the subset of 45 patients with PDAC with resectable stages IA-IIB tumors, the sensitivity, specificity, and accuracy were 73.2%, 89.6%, and 82.7%, respectively;for those with detectable CA19-9 >2 U/mL, 81.6%, 88.7%, and 84.5%, respectively;and for those with CA19-9 <37 U/mL, 39.7%, 94.1%, and 76.3%, respectively. CONCLUSIONS: The single-platform, single-run, m-Metabolic signature of just 4 metabolites used in combination with serum CA19-9 levels is an innovative accurate diagnostic tool for PDAC at the time of clinical presentation, warranting further large-scale evaluation.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0016-5085
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 413635475
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 329628492