Nanoparticle-protein corona enhances accuracy of Ca-19.9-based pancreatic cancer classification

• Published in: Nanoscale Vol. 17; no. 12; pp. 766 - 775
• Main Authors: Digiacomo, Luca, Caputo, Damiano, Cammarata, Roberto, La Vaccara, Vincenzo, Coppola, Roberto, Quagliarini, Erica, Iacobini, Manuela, Renzi, Serena, Giulimondi, Francesca, Pozzi, Daniela, Caracciolo, Giulio, Amenitsch, Heinz
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 24.03.2025
• Subjects: Adult; Aged; Aged, 80 and over; Biomarkers; Blood plasma; CA-19-9 Antigen - blood; Cancer; Carbohydrates; Carcinoma, Pancreatic Ductal - blood; Carcinoma, Pancreatic Ductal - classification; Carcinoma, Pancreatic Ductal - diagnosis; Case-Control Studies; Classification; Female; Graphene; Graphite; Humans; Male; Medical prognosis; Middle Aged; Nanoparticles; Pancreatic cancer; Pancreatic Neoplasms - blood; Pancreatic Neoplasms - classification; Pancreatic Neoplasms - diagnosis; Protein Corona - analysis; Proteins; Young Adult
• ISSN: 2040-3364; 2040-3372; 2040-3372
• DOI: 10.1039/d4nr02435d

Among the various types of pancreatic cancers, pancreatic ductal adenocarcinoma (PDAC) is the most lethal and aggressive, due to its tendency to metastasize quickly and has a particularly low five-year survival rate. Carbohydrate antigen 19-9 (CA 19-9) is the only biomarker approved by the Food and Drug Administration for PDAC and has been a focal point in diagnostic strategies, but its sensitivity and specificity are not sufficient for early and accurate detection. To address this issue, we introduce a synergistic approach combining CA 19-9 levels with a graphene oxide (GO)-based blood test. This non-invasive technique relies on the analysis of personalized protein corona formed on GO sheets once they are embedded in human plasma. Pairing CA 19-9 values with GO protein patterns from N = 106 donors significantly improved the ability to differentiate between non-oncological and PDAC patients (up to 92%), also boosting the classification of PDAC subjects by 50% compared to CA 19-9 testing alone. Overall, this study sought to bridge the existing gaps in PDAC detection by exploiting the complementary strengths of conventional biomarkers and cutting-edge nanotechnology. Exploration of this combined strategy holds promise for advancing the early detection of PDAC, ultimately contributing to improved patient prognosis and treatment outcomes. The integration of nanotechnology with traditional biomarker analysis offers a novel and promising pathway to enhance the accuracy and early detection of pancreatic ductal adenocarcinoma.