A Cross-Sectional and Longitudinal Analysis of Pre-Diagnostic Blood Plasma Biomarkers for Early Detection of Pancreatic Cancer

• Published in: International Journal of Molecular Sciences
• Main Authors: James Mason, Erik Lundberg, Pär Jonsson, Hanna Nyström, Oskar Franklin, Christina Lundin, Peter Naredi, Henrik Antti, Malin Sund, Daniel Öhlund
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2022
• Subjects: carcinoma; pancreatic ductal; biomarkers; tumor; early detection of cancer; tumor microenvironment; analysis; Northern Sweden
• Online Access: https://doi.org/10.3390/ijms232112969

Pancreatic ductal adenocarcinoma (PDAC) is a major cause of cancer death that typically presents at an advanced stage. No reliable markers for early detection presently exist. The prominent tumor stroma represents a source of circulating biomarkers for use together with cancer cell-derived biomarkers for earlier PDAC diagnosis. CA19-9 and CEA (cancer cell-derived biomarkers), together with endostatin and collagen IV (stroma-derived) were examined alone, or together, by multivariable modelling, using pre-diagnostic plasma samples (n = 259 samples) from the Northern Sweden Health and Disease Study biobank. Serial samples were available for a subgroup of future patients. Marker efficacy for future PDAC case prediction (n = 154 future cases) was examined by both cross-sectional (ROC analysis) and longitudinal analyses. CA19-9 performed well at, and within, six months to diagnosis and multivariable modelling was not superior to CA19-9 alone in cross-sectional analysis. Within six months to diagnosis, CA19-9 (AUC = 0.92) outperformed the multivariable model (AUC = 0.81) at a cross-sectional level. At diagnosis, CA19-9 (AUC = 0.995) and the model (AUC = 0.977) performed similarly. Longitudinal analysis revealed increases in CA19-9 up to two years to diagnosis which indicates a window of opportunity for early detection of PDAC.