Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy.

Abstract

Simple SummaryPancreatic tumors are extremely difficult to detect in their early stages due to the lack of early symptomatic evidence and fast, simple, non-invasive, and accurate diagnostic tests. Computed tomography (CT) scans are the usual first step in investigating suspected pancreatic cancer, but may not detect early tumors—especially in asymptomatic patients. Equally, the carbohydrate antigen (CA) 19-9 blood test is not specific to pancreatic cancer, as CA 19-9 levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors located in the surrounding area. In this proof-of-concept study, infrared spectroscopy was used to discriminate cancers versus healthy controls, as well as cancers versus symptomatic controls. Classification algorithms successfully discriminated the classes with high performances, accounting for detection rates of up to 92%. Simple, minimally invasive, and accurate approaches can represent a powerful aid in the achievement of pancreatic cancer’s earlier detection to improve patients’ prognosis and quality of life.Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer’s detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.