[Early detection of pancreatic cancer by novel proteomic technique]

Abstract

Pancreatic cancer is the fifth leading cause of cancer-related mortality in Japan. Early detection in pancreatic cancer is one of the most feasible strategies to improve outcome. We compared plasma proteome between pancreatic cancer patients and healthy controls using surface-enhanced laser desorption/ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. Proteomic spectra were generated from a total of 245 plasma samples obtained from two institutes. A discriminating proteomic pattern was built from training cohort using machine learning algorithm and was applied two validation cohorts. This set discriminating cancer patients in the first validation cohort with a sensitivity of 90.9% and a specificity of 91.9%, and was further validated in an independent cohort at a second institution. When combined with CA19-9, 100% tumor of pancreatic cancers, including early stage tumors, were detected. In this report, we describe a possible detection of early pancreatic cancer using novel proteomic technique.