Fast Screening Method of Biological Samples Based on Needle Stochastic Sensors for Early Detection of Gastric Cancer

Early detection of cancer is essential for saving the life of patients. Needle stochastic sensors were proposed as new tools for the fast screening of biological samples. The design of the stochastic sensors was based on the immobilization of protoporphyrin IX in pastes of S-doped graphene. The selected biomarkers were CEA and CA19-9. High sensitivities, and wide linear concentration ranges as well as low limits of quantification were achieved. The proposed sensors were validated; student t-test shown that the proposed needle stochastic sensors can be reliably used for the pattern recognition and quantification of CEA and CA19-9 in whole blood, gastric tumor tissue, saliva, and urine.