CA 19-9 Pancreatic Tumor Marker Fluorescence Immunosensing Detection via Immobilized Carbon Quantum Dots Conjugated Gold Nanocomposite.
Nawal Ahmad AlarfajMaha Farouk El-TohamyHesham Farouk OrabyPublished in: International journal of molecular sciences (2018)
The clinical detection of carbohydrate antigen 19-9 (CA 19-9), a tumor marker in biological samples, improves and facilitates the rapid screening and diagnosis of pancreatic cancer. A simple, low cost, fast, and green synthesis method to prepare a viable carbon quantum dots/gold (CQDs/Au) nanocomposite fluorescence immunosensing solution for the detection of CA 19-9 was reported. The present method is conducted by preparing glucose-derived CQDs using a microwave-assisted method. CQDs were employed as reducing and stabilizing agents for the preparation of a CQDs/Au nanocomposite. The immobilized anti-CA 19-9-labeled horseradish peroxidase enzyme (Ab-HRP) was anchored to the surface of a CQDs/Au nanocomposite by a peptide interaction between the carboxylic and amine active groups. The CA 19-9 antigen was trapped by another monoclonal antibody that was coated on the surface of microtiter wells. The formed sandwich capping antibody-antigen-antibody enzyme complex had tunable fluorescence properties that were detected under excitation and emission wavelengths of 420 and 530 nm. The increase in fluorescence intensities of the immunoassay sensing solution was proportional to the CA 19-9 antigen concentration in the linear range of 0.01-350 U mL-1 and had a lower detection limit of 0.007 U mL-1. The proposed CQDs/Au nanocomposite immunoassay method provides a promising tool for detecting CA 19-9 in human serum.
Keyphrases
- quantum dots
- sensitive detection
- loop mediated isothermal amplification
- energy transfer
- reduced graphene oxide
- label free
- protein kinase
- single molecule
- low cost
- visible light
- gold nanoparticles
- monoclonal antibody
- real time pcr
- photodynamic therapy
- computed tomography
- ionic liquid
- solid phase extraction
- insulin resistance
- adipose tissue
- metabolic syndrome
- capillary electrophoresis
- neural network