Dual-signal amplified electrochemical biosensor based on eATRP and PEI for early detection of lung cancer

Carcinoembryonic antigen (CEA), a lung cancer marker with high sensitivity and specificity, plays vital roles in the early diagnosis of lung cancer. In this paper, an electrochemical biosensor for highly sensitive detection of CEA was constructed, which based on dual signal amplification of electrically mediated atom transfer radical polymerization (eATRP) and polyethyleneimine (PEI) for the first time. Firstly, CEA was captured in a specific recognition manner with CEA aptamer 1 (Apt1), which self-assembled on the electrode via Au-S bond. After that, CEA aptamer 2-PEI (Apt2-PEI) was recognized by CEA to form an Apt-antigen-Apt sandwich structure. Next, multiple initiation sites were introduced for the eATRP reaction by the amide reaction. Finally, numerous electroactive monomers, ferrocene methacrylate (FMMA), were grafted onto the modified electrode by eATRP. Under the optimized conditions, there was a wide linear detection range of 10(-3) similar to 10(2) ngmL(-1), and the limit of detection (LOD) was 70.17 fg.mL(-1). Compared to other reported sensors, this electrochemical biosensor used a simpler and more environmentally friendly eATRP, and the use of PEI increased the electron transfer rate. Moreover, the biosensor showed superior analytical performance in the clinical serums and has great promise for early lung cancer diagnosis applications.

Automated summary

An electrochemical biosensor was developed for highly sensitive detection of CEA, using dual signal amplification of electrically mediated atom transfer radical polymerization (eATRP) and polyethyleneimine (PEI). The biosensor showed a wide linear detection range and low limit of detection. Compared to other sensors, this biosensor used a simpler and more environmentally friendly technique and improved electron transfer rate with the use of PEI. It demonstrated superior analytical performance in clinical serums and holds great promise for early lung cancer diagnosis applications.