Immunomagnetic Fluorogenic ELISA Enabled by HRP-Catalyzed Resorufin Generation for Sensitive Quantification of Carcinoembryonic Antigen in Cancer Cells

Abstract

Sensitive and reliable quantification of tumor biomarkers at the cellular level remains a critical requirement for early cancer diagnosis and therapeutic monitoring. Here, we report a magnetically programmable fluorescence-based enzyme-linked immunosorbent assay (ELISA) that integrates immunomagnetic separation with enzyme-amplified fluorogenic detection for the quantitative analysis of carcinoembryonic antigen (CEA) in gastric cancer cells. The assay employs antibody-functionalized magnetic beads for efficient target capture and isolation, followed by a horseradish peroxidase (HRP)-labeled secondary antibody to enable signal amplification through enzymatic catalysis.

The detection mechanism is based on the HRP-mediated oxidation of the non-fluorescent substrate 10-acetyl-3,7-dihydroxyphenoxazine (ADHP) into highly fluorescent resorufin, providing a robust fluorescence readout with minimal background interference. Systematic optimization of key assay parameters—including incubation time, pH, substrate concentration, oxidant level, and magnetic bead loading—enabled high analytical performance under mild, biologically compatible conditions. The resulting platform exhibited a linear response to CEA concentrations from 3.0 to 60 ng/mL, with a detection limit of 1.5 ng/mL (3σ) and excellent reproducibility (RSD ≈ 1.2%).

Importantly, the method was successfully applied to quantify endogenous CEA in extracts of gastric cancer cells, yielding concentrations in the range of 16.5–28.3 ng/mL with recoveries between 94.7% and 107%, demonstrating strong accuracy and matrix tolerance. Compared with conventional ELISA formats, the proposed approach offers enhanced sensitivity, rapid magnetic separation, reduced sample handling, and improved adaptability to complex biological matrices.

This magnetically assisted fluorogenic ELISA provides a versatile and scalable analytical framework for tumor marker detection and can be readily extended to other clinically relevant biomarkers, supporting its potential integration into cancer diagnostics and bioanalytical platforms.