Colorectal Cancer Label-Free Impedimetric Immunosensor for Blood-Based Biomarker CCSP-2

Abstract

Colorectal cancer (CRC) is one of the most treatable cancers, yet it ranks second in mortality worldwide. Early detection significantly impacts treatment outcomes, but early stage CRC often presents no symptoms or nonspecific symptoms. The current screening methods are invasive and lacks specificity, hindering widespread CRC screening efforts. This underscores the urgent need for improved CRC screening tools. In this study, a label-free impedimetric immunosensor for detecting colon cancer-secreted protein-2 (CCSP-2), which exhibits a mean 78-fold increase in primary colon cancers compared to normal mucosa, was developed. Our cost-effective and noninvasive electrochemical immunosensor for CCSP-2 biomarker detection aims to facilitate early diagnosis and monitoring of CRC. The designed immunosensor features a functionalized gold electrode (Au) modified with cysteine-modified recombinant protein G (RPGCys) to immobilize the CCSP-2 antibody (Ab), and bovine serum albumin (BSA) used to prevent sensor surface fouling. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were employed to analyze the electrochemical response to the binding of CCSP-2 antigen (Ag) and Ab. The changes in relative charge transfer resistance (ΔR_ct/R_cti) with varying concentrations of Ag were plotted and a calibration curve was established between ΔR_ct/R_cti and logarithm of Ag concentration to assess sensor’s sensitivity. The sensor demonstrated a linear response (R² = 0.95) within the range of 10–100 ng/μL, plateauing after 100 ng/μL, with a detection limit of 0.71 ng/μL. Statistical analysis of specificity and selectivity studies showed significant differences in Ag detection compared to blank and nonspecific protein BSA, both with and without cell extracts. This immunosensor effectively detects the CRC biomarker CCSP-2 with high sensitivity and specificity. Integrating this sensor with other sensors for serum CRC biomarkers present a promising approach for developing diagnostic and prognostic tools for CRC.