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Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor
Published on: February 16, 2018
Non-invasive ultra-sensitive detection of breast cancer biomarker using cerium nanoparticle functionalized graphene
Arpana Parihar1, Preeti Vishwakarma2, Pradeep Prajapati2
1Department of Translational Medicine, All India Institute of Medical Sciences Bhopal, Saket Nagar, Bhopal, 462020, MP, India; Industrial Waste Utilization, Nano and Biomaterials, CSIR-Advanced Materials and Processes Research Institute (AMPRI), Hoshangabad Road, Bhopal, 462026, MP, India.
Abstract:
Epidermal growth factor receptor (EGFR) is a transmembrane protein and a key biomarker implicated in the pathogenesis of breast cancer. Early and precise detection of EGFR is crucial for effective diagnosis, prognosis, and therapeutic intervention. However, conventional EGFR detection techniques, such as biopsy and immunohistochemistry, are often invasive, time-consuming, and limited in sensitivity, highlighting the demand for non-invasive, highly sensitive detection methods. In this study, we fabricated a cerium oxide (CeO₂) and graphene oxide (GO) nanocomposite-based aptasensor for the non-invasive detection of EGFR using electrochemical impedance spectroscopy (EIS). The CeO₂-GO nanocomposite was synthesized via the sol-gel method and characterized through UV-Vis spectroscopy, FTIR, TEM, and XRD, confirming the crystalline structure of hexagonal CeO₂ nanoparticles on amorphous GO sheets. The nanocomposite was functionalized with aptamers specific to EGFR using covalent coupling reactions. The EIS analysis of the fabricated aptasensor (GCE/CeO₂-GO/EGFR-Apt/BSA) demonstrated a wide linear detection range from 10 fg mL-1 to 100 ng mL-1, with an ultralow detection limit of 1.87 fg mL-1 in PBS, 3.16 fg mL-1 in serum, 5.31 fg mL-1 in sweat, and 6.14 fg mL-1 in saliva samples. These results highlight the aptasensor's high sensitivity, specificity, and potential for real-time, non-invasive EGFR monitoring in clinical samples such as serum, sweat, and saliva. This approach would facilitate early detection of cancer and personalized diagnostics in point-of-care settings.

