Nanotechnology-based approaches for effective detection of tumor markers: A comprehensive state-of-the-art review

Abstract

As well-appreciated biomarkers, tumor markers have been spotlighted as reliable tools for predicting the behavior of different tumors and helping clinicians ascertain the type of molecular mechanism of tumorigenesis. The sensitivity and specificity of these markers have made them an object of even broader interest for sensitive detection and staging of various cancers. Enzyme-linked immunosorbent assay (ELISA), fluorescence-based, mass-based, and electrochemical-based detections are current techniques for sensing tumor markers. Although some of these techniques provide good selectivity, certain obstacles, including a low sample concentration or difficulty carrying out the measurement, limit their application. With the advent of nanotechnology, many studies have been carried out to synthesize and employ nanomaterials (NMs) in sensing techniques to determine these tumor markers at low concentrations. The fabrication, sensitivity, design, and multiplexing of sensing techniques have been uplifted due to the attractive features of NMs. Various NMs, such as magnetic and metal nanoparticles, up-conversion NPs, carbon nanotubes (CNTs), carbon-based NMs, quantum dots (QDs), and graphene-based nanosensors, hyperbranched polymers, optical nanosensors, piezoelectric biosensors, paper-based biosensors, microfluidic-based lab-on-chip sensors, and hybrid NMs have proven effective in detecting tumor markers with great sensitivity and selectivity. This review summarizes various categories of NMs for detecting these valuable markers, such as prostate-specific antigen (PSA), human carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), human chorionic gonadotropin (hCG), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA125), cancer antigen 15-3 (CA15-3, MUC1), and cancer antigen 19-9 (CA19-9), and highlights recent nanotechnology-based advancements in detection of these prognostic biomarkers.