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Aptamer versus Antibody Recognition Elements in Electrochemical Biosensors for Breast Cancer Biomarkers: A Comparative Systematic Review and Quantitative Meta-AnalysisFirst

Jul 2026 · International Journal For Multidisciplinary Research · Vol 8 · 0 citations · 15 references

TL;DR

This review highlights the comparison of two electrochemical platforms—antibody-based platform (immunosensor) and aptamer-based platform (aptasensor)—developed from 2021 to 2026 for four important BC biomarkers, human epidermal growth factor receptor 2 (HER2), carbohydrate antigen 15-3 (CA 15-3), carcinoembryonic antigen (CEA), and circulating microRNA-21.

Abstract

Accurate diagnosis of biomarkers of breast cancer (BC) at an early stage is at the centre of the reduction in breast cancer (BC) mortality. In order to provide an alternative, low cost, compact and fast measurement methods to traditional immunoassays and imaging techniques, electrochemical biosensors are now being developed, controlling the analytical performance of the biosensors by choosing the appropriate biorecognition element. This review highlights the comparison of two electrochemical platforms—antibody-based platform (immunosensor) and aptamer-based platform (aptasensor)—developed from 2021 to 2026 for four important BC biomarkers, human epidermal growth factor receptor 2 (HER2), carbohydrate antigen 15-3 (CA 15-3), carcinoembryonic antigen (CEA), and circulating microRNA-21. The limits of detection (LOD), linear range, stability and reproducibility data reported in the literature were reviewed and combined quantitatively, and presented with qualitative consensus scoring for production cost, batch reproducibility and clinical maturity. In general, aptamer-based platforms have an advantage in terms of their chemical stability and low batch-to-batch variability, as antibody-based platforms have an advantage in terms of their analytical maturity and availability, and the analytical level appears to be more dependent on the nanomaterial signal- amplification strategy than on only the recognition-element class. The heterogeneous nature of the validation methods used in different studies makes statistical comparison of studies difficult, and is one of the main translational barriers.

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