Versatile quantitative biopsy: an approach for cost-effective detection of hydrogen peroxide in tissue specimens

Abstract

Biopsies are widely used by surgeons due to their simplicity and practicality, but without sufficient information on a potential biomarker, it is difficult to achieve the goal of accurate disease diagnosis using this strategy. Furthermore, biomarker analysis needs well-developed techniques that are not suitable for detection in poorly equipped areas or rural countries. Therefore, we report a versatile quantitative biopsy (PEG-b-(PPRLT-g-BPmoc)@Amylose/Glu-PGM) for the quantitative detection of biomarkers cost-effectively. In our proposed method, hydrogen peroxide (H₂O₂) is chosen as a potential biomarker due to its close association with cancer progression, which was recognized by an amphiphilic polymer, viz. PEG-b-(PPRLT-g-BPmoc), synthesized via the “click” reaction. The polymer can self-assemble into micelles, in which amylose is ensnared. Emergence of H₂O₂ can activate the micelles and release amylose, which comes into contact with glucoamylase solution added to the sample, leading to the generation of glucose for cost-effective detection by a personal glucose meter (PGM). Through the detection of H₂O₂ in a tumor mice model at different periods (6–30 days), we observed that the PGM value increased significantly from 12 to 30 days, meaning that as the tumor enlarged, the concentration of H₂O₂ maintained an upward trend. Moreover, three kinds of actual cancer samples were studied by PGM, and the breast cancer sample presents the highest concentration of H₂O₂, followed by colon cancer, and cervical cancer shows the lowest concentration of H₂O₂. Thus, the feasibility is verified by quantitative analysis of the H₂O₂ concentration in three kinds of actual cancer and different stages of cancer samples. To the best of our knowledge, this is the first example to rationally design a quantification-based biopsy for low-cost identification of disease, which will provide possibilities for developing biomarker-recognition based quantitative biopsies for hospitals in poorly equipped rural areas.