ABSTRACT
Breast cancer, a disease with highly heterogeneous features, is the most common malignancy diagnosed in people worldwide. Early diagnosis of breast cancer is crucial for improving its cure rate, and accurate classification of the subtype-specific features is essential to precisely treat the disease. An enzyme-powered microRNA (miRNA, RNA = ribonucleic acid) discriminator was developed to selectively distinguish breast cancer cells from normal cells and further identify subtype-specific features. Specifically, miR-21 was used as a universal biomarker to discriminate between breast cancer cells and normal cells, and miR-210 was used to identify triple-negative subtype features. The experimental results demonstrated that the enzyme-powered miRNA discriminator displayed low limits of detection at fM levels for both miR-21 and miR-210. Moreover, the miRNA discriminator enabled the discrimination and quantitative determination of breast cancer cells derived from different subtypes based on their miR-21 levels, and the further identification of the triple-negative subtype in combination with the miR-210 levels. Therefore, it is hoped that this study will provide insight into subtype-specific miRNA profiling, which may have potential use in the clinical management of breast tumours based on their subtype characteristics.
ABSTRACT
Sensitive and selective detection of cancer biomarkers is crucial for early diagnosis and treatment of cancer, one of the most dangerous diseases in the world. Metal-organic frameworks (MOFs), a class of hybrid porous materials fabricated through the assembly of metal ions/clusters and organic ligands, have attracted increasing attention in the sensing of cancer biomarkers, due to the advantages of adjustable size, high porosity, large surface area and ease of modification. MOFs have been utilized to not only fabricate active sensing interfaces but also arouse a variety of measurable signals. Several representative analytical technologies have been applied in MOF-based biosensing strategies to ensure high detection sensitivity toward cancer biomarkers, such as fluorescence, electrochemistry, electrochemiluminescence, photochemistry and colorimetric methods. In this review, we summarized recent advances on MOFs-based biosensing strategies for the detection of cancer biomarkers in recent three years based on the categories of metal nodes, and aimed to provide valuable references for the development of innovative biosensing platform for the purpose of clinical diagnosis.