Biomimetic Nanostructure Platform for Cancer Diagnosis Based on Tumor Biomarkers

Abstract

Biomarker discovery and its clinical use have attracted considerable attention since early cancer diagnosis can significantly decrease mortality. Cancer biomarkers include a wide range of biomolecules, such as nucleic acids, proteins, metabolites, sugars, and cytogenetic substances present in human biofluids. Except for free-circulating biomarkers, tumor-extracellular vesicles (tEVs) and circulating tumor cells (CTCs) can serve as biomarkers for the diagnosis and prognosis of various cancers. Considering the potential of tumor biomarkers in clinical settings, several bioinspired detection systems based on nanotechnologies are in the spotlight for detection. However, tremendous challenges remain in detection because of massive contamination, unstable signal-to-noise ratios due to heterogeneity, nonspecific bindings, or a lack of efficient amplification. To date, many approaches are under development to improve the sensitivity and specificity of tumor biomarker isolation and detection. Particularly, the exploration of natural materials in biological frames has encouraged researchers to develop new bioinspired and biomimetic nanostructures, which can mimic the natural processes to facilitate biomarker capture and detection in clinical settings. These platforms have substantial influence in biomedical applications, owing to their capture ability, significant contrast increase, high sensitivity, and specificity. In this review, we first describe the potential of tumor biomarkers in a liquid biopsy and then provide an overview of the progress of biomimetic nanostructure platforms to isolate and detect tumor biomarkers, including in vitro and in vivo studies. Capture efficiency, scale, amplification, sensitivity, and specificity are the criteria that will be further discussed for evaluating the capability of platforms. Bioinspired and biomimetic systems appear to have a bright future to settle obstacles encountered in tumor biomarker detection, thus enhancing effective cancer diagnosis.