Nanoscopic technologies toward molecular profiling of single extracellular vesicles for cancer liquid biopsy

Abstract

Extracellular vesicles (EVs) have emerged as promising cancer biomarkers due to their encapsulation of molecular signals reflective of originating tumor cells. Conventional analytical methods often fall short in comprehensive EV molecular profiling, necessitating innovative approaches for enhanced sensitivity and selectivity. This review focuses on the utilization of nanoplasmonic structures for optical signal detection of EVs, exploring advancements, challenges, and future prospects toward single EV molecular profiling. Nanoplasmonic structures offer enhanced optical readout capabilities, leveraging light iridescence, and plasmonic amplification suitable for the size range and complexity of the EVs. We delve into the research and implications of on-chip methods, shedding light on EVs' role in health and disease. Despite notable progress, opportunities still exist to further develop nanoplasmonic arrays, customizing them for bioanalytes of interest, crucial for both label-free and labeled techniques to attain the objectives of their EV profiling. One such example is the use of specific antibodies for surface functionalization in nanoplasmonic arrays. Other approaches involve tailoring the design of platforms to the physical properties of target EVs, thereby enhancing characterization capabilities. The subsequent sections will cover a curated selection of relevant studies. We later discuss EV analysis through plasmonic nanoarrays in clinical sample scenarios. While patterning methods, such as colloidal self-assembly and e-beam lithography, enable integration with microfluidic systems, facilitating future investigations, few technologies have entered clinical trials. This roadblock highlights the need for further development of cost-effective, detailed molecular profiling methods. Moreover, we discuss avenues like single EV profiling and machine learning to address challenges related to heterogeneity of EVs as liquid biopsy biomarkers. Finally, we discuss future opportunities in developing nanoplasmonic-assisted EV profiling and studied their driving advancements in diagnostic and therapeutic realms, such as customizable nanoplasmonic structures coupled with artificial intelligence analysis modules, as a path forward for precise EV molecular profiling, which may enable personalized therapeutic interventions.