Biomarkers for the early detection of breast cancer
If breast cancers are detected early, survival rates can increase dramatically. One emerging biomarker for liquid biopsy of cancers is extracellular vesicles (EVs), such as exosomes – particles secreted from cells into bodily fluids. While studies have shown that EVs circulating in blood carry molecular information from their cells of origin, including cancer cells, a major challenge was how to extract this information reliably. “EVs are extremely small and heterogeneous, and isolating and characterising disease-relevant vesicles from complex samples such as blood can be difficult and time-consuming,” says Uğur Aygün, research assistant professor at Koç University(opens in new window) in Türkiye. Through the EXCEED project, which was funded by the Marie Skłodowska-Curie Actions(opens in new window) programme, Aygün and his colleagues, including Hakan Ürey(opens in new window) and Utkan Demirci(opens in new window), focused on this analytical bottleneck by developing new approaches for sensitive, label-free and single-particle characterisation of EVs.
Creating a new analytical pipeline for Evs
In EXCEED, the team developed a new analytical pipeline combining ExoTIC(opens in new window), a microfluidic EV isolation technology developed in Demirci’s lab at Stanford University, with a custom-built imaging system able to characterise single particles. The imaging system uses scattered and reflected light to detect individual nanoscale vesicles, meaning they can be detected without fluorescent labels. The team complemented this approach with another technique called Raman spectroscopy (SERS), to gather chemical information from EVs. The platform was evaluated using reference nanoparticles and EVs from cancer and non-cancerous cell models, as well as clinically derived samples. “This allowed us to investigate both the physical and chemical characteristics of these nanoscale vesicles and explore the broader potential of the approach for cancer-related liquid biopsy,” explains Aygün.
Demonstrating label-free detection
One of the most important outcomes of the project was demonstrating label-free detection and characterisation of individual EVs, as small as 30 nm over a relatively large field of view. “This enables the analysis of many individual vesicles simultaneously,” notes Aygün. The team also demonstrated the detection and characterisation of specific cancer-relevant EVs, and explored the broader applicability using samples from other cancer types. In parallel, they developed machine learning approaches to differentiate nanoparticles based on their optical and physical properties. The results demonstrate the broader potential of the platform to combine physical, chemical and computational information for detailed analysis of heterogeneous EV populations.
Expanding EV biomarkers beyond breast cancer
“I believe EVs have significant potential as biomarkers, not only for breast cancer but for many diseases, because they carry molecular information reflecting the cells and tissues from which they originate,” adds Aygün. While EVs are not yet routinely used in clinical blood tests, he says technologies such as those developed in EXCEED can help bridge that gap and may increasingly be used in European health systems in the future. “Initially, these platforms can enable researchers to identify and validate disease-associated EV signatures that are difficult to resolve today,” he remarks. “In the longer term, validated signatures could form the basis of minimally invasive blood tests for monitoring treatment response, disease progression and recurrence, as well as potentially early detection.” During the project, the team realised that the same technologies could be useful not only for studying EVs across different diseases, but also for characterising other biological nanoparticles, including viruses and nanoparticles relevant to vaccine development. “Ultimately, I would like to see these technologies move beyond the research laboratory and become practical tools that researchers and clinicians can use for biomarker discovery and, eventually, blood-based diagnostics,” he says.
