A study published in Matter has introduced a new microfluidic platform that leverages chiral nanoparticles to isolate and analyze cancer-associated extracellular vesicles from blood plasma. The research, led by Yoon-Tae Kang and colleagues from the University of Michigan, focuses on the development of the CDEXO chip – a device designed to capture and profile cancer-specific exosomes using chiroptical detection – offering potential advancements in liquid biopsy techniques for early cancer diagnosis.

The CDEXO chip incorporates gold nanoparticles with a twisted disk geometry to enhance the detection of exosomes. These nanoparticles exhibit chiroptical properties, allowing them to detect specific surface proteins of exosomes through changes in circular dichroism (CD) signals. The researchers demonstrated that exosomes derived from lung cancer patients could be distinguished from those of healthy donors based on these CD signals, presenting a non-invasive method for identifying cancer-associated biomarkers directly from blood plasma.

One of the team’s key findings is the ability of the CDEXO chip to identify mutations in exosomal surface proteins – specifically mutations in the epidermal growth factor receptor (EGFR), which are common in lung cancer. The device was able to detect both wild-type and mutated EGFR proteins in exosomes with high sensitivity. The CD signal changes were substantial enough to offer a pathway for mutation-specific cancer diagnosis.

The researchers reported a 14-fold increase in detection sensitivity and a 10-fold improvement in detection speed using their microfluidic system compared with traditional approaches.

When the CDEXO chip was tested with exosomes from both healthy donors and patients with non-small cell lung cancer (NSCLC), it demonstrated high specificity, capturing 82 percent of cancer-associated exosomes, compared to 44 percent for normal-cell-derived exosomes. In clinical tests, exosomes from patients with NSCLC showed distinct CD spectral profiles, allowing for the accurate detection of lung cancer-related mutations.

The authors suggest that the platform could be adapted to detect exosomes associated with other tumor types, such as glioblastoma, by targeting different surface markers. Further clinical validation is needed to determine its utility across a wider range of cancers and patient populations.

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