Innovative Technology Successfully Monitors Cancer Progression

Live-cell fluorescence microscopy is currently the predominant method for monitoring the spatiotemporal dynamics of cancer cells, but it has several limitations. These include cytotoxicity caused by fluorescent dyes, cellular photo-damage from prolonged imaging, and the inability to access opaque clinical samples. Such drawbacks hinder long-term and real-time observation of cancer cell evolution and interactions. Now, a novel non-invasive and label-free technique enables quantitative, real-time monitoring of cell spatiotemporal dynamics, providing valuable insights into how cancer cells change over time.

Sensome (Massy, France) has introduced an innovative methodology that uses its revolutionary sensor technology to non-invasively monitor cell spatiotemporal dynamics involved in cancer progression in a real-time and label-free manner, which can provide new insights for cancer diagnosis and treatment. It combines Sensome’s proprietary microsensing technology with micro-electrode arrays and electrical impedance spectroscopy (EIS) to analyze the tissue environment in a label-free, real-time manner. Central to the methodology is the use of predictive algorithms that enable faster data processing, improved noise resilience, and the identification of complex patterns, making it a significant advancement over traditional EIS approaches. In a study conducted in partnership with École Polytechnique (Palaiseau, France), the technology was exposed to both normal and cancerous breast epithelial cells to examine cellular dynamics such as cell density, substrate coverage, mean cell diameter, and cell type.

The technology accurately predicted the spatiotemporal evolution of cellular parameters, with results closely matching those obtained through microscopy. It also enabled real-time tracking of heterogeneities in breast cancer cell growth and competition between normal and cancerous cells using EIS measurements alone. The findings, published in Science Advances, suggest that the platform could replace microscopy in certain cancer monitoring applications. It provides a minimally disruptive method to study cancer cell organization and behavior over extended periods. Looking ahead, the developers are exploring further applications of the sensing platform, including in situ detection for lung cancer and other clinical scenarios, and are actively seeking industrial partnerships to develop medical devices based on this technology.

“This study shows that the proprietary signal processing and machine learning algorithms involved in our technology can empower a method to successfully monitor cancer cell differentiation and evolution over time,” said Franz Bozsak, CEO and co-founder of Sensome, and lead developer of the microsensing platform. This breakthrough is the first step in exploring the use of our tissue-sensing technology in monitoring cancer-related phenomena, such as tumor growth. It complements the work we are currently doing in lung cancer—where in-situ cancer detection is crucial—which is one of several applications where we are applying our mastery of electrical impedance spectroscopy to novel uses in medicine. We are actively seeking industrial partners to realize innovative medical devices centered on our technology.”

“This technology has the potential to obviate the need for microscopy imaging in cancer cell monitoring in various settings and significantly advance our understanding of cancer cell behavior and interactions,” said co-author Abdul Barakat, CNRS Director of Research and Professor at École Polytechnique. “Assessing how cells organize in space and time is essential to elucidating cancer progression. Live-cell fluorescence microscopy is the predominant method for tracking these dynamics today but is often limited by cytotoxicity induced by the fluorescent dyes, by cellular photo-damage during extended periods of microscopic imaging, and by restrictions in optical access in the case of opaque clinical samples. This methodology using Sensome’s technology demonstrates a non-invasive, label-free method enabling long-term monitoring of cancer-related cellular spatiotemporal dynamics with minimal disruption of natural cellular processes.”

Related Links:
Sensome 
École Polytechnique