The journal Advanced Materials recently featured a groundbreaking study from the Technion–Israel Institute of Technology, which introduced a novel method for monitoring molecular processes deep within tissue. This new technology, developed by a team of researchers led by Prof. Hossam Haick, Dr. Arnab Maity, and Ph.D. student Vivian Darsa Maidantchik from the Wolfson Faculty of Chemical Engineering at the Technion, is poised to significantly enhance advancements in personalized medicine, cancer diagnosis, and the early detection of diseases. The study also involved collaboration with Dr. Dalit Barkan, Dr. Keren Weidenfeld, and Prof. Sarit Larisch from the University of Haifa’s Faculty of Natural Sciences.
The core of this research is a method designed to enable the functional and molecular mapping of organoids—three-dimensional, cell-based models that closely mimic the structural and functional characteristics of natural tissues. Organoids are becoming an essential tool in biomedical research as they offer a more accurate representation of how tissues behave in the human body compared to traditional two-dimensional cell cultures. They allow scientists to simulate disease conditions, study the effects of treatments on tissues and organs, and model human diseases with a high degree of fidelity. However, despite their immense potential, organoids have long faced challenges in monitoring the internal molecular and functional processes occurring within them.
Traditional methods for studying organoids often have significant limitations. Some techniques, like RNA sequencing, destroy the tissue in the process, making them unsuitable for long-term monitoring or repeated assessments. Other methods, such as confocal microscopy, are effective for visualizing surface-level phenomena but fail to capture the molecular activities happening deep within the tissue. These limitations have hindered progress in organoid-based research, particularly in fields like cancer research, where understanding the molecular changes within tissues is crucial.
The Technion researchers have overcome these challenges with a novel, low-cost, non-invasive approach that provides continuous monitoring of structural and molecular changes within organoids. This innovation, which they have dubbed chemical tomography, offers a solution to the problem of monitoring deep-tissue processes without damaging the tissue or relying on expensive and limited techniques.
Chemical tomography works by detecting volatile organic compounds (VOCs)—molecules present in exhaled breath, saliva, sweat, and other bodily fluids. These VOCs are produced as a result of biochemical reactions in the body, and their presence or changes in their concentrations can offer key insights into various health conditions. Prof. Hossam Haick, who is a leading expert in VOC analysis for early disease detection, has previously developed diagnostic technologies based on VOCs. In this latest study, the researchers used VOC monitoring to perform dynamic molecular and functional mapping of human breast tissue organoids.
By analyzing the VOCs emitted by the organoids, the researchers were able to identify important protein and genomic data linked to the transformation of healthy breast tissue into cancerous tissue. This discovery not only provides deeper insight into the progression of cancer but also holds potential for monitoring disease states and identifying biomarkers for early diagnosis.
The VOCs were detected using a graphene-based sensor array, which captures the compounds and sends the data for analysis by generative artificial intelligence (AI). The technology is inspired by the compound eyes of insects, which are composed of multiple small eyes that each capture part of the visual field. These individual “eyes” send information to the insect’s brain for processing. Similarly, the graphene sensors in the Technion system act as the compound eyes, while the AI functions as the brain, processing and interpreting the complex data. This combination of graphene sensors and AI enables the continuous, real-time monitoring of organoids without causing damage to the tissue.
One of the most exciting aspects of this technology is that it offers a significantly lower cost alternative to current methods. Traditional techniques for studying organoids often require expensive equipment and complex procedures, making them inaccessible to many research labs. In contrast, this chemical tomography method is more affordable, democratizing access to organoid-based research and enabling more scientists to explore these advanced models.
Moreover, the system allows for the real-time mapping of organoids, enabling researchers to track cancer progression at different stages and gain a more comprehensive understanding of cancer biology. By mapping biochemical pathways, metabolic markers, and molecular processes, the system offers insights into how cancer develops, spreads, and interacts with various treatments. This data is invaluable not only for understanding the fundamental mechanisms of cancer but also for designing more effective personalized therapies tailored to the specific molecular makeup of a patient’s disease.
The researchers’ analysis uncovered six distinct biochemical pathways responsible for the production of 12 different types of VOCs. These VOCs could potentially serve as biomarkers for different disease states, further improving diagnostic capabilities. The ability to detect these biomarkers non-invasively provides a major advantage in clinical settings, as it opens the door to more frequent monitoring and earlier intervention in diseases like cancer.
Beyond cancer, the researchers believe that this system has far-reaching applications in diagnosing issues in other organs, such as the kidneys, brain, and liver. The ability to monitor internal tissue health continuously and non-invasively could revolutionize how we approach personalized healthcare. Imagine a system that could transmit real-time data on tissue health to an external monitoring device via an antenna, allowing for continuous tracking of potential health issues and providing early warnings for diseases before symptoms even appear.
This breakthrough also represents a significant step forward in the integration of artificial intelligence into medicine. The use of AI to process vast amounts of data from graphene sensors and provide actionable insights is a major advancement in personalized health care. The researchers envision a future where AI systems are capable of dynamically adjusting treatment plans based on real-time data from an individual’s tissues, paving the way for truly personalized medicine that is tailored to the unique molecular profile of each patient.
Prof. Haick and his team are optimistic about the broad potential of this new system. In his statement, he emphasized that the technology could be applied not only for cancer but also for diagnosing a wide range of diseases. As the system continues to evolve, it could be used in clinical settings for monitoring various conditions in real-time, offering a less invasive, more efficient way to track disease progression and response to treatments.
More information: Arnab Maity et al, Chemical Tomography of Cancer Organoids and Cyto‐Proteo‐Genomic Development Stages Through Chemical Communication Signals, Advanced Materials (2025). DOI: 10.1002/adma.202413017