Periodic Reporting for period 4 - ENDOMICS (Raman Endoscopic Proteo-lipidomics of Bladder Cancer)
Período documentado: 2023-09-01 hasta 2024-09-30
The Problem: Cancer diagnosis currently relies on invasive biopsies and histopathological analysis, which can be time-consuming, subjective, and limited in providing real-time molecular insights. Existing Raman endoscopy, a technique that uses light to analyze tissue composition, offers a non-invasive “optical biopsy,” but it lacks the ability to provide detailed molecular information on the proteins and lipids that drive cancer progression. This limitation makes it difficult to accurately detect, grade, and stage cancer during clinical procedures.
Why It Matters: Cancers are common worldwide, with high recurrence rates and the need for frequent monitoring, leading to a significant burden on healthcare systems and patients. A more precise and real-time diagnostic tool would improve early detection, reduce unnecessary biopsies, and guide more personalized treatment strategies. By providing a deeper understanding of the molecular biology of cancer, this research could also lead to the discovery of new biomarkers for better prognostics and targeted therapies.
Project Objectives: The ENDOMICS project introduced a groundbreaking approach to Raman spectroscopy that allows for lipidomic analysis offering a new level of molecular specificity for cancer diagnostics. To achieve this, the project combined Raman spectroscopy with mass spectrometry to translate vibrational signals into detailed molecular compositions. The project resulted in a new Raman-based technology capable of providing specific molecular analysis. This advancement paves the way for non-invasive, highly specific cancer diagnostics and a deeper understanding of tumor biology, ultimately improving patient outcomes and shaping future cancer research.
Why It Matters: Cancers are common worldwide, with high recurrence rates and the need for frequent monitoring, leading to a significant burden on healthcare systems and patients. A more precise and real-time diagnostic tool would improve early detection, reduce unnecessary biopsies, and guide more personalized treatment strategies. By providing a deeper understanding of the molecular biology of cancer, this research could also lead to the discovery of new biomarkers for better prognostics and targeted therapies.
Project Objectives: The ENDOMICS project introduced a groundbreaking approach to Raman spectroscopy that allows for lipidomic analysis offering a new level of molecular specificity for cancer diagnostics. To achieve this, the project combined Raman spectroscopy with mass spectrometry to translate vibrational signals into detailed molecular compositions. The project resulted in a new Raman-based technology capable of providing specific molecular analysis. This advancement paves the way for non-invasive, highly specific cancer diagnostics and a deeper understanding of tumor biology, ultimately improving patient outcomes and shaping future cancer research.
The ENDOMICS project aimed to revolutionize how doctors detect cancer during endoscopic procedures by making Raman spectroscopy, a technique that uses light to analyze tissues, much more detailed and specific at the molecular level. To do this, we combined Raman spectroscopy with another powerful method called DESI mass spectrometry, creating the world’s first integrated system known as the “Rosetta Stone”. (Jensen et al., Advanced Science 2024) This system uses advanced artificial intelligence to translate complex light signals into detailed chemical fingerprints of tissues in real time, without needing dyes or labels. This breakthrough means doctors can get much clearer and faster information about what’s happening inside the body, potentially spotting cancer more accurately and earlier. Alongside this, we developed new specialized tools to improve how the system “sees” inside tissues, including ways to focus on different depths and to better understand the structure of molecules (Jensen et al., Optics Letters 2020 & Horgan et al., Biomedical Optics Express 2022). These innovations led to patents and important scientific publications. We also tackled a big challenge in making the technology fast enough for clinical use by applying cutting-edge AI methods, which dramatically sped up data collection and analysis (Horgan et al., Analytical Chemistry 2021).
To bring this technology closer to patients, we worked closely with clinicians at Guy’s Hospital and engineers at the London Institute for Healthcare Engineering (LIHE), designing a full clinical trial protocol and securing national funding to start testing in 2025. We also built a fully functional prototype that can be used in real hospital settings, mounted on a medical trolley ready for patient use. We expect a spin-out will be created from this research in 2025-2026.
Throughout the project, we shared our findings widely through high-profile scientific papers and presentations, won awards like the Best Innovation Prize at the 2024 LIHE Accelerator Programme, and partnered with companies such as Ibsen Photonics to explore commercializing our Raman probes. We are now preparing to launch a spin-out company focused on bringing this technology to hospitals for real-time cancer diagnosis. ENDOMICS also invested heavily in training the next generation of scientists and engineers from across Europe, with our team members winning prestigious awards and moving on to top positions in academia and industry worldwide.
In summary, ENDOMICS has taken a major step forward in transforming endoscopy by providing doctors with powerful new tools to detect and monitor cancer more precisely and in real time, opening the door to better patient care and personalized medicine in the near future.
To bring this technology closer to patients, we worked closely with clinicians at Guy’s Hospital and engineers at the London Institute for Healthcare Engineering (LIHE), designing a full clinical trial protocol and securing national funding to start testing in 2025. We also built a fully functional prototype that can be used in real hospital settings, mounted on a medical trolley ready for patient use. We expect a spin-out will be created from this research in 2025-2026.
Throughout the project, we shared our findings widely through high-profile scientific papers and presentations, won awards like the Best Innovation Prize at the 2024 LIHE Accelerator Programme, and partnered with companies such as Ibsen Photonics to explore commercializing our Raman probes. We are now preparing to launch a spin-out company focused on bringing this technology to hospitals for real-time cancer diagnosis. ENDOMICS also invested heavily in training the next generation of scientists and engineers from across Europe, with our team members winning prestigious awards and moving on to top positions in academia and industry worldwide.
In summary, ENDOMICS has taken a major step forward in transforming endoscopy by providing doctors with powerful new tools to detect and monitor cancer more precisely and in real time, opening the door to better patient care and personalized medicine in the near future.
The ENDOMICS project has achieved substantial progress beyond the state of the art by redefining what is possible with Raman spectroscopy. Conventional Raman endoscopy has long been constrained by limited molecular specificity, slow acquisition times, and challenges in translating spectral features into actionable biochemical insights, making its use in real-time cancer diagnostics largely aspirational. Through the development of the integrated Raman/DESI-MS “Rosetta Stone” platform, we have bridged a critical gap by correlating vibrational spectral features with mass spectrometry–derived molecular fingerprints, enabling direct and interpretable biochemical readouts, a conceptual and technical leap not previously achieved in this domain (Jensen et al., Advanced Science 2024). Similarly, our development of advanced Raman probes, combining polarization-resolved detection with depth-selective capabilities, has addressed key limitations in signal specificity and spatial resolution, delivering new capacity to distinguish structural and biochemical features of tissue in situ. The application of deep learning frameworks to Raman data has been transformative, overcoming traditional constraints in acquisition speed and noise management, and positioning our platform as a viable candidate for real-time clinical diagnostics. These innovations collectively advance the state of the art by moving from descriptive, research-oriented Raman imaging to actionable, high-throughput molecular diagnostics suitable for point-of-care use.