Funded by the Horizon 2020 framework (Call: Information and Communication Technologies, Disruptive Photonics Technology), the European consortium for REAP consists of 9 multidisciplinary teams from academia, research institute and industry spanning areas of expertise in biology, material science, oncology, chemistry, photonics, electrical and biomedical engineering. In order to benefit from external input, representatives from industry, academia, and health care institutes form an advisory board providing feedback on improvements and adjustments to the project.
Efforts will be intertwined to spearhead developments of microscopy and tomography multimodal imaging systems to provide a platform revealing drug tolerant persister cells in breast cancer in a preclinical setting.
The objective of this project is to reveal the drug tolerant persister cells (DTPs) in cancer using contrast enhanced optical coherence and photoacoustic tomography. Although people have gained unprecedented insight into the molecular mechanism of cancer, the drug resistance of cancer is still the Gordian knot for targeted therapy options, especially for cancers in advanced stages. The ringleader for this resistance can be traced to the DTPs, which can survive treatment. Detection of the DTPs, therefore, is of key importance for cancer treatment. However, due to the scarcity of the DTPs, tracking and analyzing them are extremely challenging with commercially available methods. In this proposal, we aim to reveal these DTPs by multimodal optical imaging. Firstly, a triple-modal two-photon laser scanning optical coherence photoacoustic microscopy (2PLS-OC-PAM) system will be built for in vitro measurements of cancer organoids. Secondly, a dual modality optical coherence photoacoustic tomography (OC-PAT) system will be implemented to visualize the tumors in vivo in a mouse model. A genetically modified mouse model of triple negative breast cancer will be dedicated in this study. As a contrast enhancement measure, nanoparticles will be designed and biofunctionalized to label the DTPs, enabling greatly increased sensitivity and specificity. To improve the image resolution, novel photoacoustic detectors will be developed based on microring technology. Furthermore, the image acquisition speed is expected to be increased by an order of magnitude by bringing in innovative laser sources to be developed in this proposal. Last but not least, real time data handling will be explored in this project as well as deep learning based automatic analysis algorithms. With the combined expertise in laser sources, detector technology, nanoparticle, and deep learning-based algorithms, this proposal has the potential to create completely new applications in imaging.