Periodic Reporting for period 2 - REAP (Revealing drug tolerant persister cells in cancer using contrast enhanced optical coherence and photoacoustic tomography)
Reporting period: 2022-07-01 to 2023-12-31
The biology and chemistry related tasks are performed by the Center for Cancer Research (CCR) of MUW, AIT, and USC in WP2 and WP3. WP2 completed task T2.1 “in vitro model of drug induced tumor relapse: repopulation assay” with all its milestones and deliverables. This task included the transcriptional profiling of DTP cells of the model, which had high exploitation power in the selection of the NP targeting strategy. In addition, in vitro biocompatibility testing of the NPs on DTP cells within the frame of this task was an essential feasibility test. In task T2.2 “Establishment of in vitro 3D mammary organoids“, establishment and validation of organoids from metastatic mammary tumors was completed, they will be utilized in whole-body course scan OC-PAT settings of WP8. In addition, cancer associated fibroblast (CAF) cell lines derived from the tumor models have been established, which will contribute to the complex in vitro 3D structures for drug analysis and imaging. Although task T2.3 “Genetic engineering of organoids“, has a slight delay, the established CAFs were successfully engineered to express reporters with complementary fluorescence with the matched organoids, which will allow the simultaneous detection of tumor cells and CAFs via 2-photon microscopy. In tasks T2.4 and 2.5 the “in vitro tumor organoid” and the “in vivo organoid-derived transplantation models”, the complete experimental pipeline is established and optimized, including the type of drugs, the applied concentrations and timings, the expected timings of the drug-induced phenotypic stages (DTP/MRD and repopulation/relapse). The missing step shared for both tasks is the validation of protocols with the final engineered organoids that will allow PAI. In addition, in T2.4 we are optimizing the CAF-organoid co-culture conditions and in T2.5 upon obtaining the ethical approval the live-animal implantation and longitudinal testing of the optical window will be performed.
• Contrast agent: biofunctionalized contrast agent will be developed to target the breast cancer cells. The contrast agent will feature tunable absorption peaks specifically designed to enhance the contrast in photoacoustic imaging (PAI).
• Photoacoustic Detector: micro-ring resonator (MRR) based detector with ≤50 μm diameter and ≥160 MHz bandwidth will be developed. Together with the interrogation laser developed in this project, we target at sub-Pa noise equivalent pressure (NEP). MRR arrays will also be developed for real time PAT imaging.
• Laser: triple wavelength photoacoustic microscopy (PAM) excitation laser will be developed with high repetition rate (100 kHz), high energy (1 μJ), low cost (5 k€), and compact size (15 × 15 × 5 cm3). An optical parametric oscillator (OPO) will be developed for PAT excitation with exceptionally high repetition rate (≥ 1 kHz) and energy (≥ 10 mJ). Two dual-purpose lasers will be developed for both all optical detection photoacoustic interrogation and optical coherence tomography (OCT) at 780 nm and 1310 nm with wide bandwidth (40 nm and 100 nm, respectively), narrow linewidth and stable phase.
• System: horizontal 2PLS-OC-PAM system will be developed with subcellular resolution, deep penetration (≥1 mm from one side and ≥2 mm with sample rotation), multiple contrast channels (fluorescence contrast for two- photon laser scanning microscopy (2PLSM), scattering contrast for OCT, absorption contrast for PAM), and fast imaging speed. A high-resolution OC-PAT system will be developed using planar MRR array for localized tumor imaging and image-guided biopsy. A rectangular-MRR-array-based photoacoustic tomography (PAT) system will be developed for deep tissue (≥2 cm penetration depth) imaging and metastasis screening.
• Algorithm: real time image reconstruction algorithms will be developed for all the imaging modalities involved. Needle tracing algorithm will be developed for image-guided biopsy. 3D visualization and quantification algorithms will be developed to perform quantitative analysis of the tumor and the DTP cells.