Periodic Reporting for period 4 - INTERCELLMED (SENSING CELL-CELL INTERACTION HETEROGENEITY IN 3D TUMOR MODELS:TOWARDS PRECISION MEDICINE)
Reporting period: 2022-05-01 to 2023-12-31
Precision oncology and personalized cancer treatment seek to tailor therapies to individual patients. However, translating drug testing results from patient-derived tumor samples to the clinic is hindered by inefficiencies due to inadequate models. This highlights the urgent need for novel tumor models and functional testing methods to enhance cancer care. INTERCELLMED’s goal was to develop a platform for next-generation chemosensitivity assays using 3D cell cultures, mimicking tumor-stroma interactions, and monitoring key physiological mechanisms. Its objectives included synthesizing optical sensors, creating biocompatible 3D matrixes, developing new methods for non-invasive metabolism monitoring and validating these systems for anticancer therapy studies, particularly focusing on pancreatic cancer.
Throughout the duration of the INTERCELLMED project, the team has successfully attained all outlined objectives. The project was meticulously executed, aligning with the three specified goals. For the first objective, we focused on synthesizing silica-based ratiometric fluorescent sensor particles capable of detecting local concentration changes in H+, O2, and K+. We implemented various cost-effective, versatile, and streamlined synthetic methods with scalable capabilities. Additionally, novel functionalization strategies were developed to stably bind fluorescent probes to solid silica microparticle surfaces while preserving their high sensitivity. The second objective involved the development of procedures for engineering 3D cell-culture systems that emulate in vivo cell-cell and cell-matrix interactions. We achieved this by creating 3D extracellular matrix-like structures, such as hydrogels, nanofibers, and additive manufacturing scaffolds, with controlled morphology and chemistry. These structures were integrated with potassium, pH, and oxygen sensing tools, along with pancreatic stromal and tumor cells. Concurrently, we started validating the 3D sensing platforms using patient-derived cells for personalized drug development and treatment planning. Regarding the third objective, which focused on validating the 3D sensing scaffold systems for pharmacological studies of anticancer therapies, we successfully developed and tested two 3D sensing platforms. These platforms were utilized to record spatial and temporal variations in external pH and O2 before and after the addition of standard-of-care chemotherapies. Additionally, innovative models were devised to automatically monitor multiple cell-cell interactions between different cell populations, such as pancreatic tumor and stromal cells. Notably, ad hoc algorithms were employed to accurately track cells during drug treatments, yielding novel insights into the microscopic interactions governing early tumor development stages, where tumor and stromal cells exhibit distinct characteristics. Significantly, we demonstrated the feasibility, ease of production, customization, and practical application of ratiometric analyte sensors with outstanding stability and sensitivity. These sensors proved to be excellent solutions for non-invasive, automated, and precise 3D pH and oxygen tracking at the single-cellular level using straightforward imaging techniques. Consequently, we have provided optical sensing platforms for noninvasive real-time drug screening and cell metabolism analyses on patient-derived 3D models.
The INTERCELLMED project has delivered highly promising tools and novel methodologies for quantifying cell-cell interactions and the dynamic heterogeneity of cancer-stroma kinetics within 3D in vitro tumor models during drug treatment. Furthermore, it has advanced non-invasive metabolism monitoring both in vitro and, in some instances, in patient-derived tumor models, by probing single-cell fermentation fluxes and exchange networks. In addition to these advancements, significant progress has been made in computational analyses through the implementation of robust mathematical models. These models are instrumental in calibrating sensing tools and accurately quantifying local changes in analytes within complex 3D in vitro systems over time. The findings from these studies are poised to make a substantial impact in the field of precision medicine drug development and treatment planning. Moreover, they hold promise for enhancing the long-term prognosis and quality of life for patients affected by these challenging pathologies.