Towards human-relevant preclinical models: fluid-dynamics and three-dimensionality as key elements

The activity of research of this thesis focuses on the relevance that appropriate in vitro fully humanized models replicating physiological microenvironments and cues (e.g., mechanical and fluidic) are essential for improving human biology knowledge and boosting new compound testing. In biomedical research, the high percentage of the low rate of successful translation from bench to bedside failure is often attributed to the inability of preclinical models in generating reliable results. Indeed, it is well known that 2D models are far from being representative of human complexity and, on the other side, although animal tests are currently required by regulatory organizations, they are commonly considered unpredictive. As a matter of fact, there is a growing awareness that 3D human tissue models and fluid-dynamic scenarios are better reproducers of the in vivo context. Therefore, during this PhD, I have worked to model and validate technologically advanced fluidic platforms, where to replicate biological processes in a systemic and dynamic environment to better assess the pharmacokinetics and the pharmacodynamics of drug candidates, by considering different case studies. First, skin absorption assays have been performed accordingly to the OECD Test Guidelines 428 comparing the standard diffusive chamber (Franz Diffusion Cell) to a novel fluidic commercially available organ on chip platform (MIVO), demonstrating the importance of emulating physiological fluid flows beneath the skin to obtain in vivo-like transdermal penetration kinetics. On the other hand, after an extensive research analysis of the currently available intestinal models, which resulted insufficient in reproducing chemicals and food absorption profiles in vivo, a mathematical model of the intestinal epithelium as a novel screening strategy has been developed. Moreover, since less than 8% of new anticancer drugs are successfully translated from preclinical to clinical trials, breast, and ovarian cancer, which are among the 5 most common causes of death in women, and neuroblastoma, which has one of the lowest survival rates of all pediatric cancers, have been considered. For each, I developed and optimized 3D ECM-like tumor models, then cultured them under fluid-dynamic conditions (previously predicted by CFD simulations) by adopting different (customized or commercially available) fluidic platforms that allowed to mimic u stimuli (fluid velocity and the fluid flow-induced shear stress) and investigate their impact on tumor cells viability and drug response. I provided evidence that such an approach is pivotal to clinically reproduce the complexity and dynamics of the cancer phenomenon (onset, progression, and metastasis) as well as to develop and validate traditional (i.e., platin-based drugs, caffein active molecule) or novel treatment strategies (i.e., hydroxyapatite nanoparticles, NK cells-based immunotherapies)

A multi-organ-on-chip to recapitulate the infiltration and the cytotoxic activity of circulating NK cells in 3D matrix-based tumor model

The success of immunotherapeutic approaches strictly depends on the immune cells interaction with cancer cells. While conventional in vitro cell cultures under-represent the complexity and dynamic crosstalk of the tumor microenvironment, animal models do not allow deciphering the anti-tumor activity of the human immune system. Therefore, the development of reliable and predictive preclinical models has become crucial for the screening of immune-therapeutic approaches. We here present an organ-on-chip organ on chips (OOC)-based approach for recapitulating the immune cell Natural Killer (NK) migration under physiological fluid flow, infiltration within a 3D tumor matrix, and activation against neuroblastoma cancer cells in a humanized, fluid-dynamic environment. Circulating NK cells actively initiate a spontaneous "extravasation " process toward the physically separated tumor niche, retaining their ability to interact with matrix-embedded tumor cells, and to display a cytotoxic effect (tumor cell apoptosis). Since NK cells infiltration and phenotype is correlated with prognosis and response to immunotherapy, their phenotype is also investigated: most importantly, a clear decrease in CD16-positive NK cells within the migrated and infiltrated population is observed. The proposed immune-tumor OOC-based model represents a promising approach for faithfully recapitulating the human pathology and efficiently employing the immunotherapies testing, eventually in a personalized perspective. An immune-organ on chip to recapitulate the tumor-mediated infiltration of circulating immune cells within 3D tumor model

A Human Ovarian Tumor & Liver Organ-on-Chip for Simultaneous and More Predictive Toxo-Efficacy Assays

In oncology, the poor success rate of clinical trials is becoming increasingly evident due to the weak predictability of preclinical assays, which either do not recapitulate the complexity of human tissues (i.e., in vitro tests) or reveal species-specific outcomes (i.e., animal testing). Therefore, the development of novel approaches is fundamental for better evaluating novel anti-cancer treatments. Here, a multicompartmental organ-on-chip (OOC) platform was adopted to fluidically connect 3D ovarian cancer tissues to hepatic cellular models and resemble the systemic cisplatin administration for contemporarily investigating drug efficacy and hepatotoxic effects in a physiological context. Computational fluid dynamics was performed to impose capillary-like blood flows and predict cisplatin diffusion. After a cisplatin concentration screening using 2D/3D tissue models, cytotoxicity assays were conducted in the multicompartmental OOC and compared with static co-cultures and dynamic single-organ models. A linear decay of SKOV-3 ovarian cancer and HepG2 liver cell viability was observed with increasing cisplatin concentration. Furthermore, 3D ovarian cancer models showed higher drug resistance than the 2D model in static conditions. Most importantly, when compared to clinical therapy, the experimental approach combining 3D culture, fluid-dynamic conditions, and multi-organ connection displayed the most predictive toxicity and efficacy results, demonstrating that OOC-based approaches are reliable 3Rs alternatives in preclinic

Biosensors to Monitor Cell Activity in 3D Hydrogel-Based Tissue Models

Three-dimensional (3D) culture models have gained relevant interest in tissue engineering and drug discovery owing to their suitability to reproduce in vitro some key aspects of human tissues and to provide predictive information for in vivo tests. In this context, the use of hydrogels as artificial extracellular matrices is of paramount relevance, since they allow closer recapitulation of (patho)physiological features of human tissues. However, most of the analyses aimed at characterizing these models are based on time-consuming and endpoint assays, which can provide only static and limited data on cellular behavior. On the other hand, biosensing systems could be adopted to measure on-line cellular activity, as currently performed in bi-dimensional, i.e., monolayer, cell culture systems; however, their translation and integration within 3D hydrogel-based systems is not straight forward, due to the geometry and materials properties of these advanced cell culturing approaches. Therefore, researchers have adopted different strategies, through the development of biochemical, electrochemical and optical sensors, but challenges still remain in employing these devices. In this review, after examining recent advances in adapting existing biosensors from traditional cell monolayers to polymeric 3D cells cultures, we will focus on novel designs and outcomes of a range of biosensors specifically developed to provide real-time analysis of hydrogel-based cultures

3D Perfusable Hydrogel Recapitulating the Cancer Dynamic Environment to in Vitro Investigate Metastatic Colonization

Metastasis is a dynamic process involving the dissemination of circulating tumor cells (CTCs) through blood flow to distant tissues within the body. Nevertheless, the development of an in vitro platform that dissects the crucial steps of metastatic cascade still remains a challenge. We here developed an in vitro model of extravasation composed of (i) a single channel-based 3D cell laden hydrogel representative of the metastatic site, (ii) a circulation system recapitulating the bloodstream where CTCs can flow. Two polymers (i.e., fibrin and alginate) were tested and compared in terms of mechanical and biochemical proprieties. Computational fluid-dynamic (CFD) simulations were also performed to predict the fluid dynamics within the polymeric matrix and, consequently, the optimal culture conditions. Next, once the platform was validated through perfusion tests by fluidically connecting the hydrogels with the external circuit, highly metastatic breast cancer cells (MDA-MB-231) were injected and exposed to physiological wall shear stress (WSS) conditions (5 Dyn/cm2) to assess their migration toward the hydrogel. Results indicated that CTCs arrested and colonized the polymeric matrix, showing that this platform can be an effective fluidic system to model the first steps occurring during the metastatic cascade as well as a potential tool to in vitro elucidate the contribution of hemodynamics on cancer dissemination to a secondary sit

High blood flow shear stress values are associated with circulating tumor cells cluster disaggregation in a multi-channel microfluidic device

Metastasis represents a dynamic succession of events involving tumor cells which disseminate through the organism via the bloodstream. Circulating tumor cells (CTCs) can flow the bloodstream as single cells or as multicellular aggregates (clusters), which present a different potential to metastasize. The effects of the bloodstream-related physical constraints, such as hemodynamic wall shear stress (WSS), on CTC clusters are still unclear. Therefore, we developed, upon theoretical and CFD modeling, a new multichannel microfluidic device able to simultaneously reproduce different WSS characterizing the human circulatory system, where to analyze the correlation between SS and CTC clusters behavior. Three physiological WSS levels (i.e. 2, 5, 20 dyn/cm2) were generated, reproducing values typical of capillaries, veins and arteries. As first validation, triple-negative breast cancer cells (MDAMB- 231) were injected as single CTCs showing that higher values of WSS are correlated with a decreased viability. Next, the SS-mediated disaggregation of CTC clusters was computationally investigated in a vessels-mimicking domain. Finally, CTC clusters were injected within the three different circuits and subjected to the three different WSS, revealing that increasing WSS levels are associated with a raising clusters disaggregation after 6 hours of circulation. These results suggest that our device may represent a valid in vitro tool to carry out systematic studies on the biological significance of blood flow mechanical forces and eventually to promote new strategies for anticancer therapy

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Precision measurement of the structure of the CMS inner tracking system using nuclear interactions

The structure of the CMS inner tracking system has been studied using nuclear interactions of hadrons striking its material. Data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded in 2015 at the LHC are used to reconstruct millions of secondary vertices from these nuclear interactions. Precise positions of the beam pipe and the inner tracking system elements, such as the pixel detector support tube, and barrel pixel detector inner shield and support rails, are determined using these vertices. These measurements are important for detector simulations, detector upgrades, and to identify any changes in the positions of inactive elements