Chitosan-based nanosystems for cancer diagnosis and therapy: Stimuli-responsive, immune response, and clinical studies

Cancer, a global health challenge of utmost severity, necessitates innovative approaches beyond conventional treatments (e.g., surgery, chemotherapy, and radiation therapy). Unfortunately, these approaches frequently fail to achieve comprehensive cancer control, characterized by inefficacy, non-specific drug distribution, and the emergence of adverse side effects. Nanoscale systems based on natural polymers like chitosan have garnered significant attention as promising platforms for cancer diagnosis and therapy owing to chitosan's inherent biocompatibility, biodegradability, nontoxicity, and ease of functionalization. Herein, recent advancements pertaining to the applications of chitosan nanoparticles in cancer imaging and drug/gene delivery are deliberated. The readers are introduced to conventional non-stimuli-responsive and stimuli-responsive chitosan-based nanoplatforms. External triggers like light, heat, and ultrasound and internal stimuli such as pH and redox gradients are highlighted. The utilization of chitosan nanomaterials as contrast agents or scaffolds for multimodal imaging techniques e.g., magnetic resonance, fluorescence, and nuclear imaging is represented. Key applications in targeted chemotherapy, combination therapy, photothermal therapy, and nucleic acid delivery using chitosan nanoformulations are explored for cancer treatment. The immunomodulatory effects of chitosan and its role in impacting the tumor microenvironment are analyzed. Finally, challenges, prospects, and future outlooks regarding the use of chitosan-based nanosystems are discussed.

Kinetic Detection of Apoptosis Events Via Caspase 3/7 Activation in a Tumor-Immune Microenvironment on a Chip

The development of advanced biological models like microphysiological systems, able to rebuild the complexity of the physiological and/or pathological environments at a single-cell detail level in an in-vivo-like approach, is proving to be a promising tool to understand the mechanisms of interactions between different cell populations and main features of several diseases. In this frame, the tumor-immune microenvironment on a chip represents a powerful tool to profile key aspects of cancer progression, immune activation, and response to therapy in several immuno-oncology applications. In the present chapter, we provide a protocol to identify and characterize the time evolution of apoptosis by time-lapse fluorescence and confocal imaging in a 3D microfluidic coculture murine model including cancer and spleen cells.

Carbohydrate polymer-based nanocomposites for breast cancer treatment

Breast cancer is known as the most common invasive malignancy in women with the highest mortality rate worldwide. This concerning disease may be presented in situ (relatively easier treatment) or be invasive, especially invasive ductal carcinoma which is highly worrisome nowadays. Among several strategies used in breast cancer treatment, nanotechnology-based targeted therapy is currently being investigated, as it depicts advanced technological features able of preventing drugs' side effects on normal cells while effectively acting on tumor cells. In this context, carbohydrate polymer-based nanocomposites have gained particular interest among the biomedical community for breast cancer therapy applications due to their advantage features, including abundance in nature, biocompatibility, straightforward fabrication methods, and good physicochemical properties. In this review, the physicochemical properties and biological activities of carbohydrate polymers and their derivate nanocomposites were discussed. Then, various methods for the fabrication of carbohydrate polymer-based nanocomposites as well as their application in breast cancer therapy and future perspectives were discussed.

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise invisible processes. Advanced cell assays closely mimicking in vivo scenery are establishing themselves as novel ways to visualize and measure the bidirectional tumor-host interplay influencing the progression of cancer. Here we describe two versatile protocols to recreate highly controllable 2D and 3D co-cultures in microdevices, mimicking the complexity of the tumor microenvironment (TME), under natural and therapy-induced immunosurveillance. In section 1, an experimental setting is provided to monitor crosstalk between adherent tumor cells and floating immune populations, by bright field time-lapse microscopy. As an applicative scenario, we analyze the effects of anti-cancer treatments, such as the so-called immunogenic cancer cell death inducers on the recruitment and activation of immune cells. In section 2, 3D tumor-immune microenvironments are assembled in a competitive layout. Differential immune infiltration is monitored by fluorescence snapshots up to 72 h, to evaluate combination therapeutic strategies. In both settings, image processing steps are illustrated to extract a plethora of immune cell parameters (e.g., immune cell migration and interaction, response to therapeutic agents). These simple and powerful methods can be further tailored to simulate the complexity of the TME encompassing the heterogeneity and plasticity of cancer, stromal and immune cells subtypes, as well as their reciprocal interactions as drivers of cancer evolution. The compliance of these rapidly evolving technologies with live-cell high-content imaging can lead to the generation of large informative datasets, bringing forth new challenges. Indeed, the triangle ''co-cultures/microscopy/advanced data analysis" sets the path towards a precise problem parametrization that may assist tailor-made therapeutic protocols. We expect that future integration of cancer-immune on-a-chip with artificial intelligence for high-throughput processing will synergize a large step forward in leveraging the capabilities as predictive and preclinical tools for precision and personalized oncology.

Organ-on-chip model shows that ATP release through connexin hemichannels drives spontaneous Ca2+ signaling in non-sensory cells of the greater epithelial ridge in the developing cochlea

Prior work supports the hypothesis that ATP release through connexin hemichannels drives spontaneous Ca2+ signaling in non-sensory cells of the greater epithelial ridge (GER) in the developing cochlea; however, direct proof is lacking. To address this issue, we plated cochlear organotypic cultures (COCs) and whole cell-based biosensors with nM ATP sensitivity (ATP-WCBs) at the bottom and top of an ad hoc designed transparent microfluidic chamber, respectively. By performing dual multiphoton Ca2+ imaging, we monitored the propagation of intercellular Ca2+ waves in the GER of COCs and ATP-dependent Ca2+ responses in overlying ATP-WCBs. Ca2+ signals in both COCs and ATP-WCBs were inhibited by supplementing the extracellular medium with ATP diphosphohydrolase (apyrase). Spontaneous Ca2+ signals were strongly depressed in the presence of Gjb6-/- COCs, in which connexin 30 (Cx30) is absent and connexin 26 (Cx26) is strongly downregulated. In contrast, spontaneous Ca2+ signals were not affected by replacement of Panx1-/- with Panx1+/+ COCs in the microfluidic chamber. Similar results were obtained by estimating ATP release from COCs using a classical luciferin-luciferase bioluminescence assay. Therefore, connexin hemichannels and not pannexin 1 channels mediate the release of ATP that is responsible for Ca2+ wave propagation in the developing mouse cochlea. The technological advances presented here have the potential to shed light on a plethora of unrelated open issues that involve paracrine signaling in physiology and pathology and cannot be addressed with standard methods.

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments

We describe a novel method to achieve a universal, massive, and fully automated analysis of cell motility behaviours, starting from time-lapse microscopy images. The approach was inspired by the recent successes in application of machine learning for style recognition in paintings and artistic style transfer. The originality of the method relies i) on the generation of atlas from the collection of single-cell trajectories in order to visually encode the multiple descriptors of cell motility, and ii) on the application of pre-trained Deep Learning Convolutional Neural Network architecture in order to extract relevant features to be used for classification tasks from this visual atlas. Validation tests were conducted on two different cell motility scenarios: 1) a 3D biomimetic gels of immune cells, co-cultured with breast cancer cells in organ-on-chip devices, upon treatment with an immunotherapy drug; 2) Petri dishes of clustered prostate cancer cells, upon treatment with a chemotherapy drug. For each scenario, single-cell trajectories are very accurately classified according to the presence or not of the drugs. This original approach demonstrates the existence of universal features in cell motility (a so called “motility style”) which are identified by the DL approach in the rationale of discovering the unknown message in cell trajectories.

Dissecting Effects of Anti-cancer Drugs and Cancer-Associated Fibroblasts by On-Chip Reconstitution of Immunocompetent Tumor Microenvironments

A major challenge in cancer research is the complexity of the tumor microenvironment, which includes the host immunological setting. Inspired by the emerging technology of organ-on-chip, we achieved 3D co-cultures in microfluidic devices (integrating four cell populations: cancer, immune, endothelial, and fibroblasts) to reconstitute ex vivo a human tumor ecosystem (HER2⁺ breast cancer). We visualized and quantified the complex dynamics of this tumor-on-chip, in the absence or in the presence of the drug trastuzumab (Herceptin), a targeted antibody therapy directed against the HER2 receptor. We uncovered the capacity of the drug trastuzumab to specifically promote long cancer-immune interactions (>50 min), recapitulating an anti-tumoral ADCC (antibody-dependent cell-mediated cytotoxicity) immune response. Cancer-associated fibroblasts (CAFs) antagonized the effects of trastuzumab. These observations constitute a proof of concept that tumors-on-chip are powerful platforms to study ex vivo immunocompetent tumor microenvironments, to characterize ecosystem-level drug responses, and to dissect the roles of stromal components.

Coplanar electrode microfluidic chip enabling accurate sheathless impedance cytometry

Microfluidic impedance cytometry offers a simple non-invasive method for single-cell analysis. Coplanar electrode chips are especially attractive due to ease of fabrication, yielding miniaturized, reproducible, and ultimately low-cost devices. However, their accuracy is challenged by the dependence of the measured signal on particle trajectory within the interrogation volume, that manifests itself as an error in the estimated particle size, unless any kind of focusing system is used. In this paper, we present an original five-electrode coplanar chip enabling accurate particle sizing without the need for focusing. The chip layout is designed to provide a peculiar signal shape from which a new metric correlating with particle trajectory can be extracted. This metric is exploited to correct the estimated size of polystyrene beads of 5.2, 6 and 7 μm nominal diameter, reaching coefficient of variations lower than the manufacturers' quoted values. The potential impact of the proposed device in the field of life sciences is demonstrated with an application to Saccharomyces cerevisiae yeast.

Multivariate analysis applied to Raman mapping of dye-functionalized carbon nanotubes: a novel approach to support the rational design of functional nanostructures

Principal component analysis is applied to analyse the Raman maps collected on carbon nanotubes at different degrees of oxidation and functionalization with dye labeling molecules. The results are used to demonstrate that the technique is extremely effective in clustering data and comparing preparation protocols, so that it enables drawing of a fast and reliable classification of the molecule propensity to interact with pristine and oxidized carbon nanotubes. The spectral findings are supported and elucidated by several experimental techniques, thermogravimetry and steady-state and time-resolved fluorescence measurements, and by computational modeling, showing that the proposed methodology could represent a powerful and routine test for the rational design of functional nanostructures.