Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functions

Structured multicellular intestinal spheroids (SMIS) as a standardized model for infection biology

BACKGROUND

3D cell culture models have recently garnered increasing attention for replicating organ microarchitecture and eliciting in vivo-like responses, holding significant promise across various biological disciplines. Broadly, 3D cell culture encompasses organoids as well as single- and multicellular spheroids. While the latter have found successful applications in tumor research, there is a notable scarcity of standardized intestinal models for infection biology that mimic the microarchitecture of the intestine. Hence, this study aimed to develop structured multicellular intestinal spheroids (SMIS) specifically tailored for studying molecular basis of infection by intestinal pathogens.

RESULTS

We have successfully engineered human SMIS comprising four relevant cell types, featuring a fibroblast core enveloped by an outer monolayer of enterocytes and goblet cells along with monocytic cells. These SMIS effectively emulate the in vivo architecture of the intestinal mucosal surface and manifest differentiated morphological characteristics, including the presence of microvilli, within a mere two days of culture. Through analysis of various differentiation factors, we have illustrated that these spheroids attain heightened levels of differentiation compared to 2D monolayers. Moreover, SMIS serve as an optimized intestinal infection model, surpassing the capabilities of traditional 2D cultures, and exhibit a regulatory pattern of immunological markers similar to in vivo infections after Campylobacter jejuni infection. Notably, our protocol extends beyond human spheroids, demonstrating adaptability to other species such as mice and pigs.

CONCLUSION

Based on the rapid attainment of enhanced differentiation states, coupled with the emergence of functional brush border features, increased cellular complexity, and replication of the intestinal mucosal microarchitecture, which allows for exposure studies via the medium, we are confident that our innovative SMIS model surpasses conventional cell culture methods as a superior model. Moreover, it offers advantages over stem cell-derived organoids due to scalability and standardization capabilities of the protocol. By showcasing differentiated morphological attributes, our model provides an optimal platform for diverse applications. Furthermore, the investigated differences of several immunological factors compared to monotypic monolayers after Campylobacter jejuni infection underline the refinement of our spheroid model, which closely mimics important features of in vivo infections.

Improved image contrast in nonlinear light-sheet fluorescence microscopy using i 2 PIE Pulse compression

Nonlinear microscopy has become an invaluable tool for biological imaging, offering high-resolution visualization of biological specimens. In this manuscript, we present the application of a spectral phase measurement technique, i2 PIE, to compress broad-bandwidth supercontinuum pulses for two-photon excitation fluorescence light-sheet fluorescence microscopy. The results demonstrated a significant improvement in the two-photon excitation response achieved. We also showed that the implementation of i2 PIE allowed for enhanced image contrasts when compared to conventional compression techniques, with i2 PIE producing an image contrast improvement over conventional methods by over 50%.

Mapping Cell-in-Cell Structures in Oral Squamous Cell Carcinoma

Cell-in-cell (CIC) structures contribute to tumor aggressiveness and poor prognosis in oral squamous cell carcinoma (OSCC). In vitro 3D models may contribute to the understanding of the underlying molecular mechanisms of these events. We employed a spheroid model to study the CIC structures in OSCC. Spheroids were obtained from OSCC (HSC3) and cancer-associated fibroblast (CAF) lines using the Nanoshuttle-PLTM bioprinting system (Greiner Bio-One). Spheroid form, size, and reproducibility were evaluated over time (EvosTM XL; ImageJ version 1.8). Slides were assembled, stained (hematoxylin and eosin), and scanned (Axio Imager Z2/VSLIDE) using the OlyVIA System (Olympus Life Science) and ImageJ software (NIH) for cellular morphology and tumor zone formation (hypoxia and/or proliferative zones) analysis. CIC occurrence, complexity, and morphology were assessed considering the spheroid regions. Well-formed spheroids were observed within 6 h of incubation, showing the morphological aspects of the tumor microenvironment, such as hypoxic (core) and proliferative zone (periphery) formation. CIC structures were found in both homotypic and heterotypic groups, predominantly in the proliferative zone of the mixed HSC3/CAF spheroids. "Complex cannibalism" events were also noted. These results showcase the potential of this model in further studies on CIC morphology, formation, and relationship with tumor prognosis.

Interactions of Nanoscale Self-Assembled Peptide-Based Assemblies with Glioblastoma Cell Models and Spheroids

Peptide nanoassemblies have garnered remarkable importance in the development of novel nanoscale biomaterials for drug delivery into tumor cells. Taking advantage of receptor mediated recognition of two known peptides, angiopep-2 (TFFYGGSRGKRNNFKTEEY) and A-COOP-K (ACGLSGLC10 VAK) that bind to the over-expressed receptors low density lipoprotein (LRP-1) and fatty acid binding protein (FABP3) respectively, we have developed new peptide conjugates by combining the anti-inflammatory, antitumor compound azelaic acid with angiopep-2, which efficiently self-assembled into nanofibers. Those nanofibers were then functionalized with the A-COOP-K sequence and formed supramolecular hierarchical structures that were found to entrap the chemotherapeutic drug doxorubicin efficaciously. Furthermore, the nanoassemblies were found to release the drug in a dose-dependent manner and showed a stepwise increase over a period of 2 weeks under acidic conditions. Two cell lines (U-87-MG and U-138-MG) were utilized as models for glioblastoma cells grown in the presence of serum and under serum-free conditions to mimic the growth conditions of natural tumors. The drug entrapped assemblies were found to inhibit the cell proliferation of both U-87 and U-138MG glioblastoma cells. Three dimensional spheroids of different sizes were grown to mimic the tumors and evaluate the efficacy of drug release and internalization. Our results indicated that the nanoassemblies were found to have higher internalization of DOX and were well-spread throughout the spheroids grown, particularly under serum-free conditions. The nanoassemblies also displayed blood-brain barrier penetration when tested with a multicellular in vitro model. Such self-assembled nanostructures with targeting ability may provide a suitable platform for the development of new peptide-based biomaterials that can provide more insights about the mechanistic approach for drug delivery for not only 2D cell cultures but also 3D tumoroids that mimic the tumor microenvironments.

A cancer model with nonlocal free boundary dynamics

Cancer cells at the tumor boundary move in the direction of the oxygen gradient, while cancer cells far within the tumor are in a necrotic state. This paper introduces a simple mathematical model that accounts for these facts. The model consists of cancer cells, cytotoxic T cells, and oxygen satisfying a system of partial differential equations. Some of the model parameters represent the effect of anti-cancer drugs. The tumor boundary is a free boundary whose dynamics is determined by the movement of cancer cells at the boundary. The model is simulated for radially symmetric and axially symmetric tumors, and it is shown that the tumor may increase or decrease in size, depending on the "strength" of the drugs. Existence theorems are proved, global in-time in the radially symmetric case, and local in-time for any shape of tumor. In the radially symmetric case, it is proved, under different conditions, that the tumor may shrink monotonically, or expand monotonically.

Flipped Well-Plate Hanging-Drop Technique for Growing Three-Dimensional Tumors

Three-dimensional (3D) tumor culture techniques are gaining popularity as in vitro models of tumoral tissue analogues. Despite the widespread interest, need, and present-day effort, most of the 3D tumor culturing methodologies have not gone beyond the inventors’ laboratories. This, in turn, limits their applicability and standardization. In this study, we introduce a straightforward and user-friendly approach based on standard 96-well plates with basic amenities for growing 3D tumors in a scaffold-free/scaffold-based format. Hanging drop preparation can be easily employed by flipping a universal 96-well plate. The droplets of the medium generated by the well-plate flip (WPF) method can be easily modified to address various mechanisms and processes in cell biology, including cancer. To demonstrate the applicability and practicality of the conceived approach, we utilized human colorectal carcinoma cells (HCT116) to first show the generation of large scaffold-free 3D tumor spheroids over 1.5 mm in diameter in single-well plates. As a proof-of-concept, we also demonstrate matrix-assisted tumor culture techniques in advancing the broader use of 3D culture systems. The conceptualized WPF approach can be adapted for a range of applications in both basic and applied biological/engineering research.

3D Spheroids of Human Primary Urine-Derived Stem Cells in the Assessment of Drug-Induced Mitochondrial Toxicity

Mitochondrial toxicity (Mito-Tox) risk has increased due to the administration of several classes of drugs, particularly some life-long antiretroviral drugs for HIV+ individuals. However, no suitable in vitro assays are available to test long-term Mito-Tox (≥4 weeks). The goal of this study is to develop a 3D spheroid system of human primary urine-derived stem cells (USC) for the prediction of drug-induced delayed Mito-Tox. The cytotoxicity and Mito-Tox were assessed in 3D USC spheroids 4 weeks after treatment with antiretroviral drugs: zalcitabine (ddC; 0.1, 1 and 10 µM), tenofovir (TFV; 3, 30 and 300 µM) or Raltegravir (RAL; 2, 20 and 200 µM). Rotenone (RTNN, 10 µM) and 0.1% DMSO served as positive and negative controls. Despite only mild cytotoxicity, ddC significantly inhibited the expression of oxidative phosphorylation enzyme Complexes I, III, and IV; and RAL transiently reduced the level of Complex IV. A significant increase in caspase 3 and ROS/RNS level but a decrease in total ATP were observed in USC treated with ddC, TFV, RAL, and RTNN. Levels of mtDNA content and mitochondrial mass were decreased in ddC but minimally or not in TFV- and RAL-treated spheroids. Thus, 3D USC spheroid using antiretroviral drugs as a model offers an alternative platform to assess drug-induced late Mito-Tox.

Cancer Cell Spheroids as a 3D Model for Exploring the Pathobiology of Vasculogenic Mimicry

Spheroids are 3D spherical cell aggregates, which, cultivated in vitro, behave differently than regular monolayer cellular cultures. Cancer spheroids share many characteristics with in vivo solid tumors, making them a powerful tool in cancer research. The use of cancer spheroids makes it possible to identify the potential of new anticancer pharmacological targets, leading them to be widely used in preclinical oncology research. 3D in vitro models allow the study in detail of many important aspects of the cellular transformation process, such as cell morphology, gene expression, cell-cell and cell-ECM interactions, angiogenesis, and vasculogenic mimicry.In this chapter, the importance of studies using spheroids for current cancer research is described, focusing on vasculogenic mimicry, its morphological structure, and the different methods used in the formation of spheroids. The main method uses agarose to produce the molds for the cancer spheroids, is known as the non-adherent hydrogel micro-mold method, and is being covered in more detail below.

CD133+/CD44+ prostate cancer stem cells exhibit embryo-like behavior patterns

Cancer stem cells (CSCs), which act as an important bridge between cancer formation and embryonic development, represent a small population associated with tumor initiation, drug resistance, metastasis and recurrence. CSCs have the ability to form spheroids in three-dimensional culture systems. Tumor spheroids derived from CSCs with symmetric and asymmetric division patterns were found to contain highly heterogeneous cell groups. The biological behavior patterns which some CSCs display serve as an important bridge between cancer formation and embryonic development. The cell population in the DU-145 prostate cancer cell line with surface markers CD133+/CD44+ was isolated by FACS. Prostate spheroids were formed by using agarose-coated plates. The morphological characteristics of the cell population within spheroid structure and the expression of Ki-67 and Caspase-3 were investigated by histochemical methods. In this study, we observed that CD133+/CD44+ prostate CSCs form different spheroid structures as well as normal spheroid structures: i) some spheroid structures formed with a highly transparent zone on the outer part of the spheroid, in addition to the normal spheroidal zones and ii) spheroidal structures obtained from prostate CD1334+/CD44+ CSCs that share the same microenvironment are hollow spheres similar to the blastula-like structure in the embryo. These spheroidal structures exhibiting embryo-like properties indicate that the expression of embryonic factors might be reiterated in CSCs. Further investigation of the formation mechanism of the transparent zone and the hollow sphere will shed light on the embryonic origin of prostate cancer and the design of new therapeutic strategies.

Fabrication of PNIPAm-based thermoresponsive hydrogel microwell arrays for tumor spheroid formation

Complex three-dimensional (3D) cell cultures are being increasingly implemented in biomedical research as they provide important insights into complex cancer biology, and cell-cell and cell-matrix interactions in the tumor microenvironment. However, most methods used today for 3D cell culture are limited by high cost, the need for specialized skills, low throughput and the use of unnatural culture environments. We report the development of a unique biomimetic hydrogel microwell array platform for the generation and stress-free isolation of cancer spheroids. The poly N-isopropylacrylamide-based hydrogel microwell array (PHMA) has thermoresponsive properties allowing for the attachment and growth of cell aggregates/ spheroids at 37 °C, and their easy isolation at room temperature (RT). The reversible phase transition of the microwell arrays at 35 °C was confirmed visually and by differential scanning calorimetry. Swelling/ shrinking studies and EVOS imaging established that the microwell arrays are hydrophilic and swollen at temperatures <35 °C, while they shrink and are hydrophobic at temperatures >35 °C. Spheroid development within the PHMA was optimized for seeding density, incubation time and cell viability. Spheroids of A549, HeLa and MG-63 cancer cell lines, and human lung fibroblast (HLF) cell line generated within the PHMAs had relatively spherical morphology with hypoxic cores. Finally, using MG-63 cell spheroids as representative models, a proof-of-concept drug response study using doxorubicin hydrochloride was conducted. Overall, we demonstrate that the PHMAs are an innovative alternative to currently used 3D cell culture techniques, for the high-throughput generation of cell spheroids for disease modeling and drug screening applications.

Bioactive three-dimensional silk composite in vitro tumoroid model for high throughput screening of anticancer drugs

HYPOTHESIS

Modeling three-dimensional (3D) in vitro culture systems recapitulating spatiotemporal characteristics of native tumor-mass has shown tremendous potential as a pre-clinical tool for drug screening. However, their applications in clinical settings are still limited due to inappropriate recapitulation of tumor topography, culture instability, and poor durability of niche support.

EXPERIMENTS

Here, we have fabricated a bio-active silk composite scaffold assimilating tunable silk from Bombyx mori and - arginine-glycine-aspartate (RGD) rich silk from Antheraea assama to provide a better 3D-matrix for breast (MCF 7) and liver (HepG2) tumoroids. Cellular mechanisms underlying physiological adaptations in 3D constructs and subsequent drug responses were compared with conventional monolayer and multicellular spheroid culture.

FINDINGS

Silk composite matrix assists prolonged growth and high metabolic activity (Cytochrome P450 reductase) in breast and liver 3D-tumoroids. Enhanced stemness expression (Cell surface adhesion receptor; CD44, Aldehyde dehydrogenase 1) and epithelial-mesenchymal-transition markers (E-cadherin, Vimentin) at transcript and protein levels demonstrate that bio-active matrix-assisted 3D environment augmenting metastatic potential in tumoroids. Together, enhanced secretion of Transforming growth factor β (TGFβ), anchorage-independency, and colony-forming potential of cells in the 3D-tumoroids further corroborates the aggressive behavior of cells. Moreover, the multilayered 3D-tumoroids exhibit decreased sensitivity to some known anticancer drugs (Doxorubicin and Paclitaxel). In conclusion, the bio-active silk composite matrix offers an advantage in developing robust and sustainable 3D tumoroids for a high-throughput drug screening platform.

Discrete Manhattan and Chebyshev pair correlation functions in k dimensions

Pair correlation functions provide a summary statistic which quantifies the amount of spatial correlation between objects in a spatial domain. While pair correlation functions are commonly used to quantify continuous-space point processes, the on-lattice discrete case is less studied. Recent work has brought attention to the discrete case, wherein on-lattice pair correlation functions are formed by normalizing empirical pair distances against the probability distribution of random pair distances in a lattice with Manhattan and Chebyshev metrics. These distance distributions are typically derived on an ad hoc basis as required for specific applications. Here we present a generalized approach to deriving the probability distributions of pair distances in a lattice with discrete Manhattan and Chebyshev metrics, extending the Manhattan and Chebyshev pair correlation functions to lattices in k dimensions. We also quantify the variability of the Manhattan and Chebyshev pair correlation functions, which is important to understanding the reliability and confidence of the statistic.

Combined radiation strategies for novel and enhanced cancer treatment

Numerous studies focus on cancer therapy worldwide, and although many advances have been recorded, the complexity of the disease dictates thinking out of the box to confront it. This study reviews some of the currently available ionizing (IR) and non-ionizing radiation (NIR)-based treatment methods and explores their possible combinations that lead to synergistic, multimodal approaches with promising therapeutic outcomes. Traditional techniques, like radiotherapy (RT) show decent results, although they cannot spare 100% the healthy tissues neighboring with the cancer ones. Targeted therapies, such as proton and photodynamic therapy (PT and PDT, respectively) present adequate outcomes, even though each one has its own drawbacks. To overcome these limitations, the combination of therapeutic modalities has been proposed and has already been showing promising results. At the same time, the recent advances in nanotechnology in the form of nanoparticles enhance cancer therapy, making multimodal treatments worthy of exploring and studying. The combination of RT and PDT has reached the level of clinical trials and is showing promising results. Moreover, in vitro and in vivo studies of nanoparticles with PDT have also provided beneficial results concerning enhanced radiation treatments. In any case, novel and multimodal approaches have to be adopted to achieve personalized, enhanced and effective cancer treatment.

Three-Dimensional Light Sheet Fluorescence Microscopy of Lungs To Dissect Local Host Immune-Aspergillus fumigatus Interactions

The use of animal models of infection is essential to advance our understanding of the complex host-pathogen interactions that take place during Aspergillus fumigatus lung infections. As in the case of humans, mice need to suffer an immune imbalance in order to become susceptible to invasive pulmonary aspergillosis (IPA), the most serious infection caused by A. fumigatus. There are several immunosuppressive regimens that are routinely used to investigate fungal growth and/or immune responses in murine models of invasive pulmonary aspergillosis. However, the precise consequences of the use of each immunosuppressive model for the local immune populations and for fungal growth are not completely understood. Here, to pin down the scenarios involving commonly used IPA models, we employed light sheet fluorescence microscopy (LSFM) to analyze whole lungs at cellular resolution. Our results will be valuable to optimize and refine animal models to maximize their use in future research.

Aspergillus fumigatus is an opportunistic fungal pathogen that can cause life-threatening invasive lung infections in immunodeficient patients. The cellular and molecular processes of infection during onset, establishment, and progression of A. fumigatus infections are highly complex and depend on both fungal attributes and the immune status of the host. Therefore, preclinical animal models are of paramount importance to investigate and gain better insight into the infection process. Yet, despite their extensive use, commonly employed murine models of invasive pulmonary aspergillosis are not well understood due to analytical limitations. Here, we present quantitative light sheet fluorescence microscopy (LSFM) to describe fungal growth and the local immune response in whole lungs at cellular resolution within its anatomical context. We analyzed three very common murine models of pulmonary aspergillosis based on immunosuppression with corticosteroids, chemotherapy-induced leukopenia, or myeloablative irradiation. LSFM uncovered distinct architectures of fungal growth and degrees of tissue invasion in each model. Furthermore, LSFM revealed the spatial distribution, interaction, and activation of two key immune cell populations in antifungal defense: alveolar macrophages and polymorphonuclear neutrophils. Interestingly, the patterns of fungal growth correlated with the detected effects of the immunosuppressive regimens on the local immune cell populations. Moreover, LSFM demonstrates that the commonly used intranasal route of spore administration did not result in complete intra-alveolar deposition, as about 80% of fungal growth occurred outside the alveolar space. Hence, characterization by LSFM is more rigorous than by previously used methods employing murine models of invasive pulmonary aspergillosis and pinpoints their strengths and limitations.

Quantifying the dominant growth mechanisms of dimorphic yeast using a lattice-based model

A mathematical model is presented for the growth of yeast that incorporates both dimorphic behaviour and nutrient diffusion. The budding patterns observed in the standard and pseudohyphal growth modes are represented by a bias in the direction of cell proliferation. A set of spatial indices is developed to quantify the morphology and compare the relative importance of the directional bias to nutrient concentration and diffusivity on colony shape. It is found that there are three different growth modes: uniform growth, diffusion-limited growth (DLG) and an intermediate region in which the bias determines the morphology. The dimorphic transition due to nutrient limitation is investigated by relating the directional bias to the nutrient concentration, and this is shown to replicate the behaviour observed in vivo Comparisons are made with experimental data, from which it is found that the model captures many of the observed features. Both DLG and pseudohyphal growth are found to be capable of generating observed experimental morphologies.

Understanding interactions between populations: Individual based modelling and quantification using pair correlation functions

Understanding the underlying mechanisms that produce the huge variety of swarming and aggregation patterns in animals and cells is fundamental in ecology, developmental biology, and regenerative medicine, to name but a few examples. Depending upon the nature of the interactions between individuals (cells or animals), a variety of different large-scale spatial patterns can be observed in their distribution; examples include cell aggregates, stripes of different coloured skin cells, etc. For the case where all individuals are of the same type (i.e., all interactions are alike), a considerable literature already exists on how the collective organisation depends on the inter-individual interactions. Here, we focus on the less studied case where there are two different types of individuals present. Whilst a number of continuum models of this scenario exist, it can be difficult to compare these models to experimental data, since real cells and animals are discrete. In order to overcome this problem, we develop an agent-based model to simulate some archetypal mechanisms involving attraction and repulsion. However, with this approach (as with experiments), each realisation of the model is different, due to stochastic effects. In order to make useful comparisons between simulations and experimental data, we need to identify the robust features of the spatial distributions of the two species which persist over many realisations of the model (for example, the size of aggregates, degree of segregation or intermixing of the two species). In some cases, it is possible to do this by simple visual inspection. In others, the features of the pattern are not so clear to the unaided eye. In this paper, we introduce a pair correlation function (PCF), which allows us to analyse multi-species spatial distributions quantitatively. We show how the differing strengths of inter-individual attraction and repulsion between species give rise to different spatial patterns, and how the PCF can be used to quantify these differences, even when it might be impossible to recognise them visually.

Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids

Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid’s size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 10⁵ to 1 × 10⁶cells/mm³. Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.