INSIDIA: A FIJI Macro Delivering High-Throughput and High-Content Spheroid Invasion Analysis

Galectin-3-Binding Protein Inhibits Extracellular Heparan 6-O-Endosulfatase Sulf-2

Human extracellular 6-O-endosulfatases Sulf-1 and Sulf-2 are the only enzymes that post-synthetically alter the 6-O sulfation of heparan sulfate proteoglycans (HSPG), which regulates interactions of HSPG with many proteins. Oncogenicity of Sulf-2 in different cancers has been documented, and we have shown that Sulf-2 is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC). Despite its importance, limited information is available on direct protein-protein interactions of the Sulf-2 protein in the tumor microenvironment. In this study, we used monoclonal antibody (mAb) affinity purification and mass spectrometry to identify galectin-3-binding protein (LG3BP) as a highly specific binding partner of Sulf-2 in the conditioned media of HNSCC cell lines. We validated their direct interaction in vitro using recombinant proteins and have shown that the chondroitin sulfate (CS) covalently bound to the Sulf-2 influences the binding to LG3BP. We confirmed the importance of the CS chain for the interaction by generating a mutant Sulf-2 protein that lacks the CS. Importantly, we have shown that the LG3BP inhibits Sulf-2 activity in vitro in a concentration-dependent manner. As a consequence, the addition of LG3BP to a spheroid cell culture inhibited the invasion of the HNSCC cells into Matrigel. Thus, Sulf-2 interaction with LG3BP may regulate the physiological activity of the Sulf-2 enzyme as well as its activity in the tumor microenvironment.

Bridging the Gap: Integrating 3D Bioprinting and Microfluidics for Advanced Multi-Organ Models in Biomedical Research

Recent advancements in 3D bioprinting and microfluidic lab-on-chip systems offer promising solutions to the limitations of traditional animal models in biomedical research. Three-dimensional bioprinting enables the creation of complex, patient-specific tissue models that mimic human physiology more accurately than animal models. These 3D bioprinted tissues, when integrated with microfluidic systems, can replicate the dynamic environment of the human body, allowing for the development of multi-organ models. This integration facilitates more precise drug screening and personalized therapy development by simulating interactions between different organ systems. Such innovations not only improve predictive accuracy but also address ethical concerns associated with animal testing, aligning with the three Rs principle. Future directions include enhancing bioprinting resolution, developing advanced bioinks, and incorporating AI for optimized system design. These technologies hold the potential to revolutionize drug development, regenerative medicine, and disease modeling, leading to more effective, personalized, and humane treatments.

Plant-derived extracellular nanovesicles: a promising biomedical approach for effective targeting of triple negative breast cancer cells

Introduction: Triple negative breast cancer (TNBC), a highly aggressive subtype accounting for 15-20% of all breast cancer cases, faces limited treatment options often accompanied by severe side effects. In recent years, natural extracellular nanovesicles derived from plants have emerged as promising candidates for cancer therapy, given their safety profile marked by non-immunogenicity and absence of inflammatory responses. Nevertheless, the potential anti-cancer effects of Citrus limon L.-derived extracellular nanovesicles (CLENs) for breast cancer treatment is still unexplored. Methods: In this study, we investigated the anti-cancer effects of CLENs on two TNBC cell lines (4T1 and HCC-1806 cells) under growth conditions in 2D and 3D culture environments. The cellular uptake efficiency of CLENs and their internalization mechanism were evaluated in both cells using confocal microscopy. Thereafter, we assessed the effect of different concentrations of CLENs on cell viability over time using a dual approach of Calcein-AM PI live-dead assay and CellTiter-Glo bioluminescence assay. We also examined the influence of CLENs on the migratory and evasion abilities of TNBC cells through wound healing and 3D Matrigel drop evasion assays. Furthermore, Western blot analysis was employed to investigate the effects of CLENs on the phosphorylation levels of phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), and extracellular signal- regulated kinase (ERK) expression. Results: We found that CLENs were internalized by the cells via endocytosis, leading to decreased cell viability, in a dose- and time-dependent manner. Additionally, the migration and evasion abilities of TNBC cells were significantly inhibited under exposed to 40 and 80 μg/mL CLENs. Furthermore, down-regulated expression levels of phosphorylated phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), and extracellular signal-regulated kinase (ERK), suggesting that the inhibition of cancer cell proliferation, migration, and evasion is driven by the inhibition of the PI3K/AKT and MAPK/ERK signaling pathways. Discussion: Overall, our results demonstrate the anti-tumor efficiency of CLENs against TNBC cells, highlighting their potential as promising natural anti-cancer agents for clinical applications in cancer treatment.

Generation of 3D melanoma models using an assembloid-based approach

While 3D tumor models have greatly evolved over the past years, there is still a strong requirement for more biosimilar models which are capable of recapitulating cellular crosstalk within the tumor microenvironment while equally displaying representative levels of tumor aggressiveness and invasion. Herein, we disclose an assembloid melanoma model based on the fusion of individual stromal multicellular spheroids (MCSs). In contrast to more traditional tumor models, we show that it is possible to develop self-organizing, heterotypic melanoma models where tumor cells present stem-cell like features like up-regulated pluripotency master regulators SOX2, POU5F1 and NANOG. Additionally, these assembloids display high levels of invasiveness while embedded in 3D matrices as evidenced by stromal cell promotion of melanoma cell invasion via metalloproteinase production. Furthermore, sensitivity to anticancer drug doxorubicin was demonstrated for the melanoma assembloid model. These findings suggest that melanoma assembloids may play a significant role in the field of 3D cancer models as they more closely mimic the tumor microenvironment when compared to more traditional MCSs, opening the doors to a better understanding of the role of tumor microenvironment in supporting tumor progression. STATEMENT OF SIGNIFICANCE: The development of complex 3D tumor models that better recapitulate the tumor microenvironment is crucial for both an improved comprehension of intercellular crosstalk and for more efficient drug screening. We have herein developed a self-organizing heterotypic assembloid-based melanoma model capable of closely mimicking the tumor microenvironment. Key features recapitulated were the preservation of cancer cell stemness, sensitivity to anti-cancer agents and tumor cell invasion promoted by stromal cells. The approach of pre-establishing distinct stromal domains for subsequent combination into more complex tumor constructs provides a route for developing superior tumor models with a higher degree of similarity to native cancer tissues.

Galectin-3-binding protein inhibits extracellular heparan 6-O-endosulfatse Sulf-2

Human extracellular 6-O-endosulfatases Sulf-1 and Sulf-2 are the only enzymes that post-synthetically alter the 6-O sulfation of heparan sulfate proteoglycans (HSPG), which regulates interactions of HSPG with many proteins. Oncogenicity of Sulf-2 in different cancers has been documented and we have shown that Sulf-2 is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC). In spite of its importance, limited information is available on direct protein-protein interactions of the Sulf-2 protein in the tumor microenvironment. In this study, we used monoclonal antibody (mAb) affinity purification and mass spectrometry to identify galectin-3-binding protein (LG3BP) as a highly specific binding partner of Sulf-2 in the secretome of HNSCC cell lines. We validated their direct interaction in vitro using recombinant proteins and have shown that the chondroitin sulfate (CS) covalently bound to the Sulf-2 influences the binding to LG3BP. We confirmed importance of the CS chain for the interaction by generating a mutant Sulf-2 protein that lacks the CS. Importantly, we have shown that the LG3BP inhibits Sulf-2 activity in vitro in a concentration dependent manner. As a consequence, the addition of LG3BP to a spheroid cell culture inhibited invasion of the HNSCC cells into Matrigel. Thus, Sulf-2 interaction with LG3BP has functional relevance, and may regulate physiological activity of the Sulf-2 enzyme as well as its activity in the tumor microenvironment.

Carboxylated graphene quantum dots-mediated photothermal therapy enhances drug-membrane permeability, ROS production, and the immune system recruitment on 3D glioblastoma models

Graphene quantum dots (GQDs) are biocompatible nanoparticles employed in biomedical field, thanks to their size and photophysical properties. GQDs have shown the capability to cross biological barriers, including the blood–brain barrier, which makes them promising agents for brain diseases therapy. It has been shown that surface-functionalized GQDs enhance membrane fluidity and intracellular uptake, exerting a synergistic effect with antitumor drugs at subtherapeutic doses. Here, we tested GQDs effects in combination with chemotherapeutic agents doxorubicin and temozolomide, on a complex 3D spheroid model of glioblastoma. We observed that the capability of GQDs to absorb and convert near-infrared light into heat is a key factor in membrane permeability enhancement on 3D model. This non-invasive therapeutic strategy named photothermal therapy (PTT), combined to chemotherapy at subtherapeutic doses, significantly increased the effect of antitumor drugs by reducing tumor growth and viability. Furthermore, the increase in membrane permeability due to GQDs-mediated PTT enhanced the release of reactive oxygen species with strong migration of the immune system towards irradiated cancer spheroids. Our data indicate that the increase in membrane permeability can enhance the efficacy of antitumor drugs at subtherapeutic doses against glioblastoma, reducing side effects, and directing immune response, ultimately improving quality of life for patients.

Extreme transport of light in spheroids of tumor cells

Extreme waves are intense and unexpected wavepackets ubiquitous in complex systems. In optics, these rogue waves are promising as robust and noise-resistant beams for probing and manipulating the underlying material. Localizing large optical power is crucial especially in biomedical systems, where, however, extremely intense beams have not yet been observed. We here discover that tumor-cell spheroids manifest optical rogue waves when illuminated by randomly modulated laser beams. The intensity of light transmitted through bio-printed three-dimensional tumor models follows a signature Weibull statistical distribution, where extreme events correspond to spatially-localized optical modes propagating within the cell network. Experiments varying the input beam power and size indicate that the rogue waves have a nonlinear origin. We show that these nonlinear optical filaments form high-transmission channels with enhanced transmission. They deliver large optical power through the tumor spheroid, and can be exploited to achieve a local temperature increase controlled by the input wave shape. Our findings shed light on optical propagation in biological aggregates and demonstrate how nonlinear extreme event formation allows light concentration in deep tissues, paving the way to using rogue waves in biomedical applications, such as light-activated therapies.

SpheroScan: a user-friendly deep learning tool for spheroid image analysis

BACKGROUND

In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays.

RESULTS

To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results.

CONCLUSION

SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan.

INSIDIA 2.0 High-Throughput Analysis of 3D Cancer Models: Multiparametric Quantification of Graphene Quantum Dots Photothermal Therapy for Glioblastoma and Pancreatic Cancer

Cancer spheroids are in vitro 3D models that became crucial in nanomaterials science thanks to the possibility of performing high throughput screening of nanoparticles and combined nanoparticle-drug therapies on in vitro models. However, most of the current spheroid analysis methods involve manual steps. This is a time-consuming process and is extremely liable to the variability of individual operators. For this reason, rapid, user-friendly, ready-to-use, high-throughput image analysis software is necessary. In this work, we report the INSIDIA 2.0 macro, which offers researchers high-throughput and high content quantitative analysis of in vitro 3D cancer cell spheroids and allows advanced parametrization of the expanding and invading cancer cellular mass. INSIDIA has been implemented to provide in-depth morphologic analysis and has been used for the analysis of the effect of graphene quantum dots photothermal therapy on glioblastoma (U87) and pancreatic cancer (PANC-1) spheroids. Thanks to INSIDIA 2.0 analysis, two types of effects have been observed: In U87 spheroids, death is accompanied by a decrease in area of the entire spheroid, with a decrease in entropy due to the generation of a high uniform density spheroid core. On the other hand, PANC-1 spheroids' death caused by nanoparticle photothermal disruption is accompanied with an overall increase in area and entropy due to the progressive loss of integrity and increase in variability of spheroid texture. We have summarized these effects in a quantitative parameter of spheroid disruption demonstrating that INSIDIA 2.0 multiparametric analysis can be used to quantify cell death in a non-invasive, fast, and high-throughput fashion.

Upregulation of Cathepsin X in Glioblastoma: Interplay with γ-Enolase and the Effects of Selective Cathepsin X Inhibitors

Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Understanding GBM pathobiology and discovering novel therapeutic targets are critical to finding efficient treatments. Upregulation of the lysosomal cysteine carboxypeptidase cathepsin X has been linked to immune dysfunction and neurodegenerative diseases, but its role in cancer and particularly in GBM progression in patients is unknown. In this study, cathepsin X expression and activity were found to be upregulated in human GBM tissues compared to low-grade gliomas and nontumor brain tissues. Cathepsin X was localized in GBM cells as well as in tumor-associated macrophages and microglia. Subsequently, potent irreversible (AMS36) and reversible (Z7) selective cathepsin X inhibitors were tested in vitro. Selective cathepsin X inhibitors decreased the viability of patient-derived GBM cells as well as macrophages and microglia that were cultured in conditioned media of GBM cells. We next examined the expression pattern of neuron-specific enzyme γ-enolase, which is the target of cathepsin X. We found that there was a correlation between high proteolytic activity of cathepsin X and C-terminal cleavage of γ-enolase and that cathepsin X and γ-enolase were colocalized in GBM tissues, preferentially in GBM-associated macrophages and microglia. Taken together, our results on patient-derived material suggest that cathepsin X is involved in GBM progression and is a potential target for therapeutic approaches against GBM.

Biobanked Glioblastoma Patient-Derived Organoids as a Precision Medicine Model to Study Inhibition of Invasion

Glioblastoma (GBM) is highly resistant to treatment and invasion into the surrounding brain is a cancer hallmark that leads to recurrence despite surgical resection. With the emergence of precision medicine, patient-derived 3D systems are considered potentially robust GBM preclinical models. In this study, we screened a library of 22 anti-invasive compounds (i.e., NF-kB, GSK-3-B, COX-2, and tubulin inhibitors) using glioblastoma U-251 MG cell spheroids. We evaluated toxicity and invasion inhibition using a 3D Matrigel invasion assay. We next selected three compounds that inhibited invasion and screened them in patient-derived glioblastoma organoids (GBOs). We developed a platform using available macros for FIJI/ImageJ to quantify invasion from the outer margin of organoids. Our data demonstrated that a high-throughput invasion screening can be done using both an established cell line and patient-derived 3D model systems. Tubulin inhibitor compounds had the best efficacy with U-251 MG cells, however, in ex vivo patient organoids the results were highly variable. Our results indicate that the efficacy of compounds is highly related to patient intra and inter-tumor heterogeneity. These results indicate that such models can be used to evaluate personal oncology therapeutic strategies.

Light-Inducible Spatio-Temporal Control of TLR4 and NF-κB-Gluc Reporter in Human Pancreatic Cell Line

Augmented Toll-like receptor 4 (TLR4) expression was found in nearly 70% of patients with pancreatic adenocarcinoma, which is correlated with increased tumorigenesis and progression. In this study, we engineered a new light-oxygen-voltage-sensing (LOV) domain-based optogenetic cell line (opto-TLR4 PANC-1) that enables time-resolved activation of the NF-κB and extracellular-signal regulated kinases (ERK)1/2 signalling pathway upon blue light-sensitive homodimerisation of the TLR4-LOV fusion protein. Continuous stimulation with light indicated strong p65 and ERK1/2 phosphorylation even after 24 h, whereas brief light exposure peaked at 8 h and reached the ground level 24 h post-illumination. The cell line further allows a voltage-dependent TLR4 activation, which can be continuously monitored, turned on by light or off in the dark. Using this cell line, we performed different phenotypic cell-based assays with 2D and 3D cultures, with the aim of controlling cellular activity with spatial and temporal precision. Light exposure enhanced cell attachment, the formation and extension of invadopodia, and cell migration in 3D spheroid cultures, but no significant changes in proliferation or viability could be detected. We conclude that the opto-TLR4 PANC-1 cell line is an ideal tool for investigating the underlying molecular mechanisms of TLR4, thereby providing strategies for new therapeutic options.

Caveolin-1, a Key Mediator Across Multiple Pathways in Glioblastoma and an Independent Negative Biomarker of Patient Survival

Glioblastoma (GB) remains an aggressive malignancy with an extremely poor prognosis. Discovering new candidate drug targets for GB remains an unmet medical need. Caveolin-1 (Cav-1) has been shown to act variously as both a tumour suppressor and tumour promoter in many cancers. The implications of Cav-1 expression in GB remains poorly understood. Using clinical and genomic databases we examined the relationship between tumour Cav-1 gene expression (including its spatial distribution) and clinical pathological parameters of the GB tumour and survival probability in a TCGA cohort (n=155) and CGGA cohort (n=220) of GB patients. High expression of Cav-1 represented a significant independent predictor of shortened survival (HR = 2.985, 5.1 vs 14.9 months) with a greater statistically significant impact in female patients and in the Proneural and Mesenchymal GB subtypes. High Cav-1 expression correlated with other factors associated with poor prognosis: IDH w/t status, high histological tumour grade and low KPS score. A total of 4879 differentially expressed genes (DEGs) in the GB tumour were found to correlate with Cav-1 expression (either positively or negatively). Pathway enrichment analysis highlighted an over-representation of these DEGs to certain biological pathways. Focusing on those that lie within a framework of epithelial to mesenchymal transition and tumour cell migration and invasion we identified 27 of these DEGs. We then examined the prognostic value of Cav-1 when used in combination with any of these 27 genes and identified a subset of combinations (with Cav-1) indicative of co-operative synergistic mechanisms of action. Overall, the work has confirmed Cav-1 can serve as an independent prognostic marker in GB, but also augment prognosis when used in combination with a panel of biomarkers or clinicopathologic parameters. Moreover, Cav-1 appears to be linked to many signalling entities within the GB tumour and as such this work begins to substantiate Cav-1 or its associated signalling partners as candidate target for GB new drug discovery.

Inhibiting the Growth of 3D Brain Cancer Models with Bio-Coronated Liposomal Temozolomide

Nanoparticles (NPs) have emerged as an effective means to deliver anticancer drugs into the brain. Among various forms of NPs, liposomal temozolomide (TMZ) is the drug-of-choice for the treatment and management of brain tumours, but its therapeutic benefit is suboptimal. Although many possible reasons may account for the compromised therapeutic efficacy, the inefficient tumour penetration of liposomal TMZ can be a vital obstacle. Recently, the protein corona, i.e., the layer of plasma proteins that surround NPs after exposure to human plasma, has emerged as an endogenous trigger that mostly controls their anticancer efficacy. Exposition of particular biomolecules from the corona referred to as protein corona fingerprints (PCFs) may facilitate interactions with specific receptors of target cells, thus, promoting efficient internalization. In this work, we have synthesized a set of four TMZ-encapsulating nanomedicines made of four cationic liposome (CL) formulations with systematic changes in lipid composition and physical−chemical properties. We have demonstrated that precoating liposomal TMZ with a protein corona made of human plasma proteins can increase drug penetration in a 3D brain cancer model derived from U87 human glioblastoma multiforme cell line leading to marked inhibition of tumour growth. On the other side, by fine-tuning corona composition we have also provided experimental evidence of a non-unique effect of the corona on the tumour growth for all the complexes investigated, thus, clarifying that certain PCFs (i.e., APO-B and APO-E) enable favoured interactions with specific receptors of brain cancer cells. Reported results open new perspectives into the development of corona-coated liposomal drugs with enhanced tumour penetration and antitumour efficacy.

SpheroidJ: An Open-Source Set of Tools for Spheroid Segmentation

BACKGROUND AND OBJECTIVES

Spheroids are the most widely used 3D models for studying the effects of different micro-environmental characteristics on tumour behaviour, and for testing different preclinical and clinical treatments. In order to speed up the study of spheroids, imaging methods that automatically segment and measure spheroids are instrumental; and, several approaches for automatic segmentation of spheroid images exist in the literature. However, those methods fail to generalise to a diversity of experimental conditions. The aim of this work is the development of a set of tools for spheroid segmentation that works in a diversity of settings.

METHODS

In this work, we have tackled the spheroid segmentation task by first developing a generic segmentation algorithm that can be easily adapted to different scenarios. This generic algorithm has been employed to reduce the burden of annotating a dataset of images that, in turn, has been employed to train several deep learning architectures for semantic segmentation. Both our generic algorithm and the constructed deep learning models have been tested with several datasets of spheroid images where the spheroids were grown under several experimental conditions, and the images acquired using different equipment.

RESULTS

The developed generic algorithm can be particularised to different scenarios; however, those particular algorithms fail to generalise to different conditions. By contrast, the best deep learning model, constructed using the HRNet-Seg architecture, generalises properly to a diversity of scenarios. In order to facilitate the dissemination and use of our algorithms and models, we present SpheroidJ, a set of open-source tools for spheroid segmentation.

CONCLUSIONS

In this work, we have developed an algorithm and trained several models for spheroid segmentation that can be employed with images acquired under different conditions. Thanks to this work, the analysis of spheroids acquired under different conditions will be more reliable and comparable; and, the developed tools will help to advance our understanding of tumour behaviour.

Concentration-Dependent Pro- and Antitumor Activities of Quercetin in Human Melanoma Spheroids: Comparative Analysis of 2D and 3D Cell Culture Models

Quercetin, a dietary flavonoid found in fruits and vegetables, has been described as a substance with many anti-cancer properties in a variety of preclinical investigations. In the present study, we demonstrate that 2D and 3D melanoma models exhibit not only different sensitivities to quercetin, but also opposite, cancer-promoting effects when metastatic melanoma spheroids are treated with quercetin. Higher concentrations of quercetin reduce melanoma growth in three tested cell lines, whereas low concentrations induce the opposite effect in metastatic melanoma spheroids but not in the non-metastatic cell line. High (>12.5 µM) or low (<6.3 µM) quercetin concentrations decrease or enhance cell viability, spheroid size, and cell proliferation, respectively. Additionally, melanoma cells cultivated in 2D already show significant caspase 3 activity at very low concentrations (>0.4 µM), whereas in 3D spheroids apoptotic cells, caspase 3 activity can only be detected in concentrations ≥12.5 µM. Further, we show that the tumor promoting or repressing effect in the 3D metastatic melanoma spheroids are likely to be elicited by a precisely controlled regulation of Nrf2/ARE-mediated cytoprotective genes, as well as ERK and NF-κB phosphorylation. According to the results obtained here, further studies are needed to better characterize the mechanisms of action underlying the pro- and anti-carcinogenic effects of quercetin on human melanomas.

Effective Permeation of Anticancer Drugs into Glioblastoma Spheroids via Conjugation with a Sulfobetaine Copolymer

Three-dimensional cell aggregates (spheroids) are becoming a research focus because their construction is similar to that in vivo microenvironments, enabling the acceleration of drug discovery and reducing the need for animal tests, and other advantages. However, the delivery of drugs to the inside of spheroids is time-consuming and has low efficiency. In this study, we selected a sulfobetaine copolymer that translocates to the cell membrane in monolayer cultured cells as a nanocarrier of anticancer drugs. Doxorubicin (Dox) and 17-demethoxy-17-allylamino geldanamycin (17AAG) were modified to the copolymer of sulfobetaine methacrylate and poly(ethylene glycol) methacrylate, P(SB-PEG), and added to glioblastoma A-172 cell spheroids. Dox-P(SB-PEG) showed fast permeation into A-172 spheroids, and the fluorescence in cells was observed in the center area of the spheroids within 1 h of polymer addition. Conversely, only the outer one to two cell layers of spheroids were observed when Dox was added to the spheroids. Dox-P(SB-PEG) in A-172 spheroids was localized in the mitochondria of each cell and exhibited comparable drug efficacy to that of Dox in growth inhibition assays of A-172 spheroids. Moreover, approximately 10-fold higher drug efficacy in growth inhibition and invasion of A-172 spheroids was found using 17AAG-P(SB-PEG). Conjugating anticancer drugs with P(SB-PEG) is a promising strategy to enhance drug permeation and efficacy against spheroid cells.

Enhanced Chemotherapy for Glioblastoma Multiforme Mediated by Functionalized Graphene Quantum Dots

Glioblastoma is the most aggressive and lethal brain cancer. Current treatments involve surgical resection, radiotherapy and chemotherapy. However, the life expectancy of patients with this disease remains short and chemotherapy leads to severe adverse effects. Furthermore, the presence of the blood–brain barrier (BBB) makes it difficult for drugs to effectively reach the brain. A promising strategy lies in the use of graphene quantum dots (GQDs), which are light-responsive graphene nanoparticles that have shown the capability of crossing the BBB. Here we investigate the effect of GQDs on U87 human glioblastoma cells and primary cortical neurons. Non-functionalized GQDs (NF-GQDs) demonstrated high biocompatibility, while dimethylformamide-functionalized GQDs (DMF-GQDs) showed a toxic effect on both cell lines. The combination of GQDs and the chemotherapeutic agent doxorubicin (Dox) was tested. GQDs exerted a synergistic increase in the efficacy of chemotherapy treatment, specifically on U87 cells. The mechanism underlying this synergy was investigated, and it was found that GQDs can alter membrane permeability in a manner dependent on the surface chemistry, facilitating the uptake of Dox inside U87 cells, but not on cortical neurons. Therefore, experimental evidence indicates that GQDs could be used in a combined therapy against brain cancer, strongly increasing the efficacy of chemotherapy and, at the same time, reducing its dose requirement along with its side effects, thereby improving the life quality of patients.

2D and 3D in vitro assays to quantify the invasive behavior of glioblastoma stem cells in response to SDF-1α

Invasion is a hallmark of cancer and therefore in vitro invasion assays are important tools in cancer research. We aimed to describe in vitro 2D transwell assays and 3D spheroid assays to quantitatively determine the invasive behavior of glioblastoma stem cells in response to the chemoattractant SDF-1α. Matrigel was used as a matrix in both assays. We demonstrated quantitatively that SDF-1α increased invasive behavior of glioblastoma stem cells in both assays. We conclude that the 2D transwell invasion assay is easy to perform, fast and less complex whereas the more time-consuming 3D spheroid invasion assay is physiologically closer to the in vivo situation.

Graphene Quantum Dots' Surface Chemistry Modulates the Sensitivity of Glioblastoma Cells to Chemotherapeutics

Recent evidence has shown that graphene quantum dots (GQDs) are capable of crossing the blood-brain barrier, the barrier that reduces cancer therapy efficacy. Here, we tested three alternative GQDs' surface chemistries on two neural lineages (glioblastoma cells and mouse cortical neurons). We showed that surface chemistry modulates GQDs' biocompatibility. When used in combination with the chemotherapeutic drug doxorubicin, GDQs exerted a synergistic effect on tumor cells, but not on neurons. This appears to be mediated by the modification of membrane permeability induced by the surface of GQDs. Our findings highlight that GQDs can be adopted as a suitable delivery and therapeutic strategy for the treatment of glioblastoma, by both directly destabilizing the cell membrane and indirectly increasing the efficacy of chemotherapeutic drugs.

The importance of scoring recognition fitness in spheroid morphological analysis for robust label-free quality evaluation

Because of the growing demand for human cell spheroids as functional cellular components for both drug development and regenerative therapy, the technology to non-invasively evaluate their quality has emerged. Image-based morphology analysis of spheroids enables high-throughput screening of their quality. However, since spheroids are three-dimensional, their images can have poor contrast in their surface area, and therefore the total spheroid recognition by image processing is greatly dependent on human who design the filter-set to fit for their own definition of spheroid outline. As a result, the reproducibility of morphology measurement is critically affected by the performance of filter-set, and its fluctuation can disrupt the subsequent morphology-based analysis. Although the unexpected failure derived from the inconsistency of image processing result is a critical issue for analyzing large image data for quality screening, it has been tackled rarely. To achieve robust analysis performances using morphological features, we investigated the influence of filter-set's reproducibility for various types of spheroid data. We propose a new scoring index, the "recognition fitness deviation (RFD)," as a measure to quantitatively and comprehensively evaluate how reproductively a designed filter-set can work with data variations, such as the variations in replicate samples, in time-course samples, and in different types of cells (a total of six normal or cancer cell types). Our result shows that RFD scoring from 5000 images can automatically rank the best robust filter-set for obtaining the best 6-cell type classification model (94% accuracy). Moreover, the RFD score reflected the differences between the worst and the best classification models for morphologically similar spheroids, 60% and 89% accuracy respectively. In addition to RFD scoring, we found that using the time-course of morphological features can augment the fluctuations in spheroid recognitions leading to robust morphological analysis.

Macromolecular gelatin properties affect fibrin microarchitecture and tumor spheroid behavior in fibrin-gelatin gels

The biophysical properties of extracellular matrices (ECM) are known to regulate cell behavior, however decoupling cell behavior changes due to the relative contributions of material microstructure versus biomechanics or nutrient permeability remains challenging, especially within complex, multi-material matrices. We developed four gelatin-fibrin interpenetrating network (IPN) formulations which are identical in composition but possess variable gelatin molecular weight distributions, and display differences in microstructure, biomechanics, and diffusivity. In this work we interrogate the response of multicellular tumor spheroids to these IPN formulations and found that a high stiffness, gelatin-network dominated IPNs impeded remodeling and invasion of multicellular tumor spheroids; whereas relatively lower stiffness, fibrin-network dominated IPNs permitted protease-dependent remodeling and spheroid invasion. Cell proliferation correlated to nutrient diffusivity across tested IPN formulations. These findings demonstrate the complexity of ECM IPNs, relative to single polymer matrices, and highlight that cell response does not derive from a single aspect of the ECM, but rather from the interplay of multiple biomechanical properties. The methodology developed here represents a framework for future studies which aim to characterize cellular phenotypic responses to biophysical cues present within complex, multi-material matrices.

Iron and copper complexes with antioxidant activity as inhibitors of the metastatic potential of glioma cells

Iron and copper complexes with antioxidant activity able to inhibit tumor metastasis by inhibiting epithelial-mesenchymal transition in glioma cells.

Morphological quantification of proliferation-to-invasion transition in tumor spheroids

BACKGROUND

Metastasis determines the lethality of cancer. In most clinical cases, patients are able to live with tumor proliferation before metastasis. Thus, the transition from tumor proliferation to metastasis/invasion is essential. However, the mechanism is still unclear and especially, the proliferation-to-metastasis/invasion transition point has not been well defined. Therefore, quantitative characterization of this transition is urgently needed.

METHODS

We have successfully developed a home-built living-cell incubation system combined with an inverted optical microscope, and a systematic, quantitative approach to describing the major characteristic morphological parameters for the identification of the critical transition points for tumor-cell spheroids in a collagen fiber scaffold.

RESULTS

The system focuses on in vitro tumor modeling, e.g. the development of tumor-cell spheroids in a collagen fiber scaffold and the monitoring of cell transition from proliferation to invasion. By applying this approach to multiple tumor spheroid models, such as U87 (glioma tumor), H1299 (lung cancer), and MDA-MB-231 (breast cancer) cells, we have obtained quantitative morphological references to evaluate the proliferation-to-invasion transition time, as well as differentiating the invasion potential of tumor cells upon environmental changes, i.e. drug application.

CONCLUSIONS

Our quantitative approach provides a feasible clarification for the proliferation-to-invasion transition of in vitro tumor models (spheroids). Moreover, the transition time is a useful reference for the invasive potential of tumor cells.

GENERAL SIGNIFICANCE

This quantitative approach is potentially applicable to primary tumor cells, and thus has potential applications in the fields of cancer metastasis investigations and clinical diagnostics.

Integrating in vitro experiments with in silico approaches for Glioblastoma invasion: the role of cell-to-cell adhesion heterogeneity

Glioblastoma cells adopt migration strategies to invade into the brain parenchyma ranging from individual to collective mechanisms, whose role and dynamics are not yet fully understood. In this work, we explore Glioblastoma heterogeneity and recapitulate its invasive patterns both in vitro, by utilizing primary cells along with the U87MG cell line, and in silico, by adopting discrete, individual cell-based mathematics. Glioblastoma cells are cultured three-dimensionally in an ECM-like substrate. The primary Glioblastoma spheroids adopt a novel cohesive pattern, mimicking perivascular invasion in the brain, while the U87MG adopt a typical, starburst invasive pattern under the same experimental setup. Mathematically, we focus on the role of the intrinsic heterogeneity with respect to cell-to-cell adhesion. Our proposed mathematical approach mimics the invasive morphologies observed in vitro and predicts the dynamics of tumour expansion. The role of the proliferation and migration is also explored showing that their effect on tumour morphology is different per cell type. The proposed model suggests that allowing cell-to-cell adhesive heterogeneity within the tumour population is sufficient for variable invasive morphologies to emerge which remain originally undetectable by conventional imaging, indicating that exploration in pathological samples is needed to improve our understanding and reveal potential patient-specific therapeutic targets.