A Novel Computer-Assisted Approach to evaluate Multicellular Tumor Spheroid Invasion Assay

GBM Immunotherapy: Macrophage Impacts

BACKGROUND

Glioblastoma (GBM) is an extremely aggressive form of brain tumor with low survival rates. Current treatments such as chemotherapy, radiation, and surgery are problematic due to tumor growth, invasion, and tumor microenvironment. GBM cells are resistant to these standard treatments, and the heterogeneity of the tumor makes it difficult to find a universal approach. Progression of GBM and acquisition of resistance to therapy are due to the complex interplay between tumor cells and the TME. A significant portion of the TME consists of an inflammatory infiltrate, with microglia and macrophages being the predominant cells.

METHODS

Analysis of the literature data over a course of 5 years suggest that the tumor-associated macrophages (TAMs) are capable of releasing cytokines and growth factors that promote tumor proliferation, survival, and metastasis while inhibiting immune cell function at the same time.

RESULTS

Thus, immunosuppressive state, provided with this intensively studied kind of TME cells, is supposed to promote GBM development through TAMs modulation of tumor treatment-resistance and aggressiveness. Therefore, TAMs are an attractive therapeutic target in the treatment of glioblastoma.

CONCLUSION

This review provides a comprehensive overview of the latest research on the nature of TAMs and the development of therapeutic strategies targeting TAMs, focusing on the variety of macrophage properties, being modulated, as well as molecular targets.

A deep learning-based pipeline for analyzing the influences of interfacial mechanochemical microenvironments on spheroid invasion using differential interference contrast microscopic images

Metastasis is the leading cause of cancer-related deaths. During this process, cancer cells are likely to navigate discrete tissue-tissue interfaces, enabling them to infiltrate and spread throughout the body. Three-dimensional (3D) spheroid modeling is receiving more attention due to its strengths in studying the invasive behavior of metastatic cancer cells. While microscopy is a conventional approach for investigating 3D invasion, post-invasion image analysis, which is a time-consuming process, remains a significant challenge for researchers. In this study, we presented an image processing pipeline that utilized a deep learning (DL) solution, with an encoder-decoder architecture, to assess and characterize the invasion dynamics of tumor spheroids. The developed models, equipped with feature extraction and measurement capabilities, could be successfully utilized for the automated segmentation of the invasive protrusions as well as the core region of spheroids situated within interfacial microenvironments with distinct mechanochemical factors. Our findings suggest that a combination of the spheroid culture and DL-based image analysis enable identification of time-lapse migratory patterns for tumor spheroids above matrix-substrate interfaces, thus paving the foundation for delineating the mechanism of local invasion during cancer metastasis.

Targeting sphingolipid metabolism with the sphingosine kinase inhibitor SKI-II overcomes hypoxia-induced chemotherapy resistance in glioblastoma cells: effects on cell death, self-renewal, and invasion

BACKGROUND

Glioblastoma patients commonly develop resistance to temozolomide chemotherapy. Hypoxia, which supports chemotherapy resistance, favors the expansion of glioblastoma stem cells (GSC), contributing to tumor relapse. Because of a deregulated sphingolipid metabolism, glioblastoma tissues contain high levels of the pro-survival sphingosine-1-phosphate and low levels of the pro-apoptotic ceramide. The latter can be metabolized to sphingosine-1-phosphate by sphingosine kinase (SK) 1 that is overexpressed in glioblastoma. The small molecule SKI-II inhibits SK and dihydroceramide desaturase 1, which converts dihydroceramide to ceramide. We previously reported that SKI-II combined with temozolomide induces caspase-dependent cell death, preceded by dihydrosphingolipids accumulation and autophagy in normoxia. In the present study, we investigated the effects of a low-dose combination of temozolomide and SKI-II under normoxia and hypoxia in glioblastoma cells and patient-derived GCSs.

METHODS

Drug synergism was analyzed with the Chou-Talalay Combination Index method. Dose-effect curves of each drug were determined with the Sulforhodamine B colorimetric assay. Cell death mechanisms and autophagy were analyzed by immunofluorescence, flow cytometry and western blot; sphingolipid metabolism alterations by mass spectrometry and gene expression analysis. GSCs self-renewal capacity was determined using extreme limiting dilution assays and invasion of glioblastoma cells using a 3D spheroid model.

RESULTS

Temozolomide resistance of glioblastoma cells was increased under hypoxia. However, combination of temozolomide (48 µM) with SKI-II (2.66 µM) synergistically inhibited glioblastoma cell growth and potentiated glioblastoma cell death relative to single treatments under hypoxia. This low-dose combination did not induce dihydrosphingolipids accumulation, but a decrease in ceramide and its metabolites. It induced oxidative and endoplasmic reticulum stress and triggered caspase-independent cell death. It impaired the self-renewal capacity of temozolomide-resistant GSCs, especially under hypoxia. Furthermore, it decreased invasion of glioblastoma cell spheroids.

CONCLUSIONS

This in vitro study provides novel insights on the links between sphingolipid metabolism and invasion, a hallmark of cancer, and cancer stem cells, key drivers of cancer. It demonstrates the therapeutic potential of approaches that combine modulation of sphingolipid metabolism with first-line agent temozolomide in overcoming tumor growth and relapse by reducing hypoxia-induced resistance to chemotherapy and by targeting both differentiated and stem glioblastoma cells.

The impact of temozolomide and lonafarnib on the stemness marker expression of glioblastoma cells in multicellular spheroids

Glioblastoma multiforme (GBM) is a highly malignant brain tumor with poor prognosis. The GBM microenvironment is highly heterogeneous and is composed of many cell types including astrocytes and endothelial cells (ECs) along with tumor cells, which are responsible for heightened resistance to standard chemotherapeutic drugs such as Temozolomide (TMZ). Here, we investigated how drug treatments impact stemness marker expression of GBM cells in multicellular tumor spheroid (MCTS) models. Co- and tri-culture MCTS constructed using U87-MG GBM cells, astrocytes and/or ECs were cultured for 7 days. At day 7, 5 μM lonafarnib (LNF), 100 μM TMZ, or combination of 5 μM LNF + 100 μM TMZ was added and the MCTS were cultured for an additional 48 h. We assessed the spheroid sizes and expression of stemness markers- NESTIN, SOX2, CD133, NANOG, and OCT4- through qRT-PCR and immunostaining. Following 48 h treatment with LNF, TMZ or their combination (LNF+TMZ), the spheroid sizes decreased compared to the untreated control. We also observed that the expression of most of the stemness markers significantly increased in the LNF+TMZ treated condition as compared to the untreated condition. These results indicate that drug treatment can influence the stemness marker expression of GBM cells in MCTS models and these aspects must be considered while evaluating therapies. In future, by incorporating other relevant cell types, we can further our understanding of their crosstalk, eventually leading to the development of new therapeutic strategies.

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.

Incorporating Tumor-Associated Macrophages into Engineered Models of Glioma

Tumor progression is profoundly influenced by interactions between cancer cells and the tumor microenvironment (TME). Among the various non-neoplastic cells present, immune cells are critical players in tumor development and have thus emerged as attractive therapeutic targets. Malignant gliomas exhibit a unique immune landscape characterized by high numbers of tumor-associated macrophages (TAMs). Despite encouraging preclinical results, targeting TAMs has yielded limited clinical success as a strategy for slowing glioma progression. The slow translational progress of TAM-targeted therapies is due in part to an incomplete understanding of the factors driving TAM recruitment, differentiation, and polarization. Furthermore, the functions that TAMs adopt in gliomas remain largely unknown. Progress in addressing these gaps requires sophisticated culture platforms capable of capturing key cellular and physical TME features. This review summarizes the current understanding of TAMs in gliomas and highlights the utility of in vitro TME models for investigating TAM-cancer cell cross talk.

Time-lapse imaging of HeLa spheroids in soft agar culture provides virtual inner proliferative activity

Cancer is a complex disease caused by multiple types of interactions. To simplify and normalize the assessment of drug effects, spheroid microenvironments have been utilized. Research models that involve agent measurement with the examination of clonogenic survival by monitoring culture process with image analysis have been developed for spheroid-based screening. Meanwhile, computer simulations using various models have enabled better predictions for phenomena in cancer. However, user-based parameters that are specific to a researcher’s own experimental conditions must be inputted. In order to bridge the gap between experimental and simulated conditions, we have developed an in silico analysis method with virtual three-dimensional embodiment computed using the researcher’s own samples. The present work focused on HeLa spheroid growth in soft agar culture, with spheroids being modeled in silico based on time-lapse images capturing spheroid growth. The spheroids in silico were optimized by adjusting the growth curves to those obtained from time-lapse images of spheroids and were then assigned virtual inner proliferative activity by using generations assigned to each cellular particle. The ratio and distribution of the virtual inner proliferative activities were confirmed to be similar to the proliferation zone ratio and histochemical profiles of HeLa spheroids, which were also consistent with those identified in an earlier study. We validated that time-lapse images of HeLa spheroids provided virtual inner proliferative activity for spheroids in vitro. The present work has achieved the first step toward an in silico analysis method using computational simulation based on a researcher’s own samples, helping to bridge the gap between experiment and simulation.

The Role of a Proprotein Convertase Inhibitor in Reactivation of Tumor-Associated Macrophages and Inhibition of Glioma Growth

Tumors are characterized by the presence of malignant and non-malignant cells, such as immune cells including macrophages, which are preponderant. Macrophages impact the efficacy of chemotherapy and may lead to drug resistance. In this context and based on our previous work, we investigated the ability to reactivate macrophages by using a proprotein convertases inhibitor. Proprotein convertases process immature proteins into functional proteins, with several of them having a role in immune cell activation and tumorigenesis. Macrophages were treated with a peptidomimetic inhibitor targeting furin, PC1/3, PC4, PACE4, and PC5/6. Their anti-glioma activity was analyzed by mass spectrometry-based proteomics and viability assays in 2D and 3D in vitro cultures. Comparison with temozolomide, the drug used for glioma therapy, established that the inhibitor was more efficient for the reduction of cancer cell density. The inhibitor was also able to reactivate macrophages through the secretion of several immune factors with antitumor properties. Moreover, two proteins considered as good glioma patient survival indicators were also identified in 3D cultures treated with the inhibitor. Finally, we established that the proprotein convertases inhibitor has a dual role as an anti-glioma drug and anti-tumoral macrophage reactivation drug. This strategy could be used together with chemotherapy to increase therapy efficacy in glioma.

Location of neonatal microglia drives small extracellular vesicles content and biological functions in vitro

Combining proteomics and systems biology approaches, we demonstrate that neonatal microglial cells derived from two different CNS locations, cortex and spinal cord, and cultured in vitro displayed different phenotypes upon different physiological or pathological conditions. These cells also exhibited greater variability in terms of cellular and small extracellular vesicles (sEVs) protein content and levels. Bioinformatic data analysis showed that cortical microglia exerted anti-inflammatory and neurogenesis/tumorigenesis properties, while the spinal cord microglia were more inflammatory. Interestingly, while both sEVs microglia sources enhanced growth of DRGs processes, only the spinal cord-derived sEVs microglia under LPS stimulation significantly attenuated glioma proliferation. These results were confirmed using the neurite outgrowth assay on DRGs cells and glioma proliferation analysis in 3D spheroid cultures. Results from these in vitro assays suggest that the microglia localized at different CNS regions can ensure different biological functions. Together, this study indicates that neonatal microglia locations regulate their physiological and pathological functional fates and could affect the high prevalence of brain vs spinal cord gliomas in adults.

Novel invasion indices quantify the feed-forward facilitation of tumor invasion by macrophages

Quantitative and reliable measurement of cellular invasion is important to understand a range of biological processes such as cancer metastasis and angiogenesis. Spheroid invasion assays are an attractive in vitro platform because they effectively mimic the tumor cell invasion of solid tissues. Here, we developed an image analysis–based method to quantify the invasiveness of HT1080 human fibrosarcoma tumor cell spheroids. We segmented a cell-covered area into three subareas using objectively set threshold pixel intensities and calculated invasion indices using these subareas. Comparison with conventional parameters for spheroid invasion assays, such as area, length, and detached cells, showed that our indices present the invasion event at an early time and without being convoluted by proliferation. As an application, we then examined paracrine interactions between LLC1 mouse lung carcinoma cells and Raw264.7 mouse macrophage cells with our developed analysis method. We found that the invasion of tumor spheroids was increased by a macrophage-conditioned medium, concomitantly with a decrease in tumor cell proliferation. Importantly, invasion was further enhanced by a conditioned medium from activated macrophages by co-culture with tumor cells. Thus, our indices reveal that tumor cell invasion is facilitated in a feed-forward manner by communication between tumor cells and macrophages in the tumor microenvironment.

Paclitaxel Treatment and Proprotein Convertase 1/3 (PC1/3) Knockdown in Macrophages is a Promising Antiglioma Strategy as Revealed by Proteomics and Cytotoxicity Studies

High grade gliomas are the most common brain tumors in adult. These tumors are characterized by a high infiltration in microglial cells and macrophages. The immunosuppressive tumor environment is known to orient immune cells toward a pro-tumoral and anti-inflammatory phenotype. Therefore, the current challenge for cancer therapy is to find a way to reorient macrophages toward an antitumoral phenotype. Previously, we demonstrated that macrophages secreted antitumoral factors when they were invalidated for the proprotein converstase 1/3 (PC1/3) and treated with LPS. However, achieving an activation of macrophages via LPS/TLR4/Myd88-dependent pathway appears yet unfeasible in cancer patients. On the contrary, the antitumor drug Paclitaxel is also known to activate the TLR4 MyD88-dependent signaling pathway and mimics LPS action. Therefore, we evaluated if PC1/3 knock-down (KD) macrophages could be activated by Paclitaxel and efficient against glioma. We report here that such a treatment of PC1/3 KD macrophages drove to the overexpression of proteins mainly involved in cytoskeleton rearrangement. In support of this finding, we found that these cells exhibited a Ca²⁺ increase after Paclitaxel treatment. This is indicative of a possible depolymerization of microtubules and may therefore reflect an activation of inflammatory pathways in macrophages. In such a way, we found that PC1/3 KD macrophages displayed a repression of the anti-inflammatory pathway STAT3 and secreted more pro-inflammatory cytokines. Extracellular vesicles isolated from these PC1/3 KD cells inhibited glioma growth. Finally, the supernatant collected from the coculture between glioma cells and PC1/3 KD macrophages contained more antitumoral factors. These findings unravel the potential value of a new therapeutic strategy combining Paclitaxel and PC1/3 inhibition to switch macrophages toward an antitumoral immunophenotype.

Application of 3D cultured multicellular spheroid tumor models in tumor-targeted drug delivery system research

Tumor-targeted drug delivery systems are promising for their advantages in enhanced tumor accumulation and reduced toxicity towards normal organs. However, few nanomedicines have been successfully translated into clinical application. One reason is the gap between current pre-clinical and clinical studies. The prevalent in vitro models utilized in pre-clinical phase are mainly based on the two-dimensional (2D) cell culture and are limited by the difficulty of simulating three-dimensional physiological conditions in human body, such as three-dimensional (3D) architecture, cell heterogeneity, nutrient gradients and the interaction between cells and the extracellular matrix (ECM). In addition, traditional animal models have drawbacks such as high-cost, long periods and physiological differences between animal and human. On the other hand, the employment of 3D tumor cell culture models, especially multicellular tumor spheroids (MCTS), has increased significantly in recent decades. These models have been shown to simulate 3D structures of tumors in vitro with relatively low cost and simple protocols. Currently, MCTS have also been widely exploited in drug delivery system research for comprehensive study of drug efficacy, drug penetration, receptor targeting, and cell recruitment abilities. This review summarizes the delivery barriers for nano-carriers presented in tumor microenvironment, the characteristics and formation methods for applicable multicellular tumor spheroid culture models and recent studies related to their applications in tumor-targeted drug delivery system research.