Single-image based methods used for non-invasive volume estimation of cancer spheroids: a practical assessing approach based on entry-level equipment

Fluid flow-induced modulation of viability and osteodifferentiation of periodontal ligament stem cell spheroids-on-chip

Developing physiologically relevant in vitro models for studying periodontitis is crucial for understanding its pathogenesis and developing effective therapeutic strategies. In this study, we aimed to integrate the spheroid culture of periodontal ligament stem cells (PDLSCs) within a spheroid-on-chip microfluidic perfusion platform and to investigate the influence of interstitial fluid flow on morphogenesis, cellular viability, and osteogenic differentiation of PDLSC spheroids. PDLSC spheroids were seeded onto the spheroid-on-chip microfluidic device and cultured under static and flow conditions. Computational analysis demonstrated the translation of fluid flow rates of 1.2 μl min-1 (low-flow) and 7.2 μl min-1 (high-flow) to maximum fluid shear stress of 59 μPa and 360 μPa for low and high-flow conditions, respectively. The spheroid-on-chip microfluidic perfusion platform allowed for modulation of flow conditions leading to larger PDLSC spheroids with improved cellular viability under flow compared to static conditions. Modulation of fluid flow enhanced the osteodifferentiation potential of PDLSC spheroids, demonstrated by significantly enhanced alizarin red staining and alkaline phosphatase expression. Additionally, flow conditions, especially high-flow conditions, exhibited extensive calcium staining across both peripheral and central regions of the spheroids, in contrast to the predominantly peripheral staining observed under static conditions. These findings highlight the importance of fluid flow in shaping the morphological and functional properties of PDLSC spheroids. This work paves the way for future investigations exploring the interactions between PDLSC spheroids, microbial pathogens, and biomaterials within a controlled fluidic environment, offering insights for the development of innovative periodontal therapies, tissue engineering strategies, and regenerative approaches.

Regulation of cytokinesis and necroptosis pathways by diosgenin inhibits the proliferation of NCI-H460 lung cancer cells

Aim Overcoming resistance to apoptosis and antimitotic chemotherapy is crucial for effective treatment of lung cancer. Diosgenin (DG), a promising phytochemical, can regulate various molecular pathways implicated in tumor formation and progression. However, the precise biological activity of DG in lung cancer remains unclear. This study aimed to investigate the antiproliferative activity of DG in NCI-H460 lung carcinoma cells to explore the underlying antimitotic mechanisms and alternative cell death pathways.

MATERIALS AND METHODS

In a 2D culture system, we analyzed cell viability, multinucleated cell frequency, cell concentration, cell cycle changes, cell death induction, intracellular reactive oxygen species (ROS) production, and nuclear DNA damage, particularly in relation to target gene expression. We also evaluated the antiproliferative activity of DG in a 3D culture system of spheroids, assessing volume changes, cell death induction, and inhibition of proliferation recovery and clonogenic growth.

KEY FINDINGS

DG reduced cell viability and concentration while increasing the frequency of cells with multiple nuclei, particularly binucleated cells resulting from daughter cell fusion. This effect was associated with genes involved in cytokinesis regulation (RAB35, OCRL, BIRC5, and AURKB). Additionally, DG-induced cell death was linked to necroptosis, as evidenced by increased intracellular ROS production and RIPK3, MLKL, TRAF2, and HSPA5 gene expression. In tumor spheroids, DG increased spheroid volume, induced cell death, and inhibited proliferation recovery and clonogenic growth.

SIGNIFICANCE

Our study provides new insights into the biological activities of DG in lung cancer cells, contributing to the development of novel oncological therapies.

L858R emerges as a potential biomarker predicting response of lung cancer models to anti-EGFR antibodies: Comparison of osimertinib vs. cetuximab

EGFR-specific tyrosine kinase inhibitors (TKIs), especially osimertinib, have changed lung cancer therapy, but secondary mutations confer drug resistance. Because other EGFR mutations promote dimerization-independent active conformations but L858R strictly depends on receptor dimerization, we herein evaluate the therapeutic potential of dimerization-inhibitory monoclonal antibodies (mAbs), including cetuximab. This mAb reduces viability of cells expressing L858R-EGFR and blocks the FOXM1-aurora survival pathway, but other mutants show no responses. Unlike TKI-treated patient-derived xenografts, which relapse post osimertinib treatment, cetuximab completely prevents relapses of L858R+ tumors. We report that osimertinib's inferiority associates with induction of mutagenic reactive oxygen species, whereas cetuximab's superiority is due to downregulation of adaptive survival pathways (e.g., HER2) and avoidance of mutation-prone mechanisms that engage AXL, RAD18, and the proliferating cell nuclear antigen. These results identify L858R as a predictive biomarker, which may pave the way for relapse-free mAb monotherapy relevant to a large fraction of patients with lung cancer.

Replacement, Reduction, and Refinement of Animal Experiments in Anticancer Drug Development: The Contribution of 3D In Vitro Cancer Models in the Drug Efficacy Assessment

In the last decades three-dimensional (3D) in vitro cancer models have been proposed as a bridge between bidimensional (2D) cell cultures and in vivo animal models, the gold standards in the preclinical assessment of anticancer drug efficacy. 3D in vitro cancer models can be generated through a multitude of techniques, from both immortalized cancer cell lines and primary patient-derived tumor tissue. Among them, spheroids and organoids represent the most versatile and promising models, as they faithfully recapitulate the complexity and heterogeneity of human cancers. Although their recent applications include drug screening programs and personalized medicine, 3D in vitro cancer models have not yet been established as preclinical tools for studying anticancer drug efficacy and supporting preclinical-to-clinical translation, which remains mainly based on animal experimentation. In this review, we describe the state-of-the-art of 3D in vitro cancer models for the efficacy evaluation of anticancer agents, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.

Understanding the Combined Effects of High Glucose Induced Hyper-Osmotic Stress and Oxygen Tension in the Progression of Tumourigenesis: From Mechanism to Anti-Cancer Therapeutics

High glucose (HG), a hallmark of the tumour microenvironment, is also a biomechanical stressor, as it exerts hyper-osmotic stress (HG-HO), but not much is known regarding how tumour cells mechanoadapt to HG-HO. Therefore, this study aimed to delineate the novel molecular mechanisms by which tumour cells mechanoadapt to HG/HG-HO and whether phytochemical-based interference in these mechanisms can generate tumour-cell-selective vulnerability to cell death. Mannitol and L-glucose were used as hyper-osmotic equivalents of high glucose. The results revealed that the tumour cells can efficiently mechanoadapt to HG-HO only in the normoxic microenvironment. Under normoxic HG/HG-HO stress, tumour cells polySUMOylate a higher pool of mitotic driver pH3(Ser10), which translocates to the nucleus and promotes faster cell divisions. On the contrary, acute hypoxia dampens HG/HG-HO-associated excessive proliferation by upregulating sentrin protease SENP7. SENP7 promotes abnormal SUMOylation of pH3(Ser10), thereby restricting its nuclear entry and promoting the M-phase arrest and cell loss. However, the hypoxia-arrested cells that managed to survive showed relapse upon reversal to normoxia as well as upregulation of pro-survival-associated SENP1, and players in tumour growth signalling, autophagy, glycolytic pathways etc. Depletion of SENP1 in both normoxia and hypoxia caused significant loss of tumour cells vs undepleted controls. SENP1 was ascertained to restrict the abnormal SUMOylation of pH3(Ser10) in both normoxia and hypoxia, although not so efficiently in hypoxia, due to the opposing activity of SENP7. Co-treatment with Momordin Ic (MC), a natural SENP1 inhibitor, and Gallic Acid (GA), an inhibitor of identified major pro-tumourigenic signalling (both enriched in Momordica charantia), eliminated surviving tumour cells in normal glucose, HG and HG-HO normoxic and hypoxic microenvironments, suggesting that appropriate and enhanced polySUMOylation of pH3(Ser10) in response to HG/HG-HO stress was attenuated by this treatment along with further dampening of other key tumourigenic signalling, due to which tumour cells could no longer proliferate and grow.

Quantification of prostate tumour diameter and volume from MR images using 3D ellipsoid model and its impact on PI-RADS v2.1 assessment

Maximum diameter and volume of the tumour provide important clinical information and are decision-making parameters for patients suspected with prostate cancer (PCa). The objectives of this study were to develop an automated method for 3D tumour measurement and compare it with the radiologist's manual assessment, as well as to investigate the impact of 3D tumour measurement on Prostate Imaging-Reporting and Data System version-2.1 (PI-RADS v2.1) scoring of prostate cancer. Tumour maximum diameter and volume were calculated using automated ellipsoid-fit method. For all PI-RADS scores, mean ± standard deviation range of tumour maximum diameter and volume measured using ellipsoid-fit method were 1.36 ± 0.28 to 1.97 ± 0.67 cm and 0.49 ± 0.31 to 1.05 ± 0.78 cc and manual assessment were in range of 0.73 ± 0.12 to 1.14 ± 0.25 cm and 0.36 ± 0.21 to 0.93 ± 0.39 cc, respectively. Ellipsoid-fit method showed significantly (p < 0.05) higher values for maximum diameter and volume than manual assessment. 3D measurement of tumour using ellipsoid-fit method was found to have higher maximum diameter and volume values (in 40-61% patients) compared to conventional assessment by radiologist, which may have an impact on PI-RADS v2.1 scoring system.

Propranolol blocks osteosarcoma cell cycle progression, inhibits angiogenesis and slows xenograft growth in combination with cisplatin-based chemotherapy

Osteosarcoma is still associated with limited response to standard-of-care therapy and alarmingly elevated mortality rates, especially in low- and middle-income countries. Despite multiple efforts to repurpose β-blocker propranolol in oncology, its potential application in osteosarcoma management remains largely unexplored. Considering the unsatisfied clinical needs of this aggressive disease, we evaluated the antitumoral activity of propranolol using different in vitro and in vivo osteosarcoma preclinical models, alone or in addition to chemotherapy. Propranolol significantly impaired cellular growth in β2-adrenergic receptor-expressing MG-63 and U-2OS cells, and was capable of blocking growth-stimulating effects triggered by catecholamines. siRNA-mediated ADRB2 knockdown in MG-63 cells was associated with decreased cell survival and a significant attenuation of PPN anti-osteosarcoma activity. Direct cytostatic effects of propranolol were independent of apoptosis induction and were associated with reduced mitosis, G0/G1 cell cycle arrest and a significant down-regulation of cell cycle regulator Cyclin D1. Moreover, colony formation, 3D spheroid growth, cell chemotaxis and capillary-like tube formation were drastically impaired after propranolol treatment. Interestingly, anti-migratory activity of β-blocker was associated with altered actin cytoskeleton dynamics. In vivo, propranolol treatment (10 mg/kg/day i.p.) reduced the early angiogenic response triggered by MG-63 cells in nude mice. Synergistic effects were observed in vitro after combining propranolol with chemotherapeutic agent cisplatin. Sustained administration of propranolol (10 mg/kg/day i.p., five days a week), alone and especially in addition to low-dose metronomic cisplatin (2 mg/kg/day i.p., three times a week), markedly reduced xenograft progression. After histological analysis, propranolol and cisplatin combination resulted in low tumor mitotic index and increased tumor necrosis. β-blockade using propranolol seems to be an achievable and cost-effective therapeutic approach to modulate osteosarcoma aggressiveness. Further translational studies of propranolol repurposing in osteosarcoma are warranted.

Diosgenin increases BBC3 expression in HepG2/C3A cells and alters cell communication in a 3D spheroid model

Preclinical studies have shown that diosgenin, a steroidal sapogenin, is a promising phytochemical for treating different pathological conditions, such as cancer, diabetes, and cardiovascular diseases. However, the toxicological safety of this molecule for therapeutic use in humans needs to be better understood. Thus, this study aimed to evaluate the mechanisms of action of diosgenin in HepG2/C3A human hepatocellular carcinoma cells. Cytotoxicity, genotoxicity, alterations in the cell cycle, and cell death (apoptosis) were investigated and associated with the gene expression profile of pathways involved in these processes. The effects of diosgenin on the growth of spheroids were also tested. Diosgenin induced a dose-dependent reduction in cell viability and cell cycle arrest in S and G₂/M phases and apoptosis in response to DNA damage. Apoptosis was associated with an increase in the expression of BBC3, a participant in the intrinsic apoptosis pathway. Diosgenin also promoted an increase in volume and greater cellular breakdown in spheroids. These results allowed a better understanding of the toxicity of diosgenin in human cells and contributed to the development of treatments based on this phytochemical.

Characterization and quantification of necrotic tissues and morphology in multicellular ovarian cancer tumor spheroids using optical coherence tomography

The three-dimensional (3D) tumor spheroid model is a critical tool for high-throughput ovarian cancer research and anticancer drug development in vitro. However, the 3D structure prevents high-resolution imaging of the inner side of the spheroids. We aim to visualize and characterize 3D morphological and physiological information of the contact multicellular ovarian tumor spheroids growing over time. We intend to further evaluate the distinctive evolutions of the tumor spheroid and necrotic tissue volumes in different cell numbers and determine the most appropriate mathematical model for fitting the growth of tumor spheroids and necrotic tissues. A label-free and noninvasive swept-source optical coherence tomography (SS-OCT) imaging platform was applied to obtain two-dimensional (2D) and 3D morphologies of ovarian tumor spheroids over 18 days. Ovarian tumor spheroids of two different initial cell numbers (5,000- and 50,000- cells) were cultured and imaged (each day) over the time of growth in 18 days. Four mathematical models (Exponential-Linear, Gompertz, logistic, and Boltzmann) were employed to describe the growth kinetics of the tumor spheroids volume and necrotic tissues. Ovarian tumor spheroids have different growth curves with different initial cell numbers and their growths contain different stages with various growth rates over 18 days. The volumes of 50,000-cells spheroids and the corresponding necrotic tissues are larger than that of the 5,000-cells spheroids. The formation of necrotic tissue in 5,000-cells numbers is slower than that in the 50,000-cells ones. Moreover, the Boltzmann model exhibits the best fitting performance for the growth of tumor spheroids and necrotic tissues. Optical coherence tomography (OCT) can serve as a promising imaging modality to visualize and characterize morphological and physiological features of multicellular ovarian tumor spheroids. The Boltzmann model integrating with 3D OCT data of ovarian tumor spheroids provides great potential for high-throughput cancer research in vitro and aiding in drug development.

A deep learning approach using synthetic images for segmenting and estimating 3D orientation of nanoparticles in EM images

BACKGROUND AND OBJECTIVE

Nanoparticles present properties that can be applied to a wide range of fields such as biomedicine, electronics or optics. The type of properties depends on several characteristics, being some of them related with the particle structure. A proper characterization of nanoparticles is crucial since it could affect their applications. To characterize a particle shape and size, the nanotechnologists employ Electron Microscopy (EM) to obtain images of nanoparticles and perform measures over them. This task could be tedious, repetitive and slow, we present a Deep Learning method based on Convolutional Neural Networks (CNNs) to detect, segment, infer orientations and reconstruct microscope images of nanoparticles. Since machine learning algorithms depend on annotated data and there is a lack of annotated datasets of nanoparticles, our work makes use of artificial datasets of images resembling real nanoparticles photographs.

METHODS

Our work is divided into three tasks. Firstly, a method to create annotated datasets of artificial images resembling Scanning Electron Microscope (SEM). Secondly, two models of convolutional neural networks are trained using the artificial datasets previously generated, the first one is in charge of the detection and segmentation of the nanoparticles while the second one will infer the nanoparticle orientation. Finally, the 3D reconstruction module will recreate in a 3D scene the set of detected particles.

RESULTS

We have tested our method with five different shapes of basic nanoparticles: spheres, cubes, ellipsoids, hexagonal discs and octahedrons. An analysis of the reconstructions was conducted by manually comparing each of them with the real images. The results obtained have been promising, the particles are segmented and reconstructed accordingly to their shapes and orientations.

CONCLUSIONS

We have developed a method for nanoparticle detection and segmentation in microscope images. Moreover, we can also infer an approximation of the 3D orientation of the particles and, in conjunction with the detections, create a 3D reconstruction of the photographs. The novelty of our approximation lies in the dataset used. Instead of using annotated images, we have created the datasets simulating the microscope images by using basic geometrical objects that imitate real nanoparticles.

Non-Destructive Tumor Aggregate Morphology and Viability Quantification at Cellular Resolution, During Development and in Response to Drug

Three-dimensional (3D) tissue-engineered in vitro models, particularly multicellular spheroids and organoids, have become important tools to explore disease progression and guide the development of novel therapeutic strategies. These avascular constructs are particularly powerful in oncological research due to their ability to mimic several key aspects of in vivo tumors, such as 3D structure and pathophysiologic gradients. Advancement of spheroid models requires characterization of critical features (i.e., size, shape, cellular density, and viability) during model development, and in response to treatment. However, evaluation of these characteristics longitudinally, quantitatively and non-invasively remains a challenge. Herein, Optical Coherence Tomography (OCT) is used as a label-free tool to assess 3D morphologies and cellular densities of tumor spheroids generated via the liquid overlay technique. We utilize this quantitative tool to assess Matrigel's influence on spheroid morphologic development, finding that the absence of Matrigel produces flattened, disk-like aggregates rather than 3D spheroids with physiologically-relevant features. Furthermore, this technology is adapted to quantify cell number within tumor spheroids, and to discern between live and dead cells, to non-destructively provide valuable information on tissue/construct viability, as well as a proof-of-concept for longitudinal drug efficacy studies. Together, these findings demonstrate OCT as a promising noninvasive, quantitative, label-free, longitudinal and cell-based method that can assess development and drug response in 3D cellular aggregates at a mesoscopic scale.

ReViMS: Software tool for estimating the volumes of 3-D multicellular spheroids imaged using a light sheet fluorescence microscope

Cancer 3-D spheroids are widely used to test drugs and radiotherapy treatments. These 3-D cell clusters range from tens to hundreds of micrometers in size, with shapes that typically differ from a perfect sphere. Change in spheroid volume is one of the most important parameters for evaluating treatment efficacy, and using light sheet fluorescence microscopes (LSFM), optical sections of samples in that size range can be obtained. However, there remains a lack of validated methods for quantifying the volumes of 3-D multicellular aggregates. Here, we present Reconstruction and Visualization from Multiple Sections (ReViMS), an open-source, user-friendly software for automatically segmenting z-stacks of fluorescence images and estimating the volumes of 3-D multicellular spheroids. To assess the precision and accuracy of the volume estimates obtained with ReViMS, we used several cancer spheroids imaged with LSFM. Both the precision and accuracy were >95%, demonstrating the effectiveness of ReViMS.

Cell Counting and Viability Assessment of 2D and 3D Cell Cultures: Expected Reliability of the Trypan Blue Assay

BACKGROUND

Whatever the target of an experiment in cell biology, cell counting and viability assessment are always computed. The Trypan Blue (TB) assay was proposed about a century ago and is still the most widely used method to perform cell viability analysis. Furthermore, the combined use of TB with a haemocytometer is also considered the standard approach to estimate cell population density. There are numerous research articles reporting the use of TB assays to compute cell number and viability of 2D and 3D cultures. However, the literature still lacks studies regarding the reliability of the TB assay in terms of assessment of its repeatability and reproducibility.

METHODS

We compared the TB assay's measurements obtained by two biologists who analysed 105 different samples in double-blind for a total of 210 counts performed. We measured: (a) the repeatability of the count performed by the same operator; (b) the reproducibility of counts performed by the two operators.

RESULTS

There were no significant differences in the results obtained with 2D and 3D cell cultures: we estimated an approximate variability of 5% when the TB assay was used to assess the viability of the culture, and a variability of around 20% when it was used to determine the cell population density.

CONCLUSIONS

The main aim of this study was to make researchers aware of potential measurement errors when TB is used with a haemocytometer for counting and viability measurements in 2D and 3D cultures. We believe that these results can help researchers to determine whether the expected reliability of the TB assay is compliant with their applications.