Detection of cell aggregation and altered cell viability by automated label-free video microscopy: a promising alternative to endpoint viability assays in high-throughput screening

Gastric cancer cell death analyzed by live cell imaging of spheroids

Gastric cancer (GC) is the third cause of cancer-related mortality worldwide and is often diagnosed at advanced stages of the disease. This makes the development of more comprehensive models and efficient treatments crucial. One option is based on repurposing already marketed drugs as adjuvants to chemotherapy. Accordingly, we have previously developed the combination of docetaxel and the cholesterol-lowering drug, lovastatin, as a powerful trigger of HGT-1 human GC cells' apoptosis using 2D cultures. Because 3D models, known as spheroids, are getting recognized as possibly better suited than 2Ds in toxicological research, we aimed to investigate the efficacy of this drug combination with such a model. We established monocellular spheroids from two human (GC) cell lines, HGT-1 and AGS, and bicellular spheroids from these cells mixed with cancer-associated fibroblasts. With these, we surveyed drug-induced cytotoxicity with MTT assays. In addition, we used the Incucyte live imaging and analysis system to follow spheroid growth and apoptosis. Taken together, our results showed that the lovastatin + docetaxel combination was an efficient strategy to eliminate GC cells grown in 2D or 3D cultures, lending further support in favor of repurposing lovastatin as an adjuvant to taxane-based anticancer treatment.

[Spheroids to organoids: Solid cancer models for anticancer drug discovery]

Cell culture is an important and necessary technology in oncology research. Currently, two-dimensional (2D) cell culture models are the most widely used, but they cannot reproduce the complexity and pathophysiology of tumors in vivo. This may be a major cause of the high rate of attrition of anticancer drugs entering clinical trials, the rate of new anticancer drugs entering the market being less than 5 %. One way to improve the success of new cancer drugs in the clinic is based on the use of three-dimensional (3D) cell culture models, more able to represent the complex environment and architecture of tumors. These 3D culture systems are also a powerful research tool for modeling the evolution of cancer from early stages to metastasis. Spheroids and organoids, the most adaptable models among 3D culture systems, are beginning to be used in pharmaceutical research and personalized medicine. In this article, we review the use of spheroids and organoids by highlighting their differences, discussing their impact on drug development, and looking at future challenges.

COMBImage: a modular parallel processing framework for pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies

BACKGROUND

Large-scale pairwise drug combination analysis has lately gained momentum in drug discovery and development projects, mainly due to the employment of advanced experimental-computational pipelines. This is fortunate as drug combinations are often required for successful treatment of complex diseases. Furthermore, most new drugs cannot totally replace the current standard-of-care medication, but rather have to enter clinical use as add-on treatment. However, there is a clear deficiency of computational tools for label-free and temporal image-based drug combination analysis that go beyond the conventional but relatively uninformative end point measurements.

RESULTS

COMBImage is a fast, modular and instrument independent computational framework for in vitro pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies. Jointly with automated analyses of temporal changes in cell morphology and confluence, it performs and displays conventional cell viability and synergy end point analyses. The image processing algorithms are parallelized using Google's MapReduce programming model and optimized with respect to method-specific tuning parameters. COMBImage is shown to process time-lapse microscopy movies from 384-well plates within minutes on a single quad core personal computer. This framework was employed in the context of an ongoing drug discovery and development project focused on glioblastoma multiforme; the most deadly form of brain cancer. Interesting add-on effects of two investigational cytotoxic compounds when combined with vorinostat were revealed on recently established clonal cultures of glioma-initiating cells from patient tumor samples. Therapeutic synergies, when normal astrocytes were used as a toxicity cell model, reinforced the pharmacological interest regarding their potential clinical use.

CONCLUSIONS

COMBImage enables, for the first time, fast and optimized pairwise drug combination analyses of temporal changes in label-free video microscopy movies. Providing this jointly with conventional cell viability based end point analyses, it could help accelerating and guiding any drug discovery and development project, without use of cell labeling and the need to employ a particular live cell imaging instrument.

Institutional profile: the national Swedish academic drug discovery & development platform at SciLifeLab

The Science for Life Laboratory Drug Discovery and Development Platform (SciLifeLab DDD) was established in Stockholm and Uppsala, Sweden, in 2014. It is one of ten platforms of the Swedish national SciLifeLab which support projects run by Swedish academic researchers with large-scale technologies for molecular biosciences with a focus on health and environment. SciLifeLab was created by the coordinated effort of four universities in Stockholm and Uppsala: Stockholm University, Karolinska Institutet, KTH Royal Institute of Technology and Uppsala University, and has recently expanded to other Swedish university locations. The primary goal of the SciLifeLab DDD is to support selected academic discovery and development research projects with tools and resources to discover novel lead therapeutics, either molecules or human antibodies. Intellectual property developed with the help of SciLifeLab DDD is wholly owned by the academic research group. The bulk of SciLifeLab DDD's research and service activities are funded from the Swedish state, with only consumables paid by the academic research group through individual grants.

Label-Free Automated Cell Tracking: Analysis of the Role of E-cadherin Expression in Collective Electrotaxis

Collective cell migration plays an important role in wound healing, organogenesis, and the progression of metastatic disease. Analysis of collective migration typically involves laborious and time-consuming manual tracking of individual cells within cell clusters over several dozen or hundreds of frames. Herein, we develop a label-free, automated algorithm to identify and track individual epithelial cells within a free-moving cluster. We use this algorithm to analyze the effects of partial E-cadherin knockdown on collective migration of MCF-10A breast epithelial cells directed by an electric field. Our data show that E-cadherin knockdown in free-moving cell clusters diminishes electrotactic potential, with empty vector MCF-10A cells showing 16% higher directedness than cells with E-cadherin knockdown. Decreased electrotaxis is also observed in isolated cells at intermediate electric fields, suggesting an adhesion-independent role of E-cadherin in regulating electrotaxis. In additional support of an adhesion-independent role of E-cadherin, isolated cells with reduced E-cadherin expression reoriented within an applied electric field 60% more quickly than control. These results have implications for the role of E-cadherin expression in electrotaxis and demonstrate proof-of-concept of an automated algorithm that is broadly applicable to the analysis of collective migration in a wide range of physiological and pathophysiological contexts.

High-throughput imaging: Focusing in on drug discovery in 3D

3D organotypic culture models such as organoids and multicellular tumor spheroids (MCTS) are becoming more widely used for drug discovery and toxicology screening. As a result, 3D culture technologies adapted for high-throughput screening formats are prevalent. While a multitude of assays have been reported and validated for high-throughput imaging (HTI) and high-content screening (HCS) for novel drug discovery and toxicology, limited HTI/HCS with large compound libraries have been reported. Nonetheless, 3D HTI instrumentation technology is advancing and this technology is now on the verge of allowing for 3D HCS of thousands of samples. This review focuses on the state-of-the-art high-throughput imaging systems, including hardware and software, and recent literature examples of 3D organotypic culture models employing this technology for drug discovery and toxicology screening.