Live cell in vitro and in vivo imaging applications: accelerating drug discovery

An in vivo microscopy dataset for the characterization of leukocyte death

Recent advancements in intravital microscopy have enabled the study of cell death in vivo under various experimental conditions, such as infection and cancer. However, the limited throughput of this technology, together with a lack of openly accessible datasets, affects the development of algorithms for the automatic detection and characterization of cell death, which in turn require the integration of extensive and curated datasets. To address these needs, we present a curated dataset of microscopy videos depicting the death of neutrophils, eosinophils, and dendritic cells, acquired in the spleen and in the lymph node of mice under inflammatory conditions. The dataset provides time-lapse imaging data, along with coordinates in space and time of cell death events displaying apoptotic-like morphodynamics, and 3D reconstruction of the cell morphology at each time point. Altogether, these data will be pivotal for developing computer vision and bioimage analysis methods to advance cell death research.

Framework Nucleic Acids: Innovative Tools for Cellular Sensing and Therapeutics

As emerging biomaterials, framework nucleic acids (FNAs) have recently demonstrated great potential in the biomedical field due to their high programmability, biocompatibility, unique structural diversity, and precise molecular design capabilities. This review focuses on the applications of FNAs in cellular sensing and disease treatment. First, we systematically introduce the applications of FNAs in cellular sensing, including their precise recognition and response to the extracellular tumor microenvironment, cell membrane proteins, and intracellular biomarkers. Subsequently, we review the potential of FNAs in disease treatment, covering their applications and development in drug delivery, regulation of cell behavior, and immunomodulation. We also discuss the limitations and potential role of FNAs in personalized medicine, precision diagnostics, and advanced therapies. The broad application of FNAs is expected to drive significant breakthroughs in future biomedical technological innovations and clinical translation.

PostFocus: automated selective post-acquisition high-throughput focus restoration using diffusion model for label-free time-lapse microscopy

MOTIVATION

High-throughput time-lapse imaging is a fundamental tool for efficient living cell profiling at single-cell resolution. Label-free phase-contrast video microscopy enables noninvasive, nontoxic, and long-term imaging. The tradeoff between speed and throughput, however, implies that despite the state-of-the-art autofocusing algorithms, out-of-focus cells are unavoidable due to the migratory nature of immune cells (velocities >10 μm/min). Here, we propose PostFocus to (i) identify out-of-focus images within time-lapse sequences with a classifier, and (ii) deploy a de-noising diffusion probabilistic model to yield reliable in-focus images.

RESULTS

De-noising diffusion probabilistic model outperformed deep discriminative models with a superior performance on the whole image and around cell boundaries. In addition, PostFocus improves the accuracy of image analysis (cell and contact detection) and the yield of usable videos.

AVAILABILITY AND IMPLEMENTATION

Open-source code and sample data are available at: https://github.com/kwu14victor/PostFocus.

Real-Time Analysis of Neuronal Cell Cultures for CNS Drug Discovery

The ability to screen for agents that can promote the development and/or maintenance of neuronal networks creates opportunities for the discovery of novel agents for the treatment of central nervous system (CNS) disorders. Over the past 10 years, advances in robotics, artificial intelligence, and machine learning have paved the way for the improved implementation of live-cell imaging systems for drug discovery. These instruments have revolutionized our ability to quickly and accurately acquire large standardized datasets when studying complex cellular phenomena in real-time. This is particularly useful in the field of neuroscience because real-time analysis can allow efficient monitoring of the development, maturation, and conservation of neuronal networks by measuring neurite length. Unfortunately, due to the relative infancy of this type of analysis, standard practices for data acquisition and processing are lacking, and there is no standardized format for reporting the vast quantities of data generated by live-cell imaging systems. This paper reviews the current state of live-cell imaging instruments, with a focus on the most commonly used equipment (IncuCyte systems). We provide an in-depth analysis of the experimental conditions reported in publications utilizing these systems, particularly with regard to studying neurite outgrowth. This analysis sheds light on trends and patterns that will enhance the use of live-cell imaging instruments in CNS drug discovery.

Design and Synthesis of ESIPT-Based Imidazole Derivatives for Cell Imaging

Excited-state intramolecular proton transfer (ESIPT)-based fluorescent molecules offer several exciting applications and are utilized most frequently as a cell imaging agent. Because of this, four distinct imidazole derivatives with ESIPT emission have been synthesized, and their fluorescence characteristics have been assessed in a variety of settings. Measurements using fluorescence spectroscopy have shown a promising candidate for cell staining, and potential candidate was specifically investigated for cell imaging uses in HT-29, MDA-MB-231, and HaCaT. Cytotoxicity of candidate molecule (1d) was analyzed using HT-29 and HaCaT cell lines, and at a dosage of 160 μM, HT-29 and HaCaT cell lines showed no signs of important cell toxicity. When spectroscopically measured, compound 1d showed no fluorescence ability in phosphate-buffered saline (PBS) solution. However, after 8 h of incubation in several cell lines, excellent fluorescence characteristics were seen in the green and red filters.

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning

MOTIVATION

Cancer is a complex disease that results in a significant number of global fatalities. Treatment strategies can vary among patients, even if they have the same type of cancer. The application of precision medicine in cancer shows promise for treating different types of cancer, reducing healthcare expenses, and improving recovery rates. To achieve personalized cancer treatment, machine learning models have been developed to predict drug responses based on tumor and drug characteristics. However, current studies either focus on constructing homogeneous networks from single data source or heterogeneous networks from multiomics data. While multiomics data have shown potential in predicting drug responses in cancer cell lines, there is still a lack of research that effectively utilizes insights from different modalities. Furthermore, effectively utilizing the multimodal knowledge of cancer cell lines poses a challenge due to the heterogeneity inherent in these modalities.

RESULTS

To address these challenges, we introduce MMCL-CDR (Multimodal Contrastive Learning for Cancer Drug Responses), a multimodal approach for cancer drug response prediction that integrates copy number variation, gene expression, morphology images of cell lines, and chemical structure of drugs. The objective of MMCL-CDR is to align cancer cell lines across different data modalities by learning cell line representations from omic and image data, and combined with structural drug representations to enhance the prediction of cancer drug responses (CDR). We have carried out comprehensive experiments and show that our model significantly outperforms other state-of-the-art methods in CDR prediction. The experimental results also prove that the model can learn more accurate cell line representation by integrating multiomics and morphological data from cell lines, thereby improving the accuracy of CDR prediction. In addition, the ablation study and qualitative analysis also confirm the effectiveness of each part of our proposed model. Last but not least, MMCL-CDR opens up a new dimension for cancer drug response prediction through multimodal contrastive learning, pioneering a novel approach that integrates multiomics and multimodal drug and cell line modeling.

AVAILABILITY AND IMPLEMENTATION

MMCL-CDR is available at https://github.com/catly/MMCL-CDR.

Multiplexed live-cell imaging for drug responses in patient-derived organoid models of cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to simultaneously quantitate cell health and apoptosis. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Targeted Bioluminescent Imaging of Pancreatic Ductal Adenocarcinoma Using Nanocarrier-Complexed EGFR-Binding Affibody-Gaussia Luciferase Fusion Protein

In vivo imaging has enabled impressive advances in biological research, both preclinical and clinical, and researchers have an arsenal of imaging methods available. Bioluminescence imaging is an advantageous method for in vivo studies that allows for the simple acquisition of images with low background signals. Researchers have increasingly been looking for ways to improve bioluminescent imaging for in vivo applications, which we sought to achieve by developing a bioluminescent probe that could specifically target cells of interest. We chose pancreatic ductal adenocarcinoma (PDAC) as the disease model because it is the most common type of pancreatic cancer and has an extremely low survival rate. We targeted the epidermal growth factor receptor (EGFR), which is frequently overexpressed in pancreatic cancer cells, using an EGFR-specific affibody to selectively identify PDAC cells and delivered a Gaussia luciferase (GLuc) bioluminescent protein for imaging by engineering a fusion protein with both the affibody and the bioluminescent protein. This fusion protein was then complexed with a G5-PAMAM dendrimer nanocarrier. The dendrimer was used to improve the protein stability in vivo and increase signal strength. Our targeted bioluminescent complex had an enhanced uptake into PDAC cells in vitro and localized to PDAC tumors in vivo in pancreatic cancer xenograft mice. The bioluminescent complexes could delineate the tumor shape, identify multiple masses, and locate metastases. Through this work, an EGFR-targeted bioluminescent-dendrimer complex enabled the straightforward identification and imaging of pancreatic cancer cells in vivo in preclinical models. This argues for the targeted nanocarrier-mediated delivery of bioluminescent proteins as a way to improve in vivo bioluminescent imaging.

Real-time luminescence enables continuous drug-response analysis in adherent and suspension cell lines

The drug-induced proliferation (DIP) rate is a metric of in vitro drug response that avoids inherent biases in commonly used metrics such as 72 h viability. However, DIP rate measurements rely on direct cell counting over time, a laborious task that is subject to numerous challenges, including the need to fluorescently label cells and automatically segment nuclei. Moreover, it is incredibly difficult to directly count cells and accurately measure DIP rates for cell populations in suspension. As an alternative, we use real-time luminescence measurements derived from the cellular activity of NAD(P)H oxidoreductase to efficiently estimate drug response in both adherent and suspension cell populations to a panel of known anticancer agents. For the adherent cell lines, we collect both luminescence reads and direct cell counts over time simultaneously to assess their congruency. Our results demonstrate that the proposed approach significantly speeds up data collection, avoids the need for cellular labels and image segmentation, and opens the door to significant advances in high-throughput screening of anticancer drugs.

Methodologies and Emerging Technologies for the Evaluation of the Hematopoietic System

Hematology and bone marrow analysis is central to our understanding of the hematopoietic system and how it responds to insults, and this session presented during the 2022 STP symposium provided a review of current and novel approaches for the evaluation of the hematopoietic system in the context of nonclinical investigations. This publication summarizes the information presented on novel approaches for evaluation of the hematopoietic system using automated hematology analyzers, including details around the quantitative assessment of bone marrow cell suspensions as well as introducing several newly available hematology parameters. It was followed by a discussion on intravital microscopy and live cell imaging and how these methods can assist with de-risking hematopoiesis-associated safety concerns, and a review of recent assays using artificial intelligence for the evaluation of bone marrow.

Effect of Three Chlorhexidine-Based Mouthwashes on Human Gingival Fibroblasts: An In Vitro Study

Mouthwashes containing chlorhexidine (CHX) are deemed to be associated with dose-dependent side effects, including burning sensation and taste alteration. To overcome these drawbacks, mouthwashes with CHX at lower concentrations with or without adjunctive agents are proposed. The aim of this in vitro study was to investigate the effects of three CHX-based mouthwashes on human gingival fibroblasts (HGFs). After 3 days of cell culture, groups were randomly treated for 30 s, 60 s or 120 s with (a) CHX 0.05% in combination with cetylpyridnium chloride (CPC) 0.05%; (b) CHX 0.1%; (c) CHX 0.2%; or (d) NaCl as control. Cell viability, cytotoxicity and apoptosis were evaluated at 2 h, 3 days and 6 days after the exposure to the different solutions. Similar cell viability values were found among the test groups at all time points. At day 0, higher cytotoxicity was measured in the group treated with CHX 0.02%, in particular after long application time (120 s), while no significant difference was found between CHX + CPC and the control group. All the investigated mouthwashes were well tolerated by HGF cells for the tested application times. The highest cytotoxic effect was observed for CHX 0.2%; therefore, clinicians should consider limiting its usage to carefully selected clinical situations.

Cell Culture-Based Assessment of Toxicity and Therapeutics of Phytochemical Antioxidants

Plant-derived natural products are significant resources for drug discovery and development including appreciable potentials in preventing and managing oxidative stress, making them promising candidates in cancer and other disease therapeutics. Their effects have been linked to phytochemicals such as phenolic compounds and their antioxidant activities. The abundance and complexity of these bio-constituents highlight the need for well-defined in vitro characterization and quantification of the plant extracts/preparations that can translate to in vivo effects and hopefully to clinical use. This review article seeks to provide relevant information about the applicability of cell-based assays in assessing anti-cytotoxicity of phytochemicals considering several traditional and current methods.

In vitro Fourier transform infrared spectroscopic study of the effect of glycerol on the uptake of beclomethasone dipropionate in living respiratory cells

The quantification of drug in living cells is of increasing interest in pharmaceutical research because of its importance in understanding drug efficacy and toxicity. Label-free in situ measurement methods are advantageous for their ability to obtain chemical and time profiles without the need of labelling or extraction steps. We have previously shown that Fourier transform infrared (FTIR) spectroscopy has the potential to quantify drug in situ within living cells at micromolar level when a simple solution of drug was added to the medium. The purpose of this study was to demonstrate that the approach can evaluate more complex systems such as the effect of membrane modification by a formulation on drug uptakes. The inhaled corticosteroid, beclomethasone dipropionate (BDP), in Calu-3 respiratory epithelial cells in the absence and presence of glycerol, an excipient in some inhaled medicines was used as the model system. The FTIR method was first validated for limit of detection (LOD) and quantification (LOQ) according to published guidelines and the LOQ was found to be ∼ 20 μM, good enough to quantify BDP in the living cell. The uptake of BDP by living Calu-3 cells was found to be reduced in the presence of glycerol as expected due to the stiffening of the cell membrane by the presence of glycerol in the formulation. This study demonstrates the valuable analytical capability of live-cell FTIR to study the effect of formulation on drug transport in lungs and to evaluate drug availability to intracellular targets. We conclude that FTIR has potential to contribute widely at the frontier of live-cell studies.

Practical segmentation of nuclei in brightfield cell images with neural networks trained on fluorescently labelled samples

Identifying nuclei is a standard first step when analysing cells in microscopy images. The traditional approach relies on signal from a DNA stain, or fluorescent transgene expression localised to the nucleus. However, imaging techniques that do not use fluorescence can also carry useful information. Here, we used brightfield and fluorescence images of fixed cells with fluorescently labelled DNA, and confirmed that three convolutional neural network architectures can be adapted to segment nuclei from the brightfield channel, relying on fluorescence signal to extract the ground truth for training. We found that U-Net achieved the best overall performance, Mask R-CNN provided an additional benefit of instance segmentation, and that DeepCell proved too slow for practical application. We trained the U-Net architecture on over 200 dataset variations, established that accurate segmentation is possible using as few as 16 training images, and that models trained on images from similar cell lines can extrapolate well. Acquiring data from multiple focal planes further helps distinguish nuclei in the samples. Overall, our work helps to liberate a fluorescence channel reserved for nuclear staining, thus providing more information from the specimen, and reducing reagents and time required for preparing imaging experiments.

Real-Time Fluorescence Image-Guided Oncolytic Virotherapy for Precise Cancer Treatment

Oncolytic virotherapy is one of the most promising, emerging cancer therapeutics. We generated three types of telomerase-specific replication-competent oncolytic adenovirus: OBP-301; a green fluorescent protein (GFP)-expressing adenovirus, OBP-401; and Killer-Red-armed OBP-301. These oncolytic adenoviruses are driven by the human telomerase reverse transcriptase (hTERT) promoter; therefore, they conditionally replicate preferentially in cancer cells. Fluorescence imaging enables visualization of invasion and metastasis in vivo at the subcellular level; including molecular dynamics of cancer cells, resulting in greater precision therapy. In the present review, we focused on fluorescence imaging applications to develop precision targeting for oncolytic virotherapy. Cell-cycle imaging with the fluorescence ubiquitination cell cycle indicator (FUCCI) demonstrated that combination therapy of an oncolytic adenovirus and a cytotoxic agent could precisely target quiescent, chemoresistant cancer stem cells (CSCs) based on decoying the cancer cells to cycle to S-phase by viral treatment, thereby rendering them chemosensitive. Non-invasive fluorescence imaging demonstrated that complete tumor resection with a precise margin, preservation of function, and prevention of distant metastasis, was achieved with fluorescence-guided surgery (FGS) with a GFP-reporter adenovirus. A combination of fluorescence imaging and laser ablation using a KillerRed-protein reporter adenovirus resulted in effective photodynamic cancer therapy (PDT). Thus, imaging technology and the designer oncolytic adenoviruses may have clinical potential for precise cancer targeting by indicating the optimal time for administering therapeutic agents; accurate surgical guidance for complete resection of tumors; and precise targeted cancer-specific photosensitization.

Intravitreal Administration of Acetyl Triethyl Citrate and Benzyl Benzoate Is Retinotoxic in Rabbits but Not in Cynomolgus Monkeys

Sustained drug delivery formulations are developed to reduce dose frequency while maintaining efficacy of intravitreal (ITV) administered therapeutics. Available safety data for components novel to the eye's posterior segment may be limited, requiring preclinical assessments to identify potential toxicities. We evaluated the in vivo and in vitro safety of two solvents, acetyl triethyl citrate (ATEC) and benzyl benzoate (BB), as novel sustained delivery formulations for ITV administration. In vivo tolerability was assessed following ITV administration of ATEC and BB to rabbits and cynomolgus monkeys. In rabbits, ITV solvent administration resulted in moderate to severe retinal toxicity characterized by focal retinal necrosis and/or degeneration, sometimes accompanied by inflammation, with a clear association between the physical presence of the solvent and areas of retinal damage. In contrast, solvent administration in monkeys appeared well tolerated, producing no histologic abnormalities. Toxicity in primary human retinal pigment epithelial cells, characterized by cellular toxicity and mitochondrial injury, corroborated the retinal toxicity in rabbits. In conclusion, ITV solvent depots of ATEC or BB result in chemical and focal retinal toxicity in rabbits, but not monkeys. Additional investigation is needed to demonstrate a sufficient margin of safety prior to use of ATEC or BB in ITV drug products.

Emerging Neuroblastoma 3D In Vitro Models for Pre-Clinical Assessments

The potential of tumor three-dimensional (3D) in vitro models for the validation of existing or novel anti-cancer therapies has been largely recognized. During the last decade, diverse in vitro 3D cell systems have been proposed as a bridging link between two-dimensional (2D) cell cultures and in vivo animal models, both considered gold standards in pre-clinical settings. The latest awareness about the power of tailored therapies and cell-based therapies in eradicating tumor cells raises the need for versatile 3D cell culture systems through which we might rapidly understand the specificity of promising anti-cancer approaches. Yet, a faithful reproduction of the complex tumor microenvironment is demanding as it implies a suitable organization of several cell types and extracellular matrix components. The proposed 3D tumor models discussed here are expected to offer the required structural complexity while also assuring cost-effectiveness during pre-selection of the most promising therapies. As neuroblastoma is an extremely heterogenous extracranial solid tumor, translation from 2D cultures into innovative 3D in vitro systems is particularly challenging. In recent years, the number of 3D in vitro models mimicking native neuroblastoma tumors has been rapidly increasing. However, in vitro platforms that efficiently sustain patient-derived tumor cell growth, thus allowing comprehensive drug discovery studies on tailored therapies, are still lacking. In this review, the latest neuroblastoma 3D in vitro models are presented and their applicability for a more accurate prediction of therapy outcomes is discussed.

BRCA1 and BRCA2 associated breast cancer and the roles of current modelling systems in drug discovery

For a drug candidate to be fully developed takes years and investment of hundreds of millions of dollars. There is no doubt that drug development is difficult and risky, but vital to protecting against devastating disease. This difficulty is clearly evident in BRCA1 and BRCA2 related breast cancer, with current treatment options largely confined to invasive surgical procedures, as well as chemotherapy and radiotherapy regimes which damage healthy tissue and can leave remnant disease. Consequently, patient survival and relapse rates are far from ideal, and new candidate treatments are needed. The preclinical stages of drug discovery are crucial to get right for translation to hospital beds. Disease models must take advantage of current technologies and be accurate for rapid and translatable treatments. Careful selection of cell lines must be coupled with high throughput techniques, with promising results trialled further in highly accurate humanised patient derived xenograft models. Traditional adherent drug screening should transition to 3D culture systems amenable to high throughput techniques if the gap between in vitro and in vivo studies is to be partially bridged. The possibility of organoid, induced pluripotent stem cell, and conditionally reprogrammed in vitro models is tantalising, however protocols are yet to be fully established. This review of BRCA1 and BRCA2 cancer biology and current modelling systems will hopefully guide the design of future drug discovery endeavours and highlight areas requiring improvement.

FUCCI Real-Time Cell-Cycle Imaging as a Guide for Designing Improved Cancer Therapy: A Review of Innovative Strategies to Target Quiescent Chemo-Resistant Cancer Cells

Simple Summary

Chemotherapy of solid tumors has made very slow progress over many decades. A major problem has been that solid tumors very often contain non-dividing cells due to lack of oxygen deep in the tumor and these non-dividing cells resist most currently-used chemotherapy which usually only targets dividing cells. The present review demonstrates how a unique imaging system, FUCCI, which color codes cells depending on whether they are in a dividing or non-dividing phase, is being used to design very novel therapy that targets non-dividing cancer cells which can greatly improve the efficacy of cancer chemotherapy.

Abstract

Progress in chemotherapy of solid cancer has been tragically slow due, in large part, to the chemoresistance of quiescent cancer cells in tumors. The fluorescence ubiquitination cell-cycle indicator (FUCCI) was developed in 2008 by Miyawaki et al., which color-codes the phases of the cell cycle in real-time. FUCCI utilizes genes linked to different color fluorescent reporters that are only expressed in specific phases of the cell cycle and can, thereby, image the phases of the cell cycle in real-time. Intravital real-time FUCCI imaging within tumors has demonstrated that an established tumor comprises a majority of quiescent cancer cells and a minor population of cycling cancer cells located at the tumor surface or in proximity to tumor blood vessels. In contrast to most cycling cancer cells, quiescent cancer cells are resistant to cytotoxic chemotherapy, most of which target cells in S/G₂/M phases. The quiescent cancer cells can re-enter the cell cycle after surviving treatment, which suggests the reason why most cytotoxic chemotherapy is often ineffective for solid cancers. Thus, quiescent cancer cells are a major impediment to effective cancer therapy. FUCCI imaging can be used to effectively target quiescent cancer cells within tumors. For example, we review how FUCCI imaging can help to identify cell-cycle-specific therapeutics that comprise decoy of quiescent cancer cells from G₁ phase to cycling phases, trapping the cancer cells in S/G₂ phase where cancer cells are mostly sensitive to cytotoxic chemotherapy and eradicating the cancer cells with cytotoxic chemotherapy most active against S/G₂ phase cells. FUCCI can readily image cell-cycle dynamics at the single cell level in real-time in vitro and in vivo. Therefore, visualizing cell cycle dynamics within tumors with FUCCI can provide a guide for many strategies to improve cell-cycle targeting therapy for solid cancers.

Monitoring cell endocytosis of liposomes by real-time electrical impedance spectroscopy

Evaluation and understanding the effect of drug delivery in in vitro systems is fundamental in drug discovery. We present an assay based on real-time electrical impedance spectroscopy (EIS) measurements that can be used to follow the internalisation and cytotoxic effect of a matrix metalloproteinase (MMP)-sensitive liposome formulation loaded with oxaliplatin (OxPt) on colorectal cancer cells. The EIS response identified two different cellular processes: (i) a negative peak in the cell index (CI) within the first 5 h, due to onset of liposome endocytosis, followed by (ii) a subsequent CI increase, due to the reattachment of cells until the onset of cytotoxicity with a decrease in CI. Free OxPt or OxPt-loaded Stealth liposomes did not show this two-stage EIS response; the latter can be due to the fact that Stealth cannot be cleaved by MMPs and thus is not taken up by the cells. Real-time bright-field imaging supported the EIS data, showing variations in cell adherence and cell morphology after exposure to the different liposome formulations. A drastic decrease in cell coverage as well as rounding up of cells during the first 5 h of exposure to OxPt-loaded (MMP)-sensitive liposome formulation is reflected by the first negative EIS response, which indicates the onset of liposome endocytosis. Graphical abstract.

3D image analysis reveals differences of CD30 positive cells and network formation in reactive and malignant human lymphoid tissue (classical Hodgkin Lymphoma)

AIMS

The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues.

MATERIALS AND RESULTS

Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL.

CONCLUSION

In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.

Live Monitoring and Analysis of Fungal Growth, Viability, and Mycelial Morphology Using the IncuCyte NeuroTrack Processing Module

Pathogenic fungi remain a major cause of infectious complications in immunocompromised patients. Microscopic techniques are crucial for our understanding of fungal biology, host-pathogen interaction, and the pleiotropic effects of antifungal drugs on fungal cell growth and morphogenesis. Taking advantage of the morphological similarities of neuronal cell networks and mycelial growth patterns, we employed the IncuCyte time-lapse microscopy system and its NeuroTrack image analysis software package to study growth and branching of a variety of pathogenic yeasts and molds. Using optimized image processing definitions, we validated IncuCyte NeuroTrack analysis as a reliable and efficient tool for translational applications such as antifungal efficacy evaluation and coculture with host immune effector cells. Hence, the IncuCyte system and its NeuroTrack module provide an appealing platform for efficient in vitro studies of antifungal compounds and immunotherapeutic strategies in medical mycology.

Efficient live-imaging methods are pivotal to understand fungal morphogenesis, especially as it relates to interactions with host immune cells and mechanisms of antifungal drugs. Due to the notable similarities in growth patterns of neuronal cells and mycelial networks, we sought to repurpose the NeuroTrack (NT) processing module of the IncuCyte time-lapse microscopy system as a tool to quantify mycelial growth and branching of pathogenic fungi. We showed the robustness of NT analysis to study Candida albicans and five different molds and confirmed established characteristics of mycelial growth kinetics. We also documented high intra- and interassay reproducibility of the NT module for a spectrum of spore inocula and culture periods. Using GFP-expressing Aspergillus fumigatus and Rhizopus arrhizus, the feasibility of fluorescence-based NT analysis was validated. In addition, we performed proof-of-concept experiments of NT analysis for several translational applications such as studying the morphogenesis of a filamentation-defective C. albicans mutant, the effects of different classes of antifungals (polyenes, azoles, and echinocandins), and coculture with host immune cells. High accuracy was found, even at high immune cell-to-fungus ratios or in the presence of fungal debris. For antifungal efficacy studies, addition of a cytotoxicity dye further refined IncuCyte-based analysis, facilitating real-time determination of fungistatic and fungicidal activity in a single assay. Complementing conventional MIC-based assays, NT analysis is an appealing method to study fungal morphogenesis and viability in the context of antifungal compound screening and evaluation of novel immune therapeutics.

Contrast Agents Delivery: An Up-to-Date Review of Nanodiagnostics in Neuroimaging

Neuroimaging is a highly important field of neuroscience, with direct implications for the early diagnosis and progression monitoring of brain-associated diseases. Neuroimaging techniques are categorized into structural, functional and molecular neuroimaging, each possessing advantages and disadvantages in terms of resolution, invasiveness, toxicity of contrast agents and costs. Nanotechnology-based approaches for neuroimaging mostly involve the development of nanocarriers for incorporating contrast agents or the use of nanomaterials as imaging agents. Inorganic and organic nanoparticles, liposomes, micelles, nanobodies and quantum dots are some of the most studied candidates for the delivery of contrast agents for neuroimaging. This paper focuses on describing the conventional modalities used for imaging and the applications of nanotechnology for developing novel strategies for neuroimaging. The aim is to highlight the roles of nanocarriers for enhancing and/or overcome the limitations associated with the most commonly utilized neuroimaging modalities. For future directions, several techniques that could benefit from the increased contrast induced by using imaging probes are presented.

Real-Time Determination of the Cell-Cycle Position of Individual Cells within Live Tumors Using FUCCI Cell-Cycle Imaging

Most cytotoxic agents have limited efficacy for solid cancers. Cell-cycle phase analysis at the single-cell level in solid tumors has shown that the majority of cancer cells in tumors is not cycling and is therefore resistant to cytotoxic chemotherapy. Intravital cell-cycle imaging within tumors demonstrated the cell-cycle position and distribution of cancer cells within a tumor, and cell-cycle dynamics during chemotherapy. Understanding cell-cycle dynamics within tumors should provide important insights into novel treatment strategies.

Raman Microspectroscopic Evidence for the Metabolism of a Tyrosine Kinase Inhibitor, Neratinib, in Cancer Cells

Tyrosine kinase receptors are one of the main targets in cancer therapy. They play an essential role in the modulation of growth factor signaling and thereby inducing cell proliferation and growth. Tyrosine kinase inhibitors such as neratinib bind to EGFR and HER2 receptors and exhibit antitumor activity. However, little is known about their detailed cellular uptake and metabolism. Here, we report for the first time the intracellular spatial distribution and metabolism of neratinib in different cancer cells using label-free Raman imaging. Two new neratinib metabolites were detected and fluorescence imaging of the same cells indicate that neratinib accumulates in lysosomes. The results also suggest that both EGFR and HER2 follow the classical endosome lysosomal pathway for degradation. A combination of Raman microscopy, DFT calculations, and LC-MS was used to identify the chemical structure of neratinib metabolites. These results show the potential of Raman microscopy to study drug pharmacokinetics.

In situ imaging of quantum dot-AZD4547 conjugates for tracking the dynamic behavior of fibroblast growth factor receptor 3

Fibroblast growth factor receptors (FGFRs) play an important role in determining cell proliferation, differentiation, migration, and survival. Although a variety of small-molecule FGFR inhibitors have been developed for cancer therapeutics, the interaction between FGFRs and FGFR inhibitors has not been well characterized. The FGFR–inhibitor interaction can be characterized using a new imaging probe that has strong, stable signal properties for in situ cellular imaging of the interaction without quenching. We developed a kinase–inhibitor-modified quantum dot (QD) probe to investigate the interaction between FGFR and potential inhibitors. Especially, turbo-green fluorescent protein-FGFR3s were overexpressed in HeLa cells to investigate the colocalization of FGFR3 and AZD4547 using the QD-AZD4547 probe. The result indicates that this probe is useful for investigating the binding behaviors of FGFR3 with the FGFR inhibitor. Thus, this new inhibitor-modified QD probe is a promising tool for understanding the interaction between FGFR and inhibitors and for creating future high-content, cell-based drug screening strategies.

Imaging drug uptake by bioorthogonal stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy in tandem with bioorthogonal Raman labelling enables intracellular drug concentrations, distribution and therapeutic response to be measured in living cells.

Stimulated Raman scattering (SRS) microscopy in tandem with bioorthogonal Raman labelling strategies is set to revolutionise the direct visualisation of intracellular drug uptake. Rational evaluation of a series of Raman-active labels has allowed the identification of highly active labels which have minimal perturbation on the biological efficacy of the parent drug. Drug uptake has been correlated with markers of cellular composition and cell cycle status, and mapped across intracellular structures using dual-colour and multi-modal imaging. The minimal phototoxicity and low photobleaching associated with SRS microscopy has enabled real-time imaging in live cells. These studies demonstrate the potential for SRS microscopy in the drug development process.

Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening

Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery.

Preclinical Advances with Multiphoton Microscopy in Live Imaging of Skin Cancers

Conventional, static analyses have historically been the bedrock and tool of choice for the study of skin cancers. Over the past several years, in vivo imaging of tumors using multiphoton microscopy has emerged as a powerful preclinical tool for revealing detailed cellular behaviors from the earliest moments of tumor development to the final steps of metastasis. Multiphoton microscopy allows for deep tissue penetration with relatively minor phototoxicity, rendering it an effective tool for the long-term observation of tumor evolution. This review highlights some of the recent preclinical insights gained using multiphoton microscopy and suggests future advances that could enhance its power in revealing the mysteries of skin tumor biology.

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell- and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates.

Next-generation phenotypic screening

Phenotypic drug discovery (PDD) strategies are defined by screening and selection of hit or lead compounds based on quantifiable phenotypic endpoints without prior knowledge of the drug target. We outline the challenges associated with traditional phenotypic screening strategies and propose solutions and new opportunities to be gained by adopting modern PDD technologies. We highlight both historical and recent examples of approved drugs and new drug candidates discovered by modern phenotypic screening. Finally, we offer a prospective view of a new era of PDD underpinned by a wealth of technology advances in the areas of in vitro model development, high-content imaging and image informatics, mechanism-of-action profiling and target deconvolution.

Stimulated Raman scattering microscopy: an emerging tool for drug discovery

Optical microscopy techniques have emerged as a cornerstone of biomedical research, capable of probing the cellular functions of a vast range of substrates, whilst being minimally invasive to the cells or tissues of interest. Incorporating biological imaging into the early stages of the drug discovery process can provide invaluable information about drug activity within complex disease models. Spontaneous Raman spectroscopy has been widely used as a platform for the study of cells and their components based on chemical composition; but slow acquisition rates, poor resolution and a lack of sensitivity have hampered further development. A new generation of stimulated Raman techniques is emerging which allows the imaging of cells, tissues and organisms at faster acquisition speeds, and with greater resolution and sensitivity than previously possible. This review focuses on the development of stimulated Raman scattering (SRS), and covers the use of bioorthogonal tags to enhance sample detection, and recent applications of both spontaneous Raman and SRS as novel imaging platforms to facilitate the drug discovery process.

Assessment of Gate Width Size on Lifetime-Based Förster Resonance Energy Transfer Parameter Estimation

Förster Resonance Energy Transfer (FRET) enables the observation of interactions at the nanoscale level through the use of fluorescence optical imaging techniques. In FRET, fluorescence lifetime imaging can be used to quantify the fluorescence lifetime changes of the donor molecule, which are associated with proximity between acceptor and donor molecules. Among the FRET parameters derived from fluorescence lifetime imaging, the percentage of donor that interacts with the acceptor (in proximity) can be estimated via model-based fitting. However, estimation of the lifetime parameters can be affected by the acquisition parameters such as the temporal characteristics of the imaging system. Herein, we investigate the effect of various gate widths on the accuracy of estimation of FRET parameters with focus on the near-infrared spectral window. Experiments were performed in silico, in vitro, and in vivo with gate width sizes ranging from 300 ps to 1000 ps in intervals of 100 ps. For all cases, the FRET parameters were retrieved accurately and the imaging acquisition time was decreased three-fold. These results indicate that increasing the gate width up to 1000 ps still allows for accurate quantification of FRET interactions even in the case of short lifetimes such as those encountered with near-infrared FRET pairs.

Optimizing Central Nervous System Drug Development Using Molecular Imaging

Advances in multimodality fusion imaging technologies promise to accelerate the understanding of the systems biology of disease and help in the development of new therapeutics. The use of molecular imaging biomarkers has been proven to shorten cycle times for central nervous system (CNS) drug development and thereby increase the efficiency and return on investment from research. Imaging biomarkers can be used to help select the molecules, doses, and patients most likely to test therapeutic hypotheses by stopping those that have little chance of success and accelerating those with potential to achieve beneficial clinical outcomes. CNS imaging biomarkers have the potential to drive new medical care practices for patients in the latent phases of progressive neurodegenerative disorders by enabling the detection, preventative treatment, and tracking of disease in a paradigm shift from today's approaches that have to see the overt symptoms of disease before treating it.

Challenges and opportunities toward enabling phenotypic screening of complex and 3D cell models

Increasingly, organotypic cellular platforms are being recognized as useful tools in drug discovery. This review offers an industry-centric perspective on the benefits of emerging complex cell models over conventional 2D systems, as well as the challenges and opportunities for incorporating these multidimensional platforms into high-density formats. We particularly highlight the need for novel chemical sensors to noninvasively quantitate 3D structures in real time, and we contend that the use of more focused chemical and genomics libraries will enable screening of complex cell models derived from primary and induced pluripotent stem cells. Finally, we offer outlooks on several emerging technologies that show great potential for future integration of complex cell systems into contemporary drug screening.

Cells on film – the past and future of cinemicroscopy

Movie making is now a ubiquitous experimental tool that biologists use alongside more traditional techniques such as molecular biology and biochemistry. It is no longer just cell biologists, but scientists from many other disciplines, such as immunology and neuroscience, that utilise movies to dissect their processes of interest. When did filming become such a standard laboratory technique? Who developed the use of the movie as an experimental tool? The Wellcome Library has recently restored and digitized a number of original 16-mm films from two pioneering cinemicroscopists, Ronald Canti and Michael Abercrombie, which are now freely available to the scientific community. In light of these films, this Essay will give a brief history of the early cinemicroscopists and discuss what is driving the use of movies in the laboratory today.

Developments in preclinical cancer imaging: innovating the discovery of therapeutics

Integrating biological imaging into early stages of the drug discovery process can provide invaluable readouts of drug activity within complex disease settings, such as cancer. Iterating this approach from initial lead compound identification in vitro to proof-of-principle in vivo analysis represents a key challenge in the drug discovery field. By embracing more complex and informative models in drug discovery, imaging can improve the fidelity and statistical robustness of preclinical cancer studies. In this Review, we highlight how combining advanced imaging with three-dimensional systems and intravital mouse models can provide more informative and disease-relevant platforms for cancer drug discovery.

Advanced intravital subcellular imaging reveals vital three-dimensional signalling events driving cancer cell behaviour and drug responses in live tissue

The integration of signal transduction pathways plays a fundamental role in governing disease initiation, progression and outcome. It is therefore necessary to understand disease at the signalling level to enable effective treatment and to intervene in its progression. The recent extension of in vitro subcellular image-based analysis to live in vivo modelling of disease is providing a more complete picture of real-time, dynamic signalling processes or drug responses in live tissue. Intravital imaging offers alternative strategies for studying disease and embraces the biological complexities that govern disease progression. In the present review, we highlight how three-dimensional or live intravital imaging has uncovered novel insights into biological mechanisms or modes of drug action. Furthermore, we offer a prospective view of how imaging applications may be integrated further with the aim of understanding disease in a more physiological and functional manner within the framework of the drug discovery process.

Intravital FLIM-FRET imaging reveals dasatinib-induced spatial control of src in pancreatic cancer

Cancer invasion and metastasis occur in a complex three-dimensional (3D) environment, with reciprocal feedback from the surrounding host tissue and vasculature-governing behavior. In this study, we used a novel intravital method that revealed spatiotemporal regulation of Src activity in response to the anti-invasive Src inhibitor dasatinib. A fluorescence lifetime imaging microscopy-fluorescence resonance energy transfer (FLIM-FRET) Src biosensor was used to monitor drug-targeting efficacy in a transgenic p53-mutant mouse model of pancreatic cancer. In contrast to conventional techniques, FLIM-FRET analysis allowed for accurate, time-dependent, live monitoring of drug efficacy and clearance in live tumors. In 3D organotypic cultures, we showed that a spatially distinct gradient of Src activity exists within invading tumor cells, governed by the depth of penetration into complex matrices. In parallel, this gradient was also found to exist within live tumors, where Src activity is enhanced at the invasive border relative to the tumor cortex. Upon treatment with dasatinib, we observed a switch in activity at the invasive borders, correlating with impaired metastatic capacity in vivo. Src regulation was governed by the proximity of cells to the host vasculature, as cells distal to the vasculature were regulated differentially in response to drug treatment compared with cells proximal to the vasculature. Overall, our results in live tumors revealed that a threshold of drug penetrance exists in vivo and that this can be used to map areas of poor drug-targeting efficiency within specific tumor microenvironments. We propose that using FLIM-FRET in this capacity could provide a useful preclinical tool in animal models before clinical translation.

Combination therapy via oral co-administration of insulin- and exendin-4-loaded nanoparticles to treat type 2 diabetic rats undergoing OGTT

Current insulin therapy via subcutaneous administration can lead to occasional hypoglycemia and peripheral hyperinsulinemia, due to its nonphysiological route. This study evaluates the feasibility of using bovine insulin and exendin-4 in a form of combination therapy, as orally delivered by nanoparticles composed of chitosan and poly(γ-glutamic acid) (CS/γPGA NPs), to control blood glucose levels in rats with type 2 diabetes mellitus (T2DM) undergoing the oral glucose tolerance test. Experimental results indicate that CS/γPGA NPs could enhance the intestinal paracellular permeation; consequently, the exogenous bovine insulin and exendin-4 could be delivered into the liver and pancreas, where they could elicit their glucoregulatory activities. In response to the stimulus of exogenously delivered bovine insulin and the endogenously secreted rat insulin stimulated by the ingested exendin-4, significant glucose utilizations were found in the cardiac and skeletal muscles, resulting in the glucose-lowering effect. Owing to its synergic stimulation effects, the hypoglycemic effect of oral ingestion of NPs containing bovine insulin and exendin-4 was significantly greater than that of the group solely treated with insulin NPs. Above results demonstrate that oral combination therapy with bovine insulin and exendin-4 improves the modulation of blood glucose levels in T2DM rats, making it highly promising for treating those T2DM patients not adequately controlled by the current insulin therapy.

Combining imaging and pathway profiling: an alternative approach to cancer drug discovery

Conventional drug discovery strategies are typically 'target centric' based on the selection of lead compounds with optimised 'on-target' potency and selectivity profiles. However, high-attrition rates are often the result of compensatory or redundant cancer mechanisms and the fact that tumours do not find it difficult to escape inhibition of a single pathway. In this article, we highlight two emerging and complimentary technologies; namely phenotypic imaging and post-translational pathway profiling, which when combined with relevant disease models can provide pharmacodiagnostic and drug combination strategies that predict and counteract inherent and adaptive drug resistance. The implementation of such approaches at early stages of the drug discovery process enables more informed decisions on candidate drug selection and how to maximise and predict efficacy before clinical development.

Advancing cancer drug discovery towards more agile development of targeted combination therapies

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.