Personalized in vitro cancer models to predict therapeutic response: Challenges and a framework for improvement

Bridging the gap between tumor and disease: Innovating cancer and glioma models

Recent advances in cancer biology and therapeutics have underscored the importance of preclinical models in understanding and treating cancer. Nevertheless, current models often fail to capture the complexity and patient-specific nature of human tumors, particularly gliomas. This review examines the strengths and weaknesses of such models, highlighting the need for a new generation of models. Emphasizing the critical role of the tumor microenvironment, tumor, and patient heterogeneity, we propose integrating our advanced understanding of glioma biology with innovative bioengineering and AI technologies to create more clinically relevant, patient-specific models. These innovations are essential for improving therapeutic development and patient outcomes.

Impact of Proton Irradiation Depending on Breast Cancer Subtype in Patient-Derived Cell Lines

Research on different types of ionizing radiation's effects has been ongoing for years, revealing its efficacy in damaging cancer cells. Solid tumors comprise diverse cell types, each being able to respond differently to radiation. This study evaluated the radiobiological response of established (MDA-MB-231 (Triple negative breast cancer, TNBC), MCF-7 (Luminal A)) and patient-derived malignant cell lines, cancer-associated fibroblasts, and skin fibroblasts following proton IRR. All cell line types were irradiated with the proton dose of 2, 4, and 6 Gy. The radiobiological response was assessed using clonogenic assay, γH2AX, and p53 staining. It was noticeable that breast cancer lines of different molecular subtypes displayed no significant variations in their response to proton IRR. In terms of cancer-associated fibroblasts extracted from the tumor tissue, the line derived from a TNBC subtype tumor demonstrated higher resistance to ionizing radiation compared to lines isolated from luminal A tumors. Fibroblasts extracted from patients' skin responded identically to all doses of proton radiation. This study emphasizes that tumor response is not exclusively determined by the elimination of breast cancer cells, but also takes into account tumor microenvironmental variables and skin reactions.

Crowdsourcing AOP development: Leveraging the thesis literature review to identify knowledge gaps and facilitate research translation

Chemical risk assessment still primarily relies on extrapolation of data from high-confidence in vivo studies. Emerging 21st Century Toxicology tools and approaches have potential to figure more prominently in chemical risk assessment, but many challenges in translating this research into assessments remain. One of these tools, the Adverse Outcome Pathway (AOP) Wiki provides a framework to map and evaluate adverse chemical dynamics, that is the biochemical and physiological effects that occur after chemical exposure. The AOP-guided targeted review of relevant literature, described here, shares similarities with a doctoral thesis or literature review but forces critical evaluation of each step in a pathway including those of central dogma. Additionally, it provides valuable translational regulatory relevance. Data gaps identified through this process can be targeted areas of study in the thesis itself to increase translational relevance. One of the challenges with this tool is that many AOPs are under- or undeveloped. To help fill this need, a concerted effort by subject matter experts to speed the development of AOPs supported under the Organization for Economic Cooperation and Development (OECD) framework would benefit this translational problem. As a case study, we present our experience developing AOP 460: Antagonism of Smoothened receptor leading to orofacial clefting (OECD AOP workplan project 1.101) as part of a graduate literature review. AOP development offers clear benefits to the regulatory and academic communities and increased dissemination of AOPs replete with the most current state of scientific knowledge will promote research translation and increased risk assessment capabilities.

Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer

OBJECTIVES

We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Preoperative enhanced abdominal CT images and the histoculture drug response assay (HDRA) results were collected from 33 PDAC patients undergoing surgery. Deep learning was performed using CT images of both the HDRA-positive and HDRA-negative groups. We trimmed small patches from the entire tumor area. We established various prediction labels for HDRA results with 5-fluorouracil (FU), gemcitabine (GEM), and paclitaxel (PTX). We built a predictive model using a residual convolutional neural network and used 3-fold cross-validation.

RESULTS

Of the 33 patients, effective response to FU, GEM, and PTX by HDRA was observed in 19 (57.6%), 11 (33.3%), and 23 (88.5%) patients, respectively. The average accuracy and the area under the receiver operating characteristic curve (AUC) of the model for predicting the effective response to FU were 93.4% and 0.979, respectively. In the prediction of GEM, the models demonstrated high accuracy (92.8%) and AUC (0.969). Likewise, the model for predicting response to PTX had a high performance (accuracy, 95.9%; AUC, 0.979).

CONCLUSIONS

Our CT patch-based DL model exhibited high predictive performance in projecting HDRA results. Our study suggests that the DL approach could possibly provide a noninvasive means for the optimization of chemotherapy.

The adverse outcome pathway for breast cancer: a knowledge management framework bridging biomedicine and toxicology

Breast cancer is the most common cancer worldwide, with an estimated 2.3 million new cases diagnosed every year. Effective measures for cancer prevention and cancer therapy require a detailed understanding of the individual key disease mechanisms involved and their interactions at the molecular, cellular, tissue, organ, and organism level. In that regard, the rapid progress of biomedical and toxicological research in recent years now allows the pursuit of new approaches based on non-animal methods that provide greater mechanistic insight than traditional animal models and therefore facilitate the development of Adverse Outcome Pathways (AOPs) for human diseases. We performed a systematic review of the current state of published knowledge with regard to breast cancer to identify relevant key mechanisms for inclusion into breast cancer AOPs, i.e. decreased cell stiffness and decreased cell adhesion, and to concurrently map non-animal methods addressing these key events. We conclude that the broader sharing of expertise and methods between biomedical research and toxicology enabled by the AOP knowledge management framework can help to coordinate global research efforts and accelerate the transition to advanced non-animal methods, which, when combined into powerful method batteries, closely mimic human physiology and disease states without the need for animal testing.

Portable optical spectroscopic assay for non-destructive measurement of key metabolic parameters on in vitro cancer cells and organotypic fresh tumor slices

To enable non-destructive metabolic characterizations on in vitro cancer cells and organotypic tumor models for therapeutic studies in an easy-to-access way, we report a highly portable optical spectroscopic assay for simultaneous measurement of glucose uptake and mitochondrial function on various cancer models with high sensitivity. Well-established breast cancer cell lines (MCF-7 and MDA-MB-231) were used to validate the optical spectroscopic assay for metabolic characterizations, while fresh tumor samples harvested from both animals and human cancer patients were used to test the feasibility of our optical metabolic assay for non-destructive measurement of key metabolic parameters on organotypic tumor slices. Our optical metabolic assay captured that MCF-7 cells had higher mitochondrial metabolism, but lower glucose uptake compared to the MDA-MB-231 cells, which is consistent with our microscopy imaging and flow cytometry data, as well as the published Seahorse Assay data. Moreover, we demonstrated that our optical assay could non-destructively measure both glucose uptake and mitochondrial metabolism on the same cancer cell samples at one time, which remains challenging by existing metabolic tools. Our pilot tests on thin fresh tumor slices showed that our optical assay captured increased metabolic activities in tumors compared to normal tissues. Our non-destructive optical metabolic assay provides a cost-effective way for future longitudinal therapeutic studies using patient-derived organotypic fresh tumor slices through the lens of tumor energetics, which will significantly advance translational cancer research.

The effect of matrices on the gene expression profile of patient-derived head and neck carcinoma cells for in vitro therapy testing

OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive tumor with a 5-year mortality rate of ~ 50%. New in vitro methods are needed for testing patients' cancer cell response to anti-cancer treatments. We aimed to investigate how the gene expression of fresh carcinoma tissue samples and freshly digested single cancer cells change after short-term cell culturing on plastic, Matrigel or Myogel. Additionally, we studied the effect of these changes on the cancer cells' response to anti-cancer treatments.

MATERIALS/METHODS

Fresh tissue samples from HNSCC patients were obtained perioperatively and single cells were enzymatically isolated and cultured on either plastic, Matrigel or Myogel. We treated the cultured cells with cisplatin, cetuximab, and irradiation; and performed cell viability measurement. RNA was isolated from fresh tissue samples, freshly isolated single cells and cultured cells, and RNA sequencing transcriptome profiling and gene set enrichment analysis were performed.

RESULTS

Cancer cells obtained from fresh tissue samples changed their gene expression regardless of the culturing conditions, which may be due to the enzymatic digestion of the tissue. Myogel was more effective than Matrigel at supporting the upregulation of pathways related to cancer cell proliferation and invasion. The impacts of anti-cancer treatments varied between culturing conditions.

CONCLUSIONS

Our study showed the challenge of in vitro cancer drug testing using enzymatic cell digestion. The upregulation of many targeted pathways in the cultured cells may partially explain the common clinical failure of the targeted cancer drugs that pass the in vitro testing.

Engineered Vasculature for Cancer Research and Regenerative Medicine

Engineered human tissues created by three-dimensional cell culture of human cells in a hydrogel are becoming emerging model systems for cancer drug discovery and regenerative medicine. Complex functional engineered tissues can also assist in the regeneration, repair, or replacement of human tissues. However, one of the main hurdles for tissue engineering, three-dimensional cell culture, and regenerative medicine is the capability of delivering nutrients and oxygen to cells through the vasculatures. Several studies have investigated different strategies to create a functional vascular system in engineered tissues and organ-on-a-chips. Engineered vasculatures have been used for the studies of angiogenesis, vasculogenesis, as well as drug and cell transports across the endothelium. Moreover, vascular engineering allows the creation of large functional vascular conduits for regenerative medicine purposes. However, there are still many challenges in the creation of vascularized tissue constructs and their biological applications. This review will summarize the latest efforts to create vasculatures and vascularized tissues for cancer research and regenerative medicine.

Microfluidics in vascular biology research: a critical review for engineers, biologists, and clinicians

Neovascularization, the formation of new blood vessels, has received much research attention due to its implications for physiological processes and diseases. Most studies using traditional in vitro and in vivo platforms find challenges in recapitulating key cellular and mechanical cues of the neovascularization processes. Microfluidic in vitro models have been presented as an alternative to these limitations due to their capacity to leverage microscale physics to control cell organization and integrate biochemical and mechanical cues, such as shear stress, cell-cell interactions, or nutrient gradients, making them an ideal option for recapitulating organ physiology. Much has been written about the use of microfluidics in vascular biology models from an engineering perspective. However, a review introducing the different models, components and progress for new potential adopters of these technologies was absent in the literature. Therefore, this paper aims to approach the use of microfluidic technologies in vascular biology from a perspective of biological hallmarks to be studied and written for a wide audience ranging from clinicians to engineers. Here we review applications of microfluidics in vascular biology research, starting with design considerations and fabrication techniques. After that, we review the state of the art in recapitulating angiogenesis and vasculogenesis, according to the hallmarks recapitulated and complexity of the models. Finally, we discuss emerging research areas in neovascularization, such as drug discovery, and potential future directions.

Development of an adverse outcome pathway network for breast cancer: a comprehensive representation of the pathogenesis, complexity and diversity of the disease

Adverse outcome pathways (AOPs), introduced in modern toxicology, intend to provide an evidence-based representation of toxicological effects and facilitate safety assessment of chemicals not solely based on laboratory animal in vivo experiments. However, some toxicological processes are too complicated to represent in one AOP. Therefore, AOP networks are developed that help understanding and predicting toxicological processes where complex exposure scenarios interact and lead to the emergence of the adverse outcome. In this study, we present an AOP network for breast cancer, developed after an in-depth survey of relevant scientific literature. Several molecular initiating events (MIE) were identified and various key events that link the MIEs with breast cancer were described. The AOP was developed according to Organization of Economic Co-Operation and Development (OECD) guidance, weight of evidence was assessed through the Bradford Hill criteria and confidence was tested by the OECD key questions. The AOP network provides a straightforward understanding of the disease onset and progression at different biological levels. It can be used to pinpoint knowledge gaps, identify novel therapeutic targets and act as a stepping stone for the development of novel in vitro test methods for hazard identification and risk assessment of newly developed chemicals and drugs.

Microphysiological model of the renal cell carcinoma to inform anti-angiogenic therapy

Renal cell carcinomas are common genitourinary tumors characterized by high vascularization and strong reliance on glycolysis. Despite the many available therapies for renal cell carcinomas, first-line targeted therapies, such as cabozantinib, and durable reaponses are seen in only a small percentage of patients. Yet, little is known about the mechanisms that drive response (or lack thereof). This dearth of knowledge can be explained by the dynamic and complex microenvironment of renal carcinoma, which remains challenging to recapitulate in vitro. Here, we present a microphysiological model of renal cell carcinoma, including a tubular blood vessel model of induced pluripotent stem cell-derived endothelial cells and an adjacent 3D carcinoma model. Our model recapitulated hypoxia, glycolic metabolism, and sprouting angiogenesis. Using our model, we showed that cabozantinib altered cancer cell metabolism and decreased sprouting angiogenesis but did not restore barrier function. This microphysiological model could be helpful to elucidate, through multiple endpoints, the contributions of the relevant environmental components in eliciting a functional response or resistance to therapy in renal cell carcinoma.

Defining clinical outcome pathways

Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: molecular initiating event (MIE) → intermediate event(s) → clinical outcome. We illustrate the concept with COP examples both for primary and alternative (i.e., drug repurposing) therapeutic applications. We also describe the elucidation of COPs for several drugs of interest using the publicly accessible Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways (ROBOKOP) biomedical knowledge graph-mining tool. We propose that broader use of COP uncovered with the help of biomedical knowledge graph mining will likely accelerate drug discovery and repurposing efforts.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Benefits of functional assays in personalized cancer medicine: more than just a proof-of-concept

As complex and heterogeneous diseases, cancers require a more tailored therapeutic management than most pathologies. Recent advances in anticancer drug development, including the immuno-oncology revolution, have been too often plagued by unsatisfying patient response rates and survivals. In reaction to this, cancer care has fully transitioned to the “personalized medicine” concept. Numerous tools are now available tools to better adapt treatments to the profile of each patient. They encompass a large array of diagnostic assays, based on biomarkers relevant to targetable molecular pathways. As a subfamily of such so-called companion diagnostics, chemosensitivity and resistance assays represent an attractive, yet insufficiently understood, approach to individualize treatments. They rely on the assessment of a composite biomarker, the ex vivo functional response of cancer cells to drugs, to predict a patient's outcome. Systemic treatments, such as chemotherapies, as well as targeted treatments, whose efficacy cannot be fully predicted yet by other diagnostic tests, may be assessed through these means. The results can provide helpful information to assist clinicians in their decision-making process. We explore here the most advanced functional assays across oncology indications, with an emphasis on tests already displaying a convincing clinical demonstration. We then recapitulate the main technical obstacles faced by researchers and clinicians to produce more accurate, and thus more predictive, models and the recent advances that have been developed to circumvent them. Finally, we summarize the regulatory and quality frameworks surrounding functional assays to ensure their safe and performant clinical implementation. Functional assays are valuable in vitro diagnostic tools that already stand beyond the “proof-of-concept” stage. Clinical studies show they have a major role to play by themselves but also in conjunction with molecular diagnostics. They now need a final lift to fully integrate the common armament used against cancers, and thus make their way into the clinical routine.

Patient-Derived Explants of Colorectal Cancer: Histopathological and Molecular Analysis of Long-Term Cultures

Simple Summary

Colorectal cancer is the third most common cancer type among men and women. Prescription of medical treatments for cancer often relies on a process of trial and potential error, more recently guided by patient stratification based on biomarkers. Nonetheless, available biomarkers do not accurately predict patient response and there is a need for predictive and translational models to provide proper clinical information on treatment guidance. Herein, we developed an ex vivo model of colorectal cancer, using fresh tumour samples to establish explant cultures, taking advantage of agitation-based culture systems. We performed a thorough characterisation over one month in culture and observed preservation of original tumour genetic features and partial preservation of architecture and non-malignant cells that compose the tumour microenvironment. Our findings highlight the importance of detailed model characterisation and support the applicability of our model in pre- and co-clinical settings.

Abstract

Colorectal cancer (CRC) is one of the most common cancers worldwide. Although short-term cultures of tumour sections and xenotransplants have been used to determine drug efficacy, the results frequently fail to confer clinically useful information. Biomarker discovery has changed the paradigm for advanced CRC, though the presence of a biomarker does not necessarily translate into therapeutic success. To improve clinical outcomes, translational models predictive of drug response are needed. We describe a simple method for the fast establishment of CRC patient-derived explant (CRC-PDE) cultures from different carcinogenesis pathways, employing agitation-based platforms. A total of 26 CRC-PDE were established and a subset was evaluated for viability (n = 23), morphology and genetic key alterations (n = 21). CRC-PDE retained partial tumor glandular architecture and microenvironment features were partially lost over 4 weeks of culture. Key proteins (p53 and Mismatch repair) and oncogenic driver mutations of the original tumours were sustained throughout the culture. Drug challenge (n = 5) revealed differential drug response from distinct CRC-PDE cases. These findings suggest an adequate representation of the original tumour and highlight the importance of detailed model characterisation. The preservation of key aspects of the CRC microenvironment and genetics supports CRC-PDE potential applicability in pre- and co-clinical settings, as long as temporal dynamics are considered.

Recapitulating the Cancer Microenvironment Using Bioprinting Technology for Precision Medicine

The complex and heterogenous nature of cancer contributes to the development of cancer cell drug resistance. The construction of the cancer microenvironment, including the cell-cell interactions and extracellular matrix (ECM), plays a significant role in the development of drug resistance. Traditional animal models used in drug discovery studies have been associated with feasibility issues that limit the recapitulation of human functions; thus, in vitro models have been developed to reconstruct the human cancer system. However, conventional two-dimensional and three-dimensional (3D) in vitro cancer models are limited in their ability to emulate complex cancer microenvironments. Advances in technologies, including bioprinting and cancer microenvironment reconstruction, have demonstrated the potential to overcome some of the limitations of conventional models. This study reviews some representative bioprinted in vitro models used in cancer research, particularly fabrication strategies for modeling and consideration of essential factors needed for the reconstruction of the cancer microenvironment. In addition, we highlight recent studies that applied such models, including application in precision medicine using advanced bioprinting technologies to fabricate biomimetic cancer models. Furthermore, we discuss current challenges in 3D bioprinting and suggest possible strategies to construct in vitro models that better mimic the pathophysiology of the cancer microenvironment for application in clinical settings.

A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer

In silico models of biomolecular regulation in cancer, annotated with patient-specific gene expression data, can aid in the development of novel personalized cancer therapeutic strategies. Drosophila melanogaster is a well-established animal model that is increasingly being employed to evaluate such preclinical personalized cancer therapies. Here, we report five Boolean network models of biomolecular regulation in cells lining the Drosophila midgut epithelium and annotate them with colorectal cancer patient-specific mutation data to develop an in silico Drosophila Patient Model (DPM). We employed cell-type-specific RNA-seq gene expression data from the FlyGut-seq database to annotate and then validate these networks. Next, we developed three literature-based colorectal cancer case studies to evaluate cell fate outcomes from the model. Results obtained from analyses of the proposed DPM help: (i) elucidate cell fate evolution in colorectal tumorigenesis, (ii) validate cytotoxicity of nine FDA-approved CRC drugs, and (iii) devise optimal personalized treatment combinations. The personalized network models helped identify synergistic combinations of paclitaxel-regorafenib, paclitaxel-bortezomib, docetaxel-bortezomib, and paclitaxel-imatinib for treating different colorectal cancer patients. Follow-on therapeutic screening of six colorectal cancer patients from cBioPortal using this drug combination demonstrated a 100% increase in apoptosis and a 100% decrease in proliferation. In conclusion, this work outlines a novel roadmap for decoding colorectal tumorigenesis along with the development of personalized combinatorial therapeutics for preclinical translational studies.

Cancer models in preclinical research: A chronicle review of advancement in effective cancer research

Cancer is a major stress for public well-being and is the most dreadful disease. The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies. Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar. The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination. Therefore, vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion, progression, and early detection. These models give an insight into cancer etiology, molecular basis, host tumor interaction, the role of microenvironment, and tumor heterogeneity in tumor metastasis. These models are also used to predict novel cancer markers, targeted therapies, and are extremely helpful in drug development. In this review, the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted. Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and translational medicine. However, they promise a brighter future for cancer treatment.

FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children

FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.

Applying evidence-based methods to the development and use of adverse outcome pathways

The workshop “Application of evidence-based methods to construct mechanistic frameworks for the development and use of non-animal toxicity tests” was organized by the Evidence-based Toxicology Collaboration and hosted by the Grading of Recommendations Assessment, Development and Evaluation Working Group on June 12, 2019. The purpose of the workshop was to bring together international regulatory bodies, risk assessors, academic scientists, and industry to explore how systematic review methods and the adverse outcome pathway framework could be combined to develop and use mechanistic test methods for predicting the toxicity of chemical substances in an evidence-based manner. The meeting covered the history of biological frameworks, the way adverse outcome pathways are currently developed, the basic principles of systematic methodology, including systematic reviews and evidence maps, and assessment of cer­tainty in models, and adverse outcome pathways in particular. Specific topics were discussed via case studies in small break-out groups. The group concluded that adverse outcome pathways provide an important framework to support mechanism-based assessment in environmental health. The process of their development has a few challenges that could be addressed with systematic methods and automation tools. Addressing these challenges will increase the transparency of the evidence behind adverse outcome pathways and the consistency with which they are defined; this in turn will increase their value for supporting public health decisions. It was suggested to explore the details of applying systematic methods to adverse outcome pathway development in a series of case studies and workshops.

The E-Morph Assay: Identification and characterization of environmental chemicals with estrogenic activity based on quantitative changes in cell-cell contact organization of breast cancer cells

Adverse health effects that are caused by endocrine disrupting chemicals (EDCs) in the environment, food or consumer products are of high public concern. The identification and characterization of EDCs including substances with estrogenic activity still necessitates the use of animal testing as most of the approved alternative test methods only address single mechanistic events of endocrine activity. Therefore, novel human-relevant in vitro assays covering more complex functional endpoints of adversity, including hormone-related tumor formation and progression, are needed. This study describes the development and evaluation of a novel high-throughput screening-compatible assay called "E-Morph Assay". This image-based phenotypic screening assay facilitates robust predictions of the estrogenic potential of environmental chemicals using quantitative changes in the cell-cell contact morphology of human breast cancer cells as a novel functional endpoint. Based on a classification model, which was developed using six reference substances with known estrogenic activity, the E-Morph Assay correctly classified an additional set of 11 reference chemicals commonly used in OECD Test Guidelines and the U.S. EPA ToxCast program. For each of the tested substances, a relative ER bioactivity score was derived that allowed their grouping into four main categories of estrogenic activity, i.e. 'strong' (>0.9; four substances, i.e. natural hormones or pharmaceutical products), 'moderate' (0.9-0.6; six substances, i.e. phytoestrogens and Bisphenol AF), 'weak' (<0.6; three substances, i.e Bisphenol S, B, and A), and 'negative' (0.0; four substances). The E-Morph Assay considerably expands the portfolio of test methods providing the possibility to characterize the influence of environmental chemicals on estrogen-dependent tumor progression.

Toward improved in vitro models of human cancer

Cancer is a leading cause of death across the world and continues to increase in incidence. Despite years of research, multiple tumors (e.g., glioblastoma, pancreatic cancer) still have limited treatment options in the clinic. Additionally, the attrition rate and cost of drug development have continued to increase. This trend is partly explained by the poor predictive power of traditional in vitro tools and animal models. Moreover, multiple studies have highlighted that cell culture in traditional Petri dishes commonly fail to predict drug sensitivity. Conversely, animal models present differences in tumor biology compared with human pathologies, explaining why promising therapies tested in animal models often fail when tested in humans. The surging complexity of patient management with the advent of cancer vaccines, immunotherapy, and precision medicine demands more robust and patient-specific tools to better inform our understanding and treatment of human cancer. Advances in stem cell biology, microfluidics, and cell culture have led to the development of sophisticated bioengineered microscale organotypic models (BMOMs) that could fill this gap. In this Perspective, we discuss the advantages and limitations of patient-specific BMOMs to improve our understanding of cancer and how these tools can help to confer insight into predicting patient response to therapy.

Patient-derived organoids as individual patient models for chemoradiation response prediction in gastrointestinal malignancies

Chemoradiotherapy (CRT) is an important treatment modality for specific gastrointestinal (GI) cancers, as it has been shown to improve clinical outcomes. Recent developments in the neoadjuvant setting such as wait-and-see strategies for rectal as well as for esophageal cancers have even proven that CRT might be an effective organ-sparing treatment. However, due to molecular heterogeneity, only a subset of patients will show a complete response to CRT, which addresses the need for an individualized treatment approach. In recent years, the demand for more physiologically relevant predictive in vitro models has fostered the development of patient-derived tumor organoids. In this review, we describe the current treatment options for patients with GI cancers who are treated with (neo)adjuvant CRT. Furthermore, we provide an in-depth discussion of the organoid technology in the context of predicting CRT response for GI cancers as well as possible challenges for clinical implementation.

Fatostatin in Combination with Tamoxifen Induces Synergistic Inhibition in ER-Positive Breast Cancer

Background

Tamoxifen is the cornerstone of adjuvant therapy for hormone receptor-positive breast cancer. Despite its efficacy, limited drug sensitivity and endocrine resistance remain the important clinical challenges. The main objective of this study was to investigate fatostatin, which was found to sensitize breast cancer to the antitumour effect of tamoxifen both in vitro and in vivo.

Methods

Fatostatin-induced ER degradation was detected by immunoprecipitation assay. The antitumour effect of fatostatin and tamoxifen on MCF-7 and T47D cells was assessed by MTT and colony forming assays. Cell cycle arrest was detected by flow cytometric analysis. Apoptosis was detected by annexin V/propidium iodide double staining and TUNEL assay. Autophagy was detected by MDC assay and acridine orange staining. Migration and invasion assays were performed using a Transwell system, and the efficacy of the synergistic use of fatostatin and tamoxifen in vivo was evaluated using an MCF-7 xenograft model in BALB/c nu/nu female mice.

Results

The synergistic use of fatostatin and tamoxifen significantly suppressed cell viability and invasion, induced cell cycle arrest, and regulated apoptosis and autophagy in MCF-7 and T47D cell lines via PI3K-AKT-mTOR signalling. Additionally, the expression levels of Atg7/12/13, beclin and LC3B increased while p-mTOR and P62 expression levels decreased after treatment with fatostatin and tamoxifen. Tumor growth in the xenograft model was suppressed significantly with the synergistic treatment of fatostatin and tamoxifen.

Conclusion

Fatostatin could induce ER degradation by K48-linked polyubiquitination, which was the key mechanism contributing to tamoxifen inhibition of PI3K-AKT-mTOR signalling in breast cancer. Fatostatin may have a promising clinical use for ER-positive breast cancer patients.

In Vitro Modeling of Non-Solid Tumors: How Far Can Tissue Engineering Go?

In hematological malignancies, leukemias or myelomas, malignant cells present bone marrow (BM) homing, in which the niche contributes to tumor development and drug resistance. BM architecture, cellular and molecular composition and interactions define differential microenvironments that govern cell fate under physiological and pathological conditions and serve as a reference for the native biological landscape to be replicated in engineered platforms attempting to reproduce blood cancer behavior. This review summarizes the different models used to efficiently reproduce certain aspects of BM in vitro; however, they still lack the complexity of this tissue, which is relevant for fundamental aspects such as drug resistance development in multiple myeloma. Extracellular matrix composition, material topography, vascularization, cellular composition or stemness vs. differentiation balance are discussed as variables that could be rationally defined in tissue engineering approaches for achieving more relevant in vitro models. Fully humanized platforms closely resembling natural interactions still remain challenging and the question of to what extent accurate tissue complexity reproduction is essential to reliably predict drug responses is controversial. However, the contributions of these approaches to the fundamental knowledge of non-solid tumor biology, its regulation by niches, and the advance of personalized medicine are unquestionable.

Bioprinting of in vitro tumor models for personalized cancer treatment: a review

Studying biological characteristics of tumors and evaluating the treatment effects require appropriate in vitro tumor models. However, the occurrence, progression, and migration of tumors involve spatiotemporal changes, cell-microenvironment and cell-cell interactions, and signal transmission in cells, which makes the construction of in vitro tumor models extremely challenging. In the past few years, advances in biomaterials and tissue engineering methods, especially development of the bioprinting technology, have paved the way for innovative platform technologies for in vitro cancer research. Bioprinting can accurately control the distribution of cells, active molecules, and biomaterials. Furthermore, this technology recapitulates the key characteristics of the tumor microenvironment and constructs in vitro tumor models with bionic structures and physiological systems. These models can be used as robust platforms to study tumor initiation, interaction with the microenvironment, angiogenesis, motility and invasion, as well as intra- and extravasation. Bioprinted tumor models can also be used for high-throughput drug screening and validation and provide the possibility for personalized cancer treatment research. This review describes the basic characteristics of the tumor and its microenvironment and focuses on the importance and relevance of bioprinting technology in the construction of tumor models. Research progress in the bioprinting of monocellular, multicellular, and personalized tumor models is discussed, and comprehensive application of bioprinting in preclinical drug screening and innovative therapy is reviewed. Finally, we offer our perspective on the shortcomings of the existing models and explore new technologies to outline the direction of future development and application prospects of next-generation tumor models.

Human Platelet Lysates-Based Hydrogels: A Novel Personalized 3D Platform for Spheroid Invasion Assessment

Fundamental physiologic and pathologic phenomena such as wound healing and cancer metastasis are typically associated with the migration of cells through adjacent extracellular matrix. In recent years, advances in biomimetic materials have supported the progress in 3D cell culture and provided biomedical tools for the development of models to study spheroid invasiveness. Despite this, the exceptional biochemical and biomechanical properties of human-derived materials are poorly explored. Human methacryloyl platelet lysates (PLMA)-based hydrogels are herein proposed as reliable 3D platforms to sustain in vivo-like cell invasion mechanisms. A systematic analysis of spheroid viability, size, and invasiveness is performed in three biomimetic materials: PLMA hydrogels at three different concentrations, poly(ethylene glycol) diacrylate, and Matrigel. Results demonstrate that PLMA hydrogels perfectly support the recapitulation of the tumor invasion behavior of cancer cell lines (MG-63, SaOS-2, and A549) and human bone-marrow mesenchymal stem cell spheroids. The distinct invasiveness ability of each cell type is reflected in the PLMA hydrogels and, furthermore, different mechanical properties produce an altered invasive behavior. The herein presented human PLMA-based hydrogels could represent an opportunity to develop accurate cell invasiveness models and open up new possibilities for humanized and personalized high-throughput screening and validation of anticancer drugs.

Modeling chemical effects on breast cancer: the importance of the microenvironment in vitro

Accumulating evidence suggests that our ability to predict chemical effects on breast cancer is limited by a lack of physiologically relevant in vitro models; the typical in vitro breast cancer model consists of the cancer cell and excludes the mammary microenvironment. As the effects of the microenvironment on cancer cell behavior becomes more understood, researchers have called for the integration of the microenvironment into in vitro chemical testing systems. However, given the complexity of the microenvironment and the variety of platforms to choose from, identifying the essential parameters to include in a chemical testing platform is challenging. This review discusses the need for more complex in vitro breast cancer models and outlines different approaches used to model breast cancer in vitro. We provide examples of the microenvironment modulating breast cancer cell responses to chemicals and discuss strategies to help pinpoint what components should be included in a model.

Hazard identification, classification, and risk assessment of carcinogens: too much or too little? - Report of an ECETOC workshop

The European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) organized a workshop "Hazard Identification, Classification and Risk Assessment of Carcinogens: Too Much or Too Little?" to explore the scientific limitations of the current binary carcinogenicity classification scheme that classifies substances as either carcinogenic or not. Classification is often based upon the rodent 2-year bioassay, which has scientific limitations and is not necessary to predict whether substances are likely human carcinogens. By contrast, tiered testing strategies founded on new approach methodologies (NAMs) followed by subchronic toxicity testing, as necessary, are useful to determine if a substance is likely carcinogenic, by which mode-of-action effects would occur and, for non-genotoxic carcinogens, the dose levels below which the key events leading to carcinogenicity are not affected. Importantly, the objective is not for NAMs to mimic high-dose effects recorded in vivo, as these are not relevant to human risk assessment. Carcinogenicity testing at the "maximum tolerated dose" does not reflect human exposure conditions, but causes major disturbances of homeostasis, which are very unlikely to occur at relevant human exposure levels. The evaluation of findings should consider biological relevance and not just statistical significance. Using this approach, safe exposures to non-genotoxic substances can be established.

Application of the adenosine triphosphate sensitivity assay in infantile vascular anomalies

Background

The term vascular anomalies include various vascular tumors and vascular malformations, among them infantile hemangiomas and capillary malformations are the most well-known associated diseases in early ages. Multiple drugs have been introduced for intervention, but susceptibility test in vitro were scarcely reported.

Objective

To evaluate the inhibition effect of different drugs by adenosine triphosphate sensitivity assay in vitro before the treatment of infantile hemangiomas and capillary malformations.

Methods

Specimens were selected from 5 cases of infantile hemangiomas and 11 cases of capillary malformations. Propranolol, rapamycin, sildenafil and itraconazole were tested for their growth inhibition effect by using the adenosine triphosphate sensitivity assay.

Results

Propranolol demonstrated inhibitory effects on infantile hemangiomas cells. Rapamycin and itraconazole both showed inhibitory effects on infantile hemangiomas cells and capillary malformations cells. Sildenafil has no growth inhibitory effect on infantile hemangiomas cells or capillary malformations cells.

Conclusion

Adenosine triphosphate sensitivity assay is a sensitive and useful testing method before the management of vascular anomalies, and individualized medication suggestions for the choice of therapeutic drugs were offered based on the testing result and together with a comprehensive evaluation of each infant.

Development of a Microfluidic Array to Study Drug Response in Breast Cancer

Luminal geometries are common structures in biology, which are challenging to mimic using conventional in vitro techniques based on the use of Petri dishes. In this context, microfluidic systems can mimic the lumen geometry, enabling a large variety of studies. However, most microfluidic models still rely on polydimethylsiloxane (PDMS), a material that is not amenable for high-throughput fabrication and presents some limitations compared with other materials such as polystyrene. Thus, we have developed a microfluidic device array to generate multiple bio-relevant luminal structures utilizing polystyrene and micro-milling. This platform offers a scalable alternative to conventional microfluidic devices designed in PDMS. Additionally, the use of polystyrene has well described advantages, such as lower permeability to hydrophobic molecules compared with PDMS, while maintaining excellent viability and optical properties. Breast cancer cells cultured in the devices exhibited high cell viability similar to PDMS-based microdevices. Further, co-culture experiments with different breast cell types showed the potential of the model to study breast cancer invasion. Finally, we demonstrated the potential of the microfluidic array for drug screening, testing chemotherapy drugs and photodynamic therapy agents for breast cancer.

A Three-Dimensional In Vitro Coculture Model to Quantify Breast Epithelial Cell Adhesion to Endothelial Cells

Three-dimensional (3D) in vitro culture models better recapitulate the tissue microenvironment, and therefore may provide a better platform to evaluate therapeutic effects on adhesive cell-cell interactions. The objective of this study was to determine if AD-01, a peptide derivative of FK506-binding protein like that is reported to bind to the adhesion receptor CD44, would induce a greater reduction in breast epithelial spheroid adhesion to endothelial tube-like networks in our 3D coculture model system compared to two-dimensional (2D) culture. MCF10A, MCF10A-NeuN, MDA-MB-231, and MCF7 breast epithelial cells were pretreated with AD-01 either as single cells or as spheroids. Breast epithelial cell adhesion to 2D tissue culture substrates was first measured, followed by spheroid formation (breast cell-cell adhesion) and spheroid adhesion to Matrigel or endothelial networks. Finally, CD44 expression was quantified in breast epithelial cells in 2D and 3D culture. Our results show that AD-01 had the largest effect on spheroid formation, specifically in breast cancer cell lines. AD-01 also inhibited breast cancer spheroid adhesion to and migration along endothelial networks. The different breast epithelial cell lines expressed more CD44 when cultured as 3D spheroids, but this did not universally translate into higher protein levels. This study shows that 3D coculture models can enable unique insights into cell adhesion, migration, and cell-cell interactions, thereby enhancing understanding of basic biological mechanisms. Furthermore, such 3D coculture systems may also represent a more relevant testing platform for understanding the mechanism-of-action of new therapeutic agents. Impact Statement Cell adhesion is inherently different in two dimensional (2D) compared to three dimensional (3D) culture; yet, most adhesion assays in academia and industry are still conducted in 2D because few simple, yet effective, adhesion models exist in 3D. Recently we developed a 3D in vitro coculture model to examine breast epithelial spheroid interactions with endothelial tubes. We now show that this 3D coculture model can effectively be used to interrogate and quantify drug-induced differences in breast epithelial cell adhesion that are unique to 3D cocultures. This 3D coculture adhesion model can furthermore be modified for use with other cell types to better predict drug effects on cell-vasculature adhesion.

An Integrated Microfluidics Approach for Personalized Cancer Drug Sensitivity and Resistance Assay

Cancer is the second leading cause of death globally. Matching proper treatment and dosage is crucial for a positive outcome. Any given drug may affect patients with similar tumors differently. Personalized medicine aims to address this issue. Unfortunately, most cancer samples cannot be expanded in culture, limiting conventional cell-based testing. Herein, presented is a microfluidic device that combines a drug microarray with cell microscopy. The device can perform 512 experiments to test chemosensitivity and resistance to a drug array. MCF7 and 293T cells are cultured inside the device and their chemosensitivity and resistance to docetaxel, applied at various concentrations, are determined. Cell mortality is determined as a function of drug concentration and exposure time. It is found that both cell types form cluster morphology within the device, not evident in conventional tissue culture under similar conditions. Cells inside the clusters are less sensitive to drugs than dispersed cells. These findings support a heterogenous response of cancer cells to drugs. Then demonstrated is the principle of drug microarrays by testing cell response to four different drugs at four different concentrations. This approach may enable the personalization of treatment to the particular tumor and patient and may eventually improve final patient outcome.

Mammary adipose stromal cells derived from obese women reduce sensitivity to the aromatase inhibitor anastrazole in an organotypic breast model

Aromatase inhibitors are the preferred treatment for certain women with estrogen receptor (ER)-positive breast cancer, but evidence suggests that women with obesity experience aromatase inhibitor resistance at higher rates. To compare how stromal cells derived from women who are lean or obese influence response to the aromatase inhibitor (anastrazole), we incorporated patient-derived stroma in a previously characterized MCF7-derived in vitro duct model. Coculture with adipose stromal cells enabled the metabolism of testosterone (T) to E₂, which induced estrogen response element activity, epithelial proliferation, and hyperplasia in MCF7 cells. The effects of T were inhibited by the ER antagonist tamoxifen and aromatase inhibitor anastrazole and were increased by the aromatase inducer dexamethasone. Primary mammary adipose stromal cells derived from women with obesity displayed increased aromatase mRNA compared with lean controls. MCF7-derived ducts cocultured with obese stromal cells exhibited higher maximal aromatization-induced ER transactivation and reduced anastrazole sensitivity, a difference not seen in 2-dimensional coculture. Finally, tamoxifen was more effective than anastrazole at reducing aromatization-induced ER transactivation and proliferation. These findings suggest that patient-specific responses to hormone therapies can be modeled and studied organotypically in vitro and add to evidence advocating obesity as a parameter to consider when identifying treatments for patients with ER-positive breast cancer.-Morgan, M. M., Arendt, L. M., Alarid, E. T., Beebe, D. J., Johnson, B. P. Mammary adipose stromal cells derived from obese women reduce sensitivity to the aromatase inhibitor anastrazole in an organotypic breast model.

Paraffin-embedding lithography and micro-dissected tissue micro-arrays: tools for biological and pharmacological analysis of ex vivo solid tumors

There is an urgent need and strong clinical and pharmaceutical interest in developing assays that allow for the direct testing of therapeutic agents on primary tissues. Current technologies fail to provide the required sample longevity, throughput, and integration with standard clinically proven assays to make the approach viable. Here we report a microfluidic micro-histological platform that enables ex vivo culture of a large array of prostate and ovarian cancer micro-dissected tissue (MDT) followed by direct on-chip fixation and paraffination, a process we term paraffin-embedding lithography (PEL). The result is a high density MDT-Micro Array (MDTMA) compatible with standard clinical histopathology that can be used to analyse ex vivo tumor response or resistance to therapeutic agents. The cellular morphology and tissue architecture are preserved in MDTs throughout the 15 day culture period. We also demonstrate how this methodology can be used to study molecular pathways involved in cancer by performing in-depth characterization of biological and pharmacological mechanisms such as p65 nuclear translocation via TNF stimuli, and to predict the treatment outcome in the clinic via MDT response to taxane-based therapies.

Genomic evolution of cancer models: perils and opportunities

Cancer research relies on model systems, which reflect the biology of actual human tumours to only a certain extent. One important feature of human cancer is its intra-tumour genomic heterogeneity and instability. However, the extent of such genomic instability in cancer models has received limited attention in research. Here, we review the state of knowledge of genomic instability of cancer models and discuss its biological origins and implications for basic research and for cancer precision medicine. We discuss strategies to cope with such genomic evolution and evaluate both the perils and the emerging opportunities associated with it.

Induced cross-resistance of BRAFV600E melanoma cells to standard chemotherapeutic dacarbazine after chronic PLX4032 treatment

The maximum response and 10-year survival rate for metastatic melanoma patients treated with standardised chemotherapy is still less than 15% and 10%, respectively. In contrast, oncogene targeting was found a promising tool for killing of BRAF^V600 mutated melanoma cells. Nevertheless, despite improved response and survival rates, resistance acquisition remains an ongoing problem. In this context, the impact of chronic BRAF inhibition on the efficacy of commonly applied cytostatics is still unknown. In our study, human melanoma cells with BRAF^V600E mutation were treated with chemotherapeutics and a BRAF inhibitor. Resistance patterns were analysed by microelectrode array-based impedance spectroscopy, XTT and flow cytometric apoptosis/proliferation assay. BRAF^V600E melanoma cells acquired a time- and concentration-dependent desensitisation up to 100-fold towards oncogene-specific PLX4032 and chemotherapeutic dacarbazine after twelve months treatment. The impact of multiple drug insensitivity on molecular melanoma characteristics was elaborated via mRNA and protein quantification. Following BRAF^V600E targeting, melanoma cells developed an increasingly aggressive, dacarbazine-insensitive phenotype. Thereby, hyperactivated canonical alternative MAPK and bypass PI3K/AKT signalling caused cross-resistance of differently acting drugs. With these results, we are the first to show that long-term melanoma therapy with BRAF inhibitors can prevent further therapeutic success with dacarbazine due to acquisition of cross-resistance.

Evaluation of PEG-based hydrogel influence on estrogen receptor driven responses in MCF7 breast cancer cells

Extracellular matrix (ECM) mimicking hydrogel scaffolds have greatly improved the physiological relevance of in vitro assays, but introduce another dimension that creates variability in cell related readouts when compared to traditional 2D cells-on-plastic assays. We have developed a synthetic poly(ethylene glycol) (PEG) based ECM mimicking hydrogel and tested it against two gold standard animal-based naturally derived hydrogel scaffolds in MCF7 cell response. We have used the percent coefficient of variation (CV) as a metric to evaluate the reproducibility of said responses. Results indicated that PEG hydrogels performed similarly to naturally derived gold standards, and variance was similar in basic characterization assays, such as viability and cell adherence. PEG based hydrogels had lower CV values in estrogen receptor driven responses to several doses of estrogen in both estrogen receptor transactivation and estrogen induced proliferation.

The Adverse Outcome Pathway: A Multifaceted Framework Supporting 21st Century Toxicology

The adverse outcome pathway (AOP) framework serves as a knowledge assembly, interpretation, and communication tool designed to support the translation of pathway-specific mechanistic data into responses relevant to assessing and managing risks of chemicals to human health and the environment. As such, AOPs facilitate the use of data streams often not employed by risk assessors, including information from in silico models, in vitro assays and short-term in vivo tests with molecular/biochemical endpoints. This translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures. Our mini-review describes the conceptual basis of the AOP framework and aspects of its current status relative to use by toxicologists and risk assessors, including four illustrative applications of the framework to diverse assessment scenarios.

Engineering Breast Cancer Microenvironments and 3D Bioprinting

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal-cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments.

Mammary fibroblasts reduce apoptosis and speed estrogen-induced hyperplasia in an organotypic MCF7-derived duct model

The estrogen receptor (ER) regulates the survival and growth of breast cancer cells, but it is less clear how components of the tissue microenvironment affect ER-mediated responses. We set out to test how human mammary fibroblasts (HMFs) modulate ER signaling and downstream cellular responses. We exposed an organotypic mammary model consisting of a collagen-embedded duct structure lined with MCF7 cells to 17-β estradiol (E2), with and without HMFs in the surrounding matrix. MCF7 cells grown as ductal structures were polarized and proliferated at rates comparable to in vivo breast tissue. In both culture platforms, exposure to E2 increased ER transactivation, increased proliferation, and induced ductal hyperplasia. When the surrounding matrix contained HMFs, the onset and severity of E2-induced ductal hyperplasia was increased due to decreased apoptosis. The reduced apoptosis may be due to fibroblasts modulating ER signaling in MCF7 cells, as suggested by the increased ER transactivation and reduced ER protein in MCF7 cells grown in co-culture. These findings demonstrate the utility of organotypic platforms when studying stromal:epithelial interactions, and add to existing literature that implicate the mammary microenvironment in ER + breast cancer progression.

The Current Landscape of 3D In Vitro Tumor Models: What Cancer Hallmarks Are Accessible for Drug Discovery?

Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery.

Integrating Population Heterogeneity Indices with Microfluidic Cell-Based Assays

Recent advances in cell-based assays have involved the integration of single-cell analyses and microfluidics technology to facilitate both high-content and high-throughput applications. These technical advances have yielded large datasets with single-cell resolution, and have given rise to the study of cell population dynamics, but statistical analyses of these populations and their properties have received much less attention, particularly for cells cultured in microfluidic systems. The objective of this study was to perform statistical analyses using Pittsburgh Heterogeneity Indices (PHIs) to understand the heterogeneity and evolution of cell population demographics on datasets generated from a microfluidic single-cell-resolution cell-based assay. We applied PHIs to cell population data obtained from studies involving drug response and soluble factor signaling of multiple myeloma cancer cells, and investigated effects of reducing population size in the microfluidic assay on both the PHIs and traditional population-averaged readouts. Results showed that PHIs are useful for examining changing population distributions within a microfluidic setting. Furthermore, PHIs provided data in support of finding the minimum population size for a microfluidic assay without altering the heterogeneity indices of the cell population. This work will be useful for novel assay development, and for advancing the integration of microfluidics, cell-based assays, and heterogeneity analyses.

Multiple Myeloma Cell Drug Responses Differ in Thermoplastic vs PDMS Microfluidic Devices

Poly(dimethylsiloxane) (PDMS) is a commonly used elastomer for fabricating microfluidic devices, but it has previously been shown to absorb hydrophobic molecules. Although this has been demonstrated for molecules such as estrogen and Nile Red, the absorption of small hydrophobic molecules in PDMS specifically used to treat cancer and its subsequent impact on cytotoxicity measurements and assays have not been investigated. This is critical for the development of microfluidic chemosensitivity and resistance assay (CSRA) platforms that have shown potential to help guide clinical therapy selection and which rely on the accuracy of the readout involving interactions between patient-derived cells and cancer drugs. It is thus important to address the issue of drug absorption into device material. We investigated drug absorption into microfluidic devices by treating multiple myeloma (MM) tumor cells with two MM drugs (bortezomib (BTZ) and carfilzomib (CFZ)) in devices fabricated using three different materials (polystyrene (PS), cyclo-olefin polymer (COP), and PDMS). Half-maximal inhibitory concentrations (IC₅₀) were obtained for each drug-material combination, and an increase in IC₅₀ of ∼4.3× was observed in PDMS devices compared to both thermoplastic devices. Additionally, each MM drug was exposed to polymer samples, and samples were analyzed using time-of-flight secondary ion mass spectrometry (ToF-SIMS) to characterize adsorption and absorption of the drugs into each material. ToF-SIMS data showed the bias observed in IC₅₀ values found in PDMS devices was directly related to the absorption of drug during dose-response experiments. Specifically, BTZ and CFZ absorption in both PS and COP were all in the range of ∼100-300 nm, whereas BTZ and CFZ absorption in PDMS was ∼5.0 and ∼3.5 μm, respectively. These results highlight the biases that exist in PDMS devices and the importance of material selection in microfluidic device design, especially in applications involving drug cytotoxicity and hydrophobic molecules.

Reconfigurable Microfluidic Magnetic Valve Arrays: Towards a Radiotherapy-Compatible Spheroid Culture Platform for the Combinatorial Screening of Cancer Therapies

We introduce here a microfluidic cell culture platform or spheroid culture chamber array (SCCA) that can synthesize, culture, and enable fluorescence imaging of 3D cell aggregates (typically spheroids) directly on-chip while specifying the flow of reagents in each chamber via the use of an array of passive magnetic valves. The SCCA valves demonstrated sufficient resistance to burst (above 100 mBar), including after receiving radiotherapy (RT) doses of up to 8 Gy combined with standard 37 °C incubation for up to 7 days, enabling the simultaneous synthesis of multiple spheroids from different cell lines on the same array. Our results suggest that SCCA would be an asset in drug discovery processes, seeking to identify combinatorial treatments.

Ex vivo evaluation of tumor cell specific drug responses in malignant pleural effusions

The effect of chemotherapy may be improved by combining the most effective drugs based on testing the sensitivity of the individual tumor ex vivo. Such estimations of tumor cells from effusions have so far not been implemented in the clinical routine as a basis for individualized choice of therapy. One obstacle for such analyses is the admixture of benign cells that might obscure the results. In this paper we test and compare two ways of performing the analysis specifically on tumor cells. First we enrich the tumor cells, using antibody labeled magnetic separation, and measure the effects of subsequent drug exposure with the metabolic activity assays WST-1 and alamar blue. The second way of estimating drug effects specifically on tumor cells employs multi parameter flow cytometry, measuring apoptosis with the propidium iodide / AnnexinV technique and, particularly for pemetrexed, possible effects on cell cycle progression in immunologically identified tumor cells. The two techniques produce similar results, indicating a possible use in personalized medicine. The possible predictive role of the analysis remains to be shown.

3D Cell Printed Tissue Analogues: A New Platform for Theranostics

Stem cell theranostics has received much attention for noninvasively monitoring and tracing transplanted therapeutic stem cells through imaging agents and imaging modalities. Despite the excellent regenerative capability of stem cells, their efficacy has been limited due to low cellular retention, low survival rate, and low engraftment after implantation. Three-dimensional (3D) cell printing provides stem cells with the similar architecture and microenvironment of the native tissue and facilitates the generation of a 3D tissue-like construct that exhibits remarkable regenerative capacity and functionality as well as enhanced cell viability. Thus, 3D cell printing can overcome the current concerns of stem cell therapy by delivering the 3D construct to the damaged site. Despite the advantages of 3D cell printing, the in vivo and in vitro tracking and monitoring of the performance of 3D cell printed tissue in a noninvasive and real-time manner have not been thoroughly studied. In this review, we explore the recent progress in 3D cell technology and its applications. Finally, we investigate their potential limitations and suggest future perspectives on 3D cell printing and stem cell theranostics.

Bringing 3D tumor models to the clinic - predictive value for personalized medicine

Current decision-guiding algorithms in cancer drug treatment are based on decades of research and numerous clinical trials. For the majority of patients, this data is successfully applied for a systemic disease management. For a number of patients however, treatment stratification according to clinically based risk criteria will not be sufficient. The most effective treatment options are ideally identified prior to the start of clinical drug therapy. This review will discuss the implementation of three-dimensional (3D) cell culture models as a preclinical testing paradigm for the efficacy of clinical cancer treatment. Patient tumor-derived cells in 3D cultures duplicate the individual tumor microenvironment with a minimum of confounding factors. Clinical implementation of such personalized tumor models requires a high quality of methodological and clinical validation comparable to other biomarkers. A non-systematic literature search demonstrated the small number of prospective studies that have been conducted in this area of research. This may explain the current reluctance of many physicians and insurance providers in implementing this type of assay into the clinical diagnostic routine despite potential benefit for patients. Achieving valid and reproducible results with a high level of evidence is central in improving the acceptance of preclinical 3D tumor models.