In Vitro and Ex Vivo Models - The Tumor Microenvironment in a Flask.

Experimental tumor modeling has long supported the discovery of fundamental mechanisms of tumorigenesis and tumor progression, as well as provided platforms for the development of novel therapies. Still, the attrition rates observed today in clinical translation could be, in part, mitigated by more accurate recapitulation of environmental cues in research and preclinical models. The increasing understanding of the decisive role that tumor microenvironmental cues play in the outcome of drug response urges its integration in preclinical tumor models. In this chapter we review recent developments concerning in vitro and ex vivo approaches.

Polymethoxylated Flavones from Orange Peels Inhibit Cell Proliferation in a 3D Cell Model of Human Colorectal Cancer.

Polymethoxylated flavones (PMFs) have been recognized to inhibit colorectal cancer proliferation through various mechanisms, however most of these studies have been performed on cells grown as monolayers that present limitations in mimicking the 3D tumor architecture and microenvironment. The main aim of this study was to investigate the anticancer potential of an orange peel extract (OPE) enriched in PMFs in a 3D cell model of colorectal cancer. The OPE was developed by supercritical fluid extraction and the anticancer effect was evaluated in HT29 spheroids cultures in a stirred-tank based system. Results showed that OPE inhibited cell proliferation, induced cell cycle arrest (G2/M phase), promoted apoptosis, and reduced ALDH+ population on HT29 spheroids. The antiproliferative activity was significantly lower than that obtained for 2D model (EC50 value of 0.43 ± 0.02 mg/mL) and this effect was dependent on diameter and cell composition/phenotype of spheroids derived from different culture days (day 3 - 0.53 ± 0.05 mg/mL; day 5 - 0.55 ± 0.03 mg/mL; day 7 - 1.24 ± 0.15 mg/mL). HT29 spheroids collected at day 7 presented typical characteristics of in vivo solid tumors including a necrotic/apoptotic core, hypoxia regions, presence of cancer stem cells, and a less differentiated invasive front. Nobiletin, sinesentin, and tangeretin were identified as the main compounds responsible for the anticancer activity.

Zebrafish Avatars: Toward Functional Precision Medicine in Low-Grade Serous Ovarian Cancer.

Ovarian cancer (OC) is an umbrella term for cancerous malignancies affecting the ovaries, yet treatment options for all subtypes are predominantly derived from high-grade serous ovarian cancer, the largest subgroup. The concept of "functional precision medicine" involves gaining personalized insights on therapy choice, based on direct exposure of patient tissues to drugs. This especially holds promise for rare subtypes like low-grade serous ovarian cancer (LGSOC). This study aims to establish an in vivo model for LGSOC using zebrafish embryos, comparing treatment responses previously observed in mouse PDX models, cell lines and 3D tumor models. To address this goal, a well-characterized patient-derived LGSOC cell line with the KRAS mutation c.35 G>T (p.(Gly12Val)) was used. Fluorescently labeled tumor cells were injected into the perivitelline space of 2 days' post-fertilization zebrafish embryos. At 1 day post-injection, xenografts were assessed for tumor size, followed by random allocation into treatment groups with trametinib, luminespib and trametinib + luminespib. Subsequently, xenografts were euthanized and analyzed for apoptosis and proliferation by confocal microscopy. Tumor cells formed compact tumor masses (n = 84) in vivo, with clear Ki67 staining, indicating proliferation. Zebrafish xenografts exhibited sensitivity to trametinib and luminespib, individually or combined, within a two-week period, establishing them as a rapid and complementary tool to existing in vitro and in vivo models for evaluating targeted therapies in LGSOC.

Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer.

Cancer patients often undergo rounds of trial-and-error to find the most effective treatment because there is no test in the clinical practice for predicting therapy response. Here, we conduct a clinical study to validate the zebrafish patient-derived xenograft model (zAvatar) as a fast predictive platform for personalized treatment in colorectal cancer. zAvatars are generated with patient tumor cells, treated exactly with the same therapy as their corresponding patient and analyzed at single-cell resolution. By individually comparing the clinical responses of 55 patients with their zAvatar-test, we develop a decision tree model integrating tumor stage, zAvatar-apoptosis, and zAvatar-metastatic potential. This model accurately forecasts patient progression with 91% accuracy. Importantly, patients with a sensitive zAvatar-test exhibit longer progression-free survival compared to those with a resistant test. We propose the zAvatar-test as a rapid approach to guide clinical decisions, optimizing treatment options and improving the survival of cancer patients.

Relapsed Ovarian Cancer Patients with Ascites and/or Pleural Effusion Still Benefit from Treatment: A Real-Life Study.

(1) Background: Relapsed HGSOC with ascites and/or pleural effusion is a poor-prognostic population and poorly represented in clinical studies. We questioned if these patients are worth treating. In other words, if these patients received the most effective treatment, would it change the course of this disease? To our knowledge this is the first real-life study to evaluate this question in this low-survival population. (2) Methods: To tackle this question we performed a retrospective, multi-centric, real-life study, that reviewed relapsed HGSOC patients with ascites and/or pleural effusion. Our rationale was to compare the OS of two groups of patients: responders, i.e., patients who had an imagological response to treatment (complete/partial response/stable disease, RECIST criteria) versus non-responders (no response/progression upon treatment). We evaluated the predictive value of clinical variables that are available in a real-life setting (e.g., staging, chemotherapy, surgery, platinum-sensitivity). Multivariate logistic regression and survival analysis was conducted. A two-step cluster analysis SPSS tool was used for subgroup analysis. Platinum sensitivity/resistance was also analyzed, as well as multivariate and cluster analysis. (3) Results: We included 57 patients, 41.4% first line responders and 59.6% non-responders. The median OS of responders was 23 months versus 8 months in non-responders (p < 0.001). This difference was verified in platinum-sensitive (mOS 28 months vs. 8 months, p < 0.001) and platinum-resistant populations (mOS 16 months vs. 7 months, p < 0.001). Thirty-one patients reached the second line, of which only 10.3% responded to treatment. Three patients out of thirty-one who did not respond in the first line of relapse, responded in the second line. In the second line, the mOS for the responders' group vs. non-responders was 31 months versus 13 months (p = 0.02). The two step cluster analysis tool found two different subgroups with different prognoses based on overall response rate, according to consolidation chemotherapy, neoadjuvant chemotherapy, FIGO staging and surgical treatment. Cluster analysis showed that even patients with standard clinical and treatment variables associated with poor prognosis might achieve treatment response (the opposite being also true). (4) Conclusions: Our data clearly show that relapsed HGSOC patients benefit from treatment. If given an effective treatment upfront, this can lead to a ~3 times increase in mOS for these patients. Moreover, this was irrespective of patient disease and treatment characteristics. Our results highlight the urgent need for a sensitivity test to tailor treatments and improve efficacy rates in a personalized manner.

Zebrafish Patient-Derived Avatars from Digestive Cancers for Anti-cancer Therapy Screening.

Patient-derived xenografts (PDXs), also called "avatars," are generated by the implantation of human primary tumor cells or tissues into a host animal. Given the complexity and unique characteristics of each tumor, PDXs are models of choice in cancer research and precision medicine. In this context, the zebrafish PDX model (zPDX or zAvatar) has been recognized as a promising in vivo model to directly challenge patient cells with anti-cancer therapies in a personalized manner. The assay relies on the injection of tumor cells from patients into zebrafish embryos to then test and identify the best available drug combination for a particular patient. Compared to mouse PDXs, zAvatar assays take less time and do not require in vitro or in vivo cell expansion. The present article describes how to generate zAvatars from resected digestive cancer from surgeries and how to then use them for anti-cancer therapy screening. We describe the steps for tumor sample collection and cryopreservation, sample preparation and fluorescent labeling for microinjection into zebrafish embryos, drug administration, and analysis of tumor behavior by single-cell confocal imaging. We provide detailed protocols and helpful tips for performing this assay, and we address the technical challenges associated with the workflow. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Patient tumor sample collection and cryopreservation Basic Protocol 2: Generation of zAvatars and anti-cancer treatment Basic Protocol 3: Whole-mount immunofluorescence Basic Protocol 4: Confocal imaging and analysis.

Patient-Derived Breast Cancer Tissue Cultures for Anti-Endocrine Drug Assays.

Breast cancer is a complex and heterogeneous pathology, characterized by a variety of histological and molecular phenotypes. The majority of the breast cancers express the estrogen receptor alpha (ER), which plays a pivotal role in the pathobiology of the disease and are therefore classified as ER-positive (ER+). In fact, targeting of the ER signaling pathway is the main therapeutic strategy for ER+ breast cancer. Despite the success of endocrine therapy, intrinsic and acquired resistance are reported in 30-50% of the ER+ breast cancers. However, the mechanisms underlying ER heterogeneity and therapeutic resistance are far from being fully disclosed, and efficacious clinical strategies to overcome resistance are still pending. One of the hurdles in studying ER+ breast cancer resistance is related with the scarcity of experimental models that can recapitulate ER heterogeneity and signaling. This is the case of ER+ breast cancer cell models, typically based on cells derived from metastasis, which also fail to recapitulate tumor complexity. Primary cultures of patient-derived breast cancer cells are difficult to establish, and generally characterized by stromal fibroblasts overgrowth and rapid loss of phenotypic and molecular traits of the tumor cells, including ER expression. Ex vivo cultures of breast cancer tissue have been reported to retain the tissue architecture, with preservation of the tumor microenvironment (TME) and ER expression for short periods of time.Given the cumulating evidence on the role of the TME in sustaining ER+ tumor cells, we hypothesized that TME preservation in culture would favor the long-term retention of ER expression and signaling. We employed alginate encapsulation to provide a supporting scaffold to breast cancer tissue microstructures, coupled to dynamic culture to improve the lifespan of the culture by avoiding diffusional limitations. In this chapter, we provide a detailed description of this culture methodology, which has been previously published by our group (Cartaxo et al., J Exp Clin Cancer Res 39:161, 2020), based on electrostatically driven breast cancer tissue encapsulation in alginate, coupled to culture under agitation in a defined culture medium. We also describe challenge of the ex vivo model with an ER activator and inhibitors (anti-endocrine drugs) and a gene expression endpoint of drug response using reverse transcription PCR-based analysis of three distinct genes downstream of ER.

Zebrafish Avatars towards Personalized Medicine-A Comparative Review between Avatar Models.

Cancer frequency and prevalence have been increasing in the past decades, with devastating impacts on patients and their families. Despite the great advances in targeted approaches, there is still a lack of methods to predict individual patient responses, and therefore treatments are tailored according to average response rates. "Omics" approaches are used for patient stratification and choice of therapeutic options towards a more precise medicine. These methods, however, do not consider all genetic and non-genetic dynamic interactions that occur upon drug treatment. Therefore, the need to directly challenge patient cells in a personalized manner remains. The present review addresses the state of the art of patient-derived invitro and invivo models, from organoids to mouse and zebrafish Avatars. The predictive power of each model based on the retrospective correlation with the patient clinical outcome will be considered. Finally, the review is focused on the emerging zebrafish Avatars and their unique characteristics allowing a fast analysis of local and systemic effects of drug treatments at the single-cell level. We also address the technical challenges that the field has yet to overcome.

A novel culture method that sustains ERα signaling in human breast cancer tissue microstructures.

BACKGROUND: Estrogen receptor α (ERα) signaling is a defining and driving event in most breast cancers; ERα is detected in malignant epithelial cells of 75% of all breast cancers (classified as ER-positive breast cancer) and, in these cases, ERα targeting is the main therapeutic strategy. However, the biological determinants of ERα heterogeneity and the mechanisms underlying therapeutic resistance are still elusive, hampered by the challenges in developing experimental models recapitulative of intra-tumoral heterogeneity and in which ERα signaling is sustained. Ex vivo cultures of human breast cancer tissue have been proposed to retain the original tissue architecture, epithelial and stromal cell components and ERα. However, loss of cellularity, viability and ERα expression are well-known culture-related phenomena. METHODS: BC samples were collected and brought to the laboratory. Then they were minced, enzymatically digested, entrapped in alginate and cultured for 1 month. The histological architecture, cellular composition and cell proliferation of tissue microstructures were assessed by immunohistochemistry. Cell viability was assessed by measurement of cell metabolic activity and histological evaluation. The presence of ERα was accessed by immunohistochemistry and RT-qPCR and its functionality evaluated by challenge with 17-ß-estradiol and fulvestrant. RESULTS: We describe a strategy based on entrapment of breast cancer tissue microstructures in alginate capsules and their long-term culture under agitation, successfully applied to tissue obtained from 63 breast cancer patients. After 1 month in culture, the architectural features of the encapsulated tissue microstructures were similar to the original patient tumors: epithelial, stromal and endothelial compartments were maintained, with an average of 97% of cell viability compared to day 0. In ERα-positive cases, fibers of collagen, the main extracellular matrix component in vivo, were preserved. ERα expression was at least partially retained at gene and protein levels and response to ERα stimulation and inhibition was observed at the level of downstream targets, demonstrating active ER signaling. CONCLUSIONS: The proposed model system is a new methodology to study ex vivo breast cancer biology, in particular ERα signaling. It is suitable for interrogating the long-term effects of anti-endocrine drugs in a set-up that closely resembles the original tumor microenvironment, with potential application in pre- and co-clinical assays of ERα-positive breast cancer.

PREDECT Protocols for Complex 2D/3D Cultures.

PREDECT, a European IMI consortium, has assumed the task to generate robust 2D and 3D culture platforms. Protocols established for 2D and 3D monoculture and stromal coculture models of increasing complexity (spheroid, stirred-tank bioreactor, Matrigel- and collagen-embedded cultures) have been established between six laboratories within academia, biotech, and pharma. These models were tested using three tumor cell lines (MCF7, LNCaP, and NCI-H1437), covering three pathologies (breast, prostate, and lung), but should be readily transferable to other model systems. Fluorescent protein tagged cell lines were used for all platforms, allowing for online measurement of growth curves and drug responses to treatments. All methods, from culture setup to phenotypic characterization and gene expression profiling are described in this chapter.The adaptable methodologies and detailed protocols described here should help to include these models more readily to the drug discovery pipeline.

3D-3-culture: A tool to unveil macrophage plasticity in the tumour microenvironment.

The tumour microenvironment (TME) shapes disease progression and influences therapeutic response. Most aggressive solid tumours have high levels of myeloid cell infiltration, namely tumour associated macrophages (TAM). Recapitulation of the interaction between the different cellular players of the TME, along with the extracellular matrix (ECM), is critical for understanding the mechanisms underlying disease progression. This particularly holds true for prediction of therapeutic response(s) to standard therapies and interrogation of efficacy of TME-targeting agents. In this work, we explored a culture platform based on alginate microencapsulation and stirred culture systems to develop the 3D-3-culture, which entails the co-culture of tumour cell spheroids of non-small cell lung carcinoma (NSCLC), cancer associated fibroblasts (CAF) and monocytes. We demonstrate that the 3D-3-culture recreates an invasive and immunosuppressive TME, with accumulation of cytokines/chemokines (IL4, IL10, IL13, CCL22, CCL24, CXCL1), ECM elements (collagen type I, IV and fibronectin) and matrix metalloproteinases (MMP1/9), supporting cell migration and promoting cell-cell interactions within the alginate microcapsules. Importantly, we show that both the monocytic cell line THP-1 and peripheral blood-derived monocytes infiltrate the tumour tissue and transpolarize into an M2-like macrophage phenotype expressing CD68, CD163 and CD206, resembling the TAM phenotype in NSCLC. The 3D-3-culture was challenged with chemo- and immunotherapeutic agents and the response to therapy was assessed in each cellular component. Specifically, the macrophage phenotype was modulated upon treatment with the CSF1R inhibitor BLZ945, resulting in a decrease of the M2-like macrophages. In conclusion, the crosstalk between the ECM and tumour, stromal and immune cells in microencapsulated 3D-3-culture promotes the activation of monocytes into TAM, mimicking aggressive tumour stages. The 3D-3-culture constitutes a novel tool to study tumour-immune interaction and macrophage plasticity in response to external stimuli, such as chemotherapeutic and immunomodulatory drugs.

Drug screening in 3D in vitro tumor models: overcoming current pitfalls of efficacy read-outs.

There is cumulating evidence that in vitro 3D tumor models with increased physiological relevance can improve the predictive value of pre-clinical research and ultimately contribute to achieve decisions earlier during the development of cancer-targeted therapies. Due to the role of tumor microenvironment in the response of tumor cells to therapeutics, the incorporation of different elements of the tumor niche on cell model design is expected to contribute to the establishment of more predictive in vitro tumor models. This review is focused on the several challenges and adjustments that the field of oncology research is facing to translate these advanced tumor cells models to drug discovery, taking advantage of the progress on culture technologies, imaging platforms, high throughput and automated systems. The choice of 3D cell model, the experimental design, choice of read-outs and interpretation of data obtained from 3D cell models are critical aspects when considering their implementation in drug discovery. In this review, we foresee some of these aspects and depict the potential directions of pre-clinical oncology drug discovery towards improved prediction of drug efficacy.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project.

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.

Modelling the tumour microenvironment in long-term microencapsulated 3D co-cultures recapitulates phenotypic features of disease progression.

3D cell tumour models are generated mainly in non-scalable culture systems, using bioactive scaffolds. Many of these models fail to reflect the complex tumour microenvironment and do not allow long-term monitoring of tumour progression. To overcome these limitations, we have combined alginate microencapsulation with agitation-based culture systems, to recapitulate and monitor key aspects of the tumour microenvironment and disease progression. Aggregates of MCF-7 breast cancer cells were microencapsulated in alginate, either alone or in combination with human fibroblasts, then cultured for 15 days. In co-cultures, the fibroblasts arranged themselves around the tumour aggregates creating distinct epithelial and stromal compartments. The presence of fibroblasts resulted in secretion of pro-inflammatory cytokines and deposition of collagen in the stromal compartment. Tumour cells established cell-cell contacts and polarised around small lumina in the interior of the aggregates. Over the culture period, there was a reduction in oestrogen receptor and membranous E-cadherin alongside loss of cell polarity, increased collective cell migration and enhanced angiogenic potential in co-cultures. These phenotypic alterations, typical of advanced stages of cancer, were not observed in the mono-cultures of MCF-7 cells. The proposed model system constitutes a new tool to study tumour-stroma crosstalk, disease progression and drug resistance mechanisms.

Adaptable stirred-tank culture strategies for large scale production of multicellular spheroid-based tumor cell models.

Currently there is an effort toward the development of in vitro cancer models more predictive of clinical efficacy. The onset of advanced analytical tools and imaging technologies has increased the utilization of spheroids in the implementation of high throughput approaches in drug discovery. Agitation-based culture systems are commonly proposed as an alternative method for the production of tumor spheroids, despite the scarce experimental evidence found in the literature. In this study, we demonstrate the robustness and reliability of stirred-tank cultures for the scalable generation of 3D cancer models. We developed standardized protocols to a panel of tumor cell lines from different pathologies and attained efficient tumor cell aggregation by tuning hydrodynamic parameters. Large numbers of spheroids were obtained (typically 1000-1500 spheroids/mL) presenting features of native tumors, namely morphology, proliferation and hypoxia gradients, in a cell line-dependent mode. Heterotypic 3D cancer models, based on co-cultures of tumor cells and fibroblasts, were also established in the absence or presence of additional physical support from an alginate matrix, with maintenance of high cell viability. Altogether, we demonstrate that 3D tumor cell model production in stirred-tank culture systems is a robust and versatile approach, providing reproducible tools for drug screening and target verification in pre-clinical oncology research.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.