3D tumor models with defined cellular and physico- chemical components: Impact of recapitulative tumor microenvironment on disease progression

The high attrition rates observed in cancer drug discovery (up to 95% of failure of drugs tested in phase I trials) have raised the awareness of the scientific and industrial communities towards the need for more predictive pre-clinical models. These models should be more representative of the disease and consequently help to eliminate at pre-clinical stages drug candidates that lack efficacy or safety. Tumor microenvironment is composed by a network of fibroblasts, endothelial cells, immune-competent cells within the extracellular matrix (ECM). Interactions between these components are critical for tumor initiation, proliferation, migration and metastasis. The design of in vitro cancer cell models that recapitulate the tumor microenvironment and 3D architecture provides higher physiological relevance as they more closely resemble the in vivo cellular context. We have established methodologies for scalable generation of 3D cancer cell models in stirred-tank culture systems, and applied these to a large panel of tumor cell lines from different pathologies, including breast, colon, hepatic and lung tumor cell lines. Large numbers of spheroids were obtained per culture (typically 1000-1500 spheroids/mL) with representative characteristics of native tumors, such as morphology, proliferation and hypoxia gradients, in a cell-line dependent mode. With the aim of increasing the relevance of spheroids as tumor cell models, several aspects of tumor microenvironment were incorporated, such as the presence of stromal cells (fibroblasts and monocytes) and specific physico-chemical parameters, namely oxygen levels. Heterotypic 3D breast and Non-Small Cell Lung Carcinoma (NSCLC) cancer models, based on co-cultures of tumor cells with stromal cells were established by using an alginate matrix to provide physical support to cells. Tumor spheroids were microencapsulated alone or with fibroblasts and monocytes, thus allowing the establishment of an epithelial tumor compartment and a stromal compartment of increasing complexity. Cultures were performed in stirred-tank vessels for 15 days with continuous monitoring. In both breast and lung tumor models, the presence of fibroblasts was associated with secretion of pro-inflammatory cytokines and accumulation of collagen in the microcapsules. Long-term culture (up to 15 days) resulted in phenotypic alterations in co-cultured breast tumor spheroids, such as loss of cell polarity, reduced cell-cell adhesions, collective cell migration and increased angiogenic potential. In contrast, the effects of fibroblasts were not as significant in NSCLC co-cultures using H1650, H1437 and H157 cell lines suggesting that the effect of tumor-stroma cross-talk is cell line dependent. Moreover, these models have also been shown as feasible tools for drug screening by assessing the effect of chemotherapeutic and specific inhibitors compounds on mono- and co-cultures. In conclusion, we have developed scalable, robust and versatile methodologies for the generation and culture of 3D cancer models, enabling long-term in vitro recapitulation of tumor-stroma crosstalk, via reconstruction of key aspects of the tumor microenvironment, allowing continuous monitoring of disease progression events in vitro. In addition, it is easily transferable to industry for feeding high-throughput systems or miniaturized bioreactors used in drug development, target validation and target identification

Patient-derived explants of colorectal cancer: histopathological and molecular analysis of long-term cultures

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).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.This research was supported by AbbVie and by iNOVA4Health—UIDB/04462/2020, a program financially supported by Fundação para a Ciência e Tecnologia (FCT)/Ministério da Educação e Ciência, through national funds. TFM and SA were recipients of individual PhD fellowships funded by FCT (PD/BD/128377/2017 and PD/BD/105768/2014, respectively). CB acknowledges the support from “The Discoveries Centre for Regenerative and Precision Medicine” (European Commission Horizon 2020 Research and Innovation programme, under the Grant Agreement number 739572).info:eu-repo/semantics/publishedVersio

Application of LDH assay for therapeutic efficacy evaluation of ex vivo tumor models

Funding Information: This work was supported by AbbVie and by iNOVA4Health – UIDB/04462/2020, a program financially supported by Fundação para a Ciência e Tecnologia (FCT) / Ministério da Educação e Ciência, through national funds. RM and TFM were recipients of PhD fellowships funded by FCT (SFRH/BD/132163/2017 and PD/BD/128377/2017, respectively) and CB was funded by “The Discoveries Centre for Regenerative and Precision Medicine” (European Commission Horizon 2020 Research and Innovation programme, under the Grant Agreement 739572). Publisher Copyright: © 2021, The Author(s).The current standard preclinical oncology models are not able to fully recapitulate therapeutic targets and clinically relevant disease biology, evidenced by the 90% attrition rate of new therapies in clinical trials. Three-dimensional (3D) culture systems have the potential to enhance the relevance of preclinical models. However, the limitations of currently available cellular assays to accurately evaluate therapeutic efficacy in these models are hindering their widespread adoption. We assessed the compatibility of the lactate dehydrogenase (LDH) assay in 3D spheroid cultures against other commercially available readout methods. We developed a standardized protocol to apply the LDH assay to ex vivo cultures, considering the impact of culture growth dynamics. We show that accounting for growth rates and background release levels of LDH are sufficient to make the LDH assay a suitable methodology for longitudinal monitoring and endpoint assessment of therapeutic efficacy in both cell line-derived xenografts (xenospheres) and patient-derived explant cultures. This method has the added value of being non-destructive and not dependent on reagent penetration or manipulation of the parent material. The establishment of reliable readout methods for complex 3D culture systems will further the utility of these tumor models in preclinical and co-clinical drug development studies.publishersversionpublishe

Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer

Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.publishersversionpublishe

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 cocultures 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.Peer reviewe

Pevonedistat and azacitidine upregulate NOXA (PMAIP1) to increase sensitivity to venetoclax in preclinical models of acute myeloid leukemia

Dysregulation of apoptotic machinery is one mechanism by which acute myeloid leukemia (AML) acquires a clonal survival advantage. B-cell lymphoma protein-2 (BCL2) overexpression is a common feature in hematologic malignancies. The selective BCL2 inhibitor, venetoclax (VEN) is used in combination with azacitidine (AZA), a DNAmethyltransferase inhibitor (DNMTi), to treat patients with AML. Despite promising response rates to VEN/AZA, resistance to the agent is common. One identified mechanism of resistance is the upregulation of myeloid cell leukemia-1 protein (MCL1). Pevonedistat (PEV), a novel agent that inhibits NEDD8-activating enzyme, and AZA both upregulate NOXA (PMAIP1), a BCL2 family protein that competes with effector molecules at the BH3 binding site of MCL1. We demonstrate that PEV/AZA combination induces NOXA to a greater degree than either PEV or AZA alone, which enhances VEN-mediated apoptosis. Herein, using AML cell lines and primary AML patient samples ex vivo, including in cells with genetic alterations linked to treatment resistance, we demonstrate robust activity of the PEV/VEN/AZA triplet. These findings were corroborated in preclinical systemic engrafted models of AML. Collectively, these results provide rational for combining PEV/VEN/AZA as a novel therapeutic approach in overcoming AML resistance in current therapies

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.Peer reviewe

The Volume of Three-Dimensional Cultures of Cancer Cells In Vitro Influences Transcriptional Profile Differences and Similarities with Monolayer Cultures and Xenografted Tumors

Improving the congruity of preclinical models with cancer as it is manifested in humans is a potential way to mitigate the high attrition rate of new cancer therapies in the clinic. In this regard, three-dimensional (3D) tumor cultures in vitro have recently regained interest as they have been acclaimed to have higher similarity to tumors in vivo than to cells grown in monolayers (2D). To identify cancer functions that are active in 3D rather than in 2D cultures, we compared the transcriptional profiles (TPs) of two non-small cell lung carcinoma cell lines, NCI-H1650 and EBC-1 grown in both conditions to the TP of xenografted tumors. Because confluence, diameter or volume can hypothetically alter TPs, we made intra- and inter-culture comparisons using samples with defined dimensions. As projected by Ingenuity Pathway Analysis (IPA), a limited number of signal transduction pathways operational in vivo were better represented by 3D than by 2D cultures in vitro. Growth of 2D and 3D cultures as well as xenografts induced major changes in the TPs of these 3 modes of culturing. Alterations of transcriptional network activation that were predicted to evolve similarly during progression of 3D cultures and xenografts involved the following functions: hypoxia, proliferation, cell cycle progression, angiogenesis, cell adhesion, and interleukin activation. Direct comparison of TPs of 3D cultures and xenografts to monolayer cultures yielded up-regulation of networks involved in hypoxia, TGF and Wnt signaling as well as regulation of epithelial mesenchymal transition. Differences in TP of 2D and 3D cancer cell cultures are subject to progression of the cultures. The emulation of the predicted cell functions in vivo is therefore not only determined by the type of culture in vitro but also by the confluence or diameter of the 2D or 3D cultures, respectively. Consequently, the successful implementation of 3D models will require phenotypic characterization to verify the relevance of applying these models for drug development