Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor.

BackgroundCancer cell resistance to therapeutics can result from acquired or de novo-mediated factors. Here, we have utilised advanced breast cancer cell culture models to elucidate de novo doxorubicin resistance mechanisms.MethodsThe response of breast cancer cell lines (MCF-7 and MDA-MB-231) to doxorubicin was examined in an in vitro three-dimensional (3D) cell culture model. Cells were cultured with Matrigel™ enabling cellular arrangements into a 3D architecture in conjunction with cell-to-extracellular matrix (ECM) contact.ResultsBreast cancer cells cultured in a 3D ECM-based model demonstrated altered sensitivity to doxorubicin, when compared to those grown in corresponding two-dimensional (2D) monolayer culture conditions. Investigations into the factors triggering the observed doxorubicin resistance revealed that cell-to-ECM interactions played a pivotal role. This finding correlated with the up-regulation of pro-survival proteins in 3D ECM-containing cell culture conditions following exposure to doxorubicin. Inhibition of integrin signalling in combination with doxorubicin significantly reduced breast cancer cell viability. Furthermore, breast cancer cells grown in a 3D ECM-based model demonstrated a significantly reduced proliferation rate in comparison to cells cultured in 2D conditions.ConclusionCollectively, these novel findings reveal resistance mechanisms which may contribute to reduced doxorubicin sensitivity.

We describe the synthesis of cyclam metal complexes derivatized with amino acids or a tripeptide using a copper(I)-catalyzed Huisgen "click" reaction. The linker triazole formed during the synthesis plays an active coordinating role in the complexes. The reaction conditions do not racemize the amino acid stereocenters. However, a methylene group adjacent to the triazole is susceptible to H/D exchange under ambient conditions, an observation which has potentially important implications for structures involving stereocenters adjacent to triazoles in click-derived structures. The successful incorporation of several amino acids is described, including reactive tryptophan and cysteine side chains. All complexes are formed rapidly upon introduction of the relevant metal salt, including synthetically convenient cases where trifluoroacetate salts of cyclam derivatives are used directly in the metalation. None of the metal complexes displayed any cytotoxicity to mammalian cells, suggesting that the attachment of such complexes to amino acids and peptides does not induce toxicity, further supporting their potential suitability for labeling/imaging studies. One Cu(II)-cyclam-triazole-cysteine disulfide complex displayed moderate activity against MCF-10A breast nontumorigenic epithelial cells.

A more relevant in vitro cell culture model that closely mimics tumor biology and provides better predictive information on anticancer therapies has been the focus of much attention in recent years. We have developed a three-dimensional (3D) human tumor cell culture model that attempts to recreate the in vivo microenvironment and tumor biology in a miniaturized 384-well plate format. This model aims to exploit the potential of 3D cell culture as a screening tool for novel therapeutics for discovery programs. Here we have evaluated a Matrigel™ based induction of 3D tumor formation using standard labware and plate reading equipment. We have demonstrated that with an optimized protocol, reproducible proliferation, and cell viability data can be obtained across a range of cell lines and reagent batches. A panel of reference drugs was used to validate the suitability of the assays for a high throughput drug discovery program. Indicators of assay reproducibility, such as Z'-factor and coefficient of variation, as well as dose response curves confirmed the robustness of the assays. Several methods of drug activity determination were examined, including metabolic and imaging based assays. These data demonstrate this model as a robust tool for drug discovery bridging the gap between monolayer cell culture and animal models, providing insights into drug efficacy at an earlier time point, ultimately reducing costs and high attrition rates.

The data presented herein demonstrates the cellular viability and physical changes observed within the 3D spheroid following exposure to drug, which is not always reflected in 2D cell culture models.

Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.

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Three-dimensional (3D) in vitro cell based assays for Prostate Cancer (PCa) research are rapidly becoming the preferred alternative to that of conventional 2D monolayer cultures. 3D assays more precisely mimic the microenvironment found in vivo, and thus are ideally suited to evaluate compounds and their suitability for progression in the drug discovery pipeline. To achieve the desired high throughput needed for most screening programs, automated quantification of 3D cultures is required. Towards this end, this paper reports on the development of a prototype analysis module for an automated high-content-analysis (HCA) system, which allows for accurate and fast investigation of in vitro 3D cell culture models for PCa. The Java based program, which we have named PCaAnalyser, uses novel algorithms that allow accurate and rapid quantitation of protein expression in 3D cell culture. As currently configured, the PCaAnalyser can quantify a range of biological parameters including: nuclei-count, nuclei-spheroid membership prediction, various function based classification of peripheral and non-peripheral areas to measure expression of biomarkers and protein constituents known to be associated with PCa progression, as well as defining segregate cellular-objects effectively for a range of signal-to-noise ratios. In addition, PCaAnalyser architecture is highly flexible, operating as a single independent analysis, as well as in batch mode; essential for High-Throughput-Screening (HTS). Utilising the PCaAnalyser, accurate and rapid analysis in an automated high throughput manner is provided, and reproducible analysis of the distribution and intensity of well-established markers associated with PCa progression in a range of metastatic PCa cell-lines (DU145 and PC3) in a 3D model demonstrated.