Drug induced micellization into ultra-high capacity and stable curcumin nanoformulations: Physico-chemical characterization and evaluation in 2D and 3D in vitro models.

Curcumin (CUR) is a natural extract from the plant Curcuma longa and part of turmeric, a spice and herbal remedy in traditional medicine. Thousands of papers claim a plethora of health benefits by CUR, but a growing number of reports and contributions caution that many experimental data may be artifacts or outright deny any suitability of CUR due to its problematic physicochemical properties. Two major issues often encountered with CUR are its extraordinarily low solubility in water and its limited chemical stability. Here, we report on a novel nanoformulation of CUR that enables CUR concentrations in water of at least 50 g/L with relative drug loadings of >50 wt% and high dose efficacy testing in 3D tumor models. Despite this high loading and concentration, the CUR nanoformulation comprises polymer-drug aggregates with a size <50 nm. Most interestingly, this is achieved using an amphiphilic block copolymer, that by itself does not form micelles due to its limited hydrophilic/lipophilic contrast. The ultra-high loaded nanoformulations exhibit a very good stability, reproducibility and redispersibility. In order to test effects of CUR in conditions closer to an in vivo situation, we utilized a 3D tumor test system based on a biological decellularized tissue matrix that better correlates to clinical results concerning drug testing. We found that in comparison to 2D culture, the invasively growing breast cancer cell line MDA-MB-231 requires high concentrations of CUR for tumor cell eradication in 3D. In addition, we supplemented a 3D colorectal cancer model of the malignant cell line SW480 with fibroblasts and observed also in this invasive tumor model with stroma components a decreased tumor cell growth after CUR application accompanied by a loss of cell-cell contacts within tumor cell clusters. In a flow bioreactor simulating cancer cell dissemination, nanoformulated CUR prevented SW480 cells from adhering to a collagen scaffold, suggesting an anti-metastatic potential of CUR. This offers a rationale that the presented ultra-high CUR-loaded nanoformulation may be considered a tool to harness the full therapeutic potential of CUR.

A combined tissue-engineered/in silico signature tool patient stratification in lung cancer.

Patient-tailored therapy based on tumor drivers is promising for lung cancer treatment. For this, we combined in vitro tissue models with in silico analyses. Using individual cell lines with specific mutations, we demonstrate a generic and rapid stratification pipeline for targeted tumor therapy. We improve in vitro models of tissue conditions by a biological matrix-based three-dimensional (3D) tissue culture that allows in vitro drug testing: It correctly shows a strong drug response upon gefitinib (Gef) treatment in a cell line harboring an EGFR-activating mutation (HCC827), but no clear drug response upon treatment with the HSP90 inhibitor 17AAG in two cell lines with KRAS mutations (H441, A549). In contrast, 2D testing implies wrongly KRAS as a biomarker for HSP90 inhibitor treatment, although this fails in clinical studies. Signaling analysis by phospho-arrays showed similar effects of EGFR inhibition by Gef in HCC827 cells, under both 2D and 3D conditions. Western blot analysis confirmed that for 3D conditions, HSP90 inhibitor treatment implies different p53 regulation and decreased MET inhibition in HCC827 and H441 cells. Using in vitro data (western, phospho-kinase array, proliferation, and apoptosis), we generated cell line-specific in silico topologies and condition-specific (2D, 3D) simulations of signaling correctly mirroring in vitro treatment responses. Networks predict drug targets considering key interactions and individual cell line mutations using the Human Protein Reference Database and the COSMIC database. A signature of potential biomarkers and matching drugs improve stratification and treatment in KRAS-mutated tumors. In silico screening and dynamic simulation of drug actions resulted in individual therapeutic suggestions, that is, targeting HIF1A in H441 and LKB1 in A549 cells. In conclusion, our in vitro tumor tissue model combined with an in silico tool improves drug effect prediction and patient stratification. Our tool is used in our comprehensive cancer center and is made now publicly available for targeted therapy decisions.

Human Organotypic Lung Tumor Models: Suitable For Preclinical 18F-FDG PET-Imaging.

Development of predictable in vitro tumor models is a challenging task due to the enormous complexity of tumors in vivo. The closer the resemblance of these models to human tumor characteristics, the more suitable they are for drug-development and -testing. In the present study, we generated a complex 3D lung tumor test system based on acellular rat lungs. A decellularization protocol was established preserving the architecture, important ECM components and the basement membrane of the lung. Human lung tumor cells cultured on the scaffold formed cluster and exhibited an up-regulation of the carcinoma-associated marker mucin1 as well as a reduced proliferation rate compared to respective 2D culture. Additionally, employing functional imaging with 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (FDG-PET) these tumor cell cluster could be detected and tracked over time. This approach allowed monitoring of a targeted tyrosine kinase inhibitor treatment in the in vitro lung tumor model non-destructively. Surprisingly, FDG-PET assessment of single tumor cell cluster on the same scaffold exhibited differences in their response to therapy, indicating heterogeneity in the lung tumor model. In conclusion, our complex lung tumor test system features important characteristics of tumors and its microenvironment and allows monitoring of tumor growth and -metabolism in combination with functional imaging. In longitudinal studies, new therapeutic approaches and their long-term effects can be evaluated to adapt treatment regimes in future.