Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing.

High attrition rates associated with drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies, our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia.

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Background: Immunotherapy with chimeric antigen receptor (CAR)-engineered T-cells is effective in some hematologic tumors. In solid tumors, however, sustained antitumor responses after CAR T-cell therapy remain to be demonstrated both in the pre-clinical and clinical setting. A perceived barrier to the efficacy of CAR T-cell therapy in solid tumors is the hostile tumor microenvironment where immunosuppressive soluble factors like transforming growth factor (TGF)-β are thought to inhibit the cellular immune response.

Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models.

To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with -mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is-in contrast to melanoma-not effective in CRC, we combined it with the EGFR inhibitor gefitinib.

ROR1-CAR T cells are effective against lung and breast cancer in advanced microphysiologic 3D tumor models.

Solid tumors impose immunologic and physical barriers to the efficacy of chimeric antigen receptor (CAR) T cell therapy that are not reflected in conventional preclinical testing against singularized tumor cells in 2-dimensional culture. Here, we established microphysiologic three-dimensional (3D) lung and breast cancer models that resemble architectural and phenotypical features of primary tumors and evaluated the antitumor function of receptor tyrosine kinase-like orphan receptor 1-specific (ROR1-specific) CAR T cells. 3D tumors were established from A549 (non-small cell lung cancer) and MDA-MB-231 (triple-negative breast cancer) cell lines on a biological scaffold with intact basement membrane (BM) under static and dynamic culture conditions, which resulted in progressively increasing cell mass and invasive growth phenotype (dynamic > static; MDA-MB-231 > A549).

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.

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.

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds.

In the present study, we combined an in vitro 3D lung tumor model with an in silico model to optimize predictions of drug response based on a specific mutational background. The model is generated on a decellularized porcine scaffold that reproduces tissue-specific characteristics regarding extracellular matrix composition and architecture including the basement membrane. We standardized a protocol that allows artificial tumor tissue generation within 14 days including three days of drug treatment.

Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model.

For the development of new treatment strategies against cancer, understanding signaling networks and their changes upon drug response is a promising approach to identify new drug targets and biomarker profiles. Pre-requisites are tumor models with multiple read-out options that accurately reflect the clinical situation. Tissue engineering technologies offer the integration of components of the tumor microenvironment which are known to impair drug response of cancer cells.