Primary Extracellular Matrix Enables Long-Term Cultivation of Human Tumor Oral Mucosa Models.

3D tumor models clearly outperform 2D cell cultures in recapitulating tissue architecture and drug response. However, their potential in understanding treatment efficacy and resistance development should be better exploited if also long-term effects of treatment could be assessed in vitro. The main disadvantages of the matrices commonly used for in vitro culture are their limited cultivation time and the low comparability with patient-specific matrix properties. Extended cultivation periods are feasible when primary human cells produce the extracellular matrix in situ. Herein, we adapted the hyalograft-3D approach from reconstructed human skin to normal and tumor oral mucosa models and compared the results to bovine collagen-based models. The hyalograft models showed similar morphology and cell proliferation after 7 weeks compared to collagen-based models after 2 weeks of cultivation. Tumor thickness and VEGF expression increased in hyalograft-based tumor models, whereas expression of laminin-332, tenascin C, and hypoxia-inducible factor 1α was lower than in collagen-based models. Taken together, the in situ produced extracellular matrix better confined tumor invasion in the first part of the cultivation period, with continuous tumor proliferation and increasing invasion later on. This proof-of-concept study showed the successful transfer of the hyalograft approach to tumor oral mucosa models and lays the foundation for the assessment of long-term drug treatment effects. Moreover, the use of an animal-derived extracellular matrix is avoided.

A multilayered epithelial mucosa model of head neck squamous cell carcinoma for analysis of tumor-microenvironment interactions and drug development.

Pharmacotherapy of head and neck squamous cell carcinoma (HNSCC) often fails due to the development of chemoresistance and severe systemic side effects of current regimens limiting dose escalation. Preclinical models comprising all major elements of treatment resistance are urgently needed for the development of new strategies to overcome these limitations. For model establishment, we used tumor cells from patient-derived HNSCC xenografts or cell lines (SCC-25, UM-SCC-22B) and characterized the model phenotype. Docetaxel and cetuximab were selected for comparative analysis of drug-related effects at topical and systemic administration. Cetuximab cell binding was mapped by cluster-based fluorescence lifetime imaging microscopy.The tumor oral mucosa (TOM) models displayed unstructured, hyper-proliferative, and pleomorphic cell layers, reflecting well the original tumor morphology and grading. Dose- and time-dependent effects of docetaxel on tumor size, apoptosis, hypoxia, and interleukin-6 release were observed. Although the spectrum of effects was comparable, significantly lower doses were required to achieve similar docetaxel-induced changes at topical compared to systemic application. Despite displaying anti-proliferative effects in monolayer cultures, cetuximab treatment showed only minor effects in TOM models. This was not due to inefficient cetuximab uptake or target cell binding but likely mediated by microenvironmental components.We developed multi-layered HNSCC models, closely reflecting tumor morphology and displaying complex interactions between the tumor and its microenvironment. Topical application of docetaxel emerged as promising option for HNSCC treatment. Aside from the development of novel strategies for topical drug delivery, our tumor model might help to better understand key regulators of drug-tumor-interactions.

Automated Real-Time Tumor Pharmacokinetic Profiling in 3D Models: A Novel Approach for Personalized Medicine.

Cancer treatment often lacks individual dose adaptation, contributing to insufficient efficacy and severe side effects. Thus, personalized approaches are highly desired. Although various analytical techniques are established to determine drug levels in preclinical models, they are limited in the automated real-time acquisition of pharmacokinetic profiles. Therefore, an online UHPLC-MS/MS system for quantitation of drug concentrations within 3D tumor oral mucosa models was generated. The integration of sampling ports into the 3D tumor models and their culture inside the autosampler allowed for real-time pharmacokinetic profiling without additional sample preparation. Docetaxel quantitation was validated according to EMA guidelines. The tumor models recapitulated the morphology of head-and-neck cancer and the dose-dependent tumor reduction following docetaxel treatment. The administration of four different docetaxel concentrations resulted in comparable courses of concentration versus time curves for 96 h. In conclusion, this proof-of-concept study demonstrated the feasibility of real-time monitoring of drug levels in 3D tumor models without any sample preparation. The inclusion of patient-derived tumor cells into our models may further optimize the pharmacotherapy of cancer patients by efficiently delivering personalized data of the target tissue.