ArticleMethods in molecular biology (Clifton, N.J.)2024
Fluid-Dynamic Culture of Tumour and Immune Cells for More Predictive Infiltration Studies and Immunotherapy Drug Screening.
Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Immunotherapies represent one of the current most promising challenges in cancer treatment. They are based on the boost of natural immune responses, aimed at cancer eradication. However, the success of immunotherapeutic approaches strictly depends on the interaction between immune cells and cancer cells. Preclinical drug tests currently available are poor in fully predicting the actual safety and efficacy of immunotherapeutic treatments under development. Indeed, conventional 2D cell culture underrepresents the complexity of the tumour microenvironment, while in vivo animal models lack in mimicking the human immune cell responses. In this context, predictability, reliability, and complete immune compatibility still represent challenges to overcome. For this aim, novel 3D, fully humanized in vitro cancer tissue models have been recently optimized by adopting emerging technologies, such as organ-on-chips (OOC) and 3D cancer cell-laden hydrogels. In particular, a novel multi-in vitro organ (MIVO) OOC platform has been recently adopted to culture 3D clinically relevant size cancer tissues under proper physiological culture conditions to investigate anti-cancer treatments and immune-tumour cell crosstalk.The proposed immune-tumour OOC-based model offers a potential tool for accurately modelling human immune-related diseases and effectively assessing immunotherapy efficacy, finally offering promising experimental approaches for personalized medicine.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.