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Lung cancer organoids

Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

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Data access policy Department of Biomedical Genetics of UMC Utrecht

The Data Access Committee of the Department of Biomedical Genetics of UMC Utrecht (DAC-DGB-UMCU) governs data access to genomic datasets and accompanying metadata via a two-step access request procedure. Access to data will only be granted to qualified users for appropriate use. Step 1: contact the DAC-DBG-UMCU at DACDBG@umcutrecht.nl, providing a brief summary of your research proposal and the requested datasets. Your proposal will be reviewed based on the necessity of the requested dataset to answer the specific research question. Step 2: The DAC will request additional documentation to complete your application. The DAC-DBG-UMCU will decide if data access is permitted by evaluating the feasibility of the project, the scientific profile of the applicant(s), and whether the relevant ethical approvals justify the proposed research. Only unanimous voting results in acceptation of the request.

Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.

Study ID Study Title Study Type
EGAS00001002899 Other

This table displays only public information pertaining to the files in the dataset. If you wish to access this dataset, please submit a request. If you already have access to these data files, please consult the download documentation.

ID File Type Size Located in
EGAF00001902477 bam 161.9 GB
EGAF00001902478 bam 58.5 GB
EGAF00001902479 bam 59.5 GB
EGAF00001902480 bam 59.4 GB
4 Files (339.2 GB)