@article{DongBoeppleThieletal.2023,
  author    = {Dong, Meng and B{\"o}pple, Kathrin and Thiel, Julia and Winkler, Bernd and Liang, Chunguang and Schueler, Julia and Davies, Emma J. and Barry, Simon T. and Metsalu, Tauno and M{\"u}rdter, Thomas E. and Sauer, Georg and Ott, German and Schwab, Matthias and Aulitzky, Walter E.},
  title     = {Perfusion air culture of precision-cut tumor slices: an ex vivo system to evaluate individual drug response under controlled culture conditions},
  series = {Cells},
  volume    = {12},
  journal   = {Cells},
  number    = {5},
  issn      = {2073-4409},
  doi       = {10.3390/cells12050807},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311030},
  year      = {2023},
  abstract  = {Precision-cut tumor slices (PCTS) maintain tissue heterogeneity concerning different cell types and preserve the tumor microenvironment (TME). Typically, PCTS are cultured statically on a filter support at an air-liquid interface, which gives rise to intra-slice gradients during culture. To overcome this problem, we developed a perfusion air culture (PAC) system that can provide a continuous and controlled oxygen medium, and drug supply. This makes it an adaptable ex vivo system for evaluating drug responses in a tissue-specific microenvironment. PCTS from mouse xenografts (MCF-7, H1437) and primary human ovarian tumors (primary OV) cultured in the PAC system maintained the morphology, proliferation, and TME for more than 7 days, and no intra-slice gradients were observed. Cultured PCTS were analyzed for DNA damage, apoptosis, and transcriptional biomarkers for the cellular stress response. For the primary OV slices, cisplatin treatment induced a diverse increase in the cleavage of caspase-3 and PD-L1 expression, indicating a heterogeneous response to drug treatment between patients. Immune cells were preserved throughout the culturing period, indicating that immune therapy can be analyzed. The novel PAC system is suitable for assessing individual drug responses and can thus be used as a preclinical model to predict in vivo therapy responses.},
  language  = {en}
}