@article{VottelerCarvajalBerrioPudlasetal.2012,
  author    = {Votteler, Miriam and Carvajal Berrio, Daniel A. and Pudlas, Marieke and Walles, Heike and Schenke-Layland, Katja},
  title     = {Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy},
  series = {Journal of Visual Expression},
  volume    = {63},
  journal   = {Journal of Visual Expression},
  number    = {e3977},
  doi       = {10.3791/3977},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-124569},
  year      = {2012},
  abstract  = {Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10 Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 °C, 5\% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 °C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.},
  language  = {en}
}
@article{FecherHofmannBucketal.2016,
  author    = {Fecher, David and Hofmann, Elisabeth and Buck, Andreas and Bundschuh, Ralph and Nietzer, Sarah and Dandekar, Gudrun and Walles, Thorsten and Walles, Heike and L{\"u}ckerath, Katharina and Steinke, Maria},
  title     = {Human Organotypic Lung Tumor Models: Suitable For Preclinical \(^{18}\)F-FDG PET-Imaging},
  series = {PLoS ONE},
  volume    = {11},
  journal   = {PLoS ONE},
  number    = {8},
  doi       = {10.1371/journal.pone.0160282},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-179678},
  year      = {2016},
  abstract  = {Development of predictable in vitro tumor models is a challenging task due to the enormous complexity of tumors in vivo. The closer the resemblance of these models to human tumor characteristics, the more suitable they are for drug-development and -testing. In the present study, we generated a complex 3D lung tumor test system based on acellular rat lungs. A decellularization protocol was established preserving the architecture, important ECM components and the basement membrane of the lung. Human lung tumor cells cultured on the scaffold formed cluster and exhibited an up-regulation of the carcinoma-associated marker mucin1 as well as a reduced proliferation rate compared to respective 2D culture. Additionally, employing functional imaging with 2-deoxy-2-[\(^{18}\)F]fluoro-D-glucose positron emission tomography (FDG-PET) these tumor cell cluster could be detected and tracked over time. This approach allowed monitoring of a targeted tyrosine kinase inhibitor treatment in the in vitro lung tumor model non-destructively. Surprisingly, FDG-PET assessment of single tumor cell cluster on the same scaffold exhibited differences in their response to therapy, indicating heterogeneity in the lung tumor model. In conclusion, our complex lung tumor test system features important characteristics of tumors and its microenvironment and allows monitoring of tumor growth and -metabolism in combination with functional imaging. In longitudinal studies, new therapeutic approaches and their long-term effects can be evaluated to adapt treatment regimes in future.},
  language  = {en}
}