German Cancer Research Center

6 ARTICLES PUBLISHED IN JoVE

Medicine

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Hanibal Bohnenberger¹, Philipp Ströbel¹, Sebastian Mohr², Jasmin Corso³, Tobias Berg², Henning Urlaub^3,4, Christof Lenz^3,4, Hubert Serve^2,5,6, Thomas Oellerich^2,5,6

¹Institute of Pathology, University Medical Center, Göttingen, ²Department of Hematology/Oncology, Goethe University of Frankfurt, ³Bioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, ⁴Bioanalytics, Institute of Clinical Chemistry, University Medical Center, Göttingen, ⁵German Cancer Consortium, ⁶German Cancer Research Center

In-depth analyses of cancer cell proteomes facilitate identification of novel drug targets and diagnostic biomarkers. We describe an experimental workflow for quantitative analysis of (phospho-)proteomes in cancer cell subpopulations derived from liquid and solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry.

Bioengineering

Atomic Force Microscopy Imaging and Force Spectroscopy of Supported Lipid Bilayers

Joseph D. Unsay^1,2,3, Katia Cosentino^1,2, Ana J. García-Sáez^1,2

¹Interfaculty Institute for Biochemistry, ²Max Planck Institute for Intelligent Systems, ³German Cancer Research Center

We describe a protocol for preparation of supported lipid bilayers and its characterization using atomic force microscopy and force spectroscopy.

Medicine

Isolation of Endothelial Progenitor Cells from Healthy Volunteers and Their Migratory Potential Influenced by Serum Samples After Cardiac Surgery

Christoph Emontzpohl^1,2, David Simons³, Sandra Kraemer⁴, Andreas Goetzenich⁴, Gernot Marx¹, Jürgen Bernhagen^5,6, Christian Stoppe¹

¹Department of Intensive Care Medicine, University Hospital Aachen, ²Institute of Biochemistry and Molecular Biology, University Hospital Aachen, ³Department of Radiology, German Cancer Research Center, ⁴Department of Thoracic and Cardiovascular Surgery, University Hospital Aachen, ⁵Department of Vascular Biology, Institute for Stroke and Dementia Research (ISD), Klinikum der Universität München, ⁶Deutsches Zentrum für Herz-/Kreislaufkrankheiten (DZHK), Munich Heart Alliance

Endothelial progenitor cells (EPCs) are crucially involved in the neovascularization of ischemic tissues. This method describes the isolation of human EPCs from peripheral blood, as well as the identification of their migratory potential against serum samples of cardiac surgical patients.

Cancer Research

Cell Cycle-specific Measurement of γH2AX and Apoptosis After Genotoxic Stress by Flow Cytometry

Ramon Lopez Perez^1,2, Franziska Münz^1,2, Jonas Kroschke^1,2, Jannek Brauer^1,2, Nils H. Nicolay^1,2,3, Peter E. Huber^1,2

¹CCU Molecular and Radiation Oncology, German Cancer Research Center, ²Department of Radiation Oncology, Heidelberg University Hospital, ³Department of Radiation Oncology, Freiburg University Medical Center

The presented method combines the quantitative analysis of DNA double-strand breaks (DSBs), cell cycle distribution and apoptosis to enable cell cycle-specific evaluation of DSB induction and repair as well as the consequences of repair failure.

Cancer Research

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Stephan Ellmann¹, Lisa Seyler¹, Clarissa Gillmann², Vanessa Popp¹, Christoph Treutlein¹, Aline Bozec³, Michael Uder¹, Tobias Bäuerle¹

¹Department of Radiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, ²Department of Medical Physics in Radiation Oncology, German Cancer Research Center, ³Department of Internal Medicine 3, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg

This protocol was designed to train a machine learning algorithm to use a combination of imaging parameters derived from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a rat model of breast cancer bone metastases to detect early metastatic disease and predict subsequent progression to macrometastases.

Cancer Research

Mast Cells in the Microenvironment of Hepatocellular Carcinoma Confer Favorable Prognosis: A Retrospective Study using QuPath Image Analysis Software

Esraa Ali¹, Lenka Červenková^2,3, Richard Pálek^2,4, Filip Ambrozkiewicz¹, Sergii Pavlov¹, Wenjing Ye¹, Petr Hošek², Ondrej Daum^5,6, Václav Liška^2,4, Kari Hemminki^1,7, Andriy Trailin¹

¹Laboratory of Translational Cancer Genomics, Biomedical Center, Faculty of Medicine in Pilsen, Charles University, ²Laboratory of Cancer Treatment and Tissue Regeneration, Biomedical Center, Faculty of Medicine in Pilsen, Charles University, ³Department of Pathology, Third Faculty of Medicine, Charles University, ⁴Department of Surgery and Biomedical Center, Faculty of Medicine in Pilsen, Charles University, ⁵Sikl's Institute of Pathology, Faculty of Medicine and Teaching Hospital in Pilsen, Charles University, ⁶Bioptická Laboratoř s.r.o., ⁷Department of Cancer Epidemiology, German Cancer Research Center

The presence of mast cells in the inner margin and peritumor areas of hepatocellular carcinoma after resection confers a favorable prognosis. This study endorses QuPath image analysis software as a promising platform that could meet the need for reproducibility, consistency, and accuracy in digital pathology.