Intratumoral hypoxia plays an important role with regard to tumor biology and susceptibility to radio- and chemotherapy. For further investigation of hypoxia-related changes, areas of certain hypoxia must be reliably detected within cancer tissues.
Pimonidazole, a 2-nitroimindazole, accumulates in hypoxic tissue and can be easily visualized using immunohistochemistry.
To improve detection of highly hypoxic versus normoxic areas in prostate cancer, immunoreactivity of pimonidazole and a combination of known hypoxia-related proteins was used to create computational oxygen supply maps of prostate cancer. Pimonidazole was intravenously administered before radical prostatectomy in n = 15 patients, using the da Vinci robot-assisted surgical system. Prostatectomy specimens were immediately transferred into buffered formaldehyde, fixed overnight, and completely embedded in paraffin. Pimonidazole accumulation and hypoxia-related protein expression were visualized by immunohistochemistry. Oxygen supply maps were created using the normalized information from pimonidazole and hypoxia-related proteins.
Based on pimonidazole staining and other hypoxia.related proteins (osteopontin, hypoxia-inducible factor 1-alpha, and glucose transporter member 1) oxygen supply maps in prostate cancer were created. Overall, oxygen supply maps consisting of information from all hypoxia-related proteins showed high correlation and mutual information to the golden standard of pimonidazole. Here, we describe an improved computer-based ex vivo model for an accurate detection of oxygen supply in human prostate cancer tissue.
This platform can be used for precise colocalization of novel candidate hypoxia-related proteins in a representative number of prostate cancer cases, and improve issues of single marker correlations. Furthermore, this study provides a source for further in situ tests and biochemical investigations.
Journal of pathology informatics. 2016 Jan 29*** epublish ***
Niels J Rupp, Peter J Schüffler, Qing Zhong, Florian Falkner, Markus Rechsteiner, Jan H Rüschoff, Christian Fankhauser, Matthias Drach, Remo Largo, Mathias Tremp, Cedric Poyet, Tullio Sulser, Glen Kristiansen, Holger Moch, Joachim Buhmann, Michael Müntener, Peter J Wild
Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Department of Computer Science, ETH Zurich, Universitaetstr 6, 8092 Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Institute of Pathology, Cantonal Hospital Winterthur, Brauerstrasse 15, 8401 Winterthur, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Department of Urology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland., Department of Plastic, Reconstructive and Aesthetic Surgery, University Hospital Basel, Spitalstrasse 21, 4031 Basel, Switzerland., Department of Urology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland., Department of Urology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland., Institute of Pathology, University Hospital Bonn, Sigmund-Freud-Strasse 25, 53127 Bonn, Germany., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland., Department of Computer Science, ETH Zurich, Universitaetstr 6, 8092 Zurich, Switzerland., Department of Urology, City Hospital Triemli, Birmensdorferstrasse 497, 8063 Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland.