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Microarray analysis identifies distinct gene expression profiles associated with histological subtype in human osteosarcoma
Authors:Bernd Kubista  Florian Klinglmueller  Martin Bilban  Martin Pfeiffer  Richard Lass  Alexander Giurea  Phillipp T. Funovics  Cyril Toma  Martin Dominkus  Rainer Kotz  Theresia Thalhammer  Klemens Trieb  Teresa Zettl  Christian F. Singer
Affiliation:1. Department of Orthopedics, Medical University of Vienna, 1090, Vienna, Austria
2. Department of Laboratory Medicine and Ludwig Boltzmann Institute for Clinical and Experimental Oncology, Medical University of Vienna, 1090, Vienna, Austria
3. Institute of Pathophysiology, Center for Physiology, Pathophysiology and Immunology, Medical University of Vienna, 1090, Vienna, Austria
4. Department of Orthopedics, Klinikum Kreuzschwestern Wels, Wels, Austria
5. Division of Special Gynecology, Department of OB/GYN, Medical University of Vienna, 1090, Vienna, Austria
Abstract:Osteosarcoma is the most common primary malignant bone tumour. Currently osteosarcoma classification is based on histological appearance. It was the aim of this study to use a more systematic approach to osteosarcoma classification based on gene expression analysis and to identify subtype specific differentially expressed genes. We analysed the global gene expression profiles of ten osteosarcoma samples using Affymetrix U133A arrays (five osteoblastic and five non-osteoblastic osteosarcoma patients). Differential gene expression analysis yielded 75 genes up-regulated and 97 genes down-regulated in osteoblastic versus non-osteoblastic osteosarcoma samples, respectively. These included genes involved in cell growth, chemotherapy resistance, angiogenesis, steroid- and neuropeptide hormone receptor activity, acute-phase response and serotonin receptor activity and members of the Wnt/ß-catenin pathway and many others. Furthermore, we validated the highly differential expression of six genes including angiopoietin 1, IGFBP3, ferredoxin 1, BMP, decorin, and fibulin 1 in osteoblastic osteosarcoma relative to non-osteoblastic osteosarcoma. Our results show the utility of gene expression analysis to study osteosarcoma subtypes, and we identified several genes that may play a role as potential therapeutic targets in the future.
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