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Sample Type Bias in the Analysis of Cancer Genomes

¹ Department of Oncology, Lombardi Comprehensive Cancer Center and ² Department of Neurosurgery, Georgetown University School of Medicine, Washington, District of Columbia; ³ Department of Neurosurgery, University of Iowa College of Medicine, Iowa City, Iowa; and ⁴ Preston Robert Tisch Brain Tumor Center, Duke University School of Medicine, Durham, North Carolina

Requests for reprints: Todd Waldman, Lombardi Comprehensive Cancer Center, E304 Research Building, 3970 Reservoir Road, Northwest, Washington, DC 20057. Phone: 202-687-1340; Fax: 202-687-7505; E-mail: waldmant{at}georgetown.edu.

Key Words: cancer genomics • amplification • homozygous deletion • tumor xenografts • cancer cell lines

Abstract

There is widespread agreement that cancer gene discovery requires high-quality tumor samples. However, whether primary tumors or cultured samples are superior for cancer genomics has been a longstanding subject of debate. This debate has recently become more important because federally funded cancer genomics has been centralized under The Cancer Genome Atlas, which has chosen to focus exclusively on primary tumors. Here, we provide a data-driven "perspective" on the effect of sample type selection on cancer genomics research. We show that, in the case of glioblastoma multiforme, primary tumors and xenografts are best for the identification of amplifications, whereas xenografts and cell lines are superior for the identification of homozygous deletions. We also note that many of the most important oncogenes and tumor suppressor genes have been discovered through the use of cell lines and xenografts, and highlight the lack of published evidence supporting the dogma that ex vivo culture generates artifactual genetic lesions. Based on this analysis, we suggest that cancer genomics projects such as The Cancer Genome Atlas should include a variety of sample types such as xenografts and cell lines in their integrated genomic analysis of cancer. [Cancer Res 2009;69(14):5630–3]