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1 Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, District of Columbia; 2 Roswell Park Cancer Institute and 3 Department of Social and Preventive Medicine, University of Buffalo, Buffalo, New York; 4 Department of Epidemiology and Biostatistics, School of Public Health, University of South Carolina, Columbia, South Carolina; and 5 Department of Epidemiology, Karolinska Insitutet, Stockholm, Sweden
Requests for reprints: Peter G. Shields, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3800 Reservoir Road Northwest, LL (s) Level, Room 150, Box 571465, Washington, DC 20057-1465. Phone: 202-687-0003; Fax: 202-687-0004. E-mail: pgs2{at}georgetown.edu.
The p53 gene acts as a regulator of cell growth and DNA repair in normal cells; inactivation of the gene seems to lead to cancer. It is the most commonly mutated gene in human cancers, and a high-throughput sequencing method is needed for cancer etiology studies using large sample sets. In our population-based case-control study of breast cancer, the p53 gene was amplified by PCR for 392 subjects from seven hospitals in Western New York using the Affymetrix GeneChip technology. One hundred thirty-eight (35%) of the breast tumors had p53 mutations, of which 88% were located in exons 5 to 8. New hotspots were identified at codons 179, 195, 196, 213, 217, 249, 254, 278, 281, and 298, and previously reported hotspots were found at codons 175, 248, and 273. Manual sequencing for exons 5 to 9 of the p53 gene was done for 139 tumors to validate the Affymetrix assay. The two methods had 100% concordance for mutations detectable by the Affymetrix assay. We also successfully assayed paraffin-embedded breast and lung tumors from as early as 1958 and employed a nested PCR strategy to improve weak PCR amplification. To have statistical power, the investigation of gene environment interactions and cancer requires a large number of tumor analyses, which are frequently only available from archived tissue from multiple sources. We have shown the utility of the Affymetrix GeneChip method under these challenging conditions and provided new data for the mutational spectra of breast cancer in a population-based study. (Cancer Epidemiol Biomarkers Prev 2006;15(1):80–5)
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