Genetics, Vol. 149, 289-299, May 1998, Copyright © 1998

Genetic Identification of Multiple Loci That Control Breast Cancer Susceptibility in the Rat

Laurie A. Shepela, Hong Lana, Jill D. Haaga, Gerlyn M. Brasica, Megan E. Gheena, Jason S. Simonc, Peter Hoffb, Michael A. Newtonb, and Michael N. Goulda
a Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin 53792
b Department of Biostatistics, University of Wisconsin-Madison, Madison, Wisconsin 53792
c Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02154

Corresponding author: Michael N. Gould, University of Wisconsin-Madison, Department of Human Oncology, K4/332, 600 Highland Ave., Madison, WI 53792, gould{at}humonc.wisc.edu (E-mail).

Communicating editor: N. A. JENKINS

We have used a rat model of induced mammary carcinomas in an effort to identify breast cancer susceptibility genes. Using genetic crosses between the carcinoma-resistant Copenhagen (COP) and carcinoma-sensitive Wistar-Furth rats, we have confirmed the identification of the Mcs1 locus that modulates tumor number. We have now also identified two additional loci, Mcs2 and Mcs3. These three loci map to chromosomes 2, 7, and 1, respectively, and interact additively to suppress mammary carcinoma development in the COP strain. They are responsible for a major portion of the tumor-resistant phenotype of the COP rat. No loss of heterozygosity was observed surrounding the three loci. A fourth COP locus, Mcs4, has also been identified on chromosome 8 and acts in contrast to increase the number of carcinomas. These results show that mammary carcinoma susceptibility in the COP rat is a polygenic trait. Interestingly, a polymorphism in the human genomic region homologous to the rat Mcs4 region is associated with an increased breast cancer risk in African-American women. The isolation of the Mcs genes may help elucidate novel mechanisms of carcinogenesis, provide information important for human breast cancer risk estimation, and also provide unique drug discovery targets for breast cancer prevention.





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