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Breast cancer risk assessment
The OUHSC Laboratory for Genomics and Bioinformatics (LGB) has aided InterGenetics in two important ways. First, InterGenetics has developed and/or optimized several high throughput genotyping technologies, mostly for single nucleotide polymorphisms (SNPs) that alter the amino acid sequences of proteins of interest. Rational process development and optimization requires that all polymorphisms in the genomic regions of interest be identified and characterized. Also, a collection of at least 20 human derived specimens must be available for which the genotypes are known with absolute certainty. To accomplish these goals, the OUHSC LGB has assisted in resequencing approximately 100 different genomic regions in 20-plus individuals. DNAs from these individuals are the standards and controls used to develop and optimize InterGenetics processes. Secondly, when most researchers think of common genetic variants, they think of SNPs. There are, however, other common genetic polymorphisms, including small insertion/deletion polymorphisms and length polymorphisms. Frequently, these occur in low complexity DNA regions, and genotyping these is problematic for most current SNP genotyping technologies. Consequently, these are an under-studied class of genetic variation. InterGenetics is developing a high throughput multiplex format to examine these polymorphisms and is employing the OUHSC LGB to analyze the InterGenetics data by capillary electrophoresis. These InterGenetics projects demonstrate the ability of the OUHSC LGB to facilitate commercial biotechnology development in central Oklahoma. For more information, contact Dr. David Ralph (CSO) (405-271-2896) or see the InterGenetics web site at www.InterGenetics.com.
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InterGenetics, Inc. is a genetics-based bioinformatics company located in the
Research Park adjacent to OUHSC. InterGenetics is developing a breast cancer risk
assessment tool to identify women at high risk of developing breast cancer but not
carrying mutations in the BRCA1 or BRCA2 genes. This risk assessment tool,
commercially available in 2005, is based on a statistical model of risk derived
from the analysis of data from a case-control associative study of nearly 9,000
individuals. Two types of data re being analyzed in this study. First, data is
collected concerning a woman's reproductive history and other personal history
measures such as her family's cancer history. Secondly, data consists of genotypes
for approximately 80 common polymorphisms located in genes important to breast
carcinogenesis. Combining this information in a large multivariate analysis
results in a statistical model that stratifies risk over a broad range.