Lynch syndrome, also known as hereditary nonpolyposis colon cancer (HNPCC), is the most common known genetic syndrome for colorectal cancer (CRC). MLH1/MSH2 mutations underlie approximately 90% of Lynch syndrome families. A total of 24% of these mutations are missense. Interpreting missense variation is extremely challenging. We have therefore developed multivariate analysis of protein polymorphisms-mismatch repair (MAPP-MMR), a bioinformatic algorithm that effectively classifies MLH1/MSH2 deleterious and neutral missense variants. We compiled a large database (n>300) of MLH1/MSH2 missense variants with associated clinical and molecular characteristics. We divided this database into nonoverlapping training and validation sets and tested MAPP-MMR. MAPP-MMR significantly outperformed other missense variant classification algorithms (sensitivity, 94%; specificity, 96%; positive predictive value [PPV] 98%; negative predictive value [NPV], 89%), such as SIFT and PolyPhen. MAPP-MMR is an effective bioinformatic tool for missense variant interpretation that accurately distinguishes MLH1/MSH2 deleterious variants from neutral variants.

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Human genetic variation data are now publicly available on a large scale, from public and private discovery efforts. Datasets from the International Haplotype Map Consortium and Perlegen Sciences provide a level of knowledge about human genetic variation that is unprecedented. In combination with novel high-throughput genotyping technologies, these new resources will allow cancer prevention investigators to identify in a more precise way which genetic subsets of patients are likely to benefit most from chemoprevention and screening interventions.

21089 Background: Genotyping of clinical samples has been limited to low levels of multiplexing, ranging from one to a few dozen single nucleotide polymorphisms (SNPs) per sample. By increasing multiplexing levels, a clinical lab can increase information content per sample, decreasing costs and sample material requirements. Methods: We have adapted the GoldenGate® Assay for simultaneously genotyping 96 to 1,536 SNPs to the BeadXpress™ System, a new high-throughput platform that utilizes digitally inscribed VeraCode™ beads in a compact fluidic instrument. Genotyping on this platform ranges from 96 to 384 multiplexing, using the same GoldenGate Assay that has proven highly robust for millions of genotypes. In preliminary tests, we have observed greater than 99% call rates, and greater than 99.5% rates for reproducibility and heritability. In a test of 96 SNP genotypes chosen for a study of colorectal cancer, a point mutation in the MSH2 gene, previously implicated in predisposition to several cancers, was correctly genotyped when compared to qPCR analysis of the same samples. Conclusion: Together with genotyping data from reference samples, the GoldenGate Assay on the BeadXpress System has yielded highly reproducible and accurate genotypes, suggesting that this approach will prove useful for rapid refinement of SNPs for development of clinical genotyping tests. No significant financial relationships to disclose.