Accurate genotyping from paraffin-embedded normal tissue adjacent to breast cancer

Genetic polymorphism analysis for disease risk is widely used in epidemiology studies; blood or oral cavity cells are the most widely used source of DNA. However, these types of samples are not always available, particularly for studies that were conducted years ago. An alternative potential source of patient DNA exists in the form of paraffin-embedded normal tissue adjacent to tumor samples, which are collected and stored routinely for clinical use. The use of such samples can be conceptually problematic, however, due to the presence of field cancerization in the surrounding normal tissue, with the possible presence of chromosomal loss. Specifically, loss of heterozygosity (LOH) might bias the genotyping results and cause genotype misclassification. However, field cancerization and LOH might not be an issue because LOH is not easily found unless there is careful microdissection of only tumor cells (leaving stromal, inflammatory and fat cells), for example, laser-capture microdissection. In this study, we set out to determine the degree of genotype misclassification from normal tissues adjacent to tumors, if any, by comparing these results with blood genotyping. We examined samples from 106 subjects with breast cancer, analyzing five different genotypes selected from regions commonly known to have LOH in breast cancer. These genotypes were methylenetetrahydrofolate reductase (MTHFR), oxoguanosine glycosylase 1 (hOGG1), dopamine beta-hydroxylase (DBH), dopamine receptor D2 (DRD2) and NAD(P)H dehydrogenase quinone 1 (NQO1), conducted by using real-time PCR and TaqMan genotyping analyses. We found that among these five genotypes and 106 comparisons, there was a 100% concordance for genotyping from normal tissue adjacent to tumor and from blood. Our findings indicate that the use of adjacent normal tissues provides accurate genotyping results with high specificity. Although this study only used breast tumor samples, and may be applicable only to breast cancer studies, we expect the results to be applicable to other types of cancers also.