Abstract
Single-nucleotide polymorphisms (SNPs) can be assayed using DNA isolated from archival formalin-fixed, paraffin-embedded (FFPE) samples, making retrospective pharmacogenetic studies possible. In this study, we describe methods that significantly increase the number of SNP determinations possible using FFPE samples. Quantifying the amount of DNA amenable to PCR (amplification-quality DNA, AQ-DNA) allows a significant reduction in the amount of sample required for Taqman-based SNP assays. Optimizing AQ-DNA input increases PCR amplification efficiency and SNP determination accuracy. DNA was extracted from 39 FFPE tumor sections and matched tumor and stromal cores, which were of the type used to generate tissue microarrays. Sections and tumor cores yielded sufficient AQ-DNA for more than 1000 SNP determinations. Seven SNPs were assessed following individual assay optimization for minimal AQ-DNA. Genotypes from tumor cores for single SNPs were 92.3–100% concordant with those obtained from sections. Using these methods, the number of SNP genotypes that can be determined from single FFPE samples is greatly increased expanding the genetic association studies possible from limited archival specimens. The use of tumor cores is of particular importance as the harvesting of tumor cores has minimal impact on the utility of the donor blocks for other purposes.
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Acknowledgements
We thank Dr Sharoni Jacobs for assistance in developing the quality control multiplex PCR. MD and JS are grateful for funding from Breakthrough Breast Cancer and the Royal Marsden NIHR Biomedical Research Centre. This work was supported in part by the Breast Cancer Research Foundation Grant N003173 and by U-01 GM61373 and T-32 GM007767 from the National Institute of General Medical Sciences, Bethesda, MD, USA.
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Sikora, M., Thibert, J., Salter, J. et al. High-efficiency genotype analysis from formalin-fixed, paraffin-embedded tumor tissues. Pharmacogenomics J 11, 348–358 (2011). https://doi.org/10.1038/tpj.2010.50
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DOI: https://doi.org/10.1038/tpj.2010.50
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