Browsing by Author "Thibert, Jacklyn N."

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    ESR1 and PGR polymorphisms are associated with estrogen and progesterone receptor expression in breast tumors
    (American Physiological Society, 2016-09-01) Hertz, Daniel L.; Henry, N. Lynn; Kidwell, Kelley M.; Thomas, Dafydd; Goddard, Audrey; Azzouz, Faouzi; Speth, Kelly; Li, Lang; Banerjee, Mousumi; Thibert, Jacklyn N.; Kleer, Celina G.; Stearns, Vered; Hayes, Daniel F.; Skaar, Todd C.; Rae, James M.; Medicine, School of Medicine
    Hormone receptor-positive (HR+) breast cancers express the estrogen (ERα) and/or progesterone (PgR) receptors. Inherited single nucleotide polymorphisms (SNPs) in ESR1, the gene encoding ERα, have been reported to predict tamoxifen effectiveness. We hypothesized that these associations could be attributed to altered tumor gene/protein expression of ESR1/ERα and that SNPs in the PGR gene predict tumor PGR/PgR expression. Formalin-fixed paraffin-embedded breast cancer tumor specimens were analyzed for ESR1 and PGR gene transcript expression by the reverse transcription polymerase chain reaction based Oncotype DX assay and for ERα and PgR protein expression by immunohistochemistry (IHC) and an automated quantitative immunofluorescence assay (AQUA). Germline genotypes for SNPs in ESR1 (n = 41) and PGR (n = 8) were determined by allele-specific TaqMan assays. One SNP in ESR1 (rs9322336) was significantly associated with ESR1 gene transcript expression (P = 0.006) but not ERα protein expression (P > 0.05). A PGR SNP (rs518162) was associated with decreased PGR gene transcript expression (P = 0.003) and PgR protein expression measured by IHC (P = 0.016), but not AQUA (P = 0.054). There were modest, but statistically significant correlations between gene and protein expression for ESR1/ERα and PGR/PgR and for protein expression measured by IHC and AQUA (Pearson correlation = 0.32–0.64, all P < 0.001). Inherited ESR1 and PGR genotypes may affect tumor ESR1/ERα and PGR/PgR expression, respectively, which are moderately correlated. This work supports further research into germline predictors of tumor characteristics and treatment effectiveness, which may someday inform selection of hormonal treatments for patients with HR+ breast cancer.
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    Genotyping concordance in DNA extracted from formalinfixed paraffin embedded (FFPE) breast tumor and whole blood for pharmacogenetic analyses
    (Wiley, 2015-11) Hertz, Daniel L.; Kidwell, Kelley M.; Thibert, Jacklyn N.; Gersch, Christina; Regan, Meredith M.; Skaar, Todd C.; Henry, N. Lynn; Hayes, Daniel F.; Van Poznak, Catherine H.; Rae, James M.; Medicine, School of Medicine
    Background: Cancer pharmacogenetic studies use archival tumor samples as a DNA source when germline DNA is unavailable. Genotyping DNA from formalin-fixed paraffin embedded tumors (FFPE-T) may be inaccurate due to FFPE storage, genetic aberrations, and/or insufficient DNA extraction. Our objective was to assess the extent and source of genotyping inaccuracy from FFPE-T DNA and demonstrate analytical validity of FFPE-T genotyping of candidate single nucleotide polymorphisms (SNPs) for pharmacogenetic analyses. Methods: Cancer pharmacogenetics SNPs were genotyped by Sequenom MassARRAYs in DNA harvested from matched FFPE-T, FFPE lymph node (FFPE-LN), and whole blood leukocyte samples obtained from breast cancer patients. No- and discordant-call rates were calculated for each tissue type and SNP. Analytical validity was defined as any SNP with <5% discordance between FFPE-T and blood and <10% discordance plus no-calls. Results: Matched samples from 114 patients were genotyped for 247 SNPs. No-call rate in FFPE-T was greater than FFPE-LN and blood (4.3% vs. 3.0% vs. 0.5%, p < 0.001). Discordant-call rate between FFPE-T and blood was very low, but greater than that between FFPE-LN and blood (1.1% vs. 0.3%, p < 0.001). Samples with heterozygous genotypes were more likely to be no- or discordantly-called in either tissue (p < 0.001). Analytical validity of FFPE-T genotyping was demonstrated for 218 (88%) SNPs. Conclusions: No- and discordant-call rates were below concerning thresholds, confirming that most SNPs can be accurately genotyped from FFPE-T on our Sequenom platform. FFPE-T is a viable DNA source for prospective-retrospective pharmacogenetic analyses of clinical trial cohorts.