Abstract 3269: QTLs in breast tumor and breast normal adjacent FFPE specimens from the Nurses’ Health Study (2014)

Abstract Rationale: Genome-wide association studies (GWAS) of breast cancer have identified 71 risk alleles, majority of which are located in intergenic or intronic regions. We used a network medicine approach to associate breast cancer risk single nucleotide polymorphisms (SNPs) with transcript abundance in formalin fixed paraffin embedded (FFPE) breast tissue. Identification of expression quantitative loci (eQTLs) may help to better understand the regulatory mechanisms by which these risk variants influence breast cancer susceptibility. Method: We identified invasive postmenopausal breast cancer cases in the Nurses’ Health Study (NHS) diagnosed from 1990-2004 with GWAS data and sufficient RNA for expression profiling in breast tumor and normal adjacent breast tissue. RNA was extracted using the Qiagen AllPrep RNA isolation kit, amplified using the NuGen Ovation FFPE WTA kit, and profiled using the Affymetrix Human Transcriptome Array (HTA 3.0v1). The HTA includes 6,892,960 features for measuring gene expression, alternative splicing, coding SNPs, and noncoding transcripts. After filtering and removing probes with a low dynamic range in our samples, we included 25,000 gene expression probes in our QTL analyses. We mapped these probes to genes using hg19. Results: Analyses were conducted separately for 376 breast tumor and 274 normal adjacent samples. We conducted quality control analyses, corrected for assay plate-to-plate variation and included patient's age at diagnosis and year of diagnosis as covariates in the multivariate linear regression model. We identified 11 trans eQTLs in normal adjacent breast tissue, 11 trans eQTLs in estrogen receptor (ER)+ breast tumor samples, and 12 trans eQTLs in ER- breast tumor samples (permutation adjusted p-value&amp;lt;0.05). We also developed a new method, functional quantitative trait loci (fQTL) analysis, to gain additional pathway insight into genetic associations important in breast cancer. In the fQTL analysis we tested for the association between SNPs and the expression of gene functional classes and pathways, evaluating the hypothesis that SNPs may also be associated with regulation of processes in addition to individual genes. Using a cutoff of false discovery rate &amp;lt;10%, we identified 2 SNPs associated with 2 Gene Ontology Molecular Functions in normal adjacent breast tissue, 1 SNP associated with 5 Molecular Functions in ER- tumor samples but no significant SNP associations in ER+ tumor samples. Integrated eQTL and fQTL analyses and variant annotation are ongoing. Conclusion: In summary, our results provide functional insights on the underlying biology of loci identified in breast cancer GWAS in the specimen type that is most impactful in translation to clinical practice. Identification of gene transcripts that can be measured in FFPE tissue and are associated with breast cancer risk loci is critical in understanding the mechanism by which these variants affect risk and mediate disease processes. Citation Format: Alejandro Quiroz-Zarate, Benjamin J. Harshfield, Rong Hu, Nick Knoblauch, Andrew H. Beck, Vincent Carey, Susan E. Hankinson, Rulla M. Tamimi, David J. Hunter, John Quackenbush, Aditi Hazra. QTLs in breast tumor and breast normal adjacent FFPE specimens from the Nurses’ Health Study. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3269. doi:10.1158/1538-7445.AM2014-3269