P3-04-03: Identification of Hormone-Responsive Genes as Biomarkers for Menstrual Cycle Phases and Menopausal Status.
Authors: J Wang, O Lee, R Heinz, D Ivancic, D Scholtens, RT Chatterton, SA Khan
Journal: Cancer Research (2011)

Abstract Background The definition and validation of biomarkers in archived breast tissue samples for prognostic research is limited by the fact that the exact menstrual cycle phases and menopausal status at the time of tissue sampling is often unknown or not accurate by patient survey. Biomarkers that vary with menstrual cycle phases in premenopausal women would be difficult to standardize. There are also significant differences in gene expression in pre- and post-menopausal women. Therefore, menstrual cycle fluctuation and menopausal status need to be considered for all candidate biomarkers as part of the validation process. The aim of this study is to identify genes responsive to different hormones to accurately define menstrual cycle phases and menopausal status. Methods: We studied gene expression profiles of 18 random fine-needle aspirate (rFNA) samples from unaffected contralateral breast (8 pre-menopausal, mean age 44.5; 10 post-menopausal, mean age 58.8) and investigated the correlation between gene expression and serum hormone levels of estradiol (E2), progesterone (P4) and follicle stimulating hormone (FSH). Genes that were highly correlated with the serum levels of each hormone (Pearson correlation coefficient r &amp;gt; 0.60) were considered as specific hormone-responsive genes (P &amp;lt; 0.0085). The combined gene profiles of hormone-responsive genes were used to dissect samples in different menstrual cycle phases and menopausal status. Selected genes related to mammary gland development and hormone regulation based on gene function and gene network analysis were validated using qRT-PCR in 18 original rFNA samples and in 28 independent samples. Results: From 35,964 genes and 12,838 undesignated transcripts, we identified genes/transcripts highly correlated with E2 (1091 genes), P4 (127 genes) or FSH (58 genes). The most significantly correlated genes in each group were selected to define four panels of genes: Panel A-21genes stimulated by E2 (r &amp;gt; 0.78); Panel B-22 genes stimulated by P4 (r &amp;gt; 0.75); Panel C-7 genes stimulated by FSH (r &amp;gt; 0.65); and Panel D-10 genes suppressed by FSH (r &amp;lt; −0.65). Hierarchical clustering analysis using the combination of gene panels dissected the samples into four clusters based on three phases of menstrual cycles and post-menopausal status. Specifically, high panel C and low panel D expression segregated post- from pre-menopausal samples. Low expression of panel A and B genes dissected early follicular phase from late follicular and luteal phases, while higher expression of panel B genes discriminated luteal phase from late follicular samples. Conclusion: Our results indicate that the menstrual cycle phases and menopausal status determined by age, patient survey and serum hormone concentrations are reflected in the expression of specific gene sets in the normal breast. The combination of hormone-responsive gene panels would allow the classification of breast samples regarding to the menstrual phases and menopausal status at the time of sampling. It would also facilitate the selection and validation of breast cancer biomarkers that are independent of menstrual cycle fluctuation and menopausal variation for clinical use. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P3-04-03.