Abstract 5303: Biomarker development for the evaluation of molecular circadian desynchrony in a single measurement.

Most organisms possess an endogenous circadian clock which is responsible for the temporal organization of rhythmic biochemical and metabolic processes. At the molecular level, rhythmicity in peripheral tissues is maintained by a core set of circadian genes, which in turn influence the expression programs of a large number of additional genes. Disruption in circadian rhythms has been implicated in a variety of human diseases, including cancer. However, the dynamic nature of the circadian system complicates study of molecular rhythms, and this is compounded by the inherent tissue-specificity of biological rhythms, which preclude the use of surrogate tissue. Since serial sampling of target peripheral tissue is unrealistic in human studies, our goal is to produce a model that will allow single-measurement evaluation of molecular desynchrony in archived tissue by identifying in-phase gene expression signatures in circadian gene pairs that vary over time on an absolute scale, but do not vary relative to one another. Using next-generation sequencing technologies, we have annotated the complete circadian transcriptome in primary, pre-stasis human mammary epithelial cells (HMECs) with sampling every 4-hours over a 24-hour time period. Cycling transcripts were identified using the non-parametric JTK_CYCLE algorithm, with further stratification according to circadian phase. In-phase transcript pairs were identified by calculating the standard error of the mean difference (SEM) in normalized gene expression across all time points for all pairwise comparisons among genes within each phase. Candidate pairs were then selected for further investigation, both in vitro and in normal and tumor tissue profiling experiments extracted from publicly available datasets, in order to evaluate their utility as biomarkers of tumor-associated desynchrony. Here we present the example of one such pair: IFNGR2 and PER1. In our primary HMEC model, IFNGR2 expression varies in a circadian manner over time, but maintains a consistent relationship with the core circadian gene PER1 with an approximately two-fold difference at each time-point (mean ratio = 2.29, SEM = 0.2280). In array data from single time point measurements of human mammary tissue (Array Express accession number E-TABM-276), the relationship between IFNGR2 and PER1 expression is similar to the tissue culture model in normal tissue, but becomes increasingly desynchronous in tissue with cystic changes (mean ratio = 3.83, SEM = 0.5717, P = 0.0422), and invasive carcinoma tissue (mean ratio=9.12, SEM = 0.9367, P = 0.0002). This data provides proof of principle that objective, quantitative biomarkers of molecular circadian disruption can be identified. In addition, these biomarkers can be useful for single measurement analysis, and are shown to correlate with the progression from normal tissue to invasive carcinoma. Citation Format: Tracy L. Mandichak, Joseph C. Combs, Elizabeth J. Ferree, Aaron E. Hoffman. Biomarker development for the evaluation of molecular circadian desynchrony in a single measurement. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5303. doi:10.1158/1538-7445.AM2013-5303