Abstract 1818: Gene expression profiling to understand stages in breast cancer development and progression: importance of tissue sampling and context .
Authors: Sun Xuezheng , Lockhart Alexandre , Gierach Gretchen L. , Sherman Mark , Figueroa Jonine D. , Schneider Sallie S. , Jerry D. Joseph , Troester Melissa A. 
Published: August 2014

Background: During the past decade, gene expression profiling has been widely employed to understand the heterogeneity of tumor biology. Novel biomarkers and signatures discovered using these techniques have impacted tumor diagnosis and prognosis, and have led to important insights into etiology. However, application of mRNA profiling to define mechanisms mediating breast cancer risk factor exposure remains underexplored. Identifying mediating pathways of breast carcinogenesis by tumor tissue profiling may be problematic because genomic instability may obscure causal changes. Methods: To evaluate how etiologically relevant signatures are expressed during different stages of carcinogenesis, we analyzed gene expression data from three types of whole tissue samples: benign tissues from non-diseased breasts (“normal”), benign tissues adjacent to cancer (“cancer-associated”), and tumors. We assessed three published signatures (Age, Obesity, and Parity, originally defined in “normal” breast tissues from healthy women) in 149 tumor tissues and paired cancer-adjacent benign tissues from the Polish Women's Breast Cancer Study. Associations of chronological age, body mass index and parity with their related mRNA signatures were evaluated. Results: The association between Obesity signature and actual obesity status showed a marked gradient from normal breast tissues (obese vs. non-obese: OR=5.78, p=0.0009) to cancer-adjacent and tumor tissues (cancer-adjacent: OR=1.85, p=0.09; tumor: OR=0.80, p=0.54). A similar pattern was also observed for Age signature (normal: OR [&lt;40 y vs. ≥ 40y] =5.03, p&lt;0.0001; cancer-adjacent: OR [&lt;45 y vs. ≥ 45y] =6.97, p=0.005; tumor: OR=0.58 p=0.35) and Parity signature (parous vs. nulliparous, normal: OR =3.95, p=0.0002; cancer-adjacent: OR=1.38, p=0.44; tumor: OR=1.20, p=0.65). Simulation studies further demonstrated that the association strength was influenced by the proportion of risk factor-associated genes that were dysregulated during carcinogenesis. Differences in cellular composition between samples may also affect association strength. Conclusions: These results suggest that associations between risk factors and gene signatures are strongest in benign tissues from non-diseased breasts and may be weakened by the responses of cancer-adjacent issues to cancer progression, and by the effects of genomic instability in tumors. While tumor tissue is readily available in many epidemiologic studies, use of this tissue for studying etiologically relevant pathways may have important limitations. Identification of etiologically relevant pathways may rely on studies of well-annotated tissues from women without cancer.

Citation Format: Xuezheng Sun, Alexandre Lockhart, Gretchen L. Gierach, Mark Sherman, Jonine D. Figueroa, Sallie S. Schneider, D. Joseph Jerry, Melissa A. Troester. Gene expression profiling to understand stages in breast cancer development and progression: importance of tissue sampling and context . [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 1818. doi:10.1158/1538-7445.AM2013-1818

Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.