Abstract P4-04-06: Study of the mutational landscape of normal and pregnant breast to predict pregnancy-associated breast cancer risk

Abstract

Abstract Background: Amongst the various risk factors for breast cancer (BC), the molecular basis which may explain the correlation between age at first full-term and breast cancer risks is still understudied. Epidemiology studies indicate that an early first full-term pregnancy (before 25 years of age) confers a significant level of protection towards the development of post-menopausal BC compared to the risk in nulliparous or late-parous women. On the other hand, any pregnancy relates to a higher risk in developing cancer during or within one year of pregnancy (pregnancy-associated breast cancer, PABC). Thus, the relation between age of pregnancy and breast cancer risk may be too difficult to explain using only epidemiology data. Aims of the study: With our research study, we aim to study a cohort of 60 normal breast samples of nulliparous and age-matched early- and late-parous women collected from Komen Tissue Bank, University of Indiana, and to create for the first time a mathematical model of cell clone expansion in the normal breast growth. This will allow us to determine how the rates of both cancer drivers, passenger mutations and genetic variations are affected by pregnancy. We then aim to translate this in cancer tissues, and to determine how the rate of the same mutations in both pregnancy and non pregnancy-associated cancers (post-menopausal). At the same time, we intend to create a mouse model which will be used to further validate our model, where driver mutations will be induced in the mammary epithelium of pregnant mice of different ages. This will allow us to test our model of growth of a mutated clone in a pregnancy environment, and to determine what are the molecular changes in the pregnant mammary gland which can trigger a different BC risk in the early-parous cohort. Results: To examine the mutational landscape in the normal parous and nulliparous women, we extracted DNA from laser-capture microdissected epithelium and the stroma, the latter of which will be used to eliminate germ line mutations. We are currently analysing the results from Whole Genome Sequencing at 30x 100pe on a MGISEQ2000 platform on a first set of samples (two nulliparous samples and two age-matched parous samples from both early and late pregnancy). Our procedure for processing and analysis of this data follows the Broad Institute's “GATK Best Practice Guidelines” for use of next generation sequencing (NGS) data. Based on the collected data, we plan to continue with targeted sequencing or whole genome sequencing on the remaining samples. Conclusions: Our study will provide novel information on which areas of the genome are mostly mutated or altered in the normal breast, and will indicate how mutated cells, including mutations in driver genes for breast cancer, and genetic alterations change in the contest of pregnancy. With the mathematical model of clone growth/extinction, we intend to explain how different ages of pregnancy can significantly alter the clone composition in the normal breast and result in a different probability of developing breast cancer. Citation Format: Cereser B, Tabassum N, Carter P, Del Bel Belluz L, Stebbing J. Study of the mutational landscape of normal and pregnant breast to predict pregnancy-associated breast cancer risk [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-04-06.