Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Edebiyat Fakültesi, Biyolojik Bilimler Bölümü, Türkiye
Tezin Onay Tarihi: 2016
Öğrenci: SIRMA DAMLA USER
Danışman: MESUT MUYAN
Özet:17β-estradiol (E2), the most potent estrogen hormone, induces cellular responses primarily through Estrogen Receptor-alpha (ERα), which is a transcription factor. Interfering E2 signaling indicates that E2 is mitogenic for cells, exemplified by MCF7 cells derived from breast adenocarcinoma, synthesizing ERα endogenously. Studies used exogenous expression of ERα in ERα-negative cell lines to examine structural/functional properties of the receptor. What was unexpected from these studies is the observation that E2 treatment represses cellular proliferation. However, mechanism(s) of this paradoxical phenomenon remains unknown. Methylation is an important epigenetic DNA modification. Changes in methylation alter gene expressions critical for cellular proliferation/differentiation, embryonic development, genomic imprinting and cancer. We therefore hypothesize that distinct methylation statuses of responsive genes’ regulatory regions underlie differential gene expressions, and hence, proliferative and anti-proliferative effects of E2 in cell models. To test this prediction, we generated a cell model stably expressing ERα in MDAMB231 breast cancer cell line. Of the monoclones synthesizing ERα, the MDA-ERα5, based on expected ERα functions, was selected as the cell model to comparatively assess the E2 effects on changes in methylome and transcriptome profiles to those observed in MCF7 cells. Our studies suggest that cell models have cell-specific methylation patterns for the same genomic region at which E2 induces distinct alterations and differentially modulates gene expressions. However, due to the existence of variations among experimental replicates, establishing a correlation between the methylation statuses to gene expression profile of cell lines appears to be immature. An increase in sample size could circumvent this issue.