Global analysis of ligand sensitivity of estrogen inducible and suppressible genes in MCF7/BUS breast cancer cells by DNA microarray.
نویسندگان
چکیده
To obtain comprehensive information on 17beta-estradiol (E2) sensitivity of genes that are inducible or suppressible by this hormone, we designed a method that determines ligand sensitivities of large numbers of genes by using DNA microarray and a set of simple Perl computer scripts implementing the standard metric statistics. We used it to characterize effects of low (0-100 pM) concentrations of E2 on the transcriptome profile of MCF7/BUS human breast cancer cells, whose E2 dose-dependent growth curve saturated with 100 pM E2. Evaluation of changes in mRNA expression for all genes covered by the DNA microarray indicated that, at a very low concentration (10 pM), E2 suppressed approximately 3-5 times larger numbers of genes than it induced, whereas at higher concentrations (30-100 pM) it induced approximately 1.5-2 times more genes than it suppressed. Using clearly defined statistical criteria, E2-inducible genes were categorized into several classes based on their E2 sensitivities. This approach of hormone sensitivity analysis revealed that expression of two previously reported E2-inducible autocrine growth factors, transforming growth factor alpha and stromal cell-derived factor 1, was not affected by 100 pM and lower concentrations of E2 but strongly enhanced by 10 nM E2, which was far higher than the concentration that saturated the E2 dose-dependent growth curve of MCF7/BUS cells. These observations suggested that biological actions of E2 are derived from expression of multiple genes whose E2 sensitivities differ significantly and, hence, depend on the E2 concentration, especially when it is lower than the saturating level, emphasizing the importance of characterizing the ligand dose-dependent aspects of E2 actions.
منابع مشابه
Effect of 17-? Estradiol on the Expression of Inducible Nitric oxide Synthase in Parent and Tamoxifen Resistant T47D Breast Cancer Cells
Indirect evidence suggests that estrogen is involved in the etiology of breast cancer. Estrogen is also thought to modulate nitric oxide (NO) in human breast tumor tissue via regulation of inducible nitric oxide synthase (iNOS). Objectives of this study were to determine whether estradiol (E2) affects iNOS expression level in breast cancer cells and to study the effect of various concentrations...
متن کاملEffect of 17-? Estradiol on the Expression of Inducible Nitric oxide Synthase in Parent and Tamoxifen Resistant T47D Breast Cancer Cells
Indirect evidence suggests that estrogen is involved in the etiology of breast cancer. Estrogen is also thought to modulate nitric oxide (NO) in human breast tumor tissue via regulation of inducible nitric oxide synthase (iNOS). Objectives of this study were to determine whether estradiol (E2) affects iNOS expression level in breast cancer cells and to study the effect of various concentrations...
متن کاملTHE EFFECT OF QUINACRINE ON THE EXPRESSION OF WNT3A GENE IN MDA-MB 231 AND MCF7 BREAST CANCER CELL LINES
Background & Aims: Triple-negative breast cancer cells refer to any breast cancer that does not express the genes for the estrogen, progesterone, and HER2 receptors. The Wnt signaling pathway is important in the development and progression of various types of cancers. Quinacrine, a derivative of 9-aminoacridine, has been shown to inhibit the growth of several types of cancer cells. In this stud...
متن کاملBioinformatics-Based Prediction of FUT8 as a Therapeutic Target in Estrogen Receptor-Positive Breast Cancer
Abstract Introduction: Estrogen receptor-positive (ER-positive) breast cancer is a subgroup of breast tumors that is more likely to respond to hormone therapy. ER-positive and ER- negative breast cancers tend to show different patterns of metastasis because of different signaling cascade and genes that are activated by estrogen response. Genetic factors can contribute to high rates of metastas...
متن کاملDiagnosis of Breast Cancer Subtypes using the Selection of Effective Genes from Microarray Data
Introduction: Early diagnosis of breast cancer and the identification of effective genes are important issues in the treatment and survival of the patients. Gene expression data obtained using DNA microarray in combination with machine learning algorithms can provide new and intelligent methods for diagnosis of breast cancer. Methods: Data on the expression of 9216 genes from 84 patients across...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Proceedings of the National Academy of Sciences of the United States of America
دوره 100 24 شماره
صفحات -
تاریخ انتشار 2003