Meta-analysis of estrogen response in MCF-7 distinguishes early target genes involved in signaling and cell proliferation from later target genes involved in cell cycle and DNA repair

ABSTRACT: BACKGROUND: Many studies have been published outlining the global effects of 17 beta-estradiol (E2) on gene expression in human epithelial breast cancer derived MCF-7 cells. These studies show large variation in results, reporting between ~100 and ~1500 genes regulated by E2, with poor overlap. RESULTS: We performed a meta-analysis of these expression studies, using the Rank product method to obtain a more accurate and stable list of the differentially expressed genes, and of pathways regulated by E2. We analyzed 9 time-series data sets, concentrating on response at 3-4 hrs (early) and at 24 hrs (late). We found >1000 statistically significant probe sets after correction for multiple testing at 3-4 hrs, and >2000 significant probe sets at 24 hrs. Differentially expressed genes were examined by pathway analysis. This revealed 15 early response pathways, mostly related to cell signaling and proliferation, and 20 late response pathways, mostly related to breast cancer, cell division, DNA repair and recombination. CONCLUSIONS: Our results show that meta-analysis identified more differentially expressed genes than the individual studies, and that these genes act together in networks. These results provide new insight into E2 regulated mechanisms, especially in the context of breast cancer

Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies

Zero to one: normal derived human ER+ cells in culture-proliferating

Cell culture technology is used to model structural and functional properties of human organs under normal and pathological conditions “in a dish”. The most obvious reason to culture human breast-derived cells is our fundamental desire to understand and ultimately treat breast cancer. Highly reproducible serum-free formulations for long-term propagation of normal human breast epithelial cells have existed for more than three decades and have served to complement the insight gained from a vast number of established breast cancer cell lines. The unspoken dichotomy in the experimental approach, however, has lied in the puzzling fact that normal-derived cells show a more myoepithelial expression profile, while breast cancer cells show more of a luminal profile making these difficult to compare experimentally. Moreover, normal estrogen receptor positive (ER+) luminal cells, thought to be equivalents to the most frequent form of human breast cancer, the ER+ subtype, completely fail to grow under standard culture conditions. One might choose to ignore this fact since breast homeostasis relies on a stem cell hierarchy and stem cells reside in the myoepithelial compartment which, if given the right conditions, can differentiate into ER+ luminal cells. The problem with this is that myoepithelial cells in culture, for unknown reasons, fail to behave like myoepithelial cells in vivo. This review summarizes some of the progress that has been made in the field with regard to the ER+ luminal breast epithelial lineage, especially within a human context, and its relevance to human breast cancer

Zero to one:normal derived human ER+ cells in culture-proliferating

Cell culture technology is used to model structural and functional properties of human organs under normal and pathological conditions “in a dish”. The most obvious reason to culture human breast-derived cells is our fundamental desire to understand and ultimately treat breast cancer. Highly reproducible serum-free formulations for long-term propagation of normal human breast epithelial cells have existed for more than three decades and have served to complement the insight gained from a vast number of established breast cancer cell lines. The unspoken dichotomy in the experimental approach, however, has lied in the puzzling fact that normal-derived cells show a more myoepithelial expression profile, while breast cancer cells show more of a luminal profile making these difficult to compare experimentally. Moreover, normal estrogen receptor positive (ER+) luminal cells, thought to be equivalents to the most frequent form of human breast cancer, the ER+ subtype, completely fail to grow under standard culture conditions. One might choose to ignore this fact since breast homeostasis relies on a stem cell hierarchy and stem cells reside in the myoepithelial compartment which, if given the right conditions, can differentiate into ER+ luminal cells. The problem with this is that myoepithelial cells in culture, for unknown reasons, fail to behave like myoepithelial cells in vivo. This review summarizes some of the progress that has been made in the field with regard to the ER+ luminal breast epithelial lineage, especially within a human context, and its relevance to human breast cancer

CXXC5 as an unmethylated CpG dinucleotide binding protein contributes to estrogen-mediated cellular proliferation.

Evidence suggests that the CXXC type zinc finger (ZF-CXXC) protein 5 (CXXC5) is a critical regulator/integrator of various signaling pathways that include the estrogen (E2)-estrogen receptor α (ERα). Due to its ZF-CXXC domain, CXXC5 is considered to be a member of the ZF-CXXC family, which binds to unmethylated CpG dinucleotides of DNA and through enzymatic activities for DNA methylation and/or chromatin modifications generates a chromatin state critical for gene expressions. Structural/functional features of CXXC5 remain largely unknown. CXXC5, suggested as transcription and/or epigenetic factor, participates in cellular proliferation, differentiation, and death. To explore the role of CXXC5 in E2-ERα mediated cellular events, we verified by generating a recombinant protein that CXXC5 is indeed an unmethylated CpG binder. We uncovered that CXXC5, although lacks a transcription activation/repression function, participates in E2-driven cellular proliferation by modulating the expression of distinct and mutual genes also regulated by E2. Furthermore, we found that the overexpression of CXXC5, which correlates with mRNA and protein levels of ERα, associates with poor prognosis in ER-positive breast cancer patients. Thus, CXXC5 as an unmethylated CpG binder contributes to E2-mediated gene expressions that result in the regulation of cellular proliferation and may contribute to ER-positive breast cancer progression

Analysis of the significance of miRNAs of the miRNA-200 family in the malignant phenotype of glioblastoma

The miR200 family has been described to exert tumor suppressing functions in different malignant epithelial tumors, and their down regulation has been associated with aggressiveness, metastatic disease, tumor progression, chemoresistance und worse prognosis. In glioblastoma, some members of the miR200 family have been shown to be expressed at very low levels, and this phenomenon has been associated to poor prognosis. Even though a role of the miRNA 200 family in glioblastomas has been suggested, no detailed data has been provided regarding differences in functional effects among their two strands. In other terms, it has not yet been established which of the two strands is functional active, and if dysregulation of isolated miRNAs of this family has relevant functional effects. For this purpose, U-87 MG and U-251 MG cells were transfected with 3p and 5p miRNA mimics of the miR200 family, and functional assays as well as next generation sequencing of RNA samples after transfection were performed. Results showed that glioblastoma cell lines express lower levels of the 3p strands of the miR200 family members compared to glioma biopsy samples and non-neoplastic brain tissue, and that inducing overexpression of these strands leads to a decrease in proliferation and increase in apoptosis in U-87MG and U-251 MG cells, as well as a decrease in the expression of ZEB1 and ZEB2. Furthermore, NGS analyses showed a functional clustering of cells overexpressing the 3p strands in two groups according to their seed sequences, with clear separation of cells overexpressing the 5p strands. 3p overexpression caused upregulation of G2/ M DNA damage checkpoint and E2F target genes. Also, targets of the c-myc and NFkß signaling pathways where up- and targets of the CDH1 gene and of hypoxia response (including HIF1α) were downregulated. In conclusion, the findings of this work suggest that the 3p strands of the miR200 family carry tumor suppressive functions in gliomas by interacting with major pathogenic pathways implicated in DNA damage/ repair, cell cycle, cell viability, cell motility/ adhesion and hypoxia response

INFORMATION INTEGRATION APPROACHES FOR INVESTIGATING ESTROGEN RECEPTOR MEDIATED TRANSCRIPTION

Estrogen plays essential roles in the function of normal physiology and diseases. Its effects are mainly mediated through two intracellular estrogen receptors, ERα and ERβ, which belong to a family of nuclear receptors (NRs) functioning as transcription regulators. In the first part of this thesis, we aim to derive a holistic view of the transcription machineries at estrogen-responsive genes and further, to reveal different mechanisms of estrogen-mediated transcription regulation. In order to achieve this, we integrated and systematically dissected a variety of genome-wide high-throughput datasets, including gene expression arrays, ChIP-seq, GRO-seq, and ChIA-PET. Our analyses have led to the following novel findings: In the absence of the ligand, most of the estrogen-responsive genes assumed a high-order chromatin configuration that involved Pol II, ERα and ERα-pioneer factors. Without the ligand, estrogen-induced genes showed active transcription at promoters but failed to elongate into gene bodies, and such a pause was lifted after estrogen treatment. However, the estrogen-repressed genes showed coordinated transcription at promoters and gene bodies in the absence and presence of estrogen. Through information integration, we inferred that, for estrogen-repressed genes, the majority of the high-order chromatin complexes containing actively transcribed genes were disrupted after estrogen treatment. The analyses led to the hypothesis that one mechanism for estrogen-mediated repression is through disrupting the original transcription-favoring chromatin structures. Further, nuclear receptors such as ERs interact with co-regulators to regulate gene transcription. Understanding the mechanism of action of co-regulator proteins—which do not bind DNA directly, but exert their effects by binding to transcription factors—is important for the study of normal physiology as well as diseased conditions. However, due to the nature of detecting indirect protein-DNA interaction, ChIP-seq signals from co-regulators can be relatively weak and thus biologically meaningful interactions remain difficult to identify. In the second part of this thesis, we investigated and compared different machine learning approaches to integrate multiple types of genomic and transcriptomic information derived from our experiments and from public databases. This helped us to overcome the difficulty of identifying functional DNA binding sites of the co-regulator SRC-1 in the context of estrogen response. Our results indicate that supervised learning with the naïve Bayes algorithm significantly enhanced the peak calling of weak ChIP-seq signals and outperformed other machine learning algorithms. Our integrative approach revealed many potential ERα/SRC-1 DNA binding sites that would otherwise be missed by conventional peak calling algorithms with default settings