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In the cell nucleus, each chromosome is confined to a chromosome territory. This spatial organization of chromosomes plays a crucial role in gene regulation and genome stability. An additional level of organization has been discovered at the chromosome scale: the spatial segregation into open and closed chromatins to form two genome-wide compartments. Although considerable progress has been made in our knowledge of chromatin organization, a fundamental issue remains the understanding of its dynamics, especially in cancer. To address this issue, we performed genome-wide mapping of chromatin interactions (Hi-C) over the time after estrogen stimulation of breast cancer cells. To biologically interpret these interactions, we integrated with estrogen receptor α (ERα) binding events, gene expression and epigenetic marks. We show that gene-rich chromosomes as well as areas of open and highly transcribed chromatins are rearranged to greater spatial proximity, thus enabling genes to share transcriptional machinery and regulatory elements. At a smaller scale, differentially interacting loci are enriched for cancer proliferation and estrogen-related genes. Moreover, these loci are correlated with higher ERα binding events and gene expression. Taken together these results reveal the role of a hormone--estrogen--on genome organization, and its effect on gene regulation in cancer.

One big limitation of computational tools for analyzing ChIP-seq data is that most of them ignore non-unique tags (NUTs) that match the human genome even though NUTs comprise up to 60% of all raw tags in ChIP-seq data. Effectively utilizing these NUTs would increase the sequencing depth and allow a more accurate detection of enriched binding sites, which in turn could lead to more precise and significant biological interpretations. In this study, we have developed a computational tool, LOcating Non-Unique matched Tags (LONUT), to improve the detection of enriched regions from ChIP-seq data. Our LONUT algorithm applies a linear and polynomial regression model to establish an empirical score (ES) formula by considering two influential factors, the distance of NUTs to peaks identified using uniquely matched tags (UMTs) and the enrichment score for those peaks resulting in each NUT being assigned to a unique location on the reference genome. The newly located tags from the set of NUTs are combined with the original UMTs to produce a final set of combined matched tags (CMTs). LONUT was tested on many different datasets representing three different characteristics of biological data types. The detected sites were validated using de novo motif discovery and ChIP-PCR. We demonstrate the specificity and accuracy of LONUT and show that our program not only improves the detection of binding sites for ChIP-seq, but also identifies additional binding sites.

Homodimerization of RON (MST1R), a receptor tyrosine kinase, usually occurs in cells stimulated by a ligand and leads to the downstream activation of signaling pathways. Here we report that bladder cancer cells, in response to physiological stress, use an alternative mechanism for signaling activation. Time-course studies indicated that RON migrated directly from the membrane to the nucleus of bladder cancer cells in response to serum starvation. Biochemical and genetic studies implied that this nuclear internalization was complexed with epidermal growth factor receptor (EGFR) and required the docking of importins. In vivo analysis confirmed that nuclear RON was present in 38.4% (28/73) of primary bladder tumors. Chromatin immunoprecipitation (ChIP) on microarray analysis further revealed that this internalized complex bound to at least 134 target genes known to participate in three stress-responsive networks: p53, stress-activated protein kinase/c-jun N-terminal kinase and phosphatidylinositol 3-kinase/Akt. These findings suggest that RON, in a complex with EGFR, acts as a transcriptional regulator in response to acute disturbances (e.g. serum starvation) imposed on cancer cells. In an attempt to re-establish homeostasis, these cells bypass regular mechanisms required by ligand stimulation and trigger the RON-directed transcriptional response, which confers a survival advantage. [ABSTRACT FROM PUBLISHER]

Background: Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results: In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7- T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions: Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases. [ABSTRACT FROM AUTHOR]

While arsenic trioxide (As2O3) is an infamous carcinogen, it is also an effective chemotherapeutic agent for acute promyelocytic leukemia and some solid tumors. In human epidermoid carcinoma A431 cells, we found that As2O3 induced cell death in time- and dose-dependent manners. Similarly, dependent regulation of the p21 WAF1/ CIP1 (p21) promoter, mRNA synthesis, and resultant protein expression was also observed. Additionally, transfection of a small interfering RNA of p21 could block the As2O3-induced cell growth arrest. The As2O3-induced p21 activation was attenuated by inhibitors of EGFR and MEK in a dose-dependent manner. Using a reporter assay, we demonstrated the involvement of the EGFR-Ras-Raf-ERK1/2 pathway in the promoter activation. In contrast, JNK inhibitor enhanced the As2O3-induced p21 activation, also in a dose-dependent fashion. Over-expression of a dominant negative JNK plasmid likewise also enhanced this activation. Furthermore, MEK inhibitor attenuated the anti-tumor effect of As2O3. In contrast, in combination with JNK inhibitor and As2O3 enhanced cellular cytotoxicity. Therefore, we conclude that in A431 cells the ERK1/2 and JNK pathways might differentially contribute to As2O3-induced p21 expression and then due to cellular cytotoxicity. [ABSTRACT FROM AUTHOR]

The current concept of epigenetic repression is based on one repressor unit corresponding to one silent gene. This notion, however, cannot adequately explain concurrent silencing of multiple loci observed in large chromosome regions. The long-range epigenetic silencing (LRES) can be a frequent occurrence throughout the human genome. To comprehensively characterize the influence of estrogen signaling on LRES, we analyzed transcriptome, methylome, and estrogen receptor alpha (ESR1)-binding datasets from normal breast epithelia and breast cancer cells. This "omics" approach uncovered 11 large repressive zones (range, 0.35⇔/45.98 megabases), including a 14-gene cluster located on 16p11.2. In normal cells, estrogen signaling induced transient formation of multiple DNA loops in the 16p11.2 region by bringing 14 distant loci to focal ESR1-docking sites for coordinate repression. However, the plasticity of this free DNA movement was reduced in breast cancer cells. Together with the acquisition of DNA methylation and repressive chromatin modifications at the 16p11.2 loci, an inflexible DNA scaffold may be a novel determinant used by breast cancer cells to reinforce estrogen-mediated repression. [ABSTRACT FROM AUTHOR]