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Sukocheva OA, Lukina E, Friedemann M, Menschikowski M, Hagelgans A, Aliev G. The crucial role of epigenetic regulation in breast cancer anti-estrogen resistance: Current findings and future perspectives. Semin Cancer Biol 2022; 82:35-59. [PMID: 33301860 DOI: 10.1016/j.semcancer.2020.12.004] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/22/2020] [Accepted: 12/03/2020] [Indexed: 02/07/2023]
Abstract
Breast cancer (BC) cell de-sensitization to Tamoxifen (TAM) or other selective estrogen receptor (ER) modulators (SERM) is a complex process associated with BC heterogeneity and the transformation of ER signalling. The most influential resistance-related mechanisms include modifications in ER expression and gene regulation patterns. During TAM/SERM treatment, epigenetic mechanisms can effectively silence ER expression and facilitate the development of endocrine resistance. ER status is efficiently regulated by specific epigenetic tools including hypermethylation of CpG islands within ER promoters, increased histone deacetylase activity in the ER promoter, and/or translational repression by miRNAs. Over-methylation of the ER α gene (ESR1) promoter by DNA methyltransferases was associated with poor prognosis and indicated the development of resistance. Moreover, BC progression and spreading were marked by transformed chromatin remodelling, post-translational histone modifications, and expression of specific miRNAs and/or long non-coding RNAs. Therefore, targeted inhibition of histone acetyltransferases (e.g. MYST3), deacetylases (e.g. HDAC1), and/or demethylases (e.g. lysine-specific demethylase LSD1) was shown to recover and increase BC sensitivity to anti-estrogens. Indicated as a powerful molecular instrument, the administration of epigenetic drugs can regain ER expression along with the activation of tumour suppressor genes, which can in turn prevent selection of resistant cells and cancer stem cell survival. This review examines recent advances in the epigenetic regulation of endocrine drug resistance and evaluates novel anti-resistance strategies. Underlying molecular mechanisms of epigenetic regulation will be discussed, emphasising the utilization of epigenetic enzymes and their inhibitors to re-program irresponsive BCs.
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Affiliation(s)
- Olga A Sukocheva
- Discipline of Health Sciences, College of Nursing and Health Sciences, Flinders University, Bedford Park, South Australia, 5042, Australia.
| | - Elena Lukina
- Discipline of Biology, College of Sciences, Flinders University, Bedford Park, South Australia, 5042, Australia
| | - Markus Friedemann
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital `Carl Gustav Carus`, Technical University of Dresden, Dresden 01307, Germany
| | - Mario Menschikowski
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital `Carl Gustav Carus`, Technical University of Dresden, Dresden 01307, Germany
| | - Albert Hagelgans
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital `Carl Gustav Carus`, Technical University of Dresden, Dresden 01307, Germany
| | - Gjumrakch Aliev
- Sechenov First Moscow State Medical University (Sechenov University), Moscow, 119991, Russia; Institute of Physiologically Active Compounds, Russian Academy of Sciences, Chernogolovka, 142432, Russia; Federal State Budgetary Institution «Research Institute of Human Morphology», 3, Tsyurupy Str., Moscow, 117418, Russian Federation; GALLY International Research Institute, San Antonio, TX, 78229, USA.
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Gerrard DL, Wang Y, Gaddis M, Zhou Y, Wang J, Witt H, Lin S, Farnham PJ, Jin VX, Frietze SE. Three-dimensional analysis reveals altered chromatin interaction by enhancer inhibitors harbors TCF7L2-regulated cancer gene signature. J Cell Biochem 2018; 120:3056-3070. [PMID: 30548288 DOI: 10.1002/jcb.27449] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 07/18/2018] [Indexed: 11/10/2022]
Abstract
Distal regulatory elements influence the activity of gene promoters through chromatin looping. Chromosome conformation capture (3C) methods permit identification of chromatin contacts across different regions of the genome. However, due to limitations in the resolution of these methods, the detection of functional chromatin interactions remains a challenge. In the current study, we employ an integrated approach to define and characterize the functional chromatin contacts of human pancreatic cancer cells. We applied tethered chromatin capture to define classes of chromatin domains on a genome-wide scale. We identified three types of structural domains (topologically associated, boundary, and gap) and investigated the functional relationships of these domains with respect to chromatin state and gene expression. We uncovered six distinct sub-domains associated with epigenetic states. Interestingly, specific epigenetically active domains are sensitive to treatment with histone acetyltransferase (HAT) inhibitors and decrease in H3K27 acetylation levels. To examine whether the subdomains that change upon drug treatment are functionally linked to transcription factor regulation, we compared TCF7L2 chromatin binding and gene regulation to HAT inhibition. We identified a subset of coding RNA genes that together can stratify pancreatic cancer patients into distinct survival groups. Overall, this study describes a process to evaluate the functional features of chromosome architecture and reveals the impact of epigenetic inhibitors on chromosome architecture and identifies genes that may provide insight into disease outcome.
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Affiliation(s)
- Diana L Gerrard
- Biomedical Health Sciences Department, University of Vermont, Burlington, VT, USA.,Cellular, Molecular, and Biomedical Sciences Program, University of Vermont, Burlington, VT, USA
| | - Yao Wang
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Malaina Gaddis
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA.,Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Yufan Zhou
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Junbai Wang
- Department of Pathology, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway
| | - Heather Witt
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA.,Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Shili Lin
- Statistics Department, The Ohio State University, Columbus, OH, USA
| | - Peggy J Farnham
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA.,Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Victor X Jin
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Seth E Frietze
- Biomedical Health Sciences Department, University of Vermont, Burlington, VT, USA.,Cellular, Molecular, and Biomedical Sciences Program, University of Vermont, Burlington, VT, USA.,The University of Vermont Cancer Center, Burlington, VT, USA
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Liu Q, Bonneville R, Li T, Jin VX. Transcription factor-associated combinatorial epigenetic pattern reveals higher transcriptional activity of TCF7L2-regulated intragenic enhancers. BMC Genomics 2017; 18:375. [PMID: 28499350 PMCID: PMC5429574 DOI: 10.1186/s12864-017-3764-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 05/03/2017] [Indexed: 01/24/2023] Open
Abstract
Background Recent studies have suggested that combinations of multiple epigenetic modifications are essential for controlling gene expression. Despite numerous computational approaches have been developed to decipher the combinatorial epigenetic patterns or “epigenetic code”, none of them has explicitly addressed the relationship between a specific transcription factor (TF) and the patterns. Methods Here, we developed a novel computational method, T-cep, for annotating chromatin states associated with a specific TF. T-cep is composed of three key consecutive modules: (i) Data preprocessing, (ii) HMM training, and (iii) Potential TF-states calling. Results We evaluated T-cep on a TCF7L2-omics data. Unexpectedly, our method has uncovered a novel set of TCF7L2-regulated intragenic enhancers missed by other software tools, where the associated genes exert the highest gene expression. We further used siRNA knockdown, Co-transfection, RT-qPCR and Luciferase Reporter Assay not only to validate the accuracy and efficiency of prediction by T-cep, but also to confirm the functionality of TCF7L2-regulated enhancers in both MCF7 and PANC1 cells respectively. Conclusions Our study for the first time at a genome-wide scale reveals the enhanced transcriptional activity of cell-type-specific TCF7L2 intragenic enhancers in regulating gene expression. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3764-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Qi Liu
- Department of Molecular Medicine, University of Texas Health Science Center, 8403 Floyd Curl, San Antonio, TX, 78229, USA.,College of Life Science, Jilin University, Changchun, 130012, China
| | - Russell Bonneville
- Biomedical Sciences Graduate Program, The Ohio State University, Columbus, OH, 43210, USA
| | - Tianbao Li
- Department of Molecular Medicine, University of Texas Health Science Center, 8403 Floyd Curl, San Antonio, TX, 78229, USA.,College of Life Science, Jilin University, Changchun, 130012, China
| | - Victor X Jin
- Department of Molecular Medicine, University of Texas Health Science Center, 8403 Floyd Curl, San Antonio, TX, 78229, USA.
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Wu S, Han J, Liu R, Liu J, Lv H. A computational model for predicting fusion peptide of retroviruses. Comput Biol Chem 2016; 61:245-50. [PMID: 26963379 DOI: 10.1016/j.compbiolchem.2016.02.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 01/27/2016] [Accepted: 02/10/2016] [Indexed: 01/04/2023]
Abstract
As a pivotal domain within envelope protein, fusion peptide (FP) plays a crucial role in pathogenicity and therapeutic intervention. Taken into account the limited FP annotations in NCBI database and absence of FP prediction software, it is urgent and desirable to develop a bioinformatics tool to predict new putative FPs (np-FPs) in retroviruses. In this work, a sequence-based FP model was proposed by combining Hidden Markov Method with similarity comparison. The classification accuracies are 91.97% and 92.31% corresponding to 10-fold and leave-one-out cross-validation. After scanning sequences without FP annotations, this model discovered 53,946 np-FPs. The statistical results on FPs or np-FPs reveal that FP is a conserved and hydrophobic domain. The FP software programmed for windows environment is available at https://sourceforge.net/projects/fptool/files/?source=navbar.
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Affiliation(s)
- Sijia Wu
- School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Jiuqiang Han
- School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
| | - Ruiling Liu
- School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Jun Liu
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Hongqiang Lv
- School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
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Kim TW, Kim B, Kim JH, Kang S, Park SB, Jeong G, Kang HS, Kim SJ. Nuclear-encoded mitochondrial MTO1 and MRPL41 are regulated in an opposite epigenetic mode based on estrogen receptor status in breast cancer. BMC Cancer 2013; 13:502. [PMID: 24160266 PMCID: PMC4015551 DOI: 10.1186/1471-2407-13-502] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2013] [Accepted: 10/22/2013] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND MTO1 and MRPL41 are nuclear-encoded mitochondrial genes encoding a mitochondrial tRNA-modifying enzyme and a mitochondrial ribosomal protein, respectively. Although both genes have been known to have potential roles in cancer, little is known about their molecular regulatory mechanism, particularly from an epigenetic approach. In this study, we aimed to address their epigenetic regulation through the estrogen receptor (ER) in breast cancer. METHODS Digital differential display (DDD) was conducted to identify mammary gland-specific gene candidates including MTO1 and MRPL41. Promoter CpG methylation and expression in breast cancer cell lines and tissues were examined by methylation-specific PCR and real time RT-PCR. Effect of estradiol (E2), tamoxifen, and trichostatin A (TSA) on gene expression was examined in ER + and ER- breast cancer cell lines. Chromatin immunoprecipitation and luciferase reporter assay were performed to identify binding and influencing of the ER to the promoters. RESULTS Examination of both cancer tissues and cell lines revealed that the two genes showed an opposite expression pattern according to ER status; higher expression of MTO1 and MRPL41 in ER- and ER+ cancer types, respectively, and their expression levels were inversely correlated with promoter methylation. Tamoxifen, E2, and TSA upregulated MTO1 expression only in ER+ cells with no significant changes in ER- cells. However, these chemicals upregulated MRPL41 expression only in ER- cells without significant changes in ER+ cells, except for tamoxifen that induced downregulation. Chromatin immunoprecipitation and luciferase reporter assay identified binding and influencing of the ER to the promoters and the binding profiles were differentially regulated in ER+ and ER- cells. CONCLUSIONS These results indicate that different epigenetic status including promoter methylation and different responses through the ER are involved in the differential expression of MTO1 and MRPL41 in breast cancer.
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Affiliation(s)
| | | | | | | | | | | | - Han-Sung Kang
- Department of Life Science, Dongguk University-Seoul, Seoul 100-715, Korea.
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Wang R, Hsu HK, Blattler A, Wang Y, Lan X, Wang Y, Hsu PY, Leu YW, Huang THM, Farnham PJ, Jin VX. LOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq data. PLoS One 2013; 8:e67788. [PMID: 23825685 PMCID: PMC3692479 DOI: 10.1371/journal.pone.0067788] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2012] [Accepted: 05/23/2013] [Indexed: 12/21/2022] Open
Abstract
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.
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Affiliation(s)
- Rui Wang
- Department of Chemistry, Lanzhou University, Lanzhou, China
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America
| | - Hang-Kai Hsu
- Department of Molecular Medicine, Institute of Biotechnology, University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Adam Blattler
- Department of Biochemistry and Molecular Biology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America
- Genetic Graduate Group, University of California-Davis, Davis, California, United States of America
| | - Yisong Wang
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America
| | - Xun Lan
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America
| | - Yao Wang
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America
| | - Pei-Yin Hsu
- Department of Molecular Medicine, Institute of Biotechnology, University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Yu-Wei Leu
- Human Epigenomics Center, Department of Life Science, Institute of Molecular Biology and Institute of Biomedical Science, National Chung Cheng University, Chia-Yi, Taiwan
| | - Tim H.-M. Huang
- Department of Molecular Medicine, Institute of Biotechnology, University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Peggy J. Farnham
- Department of Biochemistry and Molecular Biology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America
| | - Victor X. Jin
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America
- * E-mail:
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Won KJ, Zhang X, Wang T, Ding B, Raha D, Snyder M, Ren B, Wang W. Comparative annotation of functional regions in the human genome using epigenomic data. Nucleic Acids Res 2013; 41:4423-32. [PMID: 23482391 PMCID: PMC3632130 DOI: 10.1093/nar/gkt143] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Epigenetic regulation is dynamic and cell-type dependent. The recently available epigenomic data in multiple cell types provide an unprecedented opportunity for a comparative study of epigenetic landscape. We developed a machine-learning method called ChroModule to annotate the epigenetic states in eight ENCyclopedia Of DNA Elements cell types. The trained model successfully captured the characteristic histone-modification patterns associated with regulatory elements, such as promoters and enhancers, and showed superior performance on identifying enhancers compared with the state-of-art methods. In addition, given the fixed number of epigenetic states in the model, ChroModule allows straightforward illustration of epigenetic variability in multiple cell types. Using this feature, we found that invariable and variable epigenetic states across cell types correspond to housekeeping functions and stimulus response, respectively. Especially, we observed that enhancers, but not the other regulatory elements, dictate cell specificity, as similar cell types share common enhancers, and cell-type-specific enhancers are often bound by transcription factors playing critical roles in that cell type. More interestingly, we found some genomic regions are dormant in cell type but primed to become active in other cell types. These observations highlight the usefulness of ChroModule in comparative analysis and interpretation of multiple epigenomes.
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Affiliation(s)
- Kyoung-Jae Won
- Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0359, USA
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