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Achinger-Kawecka J, Stirzaker C, Portman N, Campbell E, Chia KM, Du Q, Laven-Law G, Nair SS, Yong A, Wilkinson A, Clifton S, Milioli HH, Alexandrou S, Caldon CE, Song J, Khoury A, Meyer B, Chen W, Pidsley R, Qu W, Gee JMW, Schmitt A, Wong ES, Hickey TE, Lim E, Clark SJ. The potential of epigenetic therapy to target the 3D epigenome in endocrine-resistant breast cancer. Nat Struct Mol Biol 2024; 31:498-512. [PMID: 38182927 PMCID: PMC10948365 DOI: 10.1038/s41594-023-01181-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 11/15/2023] [Indexed: 01/07/2024]
Abstract
Three-dimensional (3D) epigenome remodeling is an important mechanism of gene deregulation in cancer. However, its potential as a target to counteract therapy resistance remains largely unaddressed. Here, we show that epigenetic therapy with decitabine (5-Aza-mC) suppresses tumor growth in xenograft models of pre-clinical metastatic estrogen receptor positive (ER+) breast tumor. Decitabine-induced genome-wide DNA hypomethylation results in large-scale 3D epigenome deregulation, including de-compaction of higher-order chromatin structure and loss of boundary insulation of topologically associated domains. Significant DNA hypomethylation associates with ectopic activation of ER-enhancers, gain in ER binding, creation of new 3D enhancer-promoter interactions and concordant up-regulation of ER-mediated transcription pathways. Importantly, long-term withdrawal of epigenetic therapy partially restores methylation at ER-enhancer elements, resulting in a loss of ectopic 3D enhancer-promoter interactions and associated gene repression. Our study illustrates the potential of epigenetic therapy to target ER+ endocrine-resistant breast cancer by DNA methylation-dependent rewiring of 3D chromatin interactions, which are associated with the suppression of tumor growth.
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Affiliation(s)
- Joanna Achinger-Kawecka
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia.
| | - Clare Stirzaker
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Neil Portman
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Elyssa Campbell
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Kee-Ming Chia
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Qian Du
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Geraldine Laven-Law
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
| | - Shalima S Nair
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Aliza Yong
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Ashleigh Wilkinson
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Samuel Clifton
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Heloisa H Milioli
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Sarah Alexandrou
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - C Elizabeth Caldon
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Jenny Song
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Amanda Khoury
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Braydon Meyer
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Wenhan Chen
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Ruth Pidsley
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Wenjia Qu
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Julia M W Gee
- Breast Cancer Molecular Pharmacology Group, School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, Wales, UK
| | | | - Emily S Wong
- Victor Chang Cardiac Institute, Sydney, New South Wales, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - Theresa E Hickey
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
| | - Elgene Lim
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Susan J Clark
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia.
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2
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Tang B, Wang X, He H, Chen R, Qiao G, Yang Y, Xu Z, Wang L, Dong Q, Yu J, Zhang MQ, Shi M, Wang J. Aging-disturbed FUS phase transition impairs hematopoietic stem cells by altering chromatin structure. Blood 2024; 143:124-138. [PMID: 37748139 DOI: 10.1182/blood.2023020539] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 09/08/2023] [Accepted: 09/09/2023] [Indexed: 09/27/2023] Open
Abstract
ABSTRACT Aged hematopoietic stem cells (HSCs) exhibit compromised reconstitution capacity. The molecular mechanisms behind this phenomenon are not fully understood. Here, we observed that the expression of FUS is increased in aged HSCs, and enforced FUS recapitulates the phenotype of aged HSCs through arginine-glycine-glycine-mediated aberrant FUS phase transition. By using Fus-gfp mice, we observed that FUShigh HSCs exhibit compromised FUS mobility and resemble aged HSCs both functionally and transcriptionally. The percentage of FUShigh HSCs is increased upon physiological aging and replication stress, and FUSlow HSCs of aged mice exhibit youthful function. Mechanistically, FUShigh HSCs exhibit a different global chromatin organization compared with FUSlow HSCs, which is observed in aged HSCs. Many topologically associating domains (TADs) are merged in aged HSCs because of the compromised binding of CCCTC-binding factor with chromatin, which is invoked by aberrant FUS condensates. It is notable that the transcriptional alteration between FUShigh and FUSlow HSCs originates from the merged TADs and is enriched in HSC aging-related genes. Collectively, this study reveals for the first time that aberrant FUS mobility promotes HSC aging by altering chromatin structure.
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Affiliation(s)
- Baixue Tang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Xinming Wang
- Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Hanqing He
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Ruiqing Chen
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Guofeng Qiao
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Yang Yang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Zihan Xu
- School of Life Sciences, Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Sciences, Peking University, Beijing, China
| | - Longteng Wang
- School of Life Sciences, Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Sciences, Peking University, Beijing, China
| | - Qiongye Dong
- Institute of Precision of Medicine, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jia Yu
- State Key Laboratory of Medical Molecular Biology, Department of Biochemistry and Molecular Biology, Haihe Laboratory of Cell Ecosystem, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Michael Q Zhang
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing, China
- Department of Biological Sciences, Center for Systems Biology, The University of Texas, Richardson, TX
| | - Minglei Shi
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing, China
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
| | - Jianwei Wang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
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3
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Shah A. Rethinking cancer initiation: The role of large-scale mutational events. Genes Chromosomes Cancer 2024; 63:e23213. [PMID: 37950638 DOI: 10.1002/gcc.23213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/24/2023] [Accepted: 10/27/2023] [Indexed: 11/13/2023] Open
Abstract
Cancer initiation is revisited in light of recent discoveries in cancer pathogenesis. Of note is the detection of mutated cancer genes in benign conditions. More significantly, somatic clones, which harbor mutations in cancer genes, arise in normal tissues from early development through adulthood, but seldom do they transform into cancer. Further, clustered mutational events-kataegis, chromothripsis and chromoplexy-are widespread in cancer, generating point mutations and chromosomal rearrangements in a single cellular catastrophe. These observations are contrary to the prevailing somatic mutation theory, which states that a cancer is caused by the gradual accumulation of mutations over time. A different perspective is proposed within the framework of Waddington's epigenetic landscape wherein tumorigenesis is viewed primarily as a disruption of cell development. Cell types are defined by their specific gene-expression profiles, determined by the gene regulatory network, and can be regarded as attractor states of the network dynamics: they represent specific, self-stabilizing patterns of gene activities across the genome. However, large-scale mutational events reshape the landscape topology, creating abnormal "unphysiological" attractors. This is the crux of the process of initiation. Initiation primes the cell for conversion into a tumor phenotype by oncogenes and tumor suppressor genes, which drive cell proliferation and clonal diversification. This view of tumorigenesis calls for a different approach to therapy.
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Affiliation(s)
- Amil Shah
- Department of Medicine, University of British Columbia, Vancouver, Canada
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4
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Zhang Y, Wang X, Zhang C, Yi H. The dysregulation of lncRNAs by epigenetic factors in human pathologies. Drug Discov Today 2023; 28:103664. [PMID: 37348827 DOI: 10.1016/j.drudis.2023.103664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023]
Abstract
Dysregulation of long noncoding RNAs (lncRNAs) contributes to numerous human diseases, including cancers and autoimmune diseases (ADs). Given the importance of lncRNAs in disease initiation and progression, a deeper understanding of their complex regulatory network is required to facilitate their use as therapeutic targets for ADs. In this review, we summarize how lncRNAs are dysregulated in pathological states by epigenetic factors, including RNA-binding proteins, chemical modifications (N6-methyladenosine, 5-methylcytosine, 7-methylguanosine, adenosine-to-inosine editing, microRNA, alternative splicing, DNA methylation, and histone modification). Moreover, the roles of lncRNA epigenetic regulators in immune response and ADs are discussed, providing new insights into the complicated epigenetic factor-lncRNA network, thus, laying a theoretical foundation for future research and clinical application of lncRNAs.
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Affiliation(s)
- Yanli Zhang
- Central Laboratory, The First Hospital of Jilin University, Changchun, Jilin, China; Key Laboratory of Organ Regeneration and Transplantation, Ministry of Education, Changchun, Jilin 130021, China; Department of Echocardiography, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Xiaocong Wang
- Department of Echocardiography, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Chen Zhang
- Colorectal and Anal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Huanfa Yi
- Central Laboratory, The First Hospital of Jilin University, Changchun, Jilin, China; Key Laboratory of Organ Regeneration and Transplantation, Ministry of Education, Changchun, Jilin 130021, China.
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5
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Liu J, Li JN, Wu H, Liu P. The Status and Prospects of Epigenetics in the Treatment of Lymphoma. Front Oncol 2022; 12:874645. [PMID: 35463343 PMCID: PMC9033274 DOI: 10.3389/fonc.2022.874645] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 03/17/2022] [Indexed: 12/12/2022] Open
Abstract
The regulation of gene transcription by epigenetic modifications is closely related to many important life processes and is a hot research topic in the post-genomic era. Since the emergence of international epigenetic research in the 1990s, scientists have identified a variety of chromatin-modifying enzymes and recognition factors, and have systematically investigated their three-dimensional structures, substrate specificity, and mechanisms of enzyme activity regulation. Studies of the human tumor genome have revealed the close association of epigenetic factors with various malignancies, and we have focused more on mutations in epigenetically related regulatory enzymes and regulatory recognition factors in lymphomas. A number of studies have shown that epigenetic alterations are indeed widespread in the development and progression of lymphoma and understanding these mechanisms can help guide clinical efforts. In contrast to chemotherapy which induces cytotoxicity, epigenetic therapy has the potential to affect multiple cellular processes simultaneously, by reprogramming cells to achieve a therapeutic effect in lymphoma. Epigenetic monotherapy has shown promising results in previous clinical trials, and several epigenetic agents have been approved for use in the treatment of lymphoma. In addition, epigenetic therapies in combination with chemotherapy and/or immunotherapy have been used in various clinical trials. In this review, we present several important epigenetic modalities of regulation associated with lymphoma, summarize the corresponding epigenetic drugs in lymphoma, and look at the future of epigenetic therapies in lymphoma.
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Affiliation(s)
- Jiaxin Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jia-Nan Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Hongyu Wu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Panpan Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
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6
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Crosstalk between Hepatitis B Virus and the 3D Genome Structure. Viruses 2022; 14:v14020445. [PMID: 35216038 PMCID: PMC8877387 DOI: 10.3390/v14020445] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/04/2022] [Accepted: 02/14/2022] [Indexed: 12/17/2022] Open
Abstract
Viruses that transcribe their DNA within the nucleus have to adapt to the existing cellular mechanisms that govern transcriptional regulation. Recent technological breakthroughs have highlighted the highly hierarchical organization of the cellular genome and its role in the regulation of gene expression. This review provides an updated overview on the current knowledge on how the hepatitis B virus interacts with the cellular 3D genome and its consequences on viral and cellular gene expression. We also briefly discuss the strategies developed by other DNA viruses to co-opt and sometimes subvert cellular genome spatial organization.
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7
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Jablonski KP, Carron L, Mozziconacci J, Forné T, Hütt MT, Lesne A. Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study. Hum Genomics 2022; 16:2. [PMID: 35016721 PMCID: PMC8753905 DOI: 10.1186/s40246-022-00375-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 01/02/2022] [Indexed: 01/31/2023] Open
Abstract
Background Genome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in three-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically associating domains (TADs) and their borders. Results For each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e., the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases displays such a preferential localization of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that localization of risk loci in TAD borders differs between cancers and non-cancer diseases. Furthermore, different TAD border enrichments are observed in embryonic stem cells and differentiated cells, consistent with changes in topological domains along embryogenesis and delineating their contribution to disease risk. Conclusions Our results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with an effect on an individual gene, the other acting in interplay with 3D genome organization. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-022-00375-2.
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Affiliation(s)
- Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics, 4058, Basel, Switzerland
| | - Leopold Carron
- Laboratoire de Physique Théorique de la Matière Condensée, LPTMC, CNRS, Sorbonne Université, Paris, France.,Laboratory of Computational and Quantitative Biology, LCQB, Sorbonne Université, Paris, France
| | - Julien Mozziconacci
- Laboratoire de Physique Théorique de la Matière Condensée, LPTMC, CNRS, Sorbonne Université, Paris, France.,Structure et Instabilité des Génomes, Muséum National d'Histoire Naturelle, Paris, France
| | - Thierry Forné
- Institut de Génétique Moléculaire de Montpellier, IGMM, CNRS, Univ. Montpellier, Montpellier, France
| | - Marc-Thorsten Hütt
- Department of Life Sciences and Chemistry, Jacobs University Bremen, Bremen, Germany.
| | - Annick Lesne
- Laboratoire de Physique Théorique de la Matière Condensée, LPTMC, CNRS, Sorbonne Université, Paris, France. .,Institut de Génétique Moléculaire de Montpellier, IGMM, CNRS, Univ. Montpellier, Montpellier, France.
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8
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González-Espinoza A, Zamora-Fuentes J, Hernández-Lemus E, Espinal-Enríquez J. Gene Co-Expression in Breast Cancer: A Matter of Distance. Front Oncol 2021; 11:726493. [PMID: 34868919 PMCID: PMC8636045 DOI: 10.3389/fonc.2021.726493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 10/26/2021] [Indexed: 01/16/2023] Open
Abstract
Gene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed us to compare and analyze complex phenotypes such as breast cancer (BrCa) and their control counterparts. Global co-expression patterns have revealed, for instance, that the highest gene-gene co-expression interactions often occur between genes from the same chromosome (cis-), meanwhile inter-chromosome (trans-) interactions are scarce and have lower correlation values. Furthermore, strength of cis- correlations have been shown to decay with the chromosome distance of gene couples. Despite this loss of long-distance co-expression has been clearly identified, it has been observed only in a small fraction of the whole co-expression landscape, namely the most significant interactions. For that reason, an approach that takes into account the whole interaction set results appealing. In this work, we developed a hybrid method to analyze whole-chromosome Pearson correlation matrices for the four BrCa subtypes (Luminal A, Luminal B, HER2+ and Basal), as well as adjacent normal breast tissue derived matrices. We implemented a systematic method for clustering gene couples, by using eigenvalue spectral decomposition and the k–medoids algorithm, allowing us to determine a number of clusters without removing any interaction. With this method we compared, for each chromosome in the five phenotypes: a) Whether or not the gene-gene co-expression decays with the distance in the breast cancer subtypes b) the chromosome location of cis- clusters of gene couples, and c) whether or not the loss of long-distance co-expression is observed in the whole range of interactions. We found that in the correlation matrix for the control phenotype, positive and negative Pearson correlations deviate from a random null model independently of the distance between couples. Conversely, for all BrCa subtypes, in all chromosomes, positive correlations decay with distance, and negative correlations do not differ from the null model. We also found that BrCa clusters are distance-dependent, meanwhile for the control phenotype, chromosome location does not determine the clustering. To our knowledge, this is the first time that a dependence on distance is reported for gene clusters in breast cancer. Since this method uses the whole cis- interaction geneset, combination with other -omics approaches may provide further evidence to understand in a more integrative fashion, the mechanisms that disrupt gene regulation in cancer.
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Affiliation(s)
- Alfredo González-Espinoza
- Department of Biology, University of Pennsylvania, Philadelphia, PA, United States.,Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Jose Zamora-Fuentes
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Enrique Hernández-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autόnoma de México, Mexico City, Mexico
| | - Jesús Espinal-Enríquez
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autόnoma de México, Mexico City, Mexico
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9
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Saintilnord WN, Fondufe-Mittendorf Y. Arsenic-induced epigenetic changes in cancer development. Semin Cancer Biol 2021; 76:195-205. [PMID: 33798722 PMCID: PMC8481342 DOI: 10.1016/j.semcancer.2021.03.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/29/2022]
Abstract
Arsenic is a ubiquitous metalloid whose high levels of toxicity pose major health concerns to millions of people worldwide by increasing susceptibility to various cancers and non-cancer illnesses. Since arsenic is not a mutagen, the mechanism by which it causes changes in gene expression and disease pathogenesis is not clear. One possible mechanism is through generation of reactive oxygen species. Another equally important mechanism still very much in its infancy is epigenetic dysregulation. In this review, we discuss recent discoveries underlying arsenic-induced epigenetic changes in cancer development. Importantly, we highlight the proposed mechanisms targeted by arsenic to drive oncogenic gene expression.
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Affiliation(s)
- Wesley N Saintilnord
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, USA.
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10
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Danieli A, Papantonis A. Spatial genome architecture and the emergence of malignancy. Hum Mol Genet 2021; 29:R197-R204. [PMID: 32619215 DOI: 10.1093/hmg/ddaa128] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/16/2020] [Accepted: 06/16/2020] [Indexed: 01/30/2023] Open
Abstract
Human chromosomes are large spatially and hierarchically structured entities, the integrity of which needs to be preserved throughout the lifespan of the cell and in conjunction with cell cycle progression. Preservation of chromosomal structure is important for proper deployment of cell type-specific gene expression programs. Thus, aberrations in the integrity and structure of chromosomes will predictably lead to disease, including cancer. Here, we provide an updated standpoint with respect to chromatin misfolding and the emergence of various cancer types. We discuss recent studies implicating the disruption of topologically associating domains, switching between active and inactive compartments, rewiring of promoter-enhancer interactions in malignancy as well as the effects of single nucleotide polymorphisms in non-coding regions involved in long-range regulatory interactions. In light of these findings, we argue that chromosome conformation studies may now also be useful for patient diagnosis and drug target discovery.
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Affiliation(s)
- Adi Danieli
- Institute of Pathology, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Argyris Papantonis
- Institute of Pathology, University Medical Center Göttingen, 37075 Göttingen, Germany
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11
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García-Cortés D, Hernández-Lemus E, Espinal-Enríquez J. Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations. Front Genet 2021; 12:629475. [PMID: 33959148 PMCID: PMC8096206 DOI: 10.3389/fgene.2021.629475] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 03/17/2021] [Indexed: 12/20/2022] Open
Abstract
Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer.
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Affiliation(s)
- Diana García-Cortés
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.,Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Enrique Hernández-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Jesús Espinal-Enríquez
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
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12
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Song M, Zhong H. Efficient weighted univariate clustering maps outstanding dysregulated genomic zones in human cancers. Bioinformatics 2021; 36:5027-5036. [PMID: 32619008 PMCID: PMC7755420 DOI: 10.1093/bioinformatics/btaa613] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 05/24/2020] [Accepted: 06/26/2020] [Indexed: 12/14/2022] Open
Abstract
Motivation Chromosomal patterning of gene expression in cancer can arise from aneuploidy, genome disorganization or abnormal DNA methylation. To map such patterns, we introduce a weighted univariate clustering algorithm to guarantee linear runtime, optimality and reproducibility. Results We present the chromosome clustering method, establish its optimality and runtime and evaluate its performance. It uses dynamic programming enhanced with an algorithm to reduce search-space in-place to decrease runtime overhead. Using the method, we delineated outstanding genomic zones in 17 human cancer types. We identified strong continuity in dysregulation polarity—dominance by either up- or downregulated genes in a zone—along chromosomes in all cancer types. Significantly polarized dysregulation zones specific to cancer types are found, offering potential diagnostic biomarkers. Unreported previously, a total of 109 loci with conserved dysregulation polarity across cancer types give insights into pan-cancer mechanisms. Efficient chromosomal clustering opens a window to characterize molecular patterns in cancer genome and beyond. Availability and implementation Weighted univariate clustering algorithms are implemented within the R package ‘Ckmeans.1d.dp’ (4.0.0 or above), freely available at https://cran.r-project.org/package=Ckmeans.1d.dp. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mingzhou Song
- Department of Computer Science.,Molecular Biology Graduate Program, New Mexico State University, Las Cruces, NM 88003, USA
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13
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Kuang S, Wang L. Identification and analysis of consensus RNA motifs binding to the genome regulator CTCF. NAR Genom Bioinform 2021; 2:lqaa031. [PMID: 33575587 PMCID: PMC7671415 DOI: 10.1093/nargab/lqaa031] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/21/2020] [Accepted: 04/28/2020] [Indexed: 12/14/2022] Open
Abstract
CCCTC-binding factor (CTCF) is a key regulator of 3D genome organization and gene expression. Recent studies suggest that RNA transcripts, mostly long non-coding RNAs (lncRNAs), can serve as locus-specific factors to bind and recruit CTCF to the chromatin. However, it remains unclear whether specific sequence patterns are shared by the CTCF-binding RNA sites, and no RNA motif has been reported so far for CTCF binding. In this study, we have developed DeepLncCTCF, a new deep learning model based on a convolutional neural network and a bidirectional long short-term memory network, to discover the RNA recognition patterns of CTCF and identify candidate lncRNAs binding to CTCF. When evaluated on two different datasets, human U2OS dataset and mouse ESC dataset, DeepLncCTCF was shown to be able to accurately predict CTCF-binding RNA sites from nucleotide sequence. By examining the sequence features learned by DeepLncCTCF, we discovered a novel RNA motif with the consensus sequence, AGAUNGGA, for potential CTCF binding in humans. Furthermore, the applicability of DeepLncCTCF was demonstrated by identifying nearly 5000 candidate lncRNAs that might bind to CTCF in the nucleus. Our results provide useful information for understanding the molecular mechanisms of CTCF function in 3D genome organization.
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Affiliation(s)
- Shuzhen Kuang
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA.,Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA
| | - Liangjiang Wang
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
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14
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Tao H, Li H, Xu K, Hong H, Jiang S, Du G, Wang J, Sun Y, Huang X, Ding Y, Li F, Zheng X, Chen H, Bo X. Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles. Brief Bioinform 2021; 22:6102668. [PMID: 33454752 PMCID: PMC8424394 DOI: 10.1093/bib/bbaa405] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/26/2020] [Accepted: 12/10/2020] [Indexed: 12/14/2022] Open
Abstract
The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles, categorize them and compare their performance. Besides, we provide a comprehensive guideline for the selection of suitable methods to predict chromatin interaction and organization based on available data and biological question of interest.
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Affiliation(s)
- Huan Tao
- Beijing Institute of Radiation Medicine
| | - Hao Li
- Beijing Institute of Radiation Medicine
| | - Kang Xu
- Beijing Institute of Radiation Medicine
| | - Hao Hong
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Shuai Jiang
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Guifang Du
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | | | - Yu Sun
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Xin Huang
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Yang Ding
- Beijing Institute of Radiation Medicine
| | - Fei Li
- Chinese Academy of Sciences, Department of Computer Network Information Center
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15
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Jing F, Zhang SW, Zhang S. Prediction of enhancer-promoter interactions using the cross-cell type information and domain adversarial neural network. BMC Bioinformatics 2020; 21:507. [PMID: 33160328 PMCID: PMC7648314 DOI: 10.1186/s12859-020-03844-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 10/27/2020] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Enhancer-promoter interactions (EPIs) play key roles in transcriptional regulation and disease progression. Although several computational methods have been developed to predict such interactions, their performances are not satisfactory when training and testing data from different cell lines. Currently, it is still unclear what extent a across cell line prediction can be made based on sequence-level information. RESULTS In this work, we present a novel Sequence-based method (called SEPT) to predict the enhancer-promoter interactions in new cell line by using the cross-cell information and Transfer learning. SEPT first learns the features of enhancer and promoter from DNA sequences with convolutional neural network (CNN), then designing the gradient reversal layer of transfer learning to reduce the cell line specific features meanwhile retaining the features associated with EPIs. When the locations of enhancers and promoters are provided in new cell line, SEPT can successfully recognize EPIs in this new cell line based on labeled data of other cell lines. The experiment results show that SEPT can effectively learn the latent import EPIs-related features between cell lines and achieves the best prediction performance in terms of AUC (the area under the receiver operating curves). CONCLUSIONS SEPT is an effective method for predicting the EPIs in new cell line. Domain adversarial architecture of transfer learning used in SEPT can learn the latent EPIs shared features among cell lines from all other existing labeled data. It can be expected that SEPT will be of interest to researchers concerned with biological interaction prediction.
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Affiliation(s)
- Fang Jing
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, 127 West Youyi Road, Xi’an, 710072 Shaanxi China
| | - Shao-Wu Zhang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, 127 West Youyi Road, Xi’an, 710072 Shaanxi China
| | - Shihua Zhang
- NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 55 Zhongguancun East Road, Beijing, 10090 China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223 China
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16
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Targeting the epigenetic regulation of antitumour immunity. Nat Rev Drug Discov 2020; 19:776-800. [PMID: 32929243 DOI: 10.1038/s41573-020-0077-5] [Citation(s) in RCA: 262] [Impact Index Per Article: 65.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2020] [Indexed: 01/10/2023]
Abstract
Dysregulation of the epigenome drives aberrant transcriptional programmes that promote cancer onset and progression. Although defective gene regulation often affects oncogenic and tumour-suppressor networks, tumour immunogenicity and immune cells involved in antitumour responses may also be affected by epigenomic alterations. This could have important implications for the development and application of both epigenetic therapies and cancer immunotherapies, and combinations thereof. Here, we review the role of key aberrant epigenetic processes - DNA methylation and post-translational modification of histones - in tumour immunogenicity, as well as the effects of epigenetic modulation on antitumour immune cell function. We emphasize opportunities for small-molecule inhibitors of epigenetic regulators to enhance antitumour immune responses, and discuss the challenges of exploiting the complex interplay between cancer epigenetics and cancer immunology to develop treatment regimens combining epigenetic therapies with immunotherapies.
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17
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Pei J, Harakalova M, Treibel TA, Lumbers RT, Boukens BJ, Efimov IR, van Dinter JT, González A, López B, El Azzouzi H, van den Dungen N, van Dijk CGM, Krebber MM, den Ruijter HM, Pasterkamp G, Duncker DJ, Nieuwenhuis EES, de Weger R, Huibers MM, Vink A, Moore JH, Moon JC, Verhaar MC, Kararigas G, Mokry M, Asselbergs FW, Cheng C. H3K27ac acetylome signatures reveal the epigenomic reorganization in remodeled non-failing human hearts. Clin Epigenetics 2020; 12:106. [PMID: 32664951 PMCID: PMC7362435 DOI: 10.1186/s13148-020-00895-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 06/30/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND H3K27ac histone acetylome changes contribute to the phenotypic response in heart diseases, particularly in end-stage heart failure. However, such epigenetic alterations have not been systematically investigated in remodeled non-failing human hearts. Therefore, valuable insight into cardiac dysfunction in early remodeling is lacking. This study aimed to reveal the acetylation changes of chromatin regions in response to myocardial remodeling and their correlations to transcriptional changes of neighboring genes. RESULTS We detected chromatin regions with differential acetylation activity (DARs; Padj. < 0.05) between remodeled non-failing patient hearts and healthy donor hearts. The acetylation level of the chromatin region correlated with its RNA polymerase II occupancy level and the mRNA expression level of its adjacent gene per sample. Annotated genes from DARs were enriched in disease-related pathways, including fibrosis and cell metabolism regulation. DARs that change in the same direction have a tendency to cluster together, suggesting the well-reorganized chromatin architecture that facilitates the interactions of regulatory domains in response to myocardial remodeling. We further show the differences between the acetylation level and the mRNA expression level of cell-type-specific markers for cardiomyocytes and 11 non-myocyte cell types. Notably, we identified transcriptome factor (TF) binding motifs that were enriched in DARs and defined TFs that were predicted to bind to these motifs. We further showed 64 genes coding for these TFs that were differentially expressed in remodeled myocardium when compared with controls. CONCLUSIONS Our study reveals extensive novel insight on myocardial remodeling at the DNA regulatory level. Differences between the acetylation level and the transcriptional level of cell-type-specific markers suggest additional mechanism(s) between acetylome and transcriptome. By integrating these two layers of epigenetic profiles, we further provide promising TF-encoding genes that could serve as master regulators of myocardial remodeling. Combined, our findings highlight the important role of chromatin regulatory signatures in understanding disease etiology.
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Affiliation(s)
- Jiayi Pei
- Department of Nephrology and Hypertension, DIGD, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
- Department of Cardiology, Division Heart & Lungs, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
- Regenerative Medicine Utrecht (RMU), UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Magdalena Harakalova
- Department of Cardiology, Division Heart & Lungs, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
- Regenerative Medicine Utrecht (RMU), UMC Utrecht, University of Utrecht, Utrecht, Netherlands
- Department of Pathology, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Thomas A Treibel
- Institute of Cardiovascular Science, University College London, London, UK
| | - R Thomas Lumbers
- Institute of Cardiovascular Science, University College London, London, UK
| | | | - Igor R Efimov
- Department of Biomedical Engineering, GWU, Washington, D.C, USA
| | - Jip T van Dinter
- Department of Cardiology, Division Heart & Lungs, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Arantxa González
- Program of Cardiovascular Diseases, CIMA Universidad de Navarra and IdiSNA, Pamplona, Spain
- CIBERCV, Carlos III Institute of Health, Madrid, Spain
| | - Begoña López
- Program of Cardiovascular Diseases, CIMA Universidad de Navarra and IdiSNA, Pamplona, Spain
- CIBERCV, Carlos III Institute of Health, Madrid, Spain
| | - Hamid El Azzouzi
- Department of Cardiology, Division Heart & Lungs, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | | | - Christian G M van Dijk
- Department of Nephrology and Hypertension, DIGD, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Merle M Krebber
- Department of Nephrology and Hypertension, DIGD, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Hester M den Ruijter
- Department of Experimental Cardiology, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Gerard Pasterkamp
- Laboratory of Clinical Chemistry and Hematology, UMC Utrecht, Utrecht, Netherlands
| | - Dirk J Duncker
- Division of Experimental Cardiology, Department of Cardiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | | | - Roel de Weger
- Department of Pathology, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Manon M Huibers
- Department of Pathology, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Aryan Vink
- Department of Pathology, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Jason H Moore
- Institute for Biomedical Informatics, UPENN, Philadelphia, USA
| | - James C Moon
- Institute of Cardiovascular Science, University College London, London, UK
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, DIGD, UMC Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Georgios Kararigas
- Charité - Universitätsmedizin Berlin, and DZHK (German Centre for Cardiovascular Research), partner site, Berlin, Germany
| | - Michal Mokry
- Regenerative Medicine Utrecht (RMU), UMC Utrecht, University of Utrecht, Utrecht, Netherlands.
- Laboratory of Clinical Chemistry and Hematology, UMC Utrecht, Utrecht, Netherlands.
- Division of Paediatrics, UMC Utrecht, University of Utrecht, Utrecht, Netherlands.
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, UMC Utrecht, University of Utrecht, Utrecht, Netherlands.
- Institute of Cardiovascular Science, Faculty of Population Health Science, University College London, London, UK.
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK.
| | - Caroline Cheng
- Department of Nephrology and Hypertension, DIGD, UMC Utrecht, University of Utrecht, Utrecht, Netherlands.
- Regenerative Medicine Utrecht (RMU), UMC Utrecht, University of Utrecht, Utrecht, Netherlands.
- Division of Experimental Cardiology, Department of Cardiology, Erasmus University Medical Center, Rotterdam, Netherlands.
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18
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Übelmesser N, Papantonis A. Technologies to study spatial genome organization: beyond 3C. Brief Funct Genomics 2020; 18:395-401. [PMID: 31609405 DOI: 10.1093/bfgp/elz019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 06/27/2019] [Accepted: 07/15/2019] [Indexed: 01/05/2023] Open
Abstract
The way that chromatin is organized in three-dimensional nuclear space is now acknowledged as a factor critical for the major cell processes, like transcription, replication and cell division. Researchers have been armed with new molecular and imaging technologies to study this structure-to-function link of genomes, spearheaded by the introduction of the 'chromosome conformation capture' technology more than a decade ago. However, this technology is not without shortcomings, and novel variants and orthogonal approaches are being developed to overcome these. As a result, the field of nuclear organization is constantly fueled by methods of increasing resolution and/or throughput that strive to eliminate systematic biases and increase precision. In this review, we attempt to highlight the most recent advances in technology that promise to provide novel insights on how chromosomes fold and function.
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Affiliation(s)
- Nadine Übelmesser
- Institute of Pathology, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Argyris Papantonis
- Institute of Pathology, University Medical Center Göttingen, 37075 Göttingen, Germany
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19
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Epigenetic reprogramming at estrogen-receptor binding sites alters 3D chromatin landscape in endocrine-resistant breast cancer. Nat Commun 2020; 11:320. [PMID: 31949157 PMCID: PMC6965612 DOI: 10.1038/s41467-019-14098-x] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Accepted: 12/17/2019] [Indexed: 02/07/2023] Open
Abstract
Endocrine therapy resistance frequently develops in estrogen receptor positive (ER+) breast cancer, but the underlying molecular mechanisms are largely unknown. Here, we show that 3-dimensional (3D) chromatin interactions both within and between topologically associating domains (TADs) frequently change in ER+ endocrine-resistant breast cancer cells and that the differential interactions are enriched for resistance-associated genetic variants at CTCF-bound anchors. Ectopic chromatin interactions are preferentially enriched at active enhancers and promoters and ER binding sites, and are associated with altered expression of ER-regulated genes, consistent with dynamic remodelling of ER pathways accompanying the development of endocrine resistance. We observe that loss of 3D chromatin interactions often occurs coincidently with hypermethylation and loss of ER binding. Alterations in active A and inactive B chromosomal compartments are also associated with decreased ER binding and atypical interactions and gene expression. Together, our results suggest that 3D epigenome remodelling is a key mechanism underlying endocrine resistance in ER+ breast cancer.
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20
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Larsen TV, Hussmann D, Nielsen AL. PD-L1 and PD-L2 expression correlated genes in non-small-cell lung cancer. Cancer Commun (Lond) 2019; 39:30. [PMID: 31159869 PMCID: PMC6545701 DOI: 10.1186/s40880-019-0376-6] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 05/23/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Programmed cell death ligand-1 (PD-L1) and ligand-2 (PD-L2) interaction with programmed cell death protein-1 (PD-1) represent an immune-inhibiting checkpoint mediating immune evasion and is, accordingly, an important target for blockade-based immunotherapy in cancer. In non-small-cell lung cancer (NSCLC), improved understanding of PD-1 checkpoint blockade-responsive biology and identification of biomarkers for prediction of a clinical response to immunotherapy is warranted. Thus, in the present study, we systematically described PD-L1 and PD-L2 expression correlated genes in NSCLC. METHODS We performed comparative retrospective analyses to identify PD-L1 and PD-L2 mRNA expression correlated genes in NSCLC. For this, we examined available datasets from the cancer cell line encyclopedia (CCLE) project lung non-small-cell (Lung_NSC) and the cancer genome atlas (TCGA) projects lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). RESULTS Analysis of the CCLE dataset Lung_NSC identified expression correlation between PD-L1 and PD-L2. Moreover, we identified expression correlation between 489 genes and PD-L1, 191 genes and PD-L2, and 111 genes for both. PD-L1 and PD-L2 also expression correlated in TCGA datasets LUAD and LUSC. In LUAD, we identified expression correlation between 257 genes and PD-L1, 914 genes and PD-L2, and 211 genes for both. In LUSC, we identified expression correlation between 26 genes and PD-L1, 326 genes and PD-L2, and 13 genes for both. Only a few genes expression correlated with PD-L1 and PD-L2 across the CCLE and TCGA datasets. Expression of Interferon signaling-involved genes converged in particular with the expression correlated genes for PD-L1 in Lung_NSC, for PD-L2 in LUSC, and for both PD-L1 and PD-L2 in LUAD. In LUSC, PD-L1, and to a lesser extent PD-L2, expression correlated with chromosome 9p24 localized genes, indicating a chromosome 9p24 topologically associated domain as an important driver of in particular LUSC PD-L1 expression. Expression correlation analyses of the PD-L1 and PD-L2 receptors programmed cell death protein-1 (PD-1), Cluster of differentiation 80 (CD80), and Repulsive guidance molecule B (RGMB) showed that PD-1 and CD80 expression correlated with both PD-L1 and PD-L2 in LUAD. CD80 expression correlated with PD-L2 in LUSC. CONCLUSIONS We present gene signatures associated with PD-L1 and PD-L2 mRNA expression in NSCLC which could possess importance in relation to understand PD-1 checkpoint blockade-responsive biology and development of gene signature based biomarkers for predicting clinical responses to immunotherapy.
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Affiliation(s)
| | - Dianna Hussmann
- Department of Biomedicine, Aarhus University, 8000, Aarhus C, Denmark
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21
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Qian M, Cheng Y, Wang X. The methodology study of three-dimensional (3D) genome research. Semin Cell Dev Biol 2019; 90:12-18. [DOI: 10.1016/j.semcdb.2018.07.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 07/03/2018] [Indexed: 12/12/2022]
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22
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Cortesi A, Pesant M, Sinha S, Marasca F, Sala E, Gregoretti F, Antonelli L, Oliva G, Chiereghin C, Soldà G, Bodega B. 4q-D4Z4 chromatin architecture regulates the transcription of muscle atrophic genes in facioscapulohumeral muscular dystrophy. Genome Res 2019; 29:883-895. [PMID: 31097473 PMCID: PMC6581056 DOI: 10.1101/gr.233288.117] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 05/13/2019] [Indexed: 12/11/2022]
Abstract
Despite increasing insights in genome structure organization, the role of DNA repetitive elements, accounting for more than two thirds of the human genome, remains elusive. Facioscapulohumeral muscular dystrophy (FSHD) is associated with deletion of D4Z4 repeat array below 11 units at 4q35.2. It is known that the deletion alters chromatin structure in cis, leading to gene up-regulation. Here we show a genome-wide role of 4q-D4Z4 array in modulating gene expression via 3D nuclear contacts. We have developed an integrated strategy of 4q-D4Z4-specific 4C-seq and chromatin segmentation analyses, showing that 4q-D4Z4 3D interactome and chromatin states of interacting genes are impaired in FSHD1 condition; in particular, genes that have lost the 4q-D4Z4 interaction and with a more active chromatin state are enriched for muscle atrophy transcriptional signature. Expression level of these genes is restored by the interaction with an ectopic 4q-D4Z4 array, suggesting that the repeat directly modulates the transcription of contacted targets. Of note, the up-regulation of atrophic genes is a common feature of several FSHD1 and FSHD2 patients, indicating that we have identified a core set of deregulated genes involved in FSHD pathophysiology.
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Affiliation(s)
- Alice Cortesi
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
| | - Matthieu Pesant
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
| | - Shruti Sinha
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
| | - Federica Marasca
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
| | - Eleonora Sala
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
| | - Francesco Gregoretti
- CNR Institute for High Performance Computing and Networking (ICAR), 8013, Naples, Italy
| | - Laura Antonelli
- CNR Institute for High Performance Computing and Networking (ICAR), 8013, Naples, Italy
| | - Gennaro Oliva
- CNR Institute for High Performance Computing and Networking (ICAR), 8013, Naples, Italy
| | - Chiara Chiereghin
- Department of Biomedical Sciences, Humanitas University, 20090, Pieve Emanuele, Milan, Italy
- Humanitas Clinical and Research Center, 20089, Rozzano, Milan, Italy
| | - Giulia Soldà
- Department of Biomedical Sciences, Humanitas University, 20090, Pieve Emanuele, Milan, Italy
- Humanitas Clinical and Research Center, 20089, Rozzano, Milan, Italy
| | - Beatrice Bodega
- Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM), 20122, Milan, Italy
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23
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Cremer M, Cremer T. Nuclear compartmentalization, dynamics, and function of regulatory DNA sequences. Genes Chromosomes Cancer 2019; 58:427-436. [DOI: 10.1002/gcc.22714] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 11/23/2018] [Accepted: 11/27/2018] [Indexed: 12/15/2022] Open
Affiliation(s)
- Marion Cremer
- Biocenter, Department Biology II; Ludwig Maximilians-Universität (LMU Munich); Munich Germany
| | - Thomas Cremer
- Biocenter, Department Biology II; Ludwig Maximilians-Universität (LMU Munich); Munich Germany
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24
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From Genotype to Phenotype: Through Chromatin. Genes (Basel) 2019; 10:genes10020076. [PMID: 30678090 PMCID: PMC6410296 DOI: 10.3390/genes10020076] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 01/16/2019] [Accepted: 01/21/2019] [Indexed: 02/07/2023] Open
Abstract
Advances in sequencing technologies have enabled the exploration of the genetic basis for several clinical disorders by allowing identification of causal mutations in rare genetic diseases. Sequencing technology has also facilitated genome-wide association studies to gather single nucleotide polymorphisms in common diseases including cancer and diabetes. Sequencing has therefore become common in the clinic for both prognostics and diagnostics. The success in follow-up steps, i.e., mapping mutations to causal genes and therapeutic targets to further the development of novel therapies, has nevertheless been very limited. This is because most mutations associated with diseases lie in inter-genic regions including the so-called regulatory genome. Additionally, no genetic causes are apparent for many diseases including neurodegenerative disorders. A complementary approach is therefore gaining interest, namely to focus on epigenetic control of the disease to generate more complete functional genomic maps. To this end, several recent studies have generated large-scale epigenetic datasets in a disease context to form a link between genotype and phenotype. We focus DNA methylation and important histone marks, where recent advances have been made thanks to technology improvements, cost effectiveness, and large meta-scale epigenome consortia efforts. We summarize recent studies unravelling the mechanistic understanding of epigenetic processes in disease development and progression. Moreover, we show how methodology advancements enable causal relationships to be established, and we pinpoint the most important issues to be addressed by future research.
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Cremer T, Cremer M, Cremer C. The 4D Nucleome: Genome Compartmentalization in an Evolutionary Context. BIOCHEMISTRY (MOSCOW) 2018; 83:313-325. [PMID: 29626919 DOI: 10.1134/s000629791804003x] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
4D nucleome research aims to understand the impact of nuclear organization in space and time on nuclear functions, such as gene expression patterns, chromatin replication, and the maintenance of genome integrity. In this review we describe evidence that the origin of 4D genome compartmentalization can be traced back to the prokaryotic world. In cell nuclei of animals and plants chromosomes occupy distinct territories, built up from ~1 Mb chromatin domains, which in turn are composed of smaller chromatin subdomains and also form larger chromatin domain clusters. Microscopic evidence for this higher order chromatin landscape was strengthened by chromosome conformation capture studies, in particular Hi-C. This approach demonstrated ~1 Mb sized, topologically associating domains in mammalian cell nuclei separated by boundaries. Mutations, which destroy boundaries, can result in developmental disorders and cancer. Nucleosomes appeared first as tetramers in the Archaea kingdom and later evolved to octamers built up each from two H2A, two H2B, two H3, and two H4 proteins. Notably, nucleosomes were lost during the evolution of the Dinoflagellata phylum. Dinoflagellate chromosomes remain condensed during the entire cell cycle, but their chromosome architecture differs radically from the architecture of other eukaryotes. In summary, the conservation of fundamental features of higher order chromatin arrangements throughout the evolution of metazoan animals suggests the existence of conserved, but still unknown mechanism(s) controlling this architecture. Notwithstanding this conservation, a comparison of metazoans and protists also demonstrates species-specific structural and functional features of nuclear organization.
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Affiliation(s)
- T Cremer
- Biocenter, Department of Biology II, Ludwig Maximilian University (LMU), Munich, Germany.
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Ron G, Globerson Y, Moran D, Kaplan T. Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains. Nat Commun 2017; 8:2237. [PMID: 29269730 PMCID: PMC5740158 DOI: 10.1038/s41467-017-02386-3] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 11/24/2017] [Indexed: 01/06/2023] Open
Abstract
Proximity-ligation methods such as Hi-C allow us to map physical DNA–DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter–enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA–DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA–DNA interaction data. Proximity-ligation methods like Hi-C map DNA-DNA interactions and reveal its organization into topologically associating domains (TADs). Here the authors describe PSYCHIC, a computational approach for analysing Hi-C data that allows the identification of promoter-enhancer interactions.
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Affiliation(s)
- Gil Ron
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Yuval Globerson
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Dror Moran
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel.
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Qiu GH, Yang X, Zheng X, Huang C. The eukaryotic genome is structurally and functionally more like a social insect colony than a book. Epigenomics 2017; 9:1469-1483. [PMID: 28972397 DOI: 10.2217/epi-2017-0059] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
Traditionally, the genome has been described as the 'book of life'. However, the metaphor of a book may not reflect the dynamic nature of the structure and function of the genome. In the eukaryotic genome, the number of centrally located protein-coding sequences is relatively constant across species, but the amount of noncoding DNA increases considerably with the increase of organismal evolutional complexity. Therefore, it has been hypothesized that the abundant peripheral noncoding DNA protects the genome and the central protein-coding sequences in the eukaryotic genome. Upon comparison with the habitation, sociality and defense mechanisms of a social insect colony, it is found that the genome is similar to a social insect colony in various aspects. A social insect colony may thus be a better metaphor than a book to describe the spatial organization and physical functions of the genome. The potential implications of the metaphor are also discussed.
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Affiliation(s)
- Guo-Hua Qiu
- Fujian Provincial Key Laboratory for the Prevention & Control of Animal Infectious Diseases & Biotechnology, College of Life Sciences, Longyan University, Longyan 364012, Fujian, PR China
| | - Xiaoyan Yang
- Fujian Provincial Key Laboratory for the Prevention & Control of Animal Infectious Diseases & Biotechnology, College of Life Sciences, Longyan University, Longyan 364012, Fujian, PR China
| | - Xintian Zheng
- Fujian Provincial Key Laboratory for the Prevention & Control of Animal Infectious Diseases & Biotechnology, College of Life Sciences, Longyan University, Longyan 364012, Fujian, PR China
| | - Cuiqin Huang
- Fujian Provincial Key Laboratory for the Prevention & Control of Animal Infectious Diseases & Biotechnology, College of Life Sciences, Longyan University, Longyan 364012, Fujian, PR China
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Abstract
The dramatic re-organization of the cancer cell nucleus creates telltale morphological features critical for pathological staging of tumors. In addition, the changes to the mutational and epigenetic landscape in cancer cells alter the structure and stability of the genome and directly contribute to malignancy. DNA methylation is one of the best studied epigenetic changes in cancer, as nearly every type of cancer studied shows a loss of DNA methylation spread across most of the genome. This global hypomethylation is accompanied by hypermethylation at distinct loci, and much of the work on DNA methylation in cancer has focused on how local changes contribute to gene expression. However, the emerging picture is that the changes to DNA methylation in cancer cells has little direct effect on gene expression but instead impacts the organization of the genome in the nucleus. Several recent studies that take a broad view of the cancer epigenome find that the most profound changes to the cancer methylome are spread across large segments of the genome, and that the focal changes are reflective of a whole reorganization of epigenome. Hallmarks of nuclear reorganization in cancer are found in the long regions of chromatin marked by histone methylation (LOCKs) and nuclear lamina interactions (LADs). In this review, we focus on a novel perspective that DNA methylation changes in cancer impact the global structure of heterochromatin, LADs and LOCKs, and how these global changes, in turn, contribute to gene expression changes and genomic stability.
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Affiliation(s)
| | - Kirsten C Sadler
- Program in Biology, New York University Abu Dhabi,Abu Dhabi, United Arab Emirates
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29
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Achinger-Kawecka J, Taberlay PC, Clark SJ. Alterations in Three-Dimensional Organization of the Cancer Genome and Epigenome. COLD SPRING HARBOR SYMPOSIA ON QUANTITATIVE BIOLOGY 2017; 81:41-51. [PMID: 28424341 DOI: 10.1101/sqb.2016.81.031013] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The structural and functional basis of the genome is provided by the three-dimensional (3D) chromatin state. To enable accurate gene regulation, enhancer elements and promoter regions are brought into close spatial proximity to ensure proper, cell type-specific gene expression. In cancer, genetic and epigenetic processes can deregulate the transcriptional program. To investigate whether the 3D chromatin state is also disrupted in cancer we performed Hi-C chromosome conformation sequencing in normal and prostate cancer cells and compared the chromatin interaction maps with changes to the genome and epigenome. Notably, we find that additional topologically associated domain (TAD) boundaries are formed in cancer cells resulting in smaller TADs and altered gene expression profiles. The new TAD boundaries are commonly associated with copy-number changes observed in the cancer genome. We also identified new cancer-specific chromatin loops within TADs that are enriched for enhancers and promoters. Finally, we find that many of the long-range epigenetically silenced (LRES) and long-range epigenetically active (LREA) regions in cancer are characterized by differential chromatin interactions. Together our data provide a new insight into charting alterations in higher-order structure and the relationship with genetic, epigenetic, and transcriptional changes across the cancer genome.
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Affiliation(s)
- Joanna Achinger-Kawecka
- Epigenetics Research Laboratory, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.,St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Darlinghurst, New South Wales 2010, Australia
| | - Phillippa C Taberlay
- Epigenetics Research Laboratory, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.,St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Darlinghurst, New South Wales 2010, Australia.,School of Medicine, Faculty of Health, University of Tasmania, Hobart, Tasmania 7000, Australia
| | - Susan J Clark
- Epigenetics Research Laboratory, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.,St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Darlinghurst, New South Wales 2010, Australia
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30
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Affiliation(s)
- Jiazhu Wu
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China
| | - Huidong Shi
- Georgia Cancer Center, Augusta University, Augusta, Georgia, USA.,Department of Biochemistry and Molecular Biology, Augusta University, Augusta, Georgia, USA
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