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Yang J, Xu J, Wang W, Zhang B, Yu X, Shi S. Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets. Signal Transduct Target Ther 2023; 8:210. [PMID: 37217462 DOI: 10.1038/s41392-023-01480-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 04/17/2023] [Accepted: 04/28/2023] [Indexed: 05/24/2023] Open
Abstract
Over decades, researchers have focused on the epigenetic control of DNA-templated processes. Histone modification, DNA methylation, chromatin remodeling, RNA modification, and noncoding RNAs modulate many biological processes that are crucial to the development of cancers. Dysregulation of the epigenome drives aberrant transcriptional programs. A growing body of evidence suggests that the mechanisms of epigenetic modification are dysregulated in human cancers and might be excellent targets for tumor treatment. Epigenetics has also been shown to influence tumor immunogenicity and immune cells involved in antitumor responses. Thus, the development and application of epigenetic therapy and cancer immunotherapy and their combinations may have important implications for cancer treatment. Here, we present an up-to-date and thorough description of how epigenetic modifications in tumor cells influence immune cell responses in the tumor microenvironment (TME) and how epigenetics influence immune cells internally to modify the TME. Additionally, we highlight the therapeutic potential of targeting epigenetic regulators for cancer immunotherapy. Harnessing the complex interplay between epigenetics and cancer immunology to develop therapeutics that combine thereof is challenging but could yield significant benefits. The purpose of this review is to assist researchers in understanding how epigenetics impact immune responses in the TME, so that better cancer immunotherapies can be developed.
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Affiliation(s)
- Jing Yang
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, Shanghai, China
- Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Jin Xu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, Shanghai, China
- Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Wei Wang
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, Shanghai, China
- Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Bo Zhang
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, Shanghai, China
- Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Xianjun Yu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Pancreatic Cancer Institute, Shanghai, China.
- Pancreatic Cancer Institute, Fudan University, Shanghai, China.
| | - Si Shi
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Pancreatic Cancer Institute, Shanghai, China.
- Pancreatic Cancer Institute, Fudan University, Shanghai, China.
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Wang Z, Gao J, Xu C. Tackling cellular senescence by targeting miRNAs. Biogerontology 2022; 23:387-400. [PMID: 35727469 DOI: 10.1007/s10522-022-09972-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 06/06/2022] [Indexed: 11/29/2022]
Abstract
Cellular senescence, which is characterized by permanent proliferation arrest, has become an important target for the amelioration of various human diseases. The activity of senescent cells is mainly related to the senescence-associated secretory phenotype (SASP). The SASP can cause chronic inflammation in local tissues and organs through autocrine and paracrine mechanisms, and a series of factors secreted by senescent cells can deteriorate the cellular microenvironment, promoting tumor formation and exacerbating aging-related diseases. Therefore, avoiding the promotion of cancer is an urgent problem. In recent years, increased attention has been given to the mechanistic study of microRNAs in senescence. As important posttranscriptional regulators, microRNAs possess unique tissue-specific expression in senescence. MicroRNAs can regulate the SASP by regulating proteins in the senescence signaling pathway, the reverse transcriptase activity of telomerase, the generation of reactive oxygen species and oxidative damage to mitochondria. Numerous studies have confirmed that removing senescent cells does not cause significant side effects, which also opens the door to the development of treatment modalities against senescent cells. Herein, this review discusses the double-edged sword of cellular senescence in tumors and aging-related diseases and emphasizes the roles of microRNAs in regulating the SASP, especially the potential of microRNAs to be used as therapeutic targets to inhibit senescence, giving rise to novel therapeutic approaches for the treatment of aging-associated diseases.
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Affiliation(s)
- Zehua Wang
- Obstetrics and Gynecology, Hospital of Fudan University, Shanghai, 200011, China.,Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China
| | - Jianwen Gao
- School of Medical Engineering, Ma'anshan University, No. 8, Huangchi Road, Gushu Town, Dangtu County, Ma'anshan, 243100, Anhui, China. .,Major of Biotechnological Pharmaceutics, Shanghai Pharmaceutical School, Shanghai, 200135, China.
| | - Congjian Xu
- Obstetrics and Gynecology, Hospital of Fudan University, Shanghai, 200011, China.,Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China.,Department of Obstetrics and Gynecology of Shanghai Medical School, Fudan University, Shanghai, 200032, China
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Khan FM, Sadeghi M, Gupta SK, Wolkenhauer O. A Network-Based Integrative Workflow to Unravel Mechanisms Underlying Disease Progression. Methods Mol Biol 2018; 1702:247-276. [PMID: 29119509 DOI: 10.1007/978-1-4939-7456-6_12] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Unraveling mechanisms underlying diseases has motivated the development of systems biology approaches. The key challenges for the development of mathematical models and computational tool are (1) the size of molecular networks, (2) the nonlinear nature of spatio-temporal interactions, and (3) feedback loops in the structure of interaction networks. We here propose an integrative workflow that combines structural analyses of networks, high-throughput data, and mechanistic modeling. As an illustration of the workflow, we use prostate cancer as a case study with the aim of identifying key functional components associated with primary to metastasis transitions. Analysis carried out by the workflow revealed that HOXD10, BCL2, and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN, and JUNB are playing a central role. The identified key elements of each network are validated using patient survival analysis. The workflow presented here allows experimentalists to use heterogeneous data sources for the identification of diagnostic and prognostic signatures.
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Affiliation(s)
- Faiz M Khan
- Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany
| | - Mehdi Sadeghi
- Research Institute for Fundamental Sciences (RIFS), University of Tabriz, Tabriz, Iran
| | - Shailendra K Gupta
- Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany.,Chhattisgarh Swami Vivekanand Technical University, Bhilai, Chhattisgarh, India
| | - Olaf Wolkenhauer
- Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany. .,Chhattisgarh Swami Vivekanand Technical University, Bhilai, Chhattisgarh, India. .,Stellenbosch Institute of Advanced Study (STIAS), Wallenberg Research Centre, Stellenbosch University, Stellenbosch, South Africa.
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Sadeghi M, Ranjbar B, Ganjalikhany MR, M. Khan F, Schmitz U, Wolkenhauer O, Gupta SK. MicroRNA and Transcription Factor Gene Regulatory Network Analysis Reveals Key Regulatory Elements Associated with Prostate Cancer Progression. PLoS One 2016; 11:e0168760. [PMID: 28005952 PMCID: PMC5179129 DOI: 10.1371/journal.pone.0168760] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 11/21/2016] [Indexed: 11/18/2022] Open
Abstract
Technological and methodological advances in multi-omics data generation and integration approaches help elucidate genetic features of complex biological traits and diseases such as prostate cancer. Due to its heterogeneity, the identification of key functional components involved in the regulation and progression of prostate cancer is a methodological challenge. In this study, we identified key regulatory interactions responsible for primary to metastasis transitions in prostate cancer using network inference approaches by integrating patient derived transcriptomic and miRomics data into gene/miRNA/transcription factor regulatory networks. One such network was derived for each of the clinical states of prostate cancer based on differentially expressed and significantly correlated gene, miRNA and TF pairs from the patient data. We identified key elements of each network using a network analysis approach and validated our results using patient survival analysis. We observed that HOXD10, BCL2 and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN and JUNB are playing a central role. Benefiting integrative networks our analysis suggests that some of these molecules were targeted by several overexpressed miRNAs which may have a major effect on the dysregulation of these molecules. For example, in the metastatic tumors five miRNAs (miR-671-5p, miR-665, miR-663, miR-512-3p and miR-371-5p) are mainly responsible for the dysregulation of STAT3 and hence can provide an opportunity for early detection of metastasis and development of alternative therapeutic approaches. Our findings deliver new details on key functional components in prostate cancer progression and provide opportunities for the development of alternative therapeutic approaches.
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Affiliation(s)
- Mehdi Sadeghi
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Bijan Ranjbar
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | | | - Faiz M. Khan
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany
| | - Ulf Schmitz
- Gene and Stem Cell Therapy Program, Centenary Institute, University of Sydney, Camperdown, Australia
- Sydney Medical School, University of Sydney, Camperdown, Australia
| | - Olaf Wolkenhauer
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany
- Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa
| | - Shailendra K. Gupta
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany
- Department of Bioinformatics, CSIR-Indian Institute of Toxicology Research, Lucknow, India
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