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Luo Y, Melhem S, Feelisch M, Chatre L, Morton NM, Dolga AM, van Goor H. Thiosulphate sulfurtransferase: Biological roles and therapeutic potential. Redox Biol 2025; 82:103595. [PMID: 40107018 PMCID: PMC11957799 DOI: 10.1016/j.redox.2025.103595] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2025] [Revised: 03/13/2025] [Accepted: 03/13/2025] [Indexed: 03/22/2025] Open
Abstract
Mitochondria are central to eukaryotic cell function, driving energy production, intermediary metabolism, and cellular homeostasis. Dysregulation of mitochondrial function often results in oxidative stress, a hallmark of numerous diseases, underscoring the critical need for maintaining mitochondrial integrity. Among mitochondrial enzymes, thiosulfate sulfurtransferase (TST) has emerged as a key regulator of sulfur metabolism, redox balance, and Fe-S protein maintenance. Beyond its well-known role in cyanide detoxification, TST facilitates hydrogen sulfide (H2S) metabolism by catalyzing the transfer of sulfur from persulfides (R-SSH) to thiosulfate (S2O32-), promoting H2S oxidation and preventing its toxic accumulation. Additionally, TST contributes to the thiol-dependent antioxidant system by regulating reactive sulfur species and sustaining mitochondrial functionality through its role in sulfide-driven bioenergetics. This review highlights the biochemical and therapeutic significance of TST in mitochondrial and cellular health, emphasizing its protective roles in diseases associated with oxidative stress and mitochondrial dysfunction. Dysregulation of TST has been implicated in diverse pathologies, including specific metabolic disorders, neurological diseases, cardiovascular conditions, kidney dysfunction, inflammatory bowel disease, and cancer. These associations underline TST's potential as a biomarker and therapeutic target. Therapeutic strategies to activate the TST pathway are explored, with a focus on sodium thiosulfate (STS), novel small molecule (Hit 2), and recombinant hTST protein. STS, an FDA-approved compound, has demonstrated antioxidant and anti-inflammatory effects across multiple preclinical models, mitigating oxidative damage and improving mitochondrial integrity. A slow-release oral formulation of STS is under development, offering promise for expanding its clinical applications. Small molecule activators like Hit 2 and hTST protein have shown efficacy in enhancing mitochondrial respiration and reducing oxidative stress, though both reagents need further in vitro and in vivo investigations. Despite promising advancements, TST-based therapies remain underexplored. Future research should focus on leveraging TST's interplay with pathways like NRF2 signaling, investigating its broader protective roles in cellular health, and developing targeted interventions. Enhancing TST activity represents an innovative therapeutic approach for addressing mitochondrial dysfunction, oxidative stress, and their associated pathologies, offering new hope for the treatment of diseases associated with mitochondrial dysfunction.
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Affiliation(s)
- Yang Luo
- University of Groningen, Dept. of Molecular Pharmacology, Groningen Research Institute of Pharmacy, Faculty of Science and Engineering, Groningen, the Netherlands; University Medical Center Groningen, Dept. of Pathology and Medical Biology, Groningen, the Netherlands
| | - Shaden Melhem
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Martin Feelisch
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Laurent Chatre
- Université de Caen Normandie, CNRS, Normandie Univ, ISTCT, UMR6030, GIP Cyceron, Caen, F-14000, France
| | - Nicholas M Morton
- Centre for Systems Health and Integrated Metabolic Research, School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Amalia M Dolga
- University of Groningen, Dept. of Molecular Pharmacology, Groningen Research Institute of Pharmacy, Faculty of Science and Engineering, Groningen, the Netherlands
| | - Harry van Goor
- University Medical Center Groningen, Dept. of Pathology and Medical Biology, Groningen, the Netherlands.
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Shen J, He Y, Li S, Chen H. Crosstalk of methylation and tamoxifen in breast cancer (Review). Mol Med Rep 2024; 30:180. [PMID: 39129315 PMCID: PMC11338244 DOI: 10.3892/mmr.2024.13304] [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: 06/02/2024] [Accepted: 07/23/2024] [Indexed: 08/13/2024] Open
Abstract
Tamoxifen is a widely used anti‑estrogen drug in the endocrine therapy of breast cancer (BC). It blocks estrogen signaling by competitively binding to estrogen receptor α (ERα), thereby inhibiting the growth of BC cells. However, with the long‑term application of tamoxifen, a subset of patients with BC have shown resistance to tamoxifen, which leads to low overall survival and progression‑free survival. The molecular mechanism of resistance is mainly due to downregulation of ERα expression and abnormal activation of the PI3K/AKT/mTOR signaling pathway. Moreover, the downregulation of targeted gene expression mediated by DNA methylation is an important regulatory mode to control protein expression. In the present review, methylation and tamoxifen are briefly introduced, followed by a focus on the effect of methylation on tamoxifen resistance and sensitivity. Finally, the clinical application of methylation for tamoxifen is described, including its use as a prognostic indicator. Finally, it is hypothesized that when methylation is used in combination with tamoxifen, it could recover the resistance of tamoxifen.
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Affiliation(s)
- Jin Shen
- Department of Rehabilitation, The Affiliated Zhuzhou Hospital of Xiangya Medical College, Central South University, Zhuzhou, Hunan 412000, P.R. China
| | - Yan He
- Department of Neurology, The Affiliated Zhuzhou Hospital of Xiangya Medical College, Central South University, Zhuzhou, Hunan 412000, P.R. China
| | - Shengpeng Li
- Department of Rehabilitation, The Affiliated Zhuzhou Hospital of Xiangya Medical College, Central South University, Zhuzhou, Hunan 412000, P.R. China
| | - Huimin Chen
- Department of Rehabilitation, The Affiliated Zhuzhou Hospital of Xiangya Medical College, Central South University, Zhuzhou, Hunan 412000, P.R. China
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Lagarde CB, Kavalakatt J, Benz MC, Hawes ML, Arbogast CA, Cullen NM, McConnell EC, Rinderle C, Hebert KL, Khosla M, Belgodere JA, Hoang VT, Collins-Burow BM, Bunnell BA, Burow ME, Alahari SK. Obesity-associated epigenetic alterations and the obesity-breast cancer axis. Oncogene 2024; 43:763-775. [PMID: 38310162 DOI: 10.1038/s41388-024-02954-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/05/2024]
Abstract
Both breast cancer and obesity can regulate epigenetic changes or be regulated by epigenetic changes. Due to the well-established link between obesity and an increased risk of developing breast cancer, understanding how obesity-mediated epigenetic changes affect breast cancer pathogenesis is critical. Researchers have described how obesity and breast cancer modulate the epigenome individually and synergistically. In this review, the epigenetic alterations that occur in obesity, including DNA methylation, histone, and chromatin modification, accelerated epigenetic age, carcinogenesis, metastasis, and tumor microenvironment modulation, are discussed. Delineating the relationship between obesity and epigenetic regulation is vital to furthering our understanding of breast cancer pathogenesis.
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Affiliation(s)
- Courtney B Lagarde
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Joachim Kavalakatt
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Megan C Benz
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Mackenzie L Hawes
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Carter A Arbogast
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Nicole M Cullen
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Emily C McConnell
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Caroline Rinderle
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Katherine L Hebert
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Maninder Khosla
- Department of Biochemistry and Molecular Biology, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA
| | - Jorge A Belgodere
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
- Department of Biological and Agricultural Engineering, Louisiana State University and Agricultural Center, Baton Rouge, LA, 70803, USA
| | - Van T Hoang
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Bridgette M Collins-Burow
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Bruce A Bunnell
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Matthew E Burow
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA.
| | - Suresh K Alahari
- Department of Biochemistry and Molecular Biology, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA.
- Stanley S. Scott Cancer Center, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA.
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4
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DeGroat W, Abdelhalim H, Patel K, Mendhe D, Zeeshan S, Ahmed Z. Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine. Sci Rep 2024; 14:1. [PMID: 38167627 PMCID: PMC10762256 DOI: 10.1038/s41598-023-50600-8] [Citation(s) in RCA: 148] [Impact Index Per Article: 148.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024] Open
Abstract
Personalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatments through predictive analysis and deep phenotyping. In this study, we proposed and employed a novel approach combining traditional statistics and a nexus of cutting-edge AI/ML techniques to identify significant biomarkers for our predictive engine by analyzing the complete transcriptome of CVD patients. After robust gene expression data pre-processing, we utilized three statistical tests (Pearson correlation, Chi-square test, and ANOVA) to assess the differences in transcriptomic expression and clinical characteristics between healthy individuals and CVD patients. Next, the recursive feature elimination classifier assigned rankings to transcriptomic features based on their relation to the case-control variable. The top ten percent of commonly observed significant biomarkers were evaluated using four unique ML classifiers (Random Forest, Support Vector Machine, Xtreme Gradient Boosting Decision Trees, and k-Nearest Neighbors). After optimizing hyperparameters, the ensembled models, which were implemented using a soft voting classifier, accurately differentiated between patients and healthy individuals. We have uncovered 18 transcriptomic biomarkers that are highly significant in the CVD population that were used to predict disease with up to 96% accuracy. Additionally, we cross-validated our results with clinical records collected from patients in our cohort. The identified biomarkers served as potential indicators for early detection of CVDs. With its successful implementation, our newly developed predictive engine provides a valuable framework for identifying patients with CVDs based on their biomarker profiles.
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Affiliation(s)
- William DeGroat
- Health Care Policy and Aging Research, Rutgers Institute for Health, Rutgers University, 112 Paterson St, New Brunswick, NJ, 08901, USA
| | - Habiba Abdelhalim
- Health Care Policy and Aging Research, Rutgers Institute for Health, Rutgers University, 112 Paterson St, New Brunswick, NJ, 08901, USA
| | - Kush Patel
- Health Care Policy and Aging Research, Rutgers Institute for Health, Rutgers University, 112 Paterson St, New Brunswick, NJ, 08901, USA
| | - Dinesh Mendhe
- Health Care Policy and Aging Research, Rutgers Institute for Health, Rutgers University, 112 Paterson St, New Brunswick, NJ, 08901, USA
| | - Saman Zeeshan
- Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany St, New Brunswick, NJ, USA
| | - Zeeshan Ahmed
- Health Care Policy and Aging Research, Rutgers Institute for Health, Rutgers University, 112 Paterson St, New Brunswick, NJ, 08901, USA.
- Department of Medicine/Cardiovascular Disease and Hypertension, Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, 125 Paterson St, New Brunswick, NJ, USA.
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