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Xia Y, Sun M, Huang H, Jin WL. Drug repurposing for cancer therapy. Signal Transduct Target Ther 2024; 9:92. [PMID: 38637540 PMCID: PMC11026526 DOI: 10.1038/s41392-024-01808-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/05/2024] [Accepted: 03/19/2024] [Indexed: 04/20/2024] Open
Abstract
Cancer, a complex and multifactorial disease, presents a significant challenge to global health. Despite significant advances in surgical, radiotherapeutic and immunological approaches, which have improved cancer treatment outcomes, drug therapy continues to serve as a key therapeutic strategy. However, the clinical efficacy of drug therapy is often constrained by drug resistance and severe toxic side effects, and thus there remains a critical need to develop novel cancer therapeutics. One promising strategy that has received widespread attention in recent years is drug repurposing: the identification of new applications for existing, clinically approved drugs. Drug repurposing possesses several inherent advantages in the context of cancer treatment since repurposed drugs are typically cost-effective, proven to be safe, and can significantly expedite the drug development process due to their already established safety profiles. In light of this, the present review offers a comprehensive overview of the various methods employed in drug repurposing, specifically focusing on the repurposing of drugs to treat cancer. We describe the antitumor properties of candidate drugs, and discuss in detail how they target both the hallmarks of cancer in tumor cells and the surrounding tumor microenvironment. In addition, we examine the innovative strategy of integrating drug repurposing with nanotechnology to enhance topical drug delivery. We also emphasize the critical role that repurposed drugs can play when used as part of a combination therapy regimen. To conclude, we outline the challenges associated with repurposing drugs and consider the future prospects of these repurposed drugs transitioning into clinical application.
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Affiliation(s)
- Ying Xia
- Center for Clinical Laboratories, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, PR China
- The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, 550001, PR China
- School of Clinical Laboratory Science, Guizhou Medical University, Guiyang, 550004, PR China
- Division of Gastroenterology and Hepatology, Department of Medicine and, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ming Sun
- Center for Clinical Laboratories, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, PR China
- School of Clinical Laboratory Science, Guizhou Medical University, Guiyang, 550004, PR China
| | - Hai Huang
- Center for Clinical Laboratories, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, PR China.
- School of Clinical Laboratory Science, Guizhou Medical University, Guiyang, 550004, PR China.
| | - Wei-Lin Jin
- Institute of Cancer Neuroscience, Medical Frontier Innovation Research Center, The First Hospital of Lanzhou University, The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, PR China.
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Marchiano F, Haering M, Habermann BH. OUP accepted manuscript. Nucleic Acids Res 2022; 50:W490-W499. [PMID: 35524562 PMCID: PMC9252804 DOI: 10.1093/nar/gkac306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 04/09/2022] [Accepted: 04/15/2022] [Indexed: 11/13/2022] Open
Abstract
Mitochondria are subcellular organelles present in almost all eukaryotic cells, which play a central role in cellular metabolism. Different tissues, health and age conditions are characterized by a difference in mitochondrial structure and composition. The visual data mining platform mitoXplorer 1.0 was developed to explore the expression dynamics of genes associated with mitochondrial functions that could help explain these differences. It, however, lacked functions aimed at integrating mitochondria in the cellular context and thus identifying regulators that help mitochondria adapt to cellular needs. To fill this gap, we upgraded the mitoXplorer platform to version 2.0 (mitoXplorer 2.0). In this upgrade, we implemented two novel integrative functions, network analysis and transcription factor enrichment, to specifically help identify signalling or transcriptional regulators of mitochondrial processes. In addition, we implemented several other novel functions to allow the platform to go beyond simple data visualization, such as an enrichment function for mitochondrial processes, a function to explore time-series data, the possibility to compare datasets across species and an IDconverter to help facilitate data upload. We demonstrate the usefulness of these functions in three specific use cases. mitoXplorer 2.0 is freely available without login at http://mitoxplorer2.ibdm.univ-mrs.fr.
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Affiliation(s)
- Fabio Marchiano
- Aix-Marseille University, CNRS, IBDM UMR 7288, 13009 Marseille, France
| | - Margaux Haering
- Aix-Marseille University, CNRS, IBDM UMR 7288, 13009 Marseille, France
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Yim A, Koti P, Bonnard A, Marchiano F, Dürrbaum M, Garcia-Perez C, Villaveces J, Gamal S, Cardone G, Perocchi F, Storchova Z, Habermann BH. mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations. Nucleic Acids Res 2020; 48:605-632. [PMID: 31799603 PMCID: PMC6954439 DOI: 10.1093/nar/gkz1128] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 10/30/2019] [Accepted: 11/18/2019] [Indexed: 12/12/2022] Open
Abstract
Mitochondria participate in metabolism and signaling. They adapt to the requirements of various cell types. Publicly available expression data permit to study expression dynamics of genes with mitochondrial function (mito-genes) in various cell types, conditions and organisms. Yet, we lack an easy way of extracting these data for mito-genes. Here, we introduce the visual data mining platform mitoXplorer, which integrates expression and mutation data of mito-genes with a manually curated mitochondrial interactome containing ∼1200 genes grouped in 38 mitochondrial processes. User-friendly analysis and visualization tools allow to mine mitochondrial expression dynamics and mutations across various datasets from four model species including human. To test the predictive power of mitoXplorer, we quantify mito-gene expression dynamics in trisomy 21 cells, as mitochondrial defects are frequent in trisomy 21. We uncover remarkable differences in the regulation of the mitochondrial transcriptome and proteome in one of the trisomy 21 cell lines, caused by dysregulation of the mitochondrial ribosome and resulting in severe defects in oxidative phosphorylation. With the newly developed Fiji plugin mitoMorph, we identify mild changes in mitochondrial morphology in trisomy 21. Taken together, mitoXplorer (http://mitoxplorer.ibdm.univ-mrs.fr) is a user-friendly, web-based and freely accessible software, aiding experimental scientists to quantify mitochondrial expression dynamics.
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Affiliation(s)
- Annie Yim
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Prasanna Koti
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Adrien Bonnard
- Aix-Marseille University, INSERM, TAGC U1090, 13009 Marseille, France
| | - Fabio Marchiano
- Aix-Marseille University, CNRS, IBDM UMR 7288, 13009 Marseille, France
| | - Milena Dürrbaum
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Cecilia Garcia-Perez
- Functional Genomics of Mitochondrial Signaling, Gene Center, Ludwig Maximilian University (LMU), Munich, Germany
| | - Jose Villaveces
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Salma Gamal
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Giovanni Cardone
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Fabiana Perocchi
- Functional Genomics of Mitochondrial Signaling, Gene Center, Ludwig Maximilian University (LMU), Munich, Germany
| | - Zuzana Storchova
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.,Department of Molecular Genetics, TU Kaiserslautern, Paul Ehrlich Strasse 24, 67663 Kaiserslautern, Germany
| | - Bianca H Habermann
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.,Aix-Marseille University, CNRS, IBDM UMR 7288, 13009 Marseille, France
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Turanli B, Altay O, Borén J, Turkez H, Nielsen J, Uhlen M, Arga KY, Mardinoglu A. Systems biology based drug repositioning for development of cancer therapy. Semin Cancer Biol 2019; 68:47-58. [PMID: 31568815 DOI: 10.1016/j.semcancer.2019.09.020] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 09/23/2019] [Accepted: 09/24/2019] [Indexed: 01/20/2023]
Abstract
Drug repositioning is a powerful method that can assists the conventional drug discovery process by using existing drugs for treatment of a disease rather than its original indication. The first examples of repurposed drugs were discovered serendipitously, however data accumulated by high-throughput screenings and advancements in computational biology methods have paved the way for rational drug repositioning methods. As chemotherapeutic agents have notorious side effects that significantly reduce quality of life, drug repositioning promises repurposed noncancer drugs with little or tolerable adverse effects for cancer patients. Here, we review current drug-related data types and databases including some examples of web-based drug repositioning tools. Next, we describe systems biology approaches to be used in drug repositioning for effective cancer therapy. Finally, we highlight examples of mostly repurposed drugs for cancer treatment and provide an overview of future expectations in the field for development of effective treatment strategies.
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Affiliation(s)
- Beste Turanli
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17121, Sweden; Department of Bioengineering, Marmara University, Istanbul, Turkey; Department of Bioengineering, Istanbul Medeniyet University, Istanbul, Turkey
| | - Ozlem Altay
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17121, Sweden
| | - Jan Borén
- Department of Molecular and Clinical Medicine, University of Gothenburg and Sahlgrenska University Hospital Gothenburg, Sweden
| | - Hasan Turkez
- Department of Molecular Biology and Genetics, Erzurum Technical University, Erzurum 25240, Turkey
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Mathias Uhlen
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17121, Sweden
| | | | - Adil Mardinoglu
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17121, Sweden; Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London SE1 9RT, United Kingdom.
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Revealing pathway cross-talk related to diabetes mellitus by Monte Carlo Cross-Validation analysis. Open Life Sci 2017. [DOI: 10.1515/biol-2017-0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
AbstractObjectiveTo explore potential functional biomarkers in diabetes mellitus (DM) by utilizing gene pathway cross-talk.MethodsFirstly, potential disrupted pathways that were enriched by differentially expressed genes (DEGs) were identified based on biological pathways downloaded from the Ingenuity Pathways Analysis (IPA) database. In addition, we quantified the pathway crosstalk for each pair of pathways based on Discriminating Score (DS). Random forest (RF) classification was then employed to find the top 10 pairs of pathways with a high area under the curve (AUC) value between DM samples versus normal samples based on 10-fold cross-validation. Finally, a Monte Carlo Cross-Validation was applied to demonstrate the identified pairs of pathways by a mutual information analysis.ResultsA total of 247 DEGs in normal and disease samples were identified. Based on the F-test, 50 disrupted pathways were obtained with false discovery rate (FDR) < 0.01. Simultaneously, after calculating the DS, the top 10 pairs of pathways were selected based on a higher AUC value as measured by RF classification. From the Monte Carlo Cross-Validation, we considered the top 10 pairs of pathways with higher AUC values ranked for all 50 bootstraps as the most frequently detected ones.ConclusionThe pairs of pathways identified in our study might be key regulators in DM.
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