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Zhou Y, Li Y, Chenm J, Mei K, Kang M, Chen P, Li Q. Matrix Protein of Vesicular Stomatitis Virus Targets the Mitochondria, Reprograms Glucose Metabolism, and Sensitizes to 2-Deoxyglucose in Glioblastoma. Hum Gene Ther 2024. [PMID: 39001830 DOI: 10.1089/hum.2024.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2024] Open
Abstract
A potential therapeutic approach for cancer treatment is target oxidative phosphorylation and glycolysis simultaneously. The matrix protein of vesicular stomatitis virus (VSV MP) can target the surface of mitochondria, causing morphological changes that may be associated with mitochondrial dysfunction and oxidative phosphorylation inhibition. Previous research has shown that mitochondrial abnormalities can direct glucose metabolism toward glycolysis. Thus, after treatment with VSV MP, glycolysis inhibition is necessary to completely block glucose metabolism and eradicate cancer. Here, to inhibit glycolysis, the 2-deoxy-D-glucose (2-DG), a synthetic glucose analog was used to combine with VSV MP to treat cancer. This study aims to determine how VSV MP affects the glucose bioenergetic metabolism of cancer cells and to evaluate the synergistic effect of 2-DG when combined with VSV. Our results indicated that in U87 and C6 glioblastoma cell lines, VSV MP caused mitochondrial membrane potential loss, cytochrome c release, and glucose bioenergetics metabolism reprogramming. When combined with 2-DG, VSV MP synergistically aggravated cell viability, apoptosis, and G2/M phase arrest. Meanwhile, the combination therapy exacerbated ATP depletion, activated AMPK, and inhibited mammalian target of rapamycin signaling pathways. In addition, 2-DG treatment alone induced autophagy in glioblastoma cells; however, VSV MP inhibited the autophagy induced by 2-DG in combined treatment and finally contributed to the enhanced cytotoxic effect of the combination strategy in U87 and C6 cancer cells. In the orthotopic U87 glioblastoma model and subcutaneous C6 glioblastoma model, the combined treatment led to significant tumor regression and prolonged survival. A potent therapeutic approach for treating glioblastoma may be found in the combination of VSV MP and glycolytic inhibitors.
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Affiliation(s)
- Yi Zhou
- Department of Abdominal Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Yongzhong Li
- Department of Oncology, LuXian People's Hospital, Luzhou, China
| | - Jing Chenm
- Department of Abdominal Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Kai Mei
- Department of Abdominal Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Mingxiang Kang
- Department of Oncology, LuXian People's Hospital, Luzhou, China
| | - Ping Chen
- Department of Abdominal Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Qiu Li
- Division of Abdominal Tumor Multimodality Treatment, Department of Medical Oncology, West China Hospital, Cancer Center, Sichuan University, Chengdu, China
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Saxena S, Dagar N, Shelke V, Lech M, Khare P, Gaikwad AB. Metabolic reprogramming: Unveiling the therapeutic potential of targeted therapies against kidney disease. Drug Discov Today 2023; 28:103765. [PMID: 37690600 DOI: 10.1016/j.drudis.2023.103765] [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: 07/13/2023] [Revised: 08/20/2023] [Accepted: 09/05/2023] [Indexed: 09/12/2023]
Abstract
As a high-metabolic-rate organ, the kidney exhibits metabolic reprogramming (MR) in various disease states. Given the >800 million cases of kidney disease worldwide in 2022, understanding the specific bioenergetic pathways involved and developing targeted interventions are vital needs. The reprogramming of metabolic pathways (glucose metabolism, amino acid metabolism, etc.) has been observed in kidney disease. Therapies targeting these specific pathways have proven to be an efficient approach for retarding kidney disease progression. In this review, we focus on potential pharmacological interventions targeting MR that have advanced through Phase III/IV clinical trials for the management of kidney disease and promising preclinical studies laying the groundwork for future clinical investigations.
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Affiliation(s)
- Shubhangi Saxena
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani Campus, Rajasthan 333031, India
| | - Neha Dagar
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani Campus, Rajasthan 333031, India
| | - Vishwadeep Shelke
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani Campus, Rajasthan 333031, India
| | - Maciej Lech
- Division of Nephrology, Department of Medicine IV, LMU University Hospital, Ludwig Maximilians University Munich, 80336 Munich, Germany
| | - Pragyanshu Khare
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani Campus, Rajasthan 333031, India
| | - Anil Bhanudas Gaikwad
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Pilani Campus, Rajasthan 333031, India.
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Fernández-Rodicio S, Ferro-Costas G, Sampedro-Viana A, Bazarra-Barreiros M, Ferreirós A, López-Arias E, Pérez-Mato M, Ouro A, Pumar JM, Mosqueira AJ, Alonso-Alonso ML, Castillo J, Hervella P, Iglesias-Rey R. Perfusion-weighted software written in Python for DSC-MRI analysis. Front Neuroinform 2023; 17:1202156. [PMID: 37593674 PMCID: PMC10431979 DOI: 10.3389/fninf.2023.1202156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 06/27/2023] [Indexed: 08/19/2023] Open
Abstract
Introduction Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes. Methods The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood-brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature. Results A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland-Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF. Conclusion An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented.
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Affiliation(s)
- Sabela Fernández-Rodicio
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | | | - Ana Sampedro-Viana
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Marcos Bazarra-Barreiros
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | | | - Esteban López-Arias
- Translational Stroke Laboratory (TREAT), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - María Pérez-Mato
- Neurological Sciences and Cerebrovascular Research Laboratory, Department of Neurology and Stroke Center, La Paz University Hospital, Neuroscience Area of IdiPAZ Health Research Institute, Universidad Autónoma de Madrid, Madrid, Spain
| | - Alberto Ouro
- NeuroAging Group (NEURAL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - José M. Pumar
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Antonio J. Mosqueira
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - María Luz Alonso-Alonso
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - José Castillo
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Pablo Hervella
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Ramón Iglesias-Rey
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
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Mozaffari M, Nyström NN, Li A, Bellyou M, Scholl TJ, Bartha R. Intracellular Acidification in a Rat C6 Glioma Model following Cariporide Injection Investigated by CEST-MRI. Metabolites 2023; 13:823. [PMID: 37512530 PMCID: PMC10386045 DOI: 10.3390/metabo13070823] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 06/30/2023] [Accepted: 06/30/2023] [Indexed: 07/30/2023] Open
Abstract
Acidification of cancerous tissue induced pharmacologically may slow tumor growth and can be detected using magnetic resonance imaging. Numerous studies have shown that pharmacologically inhibiting specific transporters, such as the Na+/H+ exchanger 1 (NHE1), can alter glycolitic metabolism and affect tumor acidosis. The sodium proton exchanger inhibitor Cariporide can acidify U87MG gliomas in mice. This study aimed to determine whether Cariporide could acidify C6 glioma tumors in rats with an intact immune system. C6 glioma cells were implanted in the right brain hemisphere of ten rats. Chemical exchange saturation transfer (CEST) MRI (9.4T) was acquired on days 7-8 and 14-15 after implantation to measure in vivo tissue intracellular pH (pHi) within the tumors and on the contralateral side. pHi was basic relative to contralateral tissue at both time points assessed using the amine and amide concentration-independent detection (AACID) value. On day 14-15, measurements were made before and up to 160 min after Cariporide injection (N = 6). Twenty minutes after drug injection, the average AACID value in the tumor significantly increased by ∼6.4% compared to pre-injection, corresponding to 0.31 ± 0.20 lower pHi, while in contralateral tissue, AACID value increased significantly by ∼4.3% compared to pre-injection, corresponding to 0.22 ± 0.19 lower pHi. Control rats without tumors showed no changes following injection of Cariporide dissolved in 10% or 1% DMSO and diluted in PBS. This study demonstrates the sensitivity of CEST-based pH-weighted imaging for monitoring the response of tumors to pharmacologically induced acidification.
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Affiliation(s)
- Maryam Mozaffari
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Nivin N Nyström
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Alex Li
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Miranda Bellyou
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Timothy J Scholl
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
- Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
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Qi Q, Fox MS, Lim H, Sullivan R, Li A, Bellyou M, Desjardins L, McClennan A, Bartha R, Hoffman L, Scholl TJ, Lee TY, Thiessen JD. Glucose Infusion Induced Change in Intracellular pH and Its Relationship with Tumor Glycolysis in a C6 Rat Model of Glioblastoma. Mol Imaging Biol 2023; 25:271-282. [PMID: 36418769 DOI: 10.1007/s11307-022-01726-0] [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: 11/05/2021] [Revised: 03/12/2022] [Accepted: 03/25/2022] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The reliance on glycolytic metabolism is a hallmark of tumor metabolism. Excess acid and protons are produced, leading to an acidic tumor environment. Therefore, we explored the relationship between the tumor glycolytic metabolism and tissue pH by comparing 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and hyperpolarized [1-13C]pyruvate MR spectroscopy imaging (MRSI) to chemical exchange saturation transfer (CEST) MRI measurements of tumor pH. METHODS 106 C6 glioma cells were implanted in the brains of male Wistar rats (N = 11) using stereotactic surgery. A 60-min PET acquisition after a bolus of FDG was performed at 11-13 days post implantation, and standardized uptake value (SUV) was calculated. CEST measurements were acquired the following day before and during constant infusion of glucose solution. Tumor intracellular pH (pHi) was evaluated using amine and amide concentration-independent detection (AACID) CEST MRI. The change of pHi (∆pHi) was calculated as the difference between pHi pre- and during glucose infusion. Rats were imaged immediately with hyperpolarized [1-13C]pyruvate MRSI. Regional maps of the ratio of Lac:Pyr were acquired. The correlations between SUV, Lac:Pyr ratio, and ∆pHi were evaluated using Pearson's correlation. RESULTS A decrease of 0.14 in pHi was found after glucose infusion in tumor region. Significant correlations between tumor glycolysis measurements of Lac:Pyr and ∆pHi within the tumor (ρ = 0.83, P = 0.01) and peritumoral region (ρ = 0.76, P = 0.028) were observed. No significant correlations were found between tumor SUV and ∆pHi within the tumor (ρ = - 0.45, P = 0.17) and peritumor regions (ρ = - 0.6, P = 0.051). CONCLUSION AACID detected the changes in pHi induced by glucose infusion. Significant correlations between tumor glycolytic measurement of Lac:Pyr and tumoral and peritumoral pHi and ∆pHi suggest the intrinsic relationship between tumor glycolytic metabolism and the tumor pH environment as well as the peritumor pH environment.
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Affiliation(s)
- Qi Qi
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Department of Physics and Astronomy, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Matthew S Fox
- Department of Physics and Astronomy, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada
| | - Heeseung Lim
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Robarts Research Institute, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Rebecca Sullivan
- Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada.,Department of Pathology, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Alex Li
- Robarts Research Institute, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Miranda Bellyou
- Robarts Research Institute, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Lise Desjardins
- Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada
| | - Andrew McClennan
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada
| | - Robert Bartha
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Robarts Research Institute, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Department of Medical Imaging, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Lisa Hoffman
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada.,Department of Pathology, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Department of Anatomy and Cell Biology, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Timothy J Scholl
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada.,Ontario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada
| | - Ting-Yim Lee
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada.,Robarts Research Institute, The University of Western Ontario, London, ON, N6A 3K7, Canada.,Department of Medical Imaging, The University of Western Ontario, London, ON, N6A 3K7, Canada
| | - Jonathan D Thiessen
- Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 3K7, Canada. .,Molecular Imaging Program, The University of Western Ontario, London, ON, N6A 3K7, Canada. .,Imaging Program, Lawson Health Research Institute, London, ON, N6A 4V2, Canada. .,Department of Medical Imaging, The University of Western Ontario, London, ON, N6A 3K7, Canada.
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