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Chen J, Chen J, Yu C, Xia K, Yang B, Wang R, Li Y, Shi K, Zhang Y, Xu H, Zhang X, Wang J, Chen Q, Liang C. Metabolic reprogramming: a new option for the treatment of spinal cord injury. Neural Regen Res 2025; 20:1042-1057. [PMID: 38989936 DOI: 10.4103/nrr.nrr-d-23-01604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 02/27/2024] [Indexed: 07/12/2024] Open
Abstract
Spinal cord injuries impose a notably economic burden on society, mainly because of the severe after-effects they cause. Despite the ongoing development of various therapies for spinal cord injuries, their effectiveness remains unsatisfactory. However, a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming. In this review, we explore the metabolic changes that occur during spinal cord injuries, their consequences, and the therapeutic tools available for metabolic reprogramming. Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling. However, spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism, lipid metabolism, and mitochondrial dysfunction. These metabolic disturbances lead to corresponding pathological changes, including the failure of axonal regeneration, the accumulation of scarring, and the activation of microglia. To rescue spinal cord injury at the metabolic level, potential metabolic reprogramming approaches have emerged, including replenishing metabolic substrates, reconstituting metabolic couplings, and targeting mitochondrial therapies to alter cell fate. The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury. To further advance the metabolic treatment of the spinal cord injury, future efforts should focus on a deeper understanding of neurometabolism, the development of more advanced metabolomics technologies, and the design of highly effective metabolic interventions.
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Affiliation(s)
- Jiangjie Chen
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Jinyang Chen
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Chao Yu
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Kaishun Xia
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Biao Yang
- Qiandongnan Prefecture People's Hospital, Kaili, Guizhou Province, China
| | - Ronghao Wang
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Yi Li
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Kesi Shi
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Yuang Zhang
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Haibin Xu
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Xuesong Zhang
- Department of Orthopedics, Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jingkai Wang
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Qixin Chen
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Chengzhen Liang
- Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
- Orthopedics Research Institute of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, Zhejiang Province, China
- Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
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2
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Miguel V, Alcalde-Estévez E, Sirera B, Rodríguez-Pascual F, Lamas S. Metabolism and bioenergetics in the pathophysiology of organ fibrosis. Free Radic Biol Med 2024; 222:85-105. [PMID: 38838921 DOI: 10.1016/j.freeradbiomed.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 05/15/2024] [Accepted: 06/02/2024] [Indexed: 06/07/2024]
Abstract
Fibrosis is the tissue scarring characterized by excess deposition of extracellular matrix (ECM) proteins, mainly collagens. A fibrotic response can take place in any tissue of the body and is the result of an imbalanced reaction to inflammation and wound healing. Metabolism has emerged as a major driver of fibrotic diseases. While glycolytic shifts appear to be a key metabolic switch in activated stromal ECM-producing cells, several other cell types such as immune cells, whose functions are intricately connected to their metabolic characteristics, form a complex network of pro-fibrotic cellular crosstalk. This review purports to clarify shared and particular cellular responses and mechanisms across organs and etiologies. We discuss the impact of the cell-type specific metabolic reprogramming in fibrotic diseases in both experimental and human pathology settings, providing a rationale for new therapeutic interventions based on metabolism-targeted antifibrotic agents.
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Affiliation(s)
- Verónica Miguel
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain.
| | - Elena Alcalde-Estévez
- Program of Physiological and Pathological Processes, Centro de Biología Molecular "Severo Ochoa" (CBMSO) (CSIC-UAM), Madrid, Spain; Department of Systems Biology, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcalá, Alcalá de Henares, Spain
| | - Belén Sirera
- Program of Physiological and Pathological Processes, Centro de Biología Molecular "Severo Ochoa" (CBMSO) (CSIC-UAM), Madrid, Spain
| | - Fernando Rodríguez-Pascual
- Program of Physiological and Pathological Processes, Centro de Biología Molecular "Severo Ochoa" (CBMSO) (CSIC-UAM), Madrid, Spain
| | - Santiago Lamas
- Program of Physiological and Pathological Processes, Centro de Biología Molecular "Severo Ochoa" (CBMSO) (CSIC-UAM), Madrid, Spain.
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3
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Luan H, Chen S, Lian J, Zhao B, Xu X, Chen Y, Yang Y, Jiang Z, Qi M, Liu J, Zhang W, Luan T, Hong X. Biofluorescence imaging-guided spatial metabolic tracing: In vivo tracking of metabolic activity in circulating tumor cell-mediated multi-organ metastases. Talanta 2024; 280:126696. [PMID: 39137660 DOI: 10.1016/j.talanta.2024.126696] [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: 04/11/2024] [Revised: 08/05/2024] [Accepted: 08/09/2024] [Indexed: 08/15/2024]
Abstract
Circulating tumor cells (CTC) are considered metastatic precursors that are shed from the primary or metastatic deposits and navigate the bloodstream before undergoing extravasation to establish distant metastases. Metabolic reprogramming appears to be a hallmark of metastatic progression, yet current methods for evaluating metabolic heterogeneity within organ-specific metastases in vivo are limited. To overcome this challenge, we present Biofluorescence Imaging-Guided Spatial Metabolic Tracing (BIGSMT), a novel approach integrating in vivo biofluorescence imaging, stable isotope tracing, stain-free laser capture microdissection, and liquid chromatography-mass spectrometry. This innovative technology obviates the need for staining or intricate sample preparation, mitigating metabolite loss, and substantially enhances detection sensitivity and accuracy through chemical derivatization of polar metabolites in central carbon pathways. Application of BIGSMT to a preclinical CTC-mediated metastasis mouse model revealed significant heterogeneity in the in vivo carbon flux from glucose into glycolysis and the tricarboxylic acid (TCA) cycle across distinct metastatic sites. Our analysis indicates that carbon predominantly enters the TCA cycle through the enzymatic reaction catalyzed by pyruvate dehydrogenase. Thus, our spatially resolved BIGSMT technology provides fresh insights into the metabolic heterogeneity and evolution during melanoma CTC-mediated metastatic progression and points to novel therapeutic opportunities.
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Affiliation(s)
- Hemi Luan
- Department of Biomedical Engineering, School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou, 510006, China; Guangdong Provincial Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center, Jieyang, 515200, China; State Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
| | - Shuailong Chen
- School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Jingru Lian
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Boxi Zhao
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Xiaolong Xu
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yafei Chen
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yufang Yang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Zhuofeng Jiang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Min Qi
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Jialing Liu
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Wenyong Zhang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Tiangang Luan
- Guangdong Provincial Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center, Jieyang, 515200, China; School of Environmental and Chemical Engineering, Wuyi University, Jiangmen, 529020, China.
| | - Xin Hong
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China; Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, 518055, China; Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China.
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4
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Vallianatou T, Angerer TB, Kaya I, Nilsson A, Shariatgorji R, Svenningsson P, Andrén PE. Applying Spatial Metabolomics To Investigate Age- and Drug-Induced Neurochemical Changes. ACS Chem Neurosci 2024; 15:2822-2829. [PMID: 39072364 PMCID: PMC11311129 DOI: 10.1021/acschemneuro.4c00199] [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: 04/03/2024] [Revised: 06/14/2024] [Accepted: 07/02/2024] [Indexed: 07/30/2024] Open
Abstract
In an era when population aging is increasing the burden of neurodegenerative conditions, deciphering the mechanisms underlying brain senescence is more important than ever. Here, we present a spatial metabolomics analysis of age-induced neurochemical alterations in the mouse brain using negative ionization mode mass spectrometry imaging. The age-dependent effects of the acetylcholinesterase inhibitor tacrine were simultaneously examined. For ultrahigh mass resolution analysis, we utilized a Fourier-transform ion cyclotron resonance spectrometer. To complement this, a trapped ion mobility spectrometry time-of-flight analyzer provided high speed and lateral resolution. The chosen approach facilitated the detection and identification of a wide range of metabolites, from amino acids to sphingolipids. We reported significant, age-dependent alterations in brain lipids which were most evident for sulfatides and lysophosphatidic acids. Sulfatide species, which are mainly localized to white matter, either increased or decreased with age, depending on the carbon chain length and hydroxylation stage. Lysophosphatidic acids were found to decrease with age in the detailed cortical and hippocampal subregions. An age-dependent increase in the glutamine/glutamate ratio, an indicator of glia-neuron interconnection and neurotoxicity, was detected after tacrine administration. The presented metabolic mapping approach was able to provide visualizations of the lipid signaling and neurotransmission alterations induced by early aging and can thus be beneficial to further elucidating age-related neurochemical pathways.
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Affiliation(s)
- Theodosia Vallianatou
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
| | - Tina B. Angerer
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
| | - Ibrahim Kaya
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
| | - Anna Nilsson
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
| | - Reza Shariatgorji
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
| | - Per Svenningsson
- Department
of Clinical Neuroscience, Karolinska Institute, Stockholm SE-17177, Sweden
| | - Per E. Andrén
- Department
of Pharmaceutical Biosciences, Spatial Mass Spectrometry, Science
for Life Laboratory, Uppsala University, Uppsala SE-75124, Sweden
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5
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Zhang J, Mao Z, Zhang D, Guo L, Zhao H, Miao M. Mass spectrometry imaging as a promising analytical technique for herbal medicines: an updated review. Front Pharmacol 2024; 15:1442870. [PMID: 39148546 PMCID: PMC11324582 DOI: 10.3389/fphar.2024.1442870] [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: 06/03/2024] [Accepted: 07/18/2024] [Indexed: 08/17/2024] Open
Abstract
Herbal medicines (HMs) have long played a pivotal role in preventing and treating various human diseases and have been studied widely. However, the complexities present in HM metabolites and their unclear mechanisms of action have posed significant challenges in the modernization of traditional Chinese medicine (TCM). Over the past two decades, mass spectrometry imaging (MSI) has garnered increasing attention as a robust analytical technique that enables the simultaneous execution of qualitative, quantitative, and localization analyses without complex sample pretreatment. With advances in technical solutions, MSI has been extensively applied in the field of HMs. MSI, a label-free ion imaging technique can comprehensively map the spatial distribution of HM metabolites in plant native tissues, thereby facilitating the effective quality control of HMs. Furthermore, the spatial dimension information of small molecule endogenous metabolites within animal tissues provided by MSI can also serve as a supplement to uncover pharmacological and toxicological mechanisms of HMs. In the review, we provide an overview of the three most common MSI techniques. In addition, representative applications in HM are highlighted. Finally, we discuss the current challenges and propose several potential solutions. We hope that the summary of recent findings will contribute to the application of MSI in exploring metabolites and mechanisms of action of HMs.
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Affiliation(s)
- Jinying Zhang
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Zhiguo Mao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Ding Zhang
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Lin Guo
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Hui Zhao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Mingsan Miao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
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Simpson CE, Ledford JG, Liu G. Application of Metabolomics across the Spectrum of Pulmonary and Critical Care Medicine. Am J Respir Cell Mol Biol 2024; 71:1-9. [PMID: 38547373 PMCID: PMC11225873 DOI: 10.1165/rcmb.2024-0080ps] [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: 02/19/2024] [Accepted: 03/28/2024] [Indexed: 07/02/2024] Open
Abstract
In recent years, metabolomics, the systematic study of small-molecule metabolites in biological samples, has yielded fresh insights into the molecular determinants of pulmonary diseases and critical illness. The purpose of this article is to orient the reader to this emerging field by discussing the fundamental tenets underlying metabolomics research, the tools and techniques that serve as foundational methodologies, and the various statistical approaches to analysis of metabolomics datasets. We present several examples of metabolomics applied to pulmonary and critical care medicine to illustrate the potential of this avenue of research to deepen our understanding of pathophysiology. We conclude by reviewing recent advances in the field and future research directions that stand to further the goal of personalizing medicine to improve patient care.
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Affiliation(s)
- Catherine E. Simpson
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Julie G. Ledford
- Department of Cellular and Molecular Medicine, University of Arizona, Tucson, Arizona; and
| | - Gang Liu
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
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7
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Garfinkel AM, Ilker E, Miyazawa H, Schmeisser K, Tennessen JM. Historic obstacles and emerging opportunities in the field of developmental metabolism - lessons from Heidelberg. Development 2024; 151:dev202937. [PMID: 38912552 PMCID: PMC11299503 DOI: 10.1242/dev.202937] [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] [Indexed: 06/25/2024]
Abstract
The field of developmental metabolism is experiencing a technological revolution that is opening entirely new fields of inquiry. Advances in metabolomics, small-molecule sensors, single-cell RNA sequencing and computational modeling present new opportunities for exploring cell-specific and tissue-specific metabolic networks, interorgan metabolic communication, and gene-by-metabolite interactions in time and space. Together, these advances not only present a means by which developmental biologists can tackle questions that have challenged the field for centuries, but also present young scientists with opportunities to define new areas of inquiry. These emerging frontiers of developmental metabolism were at the center of a highly interactive 2023 EMBO workshop 'Developmental metabolism: flows of energy, matter, and information'. Here, we summarize key discussions from this forum, emphasizing modern developmental biology's challenges and opportunities.
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Affiliation(s)
- Alexandra M. Garfinkel
- Pediatric Genomics Discovery Program, Department of Pediatrics and Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
- Section of Endocrinology, Department of Internal Medicine, Yale University, New Haven, CT 06510, USA
| | - Efe Ilker
- Max Planck Institute for the Physics of Complex Systems, Dresden 01187, Germany
| | - Hidenobu Miyazawa
- Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
| | - Kathrin Schmeisser
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany
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Li H, Humphreys BD. Spatially resolved metabolomic dataset of distinct human kidney anatomic regions. Data Brief 2024; 54:110431. [PMID: 38708307 PMCID: PMC11067325 DOI: 10.1016/j.dib.2024.110431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 05/07/2024] Open
Abstract
Cortex, medulla and papilla are three major human kidney anatomic structures and they harbour unique metabolic functions, but the underlying metabolomic profiles are largely unknown at spatial resolution. Here, we generated a spatially resolved metabolomics dataset on human kidney cortex, medulla and papilla tissues dissected from the same donor. Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry (MALDI-IMS) was used to detect metabolite species over mass-to-charge ratios of 50 -1500 for each section at a resolution of 10 × 10 µm2 pixel size. We present raw data matrix of each sample, feature annotations, raw AnnData merged from three samples and processed AnnData files after quality control, dimensional reduction and data integration, which contains a total of 170,459 spatially resolved metabolomes with 562 features detected. This dataset can be either visualized through an interactive browser or further analyzed to study metabolomic heterogeneity across regional human kidney anatomy.
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Affiliation(s)
- Haikuo Li
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Benjamin D. Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA
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9
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Valihrach L, Zucha D, Abaffy P, Kubista M. A practical guide to spatial transcriptomics. Mol Aspects Med 2024; 97:101276. [PMID: 38776574 DOI: 10.1016/j.mam.2024.101276] [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: 10/30/2023] [Revised: 04/30/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024]
Abstract
Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.
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Affiliation(s)
- Lukas Valihrach
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic; Department of Cellular Neurophysiology, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic.
| | - Daniel Zucha
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic; Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology, Prague, Czech Republic
| | - Pavel Abaffy
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic
| | - Mikael Kubista
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.
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10
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Chapman NM, Chi H. Metabolic rewiring and communication in cancer immunity. Cell Chem Biol 2024; 31:862-883. [PMID: 38428418 PMCID: PMC11177544 DOI: 10.1016/j.chembiol.2024.02.001] [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: 11/09/2023] [Revised: 01/29/2024] [Accepted: 02/08/2024] [Indexed: 03/03/2024]
Abstract
The immune system shapes tumor development and progression. Although immunotherapy has transformed cancer treatment, its overall efficacy remains limited, underscoring the need to uncover mechanisms to improve therapeutic effects. Metabolism-associated processes, including intracellular metabolic reprogramming and intercellular metabolic crosstalk, are emerging as instructive signals for anti-tumor immunity. Here, we first summarize the roles of intracellular metabolic pathways in controlling immune cell function in the tumor microenvironment. How intercellular metabolic communication regulates anti-tumor immunity, and the impact of metabolites or nutrients on signaling events, are also discussed. We then describe how targeting metabolic pathways in tumor cells or intratumoral immune cells or via nutrient-based interventions may boost cancer immunotherapies. Finally, we conclude with discussions on profiling and functional perturbation methods of metabolic activity in intratumoral immune cells, and perspectives on future directions. Uncovering the mechanisms for metabolic rewiring and communication in the tumor microenvironment may enable development of novel cancer immunotherapies.
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Affiliation(s)
- Nicole M Chapman
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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Berrell N, Sadeghirad H, Blick T, Bidgood C, Leggatt GR, O'Byrne K, Kulasinghe A. Metabolomics at the tumor microenvironment interface: Decoding cellular conversations. Med Res Rev 2024; 44:1121-1146. [PMID: 38146814 DOI: 10.1002/med.22010] [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: 09/21/2023] [Revised: 11/08/2023] [Accepted: 12/07/2023] [Indexed: 12/27/2023]
Abstract
Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.
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Affiliation(s)
- Naomi Berrell
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Habib Sadeghirad
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Tony Blick
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Charles Bidgood
- APCRC-Q, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Graham R Leggatt
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Ken O'Byrne
- Princess Alexandra Hospital, Woolloongabba, Queensland, Australia
| | - Arutha Kulasinghe
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
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12
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Jackson BT, Finley LWS. Metabolic regulation of the hallmarks of stem cell biology. Cell Stem Cell 2024; 31:161-180. [PMID: 38306993 PMCID: PMC10842269 DOI: 10.1016/j.stem.2024.01.003] [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: 12/03/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 02/04/2024]
Abstract
Stem cells perform many different functions, each of which requires specific metabolic adaptations. Over the past decades, studies of pluripotent and tissue stem cells have uncovered a range of metabolic preferences and strategies that correlate with or exert control over specific cell states. This review aims to describe the common themes that emerge from the study of stem cell metabolism: (1) metabolic pathways supporting stem cell proliferation, (2) metabolic pathways maintaining stem cell quiescence, (3) metabolic control of cellular stress responses and cell death, (4) metabolic regulation of stem cell identity, and (5) metabolic requirements of the stem cell niche.
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Affiliation(s)
- Benjamin T Jackson
- Cell Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, New York, NY, USA
| | - Lydia W S Finley
- Cell Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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13
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Stroe MC, Gao J, Pitz M, Fischer R. Complexity of fungal polyketide biosynthesis and function. Mol Microbiol 2024; 121:18-25. [PMID: 37961029 DOI: 10.1111/mmi.15192] [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: 08/01/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 11/15/2023]
Abstract
Where does one draw the line between primary and secondary metabolism? The answer depends on the perspective. Microbial secondary metabolites (SMs) were at first believed not to be very important for the producers because they are dispensable for growth under laboratory conditions. However, such compounds become important in natural niches of the organisms, and some are of prime importance for humanity. Polyketides are an important group of SMs with aflatoxin as a well-known and well-characterized example. In Aspergillus spp., all 34 afl genes encoding the enzymes for aflatoxin biosynthesis are located in close vicinity on chromosome III in a so-called gene cluster. This led to the assumption that most genes required for polyketide biosynthesis are organized in gene clusters. Recent research, however, revealed an enormous complexity of the biosynthesis of different polyketides, ranging from individual polyketide synthases to a gene cluster producing several compounds, or to several clusters with additional genes scattered in the genome for the production of one compound. Research of the last decade furthermore revealed a huge potential for SM biosynthesis hidden in fungal genomes, and methods were developed to wake up such sleeping genes. The analysis of organismic interactions starts to reveal some of the ecological functions of polyketides for the producing fungi.
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Affiliation(s)
- Maria C Stroe
- Department of Microbiology, Institute for Applied Biosciences, Karlsruhe Institute of Technology (KIT) - South Campus, Karlsruhe, Germany
| | - Jia Gao
- Department of Microbiology, Institute for Applied Biosciences, Karlsruhe Institute of Technology (KIT) - South Campus, Karlsruhe, Germany
| | - Michael Pitz
- Department of Microbiology, Institute for Applied Biosciences, Karlsruhe Institute of Technology (KIT) - South Campus, Karlsruhe, Germany
| | - Reinhard Fischer
- Department of Microbiology, Institute for Applied Biosciences, Karlsruhe Institute of Technology (KIT) - South Campus, Karlsruhe, Germany
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14
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Morosi L, Miotto M, Timo S, Carloni S, Bruno E, Meroni M, Menna E, Lodato S, Rescigno M, Martano G. MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments. Brief Bioinform 2023; 25:bbad463. [PMID: 38102070 PMCID: PMC10753532 DOI: 10.1093/bib/bbad463] [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: 06/23/2023] [Revised: 10/13/2023] [Accepted: 11/22/2023] [Indexed: 12/17/2023] Open
Abstract
Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.
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Affiliation(s)
- Lavinia Morosi
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
| | - Matteo Miotto
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
| | - Sara Timo
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
| | - Sara Carloni
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
- Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, Pieve Emanuele (MI), Italy
| | - Eleonora Bruno
- Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei tumori di Milano. Via Venezian 1, Milan, Italy
| | - Marina Meroni
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via Mario Negri 2, Milan, Italy
| | - Elisabetta Menna
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
- Institute of Neuroscience, National Research Council of Italy (CNR) c/o Humanitas Mirasole S.p.A, Via Manzoni 56, Rozzano (MI), Italy
| | - Simona Lodato
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
- Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, Pieve Emanuele (MI), Italy
| | - Maria Rescigno
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
- Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, Pieve Emanuele (MI), Italy
| | - Giuseppe Martano
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy
- Institute of Neuroscience, National Research Council of Italy (CNR) c/o Humanitas Mirasole S.p.A, Via Manzoni 56, Rozzano (MI), Italy
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15
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Lu T, Freytag L, Narayana VK, Moore Z, Oliver SJ, Valkovic A, Nijagal B, Peterson AL, de Souza DP, McConville MJ, Whittle JR, Best SA, Freytag S. Matrix Selection for the Visualization of Small Molecules and Lipids in Brain Tumors Using Untargeted MALDI-TOF Mass Spectrometry Imaging. Metabolites 2023; 13:1139. [PMID: 37999235 PMCID: PMC10673325 DOI: 10.3390/metabo13111139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 11/25/2023] Open
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging allows for the study of metabolic activity in the tumor microenvironment of brain cancers. The detectable metabolites within these tumors are contingent upon the choice of matrix, deposition technique, and polarity setting. In this study, we compared the performance of three different matrices, two deposition techniques, and the use of positive and negative polarity in two different brain cancer types and across two species. Optimal combinations were confirmed by a comparative analysis of lipid and small-molecule abundance by using liquid chromatography-mass spectrometry and RNA sequencing to assess differential metabolites and enzymes between normal and tumor regions. Our findings indicate that in the tumor-bearing brain, the recrystallized α-cyano-4-hydroxycinnamic acid matrix with positive polarity offered superior performance for both detected metabolites and consistency with other techniques. Beyond these implications for brain cancer, our work establishes a workflow to identify optimal matrices for spatial metabolomics studies.
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Affiliation(s)
- Tianyao Lu
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Lutz Freytag
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
| | - Vinod K. Narayana
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne 3010, Australia
| | - Zachery Moore
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Shannon J. Oliver
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
| | - Adam Valkovic
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
| | - Brunda Nijagal
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne 3010, Australia
| | - Amanda L. Peterson
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne 3010, Australia
| | - David P. de Souza
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne 3010, Australia
| | - Malcolm J. McConville
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne 3010, Australia
- Department of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Melbourne 3010, Australia
| | - James R. Whittle
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne 3052, Australia
| | - Sarah A. Best
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Saskia Freytag
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
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