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Sushentsev N, Hamm G, Flint L, Birtles D, Zakirov A, Richings J, Ling S, Tan JY, McLean MA, Ayyappan V, Horvat Menih I, Brodie C, Miller JL, Mills IG, Gnanapragasam VJ, Warren AY, Barry ST, Goodwin RJA, Barrett T, Gallagher FA. Metabolic imaging across scales reveals distinct prostate cancer phenotypes. Nat Commun 2024; 15:5980. [PMID: 39013948 PMCID: PMC11252279 DOI: 10.1038/s41467-024-50362-5] [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: 10/03/2023] [Accepted: 07/07/2024] [Indexed: 07/18/2024] Open
Abstract
Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.
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Affiliation(s)
- Nikita Sushentsev
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - Gregory Hamm
- Integrated BioAnalysis, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Lucy Flint
- Integrated BioAnalysis, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Daniel Birtles
- Integrated BioAnalysis, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Aleksandr Zakirov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Jack Richings
- Predictive AI & Data, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Stephanie Ling
- Integrated BioAnalysis, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Jennifer Y Tan
- Predictive AI & Data, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Mary A McLean
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Vinay Ayyappan
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Ines Horvat Menih
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Cara Brodie
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Jodi L Miller
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ian G Mills
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Vincent J Gnanapragasam
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Division of Urology, Department of Surgery, University of Cambridge, Cambridge, UK
- Cambridge Urology Translational Research and Clinical Trials Office, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, UK
| | - Anne Y Warren
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Simon T Barry
- Bioscience, Early Oncology, AstraZeneca, Cambridge, UK
| | - Richard J A Goodwin
- Integrated BioAnalysis, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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2
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Lu Y, Han X, Zhang H, Zheng L, Li X. Multi-omics study on the molecular mechanism of anlotinib in regulating tumor metabolism. Eur J Pharmacol 2024; 975:176639. [PMID: 38729415 DOI: 10.1016/j.ejphar.2024.176639] [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: 01/24/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/12/2024]
Abstract
Anlotinib, an orally administered small molecule inhibitor of receptor tyrosine kinases (RTKs), exerts significant anti-angiogenic and vascular normalization effects. However, the mechanisms underlying its involvement in tumor metabolic reprogramming are still unclear. This study aims to investigate the distribution and expression levels of metabolites within tumors after anlotinib treatment using spatial metabolomics analysis. Subsequently, by integrating the transcriptomics and proteomics analyses, we identified that anlotinib treatment primarily modulated four metabolic pathways, including taurine and hypotaurine metabolism, steroid synthesis, pentose phosphate pathway, and lipid biosynthesis. This regulation significantly influenced the metabolic levels of compounds such as sulfonic acids, cholesterol, inositol phosphate pyrophosphate, and palmitoyl-CoA in the tumor, thereby impacting tumor initiation and progression. This study provides potential metabolic biomarkers for anlotinib treatment in tumors.
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Affiliation(s)
- Yu Lu
- School of Life Science and Technology, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 639 Longmian Road, Nanjing, 211198, China
| | - Xuedan Han
- School of Life Science and Technology, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 639 Longmian Road, Nanjing, 211198, China
| | - Hongwei Zhang
- Department of Anesthesiology, The First Affiliated Hospital of Xinxiang Medical University, Wei Hui, 453100, China
| | - Lufeng Zheng
- School of Life Science and Technology, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 639 Longmian Road, Nanjing, 211198, China.
| | - Xiaoman Li
- Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
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3
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Brennen WN, Le Magnen C, Karkampouna S, Anselmino N, Bock N, Choo N, Clark AK, Coleman IM, Dolgos R, Ferguson AM, Goode DL, Krutihof-de Julio M, Navone NM, Nelson PS, O'Neill E, Porter LH, Ranasinghe W, Sunada T, Williams ED, Butler LM, Corey E, van Weerden WM, Taylor RA, Risbridger GP, Lawrence MG. Defining the challenges and opportunities for using patient-derived models in prostate cancer research. Prostate 2024; 84:623-635. [PMID: 38450798 PMCID: PMC11014775 DOI: 10.1002/pros.24682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/29/2024] [Accepted: 02/15/2024] [Indexed: 03/08/2024]
Abstract
BACKGROUND There are relatively few widely used models of prostate cancer compared to other common malignancies. This impedes translational prostate cancer research because the range of models does not reflect the diversity of disease seen in clinical practice. In response to this challenge, research laboratories around the world have been developing new patient-derived models of prostate cancer, including xenografts, organoids, and tumor explants. METHODS In May 2023, we held a workshop at the Monash University Prato Campus for researchers with expertise in establishing and using a variety of patient-derived models of prostate cancer. This review summarizes our collective ideas on how patient-derived models are currently being used, the common challenges, and future opportunities for maximizing their usefulness in prostate cancer research. RESULTS An increasing number of patient-derived models for prostate cancer are being developed. Despite their individual limitations and varying success rates, these models are valuable resources for exploring new concepts in prostate cancer biology and for preclinical testing of potential treatments. Here we focus on the need for larger collections of models that represent the changing treatment landscape of prostate cancer, robust readouts for preclinical testing, improved in vitro culture conditions, and integration of the tumor microenvironment. Additional priorities include ensuring model reproducibility, standardization, and replication, and streamlining the exchange of models and data sets among research groups. CONCLUSIONS There are several opportunities to maximize the impact of patient-derived models on prostate cancer research. We must develop large, diverse and accessible cohorts of models and more sophisticated methods for emulating the intricacy of patient tumors. In this way, we can use the samples that are generously donated by patients to advance the outcomes of patients in the future.
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Affiliation(s)
- W Nathaniel Brennen
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center (SKCCC), Johns Hopkins University, Baltimore, Maryland, USA
- Department of Urology, James Buchanan Brady Urological Institute, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Pharmacology & Molecular Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Clémentine Le Magnen
- Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Urology, University Hospital Basel, Basel, Switzerland
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Sofia Karkampouna
- Urology Research Laboratory, Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Nicolas Anselmino
- Department of Genitourinary Medical Oncology and the David H. Koch Center for Applied Research of Genitourinary Cancers, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nathalie Bock
- School of Biomedical Sciences at Translational Research Institute, Faculty of Health, Queensland University of Technology (QUT), Brisbane, QLD, Australia
- Max Planck Queensland Centre for the Materials Science of Extracellular Matrices, Queensland University of Technology (QUT), Brisbane, QLD, Australia
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
| | - Nicholas Choo
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
| | - Ashlee K Clark
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
| | - Ilsa M Coleman
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Robin Dolgos
- Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Urology, University Hospital Basel, Basel, Switzerland
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Alison M Ferguson
- Department for BioMedical Research, University of Bern, Bern, Switzerland
- Katharina Gaus Light Microscopy Facility, Mark Wainwright Analytical Centre, Division of Research and Enterprise, University of New South Wales, Sydney, NSW, Australia
| | - David L Goode
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Marianna Krutihof-de Julio
- Urology Research Laboratory, Department for BioMedical Research, University of Bern, Bern, Switzerland
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department for BioMedical Research, Translational Organoid Resource, University of Bern, Bern, Switzerland
| | - Nora M Navone
- Department of Genitourinary Medical Oncology and the David H. Koch Center for Applied Research of Genitourinary Cancers, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peter S Nelson
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Edward O'Neill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Laura H Porter
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
| | - Weranja Ranasinghe
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
- Department of Surgery, Monash University, Melbourne, VIC, Australia
- Department of Urology, Monash Health, Melbourne, VIC, Australia
- Department of Urology, Austin Health, Melbourne, VIC, Australia
| | - Takuro Sunada
- Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Elizabeth D Williams
- School of Biomedical Sciences at Translational Research Institute, Faculty of Health, Queensland University of Technology (QUT), Brisbane, QLD, Australia
- Australian Prostate Cancer Research Centre-Queensland, Brisbane, QLD, Australia
- Centre for Genomics and Personalised Health, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - Lisa M Butler
- South Australian Immunogenomics Cancer Institute, University of Adelaide, Adelaide, SA, Australia
- Precision Cancer Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Eva Corey
- Department of Urology, University of Washington, Seattle, Washington, USA
| | | | - Renea A Taylor
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Physiology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
- Cabrini Institute, Cabrini Health, Malvern, VIC, Australia
- Melbourne Urological Research Alliance, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Gail P Risbridger
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
- Cabrini Institute, Cabrini Health, Malvern, VIC, Australia
- Melbourne Urological Research Alliance, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Mitchell G Lawrence
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
- Cabrini Institute, Cabrini Health, Malvern, VIC, Australia
- Melbourne Urological Research Alliance, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
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4
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Vandenbosch M, Mutuku SM, Mantas MJQ, Patterson NH, Hallmark T, Claesen M, Heeren RMA, Hatcher NG, Verbeeck N, Ekroos K, Ellis SR. Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture. Anal Chem 2023; 95:18719-18730. [PMID: 38079536 DOI: 10.1021/acs.analchem.3c02724] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.
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Affiliation(s)
- Michiel Vandenbosch
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Shadrack M Mutuku
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
| | | | | | | | | | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Nathan G Hatcher
- Merck & Co., Inc., 770 Sumneytown Pk, West Point, Pennsylvania 19486, United States
| | | | - Kim Ekroos
- Lipidomics Consulting Ltd., Esbo 02230, Finland
| | - Shane R Ellis
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
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5
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Dudka I, Lundquist K, Wikström P, Bergh A, Gröbner G. Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes. J Transl Med 2023; 21:860. [PMID: 38012666 PMCID: PMC10683247 DOI: 10.1186/s12967-023-04747-7] [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: 05/22/2023] [Accepted: 11/21/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis. METHODS A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity). RESULTS Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B. CONCLUSIONS The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.
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Affiliation(s)
- Ilona Dudka
- Department of Chemistry, Umeå University, Umeå, Sweden
| | | | - Pernilla Wikström
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.
| | - Anders Bergh
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
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6
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Abstract
Imaging mass spectrometry is a well-established technology that can easily and succinctly communicate the spatial localization of molecules within samples. This review communicates the recent advances in the field, with a specific focus on matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) applied on tissues. The general sample preparation strategies for different analyte classes are explored, including special considerations for sample types (fresh frozen or formalin-fixed,) strategies for various analytes (lipids, metabolites, proteins, peptides, and glycans) and how multimodal imaging strategies can leverage the strengths of each approach is mentioned. This work explores appropriate experimental design approaches and standardization of processes needed for successful studies, as well as the various data analysis platforms available to analyze data and their strengths. The review concludes with applications of imaging mass spectrometry in various fields, with a focus on medical research, and some examples from plant biology and microbe metabolism are mentioned, to illustrate the breadth and depth of MALDI IMS.
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Affiliation(s)
- Jessica L Moore
- Department of Proteomics, Discovery Life Sciences, Huntsville, Alabama 35806, United States
| | - Georgia Charkoftaki
- Department of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, Connecticut 06520, United States
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7
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Swinkels D, Kocherlakota S, Das Y, Dane AD, Wever EJM, Vaz FM, Bazan NG, Van Veldhoven PP, Baes M. DHA Shortage Causes the Early Degeneration of Photoreceptors and RPE in Mice With Peroxisomal β-Oxidation Deficiency. Invest Ophthalmol Vis Sci 2023; 64:10. [PMID: 37934161 PMCID: PMC10631513 DOI: 10.1167/iovs.64.14.10] [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: 05/23/2023] [Accepted: 09/06/2023] [Indexed: 11/08/2023] Open
Abstract
Purpose Patients deficient in peroxisomal β-oxidation, which is essential for the synthesis of docosahexaenoic acid (DHA, C22:6n-3) and breakdown of very-long-chain polyunsaturated fatty acids (VLC-PUFAs), both important components of photoreceptor outer segments, develop retinopathy present with retinopathy. The representative mouse model lacking the central enzyme of this pathway, multifunctional protein 2 (Mfp2-/-), also show early-onset retinal decay and cell-autonomous retinal pigment epithelium (RPE) degeneration, accompanied by reduced plasma and retinal DHA levels. In this study, we investigated whether DHA supplementation can rescue the retinal degeneration of Mfp2-/- mice. Methods Mfp2+/- breeding pairs and their offspring were fed a 0.12% DHA or control diet during gestation and lactation and until sacrifice. Offspring were analyzed for retinal function via electroretinograms and for lipid composition of neural retina and plasma with lipidome analysis and gas chromatography, respectively, and histologically using retinal sections and RPE flatmounts at the ages of 4, 8, and 16 weeks. Results DHA supplementation to Mfp2-/- mice restored retinal DHA levels and prevented photoreceptor shortening, death, and impaired functioning until 8 weeks. In addition, rescue of retinal DHA levels temporarily improved the ability of the RPE to phagocytose outer segments and delayed the RPE dedifferentiation. However, despite the initial rescue of retinal integrity, DHA supplementation could not prevent retinal degeneration at 16 weeks. Conclusions We reveal that the shortage of a systemic supply of DHA is pivotal for the early retinal degeneration in Mfp2-/- mice. Furthermore, we report that adequate retinal DHA levels are essential not only for photoreceptors but also for RPE homeostasis.
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Affiliation(s)
- Daniëlle Swinkels
- Laboratory of Cell Metabolism, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Sai Kocherlakota
- Laboratory of Cell Metabolism, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Yannick Das
- Laboratory of Cell Metabolism, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Adriaan D. Dane
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Chemistry and Pediatrics, Laboratory Genetic Metabolic Diseases, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Eric J. M. Wever
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Chemistry and Pediatrics, Laboratory Genetic Metabolic Diseases, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Frédéric M. Vaz
- Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Chemistry and Pediatrics, Laboratory Genetic Metabolic Diseases, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Inborn Errors of Metabolism, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands
| | - Nicolas G. Bazan
- Neuroscience Center of Excellence, Louisiana State University School of Medicine, Louisiana State University, New Orleans, Louisiana, United States
| | - Paul P. Van Veldhoven
- Laboratory of Peroxisome Biology and Intracellular Communication, Department of Cellular and Molecular Medicine, KU Leuven, Leuven, Belgium
| | - Myriam Baes
- Laboratory of Cell Metabolism, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
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8
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Logotheti S, Papadaki E, Zolota V, Logothetis C, Vrahatis AG, Soundararajan R, Tzelepi V. Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics. Cancers (Basel) 2023; 15:4357. [PMID: 37686633 PMCID: PMC10486655 DOI: 10.3390/cancers15174357] [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: 07/31/2023] [Revised: 08/21/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.
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Affiliation(s)
- Souzana Logotheti
- Department of Pathology, University of Patras, 26504 Patras, Greece; (S.L.); (E.P.); (V.Z.)
| | - Eugenia Papadaki
- Department of Pathology, University of Patras, 26504 Patras, Greece; (S.L.); (E.P.); (V.Z.)
- Department of Informatics, Ionian University, 49100 Corfu, Greece;
| | - Vasiliki Zolota
- Department of Pathology, University of Patras, 26504 Patras, Greece; (S.L.); (E.P.); (V.Z.)
| | - Christopher Logothetis
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | | | - Rama Soundararajan
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Vasiliki Tzelepi
- Department of Pathology, University of Patras, 26504 Patras, Greece; (S.L.); (E.P.); (V.Z.)
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9
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Saha R, Subramani K, Dey S, Sikdar S, Incharoensakdi A. Physicochemical properties of green synthesised ZnO nanoparticles and utilisation for treatment of breast cancer. Process Biochem 2023. [DOI: 10.1016/j.procbio.2023.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
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10
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Scheinberg T, Mak B, Butler L, Selth L, Horvath LG. Targeting lipid metabolism in metastatic prostate cancer. Ther Adv Med Oncol 2023; 15:17588359231152839. [PMID: 36743527 PMCID: PMC9893394 DOI: 10.1177/17588359231152839] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 01/05/2023] [Indexed: 02/04/2023] Open
Abstract
Despite key advances in the treatment of prostate cancer (PCa), a proportion of men have de novo resistance, and all will develop resistance to current therapeutics over time. Aberrant lipid metabolism has long been associated with prostate carcinogenesis and progression, but more recently there has been an explosion of preclinical and clinical data which is informing new clinical trials. This review explores the epidemiological links between obesity and metabolic syndrome and PCa, the evidence for altered circulating lipids in PCa and their potential role as biomarkers, as well as novel therapeutic strategies for targeting lipids in men with PCa, including therapies widely used in cardiovascular disease such as statins, metformin and lifestyle modification, as well as novel targeted agents such as sphingosine kinase inhibitors, DES1 inhibitors and agents targeting FASN and beta oxidation.
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Affiliation(s)
- Tahlia Scheinberg
- Medical Oncology, Chris O’Brien Lifehouse, Camperdown NSW, Australia,Advanced Prostate Cancer Group, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia,University of Sydney, Camperdown, NSW, Australia
| | - Blossom Mak
- Medical Oncology, Chris O’Brien Lifehouse, Camperdown NSW, Australia,Advanced Prostate Cancer Group, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia,University of Sydney, Camperdown, NSW, Australia
| | - Lisa Butler
- Prostate Cancer Research Group, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia,South Australian Immunogenomics Cancer Institute and Freemason’s Centre for Male Health and Wellbeing, University of Adelaide, South Australia, Australia
| | - Luke Selth
- South Australian Immunogenomics Cancer Institute and Freemason’s Centre for Male Health and Wellbeing, University of Adelaide, South Australia, Australia,Dame Roma Mitchell Cancer Research Labs, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia,Flinders Health and Medical Research Institute, Flinders University, College of Medicine and Public Health, Bedford Park, Australia
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Nevedomskaya E, Haendler B. From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer. Int J Mol Sci 2022; 23:ijms23116281. [PMID: 35682963 PMCID: PMC9181488 DOI: 10.3390/ijms23116281] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/24/2022] [Accepted: 06/01/2022] [Indexed: 02/01/2023] Open
Abstract
Cancer arises following alterations at different cellular levels, including genetic and epigenetic modifications, transcription and translation dysregulation, as well as metabolic variations. High-throughput omics technologies that allow one to identify and quantify processes involved in these changes are now available and have been instrumental in generating a wealth of steadily increasing data from patient tumors, liquid biopsies, and from tumor models. Extensive investigation and integration of these data have led to new biological insights into the origin and development of multiple cancer types and helped to unravel the molecular networks underlying this complex pathology. The comprehensive and quantitative analysis of a molecule class in a biological sample is named omics and large-scale omics studies addressing different prostate cancer stages have been performed in recent years. Prostate tumors represent the second leading cancer type and a prevalent cause of cancer death in men worldwide. It is a very heterogenous disease so that evaluating inter- and intra-tumor differences will be essential for a precise insight into disease development and plasticity, but also for the development of personalized therapies. There is ample evidence for the key role of the androgen receptor, a steroid hormone-activated transcription factor, in driving early and late stages of the disease, and this led to the development and approval of drugs addressing diverse targets along this pathway. Early genomic and transcriptomic studies have allowed one to determine the genes involved in prostate cancer and regulated by androgen signaling or other tumor-relevant signaling pathways. More recently, they have been supplemented by epigenomic, cistromic, proteomic and metabolomic analyses, thus, increasing our knowledge on the intricate mechanisms involved, the various levels of regulation and their interplay. The comprehensive investigation of these omics approaches and their integration into multi-omics analyses have led to a much deeper understanding of the molecular pathways involved in prostate cancer progression, and in response and resistance to therapies. This brings the hope that novel vulnerabilities will be identified, that existing therapies will be more beneficial by targeting the patient population likely to respond best, and that bespoke treatments with increased efficacy will be available soon.
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Affiliation(s)
| | - Bernard Haendler
- Correspondence: ; Tel.: +49-30-2215-41198; Fax: +49-30-468-18069
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