1
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Trivedi R, Bhat KP. Liquid biopsy: creating opportunities in brain space. Br J Cancer 2023; 129:1727-1746. [PMID: 37752289 PMCID: PMC10667495 DOI: 10.1038/s41416-023-02446-0] [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: 05/24/2023] [Revised: 09/10/2023] [Accepted: 09/15/2023] [Indexed: 09/28/2023] Open
Abstract
In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.
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Affiliation(s)
- Rakesh Trivedi
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Krishna P Bhat
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA
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2
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Khalili N, Shooli H, Hosseini N, Fathi Kazerooni A, Familiar A, Bagheri S, Anderson H, Bagley SJ, Nabavizadeh A. Adding Value to Liquid Biopsy for Brain Tumors: The Role of Imaging. Cancers (Basel) 2023; 15:5198. [PMID: 37958372 PMCID: PMC10650848 DOI: 10.3390/cancers15215198] [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: 09/18/2023] [Revised: 10/24/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023] Open
Abstract
Clinical management in neuro-oncology has changed to an integrative approach that incorporates molecular profiles alongside histopathology and imaging findings. While the World Health Organization (WHO) guideline recommends the genotyping of informative alterations as a routine clinical practice for central nervous system (CNS) tumors, the acquisition of tumor tissue in the CNS is invasive and not always possible. Liquid biopsy is a non-invasive approach that provides the opportunity to capture the complex molecular heterogeneity of the whole tumor through the detection of circulating tumor biomarkers in body fluids, such as blood or cerebrospinal fluid (CSF). Despite all of the advantages, the low abundance of tumor-derived biomarkers, particularly in CNS tumors, as well as their short half-life has limited the application of liquid biopsy in clinical practice. Thus, it is crucial to identify the factors associated with the presence of these biomarkers and explore possible strategies that can increase the shedding of these tumoral components into biological fluids. In this review, we first describe the clinical applications of liquid biopsy in CNS tumors, including its roles in the early detection of recurrence and monitoring of treatment response. We then discuss the utilization of imaging in identifying the factors that affect the detection of circulating biomarkers as well as how image-guided interventions such as focused ultrasound can help enhance the presence of tumor biomarkers through blood-brain barrier (BBB) disruption.
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Affiliation(s)
- Nastaran Khalili
- Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (N.K.); (A.F.K.); (A.F.)
| | - Hossein Shooli
- Department of Radiology, Bushehr University of Medical Sciences, Bushehr 75146-33196, Iran
| | - Nastaran Hosseini
- School of Medicine, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran;
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (N.K.); (A.F.K.); (A.F.)
- AI2D Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ariana Familiar
- Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (N.K.); (A.F.K.); (A.F.)
| | - Sina Bagheri
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (H.A.)
| | - Hannah Anderson
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (H.A.)
| | - Stephen J. Bagley
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Ali Nabavizadeh
- Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (N.K.); (A.F.K.); (A.F.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (H.A.)
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3
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Muller Bark J, Karpe AV, Doecke JD, Leo P, Jeffree RL, Chua B, Day BW, Beale DJ, Punyadeera C. A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients. Cancer Med 2023. [PMID: 37031458 DOI: 10.1002/cam4.5857] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/04/2023] [Accepted: 03/14/2023] [Indexed: 04/11/2023] Open
Abstract
BACKGROUND Despite aggressive treatment, more than 90% of glioblastoma (GBM) patients experience recurrences. GBM response to therapy is currently assessed by imaging techniques and tissue biopsy. However, difficulties with these methods may cause misinterpretation of treatment outcomes. Currently, no validated therapy response biomarkers are available for monitoring GBM progression. Metabolomics holds potential as a complementary tool to improve the interpretation of therapy responses to help in clinical interventions for GBM patients. METHODS Saliva and blood from GBM patients were collected pre and postoperatively. Patients were stratified conforming their progression-free survival (PFS) into favourable or unfavourable clinical outcomes (>9 months or PFS ≤ 9 months, respectively). Analysis of saliva (whole-mouth and oral rinse) and plasma samples was conducted utilising LC-QqQ-MS and LC-QTOF-MS to determine the metabolomic and lipidomic profiles. The data were investigated using univariate and multivariate statistical analyses and graphical LASSO-based graphic network analyses. RESULTS Altogether, 151 metabolites and 197 lipids were detected within all saliva and plasma samples. Among the patients with unfavourable outcomes, metabolites such as cyclic-AMP, 3-hydroxy-kynurenine, dihydroorotate, UDP and cis-aconitate were elevated, compared to patients with favourable outcomes during pre-and post-surgery. These metabolites showed to impact the pentose phosphate and Warburg effect pathways. The lipid profile of patients who experienced unfavourable outcomes revealed a higher heterogeneity in the abundance of lipids and fewer associations between markers in contrast to the favourable outcome group. CONCLUSION Our findings indicate that changes in salivary and plasma metabolites in GBM patients can potentially be employed as less invasive prognostic biomarkers/biomarker panel but validation with larger cohorts is required.
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Affiliation(s)
- Juliana Muller Bark
- Faculty of Health, Centre for Biomedical Technologies, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- Saliva and Liquid Biopsy Translational Laboratory, Griffith Institute for Drug Discovery - Griffith University, Brisbane, Queensland, Australia
- Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Gardens Point, Queensland, Australia
| | - Avinash V Karpe
- Environment, Commonwealth Scientific and Industrial Research Organization (CSIRO), Ecosciences Precinct, Dutton Park, Queensland, Australia
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organization (CSIRO), Acton, Australian Capital Territory, Australia
| | - James D Doecke
- Australian eHealth Research Centre, CSIRO. Level 7, Surgical Treatment and Rehabilitation Service - STARS, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
| | - Paul Leo
- Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Gardens Point, Queensland, Australia
- Faculty of Health, Translational Genomics Group, School of Biomedical Sciences, Queensland University of Technology, Woolloongabba, Australia
| | - Rosalind L Jeffree
- QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, University of Queensland, Herston, Queensland, Australia
- Kenneth G. Jamieson Department of Neurosurgery, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
- Cell and Molecular Biology Department, Sid Faithfull Brain Cancer Laboratory, QIMR Berghofer MRI, Brisbane, Queensland, Australia
| | - Benjamin Chua
- Faculty of Medicine, University of Queensland, Herston, Queensland, Australia
- Cancer Care Services, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Bryan W Day
- Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Gardens Point, Queensland, Australia
- Faculty of Medicine, University of Queensland, Herston, Queensland, Australia
- Cell and Molecular Biology Department, Sid Faithfull Brain Cancer Laboratory, QIMR Berghofer MRI, Brisbane, Queensland, Australia
| | - David J Beale
- Environment, Commonwealth Scientific and Industrial Research Organization (CSIRO), Ecosciences Precinct, Dutton Park, Queensland, Australia
| | - Chamindie Punyadeera
- Saliva and Liquid Biopsy Translational Laboratory, Griffith Institute for Drug Discovery - Griffith University, Brisbane, Queensland, Australia
- Menzies Health Institute, Griffith University, Southport, Queensland, Australia
- Translational Research Institute, Woolloongabba, Queensland, Australia
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4
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Aboud O, Liu YA, Fiehn O, Brydges C, Fragoso R, Lee HS, Riess J, Hodeify R, Bloch O. Application of Machine Learning to Metabolomic Profile Characterization in Glioblastoma Patients Undergoing Concurrent Chemoradiation. Metabolites 2023; 13:299. [PMID: 36837918 PMCID: PMC9961856 DOI: 10.3390/metabo13020299] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
We here characterize changes in metabolite patterns in glioblastoma patients undergoing surgery and concurrent chemoradiation using machine learning (ML) algorithms to characterize metabolic changes during different stages of the treatment protocol. We examined 105 plasma specimens (before surgery, 2 days after surgical resection, before starting concurrent chemoradiation, and immediately after chemoradiation) from 36 patients with isocitrate dehydrogenase (IDH) wildtype glioblastoma. Untargeted GC-TOF mass spectrometry-based metabolomics was used given its superiority in identifying and quantitating small metabolites; this yielded 157 structurally identified metabolites. Using Multinomial Logistic Regression (MLR) and GradientBoostingClassifier (GB Classifier), ML models classified specimens based on metabolic changes. The classification performance of these models was evaluated using performance metrics and area under the curve (AUC) scores. Comparing post-radiation to pre-radiation showed increased levels of 15 metabolites: glycine, serine, threonine, oxoproline, 6-deoxyglucose, gluconic acid, glycerol-alpha-phosphate, ethanolamine, propyleneglycol, triethanolamine, xylitol, succinic acid, arachidonic acid, linoleic acid, and fumaric acid. After chemoradiation, a significant decrease was detected in 3-aminopiperidine 2,6-dione. An MLR classification of the treatment phases was performed with 78% accuracy and 75% precision (AUC = 0.89). The alternative GB Classifier algorithm achieved 75% accuracy and 77% precision (AUC = 0.91). Finally, we investigated specific patterns for metabolite changes in highly correlated metabolites. We identified metabolites with characteristic changing patterns between pre-surgery and post-surgery and post-radiation samples. To the best of our knowledge, this is the first study to describe blood metabolic signatures using ML algorithms during different treatment phases in patients with glioblastoma. A larger study is needed to validate the results and the potential application of this algorithm for the characterization of treatment responses.
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Affiliation(s)
- Orwa Aboud
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
| | - Yin Allison Liu
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Department of Ophthalmology, University of California, Davis, Sacramento, CA 95817, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95817, USA
| | - Christopher Brydges
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95817, USA
| | - Ruben Fragoso
- Department of Radiation Oncology, University of California, Davis, Sacramento, CA 95817, USA
| | - Han Sung Lee
- Department of Pathology, University of California, Davis, Sacramento, CA 95817, USA
| | - Jonathan Riess
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
- Department of Internal Medicine, Division of Hematology and Oncology, University of California, Davis, Sacramento, CA 95817, USA
| | - Rawad Hodeify
- Department of Biotechnology, School of Arts and Sciences, American University of Ras Al Khaimah, Ras Al Khaimah 72603, United Arab Emirates
| | - Orin Bloch
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
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5
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Ahmed M, Semreen AM, El-Huneidi W, Bustanji Y, Abu-Gharbieh E, Alqudah MAY, Alhusban A, Shara M, Abuhelwa AY, Soares NC, Semreen MH, Alzoubi KH. Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research. Int J Mol Sci 2022; 24:ijms24010348. [PMID: 36613792 PMCID: PMC9820403 DOI: 10.3390/ijms24010348] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022] Open
Abstract
Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative "omics" approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.
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Affiliation(s)
- Munazza Ahmed
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Ahlam M. Semreen
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Waseem El-Huneidi
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Yasser Bustanji
- Department of Basic and Clinical Pharmacology, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Eman Abu-Gharbieh
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Mohammad A. Y. Alqudah
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan
| | - Ahmed Alhusban
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Mohd Shara
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Ahmad Y. Abuhelwa
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Nelson C. Soares
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Mohammad H. Semreen
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Correspondence: (M.H.S.); (K.H.A.)
| | - Karem H. Alzoubi
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Correspondence: (M.H.S.); (K.H.A.)
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6
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Rewired Metabolism of Amino Acids and Its Roles in Glioma Pathology. Metabolites 2022; 12:metabo12100918. [PMID: 36295820 PMCID: PMC9611130 DOI: 10.3390/metabo12100918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 09/24/2022] [Accepted: 09/26/2022] [Indexed: 11/21/2022] Open
Abstract
Amino acids (AAs) are indispensable building blocks of diverse bio-macromolecules as well as functional regulators for various metabolic processes. The fact that cancer cells live with a voracious appetite for specific AAs has been widely recognized. Glioma is one of the most lethal malignancies occurring in the central nervous system. The reprogrammed metabolism of AAs benefits glioma proliferation, signal transduction, epigenetic modification, and stress tolerance. Metabolic alteration of specific AAs also contributes to glioma immune escape and chemoresistance. For clinical consideration, fluctuations in the concentrations of AAs observed in specific body fluids provides opportunities to develop new diagnosis and prognosis markers. This review aimed at providing an extra dimension to understanding glioma pathology with respect to the rewired AA metabolism. A deep insight into the relevant fields will help to pave a new way for new therapeutic target identification and valuable biomarker development.
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7
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Glioblastoma and Methionine Addiction. Int J Mol Sci 2022; 23:ijms23137156. [PMID: 35806160 PMCID: PMC9266821 DOI: 10.3390/ijms23137156] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 06/21/2022] [Accepted: 06/24/2022] [Indexed: 02/01/2023] Open
Abstract
Glioblastoma is a fatal brain tumor with a bleak prognosis. The use of chemotherapy, primarily the alkylating agent temozolomide, coupled with radiation and surgical resection, has provided some benefit. Despite this multipronged approach, average patient survival rarely extends beyond 18 months. Challenges to glioblastoma treatment include the identification of functional pharmacologic targets as well as identifying drugs that can cross the blood-brain barrier. To address these challenges, current research efforts are examining metabolic differences between normal and tumor cells that could be targeted. Among the metabolic differences examined to date, the apparent addiction to exogenous methionine by glioblastoma tumors is a critical factor that is not well understood and may serve as an effective therapeutic target. Others have proposed this property could be exploited by methionine dietary restriction or other approaches to reduce methionine availability. However, methionine links the tumor microenvironment with cell metabolism, epigenetic regulation, and even mitosis. Therefore methionine depletion could result in complex and potentially undesirable responses, such as aneuploidy and the aberrant expression of genes that drive tumor progression. If methionine manipulation is to be a therapeutic strategy for glioblastoma patients, it is essential that we enhance our understanding of the role of methionine in the tumor microenvironment.
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8
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Pienkowski T, Kowalczyk T, Garcia-Romero N, Ayuso-Sacido A, Ciborowski M. Proteomics and metabolomics approach in adult and pediatric glioma diagnostics. Biochim Biophys Acta Rev Cancer 2022; 1877:188721. [PMID: 35304294 DOI: 10.1016/j.bbcan.2022.188721] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/10/2022] [Accepted: 03/11/2022] [Indexed: 12/26/2022]
Abstract
The diagnosis of glioma is mainly based on imaging methods that do not distinguish between stage and subtype prior to histopathological analysis. Patients with gliomas are generally diagnosed in the symptomatic stage of the disease. Additionally, healing scar tissue may be mistakenly identified based on magnetic resonance imaging (MRI) as a false positive tumor recurrence in postoperative patients. Current knowledge of molecular alterations underlying gliomagenesis and identification of tumoral biomarkers allow for their use as discriminators of the state of the organism. Moreover, a multiomics approach provides the greatest spectrum and the ability to track physiological changes and can serve as a minimally invasive method for diagnosing asymptomatic gliomas, preceding surgery and allowing for the initiation of prophylactic treatment. It is important to create a vast biomarker library for adults and pediatric patients due to their metabolic differences. This review focuses on the most promising proteomic, metabolomic and lipidomic glioma biomarkers, their pathways, the interactions, and correlations that can be considered characteristic of tumor grade or specific subtype.
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Affiliation(s)
- Tomasz Pienkowski
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland.
| | - Tomasz Kowalczyk
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland; Department of Medical Microbiology and Nanobiomedical Engineering, Medical University of Bialystok, Mickiewicza 2C, 15-222 Bialystok, Poland
| | - Noemi Garcia-Romero
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223 Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043 Madrid, Spain
| | - Angel Ayuso-Sacido
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223 Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043 Madrid, Spain; Faculty of Medicine, Universidad Francisco de Vitoria, 28223 Madrid, Spain
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
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9
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Abstract
Since the inception of their profession, neurosurgeons have defined themselves as physicians with a surgical practice. Throughout time, neurosurgery has always taken advantage of technological advances to provide better and safer care for patients. In the ongoing precision medicine surge that drives patient-centric healthcare, neurosurgery strives to effectively embrace the era of data-driven medicine. Neuro-oncology best illustrates this convergence between surgery and precision medicine with the advent of molecular profiling, imaging and data analytics. This convenient convergence paves the way for new preventive, diagnostic, prognostic and targeted therapeutic perspectives. The prominent advances in healthcare and big data forcefully challenge the medical community to deeply rethink current and future medical practice. This work provides a historical perspective on neurosurgery. It also discusses the impact of the conceptual shift of precision medicine on neurosurgery through the lens of neuro-oncology.
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10
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Firdous S, Abid R, Nawaz Z, Bukhari F, Anwer A, Cheng LL, Sadaf S. Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data. Metabolites 2021; 11:metabo11080507. [PMID: 34436448 PMCID: PMC8402070 DOI: 10.3390/metabo11080507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/22/2021] [Accepted: 07/28/2021] [Indexed: 01/04/2023] Open
Abstract
Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.
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Affiliation(s)
- Safia Firdous
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan; (S.F.); (R.A.)
- Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University, Lahore 54770, Pakistan
| | - Rizwan Abid
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan; (S.F.); (R.A.)
| | - Zubair Nawaz
- Department of Data Science, Punjab University College of Information Technology, University of the Punjab, Lahore 54590, Pakistan; (Z.N.); (F.B.)
| | - Faisal Bukhari
- Department of Data Science, Punjab University College of Information Technology, University of the Punjab, Lahore 54590, Pakistan; (Z.N.); (F.B.)
| | - Ammar Anwer
- Punjab Institute of Neurosciences (PINS), Lahore General Hospital, Lahore 54000, Pakistan;
| | - Leo L. Cheng
- Departments of Radiology and Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA;
| | - Saima Sadaf
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan; (S.F.); (R.A.)
- Correspondence:
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11
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Ali H, Harting R, de Vries R, Ali M, Wurdinger T, Best MG. Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review. Front Oncol 2021; 11:665235. [PMID: 34150629 PMCID: PMC8211985 DOI: 10.3389/fonc.2021.665235] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 05/18/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Gliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer. METHODS The Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported. RESULTS 7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types. CONCLUSION Panels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.
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Affiliation(s)
- Hamza Ali
- Department of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center and Academic Medical Center, Amsterdam, Netherlands
| | - Romée Harting
- Department of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center and Academic Medical Center, Amsterdam, Netherlands
| | - Ralph de Vries
- Medical Library, Vrije Universiteit, Amsterdam, Netherlands
| | - Meedie Ali
- Department of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center and Academic Medical Center, Amsterdam, Netherlands
| | - Thomas Wurdinger
- Department of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center and Academic Medical Center, Amsterdam, Netherlands
| | - Myron G. Best
- Department of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center and Academic Medical Center, Amsterdam, Netherlands
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Szeliga M, Albrecht J. Roles of nitric oxide and polyamines in brain tumor growth. Adv Med Sci 2021; 66:199-205. [PMID: 33711670 DOI: 10.1016/j.advms.2021.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/08/2021] [Accepted: 02/26/2021] [Indexed: 12/27/2022]
Abstract
Nitric oxide (NO) and polyamines: putrescine, spermidine and spermine, are key arginine metabolites in mammalian tissues that play critical roles i.a. in regulation of vascular tone (NO), and cell cycle regulation (polyamines). In the brain, both classes of molecules additionally have neuromodulatory and neuroprotective potential, and NO also a neurotoxic potential. Here we review evidence that brain tumors use the NO- and polyamine-synthesizing machineries to the benefit of their differentiation and growth from healthy glia and neurons. With a few exceptions, brain tumors show increased activities of one or all of the three arginine (Arg) to NO-converting nitric oxide synthase (NOS) isoforms (iNOS, eNOS, nNOS), but also elevated activities of polyamines-generating and modifying enzymes: arginase I/II, ornithine decarboxylase and spermidine/spermine N1-acetyltransferase. The degree of stimulation of NO- and polyamine synthesis often correlates with brain tumor malignancy. Excess NO, but also spermine, spermidine and their N1-acetylated forms, are tumor- and context-dependently involved in angiogenesis, tumor initiation and growth, and resistance to chemo- or radiotherapy. Hypothetically, increased demand for NO and/or polyamines is likely to contribute to Arg auxotrophy of malignant brain tumors, albeit the causal nexus awaits experimental verification.
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Abstract
This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.
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14
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Take Advantage of Glutamine Anaplerosis, the Kernel of the Metabolic Rewiring in Malignant Gliomas. Biomolecules 2020; 10:biom10101370. [PMID: 32993063 PMCID: PMC7599606 DOI: 10.3390/biom10101370] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 09/18/2020] [Accepted: 09/24/2020] [Indexed: 12/11/2022] Open
Abstract
Glutamine is a non-essential amino acid that plays a key role in the metabolism of proliferating cells including neoplastic cells. In the central nervous system (CNS), glutamine metabolism is particularly relevant, because the glutamine-glutamate cycle is a way of controlling the production of glutamate-derived neurotransmitters by tightly regulating the bioavailability of the amino acids in a neuron-astrocyte metabolic symbiosis-dependent manner. Glutamine-related metabolic adjustments have been reported in several CNS malignancies including malignant gliomas that are considered ‘glutamine addicted’. In these tumors, glutamine becomes an essential amino acid preferentially used in energy and biomass production including glutathione (GSH) generation, which is crucial in oxidative stress control. Therefore, in this review, we will highlight the metabolic remodeling that gliomas undergo, focusing on glutamine metabolism. We will address some therapeutic regimens including novel research attempts to target glutamine metabolism and a brief update of diagnosis strategies that take advantage of this altered profile. A better understanding of malignant glioma cell metabolism will help in the identification of new molecular targets and the design of new therapies.
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15
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Chen Z, Dai Y, Huang X, Chen K, Gao Y, Li N, Wang D, Chen A, Yang Q, Hong Y, Zeng S, Mao W. Combined Metabolomic Analysis of Plasma and Tissue Reveals a Prognostic Risk Score System and Metabolic Dysregulation in Esophageal Squamous Cell Carcinoma. Front Oncol 2020; 10:1545. [PMID: 32984013 PMCID: PMC7479226 DOI: 10.3389/fonc.2020.01545] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 07/20/2020] [Indexed: 12/14/2022] Open
Abstract
Background: Esophageal squamous cell carcinoma (ESCC) is a gastrointestinal malignancy with a poor prognosis. Although studies have shown metabolic reprogramming to be linked to ESCC development, no prognostic metabolic biomarkers or potential therapeutic metabolic targets have been identified. Method: The present study investigated some circulating metabolites associated with overall survival in 276 curatively resected ESCC patients using liquid chromatography/mass spectrometry metabolomics and Kaplan-Meier analysis. Tissue metabolomic analysis of 23-paired ESCC tissue samples was performed to discover metabolic dysregulation in ESCC cancerous tissue. A method consisting of support vector machine recursive feature elimination and LIMMA differential expression analysis was utilized to select promising feature genes within transcriptomic data from 179-paired ESCC tissue samples. Joint pathway analysis with genes and metabolites identified relevant metabolic pathways and targets for ESCC. Results: Four metabolites, kynurenine, 1-myristoyl-glycero-3-phosphocholine (LPC(14:0)sn-1), 2-piperidinone, and hippuric acid, were identified as prognostic factors in the preoperative plasma from ESCC patients. A risk score consisting of kynurenine and LPC(14:0)sn-1 significantly improved the prognostic performance of the tumor-node-metastasis staging system and was able to stratify risk for ESCC. Combined tissue metabolomic analysis and support vector machine recursive feature elimination gene selection revealed dysregulated kynurenine pathway as an important metabolic feature of ESCC, including accumulation of tryptophan, formylkynurenine, and kynurenine, as well as up-regulated indoleamine 2,3-dioxygenase 1 in ESCC cancerous tissue. Conclusions: This work identified for the first time four potential prognostic circulating metabolites. In addition, kynurenine pathway metabolism was shown to be up-regulated tryptophan-kynurenine metabolism in ESCC. Results not only provide a metabolite-based risk score system for prognosis, but also improve the understanding of the molecular basis of ESCC onset and progression, and as well as novel potential therapeutic targets for ESCC.
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Affiliation(s)
- Zhongjian Chen
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.,Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Yalan Dai
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Xiancong Huang
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Keke Chen
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China.,School of Medicine, Imperial College London, London, United Kingdom
| | - Yun Gao
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Na Li
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Ding Wang
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Aiping Chen
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
| | - Qingxia Yang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Yanjun Hong
- Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
| | - Su Zeng
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Weimin Mao
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, China.,Zhejiang Cancer Hospital, Hangzhou, China
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Kowalczyk T, Ciborowski M, Kisluk J, Kretowski A, Barbas C. Mass spectrometry based proteomics and metabolomics in personalized oncology. Biochim Biophys Acta Mol Basis Dis 2020; 1866:165690. [PMID: 31962175 DOI: 10.1016/j.bbadis.2020.165690] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 12/18/2019] [Accepted: 01/15/2020] [Indexed: 02/06/2023]
Abstract
Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.
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Affiliation(s)
- Tomasz Kowalczyk
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Michal Ciborowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Joanna Kisluk
- Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland
| | - Adam Kretowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland; Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Coral Barbas
- Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Madrid, Spain.
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Baranovičová E, Galanda T, Galanda M, Hatok J, Kolarovszki B, Richterová R, Račay P. Metabolomic profiling of blood plasma in patients with primary brain tumours: Basal plasma metabolites correlated with tumour grade and plasma biomarker analysis predicts feasibility of the successful statistical discrimination from healthy subjects - a preliminary study. IUBMB Life 2019; 71:1994-2002. [PMID: 31419008 DOI: 10.1002/iub.2149] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 07/27/2019] [Indexed: 12/12/2022]
Abstract
The brain tumours represent a complex tissue that has its own characteristic metabolic features and is interfaced with the whole organism. We investigated changes in basal blood plasma metabolites in the presence of primary brain tumour, their correlation with tumour grade, as well as the feasibility of statistical discrimination based on plasma metabolites. Together 60 plasma samples from patients with clinically defined glioblastoma, meningioma, oligodendrioglioma, astrocytoma, and non-specific glial tumour and plasma samples from 28 healthy volunteers without any cancer history were measured by NMR spectroscopy. In blood plasma of primary brain tumour patients, we found significantly increased levels of glycolytic metabolites glucose and pyruvate, and significantly decreased level of glutamine and also metabolites participating in tricarboxylic acid (TCA) cycle, citrate and succinate, when compared with controls. Further, plasma metabolites levels: tyrosine, phenylalanine, glucose, creatine and creatinine correlated significantly with tumour grade. In general, observed changes are parallel to the biochemistry expected for tumourous tissue and metabolic changes in plasma seem to follow the similar rules in all primary brain tumours, with very subtle variations among tumour types. Only two plasma metabolites tyrosine and phenylalanine were increased exclusively in blood plasma of patients with glioblastoma. Based on metabolite levels, an excellent discrimination between plasma from patient's tumours and controls was attainable. The metabolites creatine, pyruvate, glucose, formate, creatinine and citrate were of the highest discriminatory power.
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Affiliation(s)
- Eva Baranovičová
- Division of Neuroscience, Biomedical Center BioMed, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Tomáš Galanda
- Department of Neurosurgery, Slovak Medical University, Roosevelt Hospital, Banska Bystrica, Slovakia
| | - Miroslav Galanda
- Department of Neurosurgery, Slovak Medical University, Roosevelt Hospital, Banska Bystrica, Slovakia
| | - Jozef Hatok
- Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Branislav Kolarovszki
- Clinic of Neurosurgery, Jessenius Faculty of Medicine in Martin, Commenius University in Bratislava and University Hospital, Martin, Slovakia
| | - Romana Richterová
- Clinic of Neurosurgery, Jessenius Faculty of Medicine in Martin, Commenius University in Bratislava and University Hospital, Martin, Slovakia
| | - Peter Račay
- Division of Neuroscience, Biomedical Center BioMed, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia.,Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
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Liquid Biopsy in Glioblastoma: Opportunities, Applications and Challenges. Cancers (Basel) 2019; 11:cancers11070950. [PMID: 31284524 PMCID: PMC6679205 DOI: 10.3390/cancers11070950] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 07/02/2019] [Accepted: 07/04/2019] [Indexed: 12/11/2022] Open
Abstract
Liquid biopsy represents a minimally invasive procedure that can provide similar information from body fluids to what is usually obtained from a tissue biopsy sample. Its implementation in the clinical setting might significantly renew the field of medical oncology, facilitating the introduction of the concepts of precision medicine and patient-tailored therapies. These advances may be useful in the diagnosis of brain tumors that currently require surgery for tissue collection, or to perform genetic tumor profiling for disease classification and guidance of therapy. In this review, we will summarize the most recent advances and putative applications of liquid biopsy in glioblastoma, the most common and malignant adult brain tumor. Moreover, we will discuss the remaining challenges and hurdles in terms of technology and biology for its clinical application.
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Pharmacokinetic and Metabolism Studies of 12-Riboside-Pseudoginsengenin DQ by UPLC-MS/MS and UPLC-QTOF-MS E. Molecules 2018; 23:molecules23102499. [PMID: 30274288 PMCID: PMC6222672 DOI: 10.3390/molecules23102499] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 09/22/2018] [Accepted: 09/26/2018] [Indexed: 01/19/2023] Open
Abstract
Pharmacokinetic and metabolism studies of 12-riboside-pseudoginsengenin DQ (RPDQ), a novel ginsenoside with an anti-cancer effect, were carried out, aiming at discussing the characteristics of the ginsenoside with glycosylation site at C-12. In the pharmacokinetic analysis, we developed and validated a method by UPLC-MS to quantify RPDQ in rat plasma. In the range of 5–1000 ng/mL, the assay was linear (R2 > 0.9966), with the LLOQ (lower limit of quantification) being 5 ng/mL. The LOD (limit of detection) was 1.5 ng/mL. The deviations of intra-day and inter-day, expressed as relative standard deviation (RSD), were ≤ 3.51% and ≤ 5.41% respectively. The accuracy, expressed as relative error (RE), was in the range –8.82~3.47% and –5.61~2.87%, respectively. The recoveries were in the range 85.66~92.90%. The method was then applied to a pharmacokinetic study in rats intragastrically administrated with 6, 12, and 24 mg/kg RPDQ. The results showed that RPDQ exhibited slow oral absorption (Tmax = 7.0 h, 7.5 h, and 7.0 h, respectively), low elimination (t1/2 = 12.59 h, 12.83 h, and 13.74 h, respectively) and poor absolute bioavailability (5.55, 5.15, and 6.08%, respectively). Moreover, the investigation of metabolites were carried out by UPLC-QTOF-MS. Thirteen metabolites of RPDQ were characterized from plasma, bile, urine, and feces of rats. Some metabolic pathways, including oxidation, acetylation, hydration, reduction, hydroxylation, glycine conjugation, sulfation, phosphorylation, glucuronidation, glutathione conjugation, and deglycosylation, were profiled. In general, both the rapid quantitative method and a good understanding of the characteristics of RPDQ in vivo were provided in this study.
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