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de la Rica-Martinez A, Martínez-Muñoz G, Sanjuan MA, Conesa-Celdrán A, Garcia-Moreno L, Estan-Cerezo G, Oates MJ, Gonzalo-Jimenez N, Ruiz-Canales A. Low-Cost Electronic Nose for the Determination of Urinary Infections. SENSORS (BASEL, SWITZERLAND) 2023; 24:157. [PMID: 38203029 PMCID: PMC10781376 DOI: 10.3390/s24010157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/29/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024]
Abstract
Currently, urine samples for bacterial or fungal infections require a long diagnostic period (48 h). In the present work, a point-of-care device known as an electronic nose (eNose) has been designed based on the "smell print" of infections, since each one emits various volatile organic compounds (VOC) that can be registered by the electronic systems of the device and recognized in a very short time. Urine samples were analyzed in parallel using urine culture and eNose technology. A total of 203 urine samples were analyzed, of which 106 were infected and 97 were not infected. A principal component analysis (PCA) was performed using these data. The algorithm was initially capable of correctly classifying 49% of the total samples. By using SVM-based models, it is possible to improve the accuracy of the classification up to 74% when randomly using 85% of the data for training and 15% for validation. The model is evaluated as having a correct classification rate of 74%. In conclusion, the diagnostic accuracy of the eNose in urine samples is high, promising and amenable for further improvement, and the eNose has the potential to become a feasible, reproducible, low-cost and high-precision device to be applied in clinical practice for the diagnosis of urinary tract infections.
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Affiliation(s)
- Alba de la Rica-Martinez
- Servicio de Microbiología, Hospital General Universitario de Elche, 03202 Elche, Spain; (A.d.l.R.-M.); (M.A.S.); (L.G.-M.); (G.E.-C.); (N.G.-J.)
| | - Gemma Martínez-Muñoz
- Engineering Department, Miguel Hernández University of Elche, 03312 Orihuela, Spain (A.C.-C.); (M.J.O.)
| | - Marta Amoros Sanjuan
- Servicio de Microbiología, Hospital General Universitario de Elche, 03202 Elche, Spain; (A.d.l.R.-M.); (M.A.S.); (L.G.-M.); (G.E.-C.); (N.G.-J.)
| | - Agustín Conesa-Celdrán
- Engineering Department, Miguel Hernández University of Elche, 03312 Orihuela, Spain (A.C.-C.); (M.J.O.)
| | - Lucía Garcia-Moreno
- Servicio de Microbiología, Hospital General Universitario de Elche, 03202 Elche, Spain; (A.d.l.R.-M.); (M.A.S.); (L.G.-M.); (G.E.-C.); (N.G.-J.)
| | - Gabriel Estan-Cerezo
- Servicio de Microbiología, Hospital General Universitario de Elche, 03202 Elche, Spain; (A.d.l.R.-M.); (M.A.S.); (L.G.-M.); (G.E.-C.); (N.G.-J.)
| | - Martin J. Oates
- Engineering Department, Miguel Hernández University of Elche, 03312 Orihuela, Spain (A.C.-C.); (M.J.O.)
| | - Nieves Gonzalo-Jimenez
- Servicio de Microbiología, Hospital General Universitario de Elche, 03202 Elche, Spain; (A.d.l.R.-M.); (M.A.S.); (L.G.-M.); (G.E.-C.); (N.G.-J.)
| | - Antonio Ruiz-Canales
- Engineering Department, Miguel Hernández University of Elche, 03312 Orihuela, Spain (A.C.-C.); (M.J.O.)
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Vignoli A, Miolo G, Tenori L, Buonadonna A, Lombardi D, Steffan A, Scalone S, Luchinat C, Corona G. Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas. iScience 2023; 26:107678. [PMID: 37752948 PMCID: PMC10518687 DOI: 10.1016/j.isci.2023.107678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 06/23/2023] [Accepted: 08/14/2023] [Indexed: 09/28/2023] Open
Abstract
Soft tissue sarcomas (STSs) are rare malignant tumors that are difficult to prognosticate using currently available instruments. Omics sciences could provide more accurate and individualized survival predictions for patients with metastatic STS. In this pilot, hypothesis-generating study, we integrated clinicopathological variables with proton nuclear magnetic resonance (1H NMR) plasma metabolomic and lipoproteomic profiles, capturing both tumor and host characteristics, to identify novel prognostic biomarkers of 2-year survival. Forty-five metastatic STS (mSTS) patients with prevalent leiomyosarcoma and liposarcoma histotypes receiving trabectedin treatment were enrolled. A score combining acetate, triglycerides low-density lipoprotein (LDL)-2, and red blood cell count was developed, and it predicts 2-year survival with optimal results in the present cohort (84.4% sensitivity, 84.6% specificity). This score is statistically significant and independent of other prognostic factors such as age, sex, tumor grading, tumor histotype, frailty status, and therapy administered. A nomogram based on these 3 biomarkers has been developed to inform the clinical use of the present findings.
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Gianmaria Miolo
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy
| | - Angela Buonadonna
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
| | - Davide Lombardi
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
| | - Simona Scalone
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy
- GiottoBiotech s.r.l, Sesto Fiorentino, Italy
| | - Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy
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3
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Almalki AH. Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer. Metabolites 2023; 13:1037. [PMID: 37887362 PMCID: PMC10609104 DOI: 10.3390/metabo13101037] [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: 08/24/2023] [Revised: 09/10/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.
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Affiliation(s)
- Atiah H. Almalki
- Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
- Addiction and Neuroscience Research Unit, Health Science Campus, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
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4
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Alonso-Moreno P, Rodriguez I, Izquierdo-Garcia JL. Benchtop NMR-Based Metabolomics: First Steps for Biomedical Application. Metabolites 2023; 13:metabo13050614. [PMID: 37233655 DOI: 10.3390/metabo13050614] [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: 12/30/2022] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
Nuclear magnetic resonance (NMR)-based metabolomics is a valuable tool for identifying biomarkers and understanding the underlying metabolic changes associated with various diseases. However, the translation of metabolomics analysis to clinical practice has been limited by the high cost and large size of traditional high-resolution NMR spectrometers. Benchtop NMR, a compact and low-cost alternative, offers the potential to overcome these limitations and facilitate the wider use of NMR-based metabolomics in clinical settings. This review summarizes the current state of benchtop NMR for clinical applications where benchtop NMR has demonstrated the ability to reproducibly detect changes in metabolite levels associated with diseases such as type 2 diabetes and tuberculosis. Benchtop NMR has been used to identify metabolic biomarkers in a range of biofluids, including urine, blood plasma and saliva. However, further research is needed to optimize the use of benchtop NMR for clinical applications and to identify additional biomarkers that can be used to monitor and manage a range of diseases. Overall, benchtop NMR has the potential to revolutionize the way metabolomics is used in clinical practice, providing a more accessible and cost-effective way to study metabolism and identify biomarkers for disease diagnosis, prognosis, and treatment.
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Affiliation(s)
- Pilar Alonso-Moreno
- NMR and Imaging in Biomedicine Group, Instituto Pluridisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Ignacio Rodriguez
- NMR and Imaging in Biomedicine Group, Instituto Pluridisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spain
- Department of Chemistry in Pharmaceutical Sciences, Pharmacy School, Universidad Complutense de Madrid, 28040 Madrid, Spain
- CIBER de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose Luis Izquierdo-Garcia
- NMR and Imaging in Biomedicine Group, Instituto Pluridisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spain
- Department of Chemistry in Pharmaceutical Sciences, Pharmacy School, Universidad Complutense de Madrid, 28040 Madrid, Spain
- CIBER de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, 28029 Madrid, Spain
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5
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Castiglione Morelli MA, Iuliano A, Matera I, Viggiani L, Schettini SCA, Colucci P, Ostuni A. A Pilot Study on Biochemical Profile of Follicular Fluid in Breast Cancer Patients. Metabolites 2023; 13:metabo13030441. [PMID: 36984881 PMCID: PMC10054828 DOI: 10.3390/metabo13030441] [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: 02/15/2023] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 03/30/2023] Open
Abstract
Breast cancer (BC) is the most common type of cancer among women in almost all countries worldwide and is one of the oncological pathologies for which is indicated fertility preservation, a type of procedure used to help keep a person's ability to have children. Follicular fluid (FF) is a major component of oocyte microenvironment, which is involved in oocyte growth, follicular maturation, and in communication between germ and somatic cells; furthermore, it accumulates all metabolites during oocytes growth. To obtain information about changes on fertility due to cancer, we aimed at investigating potential biomarkers to discriminate between FF samples obtained from 16 BC patients and 10 healthy women undergoing in vitro fertilization treatments. An NMR-based metabolomics approach was performed to investigate the FF metabolic profiles; ELISA and western blotting assays were used to investigate protein markers of oxidative and inflammatory stress, which are processes closely related to cancer. Our results seem to suggest that FFs of BC women display some significant metabolic alterations in comparison to healthy controls, and these variations are also related with tumor staging.
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Affiliation(s)
| | - Assunta Iuliano
- Center for Reproductive Medicine of "San Carlo" Hospital, 85100 Potenza, Italy
| | - Ilenia Matera
- Department of Sciences, University of Basilicata, 85100 Potenza, Italy
| | - Licia Viggiani
- Department of Sciences, University of Basilicata, 85100 Potenza, Italy
| | | | - Paola Colucci
- Center for Reproductive Medicine of "San Carlo" Hospital, 85100 Potenza, Italy
| | - Angela Ostuni
- Department of Sciences, University of Basilicata, 85100 Potenza, Italy
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Di Cesare F, Vignoli A, Luchinat C, Tenori L, Saccenti E. Exploration of Blood Metabolite Signatures of Colorectal Cancer and Polyposis through Integrated Statistical and Network Analysis. Metabolites 2023; 13:metabo13020296. [PMID: 36837915 PMCID: PMC9965766 DOI: 10.3390/metabo13020296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/07/2023] [Accepted: 02/12/2023] [Indexed: 02/19/2023] Open
Abstract
Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic purposes. Integrative systems biology approaches offer an optimal point of view to analyze CRC and patients with polyposis. The present study analyzed the association networks constructed from a publicly available array of 113 serum metabolites measured on a cohort of 234 subjects from three groups (66 CRC patients, 76 patients with polyposis, and 92 healthy controls), which concentrations were obtained via targeted liquid chromatography-tandem mass spectrometry. In terms of architecture, topology, and connectivity, the metabolite-metabolite association network of CRC patients appears to be completely different with respect to patients with polyposis and healthy controls. The most relevant nodes in the CRC network are those related to energy metabolism. Interestingly, phenylalanine, tyrosine, and tryptophan metabolism are found to be involved in both CRC and polyposis. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate molecular aspects of CRC.
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Affiliation(s)
- Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
- Correspondence: (L.T.); (E.S.)
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE Wageningen, The Netherlands
- Correspondence: (L.T.); (E.S.)
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The Relationship between Histological Composition and Metabolic Profile in Breast Tumors and Peritumoral Tissue Determined with 1H HR-MAS NMR Spectroscopy. Cancers (Basel) 2023; 15:cancers15041283. [PMID: 36831625 PMCID: PMC9954108 DOI: 10.3390/cancers15041283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
Breast tumors constitute the complex entities composed of cancer cells and stromal components. The compositional heterogeneity should be taken into account in bulk tissue metabolomics studies. The aim of this work was to find the relation between the histological content and 1H HR-MAS (high-resolution magic angle spinning nuclear magnetic resonance) metabolic profiles of the tissue samples excised from the breast tumors and the peritumoral areas in 39 patients diagnosed with invasive breast carcinoma. The total number of the histologically verified specimens was 140. The classification accuracy of the OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) model differentiating the cancerous from non-involved samples was 87% (sensitivity of 72.2%, specificity of 92.3%). The metabolic contents of the epithelial and stromal compartments were determined from a linear regression analysis of the levels of the evaluated compounds against the cancer cell fraction in 39 samples composed mainly of cancer cells and intratumoral fibrosis. The correlation coefficients between the levels of several metabolites and a tumor purity were found to be dependent on the tumor grade (I vs II/III). The comparison of the levels of the metabolites in the intratumoral fibrosis (obtained from the extrapolation of the regression lines to 0% cancer content) to those levels in the fibrous connective tissue beyond the tumors revealed a profound metabolic reprogramming in the former tissue. The joint analysis of the metabolic profiles of the stromal and epithelial compartments in the breast tumors contributes to the increased understanding of breast cancer biology.
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Costantini S, Di Gennaro E, Capone F, De Stefano A, Nasti G, Vitagliano C, Setola SV, Tatangelo F, Delrio P, Izzo F, Avallone A, Budillon A. Plasma metabolomics, lipidomics and cytokinomics profiling predict disease recurrence in metastatic colorectal cancer patients undergoing liver resection. Front Oncol 2023; 12:1110104. [PMID: 36713567 PMCID: PMC9875807 DOI: 10.3389/fonc.2022.1110104] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 12/22/2022] [Indexed: 01/13/2023] Open
Abstract
Purpose In metastatic colorectal cancer (mCRC) patients (pts), treatment strategies integrating liver resection with induction chemotherapy offer better 5-year survival rates than chemotherapy alone. However, liver resection is a complex and costly procedure, and recurrence occurs in almost 2/3rds of pts, suggesting the need to identify those at higher risk. The aim of this work was to evaluate whether the integration of plasma metabolomics and lipidomics combined with the multiplex analysis of a large panel of plasma cytokines can be used to predict the risk of relapse and other patient outcomes after liver surgery, beyond or in combination with clinical morphovolumetric criteria. Experimental design Peripheral blood metabolomics and lipidomics were performed by 600 MHz NMR spectroscopy on plasma from 30 unresectable mCRC pts treated with bevacizumab plus oxaliplatin-based regimens within the Obelics trial (NCT01718873) and subdivided into responder (R) and non-R (NR) according to 1-year disease-free survival (DFS): ≥ 1-year (R, n = 12) and < 1-year (NR, n = 18). A large panel of cytokines, chemokines, and growth factors was evaluated on the same plasma using Luminex xMAP-based multiplex bead-based immunoassay technology. A multiple biomarkers model was built using a support vector machine (SVM) classifier. Results Sparse partial least squares discriminant analysis (sPLS-DA) and loading plots obtained by analyzing metabolomics profiles of samples collected at the time of response evaluation when resectability was established showed significantly different levels of metabolites between the two groups. Two metabolites, 3-hydroxybutyrate and histidine, significantly predicted DFS and overall survival. Lipidomics analysis confirmed clear differences between the R and NR pts, indicating a statistically significant increase in lipids (cholesterol, triglycerides and phospholipids) in NR pts, reflecting a nonspecific inflammatory response. Indeed, a significant increase in proinflammatory cytokines was demonstrated in NR pts plasma. Finally, a multiple biomarkers model based on the combination of presurgery plasma levels of 3-hydroxybutyrate, cholesterol, phospholipids, triglycerides and IL-6 was able to correctly classify patients by their DFS with good accuracy. Conclusion Overall, this exploratory study suggests the potential of these combined biomarker approaches to predict outcomes in mCRC patients who are candidates for liver metastasis resection after induction treatment for defining personalized management and treatment strategies.
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Affiliation(s)
- Susan Costantini
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Elena Di Gennaro
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Francesca Capone
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Alfonso De Stefano
- Experimental Clinical Abdominal Oncology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Guglielmo Nasti
- Innovative Therapy for Abdominal Metastases Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Carlo Vitagliano
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Sergio Venanzio Setola
- Radiology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Fabiana Tatangelo
- Pathology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Paolo Delrio
- Colorectal Oncological Surgery Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Francesco Izzo
- Hepatobiliary Surgery Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Antonio Avallone
- Experimental Clinical Abdominal Oncology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy
| | - Alfredo Budillon
- Experimental Pharmacology Unit, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Napoli, Italy,*Correspondence: Alfredo Budillon,
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Vignoli A, Meoni G, Ghini V, Di Cesare F, Tenori L, Luchinat C, Turano P. NMR-Based Metabolomics to Evaluate Individual Response to Treatments. Handb Exp Pharmacol 2023; 277:209-245. [PMID: 36318327 DOI: 10.1007/164_2022_618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy. .,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy. .,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy.
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10
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Risi E, Lisanti C, Vignoli A, Biagioni C, Paderi A, Cappadona S, Monte FD, Moretti E, Sanna G, Livraghi L, Malorni L, Benelli M, Puglisi F, Luchinat C, Tenori L, Biganzoli L. Risk assessment of disease recurrence in early breast cancer: A serum metabolomic study focused on elderly patients. Transl Oncol 2022; 27:101585. [PMID: 36403505 PMCID: PMC9676351 DOI: 10.1016/j.tranon.2022.101585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 10/28/2022] [Accepted: 11/08/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND We previously showed that metabolomics predicts relapse in early breast cancer (eBC) patients, unselected by age. This study aims to identify a "metabolic signature" that differentiates eBC from advanced breast cancer (aBC) patients, and to investigate its potential prognostic role in an elderly population. METHODS Serum samples from elderly breast cancer (BC) patients enrolled in 3 onco-geriatric trials, were retrospectively analyzed via proton nuclear magnetic resonance (1H NMR) spectroscopy. Three nuclear magnetic resonance (NMR) spectra were acquired for each serum sample: NOESY1D, CPMG, Diffusion-edited. Random Forest (RF) models to predict BC relapse were built on NMR spectra, and resulting RF risk scores were evaluated by Kaplan-Meier curves. RESULTS Serum samples from 140 eBC patients and 27 aBC were retrieved. In the eBC cohort, median age was 76 years; 77% of patients had luminal, 10% HER2-positive and 13% triple negative (TN) BC. Forty-two percent of patients had tumors >2 cm, 43% had positive axillary nodes. Using NOESY1D spectra, the RF classifier discriminated free-from-recurrence eBC from aBC with sensitivity, specificity and accuracy of 81%, 67% and 70% respectively. We tested the NOESY1D spectra of each eBC patient on the RF models already calculated. We found that patients classified as "high risk" had higher risk of disease recurrence (hazard ratio (HR) 3.42, 95% confidence interval (CI) 1.58-7.37) than patients at low-risk. CONCLUSIONS This analysis suggests that a "metabolic signature", identified employing NMR fingerprinting, is able to predict the risk of disease recurrence in elderly patients with eBC independently from standard clinicopathological features.
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Affiliation(s)
- Emanuela Risi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Camilla Lisanti
- Cro Aviano - National Cancer Institute - IRCCS, Medical Oncology and Cancer Prevention, Aviano, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | | | - Agnese Paderi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Silvia Cappadona
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Francesca Del Monte
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Erica Moretti
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Giuseppina Sanna
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Luca Livraghi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Luca Malorni
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | | | - Fabio Puglisi
- Cro Aviano - National Cancer Institute - IRCCS, Medical Oncology and Cancer Prevention, Aviano, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Laura Biganzoli
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy,Corresponding author.
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11
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Giró Benet J, Seo M, Khine M, Gumà Padró J, Pardo Martnez A, Kurdahi F. Breast cancer detection by analyzing the volatile organic compound (VOC) signature in human urine. Sci Rep 2022; 12:14873. [PMID: 36050339 PMCID: PMC9435419 DOI: 10.1038/s41598-022-17795-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 07/31/2022] [Indexed: 11/12/2022] Open
Abstract
A rising number of authors are drawing evidence on the diagnostic capacity of specific volatile organic compounds (VOCs) resulting from some body fluids. While cancer incidence in society is on the rise, it becomes clear that the analysis of these VOCs can yield new strategies to mitigate advanced cancer incidence rates. This paper presents the methodology implemented to test whether a device consisting of an electronic nose inspired by a dog’s olfactory system and olfactory neurons is significantly informative to detect breast cancer (BC). To test this device, 90 human urine samples were collected from control subjects and BC patients at a hospital. To test this system, an artificial intelligence-based classification algorithm was developed. The algorithm was firstly trained and tested with data resulting from gas chromatography-mass spectrometry (GC–MS) urine readings, leading to a classification rate of 92.31%, sensitivity of 100.00%, and specificity of 85.71% (N = 90). Secondly, the same algorithm was trained and tested with data obtained with our eNose prototype hardware, and class prediction was achieved with a classification rate of 75%, sensitivity of 100%, and specificity of 50%.
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Affiliation(s)
- Judit Giró Benet
- Center for Embedded Cyber-Physical Systems (CEPS), University of California Irvine (UCI), Irvine, 92697, USA.
| | - Minjun Seo
- Center for Embedded Cyber-Physical Systems (CEPS), University of California Irvine (UCI), Irvine, 92697, USA
| | - Michelle Khine
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, 92697, USA
| | - Josep Gumà Padró
- South Catalonia Oncology Institute (IOCS), Sant Joan de Reus University Hospital, IISPV, Rovira i Virgili University, 43204, Reus, Spain
| | - Antonio Pardo Martnez
- Department of Electronic and Biomedical Engineering, Universitat de Barcelona (UB), 08028, Barcelona, Spain
| | - Fadi Kurdahi
- Center for Embedded Cyber-Physical Systems (CEPS), University of California Irvine (UCI), Irvine, 92697, USA
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12
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Zhuang J, Yang X, Zheng Q, Li K, Cai L, Yu H, Lv J, Bai K, Cao Q, Li P, Yang H, Wang J, Lu Q. Metabolic Profiling of Bladder Cancer Patients' Serum Reveals Their Sensitivity to Neoadjuvant Chemotherapy. Metabolites 2022; 12:metabo12060558. [PMID: 35736490 PMCID: PMC9229374 DOI: 10.3390/metabo12060558] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 02/07/2023] Open
Abstract
Numerous patients with muscle-invasive bladder cancer develop low responsiveness to cisplatin. Our purpose was to explore differential metabolites derived from serum in bladder cancer patients treated with neoadjuvant chemotherapy (NAC). Data of patients diagnosed with cT2-4aNxM0 was collected. Blood samples were retained prospectively before the first chemotherapy for untargeted metabolomics by 1H-NMR and UPLC-MS. To identify characterized metabolites, multivariate statistical analyses were applied, and the intersection of the differential metabolites discovered by the two approaches was used to identify viable biomarkers. A total of 18 patients (6 NAC-sensitive patients and 12 NAC-resistant patients) were enrolled. There were 29 metabolites detected by 1H-NMR and 147 metabolites identified by UPLC-MS. Multivariate statistics demonstrated that in the sensitive group, glutamine and taurine were considerably increased compared to their levels in the resistant group, while glutamate and hypoxanthine were remarkably decreased. Pathway analysis and enrichment analysis showed significant alterations in amino acid pathways, suggesting that response to chemotherapy may be related to amino acid metabolism. In addition, hallmark analysis showed that DNA repair played a regulatory role. Overall, serum metabolic profiles of NAC sensitivity are significantly different in bladder cancer patients. Glycine, hypoxanthine, taurine and glutamine may be the potential biomarkers for clinical treatment. Amino acid metabolism has potential value in enhancing drug efficacy.
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Affiliation(s)
- Juntao Zhuang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Xiao Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Qi Zheng
- Center of Molecular Metabolism, Nanjing University of Science and Technology, Nanjing 210094, China;
| | - Kai Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Lingkai Cai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Hao Yu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Jiancheng Lv
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Kexin Bai
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Qiang Cao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Pengchao Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Haiwei Yang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
| | - Junsong Wang
- Center of Molecular Metabolism, Nanjing University of Science and Technology, Nanjing 210094, China;
- Correspondence: (J.W.); (Q.L.)
| | - Qiang Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; (J.Z.); (X.Y.); (K.L.); (L.C.); (H.Y.); (J.L.); (K.B.); (Q.C.); (P.L.); (H.Y.)
- Correspondence: (J.W.); (Q.L.)
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13
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Migdadi L, Telfah A, Hergenröder R, Wöhler C. Novelty Detection for Metabolic Dynamics Established On Breast Cancer Tissue Using 2D NMR TOCSY Spectra. Comput Struct Biotechnol J 2022; 20:2965-2977. [PMID: 35782733 PMCID: PMC9213235 DOI: 10.1016/j.csbj.2022.05.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/26/2022] [Accepted: 05/26/2022] [Indexed: 11/30/2022] Open
Abstract
Automatic novelty detection of metabolites of 2D-TOCSY NMR spectra. Metabolic profiling of the dynamics changes in Breast cancer tissue sample. Accurate and fast automatic multicomponent peak assignment of 2D NMR spectrum. One- and multi- novelty detection of metabolites.
Most metabolic profiling approaches focus only on identifying pre-known metabolites on NMR TOCSY spectrum using configured parameters. However, there is a lack of tasks dealing with automating the detection of new metabolites that might appear during the dynamic evolution of biological cells. Novelty detection is a category of machine learning that is used to identify data that emerge during the test phase and were not considered during the training phase. We propose a novelty detection system for detecting novel metabolites in the 2D NMR TOCSY spectrum of a breast cancer-tissue sample. We build one- and multi-class recognition systems using different classifiers such as, Kernel Null Foley-Sammon Transform, Kernel Density Estimation, and Support Vector Data Description. The training models were constructed based on different sizes of training data and are used in the novelty detection procedure. Multiple evaluation measures were applied to test the performance of the novelty detection methods. Depending on the training data size, all classifiers were able to achieve 0% false positive rates and total misclassification error in addition to 100% true positive rates. The median total time for the novelty detection process varies between 1.5 and 20 seconds, depending on the classifier and the amount of training data. The results of our novel metabolic profiling method demonstrate its suitability, robustness and speed in automated metabolic research.
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Affiliation(s)
- Lubaba Migdadi
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V, 44139 Dortmund, Germany
- Image Analysis Group, TU Dortmund, 44227 Dortmund, Germany
- Corresponding author.
| | - Ahmad Telfah
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V, 44139 Dortmund, Germany
| | - Roland Hergenröder
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V, 44139 Dortmund, Germany
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14
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Moco S. Studying Metabolism by NMR-Based Metabolomics. Front Mol Biosci 2022; 9:882487. [PMID: 35573745 PMCID: PMC9094115 DOI: 10.3389/fmolb.2022.882487] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 03/24/2022] [Indexed: 12/12/2022] Open
Abstract
During the past few decades, the direct analysis of metabolic intermediates in biological samples has greatly improved the understanding of metabolic processes. The most used technologies for these advances have been mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. NMR is traditionally used to elucidate molecular structures and has now been extended to the analysis of complex mixtures, as biological samples: NMR-based metabolomics. There are however other areas of small molecule biochemistry for which NMR is equally powerful. These include the quantification of metabolites (qNMR); the use of stable isotope tracers to determine the metabolic fate of drugs or nutrients, unravelling of new metabolic pathways, and flux through pathways; and metabolite-protein interactions for understanding metabolic regulation and pharmacological effects. Computational tools and resources for automating analysis of spectra and extracting meaningful biochemical information has developed in tandem and contributes to a more detailed understanding of systems biochemistry. In this review, we highlight the contribution of NMR in small molecule biochemistry, specifically in metabolic studies by reviewing the state-of-the-art methodologies of NMR spectroscopy and future directions.
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15
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Chamaraux-Tran TN, Muller M, Pottecher J, Diemunsch PA, Tomasetto C, Namer IJ, Dali-Youcef N. Metabolomic Impact of Lidocaine on a Triple Negative Breast Cancer Cell Line. Front Pharmacol 2022; 13:821779. [PMID: 35273500 PMCID: PMC8902240 DOI: 10.3389/fphar.2022.821779] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 01/24/2022] [Indexed: 12/12/2022] Open
Abstract
Background: Metabolomics and onco-anesthesia are two emerging research fields in oncology. Metabolomics (metabolites analysis) is a new diagnostic and prognostic tool that can also be used for predicting the therapeutic or toxic responses to anticancer treatments. Onco-anesthesia studies assess the impact of anesthesia on disease-free and overall survival after cancer surgery. It has been shown that local anesthetics (LA), particularly lidocaine (LIDO), exert antitumor properties both in vitro and in vivo and may alter the biologic fingerprints of cancer cells. As LA are known to impair mitochondrial bioenergetics and byproducts, the aim of the present study was to assess the impact of LIDO on metabolomic profile of a breast cancer cell line. Methods: Breast cancer MDA-MB-231 cells were exposed for 4 h to 0.5 mM LIDO or vehicle (n = 4). The metabolomic fingerprint was characterized by high resolution magic angle spinning NMR spectroscopy (HRMAS). The multivariate technique using the Algorithm to Determine Expected Metabolite Level Alteration (ADEMA) (Cicek et al., PLoS Comput. Biol., 2013, 9, e1002859), based on mutual information to identify expected metabolite level changes with respect to a specific condition, was used to determine the metabolites variations caused by LIDO. Results: LIDO modulates cell metabolites levels. Several pathways, including glutaminolysis, choline, phosphocholine and total choline syntheses were significantly downregulated in the LIDO group. Discussion: This is the first study assessing the impact of LIDO on metabolomic fingerprint of breast cancer cells. Among pathways downregulated by LIDO, many metabolites are reported to be associated with adverse prognosis when present at a high titer in breast cancer patients. These results fit with the antitumor properties of LIDO and suggest its impact on metabolomics profile of cancer cells. These effects of LIDO are of clinical significance because it is widely used for local anesthesia with cutaneous infiltration during percutaneous tumor biopsy. Future in vitro and preclinical studies are necessary to assess whether metabolomics analysis requires modification of local anesthetic techniques during tumor biopsy.
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Affiliation(s)
- Thiên-Nga Chamaraux-Tran
- Service d'anesthésie-réanimation et Médecine Périopératoire, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.,Institut de Génétique et de Biologie Moléculaire et Cellulaire Illkirch, Illkirch, France.,Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France.,Institut National de la Santé et de la Recherche Médicale, U1258, Illkirch, France.,ER 3072, Mitochondrie Stress Oxydant et Protection Musculaire, Faculté de Médecine, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, France
| | - Marie Muller
- Service d'anesthésie-réanimation et Médecine Périopératoire, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.,Université de Strasbourg, Faculté de Médecine, Strasbourg, France
| | - Julien Pottecher
- Service d'anesthésie-réanimation et Médecine Périopératoire, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.,ER 3072, Mitochondrie Stress Oxydant et Protection Musculaire, Faculté de Médecine, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, France.,Université de Strasbourg, Faculté de Médecine, Strasbourg, France
| | - Pierre A Diemunsch
- Service d'anesthésie-réanimation et Médecine Périopératoire, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Catherine Tomasetto
- Institut de Génétique et de Biologie Moléculaire et Cellulaire Illkirch, Illkirch, France.,Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France.,Institut National de la Santé et de la Recherche Médicale, U1258, Illkirch, France
| | - Izzie-Jacques Namer
- Université de Strasbourg, Faculté de Médecine, Strasbourg, France.,MNMS-Platform, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.,Service de Médecine Nucléaire et d'Imagerie Moléculaire, Institut de Cancérologie Strasbourg Europe, Strasbourg, France.,ICube, Université de Strasbourg/CNRS, UMR 7357, Strasbourg, France
| | - Nassim Dali-Youcef
- Institut de Génétique et de Biologie Moléculaire et Cellulaire Illkirch, Illkirch, France.,Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France.,Institut National de la Santé et de la Recherche Médicale, U1258, Illkirch, France.,Université de Strasbourg, Faculté de Médecine, Strasbourg, France.,Laboratoire de Biochimie et Biologie Moléculaire, Pôle de Biologie, Hôpitaux Universitaires de Strasbourg, Nouvel Hôpital Civil, 1 Place de l'hôpital, Strasbourg, France
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16
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Zinga MM, Abdel-Shafy E, Melak T, Vignoli A, Piazza S, Zerbini LF, Tenori L, Cacciatore S. KODAMA exploratory analysis in metabolic phenotyping. Front Mol Biosci 2022; 9:1070394. [PMID: 36733493 PMCID: PMC9887019 DOI: 10.3389/fmolb.2022.1070394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/28/2022] [Indexed: 01/18/2023] Open
Abstract
KODAMA is a valuable tool in metabolomics research to perform exploratory analysis. The advanced analytical technologies commonly used for metabolic phenotyping, mass spectrometry, and nuclear magnetic resonance spectroscopy push out a bunch of high-dimensional data. These complex datasets necessitate tailored statistical analysis able to highlight potentially interesting patterns from a noisy background. Hence, the visualization of metabolomics data for exploratory analysis revolves around dimensionality reduction. KODAMA excels at revealing local structures in high-dimensional data, such as metabolomics data. KODAMA has a high capacity to detect different underlying relationships in experimental datasets and correlate extracted features with accompanying metadata. Here, we describe the main application of KODAMA exploratory analysis in metabolomics research.
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Affiliation(s)
- Maria Mgella Zinga
- Bioinformatics Unit, International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa
- Department of Medical Parasitology and Entomology, Catholic University of Health and Allied Sciences, Mwanza, Tanzania
| | - Ebtesam Abdel-Shafy
- Bioinformatics Unit, International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa
- National Research Centre, Cairo, Egypt
| | - Tadele Melak
- Computation Biology, International Centre for Genetic Engineering and Biotechnology, Trieste, Italy
- Department of clinical chemistry, University of Gondar, Gondar, Ethiopia
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Silvano Piazza
- Computation Biology, International Centre for Genetic Engineering and Biotechnology, Trieste, Italy
| | - Luiz Fernando Zerbini
- Cancer Genomics, International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Stefano Cacciatore
- Bioinformatics Unit, International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa
- Institute of Reproductive and Developmental Biology, Imperial College London, London, United Kingdom
- *Correspondence: Stefano Cacciatore,
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17
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Ha JH, Jayaraman M, Nadhan R, Kashyap S, Mukherjee P, Isidoro C, Song YS, Dhanasekaran DN. Unraveling Autocrine Signaling Pathways through Metabolic Fingerprinting in Serous Ovarian Cancer Cells. Biomedicines 2021; 9:1927. [PMID: 34944743 PMCID: PMC8698993 DOI: 10.3390/biomedicines9121927] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/06/2021] [Accepted: 12/14/2021] [Indexed: 12/26/2022] Open
Abstract
Focusing on defining metabolite-based inter-tumoral heterogeneity in ovarian cancer, we investigated the metabolic diversity of a panel of high-grade serous ovarian carcinoma (HGSOC) cell-lines using a metabolomics platform that interrogate 731 compounds. Metabolic fingerprinting followed by 2-dimensional and 3-dimensional principal component analysis established the heterogeneity of the HGSOC cells by clustering them into five distinct metabolic groups compared to the fallopian tube epithelial cell line control. An overall increase in the metabolites associated with aerobic glycolysis and phospholipid metabolism were observed in the majority of the cancer cells. A preponderant increase in the levels of metabolites involved in trans-sulphuration and glutathione synthesis was also observed. More significantly, subsets of HGSOC cells showed an increase in the levels of 5-Hydroxytryptamine, γ-aminobutyrate, or glutamate. Additionally, 5-hydroxytryptamin synthesis inhibitor as well as antagonists of γ-aminobutyrate and glutamate receptors prohibited the proliferation of HGSOC cells, pointing to their potential roles as oncometabolites and ligands for receptor-mediated autocrine signaling in cancer cells. Consistent with this role, 5-Hydroxytryptamine synthesis inhibitor as well as receptor antagonists of γ-aminobutyrate and Glutamate-receptors inhibited the proliferation of HGSOC cells. These antagonists also inhibited the three-dimensional spheroid growth of TYKNU cells, a representative HGSOC cell-line. These results identify 5-HT, GABA, and Glutamate as putative oncometabolites in ovarian cancer metabolic sub-type and point to them as therapeutic targets in a metabolomic fingerprinting-based therapeutic strategy.
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Affiliation(s)
- Ji Hee Ha
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
- Department of Cell Biology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Muralidharan Jayaraman
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
- Department of Cell Biology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Revathy Nadhan
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
| | - Srishti Kashyap
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
| | - Priyabrata Mukherjee
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
- Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Ciro Isidoro
- Laboratory of Molecular Pathology and NanoBioImaging, Department of Health Sciences, Università del Piemonte Orientale, 28100 Novara, Italy;
| | - Yong Sang Song
- Department of Obstetrics and Gynecology, Cancer Research Institute, College of Medicine, Seoul National University, Seoul 151-921, Korea;
| | - Danny N. Dhanasekaran
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.H.H.); (M.J.); (R.N.); (S.K.); (P.M.)
- Department of Cell Biology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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18
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Exploring Serum NMR-Based Metabolomic Fingerprint of Colorectal Cancer Patients: Effects of Surgery and Possible Associations with Cancer Relapse. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app112311120] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background: Colorectal cancer (CRC) is the fourth most commonly diagnosed and third most deadly cancer worldwide. Surgery is the main treatment option for early disease; however, a relevant proportion of CRC patients relapse. Here, variations among preoperative and postoperative serum metabolomic fingerprint of CRC patients were studied, and possible associations between metabolic variations and cancer relapse were explored. Methods: A total of 41 patients with stage I-III CRC, planned for radical resection, were enrolled. Serum samples, collected preoperatively (t0) and 4–6 weeks after surgery before the start of any treatment (t1), were analyzed via NMR spectroscopy. NMR data were analyzed using multivariate and univariate statistical approaches. Results: Serum metabolomic fingerprints show differential clustering between t0 and t1 (82–85% accuracy). Pyruvate, HDL-related parameters, acetone, and 3-hydroxybutyrate appear to be the major players in this discrimination. Eight out of the 41 CRC patients enrolled developed cancer relapse. Postoperative, relapsed patients show an increase of pyruvate and HDL-related parameters, and a decrease of Apo-A1 Apo-B100 ratio and VLDL-related parameters. Conclusions: Surgery significantly alters the metabolomic fingerprint of CRC patients. Some metabolic changes seem to be associated with the development of cancer relapse. These data, if validated in a larger cohort, open new possibilities for risk stratification in patients with early-stage CRC.
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19
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Letertre MPM, Giraudeau P, de Tullio P. Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives. Front Mol Biosci 2021; 8:698337. [PMID: 34616770 PMCID: PMC8488110 DOI: 10.3389/fmolb.2021.698337] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/30/2021] [Indexed: 12/12/2022] Open
Abstract
Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.
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Affiliation(s)
| | | | - Pascal de Tullio
- Metabolomics Group, Center for Interdisciplinary Research of Medicine (CIRM), Department of Pharmacy, Université de Liège, Liège, Belgique
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Viera M, Yip GWC, Shen HM, Baeg GH, Bay BH. Targeting CD82/KAI1 for Precision Therapeutics in Surmounting Metastatic Potential in Breast Cancer. Cancers (Basel) 2021; 13:4486. [PMID: 34503296 PMCID: PMC8431267 DOI: 10.3390/cancers13174486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/27/2021] [Accepted: 09/03/2021] [Indexed: 11/16/2022] Open
Abstract
Metastasis is the main cause of mortality in breast cancer patients. There is an unmet need to develop therapies that can impede metastatic spread. Precision oncology has shown great promise for the treatment of cancers, as the therapeutic approach is tailored to a specific group of patients who are likely to benefit from the treatment, rather than the traditional approach of "one size fits all". CD82, also known as KAI1, a glycoprotein belonging to the tetraspanin family and an established metastasis suppressor, could potentially be exploited to hinder metastases in breast cancer. This review explores the prospect of targeting CD82 as an innovative therapeutic approach in precision medicine for breast cancer patients, with the goal of preventing cancer progression and metastasis. Such an approach would entail the selection of a subset of breast cancer patients with low levels of CD82, and instituting an appropriate treatment scheme tailored towards restoring the levels of CD82 in this group of patients. Proposed precision treatment regimens include current modalities of treating breast cancer, in combination with either clinically approved drugs that could restore the levels of CD82, CD82 peptide mimics or non-coding RNA-based therapeutics.
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Affiliation(s)
- Maximillian Viera
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117594, Singapore; (M.V.); (G.W.C.Y.)
| | - George Wai Cheong Yip
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117594, Singapore; (M.V.); (G.W.C.Y.)
| | - Han-Ming Shen
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore;
- Faculty of Health Sciences, University of Macau, Taipa, China
| | - Gyeong Hun Baeg
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117594, Singapore; (M.V.); (G.W.C.Y.)
- Ciechanover Institute of Precision and Regenerative Medicine, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen 518172, China
| | - Boon Huat Bay
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117594, Singapore; (M.V.); (G.W.C.Y.)
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Boyson SP, Gao C, Quinn K, Boyd J, Paculova H, Frietze S, Glass KC. Functional Roles of Bromodomain Proteins in Cancer. Cancers (Basel) 2021; 13:3606. [PMID: 34298819 PMCID: PMC8303718 DOI: 10.3390/cancers13143606] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 07/09/2021] [Accepted: 07/09/2021] [Indexed: 12/31/2022] Open
Abstract
Histone acetylation is generally associated with an open chromatin configuration that facilitates many cellular processes including gene transcription, DNA repair, and DNA replication. Aberrant levels of histone lysine acetylation are associated with the development of cancer. Bromodomains represent a family of structurally well-characterized effector domains that recognize acetylated lysines in chromatin. As part of their fundamental reader activity, bromodomain-containing proteins play versatile roles in epigenetic regulation, and additional functional modules are often present in the same protein, or through the assembly of larger enzymatic complexes. Dysregulated gene expression, chromosomal translocations, and/or mutations in bromodomain-containing proteins have been correlated with poor patient outcomes in cancer. Thus, bromodomains have emerged as a highly tractable class of epigenetic targets due to their well-defined structural domains, and the increasing ease of designing or screening for molecules that modulate the reading process. Recent developments in pharmacological agents that target specific bromodomains has helped to understand the diverse mechanisms that bromodomains play with their interaction partners in a variety of chromatin processes, and provide the promise of applying bromodomain inhibitors into the clinical field of cancer treatment. In this review, we explore the expression and protein interactome profiles of bromodomain-containing proteins and discuss them in terms of functional groups. Furthermore, we highlight our current understanding of the roles of bromodomain-containing proteins in cancer, as well as emerging strategies to specifically target bromodomains, including combination therapies using bromodomain inhibitors alongside traditional therapeutic approaches designed to re-program tumorigenesis and metastasis.
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Affiliation(s)
- Samuel P. Boyson
- Department of Pharmaceutical Sciences, Albany College of Pharmacy and Health Sciences, Colchester, VT 05446, USA;
- Department of Pharmacology, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA;
| | - Cong Gao
- Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; (C.G.); (J.B.); (H.P.)
| | - Kathleen Quinn
- Department of Pharmacology, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA;
- Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; (C.G.); (J.B.); (H.P.)
| | - Joseph Boyd
- Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; (C.G.); (J.B.); (H.P.)
| | - Hana Paculova
- Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; (C.G.); (J.B.); (H.P.)
| | - Seth Frietze
- Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; (C.G.); (J.B.); (H.P.)
- University of Vermont Cancer Center, Burlington, VT 05405, USA
| | - Karen C. Glass
- Department of Pharmaceutical Sciences, Albany College of Pharmacy and Health Sciences, Colchester, VT 05446, USA;
- Department of Pharmacology, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA;
- University of Vermont Cancer Center, Burlington, VT 05405, USA
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