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Teng T, Shi H, Fan Y, Guo P, Zhang J, Qiu X, Feng J, Huang H. Metabolic responses to the occurrence and chemotherapy of pancreatic cancer: biomarker identification and prognosis prediction. Sci Rep 2024; 14:6938. [PMID: 38521793 PMCID: PMC10960848 DOI: 10.1038/s41598-024-56737-4] [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: 01/12/2024] [Accepted: 03/11/2024] [Indexed: 03/25/2024] Open
Abstract
As the most malignant tumor, the prognosis of pancreatic cancer is not ideal even in the small number of patients who can undergo radical surgery. As a highly heterogeneous tumor, chemotherapy resistance is a major factor leading to decreased efficacy and postoperative recurrence of pancreatic cancer. In this study, nuclear magnetic resonance (NMR)-based metabolomics was applied to identify serum metabolic characteristics of pancreatic ductal adenocarcinoma (PDAC) and screen the potential biomarkers for its diagnosis. Metabolic changes of patients with different CA19-9 levels during postoperative chemotherapy were also monitored and compared to identify the differential metabolites that may affect the efficacy of chemotherapy. Finally, 19 potential serum biomarkers were screened to serve the diagnosis of PDAC, and significant metabolic differences between the two CA19-9 stratifications of PDAC were involved in energy metabolism, lipid metabolism, amino acid metabolism, and citric acid metabolism. Enrichment analysis of metabolic pathways revealed six shared pathways by PDAC and chemotherapy such as alanine, aspartate and glutamate metabolism, arginine biosynthesis, glutamine and glutamate metabolism, citrate cycle, pyruvate metabolism, and glycogolysis/gluconeogeneis. The similarity between the metabolic characteristics of PDAC and the metabolic responses to chemotherapy provided a reference for clinical prediction of benefits of postoperative chemotherapy in PDAC patients.
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Affiliation(s)
- Tianhong Teng
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Han Shi
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Yanying Fan
- Fuzhou Children Hospital of Fujian Province, Fuzhou, Fujian, China
| | - Pengfei Guo
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jin Zhang
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Xinyu Qiu
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Jianghua Feng
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.
| | - Heguang Huang
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
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Nunes SC, Sousa J, Silva F, Silveira M, Guimarães A, Serpa J, Félix A, Gonçalves LG. Peripheral Blood Serum NMR Metabolomics Is a Powerful Tool to Discriminate Benign and Malignant Ovarian Tumors. Metabolites 2023; 13:989. [PMID: 37755269 PMCID: PMC10537270 DOI: 10.3390/metabo13090989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023] Open
Abstract
Ovarian cancer is the major cause of death from gynecological cancer and the third most common gynecological malignancy worldwide. Despite a slight improvement in the overall survival of ovarian carcinoma patients in recent decades, the cure rate has not improved. This is mainly due to late diagnosis and resistance to therapy. It is therefore urgent to develop effective methods for early detection and prognosis. We hypothesized that, besides being able to distinguish serum samples of patients with ovarian cancer from those of patients with benign ovarian tumors, 1H-NMR metabolomics analysis might be able to predict the malignant potential of tumors. For this, serum 1H-NMR metabolomics analyses were performed, including patients with malignant, benign and borderline ovarian tumors. The serum metabolic profiles were analyzed by multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A metabolic profile associated with ovarian malignant tumors was defined, in which lactate, 3-hydroxybutyrate and acetone were increased and acetate, histidine, valine and methanol were decreased. Our data support the use of 1H-NMR metabolomics analysis as a screening method for ovarian cancer detection and might be useful for predicting the malignant potential of borderline tumors.
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Affiliation(s)
- Sofia C. Nunes
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (S.C.N.); (J.S.); (A.F.)
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - Joana Sousa
- Instituto de Tecnologia Química e Biológica António Xavier (ITQB NOVA), Avenida da República (EAN), 2780-157 Oeiras, Portugal
| | - Fernanda Silva
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (S.C.N.); (J.S.); (A.F.)
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - Margarida Silveira
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - António Guimarães
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - Jacinta Serpa
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (S.C.N.); (J.S.); (A.F.)
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - Ana Félix
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (S.C.N.); (J.S.); (A.F.)
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal
| | - Luís G. Gonçalves
- Instituto de Tecnologia Química e Biológica António Xavier (ITQB NOVA), Avenida da República (EAN), 2780-157 Oeiras, Portugal
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Pei C, Wang Y, Ding Y, Li R, Shu W, Zeng Y, Yin X, Wan J. Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2209083. [PMID: 36764026 DOI: 10.1002/adma.202209083] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/25/2023] [Indexed: 05/05/2023]
Abstract
Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC is in high demand to improve prognostic outcome but is still missing. Here, a concave octahedron Mn2 O3 /(Co,Mn)(Co,Mn)2 O4 (MO/CMO) composite with a heterojunction, rough surface, hollow interior, and sharp corners is developed to record metabolic patterns of ovarian tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites with multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, and selective trapping of small molecules. The MO/CMO shows ≈2-5-fold signal enhancement compared to mono- or dual-enhancement counterparts, and ≈10-48-fold compared to the commercialized products. Subsequently, serum metabolic fingerprints of ovarian tumors are revealed by MO/CMO-assisted LDI-MS, achieving high reproducibility of direct serum detection without treatment. Furthermore, machine learning of the metabolic fingerprints distinguishes malignant ovarian tumors from benign controls with the area under the curve value of 0.987. Finally, seven metabolites associated with the progression of ovarian tumors are screened as potential biomarkers. The approach guides the future depiction of the state-of-the-art matrix for intensive MS detection and accelerates the growth of nanomaterials-based platforms toward precision diagnosis scenarios.
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Affiliation(s)
- Congcong Pei
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - You Wang
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
- Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Yajie Ding
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Rongxin Li
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Weikang Shu
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Yu Zeng
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Xia Yin
- State Key Laboratory for Oncogenes and Related Genes, Shanghai Key Laboratory of Gynecologic Oncology, Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
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Shekher A, Puneet, Awasthee N, Kumar U, Raj R, Kumar D, Gupta SC. Association of altered metabolic profiles and long non-coding RNAs expression with disease severity in breast cancer patients: analysis by 1H NMR spectroscopy and RT-q-PCR. Metabolomics 2023; 19:8. [PMID: 36710275 DOI: 10.1007/s11306-023-01972-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 01/12/2023] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Globally, one of the major causes of cancer related deaths in women is breast cancer. Although metabolic pattern is altered in cancer patients, robust metabolic biomarkers with a potential to improve the screening and disease monitoring are lacking. A complete metabolome profiling of breast cancer patients may lead to the identification of diagnostic/prognostic markers and potential targets. OBJECTIVES The aim of this study was to analyze the metabolic profile in the serum from 43 breast cancer patients and 13 healthy individuals. MATERIALS & METHODS We used 1H NMR spectroscopy for the identification and quantification of metabolites. q-RT-PCR was used to examine the relative expression of lncRNAs. RESULTS Metabolites such as amino acids, lipids, membrane metabolites, lipoproteins, and energy metabolites were observed in the serum from both patients and healthy individuals. Using unsupervised PCA, supervised PLS-DA, supervised OPLS-DA, and random forest classification, we observed that more than 25 metabolites were altered in the breast cancer patients. Metabolites with AUC value > 0.9 were selected for further analysis that revealed significant elevation of lactate, LPR and glycerol, while the level of glucose, succinate, and isobutyrate was reduced in breast cancer patients in comparison to healthy control. The level of these metabolites (except LPR) was altered in advanced-stage breast cancer patients in comparison to early-stage breast cancer patients. The altered metabolites were also associated with over 25 signaling pathways related to metabolism. Further, lncRNAs such as H19, MEG3 and GAS5 were dysregulated in the breast tumor tissue in comparison to normal adjacent tissue. CONCLUSION The study provides insights into metabolic alteration in breast cancer patients. It also provides an avenue to examine the association of lncRNAs with metabolic patterns in patients.
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Affiliation(s)
- Anusmita Shekher
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
- Department of General Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
| | - Puneet
- Department of General Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
| | - Nikee Awasthee
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
- Department of Anatomy and Cell Biology, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Umesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India
| | - Ritu Raj
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India
| | - Dinesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India.
| | - Subash Chandra Gupta
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India.
- Department of Biochemistry, All India Institute of Medical Sciences, Guwahati, Assam, 781101, India.
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Yang Q, Bae G, Nadiradze G, Castagna A, Berezhnoy G, Zizmare L, Kulkarni A, Singh Y, Weinreich FJ, Kommoss S, Reymond MA, Trautwein C. Acidic ascites inhibits ovarian cancer cell proliferation and correlates with the metabolomic, lipidomic and inflammatory phenotype of human patients. J Transl Med 2022; 20:581. [PMID: 36503580 PMCID: PMC9743551 DOI: 10.1186/s12967-022-03763-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/05/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The poor prognosis of ovarian cancer patients is strongly related to peritoneal metastasis with the production of malignant ascites. However, it remains largely unclear how ascites in the peritoneal cavity influences tumor metabolism and recurrence. This study is an explorative approach aimed at for a deeper molecular and physical-chemical characterization of malignant ascites and to investigate their effect on in vitro ovarian cancer cell proliferation. METHODS This study included 10 malignant ascites specimens from patients undergoing ovarian cancer resection. Ascites samples were deeply phenotyped by 1H-NMR based metabolomics, blood-gas analyzer based gas flow analysis and flow cytomertry based a 13-plex cytokine panel. Characteristics of tumor cells were investigated in a 3D spheroid model by SEM and metabolic activity, adhesion, anti-apoptosis, migratory ability evaluated by MTT assay, adhesion assay, flowcytometry and scratch assay. The effect of different pH values was assessed by adding 10% malignant ascites to the test samples. RESULTS The overall extracellular (peritoneal) environment was alkaline, with pH of ascites at stage II-III = 7.51 ± 0.16, and stage IV = 7.78 ± 0.16. Ovarian cancer spheroids grew rapidly in a slightly alkaline environment. Decreasing pH of the cell culture medium suppressed tumor features, metabolic activity, adhesion, anti-apoptosis, and migratory ability. However, 10% ascites could prevent tumor cells from being affected by acidic pH. Metabolomics analysis identified stage IV patients had significantly higher concentrations of alanine, isoleucine, phenylalanine, and glutamine than stage II-III patients, while stage II-III patients had significantly higher concentrations of 3-hydroxybutyrate. pH was positively correlated with acetate, and acetate positively correlated with lipid compounds. IL-8 was positively correlated with lipid metabolites and acetate. Glutathione and carnitine were negatively correlated with cytokines IL-6 and chemokines (IL-8 & MCP-1). CONCLUSION Alkaline malignant ascites facilitated ovarian cancer progression. Additionally, deep ascites phenotyping by metabolomics and cytokine investigations allows for a refined stratification of ovarian cancer patients. These findings contribute to the understanding of ascites pathology in ovarian cancer.
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Affiliation(s)
- Qianlu Yang
- National Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany
| | - Gyuntae Bae
- grid.411544.10000 0001 0196 8249Present Address: Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany
| | - Giorgi Nadiradze
- National Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany ,grid.411544.10000 0001 0196 8249Department of General and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany
| | - Arianna Castagna
- National Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany ,grid.411544.10000 0001 0196 8249Department of General and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany
| | - Georgy Berezhnoy
- grid.411544.10000 0001 0196 8249Present Address: Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany
| | - Laimdota Zizmare
- grid.411544.10000 0001 0196 8249Present Address: Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany
| | - Aditi Kulkarni
- grid.411544.10000 0001 0196 8249Present Address: Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany
| | - Yogesh Singh
- grid.411544.10000 0001 0196 8249Institute of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany ,grid.411544.10000 0001 0196 8249Research Institute of Women’s Health, Women’s Hospital, University Hospital Tübingen, Tübingen, Germany
| | - Frank J. Weinreich
- National Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany
| | - Stefan Kommoss
- grid.411544.10000 0001 0196 8249Research Institute of Women’s Health, Women’s Hospital, University Hospital Tübingen, Tübingen, Germany
| | - Marc A. Reymond
- National Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany ,grid.411544.10000 0001 0196 8249Department of General and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany
| | - Christoph Trautwein
- grid.411544.10000 0001 0196 8249Present Address: Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany
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Guo P, Teng T, Liu W, Fang Y, Wei B, Feng J, Huang H. Metabolomic analyses redefine the biological classification of pancreatic cancer and correlate with clinical outcomes. Int J Cancer 2022; 151:1835-1846. [PMID: 35830200 DOI: 10.1002/ijc.34208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/24/2022] [Accepted: 07/07/2022] [Indexed: 11/10/2022]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is characterized by high heterogeneity, and the postoperative prognosis of different patients often varies greatly. Therefore, the classification of pancreatic cancer patients and precise treatment becomes particularly important. In our study, 1 H NMR spectroscopy was used to analyze the 76 PDAC serum samples and identify the potential metabolic subtypes. The metabolic characteristics of each metabolic subtype were screened out and the relationship between metabolic subtype and the long-term prognosis was further identified. The clinical stages of PDAC did not show the metabolic differences at the serum metabolomic level. And three metabolic subtypes, basic, choline-like and amino acid-enriched types, were defined by the hierarchical cluster analysis of the serum metabolites and the disturbed metabolic pathways. The characteristic metabolites of each PDAC subtype were identified, and the metabolite model was established to distinguish the PDAC patients in the different subtypes. Among the three metabolic subtypes, choline-like type displayed better long-term prognosis compared to the other two types of patients. Metabolic subtypes are of clinical importance and are closer to expressing the heterogeneity in the actual life activities of pancreatic cancer than molecular typing. The excavation of metabolic subtypes based on this will be more in line with clinical reality and more promising to guide clinical precision individualization treatment.
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Affiliation(s)
- Pengfei Guo
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Tianhong Teng
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Wuping Liu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Yanying Fang
- Fuzhou Children Hospital of Fujian Province, Fuzhou, China
| | - Binbin Wei
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jianghua Feng
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Heguang Huang
- Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China
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Liberto JM, Chen SY, Shih IM, Wang TH, Wang TL, Pisanic TR. Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review. Cancers (Basel) 2022; 14:2885. [PMID: 35740550 PMCID: PMC9221480 DOI: 10.3390/cancers14122885] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/06/2022] [Accepted: 06/08/2022] [Indexed: 02/04/2023] Open
Abstract
With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.
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Affiliation(s)
- Juliane M. Liberto
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
| | - Sheng-Yin Chen
- School of Medicine, Chang Gung University, 33302 Taoyuan, Taiwan;
| | - Ie-Ming Shih
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Tza-Huei Wang
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Tian-Li Wang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Thomas R. Pisanic
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
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8
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Eroglu EC, Kucukgoz Gulec U, Vardar MA, Paydas S. GC-MS based metabolite fingerprinting of serous ovarian carcinoma and benign ovarian tumor. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2022; 28:12-24. [PMID: 35503418 DOI: 10.1177/14690667221098520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The aim of this study is to identify urinary metabolomic profile of benign and malign ovarian tumors patients. Samples were analyzed using gas chromatography-mass spectrometry (GC-MS) and metabolomic tools to define biomarkers that cause differentiation between groups. 7 metabolites were found to be different in patients with ovarian cancer (OC) and benign tumors (BT). R2Y and Q2 values were found to be 0.670 and 0.459, respectively. L-tyrosine, glycine, stearic acid, turanose and L-threonine metabolites were defined as prominent biomarkers. The sensitivity of the model was calculated as 90.72% and the specificity as 82.09%. In the pathway analysis, glutathione metabolism, aminoacyl-tRNA biosynthesis, glycine serine and threonine metabolic pathway, primary bile acid biosynthesis pathways were found to be important. According to the t-test, 29 metabolites were found to be significant in urine samples of OC patients and healthy controls (HC). R2Y and Q2 values were found to be 0.8170 and 0.749, respectively. These results showed that the model has high compatibility and predictive power. Benzoic acid, L-threonine, L-pyroglutamic acid, creatinine and 3,4-dihydroxyphenylacetic acid metabolites were determined as prominent biomarkers. The sensitivity of the model was calculated as 93.81% and the specificity as 98.59%. Glycine serine and threonine metabolic pathway, glutathione metabolism and aminoacyl-tRNA biosynthesis pathways were determined important in OC patients and HC. The R2Y, Q2, sensitivity and specificity values in the urine samples of BT patients and HC were found to be 0.869, 0.794, 91.75, 97.01% and 97.18%, respectively. L-threonine, L-pyroglutamic acid, benzoic acid, creatinine and pentadecanol metabolites were determined as prominent biomarkers. Valine, leucine and isoleucine biosynthesis and aminoacyl-tRNA biosynthesis were significant. In this study, thanks to the untargeted metabolomic approach and chemometric methods, every group was differentiated from the others and prominent biomarkers were determined.
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Affiliation(s)
| | - Umran Kucukgoz Gulec
- Medical Faculty, Department of Gynecological Oncology, 63988Cukurova University, Adana, Turkey
| | - Mehmet Ali Vardar
- Medical Faculty, Department of Gynecological Oncology, 63988Cukurova University, Adana, Turkey
| | - Semra Paydas
- Medical Faculty, Department of Oncology, 63988Cukurova University, Adana, Turkey
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9
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Chen J, Chen Y, Sun K, Wang Y, He H, Sun L, Ha S, Li X, Ou Y, Zhang X, Bi Y. Prediction of Ovarian Cancer-Related Metabolites Based on Graph Neural Network. Front Cell Dev Biol 2021; 9:753221. [PMID: 34676219 PMCID: PMC8525679 DOI: 10.3389/fcell.2021.753221] [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: 08/04/2021] [Accepted: 08/27/2021] [Indexed: 11/13/2022] Open
Abstract
Ovarian cancer is one of the three most malignant tumors of the female reproductive system. At present, researchers do not know its pathogenesis, which makes the treatment effect unsatisfactory. Metabolomics is closely related to drug efficacy, safety evaluation, mechanism of action, and rational drug use. Therefore, identifying ovarian cancer-related metabolites could greatly help researchers understand the pathogenesis and develop treatment plans. However, the measurement of metabolites is inaccurate and greatly affects the environment, and biological experiment is time-consuming and costly. Therefore, researchers tend to use computational methods to identify disease-related metabolites in large scale. Since the hypothesis that similar diseases are related to similar metabolites is widely accepted, in this paper, we built both disease similarity network and metabolite similarity network and used graph convolutional network (GCN) to encode these networks. Then, support vector machine (SVM) was used to identify whether a metabolite is related to ovarian cancer. The experiment results show that the AUC and AUPR of our method are 0.92 and 0.81, respectively. Finally, we proposed an effective method to prioritize ovarian cancer-related metabolites in large scale.
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Affiliation(s)
- Jingjing Chen
- Department of Obstetrics and Gynecology, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yingying Chen
- Department of Obstetrics and Gynecology, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Kefeng Sun
- Department of Obstetrics and Gynecology, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yu Wang
- Department of Obstetrics and Gynecology, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hui He
- Department of Obstetrics and Gynecology, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Lin Sun
- Department of Reproductive Medicine, Dalian Maternal and Children's Centre, Dalian, China
| | - Sifu Ha
- Department of Reproductive Medicine, Dalian Maternal and Children's Centre, Dalian, China
| | - Xiaoxiao Li
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yifei Ou
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xue Zhang
- Department of General Practice, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yanli Bi
- Department of Reproductive Medicine, The First Affiliated Hospital, Henan University of Chinese Medicine, Zhengzhou, China
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10
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Pietkiewicz D, Klupczynska-Gabryszak A, Plewa S, Misiura M, Horala A, Miltyk W, Nowak-Markwitz E, Kokot ZJ, Matysiak J. Free Amino Acid Alterations in Patients with Gynecological and Breast Cancer: A Review. Pharmaceuticals (Basel) 2021; 14:ph14080731. [PMID: 34451829 PMCID: PMC8400482 DOI: 10.3390/ph14080731] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/15/2021] [Accepted: 07/21/2021] [Indexed: 02/06/2023] Open
Abstract
Gynecological and breast cancers still remain a significant health problem worldwide. Diagnostic methods are not sensitive and specific enough to detect the disease at an early stage. During carcinogenesis and tumor progression, the cellular need for DNA and protein synthesis increases leading to changes in the levels of amino acids. An important role of amino acids in many biological pathways, including biosynthesis of proteins, nucleic acids, enzymes, etc., which serve as an energy source and maintain redox balance, has been highlighted in many research articles. The aim of this review is a detailed analysis of the literature on metabolomic studies of gynecology and breast cancers with particular emphasis on alterations in free amino acid profiles. The work includes a brief overview of the metabolomic methodology and types of biological samples used in the studies. Special attention was paid to the possible role of selected amino acids in the carcinogenesis, especially proline and amino acids related to its metabolism. There is a clear need for further research and multiple external validation studies to establish the role of amino acid profiling in diagnosing gynecological and breast cancers.
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Affiliation(s)
- Dagmara Pietkiewicz
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Agnieszka Klupczynska-Gabryszak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Magdalena Misiura
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland; (M.M.); (W.M.)
| | - Agnieszka Horala
- Gynecologic Oncology Department, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (A.H.); (E.N.-M.)
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland; (M.M.); (W.M.)
| | - Ewa Nowak-Markwitz
- Gynecologic Oncology Department, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (A.H.); (E.N.-M.)
| | - Zenon J. Kokot
- Faculty of Health Sciences, Calisia University, 62-800 Kalisz, Poland;
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
- Correspondence:
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11
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Wang X, Zhao X, Zhao J, Yang T, Zhang F, Liu L. Serum metabolite signatures of epithelial ovarian cancer based on targeted metabolomics. Clin Chim Acta 2021; 518:59-69. [PMID: 33746017 DOI: 10.1016/j.cca.2021.03.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 03/12/2021] [Accepted: 03/12/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND Epithelial ovarian cancer (EOC) is a common gynecological cancer with high mortality rates. The main objective of this study was to investigate the serum amino acid and organic acid profiles to distinguish key metabolites for screening EOC patients. METHODS In total, 39 patients with EOC and 31 healthy controls were selected as the training set. Serum amino acid and organic acid profiles were determined using the targeted metabolomics approach. Metabolite profiles were processed via multivariate analysis to identify potential metabolites and construct a metabolic network. Finally, a test dataset derived from 29 patients and 28 healthy controls was constructed to validate the potential metabolites. RESULTS Distinct amino acid and organic acid profiles were obtained between EOC and healthy control groups. Methionine, glutamine, asparagine, glutamic acid and glycolic acid were identified as potential metabolites to distinguish EOC from control samples. The areas under the curve for methionine, glutamine, asparagine, glutamic acid and glycolic acid were 0.775, 0 778, 0.955, 0.874 and 0.897, respectively, in the validation study. Metabolic network analysis of the training set indicated key roles of alanine, aspartate and glutamate metabolism as well as D-glutamine and D-glutamate metabolism in the pathogenesis of EOC. CONCLUSIONS Amino acid and organic acid profiles may serve as potential screening tools for EOC. Data from this study provide useful information to bridge gaps in the understanding of the amino acid and organic acid alterations associated with epithelial ovarian cancer.
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Affiliation(s)
- Xinyang Wang
- Department of Microbiology, Harbin Medical University, Harbin, PR China; Wu Lien-Teh Institute, Harbin Medical University, Harbin, PR China
| | - Xinshu Zhao
- The Affiliated Tumor Hospital of Harbin Medical University, Harbin, PR China
| | - Jinhui Zhao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China
| | - Tongshu Yang
- The Affiliated Tumor Hospital of Harbin Medical University, Harbin, PR China
| | - Fengmin Zhang
- Department of Microbiology, Harbin Medical University, Harbin, PR China; Wu Lien-Teh Institute, Harbin Medical University, Harbin, PR China.
| | - Liyan Liu
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China.
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12
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Horala A, Plewa S, Derezinski P, Klupczynska A, Matysiak J, Nowak-Markwitz E, Kokot ZJ. Serum Free Amino Acid Profiling in Differential Diagnosis of Ovarian Tumors-A Comparative Study with Review of the Literature. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18042167. [PMID: 33672144 PMCID: PMC7926859 DOI: 10.3390/ijerph18042167] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 02/11/2021] [Accepted: 02/16/2021] [Indexed: 12/21/2022]
Abstract
Proper preoperative ovarian cancer (OC) diagnosis remains challenging. Serum free amino acid (SFAA) profiles were investigated to identify potential novel biomarkers of OC and assess their performance in ovarian tumor differential diagnosis. Serum samples were divided based on the histopathological result: epithelial OC (n = 38), borderline ovarian tumors (n = 6), and benign ovarian tumors (BOTs) (n = 62). SFAA profiles were evaluated using aTRAQ methodology based on high-performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Levels of eleven amino acids significantly differed between OC+borderline and BOTs. The highest area under the receiver operating characteristic curve (AUC of ROC) (0.787) was obtained for histidine. Cystine and histidine were identified as best single markers for early stage OC/BOT and type I OC. For advanced stage OC, seven amino acids differed significantly between the groups and citrulline obtained the best AUC of 0.807. Between type II OC and BOTs, eight amino acids differed significantly and the highest AUC of 0.798 was achieved by histidine and citrulline (AUC of 0.778). Histidine was identified as a potential new biomarker in differential diagnosis of ovarian tumors. Adding histidine to a multimarker panel together with CA125 and HE4 improved the differential diagnosis between OC and BOTs.
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Affiliation(s)
- Agnieszka Horala
- Gynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland;
- Correspondence:
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Pawel Derezinski
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Agnieszka Klupczynska
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Ewa Nowak-Markwitz
- Gynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland;
| | - Zenon J. Kokot
- Faculty of Health Sciences, Calisia University, 13 Kaszubska Street, 62-800 Kalisz, Poland;
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13
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Abstract
Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.
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14
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Ahmed-Salim Y, Galazis N, Bracewell-Milnes T, Phelps DL, Jones BP, Chan M, Munoz-Gonzales MD, Matsuzono T, Smith JR, Yazbek J, Krell J, Ghaem-Maghami S, Saso S. The application of metabolomics in ovarian cancer management: a systematic review. Int J Gynecol Cancer 2020; 31:754-774. [PMID: 33106272 DOI: 10.1136/ijgc-2020-001862] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 09/24/2020] [Accepted: 09/28/2020] [Indexed: 12/15/2022] Open
Abstract
Metabolomics, the global analysis of metabolites in a biological specimen, could potentially provide a fast method of biomarker identification for ovarian cancer. This systematic review aims to examine findings from studies that apply metabolomics to the diagnosis, prognosis, treatment, and recurrence of ovarian cancer. A systematic search of English language publications was conducted on PubMed, Science Direct, and SciFinder. It was augmented by a snowball strategy, whereby further relevant studies are identified from reference lists of included studies. Studies in humans with ovarian cancer which focus on metabolomics of biofluids and tumor tissue were included. No restriction was placed on the time of publication. A separate review of targeted metabolomic studies was conducted for completion. Qualitative data were summarized in a comprehensive table. The studies were assessed for quality and risk of bias using the ROBINS-I tool. 32 global studies were included in the main systematic review. Most studies applied metabolomics to diagnosing ovarian cancer, within which the most frequently reported metabolite changes were a down-regulation of phospholipids and amino acids: histidine, citrulline, alanine, and methionine. Dysregulated phospholipid metabolism was also reported in the separately reviewed 18 targeted studies. Generally, combinations of more than one significant metabolite as a panel, in different studies, achieved a higher sensitivity and specificity for diagnosis than a single metabolite; for example, combinations of different phospholipids. Widespread metabolite differences were observed in studies examining prognosis, treatment, and recurrence, and limited conclusions could be drawn. Cellular processes of proliferation and invasion may be reflected in metabolic changes present in poor prognosis and recurrence. For example, lower levels of lysine, with increased cell invasion as an underlying mechanism, or glutamine dependency of rapidly proliferating cancer cells. In conclusion, this review highlights potential metabolites and biochemical pathways which may aid the clinical care of ovarian cancer if further validated.
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Affiliation(s)
| | - Nicolas Galazis
- Department of Obstetrics and Gynaecology, Northwick Park Hospital, Harrow, UK
| | | | - David L Phelps
- Department of Gynaecological Oncology, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
| | - Benjamin P Jones
- Division of Surgery and Cancer, Institute of Reproductive and Developmental Biology, Hammersmith Hospital Campus, Du Cane Road, Imperial College London, London, UK
| | - Maxine Chan
- South Kensington Campus, Imperial College London Department of Materials, London, UK
| | | | - Tomoko Matsuzono
- Queen Elizabeth Hospital, Department of Obstetrics and Gynaecology, Hong Kong, Hong Kong
| | - James Richard Smith
- West London Gynaecological Cancer Centre, Queen Charlotte's Hospital, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
| | - Joseph Yazbek
- West London Gynaecological Cancer Centre, Queen Charlotte's Hospital, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
| | - Jonathan Krell
- West London Gynaecological Cancer Centre, Queen Charlotte's Hospital, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
| | - Sadaf Ghaem-Maghami
- Department of Gynaecological Oncology, West London Gynaecological Cancer Centre, Queen Charlotte's Hospital, Hammersmith Hospital Campus, Imperial College London and NHS Trust, Du Cane Road, Imperial College London, London, UK
| | - Srdjan Saso
- Division of Surgery and Cancer, Institute of Reproductive and Developmental Biology, Hammersmith Hospital Campus, Du Cane Road, Imperial College London, London, UK
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15
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Saorin A, Di Gregorio E, Miolo G, Steffan A, Corona G. Emerging Role of Metabolomics in Ovarian Cancer Diagnosis. Metabolites 2020; 10:E419. [PMID: 33086611 PMCID: PMC7603269 DOI: 10.3390/metabo10100419] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 01/20/2023] Open
Abstract
Ovarian cancer is considered a silent killer due to the lack of clear symptoms and efficient diagnostic tools that often lead to late diagnoses. Over recent years, the impelling need for proficient biomarkers has led researchers to consider metabolomics, an emerging omics science that deals with analyses of the entire set of small-molecules (≤1.5 kDa) present in biological systems. Metabolomics profiles, as a mirror of tumor-host interactions, have been found to be useful for the analysis and identification of specific cancer phenotypes. Cancer may cause significant metabolic alterations to sustain its growth, and metabolomics may highlight this, making it possible to detect cancer in an early phase of development. In the last decade, metabolomics has been widely applied to identify different metabolic signatures to improve ovarian cancer diagnosis. The aim of this review is to update the current status of the metabolomics research for the discovery of new diagnostic metabolomic biomarkers for ovarian cancer. The most promising metabolic alterations are discussed in view of their potential biological implications, underlying the issues that limit their effective clinical translation into ovarian cancer diagnostic tools.
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Affiliation(s)
- Asia Saorin
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
| | - Emanuela Di Gregorio
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
| | - Gianmaria Miolo
- 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; (A.S.); (E.D.G.); (A.S.)
| | - Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
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16
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Govorov I, Sitkin S, Pervunina T, Moskvin A, Baranenko D, Komlichenko E. Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path? Curr Med Chem 2020; 27:3611-3622. [PMID: 30608036 DOI: 10.2174/0929867326666190104124245] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 12/21/2018] [Accepted: 12/31/2018] [Indexed: 12/27/2022]
Abstract
Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome - the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.
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Affiliation(s)
- Igor Govorov
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation.,International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Stanislav Sitkin
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation.,International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation.,North-Western State Medical University named after I.I. Mechnikov, St. Petersburg 191015, Russian Federation
| | - Tatyana Pervunina
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation.,International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Alexey Moskvin
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Denis Baranenko
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Eduard Komlichenko
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation.,International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
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17
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Abstract
The fast-growing field of metabolomics is impacting numerous areas of basic and life sciences. In metabolomics, analytical methods play a pivotal role, and nuclear magnetic resonance (NMR) and mass spectrometry (MS) have proven to be the most suitable and powerful methods. Although NMR exhibits lower sensitivity and resolution compared to MS, NMR's numerous important characteristics far outweigh its limitations. Some of its characteristics include excellent reproducibility and quantitative accuracy, the capability to analyze intact biospecimens, an unparalleled ability to identify unknown metabolites, the ability to trace in-cell and in-organelle metabolism in real time, and the capacity to trace metabolic pathways atom by atom using 2H, 13C, or 15N isotopes. Each of these characteristics has been exploited extensively in numerous studies. In parallel, the field has witnessed significant progress in instrumentation, methods development, databases, and automation that are focused on higher throughput and alleviating the limitations of NMR, in particular, resolution and sensitivity. Despite the advances, however, the high complexity of biological mixtures combined with the limitations in sensitivity and resolution continues to pose major challenges. These challenges need to be dealt with effectively to better realize the potential of metabolomics, in general. As a result, multifaceted efforts continue to focus on addressing the challenges as well as reaping the benefits of NMR-based metabolomics. This chapter highlights the current status with emphasis on the opportunities and challenges in NMR-based metabolomics.
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18
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One-Carbon Metabolism: Biological Players in Epithelial Ovarian Cancer. Int J Mol Sci 2018; 19:ijms19072092. [PMID: 30029471 PMCID: PMC6073728 DOI: 10.3390/ijms19072092] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 07/06/2018] [Accepted: 07/17/2018] [Indexed: 02/07/2023] Open
Abstract
Metabolism is deeply involved in cell behavior and homeostasis maintenance, with metabolites acting as molecular intermediates to modulate cellular functions. In particular, one-carbon metabolism is a key biochemical pathway necessary to provide carbon units required for critical processes, including nucleotide biosynthesis, epigenetic methylation, and cell redox-status regulation. It is, therefore, not surprising that alterations in this pathway may acquire fundamental importance in cancer onset and progression. Two of the major actors in one-carbon metabolism, folate and choline, play a key role in the pathobiology of epithelial ovarian cancer (EOC), the deadliest gynecological malignancy. EOC is characterized by a cholinic phenotype sustained via increased activity of choline kinase alpha, and via membrane overexpression of the alpha isoform of the folate receptor (FRα), both of which are known to contribute to generating regulatory signals that support EOC cell aggressiveness and proliferation. Here, we describe in detail the main biological processes associated with one-carbon metabolism, and the current knowledge about its role in EOC. Moreover, since the cholinic phenotype and FRα overexpression are unique properties of tumor cells, but not of normal cells, they can be considered attractive targets for the development of therapeutic approaches.
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19
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Li X, Wu T, Jiang Y, Zhang Z, Han X, Geng W, Ding H, Kang J, Wang Q, Shang H. Plasma metabolic changes in Chinese HIV-infected patients receiving lopinavir/ritonavir based treatment: Implications for HIV precision therapy. Cytokine 2018; 110:204-212. [PMID: 29778008 DOI: 10.1016/j.cyto.2018.05.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 03/30/2018] [Accepted: 05/02/2018] [Indexed: 12/25/2022]
Abstract
OBJECTIVES The goal of this study is to profile the metabolic changes in the plasma of HIV patients receiving lopinavir/ritonavir (LPV/r)-based highly active antiretroviral therapy (HAART) relative to their treatment-naïve phase, aimed to identify precision therapy for HIV for improving prognosis and predicting dyslipidemia caused by LPV/r. METHODS 38 longitudinal plasma samples were collected from 19 HIV-infected patients both before and after antiretroviral therapy, and 18 samples from healthy individuals were used as controls. Untargeted metabolomics profiling of these plasma samples was performed using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). RESULTS A total of 331 compounds of known identity were detected among these metabolites, a 67-metabolite signature mainly mapping to tryptophan, histidine, acyl carnitine, ketone bodies and fatty acid metabolism distinguished HIV patients from healthy controls. The levels of 19 out of the 67 altered metabolites including histidine, kynurenine, and 3-hydroxybutyrate (BHBA), recovered after LPV/r-based antiretroviral therapy, and histidine was positively correlated with the presence of CD4 + T lymphocytes. Furthermore, using receiver operating characteristic (ROC) analyses, we discovered that butyrylcarnitine in combination with myristic acid from plasma in treatment-naïve patients could predict dyslipidemia caused by LPV/r with 87% accuracy. CONCLUSIONS Metabolites alterations in treatment-naïve HIV patients may indicate an inflammatory, oxidative state and mitochondrial dysfunction that is permissive for disease progression. Histidine may provide a specific protective function for HIV patients. Besides, elevated fatty acids levels including butyrylcarnitine and myristic acid after infection may indicate patients at risk of suffering from dyslipidemia after LPV/r-based HAART.
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Affiliation(s)
- Xiaolin Li
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Tong Wu
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Yongjun Jiang
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Zining Zhang
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Xiaoxu Han
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Wenqing Geng
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Haibo Ding
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Jing Kang
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Qi Wang
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China
| | - Hong Shang
- Key Laboratory of AIDS Immunology of National Health and Family Planning Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, PR China.
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20
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Giskeødegård GF, Madssen TS, Euceda LR, Tessem MB, Moestue SA, Bathen TF. NMR-based metabolomics of biofluids in cancer. NMR IN BIOMEDICINE 2018; 32:e3927. [PMID: 29672973 DOI: 10.1002/nbm.3927] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 02/13/2018] [Accepted: 03/07/2018] [Indexed: 06/08/2023]
Abstract
This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.
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Affiliation(s)
- Guro F Giskeødegård
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Torfinn S Madssen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Leslie R Euceda
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Siver A Moestue
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
- Department of Health Science, Nord University, Bodø, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
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Bahado-Singh RO, Lugade A, Field J, Al-Wahab Z, Han B, Mandal R, Bjorndahl TC, Turkoglu O, Graham SF, Wishart D, Odunsi K. Metabolomic prediction of endometrial cancer. Metabolomics 2017; 14:6. [PMID: 30830361 DOI: 10.1007/s11306-017-1290-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Accepted: 10/25/2017] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality. OBJECTIVE To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC. METHODS We performed NMR and mass spectrometry based metabolomic analyses of serum in EC cases versus controls. A total of 46 early-stage (FIGO stages I-II) and 10 late-stage (FIGO stages III-IV) EC cases constituted the study group. A total of 60 unaffected control samples were used. Patients and controls were divided randomly into a discovery group (n = 69) and an independent validation group (n = 47). Predictive algorithms based on biomarkers and demographic characteristics were generated using logistic regression analysis. RESULTS A total of 181 metabolites were evaluated. Extensive changes in metabolite levels were noted in the EC versus the control group. The combination of C14:2, phosphatidylcholine with acyl-alkyl residue sum C38:1 (PCae C38:1) and 3-hydroxybutyric acid had an area under the receiver operating characteristics curve (AUC) (95% CI) = 0.826 (0.706-0.946) and a sensitivity = 82.6%, and specificity = 70.8% for EC overall. For early EC prediction: BMI, C14:2 and PC ae C40:1 had an AUC (95% CI) = 0.819 (0.689-0.95) and a sensitivity = 72.2% and specificity = 79.2% in the validation group. CONCLUSIONS EC is characterized by significant perturbations in important cellular metabolites. Metabolites accurately detected early-stage EC cases and EC overall which could lead to the development of non-invasive biomarkers for earlier detection of EC and for monitoring disease recurrence.
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Affiliation(s)
- Ray O Bahado-Singh
- Department of Obstetrics and Gynecology, William Beaumont Health, Royal Oak, MI, 48073, USA.
| | - Amit Lugade
- Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Jayson Field
- Department of Gynecologic Oncology, William Beaumont Health, Royal Oak, MI, USA
| | - Zaid Al-Wahab
- Department of Gynecologic Oncology, William Beaumont Health, Royal Oak, MI, USA
| | - BeomSoo Han
- Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada
| | - Rupasri Mandal
- Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada
| | - Trent C Bjorndahl
- Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada
| | - Onur Turkoglu
- Department of Obstetrics and Gynecology, William Beaumont Health, Royal Oak, MI, 48073, USA
| | - Stewart F Graham
- Department of Obstetrics and Gynecology, William Beaumont Health, Royal Oak, MI, 48073, USA
| | - David Wishart
- Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada
- Department of Computing Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada
| | - Kunle Odunsi
- Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, USA
- Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, USA
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22
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Louis E, Cantrelle FX, Mesotten L, Reekmans G, Bervoets L, Vanhove K, Thomeer M, Lippens G, Adriaensens P. Metabolic phenotyping of human plasma by 1 H-NMR at high and medium magnetic field strengths: a case study for lung cancer. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:706-713. [PMID: 28061019 DOI: 10.1002/mrc.4577] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 12/25/2016] [Accepted: 01/04/2017] [Indexed: 06/06/2023]
Abstract
Accurate identification and quantification of human plasma metabolites can be challenging in crowded regions of the NMR spectrum with severe signal overlap. Therefore, this study describes metabolite spiking experiments on the basis of which the NMR spectrum can be rationally segmented into well-defined integration regions, and this for spectrometers having magnetic field strengths corresponding to 1 H resonance frequencies of 400 MHz and 900 MHz. Subsequently, the integration data of a case-control dataset of 69 lung cancer patients and 74 controls were used to train a multivariate statistical classification model for both field strengths. In this way, the advantages/disadvantages of high versus medium magnetic field strength were evaluated. The discriminative power obtained from the data collected at the two magnetic field strengths is rather similar, i.e. a sensitivity and specificity of respectively 90 and 97% for the 400 MHz data versus 88 and 96% for the 900 MHz data. This shows that a medium-field NMR spectrometer (400-600 MHz) is already sufficient to perform clinical metabolomics. However, the improved spectral resolution (reduced signal overlap) and signal-to-noise ratio of 900 MHz spectra yield more integration regions that represent a single metabolite. This will simplify the unraveling and understanding of the related, disease disturbed, biochemical pathways. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- Evelyne Louis
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
| | - Francois-Xavier Cantrelle
- CNRS UMR 8576, Unité de Glycobiologie Structurale et Fonctionnelle, Université des Sciences et Technologies de Lille 1, Cité Scientifique, 59655, Villeneuve d'Ascq Cedex, France
| | - Liesbet Mesotten
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Nuclear Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium
| | - Gunter Reekmans
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Liene Bervoets
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
| | - Karolien Vanhove
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Respiratory Medicine, Algemeen Ziekenhuis Vesalius, Hazelereik 51, 3700, Tongeren, Belgium
| | - Michiel Thomeer
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Respiratory Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium
| | - Guy Lippens
- CNRS UMR 8576, Unité de Glycobiologie Structurale et Fonctionnelle, Université des Sciences et Technologies de Lille 1, Cité Scientifique, 59655, Villeneuve d'Ascq Cedex, France
- Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés, INSA, University of Toulouse, CNRS, INRA, 135 Avenue de Rangueil, 31400, Toulouse, France
| | - Peter Adriaensens
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
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Lin X, Zhan B, Wen S, Li Z, Huang H, Feng J. Metabonomic alterations from pancreatic intraepithelial neoplasia to pancreatic ductal adenocarcinoma facilitate the identification of biomarkers in serum for early diagnosis of pancreatic cancer. MOLECULAR BIOSYSTEMS 2017; 12:2883-92. [PMID: 27400832 DOI: 10.1039/c6mb00381h] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Pancreatic cancer is a highly malignant disease with a poor prognosis and it is essential to diagnose and treat the disease at an early stage. The aim of this study was to understand the underlying biochemical mechanisms of pancreatic intraepithelial neoplasia (PanIN) and pancreatic ductal adenocarcinoma (PDAC) and to identify potential serum biomarkers for early detection of pancreatic cancer. 7,12-Dimethylbenz(a)anthracene (DMBA)-induced PanIN and PDAC rat models were established and the serum samples were collected. The serum samples were measured using (1)H nuclear magnetic resonance (NMR) spectroscopy and analyzed by chemometric methods including principal component analysis (PCA) and (orthogonal) partial least squares discriminant analysis ((O)PLS-DA). The related biochemical pathways were derived from KEGG analysis of the significantly different metabolites. As results, some serum metabolites demonstrated alarming metabolic changes in the precursor lesion of pancreatic cancer (PanIN-2 in this study). These changes involved elevated levels of ketone compounds including 3-hydroxybutyrate, acetoacetate, and acetone, some amino acids including asparagine, glutamate, threonine, and phenylalanine, glycoproteins and lipoproteins including N-acetylglycoprotein, LDL and VLDL, and some metabolites that have been shown to contribute to mutagenicity and cancer promotion such as deoxyguanosine and cytidine. More metabolites were shown to be significantly different between PanIN and PDAC, suggesting that a more complex set of changes occurs from noninvasive precursor lesion to invasive cancer. The serum metabonomic changes of rats with PanIN and PDAC may extend our understanding of pancreatic molecular pathogenesis, and the metabolic variations from PanIN to PDAC will be helpful to understand evolution processes of the pancreatic disease. NMR-based metabonomic analysis of animal models will be beneficial for the human study and will be helpful for the early detection of pancreatic cancer.
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Affiliation(s)
- Xianchao Lin
- General Surgery Department, Fujian Medical University Union Hospital, Fuzhou 350001, China.
| | - Bohan Zhan
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
| | - Shi Wen
- General Surgery Department, Fujian Medical University Union Hospital, Fuzhou 350001, China.
| | - Zhishui Li
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
| | - Heguang Huang
- General Surgery Department, Fujian Medical University Union Hospital, Fuzhou 350001, China.
| | - Jianghua Feng
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
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24
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Zennaro L, Vanzani P, Nicolè L, Cappellesso R, Fassina A. Metabonomics by proton nuclear magnetic resonance in human pleural effusions: A route to discriminate between benign and malignant pleural effusions and to target small molecules as potential cancer biomarkers. Cancer Cytopathol 2017; 125:341-348. [PMID: 28140518 DOI: 10.1002/cncy.21832] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 12/22/2016] [Accepted: 12/22/2016] [Indexed: 11/12/2022]
Abstract
BACKGROUND Cytopathology is a noninvasive and cost-effective method for detecting cancer cells in pleural effusions (PEs), although in many cases, the diagnostic performance is hindered by the paucity of significant cells or the lack of clear morphological criteria. This study presents the results of an omics approach to improving the diagnostic performance of PE cytology. METHODS Metabolic profiling with proton nuclear magnetic resonance (1 H-NMR) was performed for 92 PEs (44 malignant cases of 8 different cancers and 48 benign cases of 7 nonneoplastic conditions). Light's criteria were used to further classify PEs as transudates or exudates, and 1 H-NMR spectroscopy was used to differentiate malignant pleural effusions (mPEs) from benign pleural effusions (bPEs). RESULTS 1 H-NMR metabolic analysis showed clearly different spectra for mPEs and bPEs in the regions of the signals due to lipids, branched amino acids, and lactate, which were increased in mPEs. Transudates and exudates in bPEs were differentiated as well on the basis of the 1 H-NMR signals from lipids and lipoproteins, which were increased in exudates. CONCLUSIONS Subject to validation in further larger studies, 1 H-NMR metabonomics could be an effective and reliable ancillary tool for PE investigations and diagnoses. Cancer Cytopathol 2017;125:341-348. © 2017 American Cancer Society.
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Affiliation(s)
- Lucio Zennaro
- Department of Molecular Medicine, University of Padua, Padua, Italy.,Section of Padua, National Institute of Biostructures and Biosystems, Rome, Italy
| | - Paola Vanzani
- Department of Molecular Medicine, University of Padua, Padua, Italy.,Section of Padua, National Institute of Biostructures and Biosystems, Rome, Italy
| | - Lorenzo Nicolè
- Surgical Pathology and Cytopathology Unit, Department of Medicine, University of Padua, Padua, Italy
| | - Rocco Cappellesso
- Surgical Pathology and Cytopathology Unit, Department of Medicine, University of Padua, Padua, Italy
| | - Ambrogio Fassina
- Surgical Pathology and Cytopathology Unit, Department of Medicine, University of Padua, Padua, Italy
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25
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Yin R, Yang T, Su H, Ying L, Liu L, Sun C. Saturated fatty acids as possible important metabolites for epithelial ovarian cancer based on the free and esterified fatty acid profiles determined by GC-MS analysis. Cancer Biomark 2016; 17:259-269. [DOI: 10.3233/cbm-160638] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Rui Yin
- Department of Analytical Chemistry, College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
- Department of Analytical Chemistry, College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
| | - Tongshu Yang
- The Affiliated Tumor Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, China
- Department of Analytical Chemistry, College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
| | - Hui Su
- Department of Pharmaceutical Engineering, College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
| | - Li Ying
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, Heilongjiang, China
| | - Liyan Liu
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, Heilongjiang, China
| | - Changhao Sun
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, Heilongjiang, China
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26
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Xie G, Zhou B, Zhao A, Qiu Y, Zhao X, Garmire L, Shvetsov YB, Yu H, Yen Y, Jia W. Lowered circulating aspartate is a metabolic feature of human breast cancer. Oncotarget 2016; 6:33369-81. [PMID: 26452258 PMCID: PMC4741772 DOI: 10.18632/oncotarget.5409] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2015] [Accepted: 09/18/2015] [Indexed: 11/25/2022] Open
Abstract
Distinct metabolic transformation is essential for cancer cells to sustain a high rate of proliferation and resist cell death signals. Such a metabolic transformation results in unique cellular metabolic phenotypes that are often reflected by distinct metabolite signatures in tumor tissues as well as circulating blood. Using a metabolomics platform, we find that breast cancer is associated with significantly (p = 6.27E-13) lowered plasma aspartate levels in a training group comprising 35 breast cancer patients and 35 controls. The result was validated with 103 plasma samples and 183 serum samples of two groups of primary breast cancer patients. Such a lowered aspartate level is specific to breast cancer as it has shown 0% sensitivity in serum from gastric (n = 114) and colorectal (n = 101) cancer patients. There was a significantly higher level of aspartate in breast cancer tissues (n = 20) than in adjacent non-tumor tissues, and in MCF-7 breast cancer cell line than in MCF-10A cell lines, suggesting that the depleted level of aspartate in blood of breast cancer patients is due to increased tumor aspartate utilization. Together, these findings suggest that lowed circulating aspartate is a key metabolic feature of human breast cancer.
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Affiliation(s)
- Guoxiang Xie
- Center for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.,University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Bingsen Zhou
- Department of Medical Oncology and Therapeutic Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Aihua Zhao
- Center for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yunping Qiu
- Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA
| | - Xueqing Zhao
- Nutrition Research Institute, University of North Carolina at Chapel Hill, North Carolina Research Campus, Kannapolis, NC, USA
| | - Lana Garmire
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | | | - Herbert Yu
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Yun Yen
- Department of Medical Oncology and Therapeutic Research, City of Hope National Medical Center, Duarte, CA, USA.,Taipei Medical University, Taipei, Taiwan
| | - Wei Jia
- Center for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.,University of Hawaii Cancer Center, Honolulu, HI, USA
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27
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28
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Gidwani K, Huhtinen K, Kekki H, van Vliet S, Hynninen J, Koivuviita N, Perheentupa A, Poutanen M, Auranen A, Grenman S, Lamminmäki U, Carpen O, van Kooyk Y, Pettersson K. A Nanoparticle-Lectin Immunoassay Improves Discrimination of Serum CA125 from Malignant and Benign Sources. Clin Chem 2016; 62:1390-400. [PMID: 27540033 DOI: 10.1373/clinchem.2016.257691] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 06/23/2016] [Indexed: 11/06/2022]
Abstract
BACKGROUND Measurement of serum cancer antigen 125 (CA125) is the standard approach for epithelial ovarian cancer (EOC) diagnostics and follow-up. However, the clinical specificity is not optimal because increased values are also detected in healthy controls and in benign diseases. CA125 is known to be differentially glycosylated in EOC, potentially offering a way to construct CA125 assays with improved cancer specificity. Our goal was to identify carbohydrate-reactive lectins for discriminating between CA125 originating from EOC and noncancerous sources. METHODS CA125 from the OVCAR-3 cancer cell line, placental homogenate, and ascites fluid from patients with cirrhosis were captured on anti-CA125 antibody immobilized on microtitration wells. A panel of lectins, each coated onto fluorescent europium-chelate-doped 97-nm nanoparticles (Eu(+3)-NPs), was tested for detection of the immobilized CA125. Serum samples from high-grade serous EOC or patients with endometriosis and healthy controls were analyzed. RESULTS By using macrophage galactose-type lectin (MGL)-coated Eu(+3)-NPs, an analytically sensitive CA125 assay (CA125(MGL)) was achieved that specifically recognized the CA125 isoform produced by EOC, whereas the recognition of CA125 from nonmalignant conditions was reduced. Serum CA125(MGL) measurement better discriminated patients with EOC from endometriosis compared to conventional immunoassay. The discrimination was particularly improved for marginally increased CA125 values and for earlier detection of EOC progression. CONCLUSIONS The new CA125(MGL) assay concept could help reduce the false-positive rates of conventional CA125 immunoassays. The improved analytical specificity of this test approach is dependent on a discriminating lectin immobilized in large numbers on Eu(+3)-NPs, providing both an avidity effect and signal amplification.
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Affiliation(s)
- Kamlesh Gidwani
- Department of Biochemistry/Biotechnology, University of Turku, Turku, Finland;
| | - Kaisa Huhtinen
- Department of Pathology, Medicity research laboratories, University of Turku and Turku University Hospital, Turku, Finland
| | - Henna Kekki
- Department of Biochemistry/Biotechnology, University of Turku, Turku, Finland
| | - Sandra van Vliet
- Department of Molecular Cell Biology and Immunology, VU University Medical Center, Amsterdam, The Netherlands
| | - Johanna Hynninen
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Niina Koivuviita
- Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Antti Perheentupa
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Matti Poutanen
- Department of Physiology, Institute of Biomedicine, and Turku Center for Disease Modeling, University of Turku, Finland
| | - Annika Auranen
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland; Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland
| | - Seija Grenman
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Urpo Lamminmäki
- Department of Biochemistry/Biotechnology, University of Turku, Turku, Finland
| | - Olli Carpen
- Department of Pathology, Medicity research laboratories, University of Turku and Turku University Hospital, Turku, Finland; Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Yvette van Kooyk
- Department of Molecular Cell Biology and Immunology, VU University Medical Center, Amsterdam, The Netherlands
| | - Kim Pettersson
- Department of Biochemistry/Biotechnology, University of Turku, Turku, Finland
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Kim WT, Yun SJ, Yan C, Jeong P, Kim YH, Lee IS, Kang HW, Park S, Moon SK, Choi YH, Choi YD, Kim IY, Kim J, Kim WJ. Metabolic Pathway Signatures Associated with Urinary Metabolite Biomarkers Differentiate Bladder Cancer Patients from Healthy Controls. Yonsei Med J 2016; 57:865-71. [PMID: 27189278 PMCID: PMC4951461 DOI: 10.3349/ymj.2016.57.4.865] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Revised: 10/22/2015] [Accepted: 10/22/2015] [Indexed: 11/27/2022] Open
Abstract
PURPOSE Our previous high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry study identified bladder cancer (BCA)-specific urine metabolites, including carnitine, acylcarnitines, and melatonin. The objective of the current study was to determine which metabolic pathways are perturbed in BCA, based on our previously identified urinary metabolome. MATERIALS AND METHODS A total of 135 primary BCA samples and 26 control tissue samples from healthy volunteers were analyzed. The association between specific urinary metabolites and their related encoding genes was analyzed. RESULTS Significant alterations in the carnitine-acylcarnitine and tryptophan metabolic pathways were detected in urine specimens from BCA patients compared to those of healthy controls. The expression of eight genes involved in the carnitine-acylcarnitine metabolic pathway (CPT1A, CPT1B, CPT1C, CPT2, SLC25A20, and CRAT) or tryptophan metabolism (TPH1 and IDO1) was assessed by RT-PCR in our BCA cohort (n=135). CPT1B, CPT1C, SLC25A20, CRAT, TPH1, and IOD1 were significantly downregulated in tumor tissues compared to normal bladder tissues (p<0.05 all) of patients with non-muscle invasive BCA, whereas CPT1B, CPT1C, CRAT, and TPH1 were downregulated in those with muscle invasive BCA (p<0.05), with no changes in IDO1 expression. CONCLUSION Alterations in the expression of genes associated with the carnitine-acylcarnitine and tryptophan metabolic pathways, which were the most perturbed pathways in BCA, were determined.
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Affiliation(s)
- Won Tae Kim
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
- Department of Urology, Graduate School of Medicine, Yonsei University, Seoul, Korea
| | - Seok Joong Yun
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Chunri Yan
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Pildu Jeong
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Ye Hwan Kim
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Il Seok Lee
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Ho Won Kang
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Sunghyouk Park
- College of Pharmacy, Natural Product Research Institute, Seoul National University, Seoul, Korea
| | - Sung Kwon Moon
- School of Food Science and Technology, Chung-Ang University, Anseong, Korea
| | - Yung Hyun Choi
- Department of Biochemistry, Dongeui University College of Oriental Medicine, Busan, Korea
| | - Young Deuk Choi
- Department of Urology, Graduate School of Medicine, Yonsei University, Seoul, Korea
| | - Isaac Yi Kim
- Section of Urological Oncology, The Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Jayoung Kim
- Department of Surgery, Harvard Medical School, Boston, MA, USA.
- Cancer Biology Division, Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Wun Jae Kim
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea.
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Fan L, Yin M, Ke C, Ge T, Zhang G, Zhang W, Zhou X, Lou G, Li K. Use of Plasma Metabolomics to Identify Diagnostic Biomarkers for Early Stage Epithelial Ovarian Cancer. J Cancer 2016; 7:1265-72. [PMID: 27390602 PMCID: PMC4934035 DOI: 10.7150/jca.15074] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 04/26/2016] [Indexed: 12/12/2022] Open
Abstract
The early detection of ovarian carcinoma is difficult due to the absence of recognizable physical symptoms and a lack of sensitive screening methods. The currently available biomarkers (such as CA125 and HE4) are insufficiently reliable to distinguish early stage (I/II) epithelial ovarian cancer (EOC) patients from normal individuals because they possess a relatively poor sensitivity and specificity. To evaluate the application of metabolomics to biomarker discovery in the early stages of epithelial ovarian cancer (EOC), plasma samples from 21 early stage EOC patients and 31 healthy controls were analyzed with ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-Tof/MS) in conjunction with multivariate statistical analysis. Eighteen metabolites, including lysophospholipids, 2-piperidone and MG (18:2), were found to be disturbed in early stage EOC with satisfactory diagnostic accuracy (AUC=0.920). These biomarkers were specifically validated in the EOC nude mouse model, and five of the biomarkers (lysophospholipids, adrenoyl ethanolamide et al.) were highly suspected of being associated with EOC because they were differentially expressed with the same tendency in the EOC nude mice versus normal controls. In conclusion, the selected metabolic biomarkers have considerable utility and significant potential for diagnosing early ovarian cancer and investigating its underlying mechanisms.
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Affiliation(s)
- Lijun Fan
- 1. National Center for Endemic Disease Control, Harbin Medical University, Harbin, China;; 2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
| | - Mingzhu Yin
- 3. Department of Gynecology Oncology, The Third Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chaofu Ke
- 2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
| | - Tingting Ge
- 3. Department of Gynecology Oncology, The Third Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Guangming Zhang
- 2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
| | - Wang Zhang
- 2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
| | - Xiaohua Zhou
- 4. Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Seattle, USA
| | - Ge Lou
- 3. Department of Gynecology Oncology, The Third Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Kang Li
- 2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
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Turkoglu O, Zeb A, Graham S, Szyperski T, Szender JB, Odunsi K, Bahado-Singh R. Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature. Metabolomics 2016; 12:60. [PMID: 28819352 PMCID: PMC5557039 DOI: 10.1007/s11306-016-0990-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
INTRODUCTION Metabolomics is the emerging member of "omics" sciences advancing the understanding, diagnosis and treatment of many cancers, including ovarian cancer (OC). OBJECTIVES To systematically identify the metabolomic abnormalities in OC detection, and the dominant metabolic pathways associated with the observed alterations. METHODS An electronic literature search was performed, up to and including January 15th 2016, for studies evaluating the metabolomic profile of patients with OC compared to controls. QUADOMICS tool was used to assess the quality of the twenty-three studies included in this systematic review. RESULTS Biological samples utilized for metabolomic analysis include: serum/plasma (n = 13), urine (n = 4), cyst fluid (n = 3), tissue (n = 2) and ascitic fluid (n = 1). Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in OC. Increased levels of tricarboxylic acid cycle intermediates and altered metabolites of the glycolytic pathway pointed to perturbations in cellular respiration. Alterations in lipid metabolism included enhanced fatty acid oxidation, abnormal levels of glycerolipids, sphingolipids and free fatty acids with common elevations of palmitate, oleate, and myristate. Increased levels of glutamine, glycine, cysteine and threonine were commonly reported while enhanced degradations of tryptophan, histidine and phenylalanine were found. N-acetylaspartate, a brain amino acid, was found elevated in primary and metastatic OC tissue and ovarian cyst fluid. Further, elevated levels of ketone bodies including 3-hydroxybutyrate were commonly reported. Increased levels of nucleotide metabolites and tocopherols were consistent through out the studies. CONCLUSION Metabolomics presents significant new opportunities for diagnostic biomarker development, elucidating previously unknown mechanisms of OC pathogenesis.
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Affiliation(s)
- Onur Turkoglu
- Department of Obstetrics and Gynecology, Beaumont Hospital, 3601 W. 13 Mile Rd., Royal Oak, MI 48073, USA
| | - Amna Zeb
- Department of Obstetrics and Gynecology, Beaumont Hospital, 3601 W. 13 Mile Rd., Royal Oak, MI 48073, USA
| | - Stewart Graham
- Department of Obstetrics and Gynecology, Beaumont Hospital, 3601 W. 13 Mile Rd., Royal Oak, MI 48073, USA
| | - Thomas Szyperski
- Department of Chemistry, College of Arts and Sciences, University at Buffalo, Buffalo, NY, USA
| | - J Brian Szender
- Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Kunle Odunsi
- Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, USA
- Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Ray Bahado-Singh
- Department of Obstetrics and Gynecology, Beaumont Hospital, 3601 W. 13 Mile Rd., Royal Oak, MI 48073, USA
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Huang S, Chong N, Lewis NE, Jia W, Xie G, Garmire LX. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis. Genome Med 2016; 8:34. [PMID: 27036109 PMCID: PMC4818393 DOI: 10.1186/s13073-016-0289-9] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Accepted: 03/16/2016] [Indexed: 01/22/2023] Open
Abstract
Background More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. Methods We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0289-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sijia Huang
- Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa, Honolulu, HI, 96822, USA.,Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
| | - Nicole Chong
- Department of Microbiology, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, CA, 92093, USA.,Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego School of Medicine, San Diego, CA, 92093, USA
| | - Wei Jia
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
| | - Guoxiang Xie
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.
| | - Lana X Garmire
- Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa, Honolulu, HI, 96822, USA. .,Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.
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Hilvo M, de Santiago I, Gopalacharyulu P, Schmitt WD, Budczies J, Kuhberg M, Dietel M, Aittokallio T, Markowetz F, Denkert C, Sehouli J, Frezza C, Darb-Esfahani S, Braicu EI. Accumulated Metabolites of Hydroxybutyric Acid Serve as Diagnostic and Prognostic Biomarkers of Ovarian High-Grade Serous Carcinomas. Cancer Res 2016; 76:796-804. [PMID: 26685161 PMCID: PMC4762194 DOI: 10.1158/0008-5472.can-15-2298] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Accepted: 12/01/2015] [Indexed: 11/16/2022]
Abstract
Ovarian cancer is a heterogeneous disease of low prevalence, but poor survival. Early diagnosis is critical for survival, but it is often challenging because the symptoms of ovarian cancer are subtle and become apparent only during advanced stages of the disease. Therefore, the identification of robust biomarkers of early disease is a clinical priority. Metabolomic profiling is an emerging diagnostic tool enabling the detection of biomarkers reflecting alterations in tumor metabolism, a hallmark of cancer. In this study, we performed metabolomic profiling of serum and tumor tissue from 158 patients with high-grade serous ovarian cancer (HGSOC) and 100 control patients with benign or non-neoplastic lesions. We report metabolites of hydroxybutyric acid (HBA) as novel diagnostic and prognostic biomarkers associated with tumor burden and patient survival. The accumulation of HBA metabolites caused by HGSOC was also associated with reduced expression of succinic semialdehyde dehydrogenase (encoded by ALDH5A1), and with the presence of an epithelial-to-mesenchymal transition gene signature, implying a role for these metabolic alterations in cancer cell migration and invasion. In conclusion, our findings represent the first comprehensive metabolomics analysis in HGSOC and propose a new set of metabolites as biomarkers of disease with diagnostic and prognostic capabilities.
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Affiliation(s)
- Mika Hilvo
- VTT Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT, Espoo, Finland
| | - Ines de Santiago
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
| | | | | | - Jan Budczies
- Institute of Pathology, Charité University Hospital, 10117 Berlin, Germany
| | - Marc Kuhberg
- Department for Gynecology, Campus Virchow Clinic, Charité Medical University, Berlin
| | - Manfred Dietel
- Institute of Pathology, Charité University Hospital, 10117 Berlin, Germany
| | - Tero Aittokallio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Florian Markowetz
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
| | - Carsten Denkert
- Institute of Pathology, Charité University Hospital, 10117 Berlin, Germany
| | - Jalid Sehouli
- Department for Gynecology, Campus Virchow Clinic, Charité Medical University, Berlin
- On behalf of the Tumor Bank Ovarian Cancer Network (www.toc-network.de)
| | - Christian Frezza
- MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, UK
| | | | - Elena Ioana Braicu
- Department for Gynecology, Campus Virchow Clinic, Charité Medical University, Berlin
- On behalf of the Tumor Bank Ovarian Cancer Network (www.toc-network.de)
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Kyriakides M, Rama N, Sidhu J, Gabra H, Keun HC, El-Bahrawy M. Metabonomic analysis of ovarian tumour cyst fluid by proton nuclear magnetic resonance spectroscopy. Oncotarget 2016; 7:7216-26. [PMID: 26769844 PMCID: PMC4872780 DOI: 10.18632/oncotarget.6891] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Accepted: 12/30/2015] [Indexed: 12/20/2022] Open
Abstract
The majority of ovarian tumours are of the epithelial type, which can be sub classified as benign, borderline or malignant. Epithelial tumours usually have cystic spaces filled with cyst fluid, the metabolic profile of which reflects the metabolic activity of the tumour cells, due to their close proximity. The approach of metabonomics using 1H-NMR spectroscopy was employed to characterize the metabolic profiles of ovarian cyst fluid samples (n = 23) from benign, borderline and malignant ovarian tumours in order to shed more light into ovarian tumour and cancer development. The analysis revealed that citrate was elevated in benign versus malignant tumours, while the amino acid lysine was elevated in malignant versus non-malignant tumours, both at a 5% significance level. Choline and lactate also had progressively increasing levels from benign to borderline to malignant samples. Finally, hypoxanthine was detected exclusively in a sub-cohort of the malignant tumours. This metabonomic study demonstrates that ovarian cyst fluid samples have potential to be used to distinguish between the different types of ovarian epithelial tumours. Furthermore, the respective metabolic profiles contain mechanistic information which could help identify biomarkers and therapeutic targets for ovarian tumours.
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Affiliation(s)
- Michael Kyriakides
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Nona Rama
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Jasmin Sidhu
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Hani Gabra
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Hector C. Keun
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Mona El-Bahrawy
- Department of Histopathology, Hammersmith Hospital, Imperial College London, London, United Kingdom
- Department of Pathology, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
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Nagana Gowda GA, Raftery D. Can NMR solve some significant challenges in metabolomics? JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2015; 260:144-60. [PMID: 26476597 PMCID: PMC4646661 DOI: 10.1016/j.jmr.2015.07.014] [Citation(s) in RCA: 137] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2015] [Revised: 07/17/2015] [Accepted: 07/18/2015] [Indexed: 05/04/2023]
Abstract
The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.
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Affiliation(s)
- G A Nagana Gowda
- Northwest Metabolomics Research Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, United States; Department of Chemistry, University of Washington, Seattle, WA 98195, United States; Fred Hutchinson Cancer Research Center, Seattle, WA 98109, United States.
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36
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Buas MF, Gu H, Djukovic D, Zhu J, Drescher CW, Urban N, Raftery D, Li CI. Identification of novel candidate plasma metabolite biomarkers for distinguishing serous ovarian carcinoma and benign serous ovarian tumors. Gynecol Oncol 2015; 140:138-44. [PMID: 26521694 DOI: 10.1016/j.ygyno.2015.10.021] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 10/23/2015] [Accepted: 10/29/2015] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Serous ovarian carcinoma (OC) represents a leading cause of cancer-related death among U.S. women. Non-invasive tools have recently emerged for discriminating benign from malignant ovarian masses, but evaluation remains ongoing, without widespread implementation. In the last decade, metabolomics has matured into a new avenue for cancer biomarker development. Here, we sought to identify novel plasma metabolite biomarkers to distinguish serous ovarian carcinoma and benign serous ovarian tumor. METHODS Using liquid chromatography-mass spectrometry, we conducted global and targeted metabolite profiling of plasma isolated at the time of surgery from 50 serous OC cases and 50 serous benign controls. RESULTS Global lipidomics analysis identified 34 metabolites (of 372 assessed) differing significantly (P<0.05) between cases and controls in both training and testing sets, with 17 candidates satisfying FDR q<0.05, and two reaching Bonferroni significance. Targeted profiling of ~150 aqueous metabolites identified a single amino acid, alanine, as differentially abundant (P<0.05). A multivariate classification model built using the top four lipid metabolites achieved an estimated AUC of 0.85 (SD=0.07) based on Monte Carlo cross validation. Evaluation of a hybrid model incorporating both CA125 and lipid metabolites was suggestive of increased classification accuracy (AUC=0.91, SD=0.05) relative to CA125 alone (AUC=0.87, SD=0.07), particularly at high fixed levels of sensitivity, without reaching significance. CONCLUSIONS Our results provide insight into metabolic changes potentially correlated with the presence of serous OC versus benign ovarian tumor and suggest that plasma metabolites may help differentiate these two conditions.
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Affiliation(s)
- Matthew F Buas
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Haiwei Gu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA
| | - Danijel Djukovic
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA
| | - Jiangjiang Zhu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA
| | - Charles W Drescher
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Nicole Urban
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Daniel Raftery
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA; Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA.
| | - Christopher I Li
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA.
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Yang Y, Liu Y, Zheng L, Zhang Q, Gu Q, Wang L, Wang L. ¹H NMR based serum metabolic profiles associated with pathological progression of pancreatic islet β cell tumor in Rip1-Tag2 mice. Int J Biol Sci 2015; 11:595-603. [PMID: 25892966 PMCID: PMC4400390 DOI: 10.7150/ijbs.11058] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 02/28/2015] [Indexed: 01/19/2023] Open
Abstract
Pancreatic islet β cell tumor is the most common islet cell tumor. A well-characterized tumor progression in Rip1-Tag2 mice undergoes five stages, involving normal, hyperplasia, angiogenic islets, tumorigenesis and invasive carcinoma. (1)H NMR based metabonomics was applied to identify potential biomarkers for monitoring pancreatic islet β cell tumor progression in Rip1-Tag2 mice. Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells. At angiogenic islets stage, the up-regulated glycolysis, disturbed choline and phospholipid metabolism composed the metabolic signature. In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism. All the changes were aggravated at invasive carcinoma stage, coupled with notable changes in alanine, glutamate and glycine. Moreover, the distinct metabolic phenotype was found associated with the implanting of SV40 large T antigen in Rip1-Tag2 mice. The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.
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Affiliation(s)
- Yongxia Yang
- 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China ; 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Ying Liu
- 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China ; 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Lingyun Zheng
- 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Qianqian Zhang
- 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Quliang Gu
- 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Linlin Wang
- 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
| | - Lijing Wang
- 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China
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Jin X, Yun SJ, Jeong P, Kim IY, Kim WJ, Park S. Diagnosis of bladder cancer and prediction of survival by urinary metabolomics. Oncotarget 2015; 5:1635-45. [PMID: 24721970 PMCID: PMC4039236 DOI: 10.18632/oncotarget.1744] [Citation(s) in RCA: 104] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Bladder cancer (BC) is a common cancer but diagnostic modalities, such as cystoscopy and urinary cytology, have limitations. Here, high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOFMS) was used to profile urine metabolites of 138 patients with BC and 121 control subjects (69 healthy people and 52 patients with hematuria due to non-malignant diseases). Multivariate statistical analysis revealed that the cancer group could be clearly distinguished from the control groups on the basis of their metabolomic profiles, even when the hematuric control group was included. Patients with muscle-invasive BC could also be distinguished from patients with non-muscle-invasive BC on the basis of their metabolomic profiles. Successive analyses identified 12 differential metabolites that contributed to the distinction between the BC and control groups, and many of them turned out to be involved in glycolysis and betaoxidation. The association of these metabolites with cancer was corroborated by microarray results showing that carnitine transferase and pyruvate dehydrogenase complex expressions are significantly altered in cancer groups. In terms of clinical applicability, the differentiation model diagnosed BC with a sensitivity and specificity of 91.3% and 92.5%, respectively, and comparable results were obtained by receiver operating characteristic analysis (AUC = 0.937). Multivariate regression also suggested that the metabolomic profile correlates with cancer-specific survival time. The excellent performance and simplicity of this metabolomics-based approach suggests that it has the potential to augment or even replace the current modalities for BC diagnosis.
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Affiliation(s)
- Xing Jin
- College of Pharmacy, Natural Product Research Institute, Seoul National University, Sillim-dong, Gwanak-gu, Seoul, 151-724, Korea
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Jones CM, Monge ME, Kim J, Matzuk MM, Fernández FM. Metabolomic Serum Profiling Detects Early-Stage High-Grade Serous Ovarian Cancer in a Mouse Model. J Proteome Res 2015; 14:917-27. [DOI: 10.1021/pr5009948] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Christina M. Jones
- School of Chemistry & Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332, United States
| | - María Eugenia Monge
- School of Chemistry & Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332, United States
| | | | | | - Facundo M. Fernández
- School of Chemistry & Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332, United States
- Institute
of Bioengineering and Biosciences, Georgia Institute of Technology, 315 Ferst Drive, Atlanta, Georgia 30332, United States
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Halama A. Metabolomics in cell culture--a strategy to study crucial metabolic pathways in cancer development and the response to treatment. Arch Biochem Biophys 2014; 564:100-9. [PMID: 25218088 DOI: 10.1016/j.abb.2014.09.002] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Revised: 09/01/2014] [Accepted: 09/02/2014] [Indexed: 12/11/2022]
Abstract
Metabolomics is a comprehensive tool for monitoring processes within biological systems. Thus, metabolomics may be widely applied to the determination of diagnostic biomarkers for certain diseases or treatment outcomes. There is significant potential for metabolomics to be implemented in cancer research because cancer may modify metabolic pathways in the whole organism. However, not all biological questions can be answered solely by the examination of small molecule composition in biofluids; in particular, the study of cellular processes or preclinical drug testing requires ex vivo models. The major objective of this review was to summarise the current achievement in the field of metabolomics in cancer cell culture-focusing on the metabolic pathways regulated in different cancer cell lines-and progress that has been made in the area of drug screening and development by the implementation of metabolomics in cell lines.
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Affiliation(s)
- Anna Halama
- Department of Physiology and Biophysics, Weill Cornell Medical College-Qatar, Doha, Qatar.
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Ke C, Hou Y, Zhang H, Fan L, Ge T, Guo B, Zhang F, Yang K, Wang J, Lou G, Li K. Large-scale profiling of metabolic dysregulation in ovarian cancer. Int J Cancer 2014; 136:516-26. [PMID: 24895217 DOI: 10.1002/ijc.29010] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2014] [Accepted: 05/26/2014] [Indexed: 01/21/2023]
Abstract
Ovarian cancer is the leading cause of death in gynecologic malignancies. Profiling of endogenous metabolites has potential to identify changes caused by cancer and provide inspiring insights into cancer metabolism. To systematically investigate ovarian cancer metabolism, we performed metabolic profiling of 448 plasma samples related to epithelial ovarian cancer (EOC) based on ultra-performance liquid chromatography mass spectrometry in both positive and negative modes. These unbiased metabolomic profiles could well distinguish EOC from benign ovarian tumor (BOT) and uterine fibroid (UF). Fifty-three metabolites were identified as specific biomarkers for EOC, and this is the first report of piperine, 3-indolepropionic acid, 5-hydroxyindoleacetaldehyde and hydroxyphenyllactate as metabolic biomarkers of EOC. The AUC values of these metabolites for discriminating EOC from BOT/UF and early-stage EOC from BOT/UF were 0.9100/0.9428 and 0.8385/0.8624, respectively. Meanwhile, our metabolites were able to distinguish early-stage EOC from late-stage EOC with an AUC of 0.8801. Importantly, analysis of dysregulated metabolic pathways extends our current understanding of EOC metabolism. Metabolic pathways in EOC patients are mainly characterized by abnormal phospholipid metabolism, altered l-tryptophan catabolism, aggressive fatty acid β-oxidation and aberrant metabolism of piperidine derivatives. Together, these metabolic pathways provide a foundation to support cancer development and progression. In conclusion, our large-scale plasma metabolomics study yielded fundamental insights into dysregulated metabolism in ovarian cancer, which could facilitate clinical diagnosis, therapy, prognosis and shed new lights on ovarian cancer pathogenesis.
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Affiliation(s)
- Chaofu Ke
- Department of Epidemiology and Biostatistics, Public Health School, Harbin Medical University, Harbin, People's Republic of China
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Duarte IF, Diaz SO, Gil AM. NMR metabolomics of human blood and urine in disease research. J Pharm Biomed Anal 2014; 93:17-26. [DOI: 10.1016/j.jpba.2013.09.025] [Citation(s) in RCA: 82] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 09/16/2013] [Accepted: 09/24/2013] [Indexed: 02/06/2023]
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Nagana Gowda G, Raftery D. Advances in NMR-Based Metabolomics. FUNDAMENTALS OF ADVANCED OMICS TECHNOLOGIES: FROM GENES TO METABOLITES 2014. [DOI: 10.1016/b978-0-444-62651-6.00008-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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Bouhifd M, Hartung T, Hogberg HT, Kleensang A, Zhao L. Review: toxicometabolomics. J Appl Toxicol 2013; 33:1365-83. [PMID: 23722930 PMCID: PMC3808515 DOI: 10.1002/jat.2874] [Citation(s) in RCA: 118] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2012] [Revised: 02/10/2013] [Accepted: 02/11/2013] [Indexed: 12/19/2022]
Abstract
Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context.
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Affiliation(s)
| | - Thomas Hartung
- Correspondence to: T. Hartung, Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Chair for Evidence-based Toxicology, Center for Alternatives to Animal Testing, 615 N. Wolfe St., Baltimore, MD, 21205, USA.
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Vettukattil R, Hetland TE, Flørenes VA, Kærn J, Davidson B, Bathen TF. Proton magnetic resonance metabolomic characterization of ovarian serous carcinoma effusions: chemotherapy-related effects and comparison with malignant mesothelioma and breast carcinoma. Hum Pathol 2013; 44:1859-66. [DOI: 10.1016/j.humpath.2013.02.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2012] [Revised: 02/09/2013] [Accepted: 02/11/2013] [Indexed: 10/26/2022]
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46
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Yu L, Jiang C, Huang S, Gong X, Wang S, Shen P. Analysis of urinary metabolites for breast cancer patients receiving chemotherapy by CE-MS coupled with on-line concentration. Clin Biochem 2013; 46:1065-1073. [DOI: 10.1016/j.clinbiochem.2013.05.049] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2013] [Revised: 05/13/2013] [Accepted: 05/15/2013] [Indexed: 11/24/2022]
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47
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1H NMR-based spectroscopy detects metabolic alterations in serum of patients with early-stage ulcerative colitis. Biochem Biophys Res Commun 2013; 433:547-51. [PMID: 23510994 DOI: 10.1016/j.bbrc.2013.03.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 03/10/2013] [Indexed: 12/11/2022]
Abstract
Ulcerative colitis (UC) has seriously impaired the health of citizens. Accurate diagnosis of UC at an early stage is crucial to improve the efficiency of treatment and prognosis. In this study, proton nuclear magnetic resonance (1H NMR)-based metabolomic analysis was performed on serum samples collected from active UC patients (n=20) and healthy controls (n=19), respectively. The obtained spectral profiles were subjected to multivariate data analysis. Our results showed that consistent metabolic alterations were present between the two groups. Compared to healthy controls, UC patients displayed increased 3-hydroxybutyrate, β-glucose, α-glucose, and phenylalanine, but decreased lipid in serum. These findings highlight the possibilities of NMR-based metabolomics as a non-invasive diagnostic tool for UC.
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48
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Chen K, Gentry-Maharaj A, Burnell M, Steentoft C, Marcos-Silva L, Mandel U, Jacobs I, Dawnay A, Menon U, Blixt O. Microarray Glycoprofiling of CA125 improves differential diagnosis of ovarian cancer. J Proteome Res 2013; 12:1408-18. [PMID: 23360124 DOI: 10.1021/pr3010474] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The CA125 biomarker assay plays an important role in the diagnosis and management of primary invasive epithelial ovarian/tubal cancer (iEOC). However, a fundamental problem with CA125 is that it is not cancer-specific and may be elevated in benign gynecological conditions such as benign ovarian neoplasms and endometriosis. Aberrant O-glycosylation is an inherent and specific property of cancer cells and could potentially aid in differentiating cancer from these benign conditions, thereby improving specificity of the assay. We report on the development of a novel microarray-based platform for profiling specific aberrant glycoforms, such as Neu5Acα2,6GalNAc (STn) and GalNAc (Tn), present on CA125 (MUC16) and CA15-3 (MUC1). In a blinded cohort study of patients with an elevated CA125 levels (30-500 kU/L) and a pelvic mass from the UK Ovarian Cancer Population Study (UKOPS), we measured STn-CA125, ST-CA125 and STn-CA15-3. The combined glycoform profile was able to distinguish benign ovarian neoplasms from invasive epithelial ovarian/tubule cancer (iEOCs) with a specificity of 61.1% at 90% sensitivity. The findings suggest that microarray glycoprofiling could improve differential diagnosis and significantly reduce the number of patients elected for further testing. The approach warrants further investigation in other cancers.
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Affiliation(s)
- Kowa Chen
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
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49
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Zhang T, Wu X, Ke C, Yin M, Li Z, Fan L, Zhang W, Zhang H, Zhao F, Zhou X, Lou G, Li K. Identification of potential biomarkers for ovarian cancer by urinary metabolomic profiling. J Proteome Res 2012; 12:505-12. [PMID: 23163809 DOI: 10.1021/pr3009572] [Citation(s) in RCA: 130] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
To evaluate the application of urinary metabolomics on discovering potential biomarkers for epithelial ovarian cancer (EOC), urine samples from 40 preoperative EOC patients, 62 benign ovarian tumor (BOT) patients, and 54 healthy controls were collected and analyzed with ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). Good separations were obtained for EOC vs BOT, EOC vs healthy controls analyzed by partial least-squares discriminant analysis, or principal component analysis. Twenty-two ascertained metabolomic biomarkers were found to be disturbed in several metabolic pathways among EOC patients, including nucleotide metabolism (pseudouridine, N4-acetylcytidine), histidine metabolism (L-histidine, imidazol-5-yl-pyruvate), tryptophan metabolism (3-indolelactic acid), and mucin metabolism (3'-sialyllactose and 3-sialyl-N-acetyllactosamine). In addition, the concentrations of some urinary metabolites of 18 postoperative EOC patients among the 40 EOC patients changed significantly compared with those of their preoperative condition, and four of them suggested recovery tendency toward normal level after surgical operation, including N4-acetylcytidine, pseudouridine, urate-3-ribonucleoside, and succinic acid. These metabolites would be highly postulated to be associated with EOC. In conclusion, our study demonstrated that urinary metabolomics analysis by UPLC-QTOF/MS, performed in a minimally noninvasive and convenient manner, possessed great potential in biomarker discovery for EOC.
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Affiliation(s)
- Tao Zhang
- Department of Epidemiology and Biostatistics, Public Health School, Harbin Medical University, Harbin, PR China
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50
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Nicholson JK, Holmes E, Kinross JM, Darzi AW, Takats Z, Lindon JC. Metabolic phenotyping in clinical and surgical environments. Nature 2012; 491:384-92. [PMID: 23151581 DOI: 10.1038/nature11708] [Citation(s) in RCA: 355] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Metabolic phenotyping involves the comprehensive analysis of biological fluids or tissue samples. This analysis allows biochemical classification of a person's physiological or pathological states that relate to disease diagnosis or prognosis at the individual level and to disease risk factors at the population level. These approaches are currently being implemented in hospital environments and in regional phenotyping centres worldwide. The ultimate aim of such work is to generate information on patient biology using techniques such as patient stratification to better inform clinicians on factors that will enhance diagnosis or the choice of therapy. There have been many reports of direct applications of metabolic phenotyping in a clinical setting.
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Affiliation(s)
- Jeremy K Nicholson
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, South Kensington, London SW7 2AZ, UK.
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