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Wu HC, Lai Y, Liao Y, Deyssenroth M, Miller GW, Santella RM, Terry MB. Plasma metabolomics profiles and breast cancer risk. Breast Cancer Res 2024; 26:141. [PMID: 39385226 PMCID: PMC11463119 DOI: 10.1186/s13058-024-01896-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 09/18/2024] [Indexed: 10/12/2024] Open
Abstract
BACKGROUND Breast cancer (BC) is the most common cancer in women and incidence rates are increasing; metabolomics may be a promising approach for identifying the drivers of the increasing trends that cannot be explained by changes in known BC risk factors. METHODS We conducted a nested case-control study (median followup 6.3 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 40 cases and 70 age-matched controls). We conducted a metabolome-wide association study using untargeted metabolomics coupling hydrophilic interaction liquid chromatography (HILIC) and C18 chromatography with high-resolution mass spectrometry (LC-HRMS) to identify BC-related metabolic features. RESULTS We found eight metabolic features associated with BC risk. For the four metabolites negatively associated with risk, the adjusted odds ratios (ORs) ranged from 0.31 (95% confidence interval (CI): 0.14, 0.66) (L-Histidine) to 0.65 (95% CI: 0.43, 0.98) (N-Acetylgalactosamine), and for the four metabolites positively associated with risk, ORs ranged from 1.61 (95% CI: 1.04, 2.51, (m/z: 101.5813, RT: 90.4, 1,3-dibutyl-1-nitrosourea, a potential carcinogen)) to 2.20 (95% CI: 1.15, 4.23) (11-cis-Eicosenic acid). These results were no longer statistically significant after adjusting for multiple comparisons. Adding the BC-related metabolic features to a model, including age, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk score improved the accuracy of BC prediction from an area under the curve (AUC) of 66% to 83%. CONCLUSIONS If replicated in larger prospective cohorts, these findings offer promising new ways to identify exposures related to BC and improve BC risk prediction.
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Affiliation(s)
- Hui-Chen Wu
- Department of Environmental Health Sciences, Mailman School of Public Health of Columbia University, New York, NY, 10032, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.
| | - Yunjia Lai
- Department of Environmental Health Sciences, Mailman School of Public Health of Columbia University, New York, NY, 10032, USA
| | - Yuyan Liao
- Department of Epidemiology, Mailman School of Public Health of Columbia University, New York, NY, USA
| | - Maya Deyssenroth
- Department of Environmental Health Sciences, Mailman School of Public Health of Columbia University, New York, NY, 10032, USA
| | - Gary W Miller
- Department of Environmental Health Sciences, Mailman School of Public Health of Columbia University, New York, NY, 10032, USA
| | - Regina M Santella
- Department of Environmental Health Sciences, Mailman School of Public Health of Columbia University, New York, NY, 10032, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Mary Beth Terry
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health of Columbia University, New York, NY, USA
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2
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Thodi G, Triantopoulou A, Iliou A, Molou E, Dotsikas Y, Loukas YL. A simplified metabolomic analysis of dried blood spots in breast cancer patients. Scand J Clin Lab Invest 2024; 84:326-335. [PMID: 39225029 DOI: 10.1080/00365513.2024.2392241] [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: 04/30/2024] [Revised: 07/21/2024] [Accepted: 08/11/2024] [Indexed: 09/04/2024]
Abstract
Breast cancer (BC) is among the most commonly diagnosed cancers. Besides mammography, breast ultrasonography and the routinely monitored protein markers, the variations of small molecular metabolites in blood may be of great diagnostic value. This study aimed to quantify specific metabolite markers with potential application in BC detection. The study enrolled 50 participants, 25 BC patients and 25 healthy controls (CTRL). Dried blood spots (DBS) were utilized as biological media and were quantified via a simplified liquid chromatography tandem mass spectrometry (LC-MS/MS) method, used in expanded newborn screening. The targeted metabolomic analysis included 12 amino acids and 32 acylcarnitines. Statistical analysis revealed a significant variation of metabolic profiles between BC patients and CTRL. Among the 44 metabolites, 18 acylcarnitines and 10 amino acids remained significant after Bonferroni correction, showing increase or decrease and enabled classification of BC patients and CTRL. The well-established LC-MS/MS protocol could provide results within few minutes. Therefore, the combination of an easy-to-handle material-DBS and LC-MS/MS protocol could facilitate BC screening/diagnosis and in the next step applied to other cancer patients, as well.
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Affiliation(s)
| | - Aikaterini Triantopoulou
- Laboratory of Pharmaceutical Analysis, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Aikaterini Iliou
- Laboratory of Pharmaceutical Analysis, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Elina Molou
- Neoscreen Diagnostic Laboratory, Athens, Greece
| | - Yannis Dotsikas
- Laboratory of Pharmaceutical Analysis, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Yannis L Loukas
- Laboratory of Pharmaceutical Analysis, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
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3
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Talarico MCR, Derchain S, da Silva LF, Sforça ML, Rocco SA, Cardoso MR, Sarian LO. Metabolomic Profiling of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy for Predicting Disease-Free and Overall Survival. Int J Mol Sci 2024; 25:8639. [PMID: 39201325 PMCID: PMC11354796 DOI: 10.3390/ijms25168639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 08/04/2024] [Accepted: 08/06/2024] [Indexed: 09/02/2024] Open
Abstract
Breast cancer (BC) remains a significant global health concern, with neoadjuvant chemotherapy (NACT) offering preoperative benefits like tumor downstaging and treatment response assessment. However, identifying factors influencing post-NACT treatment response and survival outcomes is challenging. Metabolomic approaches offer promising insights into understanding these outcomes. This study analyzed the serum of 80 BC patients before and after NACT, followed for up to five years, correlating with disease-free survival (DFS) and overall survival (OS). Using untargeted nuclear magnetic resonance (NMR) spectroscopy and a novel statistical model that avoids collinearity issues, we identified metabolic changes associated with survival outcomes. Four metabolites (histidine, lactate, serine, and taurine) were significantly associated with DFS. We developed a metabolite-related survival score (MRSS) from these metabolites, stratifying patients into low- and high-risk relapse groups, independent of classical prognostic factors. High-risk patients had a hazard ratio (HR) for DFS of 3.42 (95% CI 1.51-7.74; p = 0.003) after adjustment for disease stage and age. A similar trend was observed for OS (HR of 3.34, 95% CI 1.64-6.80; p < 0.001). Multivariate Cox proportional hazards analysis confirmed the independent prognostic value of the MRSS. Our findings suggest the potential of metabolomic data, alongside traditional markers, in guiding personalized treatment decisions and risk stratification in BC patients undergoing NACT. This study provides a methodological framework for leveraging metabolomics in survival analyses.
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Affiliation(s)
- Maria Cecília Ramiro Talarico
- Department of Obstetrics and Gynecology, Division of Gynecologic and Breast Oncology, School of Medical Sciences, University of Campinas (UNICAMP-Universidade Estadual de Campinas), Campinas 13083-881, SP, Brazil
| | - Sophie Derchain
- Department of Obstetrics and Gynecology, Division of Gynecologic and Breast Oncology, School of Medical Sciences, University of Campinas (UNICAMP-Universidade Estadual de Campinas), Campinas 13083-881, SP, Brazil
| | | | - Maurício L. Sforça
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, SP, Brazil
| | - Silvana A. Rocco
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, SP, Brazil
| | - Marcella R. Cardoso
- Division of Gynecologic Oncology-MGH Global Disaster Response, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Center for Global Health, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Luís Otávio Sarian
- Department of Obstetrics and Gynecology, Division of Gynecologic and Breast Oncology, School of Medical Sciences, University of Campinas (UNICAMP-Universidade Estadual de Campinas), Campinas 13083-881, SP, Brazil
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4
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Bauer BA, Schmidt CM, Ruddy KJ, Olson JE, Meydan C, Schmidt JC, Smith SY, Couch FJ, Earls JC, Price ND, Dudley JT, Mason CE, Zhang B, Phipps SM, Schmidt MA. A Multiomics, Molecular Atlas of Breast Cancer Survivors. Metabolites 2024; 14:396. [PMID: 39057719 PMCID: PMC11279123 DOI: 10.3390/metabo14070396] [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: 06/02/2024] [Revised: 07/09/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims.
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Affiliation(s)
| | - Caleb M. Schmidt
- Sovaris Aerospace, Boulder, CO 80302, USA
- Advanced Pattern Analysis and Human Performance Group, Boulder, CO 80302, USA
| | | | | | - Cem Meydan
- Thorne Research, Inc., Summerville, SC 29483, USA
| | - Julian C. Schmidt
- Sovaris Aerospace, Boulder, CO 80302, USA
- Advanced Pattern Analysis and Human Performance Group, Boulder, CO 80302, USA
| | | | | | | | - Nathan D. Price
- Thorne Research, Inc., Summerville, SC 29483, USA
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | | | | | - Bodi Zhang
- Thorne Research, Inc., Summerville, SC 29483, USA
| | | | - Michael A. Schmidt
- Sovaris Aerospace, Boulder, CO 80302, USA
- Advanced Pattern Analysis and Human Performance Group, Boulder, CO 80302, USA
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5
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Yang PJ, Tsai EM, Hou MF, Lee YJ, Wang TN. Global untargeted and individual targeted plasma metabolomics of breast cancer recurrence modified by hormone receptors. Breast Cancer 2024; 31:659-670. [PMID: 38652345 DOI: 10.1007/s12282-024-01579-1] [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: 12/17/2023] [Accepted: 03/26/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis. METHODS We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case-control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model. RESULTS In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18-0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant. CONCLUSION Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis.
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Affiliation(s)
- Pei-Jing Yang
- Department of Public Health, College of Health Science, Kaohsiung Medical University, No. 100, Shin-Chuan 1St Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Eing-Mei Tsai
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
- Department of Obstetrics and Gynecology, Kaohsiung Medical University Chung-Ho Memorial Hospital, No.100, Tzyou 1st Road, Sanmin Dist., Kaohsiung, 80756, Taiwan
| | - Ming-Feng Hou
- Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Chung-Ho Memorial Hospital, No.100, Tzyou 1st Road, Sanmin Dist., Kaohsiung, 80756, Taiwan
- Department of Biomedical Science and Environmental Biology, College of Life Science, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Yen-Jung Lee
- Center for Research Resources and Development, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Tsu-Nai Wang
- Department of Public Health, College of Health Science, Kaohsiung Medical University, No. 100, Shin-Chuan 1St Road, Sanmin Dist., Kaohsiung, 80708, Taiwan.
- Research Center for Environmental Medicine, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan.
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6
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Marlin S, Goepp M, Desiderio A, Rougé S, Aldekwer S, Le Guennec D, Goncalves-Mendes N, Talvas J, Farges MC, Rossary A. Long-Term High-Fat Diet Limits the Protective Effect of Spontaneous Physical Activity on Mammary Carcinogenesis. Int J Mol Sci 2024; 25:6221. [PMID: 38892407 PMCID: PMC11172547 DOI: 10.3390/ijms25116221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/31/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024] Open
Abstract
Breast cancer is influenced by factors such as diet, a sedentary lifestyle, obesity, and postmenopausal status, which are all linked to prolonged hormonal and inflammatory exposure. Physical activity offers protection against breast cancer by modulating hormones, immune responses, and oxidative defenses. This study aimed to assess how a prolonged high-fat diet (HFD) affects the effectiveness of physical activity in preventing and managing mammary tumorigenesis. Ovariectomised C57BL/6 mice were provided with an enriched environment to induce spontaneous physical activity while being fed HFD. After 44 days (short-term, ST HFD) or 88 days (long-term, LT HFD), syngenic EO771 cells were implanted into mammary glands, and tumour growth was monitored until sacrifice. Despite similar physical activity and food intake, the LT HFD group exhibited higher visceral adipose tissue mass and reduced skeletal muscle mass. In the tumour microenvironment, the LT HFD group showed decreased NK cells and TCD8+ cells, with a trend toward increased T regulatory cells, leading to a collapse of the T8/Treg ratio. Additionally, the LT HFD group displayed decreased tumour triglyceride content and altered enzyme activities indicative of oxidative stress. Prolonged exposure to HFD was associated with tumour growth despite elevated physical activity, promoting a tolerogenic tumour microenvironment. Future studies should explore inter-organ exchanges between tumour and tissues.
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MESH Headings
- Animals
- Diet, High-Fat/adverse effects
- Female
- Mice
- Mice, Inbred C57BL
- Physical Conditioning, Animal
- Tumor Microenvironment
- Oxidative Stress
- Carcinogenesis
- Mammary Neoplasms, Experimental/pathology
- Mammary Neoplasms, Experimental/metabolism
- Mammary Neoplasms, Experimental/prevention & control
- Cell Line, Tumor
- Mammary Neoplasms, Animal/pathology
- Mammary Neoplasms, Animal/metabolism
- Mammary Neoplasms, Animal/prevention & control
- Intra-Abdominal Fat/metabolism
- Killer Cells, Natural/immunology
- Killer Cells, Natural/metabolism
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Affiliation(s)
- Sébastien Marlin
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Marie Goepp
- Resolution Therapeutics, University of Edinburgh, Edinburgh EH16 4UU, UK
| | - Adrien Desiderio
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Stéphanie Rougé
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Sahar Aldekwer
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Delphine Le Guennec
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Nicolas Goncalves-Mendes
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Jérémie Talvas
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Marie-Chantal Farges
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
| | - Adrien Rossary
- UNH—Unité de Nutrition Humaine, CRNH-Auvergne, Université Clermont-Auvergne, INRAe, F-63000 Clermont-Ferrand, France; (S.M.); (A.D.); (S.R.); (S.A.); (D.L.G.); (N.G.-M.); (J.T.)
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Samuels E, Parks J, Chu J, McDonald T, Spinelli J, Murphy RA, Bhatti P. Metabolites Associated with Polygenic Risk of Breast Cancer. Metabolites 2024; 14:295. [PMID: 38921430 PMCID: PMC11205321 DOI: 10.3390/metabo14060295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 05/11/2024] [Accepted: 05/20/2024] [Indexed: 06/27/2024] Open
Abstract
While hundreds of germline genetic variants have been associated with breast cancer risk, the mechanisms underlying the impacts of most of these variants on breast cancer remain uncertain. Metabolomics may offer valuable insights into the mechanisms underlying genetic risks of breast cancer. Among 143 cancer-free female participants, we used linear regression analyses to explore associations between the genetic risk of breast cancer, as determined by a previously developed polygenic risk score (PRS) that included 266 single-nucleotide polymorphisms (SNPs), and 223 measures of metabolites obtained from blood samples using nuclear magnetic resonance (NMR). A false discovery rate of 10% was applied to account for multiple comparisons. PRS was statistically significantly associated with 45 metabolite measures. These were primarily measures of very low-density lipoproteins (VLDLs) and high-density lipoproteins (HDLs), including triglycerides, cholesterol, and phospholipids. For example, the strongest effect was observed with the percent ratio of medium VLDL triglycerides to total lipids (0.53 unit increase in mean-standardized ln-transformed percent ratio per unit increase in PRS; q = 0.1). While larger-scale studies are needed to confirm these results, this exploratory study presents biologically plausible findings that are consistent with previously reported associations between lipids and breast cancer risk. If confirmed, these lipids could be targeted for lifestyle and pharmaceutical interventions among women at increased genetic risk of breast cancer.
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Affiliation(s)
- Elizabeth Samuels
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Jaclyn Parks
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
| | - Jessica Chu
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
| | - Treena McDonald
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
| | - John Spinelli
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Rachel A. Murphy
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
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8
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Zniber M, Lamminen T, Taimen P, Boström PJ, Huynh TP. 1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia. Heliyon 2024; 10:e28949. [PMID: 38617934 PMCID: PMC11015411 DOI: 10.1016/j.heliyon.2024.e28949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/27/2024] [Accepted: 03/27/2024] [Indexed: 04/16/2024] Open
Abstract
Background Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies. Significance This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies. Results The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.
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Affiliation(s)
- Mohammed Zniber
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
| | - Tarja Lamminen
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Pekka Taimen
- Institute of Biomedicine and FICAN West Cancer Centre, University of Turku and Department of Pathology, Turku University Hospital, Turku, Finland
| | - Peter J. Boström
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Tan-Phat Huynh
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
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9
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De Mario A, Trevellin E, Piazza I, Vindigni V, Foletto M, Rizzuto R, Vettor R, Mammucari C. Mitochondrial Ca 2+ signaling is a hallmark of specific adipose tissue-cancer crosstalk. Sci Rep 2024; 14:8469. [PMID: 38605098 PMCID: PMC11009327 DOI: 10.1038/s41598-024-55650-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 02/26/2024] [Indexed: 04/13/2024] Open
Abstract
Obesity is associated with increased risk and worse prognosis of many tumours including those of the breast and of the esophagus. Adipokines released from the peritumoural adipose tissue promote the metastatic potential of cancer cells, suggesting the existence of a crosstalk between the adipose tissue and the surrounding tumour. Mitochondrial Ca2+ signaling contributes to the progression of carcinoma of different origins. However, whether adipocyte-derived factors modulate mitochondrial Ca2+ signaling in tumours is unknown. Here, we show that conditioned media derived from adipose tissue cultures (ADCM) enriched in precursor cells impinge on mitochondrial Ca2+ homeostasis of target cells. Moreover, in modulating mitochondrial Ca2+ responses, a univocal crosstalk exists between visceral adipose tissue-derived preadipocytes and esophageal cancer cells, and between subcutaneous adipose tissue-derived preadipocytes and triple-negative breast cancer cells. An unbiased metabolomic analysis of ADCM identified creatine and creatinine for their ability to modulate mitochondrial Ca2+ uptake, migration and proliferation of esophageal and breast tumour cells, respectively.
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Affiliation(s)
- Agnese De Mario
- Department of Biomedical Sciences, University of Padua, via U. Bassi 58/B, 35131, Padua, Italy
| | - Elisabetta Trevellin
- Internal Medicine Unit, Department of Medicine, Padua University Hospital, via Giustiniani 2, 35128, Padua, Italy
| | - Ilaria Piazza
- Department of Biomedical Sciences, University of Padua, via U. Bassi 58/B, 35131, Padua, Italy
| | - Vincenzo Vindigni
- Clinic of Plastic and Reconstructive Surgery, Department of Neurosciences, University of Padua, Padua, Italy
| | - Mirto Foletto
- Bariatric Unit, Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - Rosario Rizzuto
- Department of Biomedical Sciences, University of Padua, via U. Bassi 58/B, 35131, Padua, Italy
| | - Roberto Vettor
- Internal Medicine Unit, Department of Medicine, Padua University Hospital, via Giustiniani 2, 35128, Padua, Italy.
| | - Cristina Mammucari
- Department of Biomedical Sciences, University of Padua, via U. Bassi 58/B, 35131, Padua, Italy.
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Lian J, Vardhanabhuti V. Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank. GeroScience 2024; 46:1515-1526. [PMID: 37648937 PMCID: PMC10828466 DOI: 10.1007/s11357-023-00918-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 08/21/2023] [Indexed: 09/01/2023] Open
Abstract
The identification of metabolic biomarkers for aging-related diseases and mortality is of significant interest in the field of longevity. In this study, we investigated the associations between nuclear magnetic resonance (NMR) metabolomics biomarkers and aging-related diseases as well as mortality using the UK Biobank dataset. We analyzed NMR samples from approximately 110,000 participants and used multi-head machine learning classification models to predict the incidence of aging-related diseases. Cox regression models were then applied to assess the relevance of NMR biomarkers to the risk of death due to aging-related diseases. Additionally, we conducted survival analyses to evaluate the potential improvements of NMR in predicting survival and identify the biomarkers most strongly associated with negative health outcomes by dividing participants into health, disease, and death groups for all age groups. Our analysis revealed specific metabolomics profiles that were associated with the incidence of age-related diseases, and the most significant biomarker was intermediate density lipoprotein cholesteryl (IDL-CE). In addition, NMR biomarkers could provide additional contributions to relevant mortality risk prediction when combined with conventional risk factors, by improving the C-index from 0.813 to 0.833, with 17 NMR biomarkers significantly contributing to disease-related death, such as monounsaturated fatty acids (MUFA), linoleic acid (LA), glycoprotein acetyls (GlycA), and omega-3. Moreover, the value of free cholesterol in very large HDL particles (XL-HDL-FC) in the healthy control group demonstrated significantly higher values than the disease and death group across all age groups. This study highlights the potential of NMR metabolomics profiling as a valuable tool for identifying metabolic biomarkers associated with aging-related diseases and mortality risk, which could have practical implications for aging-related disease risk and mortality prediction.
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Affiliation(s)
- Jie Lian
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pokfulam Road, Hong Kong, SAR, China
| | - Varut Vardhanabhuti
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pokfulam Road, Hong Kong, SAR, China.
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Xia H, Zhu J, Zheng Z, Xiao P, Yu X, Wu M, Xue L, Xu X, Wang X, Guo Y, Zheng C, Ding S, Wang Y, Peng X, Fu S, Li J, Deng X. Amino acids and their roles in tumor immunotherapy of breast cancer. J Gene Med 2024; 26:e3647. [PMID: 38084655 DOI: 10.1002/jgm.3647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/20/2023] [Accepted: 11/13/2023] [Indexed: 01/30/2024] Open
Abstract
Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.
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Affiliation(s)
- Hongzhuo Xia
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Jianyu Zhu
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
- Department of Pathophysiology, Jishou University, Jishou, Hunan, China
| | - Zhuomeng Zheng
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Peiyao Xiao
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Xiaohui Yu
- Department of Pathology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Muyao Wu
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Lian Xue
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Xi Xu
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Xinyu Wang
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Yuxuan Guo
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Chanjuan Zheng
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Siyu Ding
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Yian Wang
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Xiaoning Peng
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
- Department of Pathophysiology, Jishou University, Jishou, Hunan, China
| | - Shujun Fu
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
| | - Junjun Li
- Department of Pathology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Xiyun Deng
- Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, Departments of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, Hunan, China
- Key Laboratory of Translational Cancer Stem Cell Research, Department of Pathophysiology, Hunan Normal University, Changsha, Hunan, China
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12
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His M, Gunter MJ, Keski-Rahkonen P, Rinaldi S. Application of Metabolomics to Epidemiologic Studies of Breast Cancer: New Perspectives for Etiology and Prevention. J Clin Oncol 2024; 42:103-115. [PMID: 37944067 DOI: 10.1200/jco.22.02754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 07/24/2023] [Accepted: 09/11/2023] [Indexed: 11/12/2023] Open
Abstract
PURPOSE To provide an overview on how the application of metabolomics (high-throughput characterization of metabolites from cells, organs, tissues, or biofluids) to population-based studies may inform our understanding of breast cancer etiology. METHODS We evaluated studies that applied metabolomic analyses to prediagnostic blood samples from prospective epidemiologic studies to identify circulating metabolites associated with breast cancer risk, overall and by breast cancer subtype and menopausal status. We provide some important considerations for the application and interpretation of metabolomics approaches in this context. RESULTS Overall, specific lipids and amino acids were indicated as the most common metabolite classes associated with breast cancer development. However, comparison of results across studies is challenging because of heterogeneity in laboratory techniques, analytical methods, sample size, and applied statistical methods. CONCLUSION Metabolomics is being increasingly applied to population-based studies for the identification of new etiologic hypotheses and/or mechanisms related to breast cancer development. Despite its success in applications to epidemiology, studies of larger sample size with detailed information on menopausal status, breast cancer subtypes, and repeated biologic samples collected over time are needed to improve comparison of results between studies and enhance validation of results, allowing potential clinical translation of findings.
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Affiliation(s)
- Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
- Prevention Cancer Environment Department, Centre Léon Bérard, Lyon, France
- Inserm, U1296 Unit, "Radiation: Defense, Health and Environment", Centre Léon Bérard, Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
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13
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Gulati K, Manukonda R, Kairamkonda M, Kaliki S, Poluri KM. Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients. ACS OMEGA 2023; 8:48233-48250. [PMID: 38144138 PMCID: PMC10733957 DOI: 10.1021/acsomega.3c07424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/17/2023] [Accepted: 11/27/2023] [Indexed: 12/26/2023]
Abstract
Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O-phosphocholine, O-phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.
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Affiliation(s)
- Khushboo Gulati
- The
Operation Eyesight Universal Institute for Eye Cancer, LV Prasad Eye Institute, Hyderabad-500034, Telangana, India
- Brien
Holden Eye Research Center, L. V. Prasad
Eye Institute, Hyderabad-500034, Telangana, India
| | - Radhika Manukonda
- The
Operation Eyesight Universal Institute for Eye Cancer, LV Prasad Eye Institute, Hyderabad-500034, Telangana, India
- Brien
Holden Eye Research Center, L. V. Prasad
Eye Institute, Hyderabad-500034, Telangana, India
| | - Manikyaprabhu Kairamkonda
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
| | - Swathi Kaliki
- The
Operation Eyesight Universal Institute for Eye Cancer, LV Prasad Eye Institute, Hyderabad-500034, Telangana, India
| | - Krishna Mohan Poluri
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
- Centre
for Nanotechnology, Indian Institute of
Technology Roorkee, Roorkee-247667, Uttarakhand, India
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14
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Wu S, Liu X, Dong A, Gragnoli C, Griffin C, Wu J, Yau ST, Wu R. The metabolomic physics of complex diseases. Proc Natl Acad Sci U S A 2023; 120:e2308496120. [PMID: 37812720 PMCID: PMC10589719 DOI: 10.1073/pnas.2308496120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 08/15/2023] [Indexed: 10/11/2023] Open
Abstract
Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of high-risk individuals and disease prevention. However, current approaches can only characterize individual key metabolites, without taking into account the reality that complex diseases are multifactorial, dynamic, heterogeneous, and interdependent. Here, we leverage a statistical physics model to combine all metabolites into bidirectional, signed, and weighted interaction networks and trace how the flow of information from one metabolite to the next causes changes in health state. Viewing a disease outcome as the consequence of complex interactions among its interconnected components (metabolites), we integrate concepts from ecosystem theory and evolutionary game theory to model how the health state-dependent alteration of a metabolite is shaped by its intrinsic properties and through extrinsic influences from its conspecifics. We code intrinsic contributions as nodes and extrinsic contributions as edges into quantitative networks and implement GLMY homology theory to analyze and interpret the topological change of health state from symbiosis to dysbiosis and vice versa. The application of this model to real data allows us to identify several hub metabolites and their interaction webs, which play a part in the formation of inflammatory bowel diseases. The findings by our model could provide important information on drug design to treat these diseases and beyond.
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Affiliation(s)
- Shuang Wu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing100083, China
| | - Xiang Liu
- Chern Institute of Mathematics, Nankai University, Tianjin300071, China
- Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing101408, China
| | - Ang Dong
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing100083, China
| | - Claudia Gragnoli
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA17033
- Department of Medicine, Creighton University School of Medicine, Omaha, NE68124
- Molecular Biology Laboratory, Bios Biotech Multi-Diagnostic Health Center, Rome00197, Italy
| | - Christopher Griffin
- Applied Research Laboratory, The Pennsylvania State University, University Park, PA16802
| | - Jie Wu
- Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing101408, China
| | - Shing-Tung Yau
- Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing101408, China
- Yau Mathematical Sciences Center, Tsinghua University, Beijing100084, China
| | - Rongling Wu
- Beijing Yanqi Lake Institute of Mathematical Sciences and Applications, Beijing101408, China
- Yau Mathematical Sciences Center, Tsinghua University, Beijing100084, China
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15
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Bel’skaya LV, Gundyrev IA, Solomatin DV. The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review. Curr Issues Mol Biol 2023; 45:7513-7537. [PMID: 37754258 PMCID: PMC10527988 DOI: 10.3390/cimb45090474] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.
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Affiliation(s)
- Lyudmila V. Bel’skaya
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Ivan A. Gundyrev
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Denis V. Solomatin
- Department of Mathematics and Mathematics Teaching Methods, Omsk State Pedagogical University, 644043 Omsk, Russia;
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16
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Yu CT, Farhat Z, Livinski AA, Loftfield E, Zanetti KA. Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review. Cancer Epidemiol Biomarkers Prev 2023; 32:1130-1145. [PMID: 37410086 PMCID: PMC10472112 DOI: 10.1158/1055-9965.epi-23-0045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 04/26/2023] [Accepted: 06/28/2023] [Indexed: 07/07/2023] Open
Abstract
An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.
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Affiliation(s)
- Catherine T Yu
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland
| | - Zeinab Farhat
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Alicia A Livinski
- National Institutes of Health Library, Office of Research Services, Office of the Director, National Institutes of Health, Bethesda, Maryland
| | - Erikka Loftfield
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Krista A Zanetti
- Office of Nutrition Research, Division of Program Coordination, Planning, and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, Maryland
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Beksac K, Reçber T, Çetin B, Alp O, Kaynaroğlu V, Kır S, Nemutlu E. GC-MS Based Metabolomics Analysis to Evaluate Short-Term Effect of Tumor Removal on Patients with Early-Stage Breast Cancer. J Chromatogr Sci 2023; 61:612-618. [PMID: 35453141 DOI: 10.1093/chromsci/bmac035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/02/2022] [Accepted: 04/04/2022] [Indexed: 11/12/2022]
Abstract
In this study, it was aimed to demonstrate the short-term effect of breast cancer surgery and tumor removal on the metabolomic profiles of patients with early-stage breast cancer. This cohort consisted of 18 early-stage breast carcinoma patients who had breast cancer surgery to remove tumor and surrounding tissues. The blood samples obtained preoperatively and 24 h after surgery were used in this investigation. Gas chromatography-mass spectrometry (GC-MS) based metabolomic analysis was performed to determine the metabolites. The GC-MS-based metabolomics profile enabled the identification of 162 metabolites in the plasma samples. Postoperatively, glyceric acid, phosphoric acid, O-phosphocolamine, 2-hydroxyethyliminodiacetic acid, N-acetyl-D-mannosamine, N-acetyl-5-hydroxytryptamine, methyl stearate, methyl oleate, iminodiacetic acid, glycerol 1-phosphate, β-glycerol phosphate and aspartic acid were found to be significantly increased (P < 0.05 for all), whereas saccharic acid, leucrose, gluconic acid, citramalic acid and acetol were significantly decreased (P < 0.05 for all). Breast cancer surgery and tumor removal has an impact on the metabolomic profiles of patients with early-stage breast cancer. These findings can be used for understanding the pathogenesis of breast cancer biology and screening the success of the surgery.
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Affiliation(s)
- Kemal Beksac
- Department of General Surgery, Ankara Oncology Hospital, Ankara 06200, Turkey
| | - Tuba Reçber
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
| | - Bahadır Çetin
- Department of General Surgery, Ankara Oncology Hospital, Ankara 06200, Turkey
| | - Orkun Alp
- Department of Analytical Chemistry, Faculty of Pharmacy, Gazi University, Ankara 06330, Turkey
| | - Volkan Kaynaroğlu
- Department of General Surgery, Faculty of Medicine, Hacettepe University, Ankara 06100, Turkey
| | - Sedef Kır
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
| | - Emirhan Nemutlu
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
- Bioanalytic and Omics Laboratory, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
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18
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Mrowiec K, Kurczyk A, Jelonek K, Debik J, Giskeødegård GF, Bathen TF, Widłak P. Association of serum metabolome profile with the risk of breast cancer in participants of the HUNT2 study. Front Oncol 2023; 13:1116806. [PMID: 37007110 PMCID: PMC10061137 DOI: 10.3389/fonc.2023.1116806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/06/2023] [Indexed: 03/18/2023] Open
Abstract
Background The serum metabolome is a potential source of molecular biomarkers associated with the risk of breast cancer. Here we aimed to analyze metabolites present in pre-diagnostic serum samples collected from healthy women participating in the Norwegian Trøndelag Health Study (HUNT2 study) for whom long-term information about developing breast cancer was available. Methods Women participating in the HUNT2 study who developed breast cancer within a 15-year follow-up period (BC cases) and age-matched women who stayed breast cancer-free were selected (n=453 case-control pairs). Using a high-resolution mass spectrometry approach 284 compounds were quantitatively analyzed, including 30 amino acids and biogenic amines, hexoses, and 253 lipids (acylcarnitines, glycerides, phosphatidylcholines, sphingolipids, and cholesteryl esters). Results Age was a major confounding factor responsible for a large heterogeneity in the dataset, hence age-defined subgroups were analyzed separately. The largest number of metabolites whose serum levels differentiated BC cases and controls (82 compounds) were observed in the subgroup of younger women (<45 years old). Noteworthy, increased levels of glycerides, phosphatidylcholines, and sphingolipids were associated with reduced risk of cancer in younger and middle-aged women (≤64 years old). On the other hand, increased levels of serum lipids were associated with an enhanced risk of breast cancer in older women (>64 years old). Moreover, several metabolites could be detected whose serum levels were different between BC cases diagnosed earlier (<5 years) and later (>10 years) after sample collecting, yet these compounds were also correlated with the age of participants. Current results were coherent with the results of the NMR-based metabolomics study performed in the cohort of HUNT2 participants, where increased serum levels of VLDL subfractions were associated with reduced risk of breast cancer in premenopausal women. Conclusions Changes in metabolite levels detected in pre-diagnostic serum samples, which reflected an impaired lipid and amino acid metabolism, were associated with long-term risk of breast cancer in an age-dependent manner.
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Affiliation(s)
- Katarzyna Mrowiec
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Agata Kurczyk
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Karol Jelonek
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Julia Debik
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Guro F. Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Surgery, St. Olavs University Hospital, Trondheim, Norway
| | - Tone F. Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Medical Imaging and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway
| | - Piotr Widłak
- Clinical Research Support Centre, Medical University of Gdańsk, Gdańsk, Poland
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Stebbing J, Takis PG, Sands CJ, Maslen L, Lewis MR, Gleason K, Page K, Guttery D, Fernandez-Garcia D, Primrose L, Shaw JA. Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS). Oncogene 2023; 42:825-832. [PMID: 36693953 PMCID: PMC10005936 DOI: 10.1038/s41388-023-02591-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/26/2023]
Abstract
To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort.
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Affiliation(s)
- Justin Stebbing
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
- School of Life Sciences, Faculty of Science and Engineering, ARU, East Road, Cambridge, CB1 1PT, UK
| | - Panteleimon G Takis
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.
| | - Caroline J Sands
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Lynn Maslen
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Matthew R Lewis
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Kelly Gleason
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
| | - Karen Page
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - David Guttery
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Daniel Fernandez-Garcia
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Lindsay Primrose
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Jacqueline A Shaw
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
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20
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Stevens VL, Carter BD, Jacobs EJ, McCullough ML, Teras LR, Wang Y. A prospective case-cohort analysis of plasma metabolites and breast cancer risk. Breast Cancer Res 2023; 25:5. [PMID: 36650550 PMCID: PMC9847033 DOI: 10.1186/s13058-023-01602-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 01/03/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk. METHODS Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling. RESULTS A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06-1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products. CONCLUSIONS Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.
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Affiliation(s)
- Victoria L Stevens
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA
- Social and Scientific Systems, DLH Holdings Corporation, Atlanta, GA, USA
| | - Brian D Carter
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA
| | - Eric J Jacobs
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA
| | - Marjorie L McCullough
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA
| | - Lauren R Teras
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA
| | - Ying Wang
- Department of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
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21
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Vignoli A, Meoni G, Ghini V, Di Cesare F, Tenori L, Luchinat C, Turano P. NMR-Based Metabolomics to Evaluate Individual Response to Treatments. Handb Exp Pharmacol 2023; 277:209-245. [PMID: 36318327 DOI: 10.1007/164_2022_618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy. .,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy. .,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy.
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22
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Baranovicova E, Racay P, Zubor P, Smolar M, Kudelova E, Halasova E, Dvorska D, Dankova Z. Circulating metabolites in the early stage of breast cancer were not related to cancer stage or subtypes but associated with ki67 level. Promising statistical discrimination from controls. Mol Cell Probes 2022; 66:101862. [PMID: 36162596 DOI: 10.1016/j.mcp.2022.101862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/30/2022] [Accepted: 09/13/2022] [Indexed: 12/30/2022]
Abstract
It was documented that the presence of malignancy in an organism causes metabolomic alterations in blood plasma which applies also to breast cancer. Breast cancer is a heterogeneous disease and there are only limited known relations of plasma metabolomic signatures with the tumour characteristics in early BC and knowing them would be of great advantage in noninvasive diagnostics. In this study, we focused on the metabolic alterations in early BC in blood plasma with the aim to identify metabolomic characteristics of BC subtypes. We used 50 early BC patients (FIGO stage I and II), where no additional metabolomic changes from metastatically changed remote organs were to be expected. We compared plasma levels of metabolites against controls and among various molecular and histological BC subtypes. BC patients showed decreased plasma levels of branched-chain amino acids BCAAs (and related keto-acids), histidine pyruvate and alanine balanced with an increased level of 3-hydroxybutyrate. The levels of circulating metabolites were not related to BC molecular subtypes (luminal A/luminal B), histological finding or grade, eventually stage, which indicate that in early BC, the BC patients share common metabolomics fingerprint in blood plasma independent of grade, stage or molecular subtype of BC. We observed statistically significant correlations between tumour proliferation marker Ki-67 level and circulating metabolites: alanine, citrate, tyrosine, glutamine, histidine and proline. This may point out the metabolites those levels could be associated with tumour growth, and conversely, the rate of tumour proliferation could be potentially estimated from plasma metabolites. When analyzing metabolomic changes in BC, we concluded that some of them could be associated with the metabolomic features of cancer cells, but the other observed alterations in blood plasma are the results of the complex mutual biochemical pathways in the comprehensive inter-organ metabolic exchange and communication. In the end, statistical discrimination against controls performed with AUC >0.91 showed the very promising potential of plasma metabolomics in the search for biomarkers for oncologic diseases.
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Affiliation(s)
- Eva Baranovicova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University Bratislava, Mala Hora 4, 036 01, Martin, Slovakia.
| | - Peter Racay
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University Bratislava, Mala Hora 4, 036 01, Martin, Slovakia.
| | - Pavol Zubor
- OBGY Health & Care, Ltd., 01001, Zilina, Slovak Republic; Department of Gynecologic Oncology, The Norwegian Radium Hospital, Oslo University Hospital, 0379, Oslo, Norway; Department of Obstetrics and Gynecology, The University Hospital of North Norway, 8516, Narvik, Norway; Vi Kan helse -Metro legesenter AS, 1473, Lørenskog, Norway.
| | - Marek Smolar
- Clinic of Surgery and Transplant Centre, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollarova 2, 036 01, Martin, Slovakia.
| | - Eva Kudelova
- Clinic of Surgery and Transplant Centre, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollarova 2, 036 01, Martin, Slovakia.
| | - Erika Halasova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University Bratislava, Mala Hora 4, 036 01, Martin, Slovakia.
| | - Dana Dvorska
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University Bratislava, Mala Hora 4, 036 01, Martin, Slovakia.
| | - Zuzana Dankova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University Bratislava, Mala Hora 4, 036 01, Martin, Slovakia.
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23
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Metabolomic profiles predict individual multidisease outcomes. Nat Med 2022; 28:2309-2320. [PMID: 36138150 PMCID: PMC9671812 DOI: 10.1038/s41591-022-01980-3] [Citation(s) in RCA: 111] [Impact Index Per Article: 55.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 07/28/2022] [Indexed: 02/02/2023]
Abstract
Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.
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24
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Amiri-Dashatan N, Yekta RF, Koushki M, Arefi Oskouie A, Esfahani H, Taheri S, Kazemian E. Metabolomic study of serum in patients with invasive ductal breast carcinoma with LC-MS/MS approach. Int J Biol Markers 2022; 37:349-359. [PMID: 36168301 DOI: 10.1177/03936155221123343] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Invasive ductal carcinoma (IDC) is the most common type of breast cancer so its early detection can lead to a significant decrease in mortality rate. However, prognostic factors for IDC are not adequate and we need novel markers for the treatment of different individuals. Although positron emission tomography and magnetic resonance imaging techniques are available, they are based on morphological features that do not provide any clue for molecular events accompanying cancer progression. In recent years, "omics" approaches have been extensively developed to propose novel molecular signatures of cancers as putative biomarkers, especially in biofluids. Therefore, a mass spectrometry-based metabolomics investigation was performed to find some putative metabolite markers of IDC and potential metabolites with prognostic value related to the estrogen receptor, progesterone receptor, lymphovascular invasion, and human epidermal growth factor receptor 2. METHODS An untargeted metabolomics study of IDC patients was performed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The multivariate principal component analysis by XCMS online built a model that could separate the study groups and define the significantly altered m/z parameters. The most important biological pathways were also identified by pathway enrichment analysis. RESULTS The results showed that the significantly altered metabolites in IDC serum samples mostly belonged to amino acids and lipids. The most important involved pathways included arginine and proline metabolism, glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. CONCLUSIONS Significantly altered metabolites in IDC serum samples compared to healthy controls could lead to the development of metabolite-based potential biomarkers after confirmation with other methods and in large cohorts.
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Affiliation(s)
- Nasrin Amiri-Dashatan
- Zanjan Metabolic Diseases Research Center, 48539Zanjan University of Medical Sciences, Zanjan, Iran.,Proteomics Research Center, 556492Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Reyhaneh Farrokhi Yekta
- Proteomics Research Center, 556492Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehdi Koushki
- Department of Clinical Biochemistry, School of Medicine, 48539Zanjan University of Medical Sciences, Zanjan, Iran
| | - Afsaneh Arefi Oskouie
- Department of Basic Sciences, Faculty of Paramedical Sciences, 556492Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hadi Esfahani
- 113401Chemistry and Chemical Engineering Research Center of Iran, Tehran, Iran
| | - Salman Taheri
- 113401Chemistry and Chemical Engineering Research Center of Iran, Tehran, Iran
| | - Elham Kazemian
- Non-communicable Diseases Research Center, 391934Alborz University of Medical Sciences, Karaj, Iran
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25
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An R, Yu H, Wang Y, Lu J, Gao Y, Xie X, Zhang J. Integrative analysis of plasma metabolomics and proteomics reveals the metabolic landscape of breast cancer. Cancer Metab 2022; 10:13. [PMID: 35978348 PMCID: PMC9382832 DOI: 10.1186/s40170-022-00289-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 08/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Breast cancer (BC) is the most commonly diagnosed cancer. Currently, mammography and breast ultrasonography are the main clinical screening methods for BC. Our study aimed to reveal the specific metabolic profiles of BC patients and explore the specific metabolic signatures in human plasma for BC diagnosis. METHODS This study enrolled 216 participants, including BC patients, benign patients, and healthy controls (HC) and formed two cohorts, one training cohort and one testing cohort. Plasma samples were collected from each participant and subjected to perform nontargeted metabolomics and proteomics. The metabolic signatures for BC diagnosis were identified through machine learning. RESULTS Metabolomics analysis revealed that BC patients showed a significant change of metabolic profiles compared to HC individuals. The alanine, aspartate and glutamate pathways, glutamine and glutamate metabolic pathways, and arginine biosynthesis pathways were the critical biological metabolic pathways in BC. Proteomics identified 29 upregulated and 2 downregulated proteins in BC. Our integrative analysis found that aspartate aminotransferase (GOT1), L-lactate dehydrogenase B chain (LDHB), glutathione synthetase (GSS), and glutathione peroxidase 3 (GPX3) were closely involved in these metabolic pathways. Support vector machine (SVM) demonstrated a predictive model with 47 metabolites, and this model achieved a high accuracy in BC prediction (AUC = 1). Besides, this panel of metabolites also showed a fairly high predictive power in the testing cohort between BC vs HC (AUC = 0.794), and benign vs HC (AUC = 0.879). CONCLUSIONS This study uncovered specific changes in the metabolic and proteomic profiling of breast cancer patients and identified a panel of 47 plasma metabolites, including sphingomyelins, glutamate, and cysteine could be potential diagnostic biomarkers for breast cancer.
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Affiliation(s)
- Rui An
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Haitao Yu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Yanzhong Wang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Jie Lu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Yuzhen Gao
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Xinyou Xie
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Jun Zhang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China. .,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.
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26
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Lipoprotein and metabolite associations to breast cancer risk in the HUNT2 study. Br J Cancer 2022; 127:1515-1524. [PMID: 35927310 PMCID: PMC9553939 DOI: 10.1038/s41416-022-01924-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 07/06/2022] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The aim of this study was to gain an increased understanding of the aetiology of breast cancer, by investigating possible associations between serum lipoprotein subfractions and metabolites and the long-term risk of developing the disease. METHODS From a cohort of 65,200 participants within the Trøndelag Health Study (HUNT study), we identified all women who developed breast cancer within a 22-year follow-up period. Using nuclear magnetic resonance (NMR) spectroscopy, 28 metabolites and 89 lipoprotein subfractions were quantified from prediagnostic serum samples of future breast cancer patients and matching controls (n = 1199 case-control pairs). RESULTS Among premenopausal women (554 cases) 14 lipoprotein subfractions were associated with long-term breast cancer risk. In specific, different subfractions of VLDL particles (in particular VLDL-2, VLDL-3 and VLDL-4) were inversely associated with breast cancer. In addition, inverse associations were detected for total serum triglyceride levels and HDL-4 triglycerides. No significant association was found in postmenopausal women. CONCLUSIONS We identified several associations between lipoprotein subfractions and long-term risk of breast cancer in premenopausal women. Inverse associations between several VLDL subfractions and breast cancer risk were found, revealing an altered metabolism in the endogenous lipid pathway many years prior to a breast cancer diagnosis.
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27
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The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis. Crit Rev Oncol Hematol 2022; 176:103757. [PMID: 35809795 DOI: 10.1016/j.critrevonc.2022.103757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/28/2022] [Accepted: 07/04/2022] [Indexed: 11/20/2022] Open
Abstract
The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.
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28
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Brantley KD, Zeleznik OA, Rosner B, Tamimi RM, Avila-Pacheco J, Clish CB, Eliassen AH. Plasma Metabolomics and Breast Cancer Risk Over 20 Years of Follow-up Among Postmenopausal Women in the Nurses' Health Study. Cancer Epidemiol Biomarkers Prev 2022; 31:839-850. [DOI: 10.1158/1055-9965.epi-21-1023] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/08/2021] [Accepted: 01/10/2022] [Indexed: 12/09/2022] Open
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29
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His M, Viallon V, Dossus L, Schmidt JA, Travis RC, Gunter MJ, Overvad K, Kyrø C, Tjønneland A, Lécuyer L, Rothwell JA, Severi G, Johnson T, Katzke V, Schulze MB, Masala G, Sieri S, Panico S, Tumino R, Macciotta A, Boer JMA, Monninkhof EM, Olsen KS, Nøst TH, Sandanger TM, Agudo A, Sánchez MJ, Amiano P, Colorado-Yohar SM, Ardanaz E, Vidman L, Winkvist A, Heath AK, Weiderpass E, Huybrechts I, Rinaldi S. Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort. BMC Med 2021; 19:312. [PMID: 34886862 PMCID: PMC8662901 DOI: 10.1186/s12916-021-02183-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/09/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2). METHODS To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786). RESULTS For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed. CONCLUSIONS These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.
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Affiliation(s)
- Mathilde His
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Laure Dossus
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Cecilie Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, Section of Environmental Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lucie Lécuyer
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
- Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy
| | - Theron Johnson
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Instituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Salvatore Panico
- Dipartimento Di Medicina Clinica E Chirurgia, Federico Ii University, Naples, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7) Ragusa, Ragusa, Italy
| | - Alessandra Macciotta
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Jolanda M A Boer
- Center for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3720, BA, the Netherlands
| | - Evelyn M Monninkhof
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Karina Standahl Olsen
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Therese H Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Torkjel M Sandanger
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Nutrition and Cancer Group; Epidemiology, Public Health, Cancer Prevention and Palliative Care Program; Bellvitge Biomedical Research Institute - IDIBELL, L'Hospitalet de Llobregat, Spain
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain
- Biodonostia Health Research Institute, Group of Epidemiology of Chronic and Communicable Diseases, San Sebastián, Spain
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Sandra M Colorado-Yohar
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Eva Ardanaz
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Linda Vidman
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Anna Winkvist
- Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Elisabete Weiderpass
- International Agency for Research on Cancer (IARC/WHO), Office of the Director, Lyon, France
| | - Inge Huybrechts
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France.
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Zhang L, Bu P. The two sides of creatine in cancer. Trends Cell Biol 2021; 32:380-390. [PMID: 34895811 DOI: 10.1016/j.tcb.2021.11.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 12/23/2022]
Abstract
Creatine is a nitrogen-containing organic acid naturally existing in mammals. It can be converted into phosphocreatine to provide energy for muscle and nerve tissues. Creatine and its analog, cyclocreatine, have been considered cancer suppressive metabolites due to their effects on suppression of subcutaneous cancer growth. Recently, emerging studies have demonstrated the promoting effect of creatine on cancer metastasis. Orthotopic mouse models revealed that creatine promoted invasion and metastasis of pancreatic cancer, colorectal cancer, and breast cancer. Thus, creatine possesses considerably complicated roles in cancer progression. In this review, we systematically summarized the role of creatine in tumor progression, which will call to caution when considering creatine supplementation to clinically treat cancer patients.
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Affiliation(s)
- Liwen Zhang
- Key Laboratory of RNA Biology, Key Laboratory of Protein and Peptide Pharmaceutical, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pengcheng Bu
- Key Laboratory of RNA Biology, Key Laboratory of Protein and Peptide Pharmaceutical, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Biomacromolecules, Chinese Academy of Sciences, Beijing 100101, China.
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31
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His M, Lajous M, Gómez-Flores-Ramos L, Monge A, Dossus L, Viallon V, Gicquiau A, Biessy C, Gunter MJ, Rinaldi S. Biomarkers of mammographic density in premenopausal women. Breast Cancer Res 2021; 23:75. [PMID: 34301304 PMCID: PMC8305592 DOI: 10.1186/s13058-021-01454-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 07/12/2021] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. METHODS A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers' Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. RESULTS Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. CONCLUSIONS We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.
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Affiliation(s)
- Mathilde His
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Martin Lajous
- Center for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México.
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Liliana Gómez-Flores-Ramos
- Center for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México
- Cátedras-CONACYT, Mexico City, Mexico
| | - Adriana Monge
- Center for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México
| | - Laure Dossus
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Audrey Gicquiau
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Carine Biessy
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France
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Bendinelli B, Vignoli A, Palli D, Assedi M, Ambrogetti D, Luchinat C, Caini S, Saieva C, Turano P, Masala G. Prediagnostic circulating metabolites in female breast cancer cases with low and high mammographic breast density. Sci Rep 2021; 11:13025. [PMID: 34158597 PMCID: PMC8219761 DOI: 10.1038/s41598-021-92508-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/11/2021] [Indexed: 02/05/2023] Open
Abstract
Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case-case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case-case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. 1H NMR metabolomic spectra were available for 87 complete case-case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the "phenylalanine, tyrosine and tryptophan pathway" emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case-case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.
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Affiliation(s)
- Benedetta Bendinelli
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Alessia Vignoli
- grid.20765.360000 0004 7402 7708Consorzio Interuniversitario Risonanze Magnetiche Di Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy
| | - Domenico Palli
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Melania Assedi
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Daniela Ambrogetti
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Claudio Luchinat
- grid.8404.80000 0004 1757 2304Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy ,grid.8404.80000 0004 1757 2304Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Saverio Caini
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Calogero Saieva
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
| | - Paola Turano
- grid.8404.80000 0004 1757 2304Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy ,grid.8404.80000 0004 1757 2304Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50139 Florence, Italy
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Houghton SC, Hankinson SE. Cancer Progress and Priorities: Breast Cancer. Cancer Epidemiol Biomarkers Prev 2021; 30:822-844. [PMID: 33947744 PMCID: PMC8104131 DOI: 10.1158/1055-9965.epi-20-1193] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/13/2020] [Accepted: 02/19/2021] [Indexed: 12/24/2022] Open
Affiliation(s)
- Serena C Houghton
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, Massachusetts.
| | - Susan E Hankinson
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, Massachusetts
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Jobard E, Dossus L, Baglietto L, Fornili M, Lécuyer L, Mancini FR, Gunter MJ, Trédan O, Boutron-Ruault MC, Elena-Herrmann B, Severi G, Rothwell JA. Investigation of circulating metabolites associated with breast cancer risk by untargeted metabolomics: a case-control study nested within the French E3N cohort. Br J Cancer 2021; 124:1734-1743. [PMID: 33723391 PMCID: PMC8110540 DOI: 10.1038/s41416-021-01304-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/01/2021] [Accepted: 02/04/2021] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Perturbations in circulating metabolites prior to a breast cancer diagnosis are not well characterised. We aimed to gain more detailed knowledge to help understand and prevent the disease. METHODS Baseline plasma samples from 791 breast cancer cases and 791 matched controls from the E3N (EPIC-France) cohort were profiled by nuclear magnetic resonance (NMR)-based untargeted metabolomics. Partial least-squares discriminant analysis (PLS-DA) models were built from NMR profiles to predict disease outcome, and odds ratios and false discovery rate (FDR)-adjusted CIs were calculated for 43 identified metabolites by conditional logistic regression. RESULTS Breast cancer onset was predicted in the premenopausal subgroup with modest accuracy (AUC 0.61, 95% CI: 0.49-0.73), and 10 metabolites associated with risk, particularly histidine (OR = 1.70 per SD increase, FDR-adjusted CI 1.19-2.41), N-acetyl glycoproteins (OR = 1.53, FDR-adjusted CI 1.18-1.97), glycerol (OR = 1.55, FDR-adjusted CI 1.11-2.18) and ethanol (OR = 1.44, FDR-adjusted CI 1.05-1.97). No predictive capacity or significant metabolites were found overall or for postmenopausal women. CONCLUSIONS Perturbed metabolism compared to controls was observed in premenopausal but not postmenopausal cases. Histidine and NAC have known involvement in inflammatory pathways, and the robust association of ethanol with risk suggests the involvement of alcohol intake.
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Affiliation(s)
- Elodie Jobard
- Univ Lyon, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Institut des Sciences Analytiques, UMR 5280, Villeurbanne, France
- Université de Lyon, Centre Léon Bérard, Département d'Oncologie Médicale, Lyon, France
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Laura Baglietto
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Marco Fornili
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Lucie Lécuyer
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, Gustave Roussy, Exposome and Heredity Team, Centre for Epidemiology and Population Health, Villejuif, France
| | - Francesca Romana Mancini
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, Gustave Roussy, Exposome and Heredity Team, Centre for Epidemiology and Population Health, Villejuif, France
| | - Marc J Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Olivier Trédan
- Université de Lyon, Centre Léon Bérard, Département d'Oncologie Médicale, Lyon, France
| | - Marie-Christine Boutron-Ruault
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, Gustave Roussy, Exposome and Heredity Team, Centre for Epidemiology and Population Health, Villejuif, France
| | - Bénédicte Elena-Herrmann
- Univ Lyon, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Institut des Sciences Analytiques, UMR 5280, Villeurbanne, France
- Univ Grenoble Alpes, CNRS, INSERM, IAB, Allée des Alpes, Grenoble, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, Gustave Roussy, Exposome and Heredity Team, Centre for Epidemiology and Population Health, Villejuif, France
- Department of Statistics, Computer Science and Applications "G. Parenti" (DISIA), University of Florence, Firenze, Italy
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, Gustave Roussy, Exposome and Heredity Team, Centre for Epidemiology and Population Health, Villejuif, France.
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Vignoli A, Risi E, McCartney A, Migliaccio I, Moretti E, Malorni L, Luchinat C, Biganzoli L, Tenori L. Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer. Int J Mol Sci 2021; 22:ijms22094687. [PMID: 33925233 PMCID: PMC8124948 DOI: 10.3390/ijms22094687] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/22/2022] Open
Abstract
Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Emanuela Risi
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Amelia McCartney
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
- School of Clinical Sciences, Monash University, Melbourne 3800, Australia
| | - Ilenia Migliaccio
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Erica Moretti
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Luca Malorni
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
- Correspondence: ; Tel.: +39-055-457-4296
| | - Laura Biganzoli
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
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Abstract
Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.
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Lécuyer L, Victor Bala A, Demidem A, Rossary A, Bouchemal N, Triba MN, Galan P, Hercberg S, Partula V, Srour B, Latino-Martel P, Kesse-Guyot E, Druesne-Pecollo N, Vasson MP, Deschasaux-Tanguy M, Savarin P, Touvier M. NMR metabolomic profiles associated with long-term risk of prostate cancer. Metabolomics 2021; 17:32. [PMID: 33704614 DOI: 10.1007/s11306-021-01780-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 02/24/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Prostate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors. OBJECTIVES The aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade. METHODS A prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis. RESULTS Men with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up. CONCLUSIONS This exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.
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Affiliation(s)
- Lucie Lécuyer
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Agnès Victor Bala
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Aicha Demidem
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
| | - Adrien Rossary
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
| | - Nadia Bouchemal
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Mohamed Nawfal Triba
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Pilar Galan
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Serge Hercberg
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
- Public Health Department, Avicenne Hospital, 93000, Bobigny, France
| | - Valentin Partula
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Bernard Srour
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Paule Latino-Martel
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Emmanuelle Kesse-Guyot
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Nathalie Druesne-Pecollo
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
| | - Marie-Paule Vasson
- INRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France
- Anticancer Center Jean-Perrin, CHU Clermont-Ferrand, 63011, Clermont-Ferrand Cedex, France
| | - Mélanie Deschasaux-Tanguy
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
| | - Philippe Savarin
- Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France
| | - Mathilde Touvier
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France
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A Metabolomics Analysis of Postmenopausal Breast Cancer Risk in the Cancer Prevention Study II. Metabolites 2021; 11:metabo11020095. [PMID: 33578791 PMCID: PMC7916573 DOI: 10.3390/metabo11020095] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 02/02/2021] [Accepted: 02/02/2021] [Indexed: 12/29/2022] Open
Abstract
Breast cancer is the most common cancer in women, but its incidence can only be partially explained through established risk factors. Our aim was to use metabolomics to identify novel risk factors for breast cancer and to validate recently reported metabolite-breast cancer findings. We measured levels of 1275 metabolites in prediagnostic serum in a nested case-control study of 782 postmenopausal breast cancer cases and 782 matched controls. Metabolomics analysis was performed by Metabolon Inc using ultra-performance liquid chromatography and a Q-Exactive high resolution/accurate mass spectrometer. Controls were matched by birth date, date of blood draw, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer at the 90th versus 10th percentile (modeled on a continuous basis) of metabolite levels were estimated using conditional logistic regression, with adjustment for age. Twenty-four metabolites were significantly associated with breast cancer risk at a false discovery rate <0.20. For the nine metabolites positively associated with risk, the ORs ranged from 1.75 (95% CI: 1.29–2.36) to 1.45 (95% CI: 1.13–1.85), and for the 15 metabolites inversely associated with risk, ORs ranged from 0.59 (95% CI: 0.43–0.79) to 0.69 (95% CI: 0.55–0.87). These metabolites largely comprised carnitines, glycerolipids, and sex steroid metabolites. Associations for three sex steroid metabolites validated findings from recent studies and the remainder were novel. These findings contribute to growing data on metabolite-breast cancer associations by confirming prior findings and identifying novel leads for future validation efforts.
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Yu S, Wang X, Zhu L, Xie P, Zhou Y, Jiang S, Chen H, Liao X, Pu S, Lei Z, Wang B, Ren Y. A systematic analysis of a potential metabolism-related prognostic signature for breast cancer patients. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:330. [PMID: 33708957 PMCID: PMC7944328 DOI: 10.21037/atm-20-7600] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background Metabolic pathways play an essential role in breast cancer. However, the role of metabolism-related genes in the early diagnosis of breast cancer remains unknown. Methods In our study, RNA sequencing (RNA-seq) expression data and clinicopathological information from The Cancer Genome Atlas (TCGA) and GSE20685 were obtained. Univariate cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed on the differentially expressed metabolism-related genes. Then, the formula of the metabolism-related risk model was composed, and the risk score of each patient was calculated. The breast cancer patients were divided into high-risk and low-risk groups with a cutoff of the median expression value of the risk score, and the prognostic analysis was also used to analyze the survival time between these two groups. In the end, we also analyzed the expression, interaction, and correlation among genes in the metabolism-related gene risk model. Results The results from the prognostic analysis indicated that the survival was significantly poorer in the high-risk group than in the low-risk group in both TCGA and GSE20685 datasets. In addition, after adjusting for different clinicopathological features in multivariate analysis, the metabolism-related risk model remained an independent prognostic indicator in TCGA dataset. Conclusions In summary, we systematically developed a potential metabolism-related gene risk model for predicting prognosis in breast cancer patients.
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Affiliation(s)
- Shibo Yu
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaowen Wang
- Department of Second Breast surgery, the Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, China
| | - Lizhe Zhu
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Peiling Xie
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yudong Zhou
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Siyuan Jiang
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Heyan Chen
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaoqin Liao
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shengyu Pu
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zhenzhen Lei
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Bin Wang
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yu Ren
- Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Associations between untargeted plasma metabolomic signatures and gut microbiota composition in the Milieu Intérieur population of healthy adults. Br J Nutr 2020; 126:982-992. [PMID: 33298217 DOI: 10.1017/s0007114520004870] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Host-microbial co-metabolism products are being increasingly recognised to play important roles in physiological processes. However, studies undertaking a comprehensive approach to consider host-microbial metabolic relationships remain scarce. Metabolomic analysis yielding detailed information regarding metabolites found in a given biological compartment holds promise for such an approach. This work aimed to explore the associations between host plasma metabolomic signatures and gut microbiota composition in healthy adults of the Milieu Intérieur study. For 846 subjects, gut microbiota composition was profiled through sequencing of the 16S rRNA gene in stools. Metabolomic signatures were generated through proton NMR analysis of plasma. The associations between metabolomic variables and α- and β-diversity indexes and relative taxa abundances were tested using multi-adjusted partial Spearman correlations, permutational ANOVA and multivariate associations with linear models, respectively. A multiple testing correction was applied (Benjamini-Hochberg, 10 % false discovery rate). Microbial richness was negatively associated with lipid-related signals and positively associated with amino acids, choline, creatinine, glucose and citrate (-0·133 ≤ Spearman's ρ ≤ 0·126). Specific associations between metabolomic signals and abundances of taxa were detected (twenty-five at the genus level and nineteen at the species level): notably, numerous associations were observed for creatinine (positively associated with eleven species and negatively associated with Faecalibacterium prausnitzii). This large-scale population-based study highlights metabolites associated with gut microbial features and provides new insights into the understanding of complex host-gut microbiota metabolic relationships. In particular, our results support the implication of a 'gut-kidney axis'. More studies providing a detailed exploration of these complex interactions and their implications for host health are needed.
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41
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Wang T, Sun Z, Wang Y, Li F, Zhou X, Tian X, Wang S. Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood. Drug Discov Ther 2020; 14:187-196. [PMID: 32848112 DOI: 10.5582/ddt.2020.03062] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The incidence rate of thyroid carcinoma, especially papillary thyroid carcinoma (PTC), has increased significantly over time. As a primary pathway for metastasis, the lymphatic system is an important prognostic factor for PTC patients. Although the metabolic changes in PTC patients have been investigated in extensive studies, few studies focused on the whole blood metabolic profiling of PTC patients. In this study, we investigated the 1H NMR-based metabolic profiles of whole blood samples that were obtained from healthy individuals and PTC patients, with or without lymph node metastasis. The estimation of the predictive potential of metabolites was evaluated using multivariate statistical analyses, which revealed that the whole blood carries information that is sufficient for distinguishing between PTC patients and healthy individuals. However, PTC patients were not well classified as positive or negative according to the lymph nodes. We did not find a metabolite that could discriminate the presence of lymph node metastasis. Further studies with larger sample sizes are needed to elucidate significant metabolites to indicate the presence of lymph node metastasis in patients with PTC.
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Affiliation(s)
- Tiantian Wang
- School of Pharmaceutical Sciences, Shandong University, Ji'nan, Shandong, China.,Department of Thyroid and Breast Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Ji'nan, Shandong, China
| | - Zhigang Sun
- Department of Thyroid and Breast Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Ji'nan, Shandong, China.,Department of Colorectal Surgery and State Key Lab of Molecular Oncology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yong Wang
- Department of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University College of Medicine, Hangzhou, Zhejiang, China
| | - Feifei Li
- School of Pharmaceutical Sciences, Shandong University, Ji'nan, Shandong, China
| | - Xiaoming Zhou
- Department of Thyroid and Breast Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Ji'nan, Shandong, China
| | - Xingsong Tian
- Department of Thyroid and Breast Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Ji'nan, Shandong, China
| | - Shuqi Wang
- School of Pharmaceutical Sciences, Shandong University, Ji'nan, Shandong, China
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Huang H, Cao S, Zhang Z, Li L, Chen F, Wu Q. Multiple omics analysis of the protective effects of SFN on estrogen-dependent breast cancer cells. Mol Biol Rep 2020; 47:3331-3346. [DOI: 10.1007/s11033-020-05403-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 03/25/2020] [Indexed: 12/14/2022]
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43
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Li L, Zhang M, Men Y, Wang W, Zhang W. Heavy metals interfere with plasma metabolites, including lipids and amino acids, in patients with breast cancer. Oncol Lett 2020; 19:2925-2933. [PMID: 32218848 PMCID: PMC7068226 DOI: 10.3892/ol.2020.11402] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 01/16/2020] [Indexed: 12/28/2022] Open
Abstract
The aim of the present study was to examine the association between plasma heavy metals and the metabolome in patients with breast cancer (BC), and the association with cancer development. Nuclear magnetic resonance was used to determine the metabolites involved and an inductively coupled plasma mass spectrometry system was used to quantify the heavy metals in the plasma samples. It was indicated that cadmium was significantly higher in the plasma of patients with BC compared with that in the control population (~15-fold increase). Chromium, arsenic and lead were also elevated in the plasma of patients with BC by ~3.24, 2.14 and 1.52 fold, respectively. A number of small molecules, including amino acids and salts, were altered in the plasma of patients with BC compared with the control population. Another notable finding in this investigation was that plasma lipid levels were elevated in patients with BC compared with those in the control population. The findings of the present study suggest that exposure to heavy metals, including cadmium, arsenic, chromium and lead, may influence blood lipid levels and other small molecule metabolites, which in turn may be involved in BC development. Further studies surrounding urinary heavy metals and the metabolome are required to further determine the impact of metals on metabolism and on BC development.
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Affiliation(s)
- Ling Li
- Department of Oncology, Affiliated Tengzhou Central People's Hospital of Jining Medical University, Tengzhou, Shandong 277599, P.R. China
| | - Meihua Zhang
- Medical Image Center, Affiliated Tengzhou Central People's Hospital of Jining Medical University, Tengzhou, Shandong 277599, P.R. China
| | - Yuhao Men
- College of Animal Sciences and Technology, Qingdao Agricultural University, Qingdao, Shandong 266109, P.R. China
| | - Wei Wang
- Department of Oncology, Affiliated Tengzhou Central People's Hospital of Jining Medical University, Tengzhou, Shandong 277599, P.R. China
| | - Weidong Zhang
- College of Animal Sciences and Technology, Qingdao Agricultural University, Qingdao, Shandong 266109, P.R. China
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Wang X, Rezeng C, Wang Y, Li J, Zhang L, Chen J, Li Z. Toxicological Risks of Renqingchangjue in Rats Evaluated by 1H NMR-Based Serum and Urine Metabolomics Analysis. ACS OMEGA 2020; 5:2169-2179. [PMID: 32064377 PMCID: PMC7016918 DOI: 10.1021/acsomega.9b03084] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 01/17/2020] [Indexed: 05/09/2023]
Abstract
Renqingchangjue (RQCJ), a kind of Traditional Tibetan Medicine, has been widely utilized to treat various gastroenteritis diseases. However, the biosafety and toxicity of RQCJ was still indefinite because of toxic components in RQCJ, which included a variety of heavy metals. Thus, this study was aimed to evaluate the toxicity and expound the toxicological mechanism of RQCJ. In this study, rats were intragastrically administered with different doses of RQCJ for 15 days, and then, the restorative observation period lasted for 15 days. Liver and kidney tissues were collected for histopathological examination, and simultaneously serum and urine samples were collected for 1H nuclear magnetic resonance (1H NMR) spectroscopy analysis and biochemical analysis combined with inductively coupled plasma mass spectrometry (ICP-MS) measurement. The 1H NMR-based metabolomics analysis revealed that the administration of RQCJ significantly altered the concentrations of 14 serum metabolites and 14 urine metabolites, which implied disturbances in energy metabolism, amino acid metabolism, intestinal flora environment, and membrane damage. Besides, the biochemical analysis of serum samples was consistent with the histopathological results, which indicated slight hepatotoxicity and nephrotoxicity. The quantification of As and Hg in urine and serum samples by ICP-MS provided more evidence about the toxicity of RQCJ. This work provided an effective method to systematically and dynamically evaluate the toxicity of RQCJ and suggested that precautions should be taken in the clinic to monitor the potential toxicity of RQCJ.
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Affiliation(s)
- Xia Wang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Caidan Rezeng
- College
of Pharmacy, Qinghai Nationalities University, No. 3 Bayizhong Road, Xining 810000, PR China
| | - Yingfeng Wang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Jian Li
- Beijing
University of Chinese Medicine, No. 11 Beisanhuandonglu, Chaoyang District, Beijing 100029, PR China
| | - Lan Zhang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Jianxin Chen
- Beijing
University of Chinese Medicine, No. 11 Beisanhuandonglu, Chaoyang District, Beijing 100029, PR China
| | - Zhongfeng Li
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
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Schmidt JA, Fensom GK, Rinaldi S, Scalbert A, Appleby PN, Achaintre D, Gicquiau A, Gunter MJ, Ferrari P, Kaaks R, Kühn T, Boeing H, Trichopoulou A, Karakatsani A, Peppa E, Palli D, Sieri S, Tumino R, Bueno-de-Mesquita B, Agudo A, Sánchez MJ, Chirlaque MD, Ardanaz E, Larrañaga N, Perez-Cornago A, Assi N, Riboli E, Tsilidis KK, Key TJ, Travis RC. Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case-control sets from EPIC. Int J Cancer 2020; 146:720-730. [PMID: 30951192 PMCID: PMC6916595 DOI: 10.1002/ijc.32314] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 03/15/2019] [Accepted: 03/19/2019] [Indexed: 01/13/2023]
Abstract
Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.
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Affiliation(s)
- Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Georgina K Fensom
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Sabina Rinaldi
- International Agency for Research on Cancer, Lyon, France
| | | | - Paul N Appleby
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | | | | | - Marc J Gunter
- International Agency for Research on Cancer, Lyon, France
| | - Pietro Ferrari
- International Agency for Research on Cancer, Lyon, France
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition (DIfE) Potsdam-Rehbrücke, Nuthetal, Germany
| | | | - Anna Karakatsani
- Hellenic Health Foundation, Athens, Greece
- 2nd Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, "ATTIKON" University Hospital, Haidari, Greece
| | | | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, "Civic - M.P.Arezzo" Hospital, Azienda Sanitaria Provinciale Di Ragusa (ASP), Ragusa, Italy
| | - Bas Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Maria-Jose Sánchez
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | - María-Dolores Chirlaque
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Department of Health and Social Sciences, Murcia University, Murcia, Spain
| | - Eva Ardanaz
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Nerea Larrañaga
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Basque Regional Health Department, Public Health Division of Gipuzkoa-BIODONOSTIA, San Sebastian, Spain
| | - Aurora Perez-Cornago
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Nada Assi
- International Agency for Research on Cancer, Lyon, France
| | - Elio Riboli
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
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Affiliation(s)
- Steven C Moore
- Metabolic Epidemiology Branch, Division of Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Dr, Bethesda, MD, 20892, USA.
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Fuertes-Martín R, Correig X, Vallvé JC, Amigó N. Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment. J Clin Med 2020; 9:E354. [PMID: 32012794 PMCID: PMC7073769 DOI: 10.3390/jcm9020354] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/13/2020] [Accepted: 01/17/2020] [Indexed: 12/17/2022] Open
Abstract
Several studies suggest that variations in the concentration of plasma glycoproteins can influence cellular changes in a large number of diseases. In recent years, proton nuclear magnetic resonance (1H-NMR) has played a major role as an analytical tool for serum and plasma samples. In recent years, there is an increasing interest in the characterization of glycoproteins through 1H-NMR in order to search for reliable and robust biomarkers of disease. The objective of this review was to examine the existing studies in the literature related to the study of glycoproteins from an analytical and clinical point of view. There are currently several techniques to characterize circulating glycoproteins in serum or plasma, but in this review, we focus on 1H-NMR due to its great robustness and recent interest in its translation to the clinical setting. In fact, there is already a marker in H-NMR representing the acetyl groups of the glycoproteins, GlycA, which has been increasingly studied in clinical studies. A broad search of the literature was performed showing a general consensus that GlycA is a robust marker of systemic inflammation. The results also suggested that GlycA better captures systemic inflammation even more than C-reactive protein (CRP), a widely used classical inflammatory marker. The applications reviewed here demonstrated that GlycA was potentially a key biomarker in a wide range of diseases such as cancer, metabolic diseases, cardiovascular risk, and chronic inflammatory diseases among others. The profiling of glycoproteins through 1H-NMR launches an encouraging new paradigm for its future incorporation in clinical diagnosis.
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Affiliation(s)
- Rocío Fuertes-Martín
- Biosfer Teslab SL, 43201 Reus, Spain; (R.F.-M.); (N.A.)
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
| | - Xavier Correig
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
| | - Joan-Carles Vallvé
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
- Lipids and Arteriosclerosis Research Unit, Sant Joan de Reus University Hospital, 43201 Reus, Spain
| | - Núria Amigó
- Biosfer Teslab SL, 43201 Reus, Spain; (R.F.-M.); (N.A.)
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
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Lécuyer L, Dalle C, Micheau P, Pétéra M, Centeno D, Lyan B, Lagree M, Galan P, Hercberg S, Rossary A, Demidem A, Vasson MP, Partula V, Deschasaux M, Srour B, Latino-Martel P, Druesne-Pecollo N, Kesse-Guyot E, Durand S, Pujos-Guillot E, Manach C, Touvier M. Untargeted plasma metabolomic profiles associated with overall diet in women from the SU.VI.MAX cohort. Eur J Nutr 2020; 59:3425-3439. [DOI: 10.1007/s00394-020-02177-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 01/03/2020] [Indexed: 12/22/2022]
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His M, Viallon V, Dossus L, Gicquiau A, Achaintre D, Scalbert A, Ferrari P, Romieu I, Onland-Moret NC, Weiderpass E, Dahm CC, Overvad K, Olsen A, Tjønneland A, Fournier A, Rothwell JA, Severi G, Kühn T, Fortner RT, Boeing H, Trichopoulou A, Karakatsani A, Martimianaki G, Masala G, Sieri S, Tumino R, Vineis P, Panico S, van Gils CH, Nøst TH, Sandanger TM, Skeie G, Quirós JR, Agudo A, Sánchez MJ, Amiano P, Huerta JM, Ardanaz E, Schmidt JA, Travis RC, Riboli E, Tsilidis KK, Christakoudi S, Gunter MJ, Rinaldi S. Prospective analysis of circulating metabolites and breast cancer in EPIC. BMC Med 2019; 17:178. [PMID: 31547832 PMCID: PMC6757362 DOI: 10.1186/s12916-019-1408-4] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 08/13/2019] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. METHODS A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. RESULTS Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. CONCLUSIONS These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.
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Affiliation(s)
- Mathilde His
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Vivian Viallon
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Laure Dossus
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Audrey Gicquiau
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - David Achaintre
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Augustin Scalbert
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Pietro Ferrari
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Isabelle Romieu
- Centre for Research on Population Health, National Institute of Public Health, Cuernavaca, Mexico
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | | | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- University of Copenhagen, Copenhagen, Denmark
| | - Agnès Fournier
- CESP, Université Paris-Sud, UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, Villejuif, France
| | - Joseph A Rothwell
- CESP, Université Paris-Sud, UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- CESP, Université Paris-Sud, UVSQ, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, Villejuif, France
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Renée T Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
| | | | - Anna Karakatsani
- Hellenic Health Foundation, Athens, Greece
- Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, "ATTIKON" University Hospital, Haidari, Greece
| | | | - Giovanna Masala
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, "M.P.Arezzo"Hospital, ASP Ragusa, Ragusa, Italy
| | - Paolo Vineis
- Italian Institute for Genomic Medicine (IIGM), 10126, Turin, Italy
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Salvatore Panico
- Dipartimento di medicina clinica e chirurgia, Federico II University, Naples, Italy
| | - Carla H van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Therese H Nøst
- Department of Community Medicine, UiT the Arctic University of Norway, Tromso, Norway
| | - Torkjel M Sandanger
- Department of Community Medicine, UiT the Arctic University of Norway, Tromso, Norway
| | - Guri Skeie
- Department of Community Medicine, UiT the Arctic University of Norway, Tromso, Norway
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | | | - Antonio Agudo
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Universidad de Granada, Granada, Spain
- CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
| | - Pilar Amiano
- CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
- Public Health Division of Gipuzkoa, BioDonostia Research Institute, San Sebastian, Spain
| | - José María Huerta
- CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
| | - Eva Ardanaz
- CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
- MRC Centre for Transplantation, King's College London, Great Maze Pond, London, SE1 9RT, UK
| | - Marc J Gunter
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France.
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Chen Z, Li Z, Li H, Jiang Y. Metabolomics: a promising diagnostic and therapeutic implement for breast cancer. Onco Targets Ther 2019; 12:6797-6811. [PMID: 31686838 PMCID: PMC6709037 DOI: 10.2147/ott.s215628] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 07/22/2019] [Indexed: 12/24/2022] Open
Abstract
Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.
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Affiliation(s)
- Zhanghan Chen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Zehuan Li
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Haoran Li
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Ying Jiang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
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