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Wang Q, Zhou JY, Liu L, Yin ZY, Li YY, Wang M, Zhang JB, Lu H, Zhou XY, Zhang B. Resveratrol activates MAPK/ERK pathway to regulate oestrogen metabolism in type I endometrial cancer. BMC Complement Med Ther 2024; 24:227. [PMID: 38862934 PMCID: PMC11167854 DOI: 10.1186/s12906-024-04509-y] [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: 04/30/2023] [Accepted: 05/21/2024] [Indexed: 06/13/2024] Open
Abstract
OBJECTIVE Endometrial cancer (EC) is an oestrogen-dependent tumour, the occurrence of which is closely related to an imbalance of oestrogen homeostasis. Our previous studies explored the effects of Resveratrol(Res) on oestrogen metabolism. However, systematic research on the exact mechanism of action of Res is still lacking. Based on network pharmacology, molecular docking and animal experiments, the effects and molecular mechanisms of Res on endometrial cancer were investigated. METHODS The target of Res was obtained from the high-throughput experiment and reference-guided database of TCM (HERB) and the Encyclopedia of Traditional Chinese Medicine (ETCM) databases, and the target of endometrial cancer was obtained by using the Genecards database. Venny map was used to obtain the intersection target of Res in the treatment of endometrial cancer, and the protein interaction network of the intersection target was constructed by importing the data into the STRING database. Then, the drug-disease-target interaction network was constructed based on Cytoscape 3.9.1 software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for intersection targets using the OmicShare cloud platform. Res and core targets were analysed by molecular docking. EC model mice induced by MNNG were randomly divided into the control group, Res group, MNNG group, MNNG + Res group, and MNNG + Res + MAPK/ERKi group. The protein levels of ERK and p-ERK in the mouse uterus were detected by Western blot. The levels of E1, E2, E3, 16-epiE3, 17-epiE3, 2-MeOE1, 4-MeOE1, 2-MeOE2, 4-MeOE2, 3-MeOE1, 2-OHE1, 4-OHE1, 2-OHE2, 4-OHE2, and 16α-OHE1 in the serum and endometrial tissue of mice were measured by LC‒MS/MS. RESULTS A total of 174 intersection targets of Res anti-endometrial cancer were obtained. The signalling pathways analysed by KEGG enrichment included the AGE-RAGE signalling pathway in diabetic complications, the PI3K-Akt signalling pathway and the MAPK signalling pathway. The top 10 core targets were MAPK3, JUN, TP53, CASP3, TNF, IL1B, AKT1, FOS, VEGFA and INS. Molecular docking showed that in addition to TNF, other targets had good affinity for Res, and the binding activity with MAPK3 was stable. Western blot results showed that Res increased the phosphorylation level of ERK and that MAPK/ERKi decreased ERK activation. In the LC-MS/MS analysis, the levels of 2-MeOE1, 2-MeOE2 and 4-MeOE1 in serum and uterine tissue showed a significantly decreasing trend in the MNNG group, while that of 4-OHE2 was increased (P < 0.05). The concentrations of 4-MeOE1 in serum and 2-MeOE1 and 2-MeOE2 in the endometrial tissue of mice were significantly increased after Res treatment, and those of 4-OHE2 in the serum and uterus of mice were significantly decreased (P < 0.05). Meanwhile, in the MAPK/ERKi intervention group, the effect of Res on the reversal of oestrogen homeostasis imbalance was obviously weakened. CONCLUSION Res has multiple targets and multiple approaches in the treatment of endometrial cancer. In this study, it was found that Res regulates oestrogen metabolism by activating the MAPK/ERK pathway. This finding provides a new perspective for subsequent research on the treatment of endometrial cancer.
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Affiliation(s)
- Qing Wang
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jia-Yun Zhou
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Li Liu
- Department of Obstetrics and Gynecology, Graduate School of Bengbu Medical University, Bengbu, China
| | - Ze-Yuan Yin
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Yan-Yu Li
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Meng Wang
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jing-Bo Zhang
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Hui Lu
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China
- Department of Physical Examination Center, Xuzhou Central Hospital, Xuzhou, China
| | - Xue-Yan Zhou
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, Jiangsu, China.
| | - Bei Zhang
- Department of Obstetrics and Gynecology, Xuzhou Central Hospital, The Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, Jiangsu, China.
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Liu X, Wang W, Zhang X, Liang J, Feng D, Li Y, Xue M, Ling B. Metabolism pathway-based subtyping in endometrial cancer: An integrated study by multi-omics analysis and machine learning algorithms. MOLECULAR THERAPY. NUCLEIC ACIDS 2024; 35:102155. [PMID: 38495844 PMCID: PMC10943971 DOI: 10.1016/j.omtn.2024.102155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/14/2024] [Indexed: 03/19/2024]
Abstract
Endometrial cancer (EC), the second most common malignancy in the female reproductive system, has garnered increasing attention for its genomic heterogeneity, but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in EC through a comprehensive multi-omics analysis (RNA-seq datasets from The Cancer Genome Atlas [TCGA], Cancer Cell Line Encyclopedia [CCLE], and GEO datasets; the Clinical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy. Unsupervised consensus clustering was performed to categorize EC patients into three metabolism-pathway-based subgroups (MPSs). These MPS subgroups had distinct clinical prognoses, transcriptomic and genomic alterations, immune microenvironment landscape, and unique patterns of chemotherapy sensitivity. Moreover, the MPS2 subgroup had a better response to immunotherapy. Finally, three machine learning algorithms (LASSO, random forest, and stepwise multivariate Cox regression) were used for developing a prognostic metagene signature based on metabolic molecules. Thus, a 13-hub gene-based classifier was constructed to predict patients' MPS subtypes, offering a more accessible and practical approach. This metabolism-based classification system can enhance prognostic predictions and guide clinical strategies for immunotherapy and metabolism-targeted therapy in EC.
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Affiliation(s)
- Xiaodie Liu
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China
- Department of Obstetrics and Gynecology, Shandong Provincial Hospital, Jinan 250000, China
| | - Wenhui Wang
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Xiaolei Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong 250012, China
| | - Jing Liang
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Dingqing Feng
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Yuebo Li
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China
| | - Ming Xue
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China
| | - Bin Ling
- Department of Obstetrics and Gynecology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China
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Fu Y, Wang C, Wu Z, Zhang X, Liu Y, Wang X, Liu F, Chen Y, Zhang Y, Zhao H, Wang Q. Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics. Comput Biol Med 2024; 173:108327. [PMID: 38552279 DOI: 10.1016/j.compbiomed.2024.108327] [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: 02/06/2024] [Revised: 03/07/2024] [Accepted: 03/17/2024] [Indexed: 04/17/2024]
Abstract
Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients' suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.
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Affiliation(s)
- Yan Fu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China
| | - Chengzhao Wang
- College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Zhimin Wu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xiaoguang Zhang
- Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China; College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yan Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xu Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Fangfang Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yujuan Chen
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yang Zhang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
| | - Huanhuan Zhao
- Department of Obstetrics and Gynecology, The Fourth Hospital of Hebei Medical University, 050011, China.
| | - Qiao Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
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Sun T, Chen X, Yan H, Liu J. The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization. Medicine (Baltimore) 2024; 103:e37085. [PMID: 38363931 PMCID: PMC10869068 DOI: 10.1097/md.0000000000037085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/05/2024] [Indexed: 02/18/2024] Open
Abstract
This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.
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Affiliation(s)
- Tao Sun
- Department of Hematology and Oncology Laboratory, The Affiliated Shaoyang Hospital, Hengyang Medical School, University of South China
| | - Xiaoyang Chen
- Department of Scientific Research and Teaching, The Affiliated Shaoyang Hospital, Hengyang Medical School, University of South China
| | - Hui Yan
- Department of Hematology and Oncology Laboratory, The Affiliated Shaoyang Hospital, Hengyang Medical School, University of South China
| | - Jun Liu
- Department of Scientific Research, The First Affiliated Hospital of Shaoyang University, Shaoyang, Hunan Province, China
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Wang W, Zhen S, Ping Y, Wang L, Zhang Y. Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring. Front Oncol 2024; 14:1331215. [PMID: 38384814 PMCID: PMC10879439 DOI: 10.3389/fonc.2024.1331215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.
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Affiliation(s)
- Wenqian Wang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Key Laboratory for Tumor Immunology and Biotherapy of Henan Province, Zhengzhou, Henan, China
| | - Shanshan Zhen
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Key Laboratory for Tumor Immunology and Biotherapy of Henan Province, Zhengzhou, Henan, China
| | - Yu Ping
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Key Laboratory for Tumor Immunology and Biotherapy of Henan Province, Zhengzhou, Henan, China
| | - Liping Wang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhang
- Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Key Laboratory for Tumor Immunology and Biotherapy of Henan Province, Zhengzhou, Henan, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, Henan, China
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Benabdelkamel H, Jaber MA, Akkour K, AlMalki RH, Alfadda AA, Masood A, Joy SS, Alhalal H, Alwehaibi MA, Arafah M, Alshehri E, Abdel Rahman AM. Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer. Metabolites 2024; 14:109. [PMID: 38393001 PMCID: PMC10890097 DOI: 10.3390/metabo14020109] [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: 12/26/2023] [Revised: 01/27/2024] [Accepted: 01/30/2024] [Indexed: 02/25/2024] Open
Abstract
Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.
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Affiliation(s)
- Hicham Benabdelkamel
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
| | - Malak A Jaber
- Pharmaceutical Medicinal Chemistry & Pharmacognosy, Faculty of Pharmacy and Medical Sciences, University of Petra, Amman 1196, Jordan
| | - Khalid Akkour
- Obstetrics and Gynecology Department, College of Medicine, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Reem H AlMalki
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11461, Saudi Arabia
| | - Assim A Alfadda
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
- Department of Medicine, College of Medicine, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Afshan Masood
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
| | - Salini Scaria Joy
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
| | - Hani Alhalal
- Obstetrics and Gynecology Department, College of Medicine, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Moudi A Alwehaibi
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
| | - Maria Arafah
- Department of Pathology, College of Medicine, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Eman Alshehri
- Obstetrics and Gynecology Department, College of Medicine, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Anas M Abdel Rahman
- Metabolomics Section, Department of Clinical Genomics, Center for Genome Medicine, King Faisal Specialist Hospital and Research Centre (KFSHRC), Riyadh 11211, Saudi Arabia
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Behrooz AB, Cordani M, Fiore A, Donadelli M, Gordon JW, Klionsky DJ, Ghavami S. The obesity-autophagy-cancer axis: Mechanistic insights and therapeutic perspectives. Semin Cancer Biol 2024; 99:24-44. [PMID: 38309540 DOI: 10.1016/j.semcancer.2024.01.003] [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: 09/20/2023] [Revised: 01/19/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
Autophagy, a self-degradative process vital for cellular homeostasis, plays a significant role in adipose tissue metabolism and tumorigenesis. This review aims to elucidate the complex interplay between autophagy, obesity, and cancer development, with a specific emphasis on how obesity-driven changes affect the regulation of autophagy and subsequent implications for cancer risk. The burgeoning epidemic of obesity underscores the relevance of this research, particularly given the established links between obesity, autophagy, and various cancers. Our exploration delves into hormonal influence, notably INS (insulin) and LEP (leptin), on obesity and autophagy interactions. Further, we draw attention to the latest findings on molecular factors linking obesity to cancer, including hormonal changes, altered metabolism, and secretory autophagy. We posit that targeting autophagy modulation may offer a potent therapeutic approach for obesity-associated cancer, pointing to promising advancements in nanocarrier-based targeted therapies for autophagy modulation. However, we also recognize the challenges inherent to these approaches, particularly concerning their precision, control, and the dual roles autophagy can play in cancer. Future research directions include identifying novel biomarkers, refining targeted therapies, and harmonizing these approaches with precision medicine principles, thereby contributing to a more personalized, effective treatment paradigm for obesity-mediated cancer.
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Affiliation(s)
- Amir Barzegar Behrooz
- Department of Human Anatomy and Cell Science, University of Manitoba, College of Medicine, Winnipeg, Manitoba, Canada; Electrophysiology Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Marco Cordani
- Department of Biochemistry and Molecular Biology, School of Biology, Complutense University, Madrid, Spain; Instituto de Investigaciones Sanitarias San Carlos (IdISSC), Madrid, Spain
| | - Alessandra Fiore
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Massimo Donadelli
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Joseph W Gordon
- Department of Human Anatomy and Cell Science, University of Manitoba, College of Medicine, Winnipeg, Manitoba, Canada; Children Hospital Research Institute of Manitoba, University of Manitoba, Winnipeg, MB, Canada
| | - Daniel J Klionsky
- Life Sciences Institute and Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Saeid Ghavami
- Life Sciences Institute and Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI, USA; Faculty of Medicine in Zabrze, University of Technology in Katowice, 41-800 Zabrze, Poland; Research Institute of Oncology and Hematology, Cancer Care Manitoba-University of Manitoba, Winnipeg, Manitoba, Canada; Children Hospital Research Institute of Manitoba, University of Manitoba, Winnipeg, MB, Canada.
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Chen J, Lu H, Cao D, Sun J, Qi F, Liu X, Liu J, Yang J, Yu M, Zhou H, Cheng N, Wang J, Zhang Y, Peng P, Wang T, Shen K, Sun W. Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry. Metabolomics 2024; 20:18. [PMID: 38281200 DOI: 10.1007/s11306-023-02085-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 12/19/2023] [Indexed: 01/30/2024]
Abstract
OBJECTIVE This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC. METHOD This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models. RESULTS Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively. CONCLUSION The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.
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Affiliation(s)
- Junyu Chen
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Obstetrics and Gynecology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Hezhen Lu
- China-Japan Union Hospital of Jilin University, Changchun, China
| | - Dongyan Cao
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
| | - Jiameng Sun
- Core Facility of Instrument, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Feng Qi
- Core Facility of Instrument, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoyan Liu
- Core Facility of Instrument, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Jiaqi Liu
- China-Japan Union Hospital of Jilin University, Changchun, China
| | - Jiaxin Yang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Mei Yu
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Huimei Zhou
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ninghai Cheng
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jinhui Wang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ying Zhang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Peng Peng
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Tao Wang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Keng Shen
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wei Sun
- China-Japan Union Hospital of Jilin University, Changchun, China.
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9
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Aboud O, Liu Y, Dahabiyeh L, Abuaisheh A, Li F, Aboubechara JP, Riess J, Bloch O, Hodeify R, Tagkopoulos I, Fiehn O. Profile Characterization of Biogenic Amines in Glioblastoma Patients Undergoing Standard-of-Care Treatment. Biomedicines 2023; 11:2261. [PMID: 37626757 PMCID: PMC10452138 DOI: 10.3390/biomedicines11082261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 07/29/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
INTRODUCTION Biogenic amines play important roles throughout cellular metabolism. This study explores a role of biogenic amines in glioblastoma pathogenesis. Here, we characterize the plasma levels of biogenic amines in glioblastoma patients undergoing standard-of-care treatment. METHODS We examined 138 plasma samples from 36 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma at multiple stages of treatment. Untargeted gas chromatography-time of flight mass spectrometry (GC-TOF MS) was used to measure metabolite levels. Machine learning approaches were then used to develop a predictive tool based on these datasets. RESULTS Surgery was associated with increased levels of 12 metabolites and decreased levels of 11 metabolites. Chemoradiation was associated with increased levels of three metabolites and decreased levels of three other metabolites. Ensemble learning models, specifically random forest (RF) and AdaBoost (AB), accurately classified treatment phases with high accuracy (RF: 0.81 ± 0.04, AB: 0.78 ± 0.05). The metabolites sorbitol and N-methylisoleucine were identified as important predictive features and confirmed via SHAP. CONCLUSION To our knowledge, this is the first study to describe plasma biogenic amine signatures throughout the treatment of patients with glioblastoma. A larger study is needed to confirm these results with hopes of developing a diagnostic algorithm.
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Affiliation(s)
- Orwa Aboud
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
| | - Yin Liu
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Department of Ophthalmology, University of California, Davis, Sacramento, CA 95817, USA
| | - Lina Dahabiyeh
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Ahmad Abuaisheh
- School of Medicine, Al Balqa Applied University, Al-Salt 19117, Jordan
| | - Fangzhou Li
- Department of Computer Science, University of California, Davis, Sacramento, CA 95616, USA
- Genome Center, University of California, Davis, Sacramento, CA 95616, USA
- USDA/NSF AI Institute for Next Generation Food Systems (AIFS), Davis, CA 95616, USA
| | | | - Jonathan Riess
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
- Department of Internal Medicine, Division of Hematology and Oncology, University of California, Davis, Sacramento, CA 95817, USA
| | - Orin Bloch
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
| | - Rawad Hodeify
- Department of Biotechnology, School of Arts and Sciences, American University of Ras Al Khaimah, Ras Al-Khaimah 10021, United Arab Emirates
| | - Ilias Tagkopoulos
- Department of Computer Science, University of California, Davis, Sacramento, CA 95616, USA
- Genome Center, University of California, Davis, Sacramento, CA 95616, USA
- USDA/NSF AI Institute for Next Generation Food Systems (AIFS), Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
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10
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Lee DH, Jin Q, Shi N, Wang F, Bever AM, Li J, Liang L, Hu FB, Song M, Zeleznik OA, Zhang X, Joshi A, Wu K, Jeon JY, Meyerhardt JA, Chan AT, Eliassen AH, Clish CB, Clinton SK, Giovannucci EL, Tabung FK. Dietary Inflammatory and Insulinemic Potentials, Plasma Metabolome and Risk of Colorectal Cancer. Metabolites 2023; 13:744. [PMID: 37367904 PMCID: PMC10304271 DOI: 10.3390/metabo13060744] [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: 04/27/2023] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 06/28/2023] Open
Abstract
The inflammatory and insulinemic potentials of diets have been associated with colorectal cancer risk. However, it is unknown whether the plasma metabolite profiles related to inflammatory diets, or to insulinemic diets, underlie this association. The aim of this study was to evaluate the association between metabolomic profile scores related to the food-based empirical dietary inflammatory patterns (EDIP), the empirical dietary index for hyperinsulinemia (EDIH), and plasma inflammation (CRP, IL-6, TNFα-R2, adiponectin) and insulin (C-peptide) biomarkers, and colorectal cancer risk. Elastic net regression was used to derive three metabolomic profile scores for each dietary pattern among 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study, and associations with CRC risk were examined using multivariable-adjusted logistic regression, in a case-control study of 524 matched pairs nested in both cohorts. Among 186 known metabolites, 27 were significantly associated with both the EDIP and inflammatory biomarkers, and 21 were significantly associated with both the EDIH and C-peptide. In men, odds ratios (ORs) of colorectal cancer, per 1 standard deviation (SD) increment in metabolomic score, were 1.91 (1.31-2.78) for the common EDIP and inflammatory-biomarker metabolome, 1.12 (0.78-1.60) for EDIP-only metabolome, and 1.65 (1.16-2.36) for the inflammatory-biomarkers-only metabolome. However, no association was found for EDIH-only, C-peptide-only, and the common metabolomic signatures in men. Moreover, the metabolomic signatures were not associated with colorectal cancer risk among women. Metabolomic profiles reflecting pro-inflammatory diets and inflammation biomarkers were associated with colorectal cancer risk in men, while no association was found in women. Larger studies are needed to confirm our findings.
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Affiliation(s)
- Dong Hoon Lee
- Department of Sport Industry Studies, Yonsei University, Seoul 03722, Republic of Korea; (D.H.L.)
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Qi Jin
- Department of Exercise and Nutrition Sciences, Moyes College of Education, Weber State University, Ogden, UT 84408, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
| | - Ni Shi
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Alaina M. Bever
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
- Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Oana A. Zeleznik
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Amit Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
- Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Kana Wu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Justin Y. Jeon
- Department of Sport Industry Studies, Yonsei University, Seoul 03722, Republic of Korea; (D.H.L.)
- Cancer Prevention Center, Yonsei Cancer Center, Seoul 03722, Republic of Korea
| | - Jeffrey A. Meyerhardt
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Andrew T. Chan
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
- Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - A. Heather Eliassen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Clary B. Clish
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Steven K. Clinton
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Edward L. Giovannucci
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Fred K. Tabung
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH 43220, USA
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11
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Romano A, Rižner TL, Werner HMJ, Semczuk A, Lowy C, Schröder C, Griesbeck A, Adamski J, Fishman D, Tokarz J. Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review. Front Oncol 2023; 13:1120178. [PMID: 37091170 PMCID: PMC10118013 DOI: 10.3389/fonc.2023.1120178] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/06/2023] [Indexed: 04/09/2023] Open
Abstract
Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.
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Affiliation(s)
- Andrea Romano
- Department of Gynaecology, Maastricht University Medical Centre (MUMC), Maastricht, Netherlands
- GROW – School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands
- *Correspondence: Andrea Romano, ; Tea Lanišnik Rižner,
| | - Tea Lanišnik Rižner
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- *Correspondence: Andrea Romano, ; Tea Lanišnik Rižner,
| | - Henrica Maria Johanna Werner
- Department of Gynaecology, Maastricht University Medical Centre (MUMC), Maastricht, Netherlands
- GROW – School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands
| | - Andrzej Semczuk
- Department of Gynaecology, Lublin Medical University, Lublin, Poland
| | | | | | | | - Jerzy Adamski
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Dmytro Fishman
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Quretec Ltd., Tartu, Estonia
| | - Janina Tokarz
- Institute for Diabetes and Cancer, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
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12
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Hao C, Lin S, Liu P, Liang W, Li Z, Li Y. Potential serum metabolites and long-chain noncoding RNA biomarkers for endometrial cancer tissue. J Obstet Gynaecol Res 2023; 49:725-743. [PMID: 36510632 DOI: 10.1111/jog.15494] [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: 06/26/2022] [Revised: 10/05/2022] [Accepted: 10/28/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Endometrial carcinoma (EC) is one of the most common tumors in the female reproductive system. There are nearly 200 000 new cases every year. It is the third most common gynecological malignant tumor leading to female death. The incidence rate is closely related to lifestyle, and the incidence rate varies in different regions. The incidence rate of EC is ranking the first in the female reproductive system cancer just second only to breast, lung, and colorectal cancer in North America and Europe and the incidence rate of EC is only second, followed by breast cancer and cervical cancer in China. PURPOSE The potential metabolic markers of endometrial cancer were screened by liquid chromatograph mass spectrometer (LC-MS), and the tissues of patients with hysteromyoma and endometrial cancer were sequenced to explore the relationship between the disease and change in the content of long-chain noncoding RNA (lncRNA). METHODS Serum and tissue samples were collected from patients with endometrial dysplasia, endometrial cancer stage I, and endometrial cancer stage III. The metabolites in all serum samples were extracted, and the metabolites in all samples were detected by LC-MS/MS technology. The Pareto-scaling method was used for normalization, and the MetaboAnalyst 4.0 software was used for different analyses. The T test between groups showed that p ≤ 0.05 was regarded as the metabolite with a difference. Further, the function of differential metabolites was determined by metabolite function enrichment and co-expression analysis. Meanwhile, the differentially expressed lncRNA was detected by Illumina second-generation high-throughput sequencing technology, and the expression was analyzed by DEGseq software. Different lncRNA were screened according to p < 0.05. LncRNA with significant differences were screened by p < 0.01, q < 0.001, fold change ≥2, and false discovery rate (FDR) ≤0.001. RESULTS Through synthesis of T test, cluster heatmap, and ROC curve analysis, five biomarkers with potential diagnostic ability were obtained, including 2,3-Pyridinedicarboxylic acid (area under the curve (AUC) = 0.69), Hematommic acid, ethyl ester (AUC = 0.69), Maltitol (AUC = 0.69), 13(S)-HODE (AUC = 0.88), and D-Mannitol (AUC = 0.69) had potential diagnostic ability between EC phase I versus EC phase III. At the same time, lncRNA sequencing results showed that when endometrial atypical hyperplasia continued to change, including LINC00511, PVT1, and IQCH-AS1 (downregulated), and only changed significantly in the endometrial dysplasia group, including MALAT1, CARMN (downregulated) and LINC00648, BISPR, LINC01534, and LINC00930 (upregulated). Moreover, both differential metabolites and differential lncRNA were annotated to the lipid metabolism pathway, suggesting that this pathway played an important role in the occurrence and development of endometrial carcinoma. CONCLUSIONS It can combine the results of metabolomics and lncRNA sequencing to assist in the early diagnosis of endometrial precancerous lesions and endometrial cancer patients, to enhance the sensitivity and specificity of diagnosis, which has a certain clinical application prospect.
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Affiliation(s)
- Chenjun Hao
- Gynaecology and Obstetrics Department, Maternal and Child Health Hospital of PanYu District, Guangzhou, China
| | - Shaodan Lin
- Gynaecology and Obstetrics Department, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ping Liu
- Gynaecology and Obstetrics Department, Maternal and Child Health Hospital of PanYu District, Guangzhou, China
| | - Weiguo Liang
- Gynaecology and Obstetrics Department, Maternal and Child Health Hospital of PanYu District, Guangzhou, China
| | - Zhi Li
- Gynaecology and Obstetrics Department, Maternal and Child Health Hospital of PanYu District, Guangzhou, China
| | - Yanqiu Li
- Gynaecology and Obstetrics Department, Maternal and Child Health Hospital of PanYu District, Guangzhou, China
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13
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Paul D, Nedelcu AM. The underexplored links between cancer and the internal body climate: Implications for cancer prevention and treatment. Front Oncol 2022; 12:1040034. [PMID: 36620608 PMCID: PMC9815514 DOI: 10.3389/fonc.2022.1040034] [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: 09/08/2022] [Accepted: 11/25/2022] [Indexed: 12/24/2022] Open
Abstract
In order to effectively manage and cure cancer we should move beyond the general view of cancer as a random process of genetic alterations leading to uncontrolled cell proliferation or simply a predictable evolutionary process involving selection for traits that increase cell fitness. In our view, cancer is a systemic disease that involves multiple interactions not only among cells within tumors or between tumors and surrounding tissues but also with the entire organism and its internal "milieu". We define the internal body climate as an emergent property resulting from spatial and temporal interactions among internal components themselves and with the external environment. The body climate itself can either prevent, promote or support cancer initiation and progression (top-down effect; i.e., body climate-induced effects on cancer), as well as be perturbed by cancer (bottom-up effect; i.e., cancer-induced body climate changes) to further favor cancer progression and spread. This positive feedback loop can move the system towards a "cancerized" organism and ultimately results in its demise. In our view, cancer not only affects the entire system; it is a reflection of an imbalance of the entire system. This model provides an integrated framework to study all aspects of cancer as a systemic disease, and also highlights unexplored links that can be altered to both prevent body climate changes that favor cancer initiation, progression and dissemination as well as manipulate or restore the body internal climate to hinder the success of cancer inception, progression and metastasis or improve therapy outcomes. To do so, we need to (i) identify cancer-relevant factors that affect specific climate components, (ii) develop 'body climate biomarkers', (iii) define 'body climate scores', and (iv) develop strategies to prevent climate changes, stop or slow the changes, or even revert the changes (climate restoration).
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Affiliation(s)
- Doru Paul
- Weill Cornell Medicine, New York, NY, United States,*Correspondence: Doru Paul,
| | - Aurora M. Nedelcu
- Biology Department, University of New Brunswick, Fredericton, NB, Canada
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14
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Breeur M, Ferrari P, Dossus L, Jenab M, Johansson M, Rinaldi S, Travis RC, His M, Key TJ, Schmidt JA, Overvad K, Tjønneland A, Kyrø C, Rothwell JA, Laouali N, Severi G, Kaaks R, Katzke V, Schulze MB, Eichelmann F, Palli D, Grioni S, Panico S, Tumino R, Sacerdote C, Bueno-de-Mesquita B, Olsen KS, Sandanger TM, Nøst TH, Quirós JR, Bonet C, Barranco MR, Chirlaque MD, Ardanaz E, Sandsveden M, Manjer J, Vidman L, Rentoft M, Muller D, Tsilidis K, Heath AK, Keun H, Adamski J, Keski-Rahkonen P, Scalbert A, Gunter MJ, Viallon V. Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition. BMC Med 2022; 20:351. [PMID: 36258205 PMCID: PMC9580145 DOI: 10.1186/s12916-022-02553-4] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/05/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.
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Affiliation(s)
- Marie Breeur
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Pietro Ferrari
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Mazda Jenab
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Mattias Johansson
- Genetics Branch, International Agency for Research on Cancer, 69372 CEDEX 08, Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Tim J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University Hospital and Aarhus University, DK-8200, Aarhus N, Denmark
| | - Kim Overvad
- Department of Public Health, Aarhus University, DK-8000, Aarhus C, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center Diet, Genes and Environment Nutrition and Biomarkers, DK-2100, Copenhagen, Denmark
| | - Cecilie Kyrø
- Danish Cancer Society Research Center Diet, Genes and Environment Nutrition and Biomarkers, DK-2100, Copenhagen, Denmark
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Nasser Laouali
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, 94800, Villejuif, France
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558, Nuthetal, Germany
| | - Fabian Eichelmann
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558, Nuthetal, Germany
- German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany
| | - Domenico Palli
- Institute of Cancer Research, Prevention and Clinical Network (ISPRO), 50139, Florence, Italy
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, 80131, Naples, Italy
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research, AIRE-ONLUS, 97100, Ragusa, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology Città della Salute e della Scienza University-Hospital, 10126, Turin, Italy
| | - Bas Bueno-de-Mesquita
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720, BA, Bilthoven, The Netherlands
| | - Karina Standahl Olsen
- Department of Community Medicine, UiT The Arctic University of Norway, N-9037, Tromsø, Norway
| | | | - Therese Haugdahl Nøst
- Department of Community Medicine, UiT The Arctic University of Norway, N-9037, Tromsø, Norway
| | - J Ramón Quirós
- Public Health Directorate, 33006, Oviedo, Asturias, Spain
| | - Catalina Bonet
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
| | - Miguel Rodríguez Barranco
- Escuela Andaluza de Salud Pública (EASP), 18011, Granada, Spain
- Instituto de Investigación Biosanitaria ibs. GRANADA, 18012, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
| | - María-Dolores Chirlaque
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia University, 30003, Murcia, Spain
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029, Madrid, Spain
- Navarra Public Health Institute, 31003, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008, Pamplona, Spain
| | - Malte Sandsveden
- Department of Clinical Sciences Malmö Lund University, SE-214 28, Malmö, Sweden
| | - Jonas Manjer
- Departement of Surgery, Skåne University Hospital Malmö, Lund University, SE-214 28, Malmö, Sweden
| | - Linda Vidman
- Department of Radiation Sciences, Oncology Umeå University, SE-901 87, Umeå, Sweden
| | - Matilda Rentoft
- Department of Radiation Sciences, Oncology Umeå University, SE-901 87, Umeå, Sweden
| | - David Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Kostas Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Hector Keun
- Department of Surgery and Cancer, Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, 1000, Ljubljana, Slovenia
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Augustin Scalbert
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France
| | - Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, NME Branch, 69372 CEDEX 08, Lyon, France.
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Melatonin Regulates the Daily Levels of Plasma Amino Acids, Acylcarnitines, Biogenic Amines, Sphingomyelins, and Hexoses in a Xenograft Model of Triple Negative Breast Cancer. Int J Mol Sci 2022; 23:ijms23169105. [PMID: 36012374 PMCID: PMC9408859 DOI: 10.3390/ijms23169105] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/04/2022] [Accepted: 08/12/2022] [Indexed: 11/17/2022] Open
Abstract
Metabolic dysregulation as a reflection of specific metabolite production and its utilization is a common feature of many human neoplasms. Melatonin, an indoleamine that is highly available during darkness, has a variety of metabolic functions in solid tumors. Because plasma metabolites undergo circadian changes, we investigated the role of melatonin on the profile of amino acids (AAs), biogenic amines, carnitines, sphingolipids, and hexoses present in the plasma of mice bearing xenograft triple negative breast cancer (MDA-MB-231 cells) over 24 h. Plasma concentrations of nine AAs were reduced by melatonin, especially during the light phase, with a profile closer to that of non-breast cancer (BC) animals. With respect to acylcarnitine levels, melatonin reduced 12 out of 24 molecules in BC-bearing animals compared to their controls, especially at 06:00 h and 15:00 h. Importantly, melatonin reduced the concentrations of asymmetric dimethylarginine, carnosine, histamine, kynurenine, methionine sulfoxide, putrescine, spermidine, spermine, and symmetric dimethylarginine, which are associated with the BC metabolite sets. Melatonin also led to reduced levels of sphingomyelins and hexoses, which showed distinct daily variations over 24 h. These results highlight the role of melatonin in controlling the levels of plasma metabolites in human BC xenografts, which may impact cancer bioenergetics, in addition to emphasizing the need for a more accurate examination of its metabolomic changes at different time points.
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Kliemann N, Ould Ammar R, Biessy C, Gicquiau A, Katzke V, Kaaks R, Tjønneland A, Olsen A, Sánchez MJ, Crous-Bou M, Pasanisi F, Tin Tin S, Perez-Cornago A, Aune D, Christakoudi S, Heath AK, Colorado-Yohar SM, Grioni S, Skeie G, Sartor H, Idahl A, Rylander C, May AM, Weiderpass E, Freisling H, Playdon MC, Rinaldi S, Murphy N, Huybrechts I, Dossus L, Gunter MJ. Metabolically Defined Body Size Phenotypes and Risk of Endometrial Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cancer Epidemiol Biomarkers Prev 2022; 31:1359-1367. [PMID: 35437568 PMCID: PMC9355542 DOI: 10.1158/1055-9965.epi-22-0160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/17/2022] [Accepted: 04/13/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. METHODS The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case-control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; <1st tertile) and metabolically unhealthy (MU; ≥1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW); body mass index (BMI)<25 kg/m2 or waist circumference (WC)<80 cm or waist-to-hip ratio (WHR)<0.8) and overweight (OW; BMI≥25 kg/m2 or WC≥80 cm or WHR≥0.8) status, generating four phenotype groups for each anthropometric measure: (i) MH/NW, (ii) MH/OW, (iii) MU/NW, and (iv) MU/OW. RESULTS In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW [ORWC, 1.48; 95% confidence interval (CI), 1.05-2.10 and ORWHR, 1.68; 95% CI, 1.21-2.35] and MU/OW (ORBMI, 2.38; 95% CI, 1.73-3.27; ORWC, 2.69; 95% CI, 1.92-3.77 and ORWHR, 1.83; 95% CI, 1.32-2.54). MH/OW individuals were also at increased endometrial cancer risk compared with MH/NW individuals (ORWC, 1.94; 95% CI, 1.24-3.04). CONCLUSIONS Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, OW status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity-related pathways are relevant for the development of this cancer beyond insulin. IMPACT Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se.
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Affiliation(s)
| | | | - Carine Biessy
- International Agency for Research on Cancer, Lyon, France
| | | | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Anja Olsen
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - 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
| | - Marta Crous-Bou
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO)—Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Fabrizio Pasanisi
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Sandar Tin Tin
- Nuffield Department of Population Health, Cancer Epidemiology Unit, University of Oxford, Oxford, England
| | - Aurora Perez-Cornago
- Nuffield Department of Population Health, Cancer Epidemiology Unit, University of Oxford, Oxford, England
| | - Dagfinn Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Nutrition, Oslo New University College, Oslo, Norway
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Inflammation Biology, King's College London, London, United Kingdom
| | - Alicia K. Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Sandra M. Colorado-Yohar
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 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
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy
| | - Guri Skeie
- Department of Community Medicine, UIT—The Arctic University of Norway, Tromsø, Norway
| | - Hanna Sartor
- Diagnostic Radiology, Lund University, Lund, Sweden
| | - Annika Idahl
- Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umeå, Sweden
| | - Charlotta Rylander
- Department of Community Medicine, UIT—The Arctic University of Norway, Tromsø, Norway
| | - Anne M. May
- Julius Center for Health Sciences and Primary care, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | | | - Mary C. Playdon
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah
- Cancer Control and Population Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Sabina Rinaldi
- International Agency for Research on Cancer, Lyon, France
| | - Neil Murphy
- International Agency for Research on Cancer, Lyon, France
| | | | - Laure Dossus
- International Agency for Research on Cancer, Lyon, France
| | - Marc J. Gunter
- International Agency for Research on Cancer, Lyon, France
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Yi R, Xie L, Wang X, Shen C, Chen X, Qiao L. Multi-Omic Profiling of Multi-Biosamples Reveals the Role of Amino Acid and Nucleotide Metabolism in Endometrial Cancer. Front Oncol 2022; 12:861142. [PMID: 35574395 PMCID: PMC9099206 DOI: 10.3389/fonc.2022.861142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 04/01/2022] [Indexed: 11/15/2022] Open
Abstract
Background Endometrial cancer (EC) is one of the most common gynecological cancers. The traditional diagnosis of EC relies on histopathology, which, however, is invasive and may arouse tumor spread. There have been many studies aiming to find the metabolomic biomarkers of EC to improve the early diagnosis of cancer in a non-invasive or minimally invasive way, which can also provide valuable information for understanding the disease. However, most of these studies only analyze a single type of sample by metabolomics, and cannot provide a comprehensive view of the altered metabolism in EC patients. Our study tries to gain a pathway-based view of multiple types of samples for understanding metabolomic disorders in EC by combining metabolomics and proteomics. Methods Forty-four EC patients and forty-three controls were recruited for the research. We collected endometrial tissue, urine, and intrauterine brushing samples. Untargeted metabolomics and untargeted proteomics were both performed on the endometrial tissue samples, while only untargeted metabolomics was performed on the urine and intrauterine brushing samples. Results By integrating the differential metabolites and proteins between EC patients and controls detected in the endometrial tissue samples, we identified several EC-related significant pathways, such as amino acid metabolism and nucleotide metabolism. The significance of these pathways and the potential of metabolite biomarker-based diagnosis were then further verified by using urine and intrauterine brushing samples. It was found that the regulation of metabolites involved in the significant pathways showed similar trends in the intrauterine brushings and the endometrial tissue samples, while opposite trends in the urine and the endometrial tissue samples. Conclusions With multi-omics characterization of multi-biosamples, the metabolomic changes related to EC are illustrated in a pathway-based way. The network of altered metabolites and related proteins provides a comprehensive view of altered metabolism in the endometrial tissue samples. The verification of these critical pathways by using urine and intrauterine brushing samples provides evidence for the possible non-invasive or minimally invasive biopsy for EC diagnosis in the future.
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Affiliation(s)
- Runqiu Yi
- Department of Chemistry, Shanghai Stomatological Hospital, and Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai, China
| | - Liying Xie
- Department of Chemistry, Shanghai Stomatological Hospital, and Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai, China
| | | | | | - Xiaojun Chen
- Department of Chemistry, Shanghai Stomatological Hospital, and Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai, China
- *Correspondence: Liang Qiao, ; Xiaojun Chen,
| | - Liang Qiao
- Department of Chemistry, Shanghai Stomatological Hospital, and Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai, China
- *Correspondence: Liang Qiao, ; Xiaojun Chen,
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18
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Yan X, Zhao W, Wei J, Yao Y, Sun G, Wang L, Zhang W, Chen S, Zhou W, Zhao H, Li X, Xiao Y, Li Y. A serum lipidomics study for the identification of specific biomarkers for endometrial polyps to distinguish them from endometrial cancer or hyperplasia. Int J Cancer 2022; 150:1549-1559. [PMID: 35076938 DOI: 10.1002/ijc.33943] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/09/2022] [Accepted: 01/13/2022] [Indexed: 11/10/2022]
Affiliation(s)
- Xingxu Yan
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Wen Zhao
- Department of Gynaecology and Obstetrics People's Hospital of Guangrao County, 257300 Dongying Shandong China
| | - Jinxia Wei
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Yaqi Yao
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Guijiang Sun
- Department of Kidney Disease and Blood Purification The Second Hospital of Tianjin Medical University Tianjin China
| | - Lei Wang
- Department of Oncology Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University Tianjin China
| | - Wenqing Zhang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Siyu Chen
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Wenjie Zhou
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Huan Zhao
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Xiaomeng Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
| | - Yu Xiao
- Hysteroscopic Center, FuXing Hospital Capital Medical University Beijing China
| | - Yubo Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine Tianjin China
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Endometrial Cancer After Pancreas-After-Kidney Transplantation: A Case Report and Review of the Literature. Transplant Proc 2022; 54:560-564. [PMID: 35067377 DOI: 10.1016/j.transproceed.2021.12.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 12/29/2021] [Indexed: 01/20/2023]
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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: 3] [Impact Index Per Article: 1.0] [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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21
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Viallon V, His M, Rinaldi S, Breeur M, Gicquiau A, Hemon B, Overvad K, Tjønneland A, Rostgaard-Hansen AL, Rothwell JA, Lecuyer L, Severi G, Kaaks R, Johnson T, Schulze MB, Palli D, Agnoli C, Panico S, Tumino R, Ricceri F, Verschuren WMM, Engelfriet P, Onland-Moret C, Vermeulen R, Nøst TH, Urbarova I, Zamora-Ros R, Rodriguez-Barranco M, Amiano P, Huerta JM, Ardanaz E, Melander O, Ottoson F, Vidman L, Rentoft M, Schmidt JA, Travis RC, Weiderpass E, Johansson M, Dossus L, Jenab M, Gunter MJ, Lorenzo Bermejo J, Scherer D, Salek RM, Keski-Rahkonen P, Ferrari P. A New Pipeline for the Normalization and Pooling of Metabolomics Data. Metabolites 2021; 11:631. [PMID: 34564446 PMCID: PMC8467830 DOI: 10.3390/metabo11090631] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/10/2021] [Accepted: 09/13/2021] [Indexed: 01/10/2023] Open
Abstract
Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.
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Affiliation(s)
- Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Marie Breeur
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Audrey Gicquiau
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Bertrand Hemon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Kim Overvad
- Department of Public Health, Aarhus University Bartholins Alle 2, DK-8000 Aarhus, Denmark;
| | - Anne Tjønneland
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark; (A.T.); (A.L.R.-H.)
| | | | - Joseph A. Rothwell
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
| | - Lucie Lecuyer
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
| | - Gianluca Severi
- UVSQ, Inserm, CESP U1018, “Exposome and Heredity” Team, Université Paris-Saclay, Gustave Roussy, 94800 Villejuif, France; (J.A.R.); (L.L.); (G.S.)
- Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence, 50134 Florence, Italy
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (R.K.); (T.J.)
| | - Theron Johnson
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (R.K.); (T.J.)
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany;
- Institute of Nutritional Science, University of Potsdam, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), 50139 Florence, Italy;
| | - Claudia Agnoli
- Epidemiology and Prevention Unit Department of Research, Fondazione IRCCS—Istituto Nazionale dei Tumori, 20133 Milan, Italy;
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, 80131 Naples, Italy;
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7), 97100 Ragusa, Italy;
| | - Fulvio Ricceri
- Department of Clinical and Biological Sciences, University of Turin, 10043 Orbassano, Italy;
- Unit of Epidemiology, Regional Health Service ASL TO3, 10095 Grugliasco, Italy
| | - W. M. Monique Verschuren
- National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands; (W.M.M.V.); (P.E.)
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
| | - Peter Engelfriet
- National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands; (W.M.M.V.); (P.E.)
| | - Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
| | - Roel Vermeulen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands; (C.O.-M.); (R.V.)
- Institute for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, 3584 CM Utrecht, The Netherlands
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, P.O. Box 6050, 9037 Tromsø, Norway; (T.H.N.); (I.U.)
| | - Ilona Urbarova
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, P.O. Box 6050, 9037 Tromsø, Norway; (T.H.N.); (I.U.)
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L’Hospitalet de Llobregat, Spain;
| | - Miguel Rodriguez-Barranco
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain;
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
| | - Pilar Amiano
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastián, Spain
- Biodonostia Health Research Institute, Group of Epidemiology of Chronic and Communicable Diseases, 20014 San Sebastián, Spain
| | - José Maria Huerta
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, 30007 Murcia, Spain
| | - Eva Ardanaz
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain; (P.A.); (J.M.H.); (E.A.)
- Navarra Public Health Institute, 31003 Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
| | - Olle Melander
- Department of Clincal Sciences, Lund University, SE-21 428 Malmö, Sweden;
- Department of Emergency and Internal Medicine, Skåne University Hospital, SE-20 502 Malmö, Sweden
| | - Filip Ottoson
- Department of Immunotechnology, Lund University, SE-22 100 Lund, Sweden;
| | - Linda Vidman
- Department of Radiation Sciences, Oncology, Umeå University, SE-901 87 Umeå, Sweden; (L.V.); (M.R.)
| | - Matilda Rentoft
- Department of Radiation Sciences, Oncology, Umeå University, SE-901 87 Umeå, Sweden; (L.V.); (M.R.)
| | - Julie A. Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (J.A.S.); (R.C.T.)
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (J.A.S.); (R.C.T.)
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France;
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France;
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Mazda Jenab
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Marc J. Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Justo Lorenzo Bermejo
- Statistical Genetics Group, Institute of Medical Biometry, University of Heidelberg, 69120 Heidelberg, Germany; (J.L.B.); (D.S.)
| | - Dominique Scherer
- Statistical Genetics Group, Institute of Medical Biometry, University of Heidelberg, 69120 Heidelberg, Germany; (J.L.B.); (D.S.)
| | - Reza M. Salek
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Pekka Keski-Rahkonen
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
| | - Pietro Ferrari
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69008 Lyon, France; (M.H.); (S.R.); (M.B.); (A.G.); (B.H.); (L.D.); (M.J.); (M.J.G.); (R.M.S.); (P.K.-R.); (P.F.)
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