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Yan F, Liu C, Song D, Zeng Y, Zhan Y, Zhuang X, Qiao T, Wu D, Cheng Y, Chen H. Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer. Cell Biol Toxicol 2024; 40:25. [PMID: 38691184 PMCID: PMC11063108 DOI: 10.1007/s10565-024-09861-w] [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: 11/01/2023] [Accepted: 03/25/2024] [Indexed: 05/03/2024]
Abstract
Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.
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Affiliation(s)
- Furong Yan
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China
| | - Chanjuan Liu
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of Hematology, Xiang'an Hospital, Xiamen University School of Medicine, Xiamen, 361101, China
| | - Dongli Song
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Clinical Bioinformatics, Shanghai, 200032, China
| | - Yiming Zeng
- Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China
| | - Yanxia Zhan
- Department of Hematology, Zhongshan Hospital, Fudan University, 180 Fenglin Rd, Shanghai, 200032, China
| | - Xibing Zhuang
- Department of Hematology, Zhongshan Hospital, Fudan University, 180 Fenglin Rd, Shanghai, 200032, China
| | - Tiankui Qiao
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China
| | - Duojiao Wu
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yunfeng Cheng
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China.
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Clinical Bioinformatics, Shanghai, 200032, China.
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Department of Hematology, Zhongshan Hospital, Fudan University, 180 Fenglin Rd, Shanghai, 200032, China.
| | - Hao Chen
- Department of Thoracic Surgery, Zhongshan-Xuhui Hospital, Fudan University, 366 North Longchuan Rd, Shanghai, 200237, China.
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Chen Y, Gu Y, Rong J, Xu L, Huang X, Zhu J, Chen Z, Mao W. Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study. PeerJ 2024; 12:e17272. [PMID: 38699187 PMCID: PMC11064858 DOI: 10.7717/peerj.17272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/29/2024] [Indexed: 05/05/2024] Open
Abstract
Background Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.
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Affiliation(s)
- Yang Chen
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Yixuan Gu
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Jinhua Rong
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
- College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Luyin Xu
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Xiancong Huang
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Jing Zhu
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Zhongjian Chen
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Weimin Mao
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
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3
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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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Chen S, Li C, Qin Z, Song L, Zhang S, Sun C, Zhuang P, Wang Y, Yang B, Ning L, Li Y. Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis: Identification of Rapid and Noninvasive Biomarker. J Infect Dis 2023; 228:1154-1165. [PMID: 37246562 DOI: 10.1093/infdis/jiad175] [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: 10/14/2022] [Revised: 02/10/2023] [Accepted: 05/26/2023] [Indexed: 05/30/2023] Open
Abstract
BACKGROUND Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB. METHODS A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating characteristic curve were used to evaluate the diagnostic efficacy of biomarkers. RESULTS Seven metabolites were identified and validated. Phenylalanylphenylalanine for distinguishing LC from PTB yielded an area under the curve of 0.89, sensitivity of 71%, and specificity of 92%. It also showed good diagnostic abilities in discovery set and identification set. Compared with that in healthy volunteers (median [interquartile range], 1.57 [1.01, 2.34] μg/mL), it was elevated in LC (4.76 [2.74, 7.08] μg/mL; ratio of median, [ROM] = 3.03, P < .01) and reduced in PTB (1.06 [0.51, 2.09] μg/mL; ROM = 0.68, P < .05). CONCLUSIONS The metabolomic profile of LC and PTB was described and a key biomarker identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from PTB.
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Affiliation(s)
- Siyu Chen
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Chunyan Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Zhonghua Qin
- Department of Clinical Laboratory, Tianjin Haihe Hospital, Tianjin, China
| | - Lili Song
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Shiyuan Zhang
- Intensive Care Unit, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Chongxiang Sun
- Intensive Care Unit, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Pengwei Zhuang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yuming Wang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Bin Yang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Li Ning
- Department of Clinical Laboratory, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yubo Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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5
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Hwang BY, Seo JW, Muftuoglu C, Mert U, Guldaval F, Asadi M, Karakus HS, Goksel T, Veral A, Caner A, Moon MH. Salivary Lipids of Patients with Non-Small Cell Lung Cancer Show Perturbation with Respect to Plasma. Int J Mol Sci 2023; 24:14264. [PMID: 37762567 PMCID: PMC10531690 DOI: 10.3390/ijms241814264] [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: 08/04/2023] [Revised: 09/12/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
A comprehensive lipid profile was analyzed in patients with non-small cell lung cancer (NSCLC) using nanoflow ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry. This study investigated 297 and 202 lipids in saliva and plasma samples, respectively, comparing NSCLC patients to healthy controls. Lipids with significant changes (>2-fold, p < 0.05) were further analyzed in each sample type. Both saliva and plasma exhibited similar lipid alteration patterns in NSCLC, but saliva showed more pronounced changes. Total triglycerides (TGs) increased (>2-3-fold) in plasma and saliva samples. Three specific TGs (50:2, 52:5, and 54:6) were significantly increased in NSCLC for both sample types. A common ceramide species (d18:1/24:0) and phosphatidylinositol 38:4 decreased in both plasma and saliva by approximately two-fold. Phosphatidylserine 36:1 was selectively detected in saliva and showed a subsequent decrease, making it a potential biomarker for predicting lung cancer. We identified 27 salivary and 10 plasma lipids as candidate markers for NSCLC through statistical evaluations. Moreover, this study highlights the potential of saliva in understanding changes in lipid metabolism associated with NSCLC.
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Affiliation(s)
- Bo Young Hwang
- Department of Chemistry, Yonsei University, Seodaemun-gu, Seoul 03722, Republic of Korea; (B.Y.H.); (J.W.S.)
| | - Jae Won Seo
- Department of Chemistry, Yonsei University, Seodaemun-gu, Seoul 03722, Republic of Korea; (B.Y.H.); (J.W.S.)
| | - Can Muftuoglu
- Institute of Health Sciences, Department of Basic Oncology, Ege University, Izmir 35040, Turkey; (C.M.); (M.A.)
- Translational Pulmonary Research Center, Ege University (EgeSAM), Izmir 35040, Turkey; (U.M.); (T.G.)
| | - Ufuk Mert
- Translational Pulmonary Research Center, Ege University (EgeSAM), Izmir 35040, Turkey; (U.M.); (T.G.)
- Ataturk Health Care Vocational School, Ege University, Izmir 35040, Turkey
| | - Filiz Guldaval
- Chest Disease Department, Izmir Dr. Suat Seren Chest Disease and Surgery Training and Research Hospital, Izmir 35170, Turkey;
| | - Milad Asadi
- Institute of Health Sciences, Department of Basic Oncology, Ege University, Izmir 35040, Turkey; (C.M.); (M.A.)
- Translational Pulmonary Research Center, Ege University (EgeSAM), Izmir 35040, Turkey; (U.M.); (T.G.)
| | | | - Tuncay Goksel
- Translational Pulmonary Research Center, Ege University (EgeSAM), Izmir 35040, Turkey; (U.M.); (T.G.)
- Department of Pulmonary Medicine, Faculty of Medicine, Ege University, Izmir 35040, Turkey;
| | - Ali Veral
- Department of Pathology, Faculty of Medicine, Ege University, Izmir 35040, Turkey;
| | - Ayse Caner
- Institute of Health Sciences, Department of Basic Oncology, Ege University, Izmir 35040, Turkey; (C.M.); (M.A.)
- Translational Pulmonary Research Center, Ege University (EgeSAM), Izmir 35040, Turkey; (U.M.); (T.G.)
- Department of Parasitology, Faculty of Medicine, Ege University, Izmir 35040, Turkey
| | - Myeong Hee Moon
- Department of Chemistry, Yonsei University, Seodaemun-gu, Seoul 03722, Republic of Korea; (B.Y.H.); (J.W.S.)
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Gruden E, Kienzl M, Hasenoehrl C, Sarsembayeva A, Ristic D, Schmid ST, Maitz K, Taschler U, Hahnefeld L, Gurke R, Thomas D, Kargl J, Schicho R. Tumor microenvironment-derived monoacylglycerol lipase provokes tumor-specific immune responses and lipid profiles. Prostaglandins Leukot Essent Fatty Acids 2023; 196:102585. [PMID: 37573716 DOI: 10.1016/j.plefa.2023.102585] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/02/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023]
Abstract
We recently described that monoacylglycerol lipase (MGL) is present in the tumor microenvironment (TME), increasing tumor growth. In this study we compare the implications of MGL deficiency in the TME in different tumor types. We show that subcutaneous injection of KP (KrasLSL-G12D/p53fl/fl, mouse lung adenocarcinoma) or B16-F10 cells (mouse melanoma) induced tumor growth in MGL wild type (WT) and knockout (KO) mice. MGL deficiency in the TME attenuated the growth of KP cell tumors whereas tumors from B16-F10 cells increased in size. Opposite immune cell profiles were detected between the two tumor types in MGL KO mice. In line with their anti-tumorigenic function, the number of CD8+ effector T cells and eosinophils increased in KP cell tumors of MGL KO vs. WT mice whereas their presence was reduced in B16-F10 cell tumors of MGL KO mice. Differences were seen in lipid profiles between the investigated tumor types. 2-arachidonoylglycerol (2-AG) content significantly increased in KP, but not B16-F10 cell tumors of MGL KO vs. WT mice while other endocannabinoid-related lipids remained unchanged. However, profiles of phospho- and lysophospholipids, sphingomyelins and fatty acids in KP cell tumors were clearly distinct to those measured in B16-F10 cell tumors. Our data indicate that TME-localized MGL impacts tumor growth, as well as levels of 2-AG and other lipids in a tumor specific manner.
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Affiliation(s)
- Eva Gruden
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Melanie Kienzl
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria.
| | - Carina Hasenoehrl
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Arailym Sarsembayeva
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Dusica Ristic
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Sophie Theresa Schmid
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Kathrin Maitz
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Ulrike Taschler
- Institute of Molecular Biosciences, University of Graz, Graz, Austria
| | - Lisa Hahnefeld
- Institute of Clinical Pharmacology, Goethe University, 60590 Frankfurt/Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - Robert Gurke
- Institute of Clinical Pharmacology, Goethe University, 60590 Frankfurt/Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - Dominique Thomas
- Institute of Clinical Pharmacology, Goethe University, 60590 Frankfurt/Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - Julia Kargl
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
| | - Rudolf Schicho
- Otto Loewi Research Center, Division of Pharmacology, Medical University of Graz, Austria
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Li J, Liu K, Ji Z, Wang Y, Yin T, Long T, Shen Y, Cheng L. Serum untargeted metabolomics reveal metabolic alteration of non-small cell lung cancer and refine disease detection. Cancer Sci 2022; 114:680-689. [PMID: 36310111 PMCID: PMC9899604 DOI: 10.1111/cas.15629] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 10/09/2022] [Accepted: 10/14/2022] [Indexed: 01/07/2023] Open
Abstract
This study was performed to characterize the metabolic alteration of non-small-cell lung cancer (NSCLC) and discover blood-based metabolic biomarkers relevant to lung cancer detection. An untargeted metabolomics-based approach was applied in a case-control study with 193 NSCLC patients and 243 healthy controls. Serum metabolomics were determined by using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. We screened differential metabolites based on univariate and multivariate analysis, followed by identification of the metabolites and related pathways. For NSCLC detection, machine learning was employed to develop and validate the model based on the altered serum metabolite features. The serum metabolic pattern of NSCLC was definitely different from the healthy condition. In total, 278 altered features were found in the serum of NSCLC patients comparing with healthy people. About one-fifth of the abundant differential features were identified successfully. The altered metabolites were enriched in metabolic pathways such as phenylalanine metabolism, linoleic acid metabolism, and biosynthesis of bile acids. We demonstrated a panel of 10 metabolic biomarkers which representing excellent discriminating capability for NSCLC discrimination, with a combined area under the curve (AUC) in the validation set of 0.95 (95% CI: 0.91-0.98). Moreover, this model showed a desirable performance for the detection of NSCLC at an early stage (AUC = 0.95, 95% CI: 0.92-0.97). Our study offers a perspective on NSCLC metabolic alteration. The finding of the biomarkers might shed light on the clinical detection of lung cancer, especially for those cancers in an early stage in Chinese population.
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Affiliation(s)
- Jiaoyuan Li
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Ke Liu
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Zhi Ji
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Yi Wang
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Tongxin Yin
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Tingting Long
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Ying Shen
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Liming Cheng
- Department of Laboratory MedicineTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
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8
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Liu Q, Shen JM, Hong HJ, Yang Q, Liu W, Guan Z, Wang YT, Chen XJ. Cell metabolomics study on the anticancer effects of Ophiopogon japonicus against lung cancer cells using UHPLC/Q-TOF-MS analysis. Front Pharmacol 2022; 13:1017830. [PMID: 36188550 PMCID: PMC9523105 DOI: 10.3389/fphar.2022.1017830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Ophiopogon japonicus (OJ) is a traditional Chinese herbal medicine that has been used for thousands of years. Recently, the anticancer effects of OJ have been reported in multiple types of cancer, particularly in lung cancer. However, the underlying mechanisms remain unclear. In present study, the effects of OJ against NCI-H1299 human lung cancer cells were investigated, and the underlying mechanisms were explored using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS)-based cell metabolomics. As a result, OJ inhibited the proliferation, induced the apoptosis and suppressed the migration of NCI-H1299 cells. A total of 22 differential metabolites responsible for the effects of OJ were screened and annotated based on the LC-MS-based cell metabolomics approach. The altered metabolites were involved in three metabolic pathways, including glycerophospholipid metabolism, ether lipid metabolism and glutathione metabolism. These results showed that cell metabolomics-based strategies are promising tools to discover the action mechanisms of OJ against lung cancer cells.
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Affiliation(s)
- Qiao Liu
- State Key Laboratory of Characteristic Chinese Medicine Resources in Southwest China, College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Jia-Man Shen
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Hui-Jie Hong
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Qi Yang
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Wen Liu
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Zhong Guan
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Yi-Tao Wang
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
| | - Xiao-Jia Chen
- Institute of Chinese Medical Sciences, State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Taipa, Macao SAR, China
- Zhuhai UM Science and Technology Research Institute, Zhuhai, China
- *Correspondence: Xiao-Jia Chen,
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Zahedi S, Carvalho AS, Ejtehadifar M, Beck HC, Rei N, Luis A, Borralho P, Bugalho A, Matthiesen R. Assessment of a Large-Scale Unbiased Malignant Pleural Effusion Proteomics Study of a Real-Life Cohort. Cancers (Basel) 2022; 14:cancers14184366. [PMID: 36139528 PMCID: PMC9496668 DOI: 10.3390/cancers14184366] [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: 08/09/2022] [Revised: 08/29/2022] [Accepted: 09/01/2022] [Indexed: 11/29/2022] Open
Abstract
Simple Summary Pleural effusion (PE) occurs as a consequence of various pathologies. Malignant effusion due to lung cancer is one of the most frequent causes. A method for accurate differentiation of malignant from benign PE is an unmet clinical need. Proteomics profiling of PE has shown promising results. However, mass spectrometry (MS) analysis typically involves the tedious elimination of abundant proteins before analysis, and clinical annotation of proteomics profiled cohorts is limited. This study compares the proteomes of malignant PE and nonmalignant PE, identifies lung cancer malignant markers in agreement with other studies, and identifies markers strongly associated with patient survival. Abstract Background: Pleural effusion (PE) is common in advanced-stage lung cancer patients and is related to poor prognosis. Identification of cancer cells is the standard method for the diagnosis of a malignant PE (MPE). However, it only has moderate sensitivity. Thus, more sensitive diagnostic tools are urgently needed. Methods: The present study aimed to discover potential protein targets to distinguish malignant pleural effusion (MPE) from other non-malignant pathologies. We have collected PE from 97 patients to explore PE proteomes by applying state-of-the-art liquid chromatography-mass spectrometry (LC-MS) to identify potential biomarkers that correlate with immunohistochemistry assessment of tumor biopsy or with survival data. Functional analyses were performed to elucidate functional differences in PE proteins in malignant and benign samples. Results were integrated into a clinical risk prediction model to identify likely malignant cases. Sensitivity, specificity, and negative predictive value were calculated. Results: In total, 1689 individual proteins were identified by MS-based proteomics analysis of the 97 PE samples, of which 35 were diagnosed as malignant. A comparison between MPE and benign PE (BPE) identified 58 differential regulated proteins after correction of the p-values for multiple testing. Furthermore, functional analysis revealed an up-regulation of matrix intermediate filaments and cellular movement-related proteins. Additionally, gene ontology analysis identified the involvement of metabolic pathways such as glycolysis/gluconeogenesis, pyruvate metabolism and cysteine and methionine metabolism. Conclusion: This study demonstrated a partial least squares regression model with an area under the curve of 98 and an accuracy of 0.92 when evaluated on the holdout test data set. Furthermore, highly significant survival markers were identified (e.g., PSME1 with a log-rank of 1.68 × 10−6).
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Affiliation(s)
- Sara Zahedi
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
| | - Ana Sofia Carvalho
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
| | - Mostafa Ejtehadifar
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
| | - Hans C. Beck
- Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense, Denmark
| | - Nádia Rei
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
| | - Ana Luis
- Hospital CUF Descobertas, CUF Oncologia, 1998-018 Lisbon, Portugal
| | - Paula Borralho
- Hospital CUF Descobertas, CUF Oncologia, 1998-018 Lisbon, Portugal
| | - António Bugalho
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
- Hospital CUF Descobertas, CUF Oncologia, 1998-018 Lisbon, Portugal
- Correspondence: (A.B.); (R.M.)
| | - Rune Matthiesen
- iNOVA4Health, NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal
- Correspondence: (A.B.); (R.M.)
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Plasm Metabolomics Study in Pulmonary Metastatic Carcinoma. JOURNAL OF ONCOLOGY 2022; 2022:9460019. [PMID: 36046366 PMCID: PMC9420632 DOI: 10.1155/2022/9460019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 07/15/2022] [Indexed: 11/18/2022]
Abstract
Background The lung is one of the most common metastatic sites of malignant tumors. Early detection of pulmonary metastatic carcinoma can effectively reduce relative cancer mortality. Human metabolomics is a qualitative and quantitative study of low-molecular metabolites in the body. By studying the plasm metabolomics of patients with pulmonary metastatic carcinoma or other lung diseases, we can find the difference in plasm levels of low-molecular metabolites among them. These metabolites have the potential to become biomarkers of lung metastases. Methods Patients with pulmonary nodules admitted to our department from February 1, 2019, to May 31, 2019, were collected. According to the postoperative pathological results, they were divided into three groups: pulmonary metastatic carcinoma (PMC), benign pulmonary nodules (BPN), and primary lung cancer (PLC). Moreover, healthy people who underwent physical examination were enrolled as the healthy population group (HPG) during the same period. On the one hand, to study lung metastases screening in healthy people, PMC was compared with HPG. The multivariate statistical analysis method was used to find the significant low-molecular metabolites between the two groups, and their discriminating ability was verified by the ROC curve. On the other hand, from the perspective of differential diagnosis of lung metastases, three groups with different pulmonary lesions (PMC, BPN, and PLC) were compared as a whole, and then the other two groups were compared with PMC, respectively. The main low-molecular metabolites were selected, and their discriminating ability was verified. Results In terms of lung metastases screening for healthy people, four significant low-molecular metabolites were found by comparison of PMC and HPG. They were O-arachidonoyl ethanolamine, adrenoyl ethanolamide, tricin 7-diglucuronoside, and p-coumaroyl vitisin A. In terms of the differential diagnosis of pulmonary nodules, the significant low-molecular metabolites selected by the comparison of the three groups as a whole were anabasine, octanoylcarnitine, 2-methoxyestrone, retinol, decanoylcarnitine, calcitroic acid, glycogen, and austalide L. For the comparison of PMC and BPN, L-tyrosine, indoleacrylic acid, and lysoPC (16 : 0) were selected, while L-octanoylcarnitine, retinol, and decanoylcarnitine were selected for the comparison of PMC and PLC. Their AUCs of ROC are all greater than 0.80. It indicates that these substances have a strong ability to differentiate between pulmonary metastatic carcinoma and other pulmonary nodule lesions. Conclusion Through the research of plasm metabolomics, it is possible to effectively detect the changes in some low-molecular metabolites among primary lung cancer, pulmonary metastatic carcinoma, and benign pulmonary nodule patients and healthy people. These significant metabolites have the potential to be biomarkers for screening and differential diagnosis of lung metastases.
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Russell JP, Osborn SD, Ivančić M, Aristizabal-Henao JJ, Bowden JA, Stedman N, Stacy NI. Chronic nonchylous lymphatic pleural effusion in a bottlenose dolphin (Tursiops truncatus). J Am Vet Med Assoc 2022; 260:1-9. [PMID: 35298406 DOI: 10.2460/javma.21.06.0311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
CASE DESCRIPTION A 19-year-old male bottlenose dolphin (Tursiops truncatus) presented with inappetence and avoidant behavior. CLINICAL FINDINGS Ultrasound revealed a large-volume left-sided pleural effusion, which was consistent with chronic nonchylous lymphatic effusion and mild chronic hemorrhage by cytology. Computed tomography identified ipsilateral rib fractures, atelectasis, nodular pleuritis, marginal lymph node enlargement, and suspected dilation of the thoracic duct and internal thoracic veins. Fifteen lipids were significantly higher in serum of the dolphin as compared with controls (n = 3) using nontargeted lipidomics. TREATMENT AND OUTCOME A series of thoracentesis procedures were performed. Follow-up CT demonstrated marked reduction in pleural effusion with persistence of thoracic duct dilation and mass-like areas of pleural thickening. Ultrasonographic resolution of pleural effusion occurred 14 months after presentation; however, recrudescence was noted 5 months later. Over a total of 24 months, 21.52 L of pleural effusion was removed. Despite the presence of pleural effusion, the patient was clinically stable during this time and quality of life was considered good on the basis of continuous animal welfare evaluations. Humane euthanasia was elected following acute clinical decline 27 months after initial diagnosis. Necropsy confirmed severe pleural effusion, chronic severe pleural fibrosis with chronic hemorrhage, and mediastinal fibrosis with entrapped lymph nodes and thymic tissue. CLINICAL RELEVANCE Pleuritis and effusion were suspected sequelae of previous rib fractures. To our knowledge, this is the first report of nonchylous lymphatic pleural effusion with repeated pleural drainage and diagnostic imaging for clinical management in a bottlenose dolphin.
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Affiliation(s)
| | | | - Marina Ivančić
- Chicago Zoological Society, Brookfield Zoo, Brookfield, IL
| | - Juan J Aristizabal-Henao
- Center for Environmental and Human Toxicology and Department of Physiological Sciences, University of Florida, Gainesville, FL
| | - John A Bowden
- Center for Environmental and Human Toxicology and Department of Physiological Sciences, University of Florida, Gainesville, FL
| | - Nancy Stedman
- SeaWorld Parks and Entertainment, Busch Gardens, Tampa, FL
| | - Nicole I Stacy
- Department of Comparative, Diagnostic, and Population Medicine, College of Veterinary Medicine, University of Florida, Gainesville, FL
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Lipid profiling in malignant mesothelioma reveals promising signatures for diagnosis and prognosis: A plasma-based LC-MS lipidomics study. Clin Chim Acta 2022; 524:34-42. [PMID: 34843704 DOI: 10.1016/j.cca.2021.11.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 11/18/2021] [Accepted: 11/24/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND AND AIM Malignant mesothelioma (MM), being a rare and aggressive carcinoma, can barely be cured. Incidence of this cancer will keep climbing up in the next few decades since its major carcinogen, asbestos, is still in use in many countries. Unfortunately, prognosis of MM is unsatisfactory principally due to poor early diagnosis as a result of its long latency period and ambiguous symptoms. Lipids are known to contribute to cellular structure, signaling, and energy storage, and are widely reported to be related with tumorigenesis. Therefore, we aim to discover novel lipid biomarkers by plasma-based lipidomics that may improve MM diagnosis. METHODS Plasma samples from 25 MM patients and 32 healthy controls (HCs) were collected and analysed using a high-throughput liquid chromatography-mass spectrometry (LC-MS). Univariate and multivariate analyses were subsequently performed to visualize the separation trend between two groups and to screen for differential feature ions. Ions were annotated using LipidSearch 4.2 and their enriched pathways were detected on LIPEA. Receiver operating characteristic (ROC) curves were used for analysing each annotated lipid's diagnostic value. Survival analyses were performed to investigate each lipid's prognostic value. RESULTS In supervised partial least squares discriminant analysis (PLS-DA), clear separation between MM and HC groups was observed. A total of 34 differential lipids were annotated, among which 5 upregulated and 29 downregulated. Levels of plasma triacylglycerols (TGs) were higher in smoking versus non-smoking patients, and lower in female versus male patients. The top six lipids possessing highest diagnostic value included two phosphatidylethanolamines (PEs), two phosphatidylcholines (PCs) and two ceramides. Moreover, elevated circulating TG levels were associated with poorer survival, whereas increased monohexosylceramide (Hex1Cer) might be beneficial. CONCLUSIONS Our study revealed differentially expressed lipid patterns in MM compared to HC. PC, PE, and ceramides showed outstanding diagnostic performance, while TG and Hex1Cer exhibited significant prognostic values. Nevertheless, more studies should verify these trends as well as further investigating on underlying mechanisms.
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Pinilla L, Benítez ID, Santamaria-Martos F, Targa A, Moncusí-Moix A, Dalmases M, Mínguez O, Aguilà M, Jové M, Sol J, Pamplona R, Barbé F, Sánchez-de-la-Torre M. Plasma profiling reveals a blood-based metabolic fingerprint of obstructive sleep apnea. Biomed Pharmacother 2021; 145:112425. [PMID: 34800782 DOI: 10.1016/j.biopha.2021.112425] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 11/03/2021] [Accepted: 11/12/2021] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION Obstructive sleep apnea (OSA) is a chronic, heterogeneous and multicomponent disorder with associated cardiovascular and metabolic alterations. Despite being the most common sleep-disordered breathing, it remains a significantly undiagnosed condition. OBJECTIVE We examined the plasma metabolome and lipidome of patients with suspected OSA, aiming to identify potential diagnosis biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Additionally, we evaluated the impact of continuous positive airway pressure (CPAP) treatment on the circulating metabolomic and lipidomic profile. MATERIAL AND METHODS Observational-prospective-longitudinal study including 206 consecutive subjects referred to the sleep unit. OSA was defined as an apnea-hypopnoea index ≥ 15 events/h after polysomnography (PSG). Patients treated with CPAP were followed-up for 6 months. Untargeted plasma metabolomic and lipidomic profiling was performed using liquid chromatography coulpled to massspectrometry. RESULTS A plasma profile composed of 33 metabolites (mainly glycerophospholipids and bile acids) was identified in OSA vs. non-OSA patients. This profile correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses disclosed a 4-metabolites-signature that provided an accuracy (95% CI) of 0.98 (0.95-0.99) for OSA detection. CPAP treatment was associated with changes in 5 plasma metabolites previously altered by OSA. CONCLUSIONS This analysis of the circulating metabolome and lipidome reveals a molecular fingerprint of OSA, which was modulated after effective CPAP treatment. Our results suggest blood-based biomarker candidates with potential application in the personalized management of OSA and suggest the activation of adaptive mechanisms in response to OSA-derived hypoxia.
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Affiliation(s)
- Lucía Pinilla
- Group of Precision Medicine in Chronic Diseases, University Hospital Arnau de Vilanova and Santa María, IRBLleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain.; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Iván D Benítez
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Fernando Santamaria-Martos
- Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Adriano Targa
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Anna Moncusí-Moix
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Mireia Dalmases
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Olga Mínguez
- Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Maria Aguilà
- Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Mariona Jové
- Department of Experimental Medicine, University of Lleida-Biomedical Research Institute of Lleida (UdL-IRBLleida), Lleida, Spain
| | - Joaquim Sol
- Department of Experimental Medicine, University of Lleida-Biomedical Research Institute of Lleida (UdL-IRBLleida), Lleida, Spain; Institut Català de la Salut, Atenció Primària, Lleida, Spain; Research Support Unit Lleida, Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Lleida, Spain
| | - Reinald Pamplona
- Department of Experimental Medicine, University of Lleida-Biomedical Research Institute of Lleida (UdL-IRBLleida), Lleida, Spain
| | - Ferran Barbé
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Group of Translational Research in Respiratory Medicine, Respiratory Department, University Hospital Arnau de Vilanova and Santa María, IRB Lleida, Lleida, Spain
| | - Manuel Sánchez-de-la-Torre
- Group of Precision Medicine in Chronic Diseases, University Hospital Arnau de Vilanova and Santa María, IRBLleida, Department of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Lleida, Lleida, Spain.; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain.
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Chen Z, Huang X, Gao Y, Zeng S, Mao W. Plasma-metabolite-based machine learning is a promising diagnostic approach for esophageal squamous cell carcinoma investigation. J Pharm Anal 2021; 11:505-514. [PMID: 34513127 PMCID: PMC8424362 DOI: 10.1016/j.jpha.2020.11.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 11/23/2020] [Accepted: 11/24/2020] [Indexed: 12/12/2022] Open
Abstract
The aim of this study was to develop a diagnostic strategy for esophageal squamous cell carcinoma (ESCC) that combines plasma metabolomics with machine learning algorithms. Plasma-based untargeted metabolomics analysis was performed with samples derived from 88 ESCC patients and 52 healthy controls. The dataset was split into a training set and a test set. After identification of differential metabolites in training set, single-metabolite-based receiver operating characteristic (ROC) curves and multiple-metabolite-based machine learning models were used to distinguish between ESCC patients and healthy controls. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were performed to investigate the prognostic significance of the plasma metabolites. Finally, twelve differential plasma metabolites (six up-regulated and six down-regulated) were annotated. The predictive performance of the six most prevalent diagnostic metabolites through the diagnostic models in the test set were as follows: arachidonic acid (accuracy: 0.887), sebacic acid (accuracy: 0.867), indoxyl sulfate (accuracy: 0.850), phosphatidylcholine (PC) (14:0/0:0) (accuracy: 0.825), deoxycholic acid (accuracy: 0.773), and trimethylamine N-oxide (accuracy: 0.653). The prediction accuracies of the machine learning models in the test set were partial least-square (accuracy: 0.947), random forest (accuracy: 0.947), gradient boosting machine (accuracy: 0.960), and support vector machine (accuracy: 0.980). Additionally, survival analysis demonstrated that acetoacetic acid was an unfavorable prognostic factor (hazard ratio (HR): 1.752), while PC (14:0/0:0) (HR: 0.577) was a favorable prognostic factor for ESCC. This study devised an innovative strategy for ESCC diagnosis by combining plasma metabolomics with machine learning algorithms and revealed its potential to become a novel screening test for ESCC. Six most prevalent diagnostic plasma metabolites were identified in ESCC. Plasma-metabolite-based machine learning models (PLS, RF, GBM, and SVM) for ESCC diagnosis. Acetoacetic acid was an unfavorable prognostic factor, while PC (14:0/0:0) was a favorable prognostic factor for ESCC.
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Affiliation(s)
- Zhongjian Chen
- Laboratory of Pharmaceutical Analysis and Drug Metabolism, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.,The Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Xiancong Huang
- The Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Yun Gao
- The Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Su Zeng
- Laboratory of Pharmaceutical Analysis and Drug Metabolism, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Weimin Mao
- The Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China
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15
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Li N, Yang C, Zhou S, Song S, Jin Y, Wang D, Liu J, Gao Y, Yang H, Mao W, Chen Z. Combination of Plasma-Based Metabolomics and Machine Learning Algorithm Provides a Novel Diagnostic Strategy for Malignant Mesothelioma. Diagnostics (Basel) 2021; 11:1281. [PMID: 34359365 PMCID: PMC8304303 DOI: 10.3390/diagnostics11071281] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/12/2021] [Accepted: 07/13/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Malignant mesothelioma (MM) is an aggressive and incurable carcinoma that is primarily caused by asbestos exposure. However, the current diagnostic tool for MM is still under-developed. Therefore, the aim of this study is to explore the diagnostic significance of a strategy that combined plasma-based metabolomics with machine learning algorithms for MM. METHODS Plasma samples collected from 25 MM patients and 32 healthy controls (HCs) were randomly divided into train set and test set, after which analyzation was performed by liquid chromatography-mass spectrometry-based metabolomics. Differential metabolites were screened out from the samples of the train set. Subsequently, metabolite-based diagnostic models, including receiver operating characteristic (ROC) curves and Random Forest model (RF), were established, and their prediction accuracies were calculated for the test set samples. RESULTS Twenty differential plasma metabolites were annotated in the train set; 10 of these metabolites were validated in the test set. The seven most prevalent diagnostic metabolites were taurocholic acid), 0.7142 (uracil), 0.7142 (biliverdin), 0.8571 (histidine), 0.5000 (tauroursodeoxycholic acid), 0.8571 (pyrroline hydroxycarboxylic acid), and 0.7857 (phenylalanine). Furthermore, RF based on 20 annotated metabolites showed a prediction accuracy of 0.9286, and its optimized version achieved 1.0000 in the test set. Moreover, the comparison between the samples of peritoneal MM (n = 8) and pleural MM (n = 17) illustrated a significant increase in levels of taurocholic acid and tauroursodeoxycholic acid, as well as an evident decrease in biliverdin. CONCLUSIONS Our results revealed the potential diagnostic value of plasma-based metabolomics combined with machine learning for MM. Further research with large sample size is worthy conducting. Moreover, our data demonstrated dysregulated metabolism pathways in MM, which aids in better understanding of molecular mechanisms related to the initiation and development of MM.
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Affiliation(s)
- Na Li
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Chenxi Yang
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Sicheng Zhou
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Siyu Song
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Yuyao Jin
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
- Department of Pharmaceutical Sciences, Hangzhou Medical College, Hangzhou 310013, China
| | - Ding Wang
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Junping Liu
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Yun Gao
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Haining Yang
- Thoracic Oncology, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Weimin Mao
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
| | - Zhongjian Chen
- Zhejiang Cancer Research Institute, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China; (N.L.); (C.Y.); (S.Z.); (S.S.); (Y.J.); (D.W.); (J.L.); (Y.G.)
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310000, China
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Wan L, Liu Q, Liang D, Guo Y, Liu G, Ren J, He Y, Shan B. Circulating Tumor Cell and Metabolites as Novel Biomarkers for Early-Stage Lung Cancer Diagnosis. Front Oncol 2021; 11:630672. [PMID: 34136379 PMCID: PMC8202280 DOI: 10.3389/fonc.2021.630672] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 04/09/2021] [Indexed: 12/12/2022] Open
Abstract
Background Lung cancer is a malignant tumor that has the highest morbidity and mortality rate among all cancers. Early diagnosis of lung cancer is a key factor in reducing mortality and improving prognosis. Methods In this study, we performed CTC next-generation sequencing (NGS) in early-stage lung cancer patients to identify lung cancer-related gene mutations. Meanwhile, a serum liquid chromatography-tandem mass spectrometry (LC-MS) untargeted metabolomics analysis was performed in the CTC-positive patients. To screen potential diagnostic markers for early lung cancer. Results 62.5% (30/48) of lung cancer patients had ≥1 CTC. By CTC NGS, we found that > 50% of patients had 4 commonly mutated genes, namely, NOTCH1, IGF2, EGFR, and PTCH1. 47.37% (9/19) patients had ARIDH1 mutations. Additionally, 30 CTC-positive patients and 30 healthy volunteers were subjected to LC-MS untargeted metabolomics analysis. We found 100 different metabolites, and 10 different metabolites were identified through analysis, which may have potential clinical application value in the diagnosis of CTC-positive early-stage lung cancer (AUC >0.9). Conclusions Our results indicate that NGS of CTC and metabolomics may provide new tumor markers for the early diagnosis of lung cancer.
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Affiliation(s)
- Lingling Wan
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Qingyi Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Di Liang
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Yongdong Guo
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Guangjie Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Jinxia Ren
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Yutong He
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
| | - Baoen Shan
- Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumor Hospital of Hebei Province, Shijiazhuang, China
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17
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Li N, Mao W, Gao Y, Wang D, Song Z, Chen Z. Liquid chromatography-mass spectrometry based metabolic characterization of pleural effusion in patients with acquired EGFR-TKI resistance. J Pharm Biomed Anal 2021; 202:114147. [PMID: 34029974 DOI: 10.1016/j.jpba.2021.114147] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 05/11/2021] [Accepted: 05/16/2021] [Indexed: 02/08/2023]
Abstract
Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) acquired resistance remains a major barrier in the clinical treatment of lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutations. Despite extensive efforts, mechanism of acquired resistance has not yet been elucidated clearly. The subject of this study was to characterize the metabolic signatures relevant to acquired EGFR-TKI resistance in pleural effusion (PE), and identify potential biomarkers in PE of patients with acquired EGFR-TKI resistance. PE from EGFR-TKI untreated group (n = 30) and EGFR-TKI resistant group (n = 18) was analyzed using liquid chromatography-mass spectrometry (LCMS) based metabolomic. Multivariate statistical analysis revealed distinctive diff ;erences between the groups. A total of 34 significantly differential metabolites in PE were identified, among which, the acquired EGFR-TKI resistant group had higher levels of l-lysine, taurine, ornithine and citrulline, and lower levels of l-tryptophan, kynurenine, l-phenylalanine, l-leucine, N-formyl-l-methionine, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine in PE than that of the EGFR-TKI untreated group. These metabolites are mainly involved in six amino acid metabolic pathways. In addition, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine showed the highest AUC values of 0.934 and 0.929 in receiver operating characteristic analysis. Through LCMS metabolomics, our study identified potential biomarkers in PE, differentiating EGFR-TKI resistant patients from untreated patients, as well as the mechanisms underlying acquired EGFR-TKI resistance; thus, providing novel insights into acquired EGFR-TKI resistance.
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Affiliation(s)
- Na Li
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310053, China
| | - Weimin Mao
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China
| | - Yun Gao
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China
| | - Ding Wang
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310053, China
| | - Zhengbo Song
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China.
| | - Zhongjian Chen
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China.
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18
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Nabi MM, Mamun MA, Islam A, Hasan MM, Waliullah ASM, Tamannaa Z, Sato T, Kahyo T, Setou M. Mass spectrometry in the lipid study of cancer. Expert Rev Proteomics 2021; 18:201-219. [PMID: 33793353 DOI: 10.1080/14789450.2021.1912602] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.
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Affiliation(s)
- Md Mahamodun Nabi
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,Institute of Food and Radiation Biology, Atomic Energy Research Establishment, Ganakbari, Savar, Dhaka, Bangladesh
| | - Md Al Mamun
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Ariful Islam
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Md Mahmudul Hasan
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - A S M Waliullah
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Zinat Tamannaa
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Tomohito Sato
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Tomoaki Kahyo
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,International Mass Imaging Center, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan
| | - Mitsutoshi Setou
- Department of Cellular & Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,International Mass Imaging Center, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.,Department of Systems Molecular Anatomy, Institute for Medical Photonics Research, Preeminent Medical Photonics Education & Research Center, Hamamatsu, Shizuoka, Japan
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Machine learning applied to near-infrared spectra for clinical pleural effusion classification. Sci Rep 2021; 11:9411. [PMID: 33941795 PMCID: PMC8093263 DOI: 10.1038/s41598-021-87736-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 03/31/2021] [Indexed: 12/22/2022] Open
Abstract
Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method based on FTIR near-infrared spectroscopy (NIRS) combined with machine learning strategy for clinical pleural effusion classification. NIRS spectra were recorded for 47 MPE samples and 35 BPE samples. The sample data were randomly divided into train set (n = 62) and test set (n = 20). Partial least squares, random forest, support vector machine (SVM), and gradient boosting machine models were trained, and subsequent predictive performance were predicted on the test set. Besides the whole spectra used in modeling, selected features using SVM recursive feature elimination algorithm were also investigated in modeling. Among those models, NIRS combined with SVM showed the best predictive performance (accuracy: 1.0, kappa: 1.0, and AUCROC: 1.0). SVM with the top 50 feature wavenumbers also displayed a high predictive performance (accuracy: 0.95, kappa: 0.89, AUCROC: 0.99). Our study revealed that the combination of NIRS and machine learning is an innovative, rapid, and convenient method for clinical pleural effusion classification, and worth further evaluation.
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20
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Bian L, Chen H, Zhou X. Untargeted lipidomics analysis of Mori Fructus polysaccharide on acute alcoholic liver injury in mice using ultra performance liquid chromatography-quadrupole-orbitrap-high resolution mass spectrometry. Int Immunopharmacol 2021; 97:107521. [PMID: 33940322 DOI: 10.1016/j.intimp.2021.107521] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 02/09/2021] [Accepted: 02/17/2021] [Indexed: 12/19/2022]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Mori Fructus (MF) is a traditional Chinese medicine with long application history, which has protective effects on liver diseases. Mori Fructus polysaccharide (MFP) is one of the active ingredients of MF and possesses therapeutic effects against acute alcoholic liver injury. Recent researches have reported that the therapeutic effects of MFP might be related to the regulation of several lipid metabolic pathways. However, the mechanism of lipid metabolism was still unclear. AIM OF THE STUDY This study aimed to investigate the regulatory effect of MFP on lipid metabolism in mice with acute alcoholic liver injury, and to enrich the application of its hepatoprotective effect. MATERIALS AND METHODS Fifty Specific Pathogen Free (SPF) Kunming (KM) male mice were divided into five groups randomly, including normal control group, model group, bifendate positive group (220 mg/ kg), MFPA1 group (50 mg/ kg) and MFPB1 group (50 mg/ kg). A model of acute alcoholic liver injury was established by treating the mice with ethanol. The liver sections were processed and histopathological changes was observed with hematoxylin and eosin staining. The secretion levels of biochemical indexes in the liver and serum were assayed by ELISA. The untargeted lipidomics analysis was performed on a Q Exactive Focus quadrupole orbitrap high resolution mass spectrometry coupled with a Dionex Ultimate 3000 RSLC (HPG) ultra-performance liquid chromatography (UPLC-Q-Orbitrap-HRMS) system (Thermo Fisher Scientific), with a HESI ionization source. RESULTS It was observed that abnormal glutamic-pyruvic transaminase enzyme (ALT), glutamic-oxaloacetic aminotransferase (AST), triglyceride (TG), superoxide dismutase (SOD), and malondialdehyde (MDA) concentrations were ameliorated after irrigation of MFP or bifendate. Histopathology examination showed that intragastric infusion of MFP can be helpful in the repair of damaged liver in mice. The multivariate analysis of hepatic lipids showed segregation of ethanol-fed groups from the normal controls. After the comparison of mass spectra, 10 lipids were found to have different content in the normal control group and the model group. Differential lipids that were increased by ethanol exposure included fatty acids, phosphatidylcholine, and lyso-phosphatidylethanolamine, whereas lyso-phosphatidylcholine decreased. Among them, 4 lipids almost returned to the level of normal mice after MFP treatment. CONCLUSION The therapeutic effect of MFP on acute alcoholic liver injury may be achieved by regulating a variety of metabolic pathways, including linoleic acid metabolism, α - linolenic acid metabolism, and glycerolphospholipid metabolism. These results revealed that MFP efficiently exerted hepatoprotective benefits, and its potential effect was associated with the amelioration of lipid metabolism.
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Affiliation(s)
- Liang Bian
- Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Engineering Laboratory for Quality Control and Evaluation Technology of Medicine, Research Center for Quality Control of Natural Medicine, Guizhou Normal University, Guiyang 550001, China
| | - Huaguo Chen
- Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Engineering Laboratory for Quality Control and Evaluation Technology of Medicine, Research Center for Quality Control of Natural Medicine, Guizhou Normal University, Guiyang 550001, China.
| | - Xin Zhou
- Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Engineering Laboratory for Quality Control and Evaluation Technology of Medicine, Research Center for Quality Control of Natural Medicine, Guizhou Normal University, Guiyang 550001, China.
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21
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Wang Y, Wang Y, Chen C, Ren F, Cao R, Wang Y, Han P, Zhang X, Xu C, Liu X, Xu G. Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography-Mass spectrometry. J Pharm Biomed Anal 2021; 199:114048. [PMID: 33836461 DOI: 10.1016/j.jpba.2021.114048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/23/2021] [Accepted: 03/24/2021] [Indexed: 12/13/2022]
Abstract
Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854∼0.865 and 0.903∼0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.
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Affiliation(s)
- Yuting Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yisheng Wang
- Hospital and Institute of Obstetrics and Gynecology, Fudan University, Shanghai, 200032, China
| | - Chen Chen
- Department of Gynecology, The Maternity Affiliated Hospital of Dalian Medical University, Dalian, 116033, China
| | - Fang Ren
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Rui Cao
- Department of Gynecology, The Maternity Affiliated Hospital of Dalian Medical University, Dalian, 116033, China
| | - Yuefei Wang
- Hospital and Institute of Obstetrics and Gynecology, Fudan University, Shanghai, 200032, China
| | - Pin Han
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Xiaoyan Zhang
- Hospital and Institute of Obstetrics and Gynecology, Fudan University, Shanghai, 200032, China
| | - Congjian Xu
- Hospital and Institute of Obstetrics and Gynecology, Fudan University, Shanghai, 200032, China.
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
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22
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Wang Y. Applications of Lipidomics in Tumor Diagnosis and Therapy. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1316:25-39. [PMID: 33740241 DOI: 10.1007/978-981-33-6785-2_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Lipids have many critical biological functions in cancer. There are characteristic changes of lipid metabolism and metabolites in different physiological and pathological processes. Lipidomics is an emerging discipline of metabolomics for systematic analysis of lipids in organisms, tissues, or cells and the molecules that interact with them. With the development of new analytical techniques, especially the application and development of mass spectrometry techniques, the determination of lipids can be carried out quickly and accurately and has a high throughput. A large number of studies have shown that abnormal lipid metabolism is closely related to the occurrence and development of tumors. The application of lipidomics technology can reveal changes in lipids and relative abnormal metabolic pathways associated with tumors. Moreover, it shows a wide range of application prospects in the identification of tumor lipid biomarkers, early tumor diagnosis, and the discovery of antitumor drug targets. This chapter mainly introduces the application and development direction of lipidomics in the diagnosis and therapy of different tumors.
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Affiliation(s)
- Yuping Wang
- Department of Gastroenterology, Key Laboratory for Gastrointestinal Diseases of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, Gansu Province, China.
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23
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Villaret-Cazadamont J, Poupin N, Tournadre A, Batut A, Gales L, Zalko D, Cabaton NJ, Bellvert F, Bertrand-Michel J. An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples. Metabolites 2020; 10:E338. [PMID: 32825089 PMCID: PMC7570216 DOI: 10.3390/metabo10090338] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 08/16/2020] [Accepted: 08/17/2020] [Indexed: 12/11/2022] Open
Abstract
The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.
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Affiliation(s)
- Joran Villaret-Cazadamont
- Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, 31027 Toulouse, France; (J.V.-C.); (N.P.); (D.Z.); (N.J.C.)
| | - Nathalie Poupin
- Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, 31027 Toulouse, France; (J.V.-C.); (N.P.); (D.Z.); (N.J.C.)
| | - Anthony Tournadre
- MetaboHUB-MetaToul-Lipidomics Core Facility, Inserm U1048, 31432 Toulouse, France; (A.T.); (A.B.)
- MetaboHUB-MetaToul, National Infrastructure for Metabolomics and Fluxomics, 31077 Toulouse, France;
| | - Aurélie Batut
- MetaboHUB-MetaToul-Lipidomics Core Facility, Inserm U1048, 31432 Toulouse, France; (A.T.); (A.B.)
- MetaboHUB-MetaToul, National Infrastructure for Metabolomics and Fluxomics, 31077 Toulouse, France;
| | - Lara Gales
- MetaboHUB-MetaToul, National Infrastructure for Metabolomics and Fluxomics, 31077 Toulouse, France;
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, 31400 Toulouse, France
| | - Daniel Zalko
- Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, 31027 Toulouse, France; (J.V.-C.); (N.P.); (D.Z.); (N.J.C.)
| | - Nicolas J. Cabaton
- Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, 31027 Toulouse, France; (J.V.-C.); (N.P.); (D.Z.); (N.J.C.)
| | - Floriant Bellvert
- MetaboHUB-MetaToul, National Infrastructure for Metabolomics and Fluxomics, 31077 Toulouse, France;
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, 31400 Toulouse, France
| | - Justine Bertrand-Michel
- MetaboHUB-MetaToul-Lipidomics Core Facility, Inserm U1048, 31432 Toulouse, France; (A.T.); (A.B.)
- MetaboHUB-MetaToul, National Infrastructure for Metabolomics and Fluxomics, 31077 Toulouse, France;
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Knuplez E, Marsche G. An Updated Review of Pro- and Anti-Inflammatory Properties of Plasma Lysophosphatidylcholines in the Vascular System. Int J Mol Sci 2020; 21:E4501. [PMID: 32599910 PMCID: PMC7350010 DOI: 10.3390/ijms21124501] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/19/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022] Open
Abstract
Lysophosphatidylcholines are a group of bioactive lipids heavily investigated in the context of inflammation and atherosclerosis development. While present in plasma during physiological conditions, their concentration can drastically increase in certain inflammatory states. Lysophosphatidylcholines are widely regarded as potent pro-inflammatory and deleterious mediators, but an increasing number of more recent studies show multiple beneficial properties under various pathological conditions. Many of the discrepancies in the published studies are due to the investigation of different species or mixtures of lysophatidylcholines and the use of supra-physiological concentrations in the absence of serum or other carrier proteins. Furthermore, interpretation of the results is complicated by the rapid metabolism of lysophosphatidylcholine (LPC) in cells and tissues to pro-inflammatory lysophosphatidic acid. Interestingly, most of the recent studies, in contrast to older studies, found lower LPC plasma levels associated with unfavorable disease outcomes. Being the most abundant lysophospholipid in plasma, it is of utmost importance to understand its physiological functions and shed light on the discordant literature connected to its research. LPCs should be recognized as important homeostatic mediators involved in all stages of vascular inflammation. In this review, we want to point out potential pro- and anti-inflammatory activities of lysophospholipids in the vascular system and highlight recent discoveries about the effect of lysophosphatidylcholines on immune cells at the endothelial vascular interface. We will also look at their potential clinical application as biomarkers.
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Affiliation(s)
- Eva Knuplez
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
| | - Gunther Marsche
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
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