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López-López Á, López-Gonzálvez Á, Barbas C. Metabolomics for searching validated biomarkers in cancer studies: a decade in review. Expert Rev Mol Diagn 2024; 24:601-626. [PMID: 38904089 DOI: 10.1080/14737159.2024.2368603] [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: 12/27/2023] [Accepted: 06/12/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways. AREAS COVERED This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types. EXPERT OPINION Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.
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Affiliation(s)
- Ángeles López-López
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
| | - Ángeles López-Gonzálvez
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Madrid, Spain
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Seok J, Kwak Y, Kim S, Kim EM, Kim A. Advances in Liquid Biopsy for Diagnosis of Bladder Cancer. Int Neurourol J 2024; 28:83-95. [PMID: 38956768 PMCID: PMC11222820 DOI: 10.5213/inj.2448198.099] [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: 04/15/2024] [Accepted: 05/06/2024] [Indexed: 07/04/2024] Open
Abstract
Bladder cancer (BCa) is the most common malignancy of the urinary system. It has a high recurrence rate and requires longterm follow-up. Significant advances in BCa research have been made in recent years; however, the initial diagnosis and follow-up of BCa relies on cystoscopy, which is an invasive and expensive procedure. Over the past decade, liquid biopsies (e.g., blood and urine) have proven to be highly efficient methods for the discovery of BCa biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into body fluids and enables serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers have been studied extensively and have shown promising results in the clinical applications of BCa, including early detection, microscopic residual disease detection, recurrence prediction, and treatment response. Therefore, this review aims to provide an update on various new liquid biopsy markers and the advantages and current limitations of liquid biopsy in the diagnosis of BCa.
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Affiliation(s)
- Jaekwon Seok
- Department of Stem Cell and Regenerative Biotechnology, Molecular & Cellular Reprogramming Center (MCRC), and Incurable Disease Animal Model & Stem Cell Institute (IDASI), Konkuk University, Seoul, Korea
| | - Yeonjoo Kwak
- Department of Stem Cell and Regenerative Biotechnology, Molecular & Cellular Reprogramming Center (MCRC), and Incurable Disease Animal Model & Stem Cell Institute (IDASI), Konkuk University, Seoul, Korea
| | - Sewhan Kim
- Department of Biomedical Engineering, School of Medicine, Dankook University, Cheonan, Korea
| | - Eun-Mee Kim
- Department of Paramedicine, Korea Nazarene University, Cheonan, Korea
| | - Aram Kim
- Department of Urology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
- University of California Irvine, Beckman Laser Institute and Medical Clinic, Irvine, CA, USA
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3
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Gerson KD, Loder A, Landau Z, Anton L. Xenobiotic metabolites modify immune responses of the cervicovaginal epithelium: potential mechanisms underlying barrier disruption. BJOG 2024; 131:665-674. [PMID: 37705143 DOI: 10.1111/1471-0528.17654] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/28/2023] [Accepted: 08/14/2023] [Indexed: 09/15/2023]
Abstract
OBJECTIVE Xenobiotic metabolites are exogenous biochemicals that can adversely impact reproductive health. We previously identified xenobiotics in cervicovaginal fluid during pregnancy in association with short cervix. In other organ systems, xenobiotics can modify epithelial barrier function. We hypothesise that xenobiotics dysregulate epithelial cell and macrophage immune responses as a mechanism to disrupt the cervicovaginal barrier. DESIGN In vitro cell culture system. SETTING Laboratory within academic institution. SAMPLE Vaginal, ectocervical and endocervical epithelial cell lines and primary macrophages. METHODS Cells were treated with diethanolamine (2.5 mM), ethyl glucoside (5 mM) or tartrate (2.5 mM) for 24 h. MAIN OUTCOME MEASURES Cytokines and matrix metalloproteinases were measured in cell supernatants (n = 3 per condition). One-way analysis of variance (ANOVA) with Dunnett's test for multiple comparisons was performed. RESULTS Diethanolamine induces inflammatory cytokines, whereas ethyl glucoside and tartrate generally exert anti-inflammatory effects across all cells. Diethanolamine increases interleukin 6 (IL-6), IL-8, interferon γ-induced protein 10 kDa (IP-10), growth-regulated oncogene (GRO), fractalkine, matrix metalloproteinase 1 (MMP-1), MMP-9 and MMP-10 (p < 0.05 for all), factors involved in acute inflammation and recruitment of monocytes, neutrophils and lymphocytes. Ethyl glucoside and tartrate decrease multiple cytokines, including RANTES and MCP-1 (p < 0.05 for all), which serve as chemotactic factors. Vaginal cells exhibit heightened inflammatory tone compared with cervical cells and macrophages, with a greater number of differentially expressed analytes after xenobiotic exposure. CONCLUSIONS Xenobiotic metabolites present in the cervicovaginal space during pregnancy modify immune responses, unveiling potential pathways through which environmental exposures may contribute to the pathogenesis of cervical remodelling preceding preterm birth. Future work identifying xenobiotic sources and routes of exposure offers the potential to modify environmental risks to improve pregnancy outcomes.
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Affiliation(s)
- Kristin D Gerson
- Center for Research on Reproduction and Women's Health, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Aaron Loder
- Center for Research on Reproduction and Women's Health, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Zachary Landau
- Center for Research on Reproduction and Women's Health, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lauren Anton
- Center for Research on Reproduction and Women's Health, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Wu S, Li R, Jiang Y, Yu J, Zheng J, Li Z, Li M, Xin K, Wang Y, Xu Z, Li S, Chen X. Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications. Biomed Pharmacother 2023; 165:115027. [PMID: 37354812 DOI: 10.1016/j.biopha.2023.115027] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/13/2023] [Accepted: 06/14/2023] [Indexed: 06/26/2023] Open
Abstract
The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.
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Affiliation(s)
- Siyu Wu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Rong Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Yuanhong Jiang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Jiazheng Yu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Jianyi Zheng
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Zeyu Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Mingyang Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Kerong Xin
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China
| | - Yang Wang
- Department of Gynecology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, Liaoning 110042, China.
| | - Zhenqun Xu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China.
| | - Shijie Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China.
| | - Xiaonan Chen
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China.
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Beksac K, Reçber T, Çetin B, Alp O, Kaynaroğlu V, Kır S, Nemutlu E. GC-MS Based Metabolomics Analysis to Evaluate Short-Term Effect of Tumor Removal on Patients with Early-Stage Breast Cancer. J Chromatogr Sci 2023; 61:612-618. [PMID: 35453141 DOI: 10.1093/chromsci/bmac035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/02/2022] [Accepted: 04/04/2022] [Indexed: 11/12/2022]
Abstract
In this study, it was aimed to demonstrate the short-term effect of breast cancer surgery and tumor removal on the metabolomic profiles of patients with early-stage breast cancer. This cohort consisted of 18 early-stage breast carcinoma patients who had breast cancer surgery to remove tumor and surrounding tissues. The blood samples obtained preoperatively and 24 h after surgery were used in this investigation. Gas chromatography-mass spectrometry (GC-MS) based metabolomic analysis was performed to determine the metabolites. The GC-MS-based metabolomics profile enabled the identification of 162 metabolites in the plasma samples. Postoperatively, glyceric acid, phosphoric acid, O-phosphocolamine, 2-hydroxyethyliminodiacetic acid, N-acetyl-D-mannosamine, N-acetyl-5-hydroxytryptamine, methyl stearate, methyl oleate, iminodiacetic acid, glycerol 1-phosphate, β-glycerol phosphate and aspartic acid were found to be significantly increased (P < 0.05 for all), whereas saccharic acid, leucrose, gluconic acid, citramalic acid and acetol were significantly decreased (P < 0.05 for all). Breast cancer surgery and tumor removal has an impact on the metabolomic profiles of patients with early-stage breast cancer. These findings can be used for understanding the pathogenesis of breast cancer biology and screening the success of the surgery.
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Affiliation(s)
- Kemal Beksac
- Department of General Surgery, Ankara Oncology Hospital, Ankara 06200, Turkey
| | - Tuba Reçber
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
| | - Bahadır Çetin
- Department of General Surgery, Ankara Oncology Hospital, Ankara 06200, Turkey
| | - Orkun Alp
- Department of Analytical Chemistry, Faculty of Pharmacy, Gazi University, Ankara 06330, Turkey
| | - Volkan Kaynaroğlu
- Department of General Surgery, Faculty of Medicine, Hacettepe University, Ankara 06100, Turkey
| | - Sedef Kır
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
| | - Emirhan Nemutlu
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
- Bioanalytic and Omics Laboratory, Faculty of Pharmacy, Hacettepe University, Ankara 06100, Turkey
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Nizioł J, Ossoliński K, Płaza-Altamer A, Kołodziej A, Ossolińska A, Ossoliński T, Nieczaj A, Ruman T. Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry. Sci Rep 2023; 13:9802. [PMID: 37328580 PMCID: PMC10275937 DOI: 10.1038/s41598-023-36874-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: 03/24/2023] [Accepted: 06/12/2023] [Indexed: 06/18/2023] Open
Abstract
Bladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.
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Affiliation(s)
- Joanna Nizioł
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland.
| | - Krzysztof Ossoliński
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Aneta Płaza-Altamer
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
- Doctoral School of Engineering and Technical Sciences at the Rzeszów University of Technology, 8 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Artur Kołodziej
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
- Doctoral School of Engineering and Technical Sciences at the Rzeszów University of Technology, 8 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Anna Ossolińska
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Tadeusz Ossoliński
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Anna Nieczaj
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Tomasz Ruman
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
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GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. Int J Mol Sci 2023; 24:ijms24021591. [PMID: 36675106 PMCID: PMC9867309 DOI: 10.3390/ijms24021591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 12/27/2022] [Accepted: 01/06/2023] [Indexed: 01/15/2023] Open
Abstract
Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.
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“Seeing” invisible volatile organic compound (VOC) marker of urinary bladder cancer: A development from bench to bedside prototype spectroscopic device. Biosens Bioelectron 2022; 218:114764. [DOI: 10.1016/j.bios.2022.114764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/20/2022] [Accepted: 09/25/2022] [Indexed: 11/30/2022]
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Ligor T, Adamczyk P, Kowalkowski T, Ratiu IA, Wenda-Piesik A, Buszewski B. Analysis of VOCs in Urine Samples Directed towards of Bladder Cancer Detection. Molecules 2022; 27:5023. [PMID: 35956972 PMCID: PMC9370153 DOI: 10.3390/molecules27155023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/30/2022] [Accepted: 08/01/2022] [Indexed: 12/25/2022] Open
Abstract
Bladder cancer is one of most common types of cancer diagnosed in the genitourinary tract. Typical tests are costly and characterized by low sensitivity, which contributes to a growing interest in volatile biomarkers. Head space solid phase microextraction (SPME) was applied for the extraction of volatile organic compounds from urine samples, and gas chromatography time of flight mass spectrometry (GC×GC TOF MS) was used for the separation and detection of urinary volatiles. A cohort of 40 adult patients with bladder cancer and 57 healthy persons was recruited. Different VOC profiles were obtained for urine samples taken from each group. Twelvecompounds were found only in the samples from theBC group.The proposed candidate biomarkers are butyrolactone; 2-methoxyphenol; 3-methoxy-5-methylphenol; 1-(2,6,6-trimethylcyclohexa-1,3-dien-1-yl)-2-buten-1-one; nootkatone and 1-(2,6,6-trimethyl-1-cyclohexenyl)-2-buten-1-one.Since most of the studies published in the field are proving the potential of VOCs detected in urine samples for the screening and discrimination of patients with bladder cancer from healthy, but rarely presenting the identity of proposed biomarkers, our study represents a novel approach.
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Affiliation(s)
- Tomasz Ligor
- Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry, Nicolaus Copernicus University, 87-100 Toruń, Poland
- Interdisciplinary Centre of Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - Przemysław Adamczyk
- Department of General and Oncologic Urology, Nicolaus Copernicus Hospital in Torun, 87-100 Toruń, Poland
| | - Tomasz Kowalkowski
- Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry, Nicolaus Copernicus University, 87-100 Toruń, Poland
- Interdisciplinary Centre of Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - Ileana Andreea Ratiu
- “Raluca Ripan” Institute for Research in Chemistry, Babes-Bolyai University, 30 Fantanele, RO-400239 Cluj-Napoca, Romania
| | - Anna Wenda-Piesik
- Department of Agronomics, Faculty of Agriculture and Biotechnology, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Bogusław Buszewski
- Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry, Nicolaus Copernicus University, 87-100 Toruń, Poland
- Interdisciplinary Centre of Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
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Jian Y, Zhang N, Liu T, Zhu Y, Wang D, Dong H, Guo L, Qu D, Jiang X, Du T, Zheng Y, Yuan M, Fu X, Liu J, Dou W, Niu F, Ning R, Zhang G, Fan J, Haick H, Wu W. Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine. ACS Sens 2022; 7:1720-1731. [PMID: 35613367 DOI: 10.1021/acssensors.2c00467] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Globally, bladder cancer (BLC) is one of the most common cancers and has a high recurrence and mortality rate. Current clinical diagnostic approaches are either invasive or inaccurate. Here, we report on a cost-efficient, artificially intelligent chemiresistive sensor array made of polyaniline (PANI) derivatives that can noninvasively diagnose BLC at an early stage and maintain postoperative surveillance through ″smelling″ clinical urine samples at room temperature. In clinical trials, 18 healthy controls and 76 BLC patients (60 and 16 at early and advanced stages, respectively) are assessed by the artificial olfactory system. With the assistance of a support vector machine (SVM), very high sensitivity and accuracy from healthy controls are achieved, exceeding those obtained by the current techniques in practice. In addition, the recurrences of both early and advanced stages are diagnosed well, with the effect of confounding factors on the performance of the artificial olfactory system found to have a negligible influence on the diagnostic performance. Overall, this study contributes a novel, noninvasive, easy-to-use, inexpensive, real-time, accurate method for urine disease diagnosis, which can be useful for personalized care/diagnosis and postoperative surveillance, resulting in saving more lives.
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Affiliation(s)
- Yingying Jian
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Nan Zhang
- Department of Urology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Taoping Liu
- Interdisciplinary Research Center of Smart Sensors, Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an 710126, China
| | - Yujin Zhu
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Di Wang
- Intelligent Perception Research Institute, Zhejiang Lab, Hangzhou 311100, China
| | - Hao Dong
- Intelligent Perception Research Institute, Zhejiang Lab, Hangzhou 311100, China
| | - Lihao Guo
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Danyao Qu
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Xue Jiang
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Tao Du
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Youbin Zheng
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Miaomiao Yuan
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
| | - Xuemei Fu
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
| | - Jinmei Liu
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Wei Dou
- College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, China
| | - Fang Niu
- College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, China
| | - Ruizhi Ning
- Interdisciplinary Research Center of Smart Sensors, Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an 710126, China
| | - Guangjian Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Jinhai Fan
- Department of Urology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Hossam Haick
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Weiwei Wu
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
- Interdisciplinary Research Center of Smart Sensors, Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an 710126, China
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Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body? Metabolites 2021; 11:metabo11110756. [PMID: 34822414 PMCID: PMC8621503 DOI: 10.3390/metabo11110756] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 12/17/2022] Open
Abstract
This work will review the metabolic information that various studies have obtained in recent years on bladder cancer, with particular attention to discovering biomarkers in urine for the diagnosis and prognosis of this disease. In principle, they would be capable of complementing cystoscopy, an invasive but nowadays irreplaceable technique or, in the best case, of replacing it. We will evaluate the degree of reproducibility that the different experiments have shown in the indication of biomarkers, and a synthesis will be attempted to obtain a consensus list that is more likely to become a guideline for clinical practice. In further analysis, we will inquire into the origin of these dysregulated metabolites in patients with bladder cancer. For this purpose, it will be helpful to compare the imbalances measured in urine with those known inside tumor cells or tissues. Although the urine analysis is sometimes considered a liquid biopsy because of its direct contact with the tumor in the bladder wall, it contains metabolites from all organs and tissues of the body, and the tumor is separated from urine by the most impermeable barrier found in mammals. The distinction between the specific and systemic responses can help understand the disease and its consequences in more depth.
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12
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Research Progress of Urine Biomarkers in the Diagnosis, Treatment, and Prognosis of Bladder Cancer. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021. [PMID: 33959906 DOI: 10.1007/978-3-030-63908-2_5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Bladder cancer (BC) is one of the most common tumor with high incidence. Relative to other cancers, BC has a high rate of recurrence, which results in increased mortality. As a result, early diagnosis and life-long monitoring are clinically significant for improving the long-term survival rate of BC patients. At present, the main methods of BC detection are cystoscopy and biopsy; however, these procedures can be invasive and expensive. This can lead to patient refusal and reluctance for monitoring. There are several BC biomarkers that have been approved by the FDA, but their sensitivity, specificity, and diagnostic accuracy are not ideal. More research is needed to identify suitable biomarkers that can be used for early detection, evaluation, and observation. There has been heavy research in the proteomics and genomics of BC and many potential biomarkers have been found. Although the advent of metabonomics came late, with the recent development of advanced analytical technology and bioinformatics, metabonomics has become a widely used diagnostic tool in clinical and biomedical research. It should be emphasized that despite progress in new biomarkers for BC diagnosis, there remains challenges and limitations in metabonomics research that affects its translation into clinical practice. In this chapter, the latest literature on BC biomarkers was reviewed.
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Song H, Qin Q, Yuan C, Li H, Zhang F, Fan L. Metabolomic Profiling of Poor Ovarian Response Identifies Potential Predictive Biomarkers. Front Endocrinol (Lausanne) 2021; 12:774667. [PMID: 34887835 PMCID: PMC8649779 DOI: 10.3389/fendo.2021.774667] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 10/26/2021] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE To characterize the serum metabolomic profile and its role in the prediction of poor ovarian response (POR). PATIENTS Twenty-five women with normal ovarian reserve (24-33 years, antral follicle count [AFC] ≥5, anti-Müllerian hormone [AMH] ≥1.2 ng/ml) as the control group and another twenty-five women with POR (19-35 years, AFC <5, AMH < 1.2 ng/ml) as the study group were collected in our study. The serum levels of the women in both groups were determined from their whole blood by untargeted liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analysis and cell signal pathways analysis were used to reveal the results. RESULTS A total of 538 different metabolites were finally identified in the two groups. Tetracosanoic acid, 2-arachidonoylglycerol, lidocaine, cortexolone, prostaglandin H2,1-naphthylamine, 5-hydroxymethyl-2-furancarboxaldehyde, 2,4-dinitrophenol, and D-erythrulose1-phosphate in POR were significantly different from control as were most important metabolites in support vector machines (p <0.05). Metabolomic profiling, together with support vector machines and pathway analysis found that the nicotinate and nicotinamide metabolism pathway, including L-aspartic acid, 6-hydroxynicotinate, maleic acid, and succinic acid semialdehyde, was identified to have significant differences in POR women compared to control women, which may be associated with ovarian reserve. CONCLUSION This study indicated that LC-MS-based untargeted metabolomics analysis of serum provided biological markers for women with POR. The nicotinate and nicotinamide metabolism pathway may offer new insight into the complementary prediction and therapeutic potential of POR. The functional associations of these metabolites need further investigation.
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Affiliation(s)
- Haixia Song
- Department of Reproductive Medicine, Shanxi Provincial People’s Hospital, Taiyuan, China
- *Correspondence: Haixia Song, ; orcid.org/0000-0002-5956-7349
| | - Qin Qin
- Department of Reproductive Medicine, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Caixia Yuan
- Department of Reproductive Medicine, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Hong Li
- Department of Reproductive Medicine, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Fang Zhang
- Department of Central Laboratory, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Lingling Fan
- Department of Reproductive Medicine, Shanxi Provincial People’s Hospital, Taiyuan, China
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Aggarwal P, Baker J, Boyd MT, Coyle S, Probert C, Chapman EA. Optimisation of Urine Sample Preparation for Headspace-Solid Phase Microextraction Gas Chromatography-Mass Spectrometry: Altering Sample pH, Sulphuric Acid Concentration and Phase Ratio. Metabolites 2020; 10:metabo10120482. [PMID: 33255680 PMCID: PMC7760603 DOI: 10.3390/metabo10120482] [Citation(s) in RCA: 5] [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: 09/28/2020] [Revised: 11/17/2020] [Accepted: 11/17/2020] [Indexed: 12/21/2022] Open
Abstract
Headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) can be used to measure volatile organic compounds (VOCs) in human urine. However, there is no widely adopted standardised protocol for the preparation of urine samples for analysis resulting in an inability to compare studies reliably between laboratories. This paper investigated the effect of altering urine sample pH, volume, and vial size for optimising detection of VOCs when using HS-SPME-GC-MS. This is the first, direct comparison of H2SO4, HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H2SO4 is more effective at optimising detection of VOCs than HCl or NaOH. H2SO4 resulted in a significantly larger mean number of VOCs being identified per sample (on average, 33.5 VOCs to 24.3 in HCl or 12.2 in NaOH treated urine) and more unique VOCs, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H2SO4 to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification.
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Affiliation(s)
- Prashant Aggarwal
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK; (P.A.); (J.B.); (C.P.)
- School of Medicine, Cedar House, University of Liverpool, Liverpool L69 3GE, UK
| | - James Baker
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK; (P.A.); (J.B.); (C.P.)
- School of Medicine, Cedar House, University of Liverpool, Liverpool L69 3GE, UK
| | - Mark T. Boyd
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK;
| | - Séamus Coyle
- Palliative Care Institute Liverpool, Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK;
- Clatterbridge Cancer Centre, Liverpool L7 8YA, UK
| | - Chris Probert
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK; (P.A.); (J.B.); (C.P.)
| | - Elinor A. Chapman
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK; (P.A.); (J.B.); (C.P.)
- Palliative Care Institute Liverpool, Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK;
- School of Medical Sciences, Bangor University, Bangor, Gwynedd LL57 2DG, UK
- Correspondence:
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Fraga-Corral M, Carpena M, Garcia-Oliveira P, Pereira AG, Prieto MA, Simal-Gandara J. Analytical Metabolomics and Applications in Health, Environmental and Food Science. Crit Rev Anal Chem 2020; 52:712-734. [DOI: 10.1080/10408347.2020.1823811] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- M. Fraga-Corral
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - M. Carpena
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
| | - P. Garcia-Oliveira
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - A. G. Pereira
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - M. A. Prieto
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
| | - J. Simal-Gandara
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
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Struck-Lewicka W, Wawrzyniak R, Artymowicz M, Kordalewska M, Markuszewski M, Matuszewski M, Gutknecht P, Siebert J, Markuszewski MJ. GC-MS-based untargeted metabolomics of plasma and urine to evaluate metabolic changes in prostate cancer. J Breath Res 2020; 14:047103. [DOI: 10.1088/1752-7163/abaeca] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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17
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Gas chromatography-mass spectrometry untargeted profiling of non-Hodgkin's lymphoma urinary metabolite markers. Anal Bioanal Chem 2020; 412:7469-7480. [PMID: 32897412 DOI: 10.1007/s00216-020-02881-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/08/2020] [Accepted: 08/13/2020] [Indexed: 12/12/2022]
Abstract
Non-Hodgkin's lymphoma (NHL) is a cancer of the lymphatic system where the lymphoid and hematopoietic tissues are infiltrated by malignant neoplasms of B, T, and natural killer lymphocytes. Effective and less invasive methods for NHL screening are urgently needed. Herein, we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to investigate metabolic changes in non-volatile derivatized compounds from urine samples of NHL patients (N = 15) and compare them to healthy controls (N = 34). Uni- and multivariate data analysis showed 18 endogenous metabolites, including amino acids and their metabolites, sugars, small organic acids, and vitamins, as statistically significant for group differentiation. A receiver operating characteristic curve (ROC) generated from a support vector machine (SVM) algorithm-based model achieved 0.998 of predictive accuracy, displaying the potential and relevance of GC-MS-detected urinary non-volatile compounds for predictive purposes. Furthermore, a specific panel of key metabolites was also evaluated, showing similar results. All in all, our results indicate that this robust GC-MS method is an effective screening tool for NHL diagnosis and it is able to highlight different pathways of the disease. Graphical Abstract.
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18
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Chen L, Zhong F, Zhu J. Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches. Metabolites 2020; 10:E348. [PMID: 32867165 PMCID: PMC7570162 DOI: 10.3390/metabo10090348] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 08/19/2020] [Accepted: 08/23/2020] [Indexed: 01/11/2023] Open
Abstract
This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.
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Affiliation(s)
- Li Chen
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210, USA;
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Fanyi Zhong
- Department of Chemistry and Biochemistry, Miami University, Oxford, OH 45056, USA;
| | - Jiangjiang Zhu
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210, USA;
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
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19
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Zheng F, Zhao X, Zeng Z, Wang L, Lv W, Wang Q, Xu G. Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry. Nat Protoc 2020; 15:2519-2537. [PMID: 32581297 DOI: 10.1038/s41596-020-0341-5] [Citation(s) in RCA: 117] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 04/20/2020] [Indexed: 01/20/2023]
Abstract
Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.
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Affiliation(s)
- Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Zhongda Zeng
- Dalian ChemDataSolution Information Technology Co. Ltd., Dalian, China
| | - Lichao Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Qingqing Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. .,University of Chinese Academy of Sciences, Beijing, China.
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Jarsiah P, Roehrich J, Wyczynski M, Hess C. Phase I metabolites (organic acids) of gamma‐hydroxybutyric acid–validated quantification using GC–MS and description of endogenous concentration ranges. Drug Test Anal 2020; 12:1135-1143. [DOI: 10.1002/dta.2820] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/05/2020] [Accepted: 05/10/2020] [Indexed: 01/04/2023]
Affiliation(s)
- Pouria Jarsiah
- Institute of Forensic Medicine, Forensic Toxicology Johannes Gutenberg University Mainz Mainz Germany
- Special Laboratory, Medical Care Centers Dr. Eberhard & Partner Dortmund Germany
| | - Joerg Roehrich
- Institute of Forensic Medicine, Forensic Toxicology Johannes Gutenberg University Mainz Mainz Germany
| | - Marek Wyczynski
- Special Laboratory, Medical Care Centers Dr. Eberhard & Partner Dortmund Germany
| | - Cornelius Hess
- Institute of Forensic Medicine, Forensic Toxicology Johannes Gutenberg University Mainz Mainz Germany
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21
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Liu X, Zhang M, Cheng X, Liu X, Sun H, Guo Z, Li J, Tang X, Wang Z, Sun W, Zhang Y, Ji Z. LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma. Front Oncol 2020; 10:717. [PMID: 32500026 PMCID: PMC7243740 DOI: 10.3389/fonc.2020.00717] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 04/16/2020] [Indexed: 12/17/2022] Open
Abstract
Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography-mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.
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Affiliation(s)
- Xiang Liu
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Mingxin Zhang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiangming Cheng
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China
| | - Xiaoyan Liu
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Haidan Sun
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhengguang Guo
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Jing Li
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoyue Tang
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhan Wang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China
| | - Wei Sun
- Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yushi Zhang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China
| | - Zhigang Ji
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China
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Zhu S, Huang Z, Nabi G. Fluorometric optical sensor arrays for the detection of urinary bladder cancer specific volatile organic compounds in the urine of patients with frank hematuria: a prospective case-control study. BIOMEDICAL OPTICS EXPRESS 2020; 11:1175-1185. [PMID: 32133241 PMCID: PMC7041448 DOI: 10.1364/boe.380629] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 12/05/2019] [Accepted: 12/11/2019] [Indexed: 05/11/2023]
Abstract
This study outlines a simple fluorometric optical sensor system for the sensitive, real time measurement of volatile organic compounds (VOCs) as biomarkers of urinary bladder cancer in patients presenting with frank hematuria and confirmed to have the disease on histopathology. Arrays of 24 sensor points based on fluorescence VOC sensitive materials were made. Urine samples of 38 consecutive patients with pathologically confirmed bladder tumours and 41 age and gender matched healthy controls were recruited and analysed using this sensor array. This system correctly classified 68 out of 79 urine samples with 84.21% sensitivity and 87.80% specificity; the system also achieved 66.67% sensitivity and 75.00% specificity for classification of high-grade and low-grade bladder cancer patients. This study showed promising results in the detection of urinary bladder cancer as well as to classify high grade versus low grade bladder cancers.
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Affiliation(s)
- Simian Zhu
- Division of Imaging Science and Technology, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
| | - Zhihong Huang
- School of Science and Engineering, University of Dundee, Dundee, DD1 4HN, UK
| | - Ghulam Nabi
- Division of Imaging Science and Technology, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
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Kowalczyk T, Ciborowski M, Kisluk J, Kretowski A, Barbas C. Mass spectrometry based proteomics and metabolomics in personalized oncology. Biochim Biophys Acta Mol Basis Dis 2020; 1866:165690. [PMID: 31962175 DOI: 10.1016/j.bbadis.2020.165690] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 12/18/2019] [Accepted: 01/15/2020] [Indexed: 02/06/2023]
Abstract
Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.
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Affiliation(s)
- Tomasz Kowalczyk
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Michal Ciborowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Joanna Kisluk
- Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland
| | - Adam Kretowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland; Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Coral Barbas
- Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Madrid, Spain.
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Yu J, Liu X, Guo J, Zhao J, Li Y, Sun C, Liu L. GC–MS analysis of organic acids in rat urine: A protocol of direct ultrasound‐assisted derivatization. Biomed Chromatogr 2020; 34:e4765. [DOI: 10.1002/bmc.4765] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 11/15/2019] [Accepted: 11/24/2019] [Indexed: 12/16/2022]
Affiliation(s)
- Jiaying Yu
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Xiaowei Liu
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Jing Guo
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Jinhui Zhao
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Ying Li
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Changhao Sun
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
| | - Liyan Liu
- Department of Nutrition and Food Hygiene, Public Health CollegeHarbin Medical University Harbin P. R. China
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Wang Z, Liu X, Liu X, Sun H, Guo Z, Zheng G, Zhang Y, Sun W. UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma. BMC Cancer 2019; 19:1195. [PMID: 31805976 PMCID: PMC6896793 DOI: 10.1186/s12885-019-6354-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 11/11/2019] [Indexed: 12/25/2022] Open
Abstract
Background To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC. Methods In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. Results The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N′-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria. Conclusions UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.
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Affiliation(s)
- Zhan Wang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Xiaoyan Liu
- Core facility of instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China
| | - Xiang Liu
- Core facility of instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China
| | - Haidan Sun
- Core facility of instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China
| | - Zhengguang Guo
- Core facility of instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China
| | - Guoyang Zheng
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Yushi Zhang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China.
| | - Wei Sun
- Core facility of instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
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Manzi M, Riquelme G, Zabalegui N, Monge ME. Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics. J Pharm Biomed Anal 2019; 178:112905. [PMID: 31707200 DOI: 10.1016/j.jpba.2019.112905] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 09/27/2019] [Accepted: 10/01/2019] [Indexed: 12/24/2022]
Abstract
The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.
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Affiliation(s)
- Malena Manzi
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Biológica, Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Junín 956, C1113AAD, Ciudad de Buenos Aires, Argentina
| | - Gabriel Riquelme
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Inorgánica, Analítica y Química Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
| | - Nicolás Zabalegui
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Inorgánica, Analítica y Química Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
| | - María Eugenia Monge
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina.
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Yang C, Sun X, Wang H, Lu T, Wu K, Guan Y, Tang J, Liang J, Sun R, Guo Z, Zheng S, Wu X, Jiang H, Jiang X, Zhong B, Niu X, Sun S, Wang X, Chen M, Fu G. Metabolomic profiling identifies novel biomarkers and mechanisms in human bladder cancer treated with submucosal injection of gemcitabine. Int J Mol Med 2019; 44:1952-1962. [PMID: 31545404 PMCID: PMC6777689 DOI: 10.3892/ijmm.2019.4347] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 09/06/2019] [Indexed: 01/22/2023] Open
Abstract
Bladder cancer (BCa) is a common urinary tract malignancy with frequent recurrences after initial resection. Submucosal injection of gemcitabine prior to transurethral resection of bladder tumor (TURBT) may prevent recurrence of urothelial cancer. However, the underlying mechanism remains unknown. In the present study, ultra-performance liquid chromatography Q-Exactive mass spectrometry was used to profile tissue metabolites from 12 BCa patients. The 48 samples included pre- and post-gemcitabine treatment BCa tissues, as well as adjacent normal tissues. Principal component analysis (PCA) revealed that the metabolic profiles of pre-gemcitabine BCa tissues differed significantly from those of pre-gemcitabine normal tissues. A total of 34 significantly altered metabolites were further analyzed. Pathway analysis using MetaboAnalyst identified three metabolic pathways closely associated with BCa, including glutathione, purine and thiamine metabolism, while gluta-thione metabolism was also identified by the enrichment analysis using MetaboAnalyst. In search of the possible targets of gemcitabine, metabolite profiles were compared between the pre-gemcitabine normal and post-gemcitabine BCa tissues. Among the 34 metabolites associated with BCa, the levels of bilirubin and retinal recovered in BCa tissues treated with gemcitabine. When comparing normal bladder tissues with and without gemcitabine treatment, among the 34 metabolites associated with BCa, it was observed that histamine change may be associated with the prevention of relapse, whereas thiamine change may be involved in possible side effects. Therefore, by employing a hypothesis-free tissue-based metabolomics study, the present study investigated the metabolic signatures of BCa and found that bilirubin and retinal may be involved in the mechanism underlying the biomolecular action of submucosal injection of gemcitabine in urothelial BCa.
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Affiliation(s)
- Chao Yang
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Xian Sun
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Hengbing Wang
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Ting Lu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Keqing Wu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Yusheng Guan
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Jing Tang
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Jian Liang
- Center of Reproduction and Genetic, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Rongli Sun
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, P.R. China
| | - Zhongying Guo
- Department of Pathology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Sinian Zheng
- Department of Urology, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang 315040, P.R. China
| | - Xiaoli Wu
- Department of Pharmacy, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Hesong Jiang
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Xi Jiang
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Bing Zhong
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Xiaobing Niu
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Suan Sun
- Department of Pathology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
| | - Xinru Wang
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Minjian Chen
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Guangbo Fu
- Department of Urology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu 223300, P.R. China
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Jacyna J, Wawrzyniak R, Balayssac S, Gilard V, Malet-Martino M, Sawicka A, Kordalewska M, Nowicki Ł, Kurek E, Bulska E, Patejko M, Markuszewski M, Gutknecht P, Matuszewski M, Siebert J, Kaliszan R, Markuszewski MJ. Urinary metabolomic signature of muscle-invasive bladder cancer: A multiplatform approach. Talanta 2019; 202:572-579. [DOI: 10.1016/j.talanta.2019.05.039] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Revised: 05/07/2019] [Accepted: 05/08/2019] [Indexed: 12/25/2022]
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Kouznetsova VL, Kim E, Romm EL, Zhu A, Tsigelny IF. Recognition of early and late stages of bladder cancer using metabolites and machine learning. Metabolomics 2019; 15:94. [PMID: 31222577 DOI: 10.1007/s11306-019-1555-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 06/10/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and biopsy. This process is expensive, unpleasant, and may have severe side effects. Recent growth in the power and accessibility of machine-learning software has allowed for the development of new, non-invasive diagnostic methods whose accuracy and sensitivity are uncompromising to function. OBJECTIVES The goal of this research was to elucidate the biomarkers including metabolites and corresponding genes for different stages of BCa, show their distinguishing and common features, and create a machine-learning model for classification of stages of BCa. METHODS Sets of metabolites for early and late stages, as well as common for both stages were analyzed using MetaboAnalyst and Ingenuity® Pathway Analysis (IPA®) software. Machine-learning methods were utilized in the development of a binary classifier for early- and late-stage metabolites of BCa. Metabolites were quantitatively characterized using EDragon 1.0 software. The two modeling methods used are Multilayer Perceptron (MLP) and Stochastic Gradient Descent (SGD) with a logistic regression loss function. RESULTS We explored metabolic pathways related to early-stage BCa (Galactose metabolism and Starch and sucrose metabolism) and to late-stage BCa (Glycine, serine, and threonine metabolism, Arginine and proline metabolism, Glycerophospholipid metabolism, and Galactose metabolism) as well as those common to both stages pathways. The central metabolite impacting the most cancerogenic genes (AKT, EGFR, MAPK3) in early stage is D-glucose, while late-stage BCa is characterized by significant fold changes in several metabolites: glycerol, choline, 13(S)-hydroxyoctadecadienoic acid, 2'-fucosyllactose. Insulin was also seen to play an important role in late stages of BCa. The best performing model was able to predict metabolite class with an accuracy of 82.54% and the area under precision-recall curve (PRC) of 0.84 on the training set. The same model was applied to three separate sets of metabolites obtained from public sources, one set of the late-stage metabolites and two sets of the early-stage metabolites. The model was better at predicting early-stage metabolites with accuracies of 72% (18/25) and 95% (19/20) on the early sets, and an accuracy of 65.45% (36/55) on the late-stage metabolite set. CONCLUSION By examining the biomarkers present in the urine samples of BCa patients as compared with normal patients, the biomarkers associated with this cancer can be pinpointed and lead to the elucidation of affected metabolic pathways that are specific to different stages of cancer. Development of machine-learning model including metabolites and their chemical descriptors made it possible to achieve considerable accuracy of prediction of stages of BCa.
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Affiliation(s)
- Valentina L Kouznetsova
- Moores Cancer Center, UC San Diego, San Diego, USA
- San Diego Supercomputer Center, UC San Diego, San Diego, USA
| | - Elliot Kim
- REHS Program UC San Diego, San Diego, USA
| | | | - Alan Zhu
- REHS Program UC San Diego, San Diego, USA
| | - Igor F Tsigelny
- Moores Cancer Center, UC San Diego, San Diego, USA.
- San Diego Supercomputer Center, UC San Diego, San Diego, USA.
- Department of Neurosciences, UC San Diego, San Diego, USA.
- CureMatch Inc., San Diego, USA.
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Tang X, You J, Liu D, Xia M, He L, Liu H. 5-Hydroxyhexanoic Acid Predicts Early Renal Functional Decline in Type 2 Diabetes Patients with Microalbuminuria. Kidney Blood Press Res 2019; 44:245-263. [DOI: 10.1159/000498962] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 01/14/2019] [Indexed: 11/19/2022] Open
Abstract
Background/Aims: Diabetic nephropathy (DN) is a leading cause of end-stage renal disease. Microalbuminuria (MA) is widely used to predict early progressive renal function decline (ERFD) of DN in type 2 diabetes mellitus (T2D) patients, but the sensitivity and specificity of MA have been questioned. Here, we determined the urine metabolites differences between T2D patients with MA who maintained stable renal function and those who progressed to ERFD in order to identify specific biomarkers of the progression of renal dysfunction. Methods: A total of 102 T2D patients with MA and normal renal function at baseline were followed up for 5–6 years. Of these, 52 patients were selected and classified into two groups according to the later renal function; 25 patients who experienced ERFD were regarded as the progressive group, while 27 patients who maintained stable renal function were considered as the stable group. In the pilot study, untargeted, broad-spectrum urine metabolomics was performed on the urine of 12 subjects from the progressive group (5 patients as “progressors”) and stable group (7 patients as “non-progressors”) to discover candidate markers. We then used a targeted metabolomics analysis to identify the selected markers in the urine of an additional 40 patients (20 from the progressive group as cases, and 20 from the stable group as controls) in the validation study. Results: A total of 318 known metabolites were detected in the pilot study and 6 metabolites with significant difference between progressors and non-progressors were identified. The levels of 4 metabolites, including azelaic acid, adipic acid, 5-hydroxyhexanoic acid, and L-tryptophan decreased significantly, while levels of L-pyroglutamic acid and D-norvaline increased observably in the progressors compared with non-progressors. Furthermore, in the validation study, 6 metabolites were confirmed by quantitative measurements and their concentrations were consistent with the changes in the pilot study. Concentrations of L-pyroglutamic acid and D-norvaline still increased in the cases, but were not statistically significant. Of the 4 metabolites with decreased concentrations among the cases, only 5-hydroxyhexanoic acid remained statistically significant while the other 3 metabolites did not differ between cases and controls. Conclusion: We have identified urine metabolites and shown that 5-hydroxyhexanoic acid can be used as a predictor of progression of ERFD in T2D patients with MA. This finding provides the new perspective that 5-hydroxyhexanoic acid may be useful to identify T2D patients with MA who are at risk of ERFD.
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Amara CS, Vantaku V, Lotan Y, Putluri N. Recent advances in the metabolomic study of bladder cancer. Expert Rev Proteomics 2019; 16:315-324. [PMID: 30773067 DOI: 10.1080/14789450.2019.1583105] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.
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Affiliation(s)
- Chandra Sekhar Amara
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA
| | - Venkatrao Vantaku
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA
| | - Yair Lotan
- b Department of Urology , University of Texas Southwestern , Dallas , TX , USA
| | - Nagireddy Putluri
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA.,c Dan L. Duncan Cancer Center, Advanced Technology Core, Alkek Center for Molecular Discovery , Baylor College of Medicine , Houston , TX , USA
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Zhang WT, Zhang ZW, Guo YD, Wang LS, Mao SY, Zhang JF, Liu MN, Yao XD. Discovering biomarkers in bladder cancer by metabolomics. Biomark Med 2018; 12:1347-1359. [PMID: 30507300 DOI: 10.2217/bmm-2018-0229] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
It has become increasingly clear that the development of cancer, a multifactorial disease, cannot be explained by a single molecule or gene mutation. As a new discipline, metabolomics focuses on the body's metabolite changes, and attempts to find differences to explain the development of cancer; it has proven to be effective and credible. Metabolic studies of bladder cancer (BCa) lag behind those of other tumors. This review systematically outlines the specific process of metabolomics and the use of metabolomics in BCa studies in recent years. We have reviewed the in vitro cell line, bladder tumor tissue and biofluid (urine, plasma and serum) studies used in metabolomics analyses of BCa. The advantages and drawbacks of the use of different samples were compared. Based on the available studies, we have further described the aberrant metabolic pathways of BCa and have suggested some metabolites that may be potential biomarkers for BCa detection.
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Affiliation(s)
- Wen-Tao Zhang
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China.,Anhui Medical University Shanghai Clinical College, PR China
| | - Zi-Wei Zhang
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Ya-Dong Guo
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Long-Sheng Wang
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Shi-Yu Mao
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Jun-Feng Zhang
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Meng-Nan Liu
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
| | - Xu-Dong Yao
- Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, PR China.,Anhui Medical University Shanghai Clinical College, PR China
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Lodewijk I, Dueñas M, Rubio C, Munera-Maravilla E, Segovia C, Bernardini A, Teijeira A, Paramio JM, Suárez-Cabrera C. Liquid Biopsy Biomarkers in Bladder Cancer: A Current Need for Patient Diagnosis and Monitoring. Int J Mol Sci 2018; 19:E2514. [PMID: 30149597 PMCID: PMC6163729 DOI: 10.3390/ijms19092514] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 08/16/2018] [Accepted: 08/21/2018] [Indexed: 02/08/2023] Open
Abstract
Bladder Cancer (BC) represents a clinical and social challenge due to its high incidence and recurrence rates, as well as the limited advances in effective disease management. Currently, a combination of cytology and cystoscopy is the routinely used methodology for diagnosis, prognosis and disease surveillance. However, both the poor sensitivity of cytology tests as well as the high invasiveness and big variation in tumour stage and grade interpretation using cystoscopy, emphasizes the urgent need for improvements in BC clinical guidance. Liquid biopsy represents a new non-invasive approach that has been extensively studied over the last decade and holds great promise. Even though its clinical use is still compromised, multiple studies have recently focused on the potential application of biomarkers in liquid biopsies for BC, including circulating tumour cells and DNA, RNAs, proteins and peptides, metabolites and extracellular vesicles. In this review, we summarize the present knowledge on the different types of biomarkers, their potential use in liquid biopsy and clinical applications in BC.
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Affiliation(s)
- Iris Lodewijk
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
| | - Marta Dueñas
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Carolina Rubio
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Ester Munera-Maravilla
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
| | - Cristina Segovia
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Alejandra Bernardini
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Alicia Teijeira
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
| | - Jesús M Paramio
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Cristian Suárez-Cabrera
- Molecular Oncology Unit, CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas), Avenida Complutense nº 40, 28040 Madrid, Spain.
- Biomedical Research Institute I+12, University Hospital "12 de Octubre", Av Córdoba s/n, 28041 Madrid, Spain.
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Wang Y, Feng R, He C, Su H, Ma H, Wan JB. An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics. J Pharm Biomed Anal 2018; 157:171-179. [PMID: 29802989 DOI: 10.1016/j.jpba.2018.05.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 04/17/2018] [Accepted: 05/15/2018] [Indexed: 01/19/2023]
Abstract
The narrow linear range and the limited scan time of the given ion make the quantification of the features challenging in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics with the full-scan mode. And metabolite identification is another bottleneck of untargeted analysis owing to the difficulty of acquiring MS/MS information of most metabolites detected. In this study, an integrated workflow was proposed using the newly established multiple ion monitoring mode with time-staggered ion lists (tsMIM) and target-directed data-dependent acquisition with time-staggered ion lists (tsDDA) to improve data acquisition and metabolite identification in UHPLC/Q-TOF MS-based untargeted metabolomics. Compared to the conventional untargeted metabolomics, the proprosed workflow exhibited the better repeatability before and after data normalization. After selecting features with the significant change by statistical analysis, MS/MS information of all these features can be obtained by tsDDA analysis to facilitate metabolite identification. Using time-staggered ion lists, the workflow is more sensitive in data acquisition, especially for the low-abundant features. Moreover, the metabolites with low abundance tend to be wrongly integrated and triggered by full scan-based untargeted analysis with MSE acquisition mode, which can be greatly improved by the proposed workflow. The integrated workflow was also successfully applied to discover serum biosignatures for the genetic modification of fat-1 in mice, which indicated its practicability and great potential in future metabolomics studies.
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Affiliation(s)
- Yang Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China
| | - Ruibing Feng
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China
| | - Chengwei He
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China
| | - Huanxing Su
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China
| | - Huan Ma
- Cardiac Rehabilitation Department, Guangdong Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jian-Bo Wan
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, 999078, China.
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35
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Current and future perspectives of functional metabolomics in disease studies-A review. Anal Chim Acta 2018; 1037:41-54. [PMID: 30292314 DOI: 10.1016/j.aca.2018.04.006] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 03/20/2018] [Accepted: 04/13/2018] [Indexed: 12/16/2022]
Abstract
Functional metabolomics is a new concept, which studies the functions of metabolites and related enzymes focused on metabolomics. It overcomes the shortcomings of traditional discovery metabolomics of mainly relying on literatures for biological interpretation. Functional metabolomics has many advantages. Firstly, the functional roles of metabolites and related metabolic enzymes are focused. Secondly, the in vivo and in vitro experiments are conducted to validate the metabolomics findings, therefore, increasing the reliability of metabolomics study and producing the new knowledge. Thirdly, functional metabolomics can be used by biologists to investigate functions of metabolites, and related genes and proteins. In this review, we summarize the analytical, biological and clinical platforms used in functional metabolomics studies. Recent progresses of functional metabolomics in cancer, metabolic diseases and biological phenotyping are reviewed, and future development is also predicted. Because of the tremendous advantages of functional metabolomics, it will have a bright future.
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36
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Zhang X, Li J, Xie B, Wu B, Lei S, Yao Y, He M, Ouyang H, Feng Y, Xu W, Yang S. Comparative Metabolomics Analysis of Cervicitis in Human Patients and a Phenol Mucilage-Induced Rat Model Using Liquid Chromatography Tandem Mass Spectrometry. Front Pharmacol 2018; 9:282. [PMID: 29670527 PMCID: PMC5893906 DOI: 10.3389/fphar.2018.00282] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Accepted: 03/13/2018] [Indexed: 12/14/2022] Open
Abstract
Cervicitis is an exceedingly common gynecological disorder that puts women at high risk of sexually transmitted infections and induces a series of reproductive system diseases. This condition also has a significant impact on quality of life and is commonly misdiagnosed in clinical practice due to its complicated pathogenesis. In the present study, we performed non-targeted plasma metabolomics analysis of cervicitis in both plasma samples obtained from human patients and plasma samples from a phenol mucilage induced rat model of cervicitis, using ultra-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. In addition to differences in histopathology, we identified differences in the metabolic profile between the cervicitis and control groups using unsupervised principal component analysis and orthogonal projections to latent structures discriminant analysis. These results demonstrated changes in plasma metabolites, with 27 and 22 potential endogenous markers identified in rat and human samples, respectively. The metabolic pathway analysis showed that linoleic acid, arachidonic acid, ether lipid, and glycerophospholipid metabolism are key metabolic pathways involved in cervicitis. This study showed the rat model was successfully created and applied to understand the pathogenesis of cervicitis.
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Affiliation(s)
- Xiaoyong Zhang
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Junmao Li
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
- State Key Laboratory of Innovative Drug and Efficient Energy-Saving Pharmaceutical Equipment, Nanchang, China
| | - Bin Xie
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Bei Wu
- Nanchang Institute for Food and Drug Control, Nanchang, China
| | - Shuangxia Lei
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Yun Yao
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Mingzhen He
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
- State Key Laboratory of Innovative Drug and Efficient Energy-Saving Pharmaceutical Equipment, Nanchang, China
| | - Hui Ouyang
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Yulin Feng
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
- State Key Laboratory of Innovative Drug and Efficient Energy-Saving Pharmaceutical Equipment, Nanchang, China
| | - Wen Xu
- Second College of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shilin Yang
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
- State Key Laboratory of Innovative Drug and Efficient Energy-Saving Pharmaceutical Equipment, Nanchang, China
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37
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GC-MS-Based Endometabolome Analysis Differentiates Prostate Cancer from Normal Prostate Cells. Metabolites 2018; 8:metabo8010023. [PMID: 29562689 PMCID: PMC5876012 DOI: 10.3390/metabo8010023] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 03/12/2018] [Accepted: 03/16/2018] [Indexed: 12/14/2022] Open
Abstract
Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography–mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine.
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38
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Zhou Y, Hu C, Zhao X, Luo P, Lu J, Li Q, Chen M, Yan D, Lu X, Kong H, Jia W, Xu G. Serum Metabolomics Study of Gliclazide-Modified-Release-Treated Type 2 Diabetes Mellitus Patients Using a Gas Chromatography–Mass Spectrometry Method. J Proteome Res 2018; 17:1575-1585. [DOI: 10.1021/acs.jproteome.7b00866] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Yang Zhou
- 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
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
- Institute for Metabolic Disease, Fengxian Central Hospital Affiliated to Southern Medical University, 6600 Nanfeng Road, Shanghai 201499, People’s Republic of China
| | - Xinjie Zhao
- 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
| | - Ping Luo
- 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
| | - Jingyi Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Qing Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Miao Chen
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Dandan Yan
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Xin Lu
- 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
| | - Hongwei Kong
- 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
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Guowang Xu
- 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
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Katsila T, Liontos M, Patrinos GP, Bamias A, Kardamakis D. The New Age of -omics in Urothelial Cancer - Re-wording Its Diagnosis and Treatment. EBioMedicine 2018; 28:43-50. [PMID: 29428524 PMCID: PMC5835572 DOI: 10.1016/j.ebiom.2018.01.044] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 01/31/2018] [Accepted: 01/31/2018] [Indexed: 02/06/2023] Open
Abstract
Unmet needs in urothelial cancer management represent an important challenge in our effort to improve long-term overall and disease-free survival rates with no significant compromise in quality of life. Radical cystectomy with pelvic lymph node dissection is the standard for the management of muscle-invasive, non-metastatic cancers. In spite of a 90% local disease control, up to 50% of patients ultimately die of distant metastasis. Bladder preservation using chemo-radiation is an acceptable alternative, but optimal patient selection remains elusive. Recent research is focused on the employment of tailored-made strategies in urothelial cancer exploiting the potential of theranostics in patient selection for specific therapies. Herein, we review the current knowledge on molecular theranostics in urothelial cancer and we suggest that this is the time to move toward imaging theranostics, if tailored-made disease management and patient stratification is envisaged. Urothelial cancer management represents an important challenge. Optimum patient stratification and tailored-made theranostics remain elusive. Imaging theranostics is envisaged as a cancer roadmap.
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Affiliation(s)
- Theodora Katsila
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece; Department of Radiation Oncology, University of Patras Medical School, Patras, Greece.
| | - Michalis Liontos
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
| | - George P Patrinos
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece; Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Aristotelis Bamias
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimitrios Kardamakis
- Department of Radiation Oncology, University of Patras Medical School, Patras, Greece
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40
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Li YF, Qiu S, Gao LJ, Zhang AH. Metabolomic estimation of the diagnosis of hepatocellular carcinoma based on ultrahigh performance liquid chromatography coupled with time-of-flight mass spectrometry. RSC Adv 2018; 8:9375-9382. [PMID: 35541871 PMCID: PMC9078651 DOI: 10.1039/c7ra13616a] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2017] [Accepted: 02/23/2018] [Indexed: 01/01/2023] Open
Abstract
Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis. Metabolic characteristics of hepatocellular carcinoma (HCC) may enable the discovery of novel biomarkers for its diagnosis. In this work, metabolomics was used to investigate metabolic alterations of HCC patients. Plasma samples from HCC patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry and metabolic differences were analyzed using pattern recognition methods. 23 distinguishable metabolites were identified. The altered metabolic pathways were associated with arginine and proline metabolism, glycine, serine and threonine metabolism, steroid hormone biosynthesis, starch and sucrose metabolism, etc. To demonstrate the utility of plasma biomarkers for the diagnosis of HCC, five metabolites comprising deoxycholic acid 3-glucuronide, 6-hydroxymelatonin glucuronide, 4-methoxycinnamic acid, 11b-hydroxyprogesterone and 4-hydroxyretinoic acid were selected as candidate biomarkers. These metabolites that contributed to the combined model could significantly increase the diagnostic performance of HCC. It has proved to be a powerful tool in the discovery of new biomarkers for disease detection and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests. Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis.![]()
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Affiliation(s)
- Yuan-Feng Li
- First Affiliated Hospital
- School of Pharmacy
- Heilongjiang University of Chinese Medicine
- Harbin 150040
- China
| | - Shi Qiu
- First Affiliated Hospital
- School of Pharmacy
- Heilongjiang University of Chinese Medicine
- Harbin 150040
- China
| | - Li-Juan Gao
- First Affiliated Hospital
- School of Pharmacy
- Heilongjiang University of Chinese Medicine
- Harbin 150040
- China
| | - Ai-Hua Zhang
- First Affiliated Hospital
- School of Pharmacy
- Heilongjiang University of Chinese Medicine
- Harbin 150040
- China
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41
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Lubes G, Goodarzi M. GC-MS based metabolomics used for the identification of cancer volatile organic compounds as biomarkers. J Pharm Biomed Anal 2017; 147:313-322. [PMID: 28750734 DOI: 10.1016/j.jpba.2017.07.013] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 07/13/2017] [Accepted: 07/14/2017] [Indexed: 01/27/2023]
Abstract
A biomarker can be a metabolite, coming from a metabolic pathway or cell process, which might be employed in the diagnostic of diseases, predict patient response towards chemical therapies and/or monitor disease recurrences. Biomarkers, e.g. aldehydes or hydrocarbons, are often identified from different body fluids such as blood, urine, serum, saliva or from various tissues samples, and their concentration can vary from one sample to the other. However, the detection and the action of these biomarkers for diseases is a complicated process. Cancer is one of the main cause of death worldwide. The main characteristic of cancerous tumor is the uncontrolled growing of cells inside the organism. Likely, these uncontrolled growths are as consequence changes in the metabolism that could be analytically monitored. Depending on where the cancer cells are located, they provide different characteristics profiles. These profiles as fingerprints are used for differentiation in a comparison to normal cells. This critical study aimed at highlighting the latest progress in this area, especially in the employment of gas chromatography for the monitoring of volatile organic compounds (VOCs) and the identification of possible molecules used as biomarkers for cancer therapy.
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Affiliation(s)
- Giuseppe Lubes
- Laboratorio de Equilibrios en Solución, Universidad Simón Bolívar, Venezuela
| | - Mohammad Goodarzi
- Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
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42
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Zhao Y, Lv H, Qiu S, Gao L, Ai H. Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer. RSC Adv 2017. [DOI: 10.1039/c7ra04337f] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Prostate cancer (PCa) is the second leading cause of cancer death among men and associated with profound metabolic changes.
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Affiliation(s)
- Yunbo Zhao
- Department of General Surgery
- The First Affiliated Hospital of Jiamusi University
- Jiamusi 154003
- China
| | - Hongmei Lv
- Jiamusi College
- Heilongjiang University of Chinese Medicine
- Jiamusi 154007
- China
| | - Shi Qiu
- College of Pharmacy
- Department of Rheumatology
- First Affiliated Hospital
- Heilongjiang University of Chinese Medicine
- Harbin 150040
| | - Lijuan Gao
- College of Pharmacy
- Department of Rheumatology
- First Affiliated Hospital
- Heilongjiang University of Chinese Medicine
- Harbin 150040
| | - Huazhang Ai
- College of Pharmacy
- Department of Rheumatology
- First Affiliated Hospital
- Heilongjiang University of Chinese Medicine
- Harbin 150040
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