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Serum lipidome screening in patients with stage I non-small cell lung cancer. Clin Exp Med 2019; 19:505-513. [PMID: 31264112 PMCID: PMC6797644 DOI: 10.1007/s10238-019-00566-7] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 06/18/2019] [Indexed: 12/24/2022]
Abstract
The ability of early lung cancer diagnosis is an unmet need in clinical practice. Lung cancer metabolomic analyses conducted so far have demonstrated several abnormalities in cancer lipid profile providing a rationale for further study of blood lipidome of the patients. In the present research, we performed a targeted lipidome screening to select molecules that show promise for early lung cancer detection. The study was conducted on serum samples collected from newly diagnosed, stage I non-small cell lung cancer (NSCLC) patients and non-cancer controls. A high-throughput mass spectrometry-based platform with confirmed interlaboratory reproducibility was used. The analyzed profile consisted of acylcarnitines, sphingomyelins, phosphatidylcholines and lysophosphatidylcholines. Among the assayed lipid species, the significant differences between NSCLC and non-cancer subjects were observed in the group of phosphatidylcholines (PC) and lysophosphatidylcholines (lysoPC), especially in the levels of lysoPC a C26:0; lysoPC a C26:1; PC aa C42:4; and PC aa C34:4. The metabolites mentioned above were used to create a multivariate classification model, which reliability was proved by permutation tests as well as external validation. Our study indicated choline-containing phospholipids as potential lung cancer markers. Further investigations of phospholipidome are crucial to better describe the shifts in metabolite composition occurring in lung cancer patients.
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Sun Q, Zhao W, Wang L, Guo F, Song D, Zhang Q, Zhang D, Fan Y, Wang J. Integration of metabolomic and transcriptomic profiles to identify biomarkers in serum of lung cancer. J Cell Biochem 2019; 120:11981-11989. [PMID: 30805978 DOI: 10.1002/jcb.28482] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/02/2018] [Accepted: 01/02/2019] [Indexed: 01/24/2023]
Abstract
We used blood serum samples collected from 31 lung cancer (LC) patients and 29 healthy volunteers in this study. Levels of serum metabolites were qualitative quantified with gas chromatography-mass spectrometry (GC-MS), and the data were analyzed by partial least-squares discrimination analysis (PLS-DA). Based on the Kyoto Encyclopedia of Genes and Genomes database, we performed pathway-based analysis utilizing metabolites presented at differential abundance between the LC serum samples and the normal healthy serum samples for systematical investigation on the metabolic alterations associated with LC pathogenesis. Finally, we analyzed the significantly enriched pathways as well as their relevant differentially expressed messenger RNAs, and drawn a correlation network plot to identify the serum metabolic biomarkers and the significantly altered metabolic pathways for LC. GC-MS analysis showed that 23 of the 169 metabolites identified were significantly different. PLS-DA model revealed that 13 of these metabolites were with variable importance > 1, and particularly five were with area under curve > 0.9. Pathway-based analysis demonstrated that five of eight enriched metabolic pathways were statistically significant with false discovery rate < 0.05. Lastly, the correlation networks between these pathways and their related genes suggested that 29 genes had correlation degree > 10, which were mainly engaged in the purine metabolism. In conclusion, we identified indole-3-lactate, erythritol, adenosine-5-phosphate, paracetamol and threitol as serum metabolic biomarkers for LC through metabolomics analysis. Besides, we identified the purine metabolism as the significantly altered metabolic pathway in LC with the help of transcriptomics analysis.
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Affiliation(s)
- Quan Sun
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Wei Zhao
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Lei Wang
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Fei Guo
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Dongjian Song
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Qian Zhang
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Da Zhang
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yingzhong Fan
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jiaxiang Wang
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
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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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Glutamine Addiction and Therapeutic Strategies in Lung Cancer. Int J Mol Sci 2019; 20:ijms20020252. [PMID: 30634602 PMCID: PMC6359540 DOI: 10.3390/ijms20020252] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 01/05/2019] [Accepted: 01/07/2019] [Indexed: 12/16/2022] Open
Abstract
Lung cancer cells are well-documented to rewire their metabolism and energy production networks to support rapid survival and proliferation. This metabolic reorganization has been recognized as a hallmark of cancer. The increased uptake of glucose and the increased activity of the glycolytic pathway have been extensively described. However, over the past years, increasing evidence has shown that lung cancer cells also require glutamine to fulfill their metabolic needs. As a nitrogen source, glutamine contributes directly (or indirectly upon conversion to glutamate) to many anabolic processes in cancer, such as the biosynthesis of amino acids, nucleobases, and hexosamines. It plays also an important role in the redox homeostasis, and last but not least, upon conversion to α-ketoglutarate, glutamine is an energy and anaplerotic carbon source that replenishes tricarboxylic acid cycle intermediates. The latter is generally indicated as glutaminolysis. In this review, we explore the role of glutamine metabolism in lung cancer. Because lung cancer is the leading cause of cancer death with limited curative treatment options, we focus on the potential therapeutic approaches targeting the glutamine metabolism in cancer.
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Metabolomic study of serum, urine and bronchoalveolar lavage fluid based on gas chromatography mass spectrometry to delve into the pathology of lung cancer. J Pharm Biomed Anal 2019; 163:122-129. [DOI: 10.1016/j.jpba.2018.09.055] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 09/26/2018] [Accepted: 09/27/2018] [Indexed: 12/15/2022]
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Seijo LM, Peled N, Ajona D, Boeri M, Field JK, Sozzi G, Pio R, Zulueta JJ, Spira A, Massion PP, Mazzone PJ, Montuenga LM. Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges. J Thorac Oncol 2018; 14:343-357. [PMID: 30529598 DOI: 10.1016/j.jtho.2018.11.023] [Citation(s) in RCA: 290] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 11/20/2018] [Accepted: 11/26/2018] [Indexed: 12/12/2022]
Abstract
The present review is an update of the research and development efforts regarding the use of molecular biomarkers in the lung cancer screening setting. The two main unmet clinical needs, namely, the refinement of risk to improve the selection of individuals undergoing screening and the characterization of undetermined nodules found during the computed tomography-based screening process are the object of the biomarkers described in the present review. We first propose some principles to optimize lung cancer biomarker discovery projects. Then, we summarize the discovery and developmental status of currently promising molecular candidates, such as autoantibodies, complement fragments, microRNAs, circulating tumor DNA, DNA methylation, blood protein profiling, or RNA airway or nasal signatures. We also mention other emerging biomarkers or new technologies to follow, such as exhaled breath biomarkers, metabolomics, sputum cell imaging, genetic predisposition studies, and the integration of next-generation sequencing into study of circulating DNA. We also underline the importance of integrating different molecular technologies together with imaging, radiomics, and artificial intelligence. We list a number of completed, ongoing, or planned trials to show the clinical utility of molecular biomarkers. Finally, we comment on future research challenges in the field of biomarkers in the context of lung cancer screening and propose a design of a trial to test the clinical utility of one or several candidate biomarkers.
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Affiliation(s)
- Luis M Seijo
- Clinica Universidad de Navarra, Madrid, Spain; CIBERES, Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Madrid, Spain
| | - Nir Peled
- Oncology Division, The Legacy Heritage Oncology Center and Dr. Larry Norton Institute, Soroka Medical Center and Ben-Gurion University, Beer-Sheva, Israel
| | - Daniel Ajona
- Solid Tumors Program, Centro de Investigación Médica Aplicada, Pamplona, Spain; Navarra Institute for Health Research, Pamplona, Spain; CIBERONC, Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Department of Biochemistry and Genetics, School of Sciences, University of Navarra, Pamplona, Spain
| | - Mattia Boeri
- Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - John K Field
- The Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Gabriella Sozzi
- Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Ruben Pio
- Solid Tumors Program, Centro de Investigación Médica Aplicada, Pamplona, Spain; Navarra Institute for Health Research, Pamplona, Spain; CIBERONC, Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Department of Biochemistry and Genetics, School of Sciences, University of Navarra, Pamplona, Spain
| | - Javier J Zulueta
- Department of Pulmonology, Clinica Universidad de Navarra, Pamplona, Spain; Visiongate Inc., Phoenix, Arizona
| | - Avrum Spira
- Boston University School of Medicine, Boston, Massachusetts
| | | | | | - Luis M Montuenga
- Solid Tumors Program, Centro de Investigación Médica Aplicada, Pamplona, Spain; Navarra Institute for Health Research, Pamplona, Spain; CIBERONC, Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Department of Pathology, Anatomy and Physiology, School of Medicine, University of Navarra, Pamplona, Spain.
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Callejón-Leblic B, Pereira-Vega A, Vázquez-Gandullo E, Sánchez-Ramos JL, Gómez-Ariza JL, García-Barrera T. Study of the metabolomic relationship between lung cancer and chronic obstructive pulmonary disease based on direct infusion mass spectrometry. Biochimie 2018; 157:111-122. [PMID: 30439409 DOI: 10.1016/j.biochi.2018.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 11/07/2018] [Indexed: 12/19/2022]
Abstract
The high prevalence of lung cancer (LC) has triggered the search of biomarkers for early diagnosis of this disease. For this purpose the study of metabolic changes related to the development of lung cancer could provide interesting information about its early diagnosis. In this sense, chronic obstructive pulmonary disease (COPD), a disease associated with tumor development, is a comorbidity that increases the risk of onset and progression of lung neoplasia and has also to be considered in the study of pathology related to lung cancer. This work develop a metabolomic approach based on direct infusion mass spectrometry using a hybrid triple quadrupole-time of flight mass spectrometer (DI-ESI-QqQ-TOF-MS) in order to identify altered metabolites from serum of LC and COPD patients and evaluate its relationship and implication in the progression of LC. This methodology has been applied to 30 serum samples from LC, 30 healthy patients used as controls (HC) and 30 serum samples from COPD to found altered metabolites from both LC and COPD diseases. In addition, some metabolic differences and similarities were found in Pulmonary Emphysema and Chronic Bronchitis patients. On the other hand, altered metabolites were studied in different stages of LC (II, III and IV) to evaluate the perturbation of them throughout the progression of disease. The sample treatment consisted of the extraction of polar and non-polar metabolites from serum that was later infused into the mass spectrometer using an electrospray ionization source in positive and negative mode. Partial least squares discriminant analysis (PLS-DA) allowed a classification between LC, HC and COPD groups in all acquisition modes. A total of 35 altered and common metabolites between LC and COPD, including amino acids, fatty acids, lysophospholipids, phospholipids and triacylglycerides were identified, being alanine, aspartate and glutamate metabolism the most altered. Finally, ROC curves were applied to the dataset and metabolites with AUC value higher than 0.70 were considered as relevant in the progression of LC.
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Affiliation(s)
- B Callejón-Leblic
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain
| | - A Pereira-Vega
- Pneumonology Area of Juan Ramón Jiménez Hospital, Huelva, Spain.
| | | | | | - J L Gómez-Ariza
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain
| | - T García-Barrera
- Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Research Center on Health and Environment (RENSMA), 21007, Huelva, Spain.
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Metabolome-based biomarkers: their potential role in the early detection of lung cancer. Contemp Oncol (Pozn) 2018; 22:135-140. [PMID: 30455584 PMCID: PMC6238086 DOI: 10.5114/wo.2018.78942] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 07/21/2018] [Indexed: 02/06/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.
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59
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The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer. BMC Cancer 2018; 18:868. [PMID: 30176828 PMCID: PMC6122613 DOI: 10.1186/s12885-018-4755-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 08/16/2018] [Indexed: 01/01/2023] Open
Abstract
Background Pulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer. Methods Metabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by 1H-NMR spectroscopy. Models to discriminate between groups were trained by PLS-LDA. A test set was used for independent validation. A ROC curve was built to evaluate the diagnostic performance of potential biomarkers. Results Sensitivity, specificity, PPV and NPV of PET-CT to diagnose cancer are 96, 23, 76 and 71%. Metabolic profiles differentiate between cancer and inflammation with a sensitivity of 89%, a specificity of 87% and a MCE of 12%. Removal of the glutamate metabolite results in an increase of MCE (38%) and a decrease of both sensitivity and specificity (62%), demonstrating the importance of glutamate for discrimination. At the cut-off point 0.31 on the ROC curve, the relative glutamate concentration discriminates between cancer and inflammation with a sensitivity of 85%, a specificity of 81%, and an AUC of 0.88. PPV and NPV are 92 and 69%. In PET-positive patients with a relative glutamate level ≤ 0.31 the sensitivity to diagnose cancer reaches 100% with a PPV of 94%. In PET-negative patients, a relative glutamate level > 0.31 increases the specificity of PET from 23% to 58% and results in a high NPV of 100%. In case of discrepancy between SUVmax and the glutamate concentration, lung cancer is missed in 19% of the cases. Conclusion This study indicates that the 1H-NMR-derived relative plasma concentration of glutamate allows discrimination between lung cancer and lung inflammation. A glutamate level ≤ 0.31 in PET-positive patients corresponds to the diagnosis of lung cancer with a higher specificity and PPV than PET-CT. Glutamate levels > 0.31 in patients with PET negative lung lesions is likely to correspond with inflammation. Caution is needed for patients with conflicting SUVmax values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS. Electronic supplementary material The online version of this article (10.1186/s12885-018-4755-1) contains supplementary material, which is available to authorized users.
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Bamji-Stocke S, van Berkel V, Miller DM, Frieboes HB. A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment. Metabolomics 2018; 14:81. [PMID: 29983671 PMCID: PMC6033515 DOI: 10.1007/s11306-018-1376-2] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 05/29/2018] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort. OBJECTIVES This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes. METHOD We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals. RESULT Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis. CONCLUSION We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.
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Affiliation(s)
- Sanaya Bamji-Stocke
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA
| | - Victor van Berkel
- Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, KY, USA
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA
| | - Donald M Miller
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA
| | - Hermann B Frieboes
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA.
- James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA.
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Hanash SM, Ostrin EJ, Fahrmann JF. Blood based biomarkers beyond genomics for lung cancer screening. Transl Lung Cancer Res 2018; 7:327-335. [PMID: 30050770 DOI: 10.21037/tlcr.2018.05.13] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
While there is considerable interest at the present time in the development of so-called liquid biopsy approaches for cancer detection based notably on circulating tumor DNA, there are other types of potential biomarkers that show promise for lung cancer screening and early detection. Here we review approaches and some of the promising markers based on proteomics, metabolomics and the immune response to tumor antigens in the form of autoantibodies.
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Affiliation(s)
- Samir M Hanash
- Department of Clinical Cancer Prevention, MD Anderson Cancer Center, Houston, TX, USA
| | - Edwin Justin Ostrin
- Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Johannes F Fahrmann
- Department of Clinical Cancer Prevention, MD Anderson Cancer Center, Houston, TX, USA
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Giskeødegård GF, Madssen TS, Euceda LR, Tessem MB, Moestue SA, Bathen TF. NMR-based metabolomics of biofluids in cancer. NMR IN BIOMEDICINE 2018; 32:e3927. [PMID: 29672973 DOI: 10.1002/nbm.3927] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 02/13/2018] [Accepted: 03/07/2018] [Indexed: 06/08/2023]
Abstract
This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.
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Affiliation(s)
- Guro F Giskeødegård
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Torfinn S Madssen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Leslie R Euceda
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Siver A Moestue
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
- Department of Health Science, Nord University, Bodø, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
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63
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Zhang J, Xu J, Lu H, Ding J, Yu D, Li P, Xiong J, Liu X, Chen H, Wei Y. Altered phosphatidylcholines expression in sputum for diagnosis of non-small cell lung cancer. Oncotarget 2018; 7:63158-63165. [PMID: 27542233 PMCID: PMC5325353 DOI: 10.18632/oncotarget.11283] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 07/19/2016] [Indexed: 11/25/2022] Open
Abstract
Non–small cell lung cancer (NSCLC) is a leading cause of cancer mortality worldwide, and early diagnosis needs to be improved. We examined whether neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) could be used to detect sputum lipids expression changes to enable earlier diagnosis. Overall, 167 NSCLC patients and 140 controls were enrolled. The main peaks in the sputum of patients with NSCLC patients differed from controls (83.3% of total variability), and the signals were not associated with pathological type, TNM stage or smoking history. The relative abundance of peaks at m/z734, m/ z756, m/z772, m/z782, m/z798 and m/z803 reliably distinguished NSCLC sputum from control. Collision-induced dissociation confirmed that m/z734, m/z756, and m/z772 represented [DPPC + H]+, [DPPC + Na]+, and [DPPC + K]+, respectively, and m/z782, m/z798, and m/z803 represented sphingomyelin, phosphatidylglycerol, and phosphatidylglycerolphosphate, respectively. The relative abundance of DPPC was clearly lower in NSCLC sputum than in control, and the relative abundances of phosphatidylglycerol and phosphatidylglycerolphosphate were higher in NSCLC sputum than in control. The detection of changes in sputum lipids with ND-EESI-MS may be a noninvasive, radiation-free, relatively inexpensive, repeatable, and efficient method for diagnosis of NSCLC.
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Affiliation(s)
- Jianyong Zhang
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, P. R. China
| | - Jianjun Xu
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, P. R. China
| | - Haiyan Lu
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi Province 330013, P. R. China
| | - Jianhua Ding
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi Province 330013, P. R. China
| | - Dongliang Yu
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, P. R. China
| | - Penghui Li
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi Province 330013, P. R. China
| | - Jianwen Xiong
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, P. R. China
| | - Xingxing Liu
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi Province 330013, P. R. China
| | - Huanwen Chen
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang, Jiangxi Province 330013, P. R. China
| | - Yiping Wei
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, P. R. China
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Hu JM, Sun HT. Serum proton NMR metabolomics analysis of human lung cancer following microwave ablation. Radiat Oncol 2018; 13:40. [PMID: 29530051 PMCID: PMC5848604 DOI: 10.1186/s13014-018-0982-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 02/22/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND To find potential serum biomarkers of microwave ablation (MWA) for treatment of human lung cancer by 1H nuclear magnetic resonance (NMR)-based metabolomics analysis. METHODS Serum specimens collected from 43 healthy individuals, 39 patients with advanced non-small cell lung cancer (NSCLC) and 38 NSCLC patients treated with MWA, were subjected to 1H NMR-based metabolomics analysis. Partial least squares discriminant analysis was used to analyze the data. RESULTS Compared with healthy controls, NSCLC patients showed significantly elevated serum levels of lactate, alanine, glutamate, proline, glycoprotein, phenylalanine, tyrosine and tryptophan, and markedly decreased serum levels of glucose, taurine, glutamine, glycine, phosphocreatine and threonine (p < 0.05). MWA treatment reversed the metabolic profiles of NSCLC patients towards the control group. CONCLUSIONS 1H NMR-based metabolomics analysis enhanced the current understanding of the mechanisms involved in NSCLC, and uncovered the therapeutic potential of MWA for treatment of NSCLC. The above disturbed serum metabolites were proposed to be the potential biomarkers that may help to predict NSCLC and to evaluate the efficacy of MWA in the treatment of NSCLC.
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Affiliation(s)
- Jian-Ming Hu
- Thoracic surgeons, Jiangxi Provincial People’s Hospital, 152 Patriotic Road, Nanchang City, 333000 People’s Republic of China
| | - Huang-Tao Sun
- Thoracic surgeons, Jiangxi Provincial People’s Hospital, 152 Patriotic Road, Nanchang City, 333000 People’s Republic of China
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Yu L, Li K, Zhang X. Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review. Oncotarget 2017; 8:115774-115786. [PMID: 29383200 PMCID: PMC5777812 DOI: 10.18632/oncotarget.22404] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 09/21/2017] [Indexed: 02/05/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death. Next-generation metabolomics is becoming a powerful emerging technology for studying the systems biology and chemistry of health and disease. This mini review summarized the main platforms of next-generation metabolomics and its main applications in lung cancer including early diagnosis, pathogenesis, classifications and precision medicine. The period covers between 2009 and August, 2017. The major issues and future directions of metabolomics in lung cancer research and clinical applications were also discussed.
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Affiliation(s)
- Li Yu
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China
| | - Kefeng Li
- School of Medicine, University of California San Diego, San Diego, CA, USA
| | - Xiaoye Zhang
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China
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Shen J, Ye Y, Chang DW, Huang M, Heymach JV, Roth JA, Wu X, Zhao H. Circulating metabolite profiles to predict overall survival in advanced non-small cell lung cancer patients receiving first-line chemotherapy. Lung Cancer 2017; 114:70-78. [PMID: 29173770 DOI: 10.1016/j.lungcan.2017.10.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 10/12/2017] [Accepted: 10/30/2017] [Indexed: 12/15/2022]
Abstract
OBJECTIVES The prognosis for advanced-stage non-small cell lung cancer (NSCLC) is usually poor. However, survival may be variable and difficult to predict. In the current study, we aimed to identify circulating metabolites as potential predictive biomarkers for overall survival of advanced-stage (III/IV) NSCLC patients treated with first-line platinum-based chemotherapy. MATERIALS AND METHODS Using two-stage study design, we performed global metabolomic profiling in blood of 220 advanced-stage NSCLC patients, including 110 with poor survival and 110 with good survival. Metabolomic profiling was conducted using Metabolon platform. The association of each metabolite with survival was assessed by Cox proportional hazard regression model with adjustment for covariates. RESULTS AND CONCLUSION We found levels of 4 metabolites, caffeine, paraxanthine, stachydrine, and methyl glucopyranoside (alpha+beta), differed significantly between NSCLC patients with poor and good survival in both discovery and validation phases (P<0.05). Interestingly, majority of the identified metabolites are involved in caffeine metabolism, and 2 metabolites are related to coffee intake. In fact, caffeine metabolism pathway was the only significant pathway identified which significantly differed between NSCLC patients with poor and good survival (P=1.48E-07) in the pathway analysis. We also found 4 metabolites whose levels were significantly associated with good survival in both discovery and validation phases. Strong cumulative effects on overall survival were observed for these 4 metabolites. In conclusion, we identified a panel of metabolites including metabolites in caffeine metabolism pathway that may predict survival outcome in advanced-stage NSCLC patients. The identified small metabolites may be useful biomarker candidates to help identify patients who may benefit from platinum-based chemotherapy.
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Affiliation(s)
- Jie Shen
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yuanqing Ye
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - David W Chang
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Maosheng Huang
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - John V Heymach
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jack A Roth
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Xifeng Wu
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Hua Zhao
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
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Serum lipid profile discriminates patients with early lung cancer from healthy controls. Lung Cancer 2017; 112:69-74. [DOI: 10.1016/j.lungcan.2017.07.036] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Revised: 07/11/2017] [Accepted: 07/31/2017] [Indexed: 01/09/2023]
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Armitage EG, Ciborowski M. Applications of Metabolomics in Cancer Studies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 965:209-234. [PMID: 28132182 DOI: 10.1007/978-3-319-47656-8_9] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.
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Affiliation(s)
- Emily Grace Armitage
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad CEU San Pablo, Campus Monteprincipe, Madrid, Spain. .,Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical Veterinary and Life Sciences, Sir Graeme Davies Building, University of Glasgow, Glasgow, UK. .,Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
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Leng S, Wu G, Klinge DM, Thomas CL, Casas E, Picchi MA, Stidley CA, Lee SJ, Aisner S, Siegfried JM, Ramalingam S, Khuri FR, Karp DD, Belinsky SA. Gene methylation biomarkers in sputum as a classifier for lung cancer risk. Oncotarget 2017; 8:63978-63985. [PMID: 28969046 PMCID: PMC5609978 DOI: 10.18632/oncotarget.19255] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 06/05/2017] [Indexed: 01/01/2023] Open
Abstract
CT screening for lung cancer reduces mortality, but will cost Medicare ∼2 billion dollars due in part to high false positive rates. Molecular biomarkers could augment current risk stratification used to select smokers for screening. Gene methylation in sputum reflects lung field cancerization that remains in lung cancer patients post-resection. This population was used in conjunction with cancer-free smokers to evaluate classification accuracy of a validated eight-gene methylation panel in sputum for cancer risk. Sputum from resected lung cancer patients (n=487) and smokers from Lovelace (n=1380) and PLuSS (n=718) cohorts was studied for methylation of an 8-gene panel. Area under a receiver operating characteristic curve was calculated to assess the prediction performance in logistic regressions with different sets of variables. The prevalence for methylation of all genes was significantly increased in the ECOG-ACRIN patients compared to cancer-free smokers as evident by elevated odds ratios that ranged from 1.6 to 8.9. The gene methylation panel showed lung cancer prediction accuracy of 82–86% and with addition of clinical variables improved to 87–90%. With sensitivity at 95%, specificity increased from 25% to 54% comparing clinical variables alone to their inclusion with methylation. The addition of methylation biomarkers to clinical variables would reduce false positive screens by ruling out one-third of smokers eligible for CT screening and could increase cancer detection rates through expanding risk assessment criteria.
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Affiliation(s)
- Shuguang Leng
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Guodong Wu
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Donna M Klinge
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Cynthia L Thomas
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Elia Casas
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Maria A Picchi
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
| | - Christine A Stidley
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Sandra J Lee
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Seena Aisner
- Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Jill M Siegfried
- Department of Pharmacology, University of Minnesota, Minneapolis, MN, USA
| | - Suresh Ramalingam
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, USA
| | - Fadlo R Khuri
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, USA
| | | | - Steven A Belinsky
- Lung Cancer Program, Lovelace Respiratory Research Institute, Albuquerque, NM, USA
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Fukumoto T, Nishiumi S, Fujiwara S, Yoshida M, Nishigori C. Novel serum metabolomics-based approach by gas chromatography/triple quadrupole mass spectrometry for detection of human skin cancers: Candidate biomarkers. J Dermatol 2017; 44:1268-1275. [PMID: 28593747 DOI: 10.1111/1346-8138.13921] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 04/21/2017] [Indexed: 12/24/2022]
Abstract
Skin cancer incidence rates are continuing to rise; however, if detected at an early stage, they can be cured with minimally invasive treatment. Therefore, the identification of novel and robust biomarkers for the early detection of skin cancer is required to improve the quality of life of the patient after treatment. In the present study, we aimed to identify novel biomarkers of skin cancers. We carried out serum metabolomics using gas chromatography/triple quadrupole mass spectrometry for two types of skin cancer: squamous cell carcinoma and melanoma. The changes in the expression of metabolites compared with healthy volunteers were analyzed by principal component analysis. Among all 118 metabolites, 27 in patients with squamous cell carcinoma and 33 in patients with melanoma showed significant changes in comparison with healthy volunteers. Principal component analysis showed that both skin cancer groups could be distinguished from the healthy volunteers group. We further investigated the specific metabolites most useful for these distinctions. In the squamous cell carcinoma group, these metabolites were glycerol, 4-hydroxybenzoic acid, sebacic acid, fucose and suberic acid. In the melanoma group, these metabolites were glutamic acid, sebacic acid, suberic acid, 4-hydroxybenzoic acid and phenylalanine. The present study identified several metabolites that were distinct for certain skin cancer types, which could potentially be used as diagnostic biomarkers leading to novel clinical management strategies.
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Affiliation(s)
- Takeshi Fukumoto
- Division of Dermatology, Department of Internal Related, Kobe, Japan
| | | | - Susumu Fujiwara
- Division of Dermatology, Department of Internal Related, Kobe, Japan
| | - Masaru Yoshida
- Division of Gastroenterology, Kobe, Japan.,Division of Metabolomics Research, Kobe University Graduate School of Medicine, Kobe, Japan.,AMED-CREST, AMED, Kobe, Japan
| | - Chikako Nishigori
- Division of Dermatology, Department of Internal Related, Kobe, Japan
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Carreras-Torres R, Johansson M, Haycock PC, Wade KH, Relton CL, Martin RM, Davey Smith G, Albanes D, Aldrich MC, Andrew A, Arnold SM, Bickeböller H, Bojesen SE, Brunnström H, Manjer J, Brüske I, Caporaso NE, Chen C, Christiani DC, Christian WJ, Doherty JA, Duell EJ, Field JK, Davies MPA, Marcus MW, Goodman GE, Grankvist K, Haugen A, Hong YC, Kiemeney LA, van der Heijden EHFM, Kraft P, Johansson MB, Lam S, Landi MT, Lazarus P, Le Marchand L, Liu G, Melander O, Park SL, Rennert G, Risch A, Haura EB, Scelo G, Zaridze D, Mukeriya A, Savić M, Lissowska J, Swiatkowska B, Janout V, Holcatova I, Mates D, Schabath MB, Shen H, Tardon A, Teare MD, Woll P, Tsao MS, Wu X, Yuan JM, Hung RJ, Amos CI, McKay J, Brennan P. Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study. PLoS One 2017; 12:e0177875. [PMID: 28594918 PMCID: PMC5464539 DOI: 10.1371/journal.pone.0177875] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 05/04/2017] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. METHODS AND FINDINGS We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. CONCLUSIONS Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.
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Affiliation(s)
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France
| | - Philip C. Haycock
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Kaitlin H. Wade
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Richard M. Martin
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- National Institute for Health Research Biomedical Research Unit in Nutrition, Diet and Lifestyle at University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, DCEG, National Cancer Institute, NIH, Rockville, Maryland, United States of America
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Angeline Andrew
- Norris Cotton Cancer Center, Lebanon, New Hampshire, United States of America
| | - Susanne M. Arnold
- University of Kentucky Markey Cancer Center, Lexington, Kentucky, United States of America
| | | | - Stig E. Bojesen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hans Brunnström
- Laboratory Medicine Region Skåne, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Jonas Manjer
- Laboratory Medicine Region Skåne, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | | | - Neil E. Caporaso
- Genetic Epidemiology Branch, DCEG, National Cancer Institute, NIH, Rockville, Maryland, United States of America
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - David C. Christiani
- Departments of Environmental Health and Epidemiology, Harvard T. H. Chan School of Public Health and Department of Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts, United States of America
| | - W. Jay Christian
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, Kentucky, United States of America
| | - Jennifer A. Doherty
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire, United States of America
| | - Eric J. Duell
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain
| | - John K. Field
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, The University of Liverpool, Liverpool, United Kingdom
| | - Michael P. A. Davies
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, The University of Liverpool, Liverpool, United Kingdom
| | - Michael W. Marcus
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, The University of Liverpool, Liverpool, United Kingdom
| | - Gary E. Goodman
- Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Aage Haugen
- National Institute of Occupational Health, Oslo, Norway
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | | | | | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | | | - Stephen Lam
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Maria Teresa Landi
- Genetic Epidemiology Branch, DCEG, National Cancer Institute, NIH, Rockville, Maryland, United States of America
| | - Philip Lazarus
- Washington State University College of Pharmacy, Spokane, Washington, United States of America
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Geoffrey Liu
- Ontario Cancer Institute, Princess Margaret Cancer Center, Toronto, Ontario, Canada
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Sungshim L. Park
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Gad Rennert
- Clalit National Cancer Control Center and Department of Community Medicine and Epidemiology, Carmel Medical Center and B. Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Angela Risch
- University of Salzburg and Cancer Cluster Salzburg, Salzburg, Austria
| | - Eric B. Haura
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America
| | - Ghislaine Scelo
- Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France
| | - David Zaridze
- Russian N.N. Blokhin Cancer Research Centre, Moscow, The Russian Federation
| | - Anush Mukeriya
- Russian N.N. Blokhin Cancer Research Centre, Moscow, The Russian Federation
| | - Milan Savić
- Department of Thoracic Surgery, Clinical Center of Serbia, Belgrade, Serbia
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, Maria Sklodowska-Curie Institute – Oncology Center, Warsaw, Poland
| | - Beata Swiatkowska
- Nofer Institute of Occupational Medicine, Department of Environmental Epidemiology, Lodz, Poland
| | - Vladimir Janout
- Department of Epidemiology and Public Health, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Ivana Holcatova
- Institute of Public Health and Preventive Medicine, Charles University, 2nd Faculty of Medicine, Prague, Czech Republic
| | - Dana Mates
- National Institute of Public Health, Bucharest, Romania
| | - Matthew B. Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Adonina Tardon
- Instituto Universitario de Oncología del Principado de Asturias (IUOPA), University of Oviedo and CIBERESP, Oviedo, Spain
| | - M Dawn Teare
- University of Sheffield, Sheffield, United Kingdom
| | - Penella Woll
- University of Sheffield, Sheffield, United Kingdom
| | | | - Xifeng Wu
- The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Jian-Min Yuan
- Division of Cancer Control and Population Science, University of Pittsburgh Cancer Institute; and Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America
| | - Rayjean J. Hung
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada
| | - Christopher I. Amos
- Department of Biomedical Data Science, Geisel School of medicine, Dartmouth College, Lebanon, New Hampshire, United States of America
| | - James McKay
- Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France
| | - Paul Brennan
- Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France
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Klupczynska A, Dereziński P, Garrett TJ, Rubio VY, Dyszkiewicz W, Kasprzyk M, Kokot ZJ. Study of early stage non-small-cell lung cancer using Orbitrap-based global serum metabolomics. J Cancer Res Clin Oncol 2017; 143:649-659. [PMID: 28168355 PMCID: PMC5352735 DOI: 10.1007/s00432-017-2347-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 01/18/2017] [Indexed: 01/06/2023]
Abstract
Purpose The aim of the project was to apply ultra-high-performance liquid chromatography–quadrupole-Orbitrap-high-resolution mass spectrometry for serum metabolite profiling of non-small-cell lung cancer (NSCLC). This Orbitrap-based methodology has been applied for a study of NSCLC potential markers for the first time. Methods After extraction using protein precipitation, sera were separated on the ACE Excel 2 C18-PFP (100 × 2.1 mm, 2.0 µm) column using gradient elution and analyzed within the range of 70–1000 m/z. Only patients with early stage disease (stages IA–IIB) were included in the study, providing opportunity to find biomarkers for early lung cancer detection. The resulting metabolite profiles were subjected to univariate and multivariate statistical tests. Results 36 features were found significantly changed between NSCLC group and controls after FDR adjustment and 19 were identified using various metabolite databases (in-house library, HMDB, mzCloud). The study revealed a number of NSCLC biomarker candidates which belong to such compound classes as acylcarnitines, organic acids, and amino acids. Multivariate ROC curve built using 12 identified metabolites was characterized by AUC = 0.836 (0.722–0.946). There were no significant differences in the serum metabolite profiles between two most common histological types of lung cancer—adenocarcinoma and squamous cell carcinoma. Conclusions Through identification of novel potential tumor markers, Orbitrap-based global metabolic profiling is a useful strategy in cancer research. Our study can accelerate development of new diagnostic and therapeutic strategies in NSCLC. The metabolites involved in discrimination between NSCLC patients and the control subjects should be further explored using a targeted approach. Electronic supplementary material The online version of this article (doi:10.1007/s00432-017-2347-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Agnieszka Klupczynska
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780, Poznan, Poland
| | - Paweł Dereziński
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780, Poznan, Poland
| | - Timothy J Garrett
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, 1395 Center Drive, Gainesville, FL, 32610, USA
| | - Vanessa Y Rubio
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, 1395 Center Drive, Gainesville, FL, 32610, USA
| | - Wojciech Dyszkiewicz
- Department of Thoracic Surgery, Poznan University of Medical Sciences, Szamarzewskiego 62 Street, 60-569, Poznan, Poland
| | - Mariusz Kasprzyk
- Department of Thoracic Surgery, Poznan University of Medical Sciences, Szamarzewskiego 62 Street, 60-569, Poznan, Poland
| | - Zenon J Kokot
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780, Poznan, Poland.
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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Overlap in serum metabolic profiles between non-related diseases: Implications for LC-MS metabolomics biomarker discovery. Biochem Biophys Res Commun 2016; 478:1472-7. [PMID: 27581198 DOI: 10.1016/j.bbrc.2016.08.155] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 08/27/2016] [Indexed: 11/21/2022]
Abstract
Untargeted metabolic profiling has generated large activity in the field of clinical biomarker discovery. Yet, no clinically approved metabolite biomarkers have emerged with failure in validation phases often being a reason. To investigate why, we have applied untargeted metabolic profiling in a retrospective cohort of serum samples representing non-related diseases. Age and gender matched samples from patients diagnosed with pneumonia, congestive heart failure, lymphoma and healthy controls were subject to comprehensive metabolic profiling using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The metabolic profile of each diagnosis was compared to the healthy control group and significant metabolites were filtered out using t-test with FDR correction. Metabolites found to be significant between each disease and healthy controls were compared and analyzed for overlap. Results show that despite differences in etiology and clinical disease presentation, the fraction of metabolites with an overlap between two or more diseases was 61%. A majority of these metabolites can be associated with immune responses thus representing non-disease specific events. We show that metabolic serum profiles from patients representing non-related diseases display very similar metabolic differences when compared to healthy controls. Many of the metabolites discovered as disease specific in this study have further been associated with other diseases in the literature. Based on our findings we suggest non-related disease controls in metabolomics biomarker discovery studies to increase the chances of a successful validation and future clinical applications.
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75
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Kotecha R, Takami A, Espinoza JL. Dietary phytochemicals and cancer chemoprevention: a review of the clinical evidence. Oncotarget 2016; 7:52517-52529. [PMID: 27232756 PMCID: PMC5239570 DOI: 10.18632/oncotarget.9593] [Citation(s) in RCA: 241] [Impact Index Per Article: 30.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2015] [Accepted: 05/12/2016] [Indexed: 12/13/2022] Open
Abstract
Cancer chemoprevention involves the use of different natural or biologic agents to inhibit or reverse tumor growth. Epidemiological and pre-clinical data suggest that various natural phytochemicals and dietary compounds possess chemopreventive properties, and in-vitro and animal studies support that these compounds may modulate signaling pathways involved in cell proliferation and apoptosis in transformed cells, enhance the host immune system and sensitize malignant cells to cytotoxic agents. Despite promising results from experimental studies, only a limited number of these compounds have been tested in clinical trials and have shown variable results. In this review, we summarize the data regarding select phytochemicals including curcumin, resveratrol, lycopene, folates and tea polyphenols with emphasis on the clinical evidence supporting the efficacy of these compounds in high-risk populations.
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Affiliation(s)
- Ritesh Kotecha
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America
| | - Akiyoshi Takami
- Department of Internal Medicine, Division of Hematology, Aichi Medical University, School of Medicine, Nagakute, Aichi, Japan
| | - J. Luis Espinoza
- Department of Hematology Oncology, Kanazawa University Graduate School of Medical Science, Kanazawa, Japan
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