Serum metabolome analysis by 1H-NMR reveals differences between chronic lymphocytic leukaemia molecular subgroups

MacIntyre, David A.; Jiménez, Beatriz; Jantus‐Lewintre, Eloísa; Martín, Cristina Reinoso; Schäfer, Hartmut; Ballesteros, Carlos García; J, Mayans; Spraul, Manfred; Garcı́a-Conde, J; Pineda‐Lucena, Antonio

doi:10.1038/leu.2009.295

Cited by 130 publications

(110 citation statements)

References 62 publications

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“…In regard to age, it was found to have a much smaller influence on the plasma composition than the disease, in line with the results reported by others for different cancer types, such as leukemia 47 or esophageal cancer. 25 However, possible bias arising from the disparate age distributions in controls (ages 22À60) and cancer subjects (ages 30À85) could not be ruled out, since the discrimination between these classes was found to be worse for a subgroup of subjects with more closely matched ages.…”

supporting

confidence: 79%

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

Rocha

Carrola²,

Barros³

et al. 2011

J. Proteome Res.

151

108

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Lung cancer is one of the most prevalent and fatal types of cancer, with average 5-year survival rates lower than 15%, 1,2 which is mainly due to the advanced stage at which lung tumors are usually diagnosed. Indeed, when lung cancer is detected before metastasizing to lymph nodes or distant sites, the 5-year survival rates increase drastically to 60À80%, thus stressing the importance of early diagnosis. However, the majority of patients show no signs or symptoms during the initial phases of neoplastic growth, hindering early detection and the possibility of curative surgical treatment. Moreover, radiological tests, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), which would allow the detection of initial cancer lesions, are not suitable for general screening of the population, mainly due to their high costs. Therefore, new methods that can aid in the early detection of lung cancer and contribute to improved prognosis are greatly needed.The search for metabolic markers of cancer in human tissues and biofluids has been the focus of a number of metabonomic studies in recent years. 3,4 In particular, metabolic profiling of blood plasma or serum has been increasingly used to unveil metabolic alterations associated with different cancer types, such as breast, 5À7 kidney, 8À10 liver, 11À13 prostate, 14À16 colorectal, 17À20 oral, 21,22 pancreatic, 23,24 esophageal, 25 and bone 26 cancers. In the case of lung cancer, only a few studies focusing on plasma or serum metabolic profiling have been recently reported. Maeda and co-workers proposed that the differences in the plasma amino acid profiles between healthy controls and non-small-cell lung cancer (NSCLC) patients, as assessed by targeted liquid chromatography coupled to mass spectrometry (LCÀMS), could potentially be useful for screening NSCLC. 27 In another MS study of specific compounds, namely, lysophosphatidylcholines (lysoPC), abnormal levels of lysoPC isomers with different fatty acyl positions were found in the plasma of lung cancer patients compared to controls. 28 Using a more global profiling approach, Jordan and colleagues reported the NMR analysis of paired tissue and serum samples from 14 subjects with two different lung cancer histological types (adenocarcinoma and squamous cell

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supporting

confidence: 79%

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

Rocha

Carrola²,

Barros³

et al. 2011

J. Proteome Res.

151

108

View full text Add to dashboard Cite

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“…Spectra were automatically phased and baseline corrected, chemical shift referenced internally to the methyl group signal of alanine at 1.47 ppm using TOPSPIN 3.0 (Bruker Biospin) and analyzed with Analysis of MIXtures (AMIX; Bruker) for metabolites assignment. Metabolites of interest were identified using Amix v 3.9.7 in combination with the Bruker NMR Metabolic Profiling Database BBIOREFCODE 2.0.0 database (Bruker Biospin), as well as other existing public databases and literature reports (7,15,16).…”

Section: Sample Preparation and 1 H-nmr Acquisitionmentioning

confidence: 99%

“…High-resolution 1 H-NMR spectroscopy provides quantitative analysis of metabolite concentrations and reproducible information with minimal sample handling. Particularly in the cancer setting, metabolomics has been applied to develop novel early diagnostic biomarkers in renal cancer (3,4), colorectal cancer (5), pancreatic cancer (6), leukemia (7), ovarian cancer (8,9) and oral cancer (10). More recently, this approach has also been used to provide predictive biomarkers associated with prognosis, response to treatment and toxicity (11,12).…”

Section: Introductionmentioning

confidence: 99%

Multiple Myeloma Patients Have a Specific Serum Metabolomic Profile That Changes after Achieving Complete Remission

Puchades‐Carrasco

Lecumberri

Martínez‐López

et al. 2013

Clinical Cancer Research

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Purpose: Multiple myeloma remains an incurable disease. New approaches to develop better tools for improving patient prognostication and monitoring treatment efficacy are very much needed. In this study, we aimed to evaluate the potential of metabolomics by 1 H-NMR to provide information on metabolic profiles that could be useful in the management of multiple myeloma. Experimental Design: Serum samples were collected from multiple myeloma patients at the time of diagnosis and after achieving complete remission. A matched control set of samples was also included in the study. The 1 H-NMR measurements used to obtain the metabolic profile for each patient were followed by the application of univariate and multivariate statistical analyses to determine significant differences.Results: Metabolic profiles of multiple myeloma patients at diagnosis exhibited higher levels of isoleucine, arginine, acetate, phenylalanine, and tyrosine, and decreased levels of 3-hydroxybutyrate, lysine, glutamine, and some lipids compared with the control set. A similar analysis conducted in multiple myeloma patients after achieving complete remission indicated that some of the metabolic changes (i.e., glutamine, cholesterol, lysine) observed at diagnosis displayed a variation in the opposite direction upon responding to treatment, thus contributing to multiple myeloma patients having a closer metabolic profile to those of healthy individuals after the disappearance of major disease manifestations.Conclusions: The results highlight the potential of metabolic profiles obtained by 1 H-NMR in identifying multiple myeloma biomarkers that may be useful to objectively discriminate individuals with and without multiple myeloma, and monitor response to treatment.

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“…Metabolomics is a post-genomic research field concerned with the study of metabolic profiles in biologic samples such as isolated cells (4), tissues (5) or body fluids (6)(7)(8)(9)(10). In recent years, metabolomic studies have provided a significant contribution to the detailed understanding of the biochemical network and pathways in oncology (11), highlighting the potential of metabolomic analyses of blood samples for the detection of cancers, including epithelial ovarian (12), leukemia (13), oral (14), breast (15,16), prostate (11), liver (17) as well as colorectal cancer (CRC; refs. [18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Metabolomic NMR Fingerprinting to Identify and Predict Survival of Patients with Metastatic Colorectal Cancer

et al. 2012

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Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ( 1 H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist that is strong enough to predict overall survival (OS). In 153 patients with mCRC and 139 healthy subjects from three Danish hospitals, we profiled two independent sets of serum samples in a prospective phase II study. In the training set, 1 H-NMR metabolomic profiling could discriminate patients with mCRC from healthy subjects with a cross-validated accuracy of 100%. In the validation set, 96.7% of subjects were correctly classified. Patients from the training set with maximally divergent OS were chosen to construct an OS predictor. After validation, patients predicted to have short OS had significantly reduced survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P ¼ 1.33 Â 10 À6 ).A number of metabolites concurred with the 1

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Serum metabolome analysis by 1H-NMR reveals differences between chronic lymphocytic leukaemia molecular subgroups

Cited by 130 publications

References 62 publications

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

Multiple Myeloma Patients Have a Specific Serum Metabolomic Profile That Changes after Achieving Complete Remission

Metabolomic NMR Fingerprinting to Identify and Predict Survival of Patients with Metastatic Colorectal Cancer

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