Cancer Metabolomics 2023

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 7959

Special Issue Editor


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Guest Editor
Institute for Advanced Biosciences, University Grenoble Alpes/CNRS/INSERM, Grenoble, France
Interests: cancer metabolomics; molecular epidemiology; metabolism and epigenetics; advanced NMR methods; chemometrics
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Special Issue Information

Dear Colleagues,

We welcome the submission of original research articles or review papers as contributions to this Special Issue of Metabolites dedicated to cancer metabolomics. The aim for this issue is to highlight innovative metabolomic approaches, as well as novel achievements of metabolomic investigations in oncology that either provide mechanistic insights into model systems or pertain to translational and clinical studies. Many aspects of metabolomics research, notably in the field of cancerology, contribute to defining disease trajectories that sustain the promotion of P4 medicine—predictive, preventive, personalized, and participatory—to transform healthcare. We therefore encourage contributions that include cross-disciplinary research, involve large-scale data collection and analysis, or involve multi-omics studies for integrative medicine. Noting that over 50% of all cancers develop in a background of pre-existing infectious, immuno-inflammatory, or metabolic chronic disease, original work that aims to understand the underlying metabolic mechanisms linking chronic diseases with cancer will be a highly relevant contribution to this Special Issue. Investigations of metabolic markers of risk, early markers of disease, and prognostic markers of the evolution of responses to cancer treatment are equally welcome.

We hope with this Special Issue to provide our readers with a timely overview of metabolomics contemporary research and perspectives in the broad area of cancerology.

Dr. Bénédicte Elena-Herrmann
Guest Editor

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Keywords

  • diagnosis or predictive metabolic markers
  • tumor metabolism
  • chronic diseases and cancer
  • molecular epidemiology of cancer
  • in vivo spectroscopy
  • model systems

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Published Papers (3 papers)

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13 pages, 4343 KiB  
Article
Exploration of Blood Metabolite Signatures of Colorectal Cancer and Polyposis through Integrated Statistical and Network Analysis
by Francesca Di Cesare, Alessia Vignoli, Claudio Luchinat, Leonardo Tenori and Edoardo Saccenti
Metabolites 2023, 13(2), 296; https://doi.org/10.3390/metabo13020296 - 17 Feb 2023
Viewed by 2406
Abstract
Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic purposes. Integrative systems biology approaches offer an optimal point of [...] Read more.
Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic purposes. Integrative systems biology approaches offer an optimal point of view to analyze CRC and patients with polyposis. The present study analyzed the association networks constructed from a publicly available array of 113 serum metabolites measured on a cohort of 234 subjects from three groups (66 CRC patients, 76 patients with polyposis, and 92 healthy controls), which concentrations were obtained via targeted liquid chromatography-tandem mass spectrometry. In terms of architecture, topology, and connectivity, the metabolite-metabolite association network of CRC patients appears to be completely different with respect to patients with polyposis and healthy controls. The most relevant nodes in the CRC network are those related to energy metabolism. Interestingly, phenylalanine, tyrosine, and tryptophan metabolism are found to be involved in both CRC and polyposis. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate molecular aspects of CRC. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2023)
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11 pages, 1686 KiB  
Article
Gamma-ray Irradiation of Rodent Diets Alters the Urinary Metabolome in Rats with Chemically Induced Mammary Cancer
by Jeevan K. Prasain, Landon S. Wilson, Clinton Grubbs and Stephen Barnes
Metabolites 2022, 12(10), 976; https://doi.org/10.3390/metabo12100976 - 16 Oct 2022
Cited by 1 | Viewed by 2021
Abstract
In this study, a comparative, untargeted metabolomics approach was applied to compare urinary metabolite profiles of rats fed irradiated and non-irradiated diets. γ-Irradiated and non-irradiated NIH 7001 diet was given orally to animals beginning 5 days after exposure to the carcinogen N-methyl-N-nitrosourea and [...] Read more.
In this study, a comparative, untargeted metabolomics approach was applied to compare urinary metabolite profiles of rats fed irradiated and non-irradiated diets. γ-Irradiated and non-irradiated NIH 7001 diet was given orally to animals beginning 5 days after exposure to the carcinogen N-methyl-N-nitrosourea and continued for 120 days. There was a 36% reduction in mammary tumor incidence in rats consuming the γ-irradiated diet, compared to rats receiving the non-irradiated form of the same diet. Urine samples from rats fed with γ-irradiated and non-irradiated diets were analyzed using nanoLC-MS/MS on a Q-TOF mass spectrometer, collecting positive and negative ion data. Data processing involved feature detection and alignment with MS-DIAL, normalization, mean-centering and Pareto scaling, and univariate and multivariate statistical analysis using MetaboAnalyst, and pathway analysis with Mummichog. Unsupervised Principal Component Analysis and supervised Partial Least Squares-Discriminant Analysis of both negative and positive ions revealed separation of the two groups. The top 25 metabolites from variable importance in projection scores >1 showed their contributions in discriminating urines the γ-irradiated diet fed group from non-irradiated control diet group. Consumption of the γ-irradiated diet led to alteration of several gut microbial metabolites such as phenylacetylglycine, indoxyl sulfate, kynurenic acid, hippurate and betaine in the urine. This study provides insights into metabolic changes in rat urine in response to a γ-irradiated diet which may be associated with mammary cancer prevention. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2023)
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28 pages, 1279 KiB  
Systematic Review
Evaluating Metabolite-Based Biomarkers for Early Diagnosis of Pancreatic Cancer: A Systematic Review
by Gloria Perazzoli, Olga M. García-Valdeavero, Mercedes Peña, Jose Prados, Consolación Melguizo and Cristina Jiménez-Luna
Metabolites 2023, 13(7), 872; https://doi.org/10.3390/metabo13070872 - 22 Jul 2023
Cited by 7 | Viewed by 2529
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical resection, but due to the delay in diagnosis, less than 20% of patients are eligible for surgery. Therefore, discovering diagnostic [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical resection, but due to the delay in diagnosis, less than 20% of patients are eligible for surgery. Therefore, discovering diagnostic biomarkers for early detection is crucial for improving clinical outcomes. Metabolomics has become a powerful technology for biomarker discovery, and several metabolomic-based panels have been proposed for PDAC diagnosis, but these advances have not yet been translated into the clinic. Therefore, this review focused on summarizing metabolites identified for the early diagnosis of PDAC in the last five years. Bibliographic searches were performed in the PubMed, Scopus and WOS databases, using the terms “Biomarkers, Tumor”, “Pancreatic Neoplasms”, “Early Diagnosis”, “Metabolomics” and “Lipidome” (January 2018–March 2023), and resulted in the selection of fourteen original studies that compared PDAC patients with subjects with other pancreatic diseases. These investigations showed amino acid and lipid metabolic pathways as the most commonly altered, reflecting their potential for biomarker research. Furthermore, other relevant metabolites such as glucose and lactate were detected in the pancreas tissue and body fluids from PDAC patients. Our results suggest that the use of metabolomics remains a robust approach to improve the early diagnosis of PDAC. However, these studies showed heterogeneity with respect to the metabolomics techniques used and further studies will be needed to validate the clinical utility of these biomarkers. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2023)
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