Metabolomics for Biomarker Discovery in  Gastroenterological Cancer

Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

doi:10.3390/metabo4030547

Cited by 24 publications

(14 citation statements)

References 95 publications

(74 reference statements)

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“…Stable isotope labeling and metabolic flux analysis would reveal flow through metabolic pathways that cannot be gained through snapshot metabolomics or metabolic gene expression studies . However, stable isotope labeling in vivo is challenging, and analysis of cultured cells may yield results that are less physiologically relevant .…”

Section: Resultsmentioning

confidence: 99%

Metabolism in cancer metastasis: bioenergetics, biosynthesis, and beyond

Teoh

Lunt

2017

WIREs Mechanisms of Disease

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Metabolic changes accompany tumor progression and metastatic dissemination of cancer cells. Yet, until recently, metabolism has received little attention in the study of cancer metastasis. Cancer cells undergo significant metabolic rewiring as they acquire metastatic traits and adapt to survive in multiple environments with varying nutrient availability, oxygen concentrations, and extracellular signals. Therefore, to effectively treat metastatic cancer, it is important to understand the metabolic strategies adopted by cancer cells during the metastatic process. Here, we focus on the metabolic pathways known to play a role in cancer metastasis, including glycolysis, the pentose phosphate pathway, tricarboxylic acid cycle, oxidative phosphorylation, amino acid metabolism, and fatty acid metabolism. Recent studies have uncovered roles for these pathways in cellular events that promote metastasis, including reactive oxygen species-mediated signaling, epigenetic regulation, and interaction with the extracellular matrix. We also discuss the metabolic interplay between immune cells and cancer cells supporting metastasis. Finally, we highlight the current limitations of our knowledge on this topic, and present future directions for the field. WIREs Syst Biol Med 2018, 10:e1406. doi: 10.1002/wsbm.1406 This article is categorized under: Biological Mechanisms > Metabolism.

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Section: Resultsmentioning

confidence: 99%

Metabolism in cancer metastasis: bioenergetics, biosynthesis, and beyond

Teoh

Lunt

2017

WIREs Mechanisms of Disease

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“…NAD + , but also metabolites related to NAD + metabolism (i.e. NADP + ), are small molecules, which have been detected and quantified in different biofluids using targeted and untargeted NMR spectroscopy and MS-based methods 150 164 165 166 .…”

Section: Metabolomics Studies Of Autophagy Regulationmentioning

confidence: 99%

Integrative metabolomics as emerging tool to study autophagy regulation

Stryeck¹,

Birner‐Gruenberger²

2017

Microb Cell

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Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be obtained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key metabolites, recent studies, and future opportunities for metabolomics in studying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics approaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote understanding of autophagy and autophagy-related diseases in living cells and organisms.

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“…Therefore, the metabolome could be considered to be a summary of the other upstream omics profiles, and metabolome analysis might be able to detect subtle changes in metabolic pathways and deviations from homeostasis before phenotypic changes occur [5, 6]. Thus, metabolomics could contribute greatly to biomarker research [7, 8]. Our previous study [4], in which a colorectal cancer prediction model was established, included colorectal cancer patients with stage 0 to IV disease, and the colorectal cancer prediction model demonstrated sensitivity and specificity values of about 80%.…”

Section: Introductionmentioning

confidence: 99%

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

et al. 2017

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In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

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Metabolomics for Biomarker Discovery in Gastroenterological Cancer

Cited by 24 publications

References 95 publications

Metabolism in cancer metastasis: bioenergetics, biosynthesis, and beyond

Metabolism in cancer metastasis: bioenergetics, biosynthesis, and beyond

Integrative metabolomics as emerging tool to study autophagy regulation

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

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