H-1-NMR-based metabolomics for cancer targeting and metabolic engineering -A review

Authors
Raja, GanesanJung, YoungmiJung, Sang HoonKim, Tae-Jin
Issue Date
2020-12
Publisher
ELSEVIER SCI LTD
Citation
PROCESS BIOCHEMISTRY, v.99, pp.112 - 122
Abstract
Nuclear magnetic resonance (NMR) spectroscopy acts as the best tool that can be used in tissue engineering scaffolds to investigate unknown metabolites. Moreover, metabolomics is a systems approach for examining in vivo and in vitro metabolic profiles, which promises to provide data on cancer metabolic alterations. However, metabolomic profiling allows for the activity of small molecules and metabolic alterations to be measured. Furthermore, metabolic profiling also provides high-spectral resolution, which can then be linked to potential metabolic relationships. An altered metabolism is a hallmark of cancer that can control many malignant properties to drive tumorigenesis. Metabolite targeting and metabolic engineering contribute to carcinogenesis by proliferation, and metabolic differentiation. The resulting the metabolic differences are examined with traditional chemometric methods such as principal component analysis (PCA), and partial least squares-discriminate analysis (PLS-DA). In this review, we examine NMR-based activity metabolomic platforms that can be used to analyze various fluxomics and for multivariant statistical analysis in cancer. We also aim to provide the reader with a basic understanding of NMR spectroscopy, cancer metabolomics, target profiling, chemometrics, and multifunctional tools for metabolomics discrimination, with a focus on metabolic phenotypic diversity for cancer therapeutics.
Keywords
PLANT-CELL CULTURES; PATTERN-RECOGNITION; SPECTROSCOPIC DATA; DATA NORMALIZATION; TECHNIQUES LESSONS; BLADDER-CANCER; NMR-SPECTRA; IDENTIFICATION; C-13; H-1; PLANT-CELL CULTURES; PATTERN-RECOGNITION; SPECTROSCOPIC DATA; DATA NORMALIZATION; TECHNIQUES LESSONS; BLADDER-CANCER; NMR-SPECTRA; IDENTIFICATION; C-13; H-1; Cancer; Metabolomics; Metabolic engineering; Target profiling; Software; Therapeutics
ISSN
1359-5113
URI
https://pubs.kist.re.kr/handle/201004/117769
DOI
10.1016/j.procbio.2020.08.023
Appears in Collections:
KIST Article > 2020
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