Abstract
Thanks to recent advances in analytical technologies and statistical capabilities, the application field of metabolomics has increased significantly. Currently, this approach is used to investigate biological substrates looking for metabolic profile alterations, diseases markers, and drug effects. In particular, NMR spectroscopy has shown great potential as a detection technique, mainly for the ability to detect multiple (10s to 100s) metabolites at once without separation. Only in recent years has the NMR-based metabolomic approach been extended to investigate the cell metabolic alterations induced by metal-based antitumor drug administration. As expected, these studies are mainly focused on platinum complexes, but some palladium and ruthenium compounds are also under investigation. The use of a metabolomics approach was very effective in assessing tumor response to drugs and providing insights into the mechanism of action and resistance. Therefore, metabolomics may open new perspectives into the development of metal-based drugs. In particular, it has been shown that NMR-based, in vitro metabolomics is a powerful tool for detecting variations of the cell metabolites induced by the metal drug exposure, thus offering also the possibility of identifying specific markers for in vivo monitoring of tumor responsiveness to anticancer treatments.
Highlights
In international scientific researches, the term “Omic” started to be used in the 1990s, when theHuman Genome Project, whose aim was to determine the DNA nucleobases’ sequences, was launched, in order to identify and map genes of the human genome [1]
This study demonstrated that the presence of glucose, amino acids, and Kreb’s cycle metabolites in the urine after cisplatin administration indicates the development of renal failure
1H-NMR-based metabolomic study to evaluate the response of a cisplatin-resistant group reported an acac)(DMS)], or Ptac2S (Figure 4c)
Summary
The term “Omic” started to be used in the 1990s, when the. There is the advantage of measuring multiple (10 to 100) metabolites at once, with no need of their physical separation and a very limited sample working up This technique is non-destructive, and can be quantitative (different from MS) but capable at the same time, to allow metabolic profiles or “fingerprint” collection of the examined biological samples. Such improvements are essentially related to more reliable spectrometers, especially highly-sensitive NMR probes, with versatile acquisition sequences that can allow faster performance and substantial NMR experiments Both the development of powerful databases of metabolic data and efficient multivariate statistical methods have simplified the high complexity (number of spectra, number of groups, number of condition) of big data set handling. All these aspects have made NMR-based metabolic profiling an unbiased tool that can provide fully quantitative data for most of the components in a complex mixture [7]
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