Glycine metabolomic changes induced by anticancer agents in A549 cells

Real-time monitoring of glucose metabolism and effects of metformin on HepG2 cells using 13C in-cell NMR spectroscopy

Metformin is currently a strong candidate antitumor agent for multiple cancers, and has the potential to inhibit cancer cell viability, growth, and proliferation. Metabolic reprogramming is a critical feature of cancer cells. However, the effects of metformin which targets glucose metabolism on HepG2 cancer cells remain unclear. In this study, to explore the effects of metformin on glucose metabolism in HepG2 cells, we conducted real-time metabolomic monitoring of live HepG2 cells treated with metformin using 13C in-cell NMR spectroscopy. Metabolic tracing with U-13C6-glucose revealed that metformin significantly increased the production of 13C-G3P and 13C-glycerol, which were reported to attenuate liver cancer development, but decreased the production of potential oncogenesis-supportive metabolites, including 13C-lactate, 13C-alanine, 13C-glycine, and 13C-glutamate. Moreover, the expression levels of enzymes associated with the measured metabolites were carried out. The results showed that the levels of ALT1, MCT4, GPD2 and MPC1 were greatly reduced, which were consistent with the changes of measured metabolites in 13C in-cell NMR spectroscopy. Overall, our approach directly provides fundamental insights into the effects of metformin on glucose metabolism in live HepG2 cells, and highlights the potential mechanism of metformin, including the increase in production of G3P and glycerol derived from glucose, as well as the inhibition of glucose incorporation into lactate, alanine, glutamate, and glycine.

Single-Cell Metabolomics-Based Strategy for Studying the Mechanisms of Drug Action

Studying the mechanisms of drug antitumor activity at the single-cell level can provide information about the responses of cell subpopulations to drug therapy, which is essential for the accurate treatment of cancer. Due to the small size of single cells and the low contents of metabolites, metabolomics-based approaches to studying the mechanisms of drug action at the single-cell level are lacking. Herein, we develop a label-free platform for studying the mechanisms of drug action based on single-cell metabolomics (sMDA-scM) by integrating intact living-cell electro-launching ionization mass spectrometry (ILCEI-MS) with metabolomics analysis. Using this platform, we reveal that non-small-cell lung cancer (NSCLC) cells treated by gefitinib can be clustered into two cell subpopulations with different metabolic responses. The glutathione metabolic pathway of the subpopulation containing 14.4% of the cells is not significantly affected by gefitinib, exhibiting certain resistance characteristics. The presence of these cells masked the judgment of whether cysteine and methionine metabolic pathway was remarkably influenced in the analysis of overall average results, revealing the heterogeneity of the response of single NSCLC cells to gefitinib treatment. The findings provide a basis for evaluating the early therapeutic effects of clinical medicines and insights for overcoming drug resistance in NSCLC subpopulations.

The Differential Metabolic Response of Oral Squamous Cell Carcinoma Cells and Normal Oral Epithelial Cells to Cisplatin Exposure

Metabolic reprogramming is one of the hallmarks of a tumor. It not only promotes the development and progression of tumor but also contributes to the resistance of tumor cells to chemotherapeutics. The difference in the metabolism between drug-resistant and sensitive tumor cells indicates that drug-resistant tumor cells have experienced metabolic adaptation. The metabolic response induced by chemotherapy is dynamic, but the early metabolic response of tumor cells to anticancer drugs and the effect of an initial response on the development of drug resistance have not been well studied. Early metabolic intervention may prevent or slow down the development of drug resistance. The differential metabolic responses of normal cells and tumor cells to drugs are unclear. The specific metabolites or metabolic pathways of tumor cells to chemotherapeutic drugs can be used as the target of metabolic intervention in tumor therapy. In this study, we used comparative metabolomics to analyze the differential metabolic responses of oral cancer cells and normal oral epithelial cells to short-term cisplatin exposure, and to identify the marker metabolites of early response in oral cancer cells. Oral cancer cells showed a dynamic metabolic response to cisplatin. Seven and five metabolites were identified as specific response markers to cisplatin exposure in oral cancer cell SCC-9 and normal oral epithelial cell HOEC, respectively. Glyoxylate and dicarboxylate metabolism and fructose, malate, serine, alanine, sorbose and glutamate were considered as specific enriched metabolic pathways and biomarkers of SCC-9 cells in response to cisplatin, respectively. The existence of differential metabolic responses lays a foundation for tumor chemotherapy combined with metabolic intervention.

A Serum Metabolomic Study Reveals Changes in Metabolites During the Treatment of Lung Cancer-Bearing Mice with Anlotinib

Background

Anlotinib is a vascular endothelial growth factor receptor tyrosine kinase inhibitor recommended for the treatment of advanced lung cancer patients after at least two previous systemic chemotherapies. Currently, many patients with lung cancer do not respond well to anlotinib treatment. Therefore, the aim of this metabolomic study was to determine the internal mechanism of anlotinib action at the molecular level and to identify the potential biomarkers and pathways associated with the therapeutic effects of anlotinib.

Methods

A total of 20 male nude mice were randomly divided into 2 groups and treated with anlotinib or physiological saline. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was performed to analyze the serum samples and determine the differential metabolites and pathways between anlotinib and control groups.

Results

We observed significant differences between the anlotinib and control groups, and 13 endogenous differential metabolites and 5 potential metabolic pathways were identified. Glyoxylate and dicarboxylate metabolism, tryptophan metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism and valine, leucine and isoleucine biosynthesis were the most important pathways regulated by anlotinib in vivo. Notably, these 5 differential pathways were highly associated with the TCA cycle, which is important in the proliferation and apoptosis of cancer cells.

Conclusion

This serum metabolomic study revealed distinct metabolic profiles in lung cancer-bearing mice treated with anlotinib and identified differential metabolites and pathways between the anlotinib and control groups, which may provide new ideas for the clinical application of anlotinib.

Dietary Melatonin and Glycine Decrease Tumor Growth through Antiangiogenic Activity in Experimental Colorectal Liver Metastasis

Despite multimodal treatment strategies, clinical outcomes of advanced stage colorectal cancer (CRC) patients remain poor. Neoadjuvant/adjuvant chemotherapy efficacy is limited due to chemoresistance, toxicity, and negative side effects. Since both melatonin and glycine have anti-cancer activities without relevant side effects, this study was designed to investigate their combined effects in experimental CRC liver metastases. CRC metastasis with CC531 cells were induced in male Wistar rats. Melatonin and glycine alone or their combination were supplemented for 14 days (n = 100). Blood parameters, a micro-computed tomography scan (tumor volume over time), and immunohistochemistry for Ki67 and CD31 expression in tumor tissue were compared between groups. Melatonin and glycine alone significantly reduced the tumor volume by 63.2% (p = 0.002) and 43% (p = 0.044) over time, respectively, while tumor volume increased by 8.7% in the controls. Moreover, treatment with melatonin and glycine alone reduced the tumor proliferation index. Most interestingly, the combination therapy did not have any influence on the above-mentioned tumor parameters. The leukocyte count was significantly increased with melatonin at the end of the experiment (p = 0.012) which was due to a high lymphocytes count. Tumor microvascular density was significantly reduced in all treatment groups. The results of this study suggest an inhibitory function for melatonin and glycine alone in the case of CRC liver metastasis growth by acting as natural antiangiogenic molecules, followed by angiogenesis-dependent cancer proliferation and immunomodulation.

Liquid chromatography-mass spectrometry based metabolic characterization of pleural effusion in patients with acquired EGFR-TKI resistance

Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) acquired resistance remains a major barrier in the clinical treatment of lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutations. Despite extensive efforts, mechanism of acquired resistance has not yet been elucidated clearly. The subject of this study was to characterize the metabolic signatures relevant to acquired EGFR-TKI resistance in pleural effusion (PE), and identify potential biomarkers in PE of patients with acquired EGFR-TKI resistance. PE from EGFR-TKI untreated group (n = 30) and EGFR-TKI resistant group (n = 18) was analyzed using liquid chromatography-mass spectrometry (LCMS) based metabolomic. Multivariate statistical analysis revealed distinctive diff ;erences between the groups. A total of 34 significantly differential metabolites in PE were identified, among which, the acquired EGFR-TKI resistant group had higher levels of l-lysine, taurine, ornithine and citrulline, and lower levels of l-tryptophan, kynurenine, l-phenylalanine, l-leucine, N-formyl-l-methionine, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine in PE than that of the EGFR-TKI untreated group. These metabolites are mainly involved in six amino acid metabolic pathways. In addition, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine showed the highest AUC values of 0.934 and 0.929 in receiver operating characteristic analysis. Through LCMS metabolomics, our study identified potential biomarkers in PE, differentiating EGFR-TKI resistant patients from untreated patients, as well as the mechanisms underlying acquired EGFR-TKI resistance; thus, providing novel insights into acquired EGFR-TKI resistance.