Untargeted Metabolomics and Polyamine Profiling in Serum before and after Surgery in Colorectal Cancer Patients

Circulating Metabolic Markers Identify Patients at Risk for Tumor Recurrence: A Prospective Cohort Study in Colorectal Cancer Surgery

OBJECTIVE

To investigate the spermidine pathway capability to predict patients at risk for tumor recurrence following colorectal cancer (CRC) surgery.

BACKGROUND

Recurrence rates after CRC surgery remain at about 20% despite an optimal technique and adjuvant therapy when necessary. Identification of risk biomarkers of recurrence is an unmet need. The spermidine pathway is indispensable for cell proliferation and differentiation, and is suggested to accelerate tumor spread.

METHODS

This was a prospective cohort study of patients undergoing CRC surgery from 2015 to 2018. Plasma samples were collected before surgery and on postoperative day 4, and the spermidine pathway was assessed through mass spectrometry. Oncological outcomes were registered.

RESULTS

A total of 146 patients were included and 24 (16.4%) developed tumor recurrence. Higher levels of preoperative spermidine pathway components (spermidine, spermine, spermidine synthase enzyme, and spermine/arginine balance) were positively associated with recurrence. Surgery promoted a decrease in these pathway elements. The greater the decline was, the lower the risk of recurrence. Preoperative spermidine over the cut-off of 0.198 µM displayed a 4.69-fold higher risk of recurrence. The spermine synthase enzyme behaved in the opposite direction.

CONCLUSIONS

The spermidine pathway is associated with tumor recurrence following CRC surgery and, after confirmation in larger cohorts, could be translated as a risk biomarker of recurrence into clinical practice.

Alterations in Plasma Lipid Profile before and after Surgical Removal of Soft Tissue Sarcoma

Soft tissue sarcoma (STS) is a relatively rare malignancy, accounting for about 1% of all adult cancers. It is known to have more than 70 subtypes. Its rarity, coupled with its various subtypes, makes early diagnosis challenging. The current standard treatment for STS is surgical removal. To identify the prognosis and pathophysiology of STS, we conducted untargeted metabolic profiling on pre-operative and post-operative plasma samples from 24 STS patients who underwent surgical tumor removal. Profiling was conducted using ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry. Thirty-nine putative metabolites, including phospholipids and acyl-carnitines were identified, indicating changes in lipid metabolism. Phospholipids exhibited an increase in the post-operative samples, while acyl-carnitines showed a decrease. Notably, the levels of pre-operative lysophosphatidylcholine (LPC) O-18:0 and LPC O-16:2 were significantly lower in patients who experienced recurrence after surgery compared to those who did not. Metabolic profiling may identify aggressive tumors that are susceptible to lipid synthase inhibitors. We believe that these findings could contribute to the elucidation of the pathophysiology of STS and the development of further metabolic studies in this rare malignancy.

Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients

Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O-phosphocholine, O-phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.

Circulating metabolites as potential biomarkers for the early detection and prognosis surveillance of gastrointestinal cancers

BACKGROUND AND AIMS

Two of the most lethal gastrointestinal (GI) cancers, gastric cancer (GC) and colon cancer (CC), are ranked in the top five cancers that cause deaths worldwide. Most GI cancer deaths can be reduced by earlier detection and more appropriate medical treatment. Unlike the current "gold standard" techniques, non-invasive and highly sensitive screening tests are required for GI cancer diagnosis. Here, we explored the potential of metabolomics for GI cancer detection and the classification of tissue-of-origin, and even the prognosis management.

METHODS

Plasma samples from 37 gastric cancer (GC), 17 colon cancer (CC), and 27 non-cancer (NC) patients were prepared for metabolomics and lipidomics analysis by three MS-based platforms. Univariate, multivariate, and clustering analyses were used for selecting significant metabolic features. ROC curve analysis was based on a series of different binary classifications as well as the true-positive rate (sensitivity) and the false-positive rate (1-specificity).

RESULTS

GI cancers exhibited obvious metabolic perturbation compared with benign diseases. The differentiated metabolites of gastric cancer (GC) and colon cancer (CC) were targeted to same pathways but with different degrees of cellular metabolism reprogramming. The cancer-specific metabolites distinguished the malignant and benign, and classified the cancer types. We also applied this test to before- and after-surgery samples, wherein surgical resection significantly altered the blood-metabolic patterns. There were 15 metabolites significantly altered in GC and CC patients who underwent surgical treatment, and partly returned to normal conditions.

CONCLUSION

Blood-based metabolomics analysis is an efficient strategy for GI cancer screening, especially for malignant and benign diagnoses. The cancer-specific metabolic patterns process the potential for classifying tissue-of-origin in multi-cancer screening. Besides, the circulating metabolites for prognosis management of GI cancer is a promising area of research.

Serum metabolomics analysis in patients with alcohol dependence

Objective

Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.

Methods

Liquid chromatography-mass spectrometry (LC-MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.

Results

The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.

Conclusion

The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.

Comprehensive serum metabolomics and network analysis to reveal the mechanism of gypenosides in treating lung cancer and enhancing the pharmacological effects of cisplatin

Gypenosides (GYP) exerted anticancer activity against various cancers. However, the mechanism of GYP against lung cancer (LC) in vivo remains unclear. This study aims to reveal the potential mechanism of GYP against LC and enhancing cisplatin efficacy using a comprehensive analysis of metabolomics, network analysis. Pharmacodynamic results showed that GYP inhibited tumor growth, reduced tumor volume and tumor weight, and alleviated pathological symptoms in Lewis tumor-bearing mice, and GYP could enhance the anti-LC effects of cisplatin. Using serum metabolomics methods, 53 metabolites were found to be significantly altered in the model group, and the levels of 23 biomarkers were significantly restored after GYP treatment. GYP-related metabolic pathways involved six pathways, including alpha-linolenic acid metabolism, glutathione metabolism, sphingolipid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and primary bile acid biosynthesis. 57 genes associated with differential metabolites of GYP recovery and 7 genes of 11 saponins of GYP against LC were screened by network analysis, the STRING database was used to find the association between 57 genes and 7 genes, and a compound-intersection gene-metabolite related gene-metabolite-pathway network was constructed, and STAT3, MAPK14, EGFR and TYMS might be the crucial targets of GYP against LC. Western blot results showed that GYP restored the levels of STA3, MAPK14, EGFR, and TYMS in the model group, and GYP also restored the levels of STAT3 and MAPK14 in the cisplatin group, indicating that GYP might exert anti-LC effects and enhance the pharmacological effects of cisplatin through MAPK14/STAT3 signaling pathway. Our method revealed the effect and mechanism of GYP on LC and the pharmacological effects of GYP-enhanced chemotherapeutic agent cisplatin, which provided some reference for the development of anti-cancer drugs.

Uncovering the mechanisms of dandelion against triple-negative breast cancer using a combined network pharmacology, molecular pharmacology and metabolomics approach

BACKGROUND

Taraxacum mongolicum, also called dandelion, has been used for thousands of years as a remedy for mammary abscess, mammary gland hyperplasia, and various other diseases afflicting the breast. In modern pharmacological research, dandelion has been proven to be effective against triple-negative breast cancer (TNBC). However, the mechanisms of this anti-tumor effect have not been fully elucidated.

PURPOSE

The aim of this investigation was to understand the multi-target mechanisms through which dandelion counteracts TNBC via a network pharmacology strategy as well as to validate its effectiveness by means of molecular pharmacology and metabolomics assessments.

METHODS

A liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (LC-Q-TOF/MS) was employed to identify the absorbed components of dandelion in rat plasma. The network pharmacology-based prediction was utilized to uncover the potential mechanisms through which dandelion counteracts TNBC, during which potential targets were identified and pathway enrichment analysis was performed. Subsequently, TNBC cells and 4T1 tumor-bearing mice were used to further verify the molecular mechanisms of dandelion.

RESULTS

Twelve active compounds were identified in rat plasma, which were connected with 50 TNBC-related targets. The pathway enrichment showed that dandelion could treat TNBC through regulating a series of biological processes involving cell cycle and metabolism. Experimentally, flow cytometry analysis revealed that dandelion could arrest the G0/G1 and G2/M cell cycles in 4T1 cells. Further western blot analysis evidenced that the protein expression of kinase 6 (CDK6) as well as cyclins B1 and B2 in mice tumor tissue were suppressed by dandelion. In addition, cell metabolomics analysis revealed the changes in the endogenous metabolite levels that result from dandelion treatments, such as the downregulation of arginine and spermine levels. All these findings were consistent with the predicted targets and pathways.

CONCLUSION

This study comprehensively demonstrates the multi-target mechanisms of dandelion against TNBC using network pharmacology, molecular pharmacology, and metabolomics approaches. These findings will provide important stepping stones for further mechanism investigations and may lead to the development of highly effective dandelion-based treatments for TNBC.

Overexpression of EiKCS confers paraquat-resistance in rice (Oryza sativa L.) by promoting the polyamine pathway

BACKGROUND

Paraquat is used widely as one of the bipyridine herbicides, which generates reactive oxygen species to cause cell death. With a growing number of paraquat-resistant weeds, the mechanism of paraquat-resistance in plants remains unclear. This research verified the functions of a previously confirmed putative paraquat-resistant gene, EiKCS, from paraquat-resistant goosegrass by genetic engineering in a single overexpressing line in rice.

RESULTS

Overexpression of EiKCS improved paraquat resistance in transgenic rice (KCSox). Pre-applied (12 h) exogenous spermidine (1.5 mmol L^-1 ), alleviated the injury of paraquat in rice. Paraquat induced injury in KCSox was 19.57%, which was lower than 32.22% injury it induced in wild-type (WT) rice. The paraquat-resistant mechanism was through the increased activity of antioxidant enzymes and the overproduction of endogenous polyamines. The spermine content in KCSox was more than 30 μg mL^-1 , while that in WT rice was less than 5 μg mL^-1 . Quantitative proteomics showed that β-ketoacyl-coenzyme A (CoA) synthase (51.81 folds) encoded by the transgenic EiKCS gene promoted the synthesis of the proteins involved with the polyamine pathway. The synthesized putrescine was promoted by the arginine decarboxylase (ADC) pathway. The spermidine synthase I (1.10-fold) and three eceriferum cofactors (CERs) were responsive to the paraquat stress. We validated putrescine (C₁₈ H₂₀ N₂ O₂ ) spermidine (C₂₈ H₃₁ N₃ O₃ ), and spermine (C₃₈ H₄₂ N₄ O₄ ) in this study.

CONCLUSION

EiKCS encoding β-ketoacyl-CoA synthase from goosegrass has been shown as an ideal candidate gene for engineering genetically modified organism (GMO) crops, as its overexpression does not only bring paraquat-resistance, but also have potential benefits without decreasing yield and rice grain quality. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

Alcohol dependence (AD) is a condition of alcohol use disorder in which the drinkers frequently develop emotional symptoms associated with a continuous alcohol intake. AD characterized by metabolic disturbances can be quantitatively analyzed by metabolomics to identify the alterations in metabolic pathways. This study aimed to: i) compare the plasma metabolic profiling between healthy and AD-diagnosed individuals to reveal the altered metabolic profiles in AD, and ii) identify potential biological correlates of alcohol-dependent inpatients based on metabolomics and interpretable machine learning. Plasma samples were obtained from healthy (n = 42) and AD-diagnosed individuals (n = 43). The plasma metabolic differences between them were investigated using liquid chromatography-tandem mass spectrometry (AB SCIEX^® QTRAP 4500 system) in different electrospray ionization modes with scheduled multiple reaction monitoring scans. In total, 59 and 52 compounds were semi-quantitatively measured in positive and negative ionization modes, respectively. In addition, 39 metabolites were identified as important variables to contribute to the classifications using an orthogonal partial least squares-discriminant analysis (OPLS-DA) (VIP > 1) and also significantly different between healthy and AD-diagnosed individuals using univariate analysis (p-value < 0.05 and false discovery rate < 0.05). Among the identified metabolites, indole-3-carboxylic acid, quinolinic acid, hydroxy-tryptophan, and serotonin were involved in the tryptophan metabolism along the indole, kynurenine, and serotonin pathways. Metabolic pathway analysis revealed significant changes or imbalances in alanine, aspartate, glutamate metabolism, which was possibly the main altered pathway related to AD. Tryptophan metabolism interactively influenced other metabolic pathways, such as nicotinate and nicotinamide metabolism. Furthermore, among the OPLS-DA-identified metabolites, normetanephrine and ascorbic acid were demonstrated as suitable biological correlates of AD inpatients from our model using an interpretable, supervised decision tree classifier algorithm. These findings indicate that the discriminatory metabolic profiles between healthy and AD-diagnosed individuals may benefit researchers in illustrating the underlying molecular mechanisms of AD. This study also highlights the approach of combining metabolomics and interpretable machine learning as a valuable tool to uncover potential biological correlates. Future studies should focus on the global analysis of the possible roles of these differential metabolites and disordered metabolic pathways in the pathophysiology of AD.

Alterations in Pattern Baldness According to Sex: Hair Metabolomics Approach

Pattern baldness has been associated with the male hormone, dihydrotestosterone. In this study, we tried to determine how the overall metabolic pathways of pattern baldness differ in patients and in normal controls. Our study aimed to identify alterations in hair metabolomic profiles in order to identify possible markers of pattern baldness according to sex. Untargeted metabolomics profiling in pattern baldness patients and control subjects was conducted using ultra-performance liquid chromatography-mass spectrometry. To identify significantly altered metabolic pathways, partial least squares discriminant analysis was performed. Our analysis indicated differences in steroid biosynthesis pathway in both males and females. However, there was a remarkable difference in the androgen metabolic pathway in males, and the estrogen metabolic and arachidonic acid pathways in females. For the first time, we were able to confirm the metabolic pathway in pattern baldness patients using hair samples. Our finding improves understanding of pattern baldness and highlights the need to link pattern baldness and sex-related differences.