Structural and Functional Characterization of the Newly Designed Antimicrobial Peptide Crabrolin21.

(1) Background: antimicrobial resistance is becoming a dramatic problem for public health, and the design of new antimicrobial agents is an active research area. (2) Methods: based on our previous work, we designed an improved version of the crabrolin peptide and characterized its functional and structural properties with a wide range of techniques. (3) Results: the newly designed peptide, crabrolin21, is much more active than the previous ones and shows specific selectivity towards bacterial cells. (4) Conclusions: crabrolin21 shows interesting properties and deserves further studies.

Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies.

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry.

BACKGROUND: The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa. METHODS: Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). RESULTS: Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower. CONCLUSION: Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.

Solution structure of the anticancer p28 peptide in biomimetic medium.

The p28 peptide derived from Pseudomonas aeruginosa azurin shows an anticancer activity after binding to p53 protein and is currently in Phase I of clinical trials. We have studied its structure in water and in a biomimetic media and show that the peptide is unstructured in water but when studied in a biomimetic medium assumes a structure very similar to the one observed in azurin, suggesting a high propensity of this peptide to maintain this secondary structure. Analysis of p28 sequences from different bacterial species indicates conservation of the secondary structure despite amino acid replacement in different positions, suggesting that others, similar peptides could be tested for binding to p53.

NMR metabolomic profiles associated with long-term risk of prostate cancer.

INTRODUCTION: Prostate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors. OBJECTIVES: The aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade. METHODS: A prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis. RESULTS: Men with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up. CONCLUSIONS: This exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.

Associations between untargeted plasma metabolomic signatures and gut microbiota composition in the Milieu Intérieur population of healthy adults.

Host-microbial co-metabolism products are being increasingly recognised to play important roles in physiological processes. However, studies undertaking a comprehensive approach to consider host-microbial metabolic relationships remain scarce. Metabolomic analysis yielding detailed information regarding metabolites found in a given biological compartment holds promise for such an approach. This work aimed to explore the associations between host plasma metabolomic signatures and gut microbiota composition in healthy adults of the Milieu Intérieur study. For 846 subjects, gut microbiota composition was profiled through sequencing of the 16S rRNA gene in stools. Metabolomic signatures were generated through proton NMR analysis of plasma. The associations between metabolomic variables and α- and ß-diversity indexes and relative taxa abundances were tested using multi-adjusted partial Spearman correlations, permutational ANOVA and multivariate associations with linear models, respectively. A multiple testing correction was applied (Benjamini-Hochberg, 10 % false discovery rate). Microbial richness was negatively associated with lipid-related signals and positively associated with amino acids, choline, creatinine, glucose and citrate (-0·133 ≤ Spearman's ρ ≤ 0·126). Specific associations between metabolomic signals and abundances of taxa were detected (twenty-five at the genus level and nineteen at the species level): notably, numerous associations were observed for creatinine (positively associated with eleven species and negatively associated with Faecalibacterium prausnitzii). This large-scale population-based study highlights metabolites associated with gut microbial features and provides new insights into the understanding of complex host-gut microbiota metabolic relationships. In particular, our results support the implication of a 'gut-kidney axis'. More studies providing a detailed exploration of these complex interactions and their implications for host health are needed.

Temozolomide, Gemcitabine, and Decitabine Hybrid Nanoconjugates: From Design to Proof-of-Concept (PoC) of Synergies toward the Understanding of Drug Impact on Human Glioblastoma Cells.

This paper emphasizes the synthesis of novel hybrid drug nanoparticles (Hyb-D-AuNPs) based on gold-temozolomide (TMZ) complexes combined with gemcitabine (GEM) and decitabine (DAC) to improve the efficiency and reduce the resistance of U87 malignant glial cells against TMZ. All products were evaluated by several spectroscopic techniques (Raman, UV-Vis) and transmission electron microscopy (TEM). Besides, for therapeutic purposes, the effect of these nanoparticles on cell proliferation and toxicity was evaluated, which clearly showed a synergic action of TMZ and GEM. Through the analysis of the exometabolome by nuclear magnetic resonance (NMR), the metabolic changes in the culture medium were measured in glial cells. Moreover, these nanoparticles are especially appropriated to the thermal destruction of cancer in the case of photothermal therapy due to their photothermal heating properties. This study presents an original chemical approach that it could play a central role in the field of nanomedicine, with novel perspectives for the development of new drugs and active targeting in glioblastoma multiforme (GBM) cancer therapy.

Effect of positive charges in the structural interaction of crabrolin isoforms with lipopolysaccharide.

Antimicrobial peptides (AMPs) appear as chemical compounds of increasing interest for their role in killing bacteria and, more recently, for their ability to bind endotoxin (lipopolysaccharide, LPS) that is released during bacterial infection and that may lead to septic shock. This dual role in the mechanism of action can further be enhanced in a synergistic way when two or more AMPs are combined together. Not all AMPs are able to bind LPS, suggesting that several modes of binding to the bacterial surface may exist. Here we analyze a natural AMP, crabrolin, and two mutated forms, one with increased positive charge (Crabrolin Plus) and the other with null charge (Crabrolin Minus), and compare their binding abilities to LPS. While Crabrolin WT as well Crabrolin Minus do not show binding to LPS, the mutated Crabrolin Plus exhibits binding and forms a well defined structure in the presence of LPS. The results strengthen the importance of positive charges for the binding to LPS and suggest the mutated form with increased positive charge as a promising candidate for antimicrobial and antiseptic activity.

Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors.

BACKGROUND: Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis. METHODS: Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality. RESULTS: Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (ΔH24-H0) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients. CONCLUSIONS: Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes. TRIAL REGISTRATION: All human serum samples were collected and stored, provided by the "center of biologic resources for liver disease", in Jean Verdier Hospital, Bondy, France (BB-0033-00027).

Nuclear magnetic resonance metabolic fingerprint of bevacizumab in mutant IDH1 glioma cells.

Background Malignant gliomas are rapidly growing tumours that extensively invade the brain and have bad prognosis. Our study was performed to assess the metabolic effects of bevacizumab on the glioma cells carrying the IDH1 mutation, a mutation, associated with better prognosis and treatment outcome. Bevacizumab is known to inhibit tumour growth by neutralizing the biological activity of vascular endothelial growth factor (VEGF). However, the direct effects of bevacizumab on tumour cells metabolism remain poorly known. Materials and methods The immunoassay and MTT assay were used to assess the concentration of secreted VEGF and cell viability after bevacizumab exposure. Metabolomic studies on cells were performed using high resolution magic angle spinning spectroscopy (HRMAS). Results mIDH1-U87 cells secreted VEGF (13 ng/mL). Regardless, bevacizumab had no cytotoxic effect, even after a 72h exposure and with doses as high as 1 mg/mL. Yet, HRMAS analysis showed a significant effect of bevacizumab (0.1 mg/mL) on the metabolic phenotype of mIDH1-U87 cells with elevation of 2-hydroxyglutarate and changes in glutamine group metabolites (alanine, glutamate, glycine) and lipids (polyunsaturated fatty acids [PUFA], glycerophosphocholine, and phosphocholine). Conclusions In mIDH1-U87 cells, changes in glutamine group metabolites and lipids were identified as metabolic markers of bevacizumab treatment. These data support the possibility of a functional tricarboxylic acid cycle that runs in reductive manner, as a probable mechanism of action of bevacizumab in IDH1 mutated gliomas and propose a new target pathway for effective treatment of malignant gliomas.

Determination of candidate metabolite biomarkers associated with recurrence of HCV-related hepatocellular carcinoma.

Hepatitis C virus (HCV) infection is associated with a high risk of developing hepatocellular carcinoma (HCC) and HCC recurrence remains the primary threat to outcomes after curative therapy. In this study, we compared recurrent and non-recurrent HCC patients treated with radiofrequency ablation (RFA) in order to identify characteristic metabolic profile variations associated with HCC recurrence. Gas chromatography-mass spectrometry (GC-MS) -based metabolomic analyses were conducted on serum samples obtained before and after RFA therapy. Significant variations were observed in metabolites in the glycerolipid, tricarboxylic acid (TCA) cycle, fatty acid, and amino acid pathways between recurrent and non-recurrent patients. Observed differences in metabolites associated with recurrence did not coincide before and after treatment except for fatty acids. Based on the comparison of serum metabolomes between recurrent and non-recurrent patients, key discriminatory metabolites were defined by a random forest (RF) test. Two combinations of these metabolites before and after RFA treatment showed outstanding performance in predicting HCV-related HCC recurrence, they were further confirmed by an external validation set. Our study showed that the determined combination of metabolites may be potential biomarkers for the prediction of HCC recurrence before and after RFA treatment.

NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer.

Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate for the first time whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy women, could contribute to predict the risk of developing breast cancer within the following decade and to better understand the aetiology of this complex disease. Methods: A prospective nested case-control study was set up in the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, including 206 breast cancer cases diagnosed during a 13-year follow-up and 396 matched controls. Untargeted nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples. Multivariable conditional logistic regression models were computed for each individual NMR variable and for combinations of variables derived by principal component analysis. Results: Several metabolomic variables from 1D NMR spectroscopy were associated with breast cancer risk. Women characterized by higher fasting plasma levels of valine, lysine, arginine, glutamine, creatine, creatinine and glucose, and lower plasma levels of lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids had a higher risk of developing breast cancer. P-values ranged from 0.00007 [odds ratio (OR)T3vsT1=0.37 (0.23-0.61) for glycerol-derived compounds] to 0.04 [ORT3vsT1=1.61 (1.02-2.55) for glutamine]. Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term breast cancer risk. These results provide interesting insights to better understand complex mechanisms involved in breast carcinogenesis and evoke plasma metabolic disorders favourable for carcinogenesis initiation. This study may contribute to develop screening strategies for the identification of at-risk women for breast cancer well before symptoms appear.

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy.

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis.

Nuclear magnetic resonance metabolomics and human liver diseases: The principles and evidence associated with protein and carbohydrate metabolism.

During the last decade, metabolomics has become widely used in the field of human diseases. Numerous studies have demonstrated that this is a powerful technique for improving the understanding, diagnosis and management of various types of liver disease, such as acute and chronic liver diseases, and liver transplantation. Nuclear magnetic resonance (NMR) spectroscopy is one of the two most commonly applied methods for metabolomics. The aim of the present review was to investigate the results from recent key publications focusing on aspects of protein and carbohydrate metabolism. The review includes existing procedures, which are currently used for NMR data acquisition and statistical analysis. In addition, notable results obtained by these studies on protein and carbohydrate metabolism concerning human liver diseases are presented.

Application of LC-MS-based metabolomics method in differentiating septic survivors from non-survivors.

Septic shock is the most severe form of sepsis, which is still one of the leading causes of death in the intensive care unit (ICU). Even though early prognosis and diagnosis are known to be indispensable for reaching an optimistic outcome, pathogenic complexities and the lack of specific treatment make it difficult to predict the outcome individually. In the present study, serum samples from surviving and non-surviving septic shock patients were drawn before clinical intervention at admission. Metabolic profiles of all the samples were analyzed by liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. One thousand four hundred nineteen peaks in positive mode and 1878 peaks in negative mode were retained with their relative standard deviation (RSD) below 30 %, in which 187 metabolites were initially identified by retention time and database in the light of the exact molecular mass. Differences between samples from the survivors and the non-survivors were investigated using multivariate and univariate analysis. Finally, 43 significantly varied metabolites were found in the comparison between survivors and non-survivors. Concretely, metabolites in the tricarboxylic acid (TCA) cycle, amino acids, and several energy metabolism-related metabolites were up-regulated in the non-survivors, whereas those in the urea cycle and fatty acids were generally down-regulated. Metabolites such as lysine, alanine, and methionine did not present significant changes in the comparison. Six metabolites were further defined as primary discriminators differentiating the survivors from the non-survivors at the early stage of septic shock. Our findings reveal that LC-MS-based metabolomics is a useful tool for studying septic shock. Graphical abstract ᅟ.

Tunable Design of Gold(III)-Doxorubicin Complex-PEGylated Nanocarrier. The Golden Doxorubicin for Oncological Applications.

To date, the translation of Au (III) complexes into chemotherapeutic agents has been hindered by their low stability under physiological conditions, a crucial parameter in drug development. In this study, we report an innovative four-step synthesis of a stable Au (III)-doxorubicin (DOX) complex, acting as a key constitutive component of doxorubicin-loaded PEG-coated nanoparticles (DOX IN-PEG-AuNPs). For therapeutic purposes, such AuNPs were then functionalized with the anti-Kv11.1 polyclonal antibody (pAb), which specifically recognizes the hERG1 channel that is overexpressed on the membrane of human pancreatic cancer cells. The nature of the interactions between DOX and Au (III) ions was probed by various analytical techniques (Raman spectroscopy, UV-vis, and (1)H NMR), which enabled studying the Au (III)-DOX interactions during AuNPs formation. The theoretical characterization of the vibrational bands and the electronic transitions of the Au (III)-DOX complex calculated through computational studies showed significant qualitative agreement with the experimental observations on AuNPs samples. Stability in physiological conditions and efficient drug loading (up to to 85 w/w %) were achieved, while drug release was strongly dependent on the structure of DOX IN-PEG-AuNPs and on the pH. Furthermore, the interactions among DOX, PEG, and Au (III) ions in DOX IN-PEG-AuNPs differed significantly from those found in polymer-modified AuNPs loaded with DOX by covalent linkage, referred to as DOX ON-PEG-AuNPs. In vitro experiments indeed demonstrated that such differences strongly influenced the therapeutic potential of AuNPs in pancreatic cancer treatment, with a significant increase of the DOX therapeutic index when complexed to Au (III) ions. Collectively, our study demonstrated that Au (III)-DOX complexes as building blocks of PEGylated AuNPs constitutes a promising approach to transform promising Au (III) complexes into real chemotherapeutic drugs for the treatment of pancreatic cancer.

Nuclear magnetic resonance spectroscopic analysis of salivary metabolome in sarcoidosis.

BACKGROUND: Sarcoidosis is a systemic granulomatous disease of unknown cause which has diverse clinical impacts, ranging from benign to very severe, which may therefore require systemic treatment. Only a few tools are currently available to monitor management in these patients. OBJECTIVES: As sarcoidosis is known to affect salivary glands, we hypothesized that analysis of saliva could reveal valuable biomarkers for disease management. We designed a comparative analysis of salivary metabolomics in patients and controls using Nuclear Magnetic Resonance (NMR). METHODS: Metabolomic profiles of saliva collected from 24 sarcoidosis patients and 45 controls were obtained by proton NMR spectroscopy with multivariate statistical analysis, followed by metabolite identification and pathway analysis. Oral and dental examinations were performed concomitantly, together with assessment of smoking habits. RESULTS: A predictive salivary metabolomic signature associated with sarcoidosis was computed with the Orthogonal Partial least squares discriminant analysis (OPLS) model. Six metabolites were altered in samples from sarcoidosis patients compared to controls, including decreased levels of methanol and butyrate and increased levels of lactate, acetate and N-butyrate. CONCLUSION: This study showed that NMR metabolomics can discriminate saliva samples from sarcoidosis patients and controls. According to these preliminary results, saliva studies in sarcoidosis patients would be particularly useful to identify potentially relevant biomarkers. A study based on a larger number of patients at different stages of the disease or with treated patients is needed to assess the clinical relevance of NMR metabolomics in sarcoidosis.

Polyamine signal through gap junctions: A key regulator of proliferation and gap-junction organization in mammalian tissues?

We propose that interaction rules derived from polyamine exchange in connected cells may explain the spatio-temporal organization of gap junctions observed during tissue regeneration and tumorigenesis. We also hypothesize that polyamine exchange can be considered as signal that allows cells to sense the proliferation status of their neighbors. Polyamines (putrescine, spermidine, and spermine) are indeed small aliphatic polycations that serve as fuels to sustain elevated proliferation rates of the order observed in cancer cells. Based on recent reports, we consider here that polyamines can be exchanged through gap junction channels between mammalian cells. Such intercellular exchange of polyamines has critical consequences on the local control of growth. In line with this hypothesis, the complex protein network that keeps polyamine levels finely tuned in mammalian cells can translate polyamine efflux or influx into integrated signals controlling transcription, translation, and cell communications.

Sequential Serum Metabolomic Profiling after Radiofrequency Ablation of Hepatocellular Carcinoma Reveals Different Response Patterns According to Etiology.

Radiofrequency ablation (RFA) is commonly performed as a curative approach in patients with hepatocellular carcinoma (HCC); however, the risk of tumor recurrence is difficult to predict due to a lack of reliable clinical and biological markers, and identification of new biomarkers poses a major challenge for improving prognoses. Metabolomics is a promising technique that may lead to the identification and characterization of new disease fingerprints. The objective of the present study was to explore, preoperatively and at various time points post-RFA, the metabolic profile of serum samples from HCC patients to identify factors associated with treatment response and recurrence. Sequential sera obtained before and after RFA procedures for 120 patients with HCC due to cirrhosis were investigated using nuclear magnetic resonance metabolomics. A multilevel orthogonal projection to latent structure analysis was used to discriminate intraindividual metabolic changes in response to RFA treatment. Recurrence-free survival differed depending on the underlying cause of cirrhosis. The statistical model showed significant differences depending on whether the liver disease had a viral or nonviral etiology before RFA intervention (explained variance of R(2)Y = 0.89 and predictability of Q(2)Y = 0.34). These profiles were also associated with specific and distinct metabolic responses after RFA.