Explore the vast range of titles available.

Polyamines are essential for the growth and proliferation of mammalian cells and are intimately involved in biological mechanisms such as DNA replication, RNA transcription, protein synthesis, and post-translational modification. These mechanisms regulate cellular proliferation, differentiation, programmed cell death, and the formation of tumors. Several studies have confirmed the positive effect of polyamines on the maintenance of health, while others have demonstrated that their activity may promote the occurrence and progression of diseases. This review examines a variety of topics, such as polyamine source and metabolism, including metabolism, transport, and the potential impact of polyamines on health and disease. In addition, a brief summary of the effects of oncogenes and signaling pathways on tumor polyamine metabolism is provided. 5ikmGssBZD_e4xpSJscY2Y Video Abstract

Dysbiosis of the gut microbiome and related metabolites in chronic kidney disease (CKD) have been intimately associated with the prevalence of cardiovascular diseases. Unfortunately, thus far, there is a paucity of sufficient knowledge of gut microbiome and related metabolites on CKD progression partly due to the severely limited investigations. Using a 5/6 nephrectomized (NX) rat model, we carried out 16S rRNA sequence and untargeted metabolomic analyses to explore the relationship between colon’s microbiota and serum metabolites. Marked decline in microbial diversity and richness was accompanied by significant changes in 291 serum metabolites, which were mediated by altered enzymatic activities and dysregulations of lipids, amino acids, bile acids and polyamines metabolisms. Interestingly, CCr was directly associated with some microbial genera and polyamine metabolism. However, SBP was directly related to certain microbial genera and glycine-conjugated metabolites in CKD rats. Administration of poricoic acid A (PAA) and Poria cocos (PC) ameliorated microbial dysbiosis as well as attenuated hypertension and renal fibrosis. In addition, treatments with PAA and PC lowered serum levels of microbial-derived products including glycine-conjugated compounds and polyamine metabolites. Collectively, the present study confirmed the CKD-associated gut microbial dysbiosis and identified a novel dietary and therapeutic strategy to improve the gut microbial dysbiosis and the associated metabolomic disorders and retarded the progression of kidney disease in the rat model of CKD.

Early studies on plant polyamine research pointed to their involvement in responses to different environmental stresses. During the last few years, genetic, transcriptomic and metabolomic approaches have unravelled key functions of different polyamines in the regulation of abiotic stress tolerance. Nevertheless, the precise molecular mechanism(s) by which polyamines control plant responses to stress stimuli are largely unknown. Recent studies indicate that polyamine signalling is involved in direct interactions with different metabolic routes and intricate hormonal cross-talks. Here we discuss the integration of polyamines with other metabolic pathways by focusing on molecular mechanisms of their action in abiotic stress tolerance. Recent advances in the cross talk between polyamines and abscisic acid are discussed and integrated with processes of reactive oxygen species (ROS) signalling, generation of nitric oxide, modulation of ion channel activities and Ca²⁺ homeostasis, amongst others.

ABSTRACT Glioblastoma stem cells (GSCs) are crucial drivers of tumor progression and therapeutic resistance in glioblastoma multiforme (GBM), yet the molecular mechanisms maintaining their self‐renewal remain incompletely understood. Here, we identify a critical role for polyamine metabolism in GSCs maintenance. We show that GSCs exhibit elevated polyamine levels compared to non‐stem tumor cells, attributed to enhanced ornithine decarboxylase (ODC) expression. High ODC expression correlates with poor patient prognosis in GBM. Genetic and pharmacologic targeting of ODC attenuated GSCs self‐renewal and tumorigenicity. Our findings reveal a previously unrecognized metabolic dependency of GSCs on polyamine synthesis, and ODC may be a potential therapeutic target in GBM. Our findings delineate a novel regulatory network that integrates metabolic and GSCs self‐renewal in GBM. By integrating genetic ODC ablation with multiomic profiling, we redefine polyamine metabolism as a linchpin of GSCs self‐renewal, a dependency exploitable through precision gene editing. While technical hurdles persist, emerging CRISPR delivery technologies and combinatorial regimens position ODC targeting as a viable strategy against glioblastoma therapeutic recalcitrance. Further in‐depth exploration of this strategy may pave the way for more effective interventions, ultimately offering renewed hope to patients afflicted by this devastating disease.

Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the identification of key genes associated with polyamines metabolism in CO could offer fresh insights for clinical management of CO. This study utilized two datasets from public databases (GSE205668 and GSE104815) and 59 polyamines metabolism-related genes (PMRGs) to screen for candidate genes. Subsequently, candidate key genes were selected using Mendelian randomization (MR) analysis, and machine learning algorithms were employed to obtain intersecting feature genes based on the MR results. Then key genes were identified through expression validation. Finally, we conducted research on the key genes including gene set enrichment analysis (GSEA), immune infiltration, and transcription factor(TF)-mRNA network. Differential analysis identified 432 candidate genes linked to childhood obesity and polyamine metabolism, with 4 key genes showing causal relationships. Specifically, WWC1 , NPL , and LAPTM5 as risk factors [odd ratio (OR) > 1], while GPAT3 (OR < 1) was identified as a protective factor for CO. Machine learning algorithms pinpointed 3 feature genes ( WWC1 , NPL , and GPAT3 ) with significant differential expression and consistent trends. GSEA revealed ribosome and lysosome pathways linked to key genes. MITF regulated these genes in the TF-mRNA network. Twelve immune cell types, mostly correlating with key genes, were identified. We identified 3 key genes ( WWC1 , NPL , and GPAT3 ) related to polyamine metabolism in CO. Additionally, we investigated their potential biological functions and regulatory mechanisms, aiming to provide new theoretical basis for the treatment and diagnosis of CO.

Naturally occurring polyamines are absolutely required for cellular growth and proliferation. Many neoplastic cells are reliant on elevated polyamine levels and maintain these levels through dysregulated polyamine metabolism. The modulation of polyamine metabolism is thus a promising avenue for cancer therapeutics and has been attempted with numerous molecules, including enzyme inhibitors and polyamine analogues. SBP-101 (diethyl dihydroxyhomospermine) is a spermine analogue that has shown efficacy in slowing pancreatic tumor progression both in vitro and in vivo; however, the mechanisms underlying these effects remain unclear. We determined the effects of the SBP-101 treatment on a variety of cancer cell types in vitro, including lung, pancreatic, and ovarian. We evaluated the activity of enzymes involved in polyamine metabolism and the effect on intracellular polyamine pools following the SBP-101 treatment. The SBP-101 treatment produced a modest but variable increase in polyamine catabolism; however, a robust downregulation of the activity of the biosynthetic enzyme, ornithine decarboxylase (ODC), was seen across all of the cell types studied and indicates that SBP-101 likely exerts its effect predominately through the downregulation of ODC, with a minor upregulation of catabolism. Our in vitro work indicated that SBP-101 was most toxic in the tested ovarian cell lines. Therefore, we evaluated the efficacy of SBP-101 as a monotherapy in the immunosuppressive VDID8+ murine ovarian model. Mice treated with SBP-101 demonstrated a delay in tumor progression, a decrease in the overall tumor burden, and a marked increase in median survival.

This study aimed to identify and validate prognostic genes associated with polyamine metabolism-related genes (PMRGs) in hepatocellular carcinoma (HCC), offering potential novel therapeutic targets and strategies. The HCC-related datasets and 19 PMRGs were included in this study. Prognostic genes were screened out through differential expression analysis, univariate and multivariate Cox regression analysis. Subsequently, the construction of the risk model and nomogram, as well as functional enrichment and immune infiltration analysis were carried out. Ultimately, prognostic gene expression was further validated by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme linked immunosorbent assay (ELISA). SMOX, SRM, and SAT1 were identified as prognostic genes. risk score and stage were investigated as independent prognostic factors to construct nomogram. Moreover, the drug metabolism cytochrome p450 pathway was found had a significantly enriched in different risk groups. After that, 11 immune cells differed significantly across risk groups, with Eosinophi having the highest positive/negative correlation with SAT1/SRM, respectively. Finally, SMOX and SRM were highly expressed in the HCC group, while SAT1 showed the opposite pattern. The three genes linked to PMRGs, were identified as prognostic genes for constructing risk models, which may provide a basis for understanding HCC pathogenesis.

We aimed to explore whether the genes associated with both platinum‐based therapy and polyamine metabolism could predict the prognosis of LUAD. We searched for the differential expression genes (DEGs) associated with platinum‐based therapy, then we interacted them with polyamine metabolism‐related genes to obtain hub genes. Subsequently, we analysed the main immune cell populations in LUAD using the scRNA‐seq data, and evaluated the activity of polyamine metabolism of different cell subpopulations. The DEGs between high and low activity groups were screened to identify key DEGs to establish prognostic risk score model. We further elucidated the landscape of immune cells, mutation and drug sensitivity analysis in different risk groups. Finally, we got 10 hub genes associated with both platinum‐based chemotherapy and polyamine metabolism, and found that these hub genes mainly affected signalling transduction pathways. B cells and mast cells with highest polyamine metabolism activity, while NK cells were found with lowest polyamine metabolism activity based on scRNA‐seq data. DEGs between high and low polyamine metabolism activity groups were identified, then 6 key genes were screened out to build risk score, which showed a good predictive power. The risk score showed a universal negative correlation with immunotherapy checkpoint genes and the cytotoxic T cells infiltration. The mutation rates of EGFR in low‐risk group was significantly higher than that of high‐risk group. In conclusion, we developed a risk score based on key genes associated with platinum‐based therapy and polyamine metabolism, which provide a new perspective for prognosis prediction of LUAD.

In our experiments, we investigated the effect of temperature on diatom polyamine metabolism using Skeletonema dohrnii as an experimental algal species. We set three different temperature conditions for incubation and selected Skeletonema dohrnii in the exponential growth period, and analyzed basic physiological parameters, polyamine composition and content, and polyamine oxidase (PAO) gene expression at different temperatures. The results showed that low temperatures led to a decrease in growth rate, an increase in biogenic silica content, an increase in the content of putrescine and spermine, a decrease in the concentration of spermidine, and a down-regulation of PAO gene expression. In addition, high temperature led to an increase in growth rate, a significant change in the concentration of putrescine and spermine, and an increase in spermidine. These findings suggest that changes in temperature affect the growth rate of algae, low temperature increases the biogenic silica content of diatoms, different temperature stresses lead to different kinds of polyamine changes in diatoms, and the PAO gene may play a role in regulating the response of algae to temperature changes. This study lays a foundation for further exploration of the function of the PAO gene in Skeletonema dohrnii.

BackgroundAccumulating evidence indicates that elevated polyamine levels are closely linked to tumor initiation and progression. However, the precise role of polyamine metabolism in hepatocellular carcinoma (HCC) remains poorly understood.MethodsWe conducted differential expression analysis on bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to identify 65 polyamine metabolism-related genes. By employing unsupervised consensus clustering, AddModuleScore, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network analysis (WGCNA), we identified polyamine metabolism-related genes at both the bulk RNA-seq and single-cell RNA-seq (scRNA-seq) levels. Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. Additionally, we developed a prognostic nomogram model by integrating PMRS with clinical variables. To explore immune treatment sensitivity, we assessed tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) score, mutation frequency, and immune checkpoint genes expression. Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.ResultsUsing 101 machine learning algorithms, we established a polyamine metabolism-related signature comprising 9 genes, which exhibited strong prognostic value for HCC patients. Further analysis revealed significant differences in clinical features, biological functions, mutation profiles, and immune cell infiltration between high-risk and low-risk groups. Notably, TIDE analysis and immune phenotype scoring (IPS) demonstrated distinct immune treatment sensitivities between the two risk groups. RT-qPCR validation confirmed that these 9 genes were highly expressed in normal cells but significantly downregulated in tumor cells.ConclusionsOur study developed a polyamine metabolism-based prognostic risk signature for HCC, which may provide valuable insights for personalized treatment strategies in HCC patients.