Targeting purine metabolism in ovarian cancer

Correlation between the bacterial community succession and purine compound changes during Huangjiu fermentation

Purine is mainly culprit of hyperuricemia (HUA) and gout, which is widely present in Huangjiu in the form of free bases. Bacterial succession plays an important role in quality control in Huangjiu. The correlation between the purine compound content and the bacterial communities during the fermentation process has not yet been evaluated. In this study, high-throughput sequencing (HTS) technology was used to monitor the bacterial community composition of Huangjiu at different fermentation stages. The correlation between the bacterial community and the contents of physicochemical properties and purine compounds were evaluated using the Spearman analysis method. The key enzymes of purine metabolism pathway in the microbial community were analyzed by bioinformatics using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). The results showed that the purine content in Huangjiu increased gradually in 0∼9d of fermentation (21.05-65.71 mg/L), and stabilized gradually in 12∼18d (65.63-69.55 mg/L), while the abundance of lactic acid bacteria (LAB) of bacterial microbial flora were increased (0∼9d) and then stabilized (12∼18d). Moreover, Lactobacillus acetotolerans and Lactobacillus helveticus were highly correlated positively with purine contents, while Limosilactobacillus fermentum and Lactiplantibacillus plantarum were correlated negatively. In addition, the dominant strains of bacteria were involved in the metabolism of purine, and the key enzymes for purine compound synthesis were more abundant than that for purine degradation. This study is helpful to scientifically understand the formation mechanism of purines, providing a basis for screening functional strains of purine degrading to accurately regulate purine level in Huangjiu.

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

BACKGROUND

Non-small cell lung cancer (NSCLC) is the primary form of lung cancer, and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease. However, the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies. Consequently, it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments.

AIM

To identify the metabolic signatures associated with neutrophil extracellular traps (NETs) and chemoimmunotherapy efficacy in NSCLC patients.

METHODS

In total, 159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled. We first investigated the characteristics influencing clinical efficacy. Circulating levels of NETs and cytokines were measured by commercial kits. Liquid chromatography tandem mass spectrometry quantified plasma metabolites, and differential metabolites were identified. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest algorithms were employed. By using plasma metabolic profiles and machine learning algorithms, predictive metabolic signatures were established.

RESULTS

First, the levels of circulating interleukin-8, neutrophil-to-lymphocyte ratio, and NETs were closely related to poor efficacy of first-line chemoimmunotherapy. Patients were classed into a low NET group or a high NET group. A total of 54 differential plasma metabolites were identified. These metabolites were primarily involved in arachidonic acid and purine metabolism. Three key metabolites were identified as crucial variables, including 8,9-epoxyeicosatrienoic acid, L-malate, and bis(monoacylglycerol)phosphate (18:1/16:0). Using metabolomic sequencing data and machine learning methods, key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy.

CONCLUSION

The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

Integrated network pharmacology and metabolomics to reveal the mechanism of Pinellia ternata inhibiting non-small cell lung cancer cells

Lung cancer is a malignant tumor with highly heterogeneous characteristics. A classic Chinese medicine, Pinellia ternata (PT), was shown to exert therapeutic effects on lung cancer cells. However, its chemical and pharmacological profiles are not yet understood. In the present study, we aimed to reveal the mechanism of PT in treating lung cancer cells through metabolomics and network pharmacology. Metabolomic analysis of two strains of lung cancer cells treated with Pinellia ternata extracts (PTE) was used to identify differentially abundant metabolites, and the metabolic pathways associated with the DEGs were identified by MetaboAnalyst. Then, network pharmacology was applied to identify potential targets against PTE-induced lung cancer cells. The integrated network of metabolomics and network pharmacology was constructed based on Cytoscape. PTE obviously inhibited the proliferation, migration and invasion of A549 and NCI-H460 cells. The results of the cellular metabolomics analysis showed that 30 metabolites were differentially expressed in the lung cancer cells of the experimental and control groups. Through pathway enrichment analysis, 5 metabolites were found to be involved in purine metabolism, riboflavin metabolism and the pentose phosphate pathway, including D-ribose 5-phosphate, xanthosine, 5-amino-4-imidazolecarboxyamide, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD). Combined with network pharmacology, 11 bioactive compounds were found in PT, and networks of bioactive compound-target gene-metabolic enzyme-metabolite interactions were constructed. In conclusion, this study revealed the complicated mechanisms of PT against lung cancer. Our work provides a novel paradigm for identifying the potential mechanisms underlying the pharmacological effects of natural compounds.

Comparative physiological, biochemical and transcriptomic analyses to reveal potential regulatory mechanisms in response to starvation stress in Cipangopaludina chinensis

Cipangopaludina chinensis, as a financially significant species in China, represents a gastropod in nature which frequently encounters starvation stress owing to its limited prey options. However, the underlying response mechanisms to combat starvation have not been investigated in depth. We collected C. chinensis under several times of starvation stress (0, 7, 30, and 60 days) for nutrient, biochemical characteristics and transcriptome analyses. The results showed that prolonged starvation stress (> 30 days) caused obvious fluctuations in the nutrient composition of snails, with dramatic reductions in body weight, survival and digestive enzyme activity (amylase, protease, and lipase), and markedly enhanced the antioxidant enzyme activities of the snails. Comparative transcriptome analyses revealed 3538 differentially expressed genes (DEGs), which were significantly associated with specific starvation stress-responsive pathways, including oxidative phosphorylation and alanine, aspartate, and glutamate metabolism. Then, we identified 40 candidate genes (e.g., HACD2, Cp1, CYP1A2, and GPX1) response to starvation stress through STEM and WGCNA analyses. RT-qPCR verified the accuracy and reliability of the high-throughput sequencing results. This study provides insights into snail overwintering survival and the potential regulatory mechanisms of snail adaptation to starvation stress.

Preclinical efficacy of CBR-5884 against epithelial ovarian cancer cells by targeting the serine synthesis pathway

Reprogramming of the serine synthesis pathway (SSP) is intricately linked to the progression of epithelial ovarian cancer (EOC). CBR-5884, a selective small-molecule inhibitor targeting phosphoglycerate dehydrogenase (PHGDH), effectively impedes the de novo synthesis of serine within cancer cells. This study aimed to evaluate the inhibitory effect of CBR-5884 on EOC cells and delineate its specific mechanism, thereby proposing a novel therapeutic approach for treating EOC. The suppression of serine biosynthesis after CBR-5884 treatment was evaluated using RNA sequencing and a serine assay kit, and the results showed that CBR-5884 effectively downregulated serine biosynthesis in EOC cells, particularly those expressing high levels of PHGDH. In vitro studies revealed that CBR-5884 demonstrated significant antitumor effects and suppressed migration and invasion of EOC cells through down-regulation of the integrin subunit beta 4 (ITGB4)/extracellular signal-regulated kinase (ERK)/epithelial-mesenchymal transition signal axis. Additionally, CBR-5884 mitigated the stemness of EOC cells and heightened their sensitivity to chemotherapy. Moreover, in vivo studies revealed that CBR-5884 significantly delayed tumor growth, with histological analysis indicating the safety profile of CBR-5884. Finally, the patient-derived organoid (PDO) models were utilized to explore the preclinical efficacy of CBR-5884 against EOC cells, and the results unveiled that CBR-5884 impeded proliferation and downregulated the expression of ITGB4 in EOC PDO models. Our findings supports the anticancer properties of CBR-5884 in EOC cells exhibiting high PHGDH expression, manifesting through the suppression of proliferation, migration, and invasion, while enhancing chemotherapy sensitivity, suggesting that CBR-5884 holds promise as an efficacious strategy for the treatment of EOC.

Perspectives and challenges in developing small molecules targeting purine nucleoside phosphorylase

As a cytosolic enzyme involved in the purine salvage pathway metabolism, purine nucleoside phosphorylase (PNP) plays an important role in a variety of cellular functions but also in immune system, including cell growth, apoptosis and cancer development and progression. Based on its T-cell targeting profile, PNP is a potential target for the treatment of some malignant T-cell proliferative cancers including lymphoma and leukemia, and some specific immunological diseases. Numerous small-molecule PNP inhibitors have been developed so far. However, only Peldesine, Forodesine and Ulodesine have entered clinical trials and exhibited some potential for the treatment of T-cell leukemia and gout. The most recent direction in PNP inhibitor development has been focused on PNP small-molecule inhibitors with better potency, selectivity, and pharmacokinetic property. In this perspective, considering the structure, biological functions, and disease relevance of PNP, we highlight the recent research progress in PNP small-molecule inhibitor development and discuss prospective strategies for designing additional PNP therapeutic agents.

Expression of human dCTP pyrophosphatase 1 (DCTPP1) and its association with cisplatin resistance characteristics in ovarian cancer

Cisplatin (DDP) resistance is a major challenge in treating ovarian cancer patients. A recently discovered enzyme called dCTP pyrophosphatase 1 (DCTPP1) has been implicated in regulating cancer characteristics, including drug responses. In this study, we aimed to understand the role of DCTPP1 in cancer progression and cisplatin response. Using publicly available databases, we analysed the expression and clinical significance of DCTPP1 in ovarian cancer. Our bioinformatics analysis confirmed that DCTPP1 is significantly overexpressed in ovarian cancer and is closely associated with tumour progression and poor prognosis after cisplatin treatment. We also found that DCTPP1 located in oxidoreductase complex and may be involved in various biological processes related to cisplatin resistance, including pyrimidine nucleotide metabolism, the P53 signalling pathway and cell cycle signalling pathways. We observed higher expression of DCTPP1 in cisplatin-resistant cells (SKOV3/DDP) and samples compared to their sensitive counterparts. Additionally, we found that DCTPP1 expression was only enhanced in SKOV3/S cells when treated with cisplatin, indicating different expression patterns of DCTPP1 in cisplatin-sensitive and cisplatin-resistant cancer cells. Our study further supports the notion that cisplatin induces intracellular reactive oxygen species (ROS) and triggers cancer cell death through excessive oxidative stress. Knocking out DCTPP1 reversed the drug resistance of ovarian cancer cells by enhancing the intracellular antioxidant stress response and accumulating ROS. Based on our research findings, we conclude that DCTPP1 has prognostic value for ovarian cancer patients, and targeting DCTPP1 may be clinically significant in overcoming cisplatin resistance in ovarian cancer.

The microbiota-gut-brain axis: A crucial immunomodulatory pathway for Bifidobacterium animalis subsp. lactis' resilience against LPS treatment in neonatal rats

An imbalanced gut microflora may contribute to immune disorders in neonates due to an immature gut barrier. Bacterial toxins, particularly, can trigger the immune system, potentially resulting in uncontrolled gut and systemic inflammation. Previous research has revealed that Bifidobacterium animalis subsp. lactis (B. lactis) could protect against early-life pathogen infections by enhancing the gut barrier. However, the effects of B. lactis on a compromised immune system remain uncertain. Hence, this study concentrated on the immunomodulatory effects and mechanisms of B. lactis in neonatal rats intraperitoneally injected with lipopolysaccharide (LPS), a bacterial toxin and inflammatory mediator. First, B. lactis significantly alleviated the adverse effects induced by LPS on the growth, development, and body temperature of neonatal rats. Second, B. lactis significantly reduced the immune responses and damage induced by LPS, affecting both systemic and local immune responses in the peripheral blood, gut, and brain. Notably, B. lactis exhibited extra potent neuroprotective and neurorepair effects. Our research found that pre-treatment with B. lactis shaped the diverse gut microecology by altering both microbial populations and metabolic biomolecules, closely linked to immunomodulation. Overall, this study elucidated the multifaceted roles of B. lactis in neonatal hosts against pathogenic infection and immune disorder, revealing the existence of the microbiota-gut-brain axis.

Spatially Resolved Molecular Analysis of Host Response to Medical Device Implantation Using the 3D OrbiSIMS Highlights a Critical Role for Lipids

A key goal for implanted medical devices is that they do not elicit a detrimental immune response. Macrophages play critical roles in the modulation of the host immune response and are the cells responsible for persistent inflammatory reactions to implanted biomaterials. Two novel immune-instructive polymers that stimulate pro- or anti-inflammatory responses from macrophages in vitro are investigated. These also modulate in vivo foreign body responses (FBR) when implanted subcutaneously in mice. Immunofluorescent staining of tissue abutting the polymer reveals responses consistent with pro- or anti-inflammatory responses previously described for these polymers. Three Dimensional OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) analysis to spatially characterize the metabolites in the tissue surrounding the implant, providing molecular histology insight into the metabolite response in the host is applied. For the pro-inflammatory polymer, monoacylglycerols (MG) and diacylglycerols (DG) are observed at increased intensity, while for the anti-inflammatory coating, the number of phospholipid species detected decreased, and pyridine and pyrimidine levels are elevated. Small molecule signatures from single-cell studies of M2 macrophages in vitro correlate with the in vivo observations, suggesting potential for prediction. Metabolite characterization by the 3D OrbiSIMS is shown to provide insight into the mechanism of bio-instructive materials as medical devices and to inform on the FBR to biomaterials.

Bioinformatic validation and machine learning-based exploration of purine metabolism-related gene signatures in the context of immunotherapeutic strategies for nonspecific orbital inflammation

Background

Nonspecific orbital inflammation (NSOI) represents a perplexing and persistent proliferative inflammatory disorder of idiopathic nature, characterized by a heterogeneous lymphoid infiltration within the orbital region. This condition, marked by the aberrant metabolic activities of its cellular constituents, starkly contrasts with the metabolic equilibrium found in healthy cells. Among the myriad pathways integral to cellular metabolism, purine metabolism emerges as a critical player, providing the building blocks for nucleic acid synthesis, such as DNA and RNA. Despite its significance, the contribution of Purine Metabolism Genes (PMGs) to the pathophysiological landscape of NSOI remains a mystery, highlighting a critical gap in our understanding of the disease's molecular underpinnings.

Methods

To bridge this knowledge gap, our study embarked on an exploratory journey to identify and validate PMGs implicated in NSOI, employing a comprehensive bioinformatics strategy. By intersecting differential gene expression analyses with a curated list of 92 known PMGs, we aimed to pinpoint those with potential roles in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), facilitated a deep dive into the biological functions and pathways associated with these PMGs. Further refinement through Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) enabled the identification of key hub genes and the evaluation of their diagnostic prowess for NSOI. Additionally, the relationship between these hub PMGs and relevant clinical parameters was thoroughly investigated. To corroborate our findings, we analyzed expression data from datasets GSE58331 and GSE105149, focusing on the seven PMGs identified as potentially crucial to NSOI pathology.

Results

Our investigation unveiled seven PMGs (ENTPD1, POLR2K, NPR2, PDE6D, PDE6H, PDE4B, and ALLC) as intimately connected to NSOI. Functional analyses shed light on their involvement in processes such as peroxisome targeting sequence binding, seminiferous tubule development, and ciliary transition zone organization. Importantly, the diagnostic capabilities of these PMGs demonstrated promising efficacy in distinguishing NSOI from non-affected states.

Conclusions

Through rigorous bioinformatics analyses, this study unveils seven PMGs as novel biomarker candidates for NSOI, elucidating their potential roles in the disease's pathogenesis. These discoveries not only enhance our understanding of NSOI at the molecular level but also pave the way for innovative approaches to monitor and study its progression, offering a beacon of hope for individuals afflicted by this enigmatic condition.

Efficient production of butyric acid from lignocellulosic biomass by revealing the mechanisms of Clostridium tyrobutyricum tolerance to phenolic inhibitors

Phenolic compounds (PCs) generated during pretreatment of lignocellulosic biomass severely hinder the biorefinery by Clostridia. As a hyperbutyrate-producing strain, Clostridium tyrobutyricum has excellent tolerance to PCs, but its tolerance mechanism is poorly understood. In this study, a comprehensive transcriptome analysis was applied to elucidate the response of C. tyrobutyricum to four typical PCs. The findings revealed that the expression levels of genes associated with PC reduction, HSPs, and membrane transport were significantly altered under PC stress. Due to PCs being reduced to low-toxicity alcohols/acids by C. tyrobutyricum, enhancing the reduction of PCs by overexpressing reductase genes could enhance the strain's tolerance to PCs. Under 1.0 g/L p-coumaric acid stress, compared with the wild-type strain, ATCC 25755/sdr1 exhibited a 31.2 % increase in butyrate production and a 38.5 % increase in productivity. These insights contribute to the construction of PC-tolerant Clostridia, which holds promise for improving biofuel and chemical production from lignocellulosic biomass.

N6-methyladenosine modification of the mRNA for a key gene in purine nucleotide metabolism regulates virus proliferation in an insect vector

The titer of viruses that persist and propagate in their insect vector must be high enough for transmission yet not harm the insect, but the mechanism of this dynamic balance is unclear. Here, expression of inosine monophosphate dehydrogenase (LsIMPDH), a rate-limiting enzyme for guanosine triphosphate (GTP) synthesis, is shown to be downregulated by increased levels of N6-methyladenosine (m6A) on LsIMPDH mRNA in rice stripe virus (RSV)-infected small brown planthoppers (SBPHs; Laodelphax striatellus), the RSV vector, which decreases GTP content, thus limiting viral proliferation. Moreover, planthopper methyltransferase-like protein 3 (LsMETTL3) and m6A reader protein LsYTHDF3 are found to catalyze and recognize the m6A on LsIMPDH mRNA, respectively, and cooperate in destabilizing LsIMPDH transcripts. Co-silencing assays show that negative regulation of viral proliferation by both LsMETTL3 and LsYTHDF3 is partially dependent on LsIMPDH. This distinct mechanism limits virus replication in an insect vector, providing a potential gene target to block viral transmission.

Exploring the causal role of multiple metabolites on ovarian cancer: a two sample Mendelian randomization study

BACKGROUND

The mechanisms and risk factors underlying ovarian cancer (OC) remain under investigation, making the identification of new prognostic biomarkers and improved predictive factors critically important. Recently, circulating metabolites have shown potential in predicting survival outcomes and may be associated with the pathogenesis of OC. However, research into their genetic determinants is limited, and there are some inadequacies in understanding the distinct subtypes of OC. In this context, we conducted a Mendelian randomization study aiming to provide evidence for the relationship between genetically determined metabolites (GDMs) and the risk of OC and its subtypes.

METHODS

In this study, we consolidated genetic statistical data of GDMs with OC and its subtypes through a genome-wide association study (GWAS) and conducted a two-sample Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method served as the primary approach, with MR-Egger and weighted median methods employed for cross-validation to determine whether a causal relationship exists between the metabolites and OC risk. Moreover, a range of sensitivity analyses were conducted to validate the robustness of the results. MR-Egger intercept, and Cochran's Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. False discovery rate (FDR) correction was applied to validate the findings. We also conducted a reverse MR analysis to validate whether the observed blood metabolite levels were influenced by OC risk. Additionally, metabolic pathway analysis was carried out using the MetaboAnalyst 5.0 software.

RESULTS

In MR analysis, we discovered 18 suggestive causal associations involving 14 known metabolites, 8 metabolites as potential risk factors, and 6 as potential cancer risk reducers. In addition, three significant pathways, "caffeine metabolism," "arginine biosynthesis," and "citrate cycle (TCA cycle)" were associated with the development of mucinous ovarian cancer (MOC). The pathways "caffeine metabolism" and "alpha-linolenic acid metabolism" were associated with the onset of endometrioid ovarian cancer (OCED).

CONCLUSIONS

Our MR analysis revealed both protective and risk-associated metabolites, providing insights into the potential causal relationships between GDMs and the metabolic pathways related to OC and its subtypes. The metabolites that drive OC could be potential candidates for biomarkers.

Cochlear metabolomics, highlighting novel insights of purine metabolic alterations in age-related hearing loss

Aging is an inevitable phase in mammals that leads to health impairments, including hearing loss. Age-related hearing loss (AHL) leads to psychosocial problems and cognitive decline in the elderly. In this study, mean thresholds of auditory brainstem responses (ABR) and distortion-product otoacoustic emissions (DPOAE) increased at multiple frequencies in aged rats (14 months old) compared to young rats (2 months old). Using untargeted ultra-high performance liquid chromatography-mass spectroscopy (LC-MS), we quantified molecular metabolic markers in the cochlea of aged rats with hearing loss. A total of 137 different metabolites were identified in two groups, highlighting several prominent metabolic pathways related to purine metabolism; glycine, serine, and threonine metabolism; arginine and proline metabolism; and pyrimidine metabolism. In addition, the beneficial effects of purine supplementation were demonstrated in a mimetic model of senescent marginal cells (MCs). Overall, altered metabolic profiling is both the cause and manifestation of pathology, and our results suggest that cellular senescence and dysfunctional cochlear metabolism may contribute to the progression of AHL. These findings are seminal in elucidating the pathophysiological mechanisms underlying AHL and serve as a basis for future clinical predictions and interventions in AHL.

Regulation of nucleotide metabolism in cancers and immune disorders

Nucleotides are the foundational elements of life. Proliferative cells acquire nutrients for energy production and the synthesis of macromolecules, including proteins, lipids, and nucleic acids. Nucleotides are continuously replenished through the activation of the nucleotide synthesis pathways. Despite the importance of nucleotides in cell physiology, there is still much to learn about how the purine and pyrimidine synthesis pathways are regulated in response to intracellular and exogenous signals. Over the past decade, evidence has emerged that several signaling pathways [Akt, mechanistic target of rapamycin complex I (mTORC1), RAS, TP53, and Hippo-Yes-associated protein (YAP) signaling] alter nucleotide synthesis activity and influence cell function. Here, we examine the mechanisms by which these signaling networks affect de novo nucleotide synthesis in mammalian cells. We also discuss how these molecular links can be targeted in diseases such as cancers and immune disorders.

Bioaccumulation and metabolic impact of environmental PFAS residue on wild-caught urban wetland tiger snakes (Notechis scutatus)

PFAS contamination of urban waters is widespread but understanding the biological impact of its accumulation is limited to humans and common ecotoxicological model organisms. Here, we combine PFAS exposure and bioaccumulation patterns with whole organism responses and omics-based ecosurveillance methods to investigate the potential impacts of PFAS on a top predator of wetlands, the tiger snake (Notechis scutatus). Tiger snakes (18 male and 17 female) were collected from four wetlands with varying PFAS chemical profiles and concentrations in Perth, Western Australia. Tiger snake livers were tested for 28 known PFAS compounds, and Σ28PFAS in liver tissues ranged between 322 ± 193 μg/kg at the most contaminated site to 1.31 ± 0.86 μg/kg at the least contaminated site. The dominant PFAS compound detected in liver tissues was PFOS. Lower body condition was associated with higher liver PFAS, and male snakes showed signs of high bioaccumulation whereas females showed signs of maternal offloading. Biochemical profiles of snake muscle, fat (adipose tissue), and gonads were analysed using a combination of liquid chromatography triple quadrupole (QqQ) and quadrupole time-of-flight (QToF) mass spectrometry methodologies. Elevated PFAS was associated with enriched energy production and maintenance pathways in the muscle, and had weak associations with energy-related lipids in the fat tissue, and lipids associated with cellular genesis and spermatogenesis in the gonads. These findings demonstrate the bioavailability of urban wetland PFAS in higher-order reptilian predators and suggest a negative impact on snake health and metabolic processes. This research expands on omics-based ecosurveillance tools for informing mechanistic toxicology and contributes to our understanding of the impact of PFAS residue on wildlife health to improve risk management and regulation.

Purine metabolism-related genes and immunization in thyroid eye disease were validated using bioinformatics and machine learning

Thyroid eye disease (TED), an autoimmune inflammatory disorder affecting the orbit, exhibits a range of clinical manifestations. While the disease presentation can vary, cases that adhere to a prototypical pattern typically commence with mild symptoms that subsequently escalate in severity before entering a phase of stabilization. Notably, the metabolic activity of cells implicated in the disease substantially deviates from that of healthy cells, with purine metabolism representing a critical facet of cellular material metabolism by supplying components essential for DNA and RNA synthesis. Nevertheless, the precise involvement of Purine Metabolism Genes (PMGs) in the defensive mechanism against TED remains largely unexplored. The present study employed a bioinformatics approach to identify and validate potential PMGs associated with TED. A curated set of 65 candidate PMGs was utilized to uncover novel PMGs through a combination of differential expression analysis and a PMG dataset. Furthermore, GSEA and GSVA were employed to explore the biological functions and pathways associated with the newly identified PMGs. Subsequently, the Lasso regression and SVM-RFE algorithms were applied to identify hub genes and assess the diagnostic efficacy of the top 10 PMGs in distinguishing TED. Additionally, the relationship between hub PMGs and clinical characteristics was investigated. Finally, the expression levels of the identified ten PMGs were validated using the GSE58331 and GSE105149 datasets. This study revealed ten PMGs related with TED. PRPS2, PFAS, ATIC, NT5C1A, POLR2E, POLR2F, POLR3B, PDE3A, ADSS, and NTPCR are among the PMGs. The biological function investigation revealed their participation in processes such as RNA splicing, purine-containing chemical metabolism, and purine nucleotide metabolism. Furthermore, the diagnostic performance of the 10 PMGs in differentiating TED was encouraging. This study was effective in identifying ten PMGs linked to TED. These findings provide light on potential new biomarkers for TED and open up possibilities for tracking disease development.

Cross talk of tumor protein D52 (TPD52) with KLF9, PKCε, and MicroRNA 223 in ovarian cancer

BACKGROUND

Gynecologic cancers comprise malignancies in the female reproductive organs. Ovarian cancer ranks sixth in terms of incidence rates while seventh in terms of mortality rates. The stage at which ovarian cancer is diagnosed mainly determines the survival outcomes of patients. Various screening approaches are presently employed for diagnosing ovarian cancer; however, these techniques have low accuracy and are non-specific, resulting in high mortality rates of patients due to this disease. Hence, it is crucial to identify improved screening and diagnostic markers to overcome this cancer. This study aimed to find new biomarkers to facilitate the prognosis and diagnosis of ovarian cancer.

METHODS

Bioinformatics approaches were used to predict the tertiary structure and cellular localization along with phylogenetic analysis of TPD52. Its molecular interactions were determined through KEGG analysis, and real-time PCR-based expression analysis was performed to assess its co-expression with another oncogenic cellular pathway (miR-223, KLF9, and PKCε) proteins in ovarian cancer.

RESULTS

Bioinformatics analysis depicted the cytoplasmic localization of TPD52 and the high conservation of its coiled-coil domains. Further study revealed that TPD52 mRNA and miRNA-223 expression was elevated, while the expression of KLF 9 and PKCε was reduced in the blood of ovarian cancer patients. Furthermore, TPD52 and miR-223 expression were upregulated in the early stages of cancer and non-metastatic cancers.

CONCLUSION

TPD52, miR-223, PKCε, and KLF9, can be used as a blood based markers for disease prognosis, metastasis, and treatment response. The study outcomes hold great potential to be translated at the clinical level after further validation on larger cohorts.

Synergistic Responses of Tibetan Sheep Rumen Microbiota, Metabolites, and the Host to the Plateau Environment

Plateau adaptation in animals involves genetic mechanisms as well as coevolutionary mechanisms of the microbiota and metabolome of the animal. Therefore, the characteristics of the rumen microbiome and metabolome, transcriptome, and serum metabolome of Tibetan sheep at different altitudes (4500 m, 3500 m, and 2500 m) were analyzed. The results showed that the rumen differential metabolites at 3500 m and 4500 m were mainly enriched in amino acid metabolism, lipid metabolism, and carbohydrate metabolism, and there was a significant correlation with microbiota. The differentially expressed genes and metabolites at middle and high altitudes were coenriched in asthma, arachidonic acid metabolism, and butanoate and propanoate metabolism. In addition, the serum differential metabolites at 3500 m and 4500 m were mainly enriched in amino acid metabolism, lipid metabolism, and metabolism of xenobiotics by cytochrome P450, and they were also related to microbiota. Further analysis revealed that rumen metabolites accounted for 7.65% of serum metabolites. These common metabolites were mainly enriched in metabolic pathways and were significantly correlated with host genes (p < 0.05). This study found that microbiota, metabolites, and epithelial genes were coenriched in pathways related to lipid metabolism, energy metabolism, and immune metabolism, which may be involved in the regulation of Tibetan sheep adaptation to plateau environmental changes.

Development and validation of prognostic index based on purine metabolism genes in patients with bladder cancer

Background

Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and is associated with significant morbidity and mortality worldwide. Dysregulation of tumor metabolic pathways is closely linked to the initiation and proliferation of BLCA. Tumor cells exhibit distinct metabolic activities compared to normal cells, and the purine metabolism pathway, responsible for providing essential components for DNA and RNA synthesis, is believed to play a crucial role. However, the precise involvement of Purine Metabolism Genes (PMGs) in the defense mechanism against BLCA remains elusive.

Methods

The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of PMGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and PMGs, unraveling their functional relevance and potential implications in BLCA.

Results

PMGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including CLDN6, CES1, SOST, SPRR2A, MYBPH, CGB5, and KRT1, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CRTAC1 was identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles.

Conclusion

PMGs have been implicated in the etiology and progression of bladder cancer (BLCA). Prognostic models corresponding to this malignancy aid in the accurate prediction of patient outcomes. Notably, exploring the potential therapeutic targets within the tumor microenvironment (TME) such as PMGs and immune cell infiltration holds promise for effective BLCA management, albeit necessitating further research. Moreover, the identification of a gene signature associated with purine Metabolism presents a credible and alternative approach for predicting BLCA, signifying a burgeoning avenue for targeted therapeutic investigations in the field of BLCA.

Antibiotic-induced gut microbiota dysbiosis has a functional impact on purine metabolism

BACKGROUND

Dysbiosis of the gut microbiota is closely linked to hyperuricemia. However, the effect of the microbiome on uric acid (UA) metabolism remains unclear. This study aimed to explore the mechanisms through which microbiomes affect UA metabolism with the hypothesis that modifying the intestinal microbiota influences the development of hyperuricemia.

RESULTS

We proposed combining an antibiotic strategy with protein-protein interaction analysis to test this hypothesis. The data demonstrated that antibiotics altered the composition of gut microbiota as UA increased, and that the spectrum of the antibiotic was connected to the purine salvage pathway. The antibiotic-elevated UA concentration was dependent on the increase in microbiomes that code for the proteins involved in purine metabolism, and was paralleled by the depletion of bacteria-coding enzymes required for the purine salvage pathway. On the contrary, the microbiota with abundant purine salvage proteins decreased hyperuricemia. We also found that the antibiotic-increased microbiota coincided with a higher relative abundance of bacteria in hyperuricemia mice.

CONCLUSIONS

An antibiotic strategy combined with the prediction of microbiome bacterial function presents a feasible method for defining the key bacteria involved in hyperuricemia. Our investigations discovered that the core microbiomes of hyperuricemia may be related to the gut microbiota that enriches purine metabolism related-proteins. However, the bacteria that enrich the purine salvage-proteins may be a probiotic for decreasing urate, and are more likely to be killed by antibiotics. Therefore, the purine salvage pathway may be a potential target for the treatment of both hyperuricemia and antibiotic resistance.

Anti-Hypercholesterolemia Effects of Edible Seaweed Extracts and Metabolomic Changes in Hep-G2 and Caco-2 Cell Lines

Hypercholesterolemia is a major risk for the development of cardiovascular diseases (CVDs), the main cause of mortality worldwide, and it is characterized by high levels of circulating cholesterol. The drugs currently available for hypercholesterolemia control have several side effects, so it is necessary to develop new effective and safer therapies. Seaweeds serve as sources of several bioactive compounds with claimed beneficial effects. Eisenia bicyclis (Aramé) and Porphyra tenera (Nori) are edible seaweeds that were previously recognized as rich in bioactive compounds. In the present study, we aim to evaluate the anti-hypercholesterolemia effect of these two seaweed extracts and their health potential. Both extracts, but more efficiently Aramé extract, have liver 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) inhibitory activity as well as the capability to reduce approximately 30% of cholesterol permeation through human Caco-2 cells by simulating the intestinal lining, which is a target for hypercholesterolemia treatments. An untargeted metabolomic assay on human intestinal Caco-2 and liver Hep-G2 cell lines exposed to Aramé and Nori extracts revealed changes in the cells' metabolism, indicating the extracts' health beneficial effects. The metabolic pathways affected by exposure to both extracts were associated with lipid metabolism, such as phospholipids, and fatty acid metabolism, amino acid pathways, cofactors, vitamins, and cellular respiration metabolism. The effects were more profound in Aramé-treated cells, but they were also observed in Nori-exposed cells. The metabolite modifications were associated with the protection against CVDs and other diseases and to the improvement of the cells' oxidative stress tolerance. The results obtained for the anti-hypercholesterolemia properties, in addition to the revelation of the positive impact on cell metabolism, offer an important contribution for further evaluation of these seaweed extracts as functional foods or for CVD prevention.

LncRNA UCA1 Participates in De Novo Synthesis of Guanine Nucleotides in Bladder Cancer by Recruiting TWIST1 to Increase IMPDH1/2

Metabolic dysregulation has been identified as one of the hallmarks of cancer biology. Based on metabolic heterogeneity between bladder cancer tissues and adjacent tissues, we discovered several potential driving factors for the bladder cancer occurrence and development. Metabolic genomics showed purine metabolism pathway was mainly accumulated in bladder cancer. Long noncoding RNA urothelial carcinoma-associated 1 (LncRNA UCA1) is a potential tumor biomarker for bladder cancer diagnosis and prognosis, and it increases bladder cancer cell proliferation, migration, and invasion via the glycolysis pathway. However, whether UCA1 plays a role in purine metabolism in bladder cancer is unknown. Our findings showed that UCA1 could increase the transcription activity of guanine nucleotide de novo synthesis rate limiting enzyme inosine monophosphate dehydrogenase 1 (IMPDH1) and inosine monophosphate dehydrogenase 2 (IMPDH2), triggering in guanine nucleotide metabolic reprogramming. This process was achieved by UCA1 recruiting the transcription factor TWIST1 which binds to the IMPDH1and IMPDH2 promoter region. Increased guanine nucleotide synthesis pathway products stimulate RNA polymerase-dependent production of pre-ribosomal RNA and GTPase activity in bladder cancer cells, hence increasing bladder cancer cell proliferation, migration, and invasion. We have demonstrated that UCA1 regulates IMPDH1/2-mediated guanine nucleotide production via TWIST1, providing additional evidence of metabolic reprogramming.

Investigation on the immunotoxicity induced by Emamectin benzoate on THP-1 macrophages based on metabolomics analysis

Emamectin benzoate (EMB) is an insecticide extensively used in agricultural area. Assessing the toxic effects of EMB in mammals or humans and its endogenous metabolites alteration are the appropriate means of evaluating its risks to human health. In the study, THP-1 macrophage, a human immune model, was applied to investigate the immunotoxicity of EMB. A global metabolomics approach was developed to analyze metabolic perturbation on macrophages and discover the potential biomarkers of EMB-induced immunotoxicity. The results indicated that EMB could inhibit immune functions of macrophages. Based on metabolomics analysis, our results illustrated that EMB caused significant alterations in metabolic profiles on macrophages. 22 biomarkers associated with immune response were screened by pattern recognition and multivariate statistical analysis. Furthermore, pathway analysis identified purine metabolism was the most relevant pathway in the metabolic process and the abnormal conversion of AMP to xanthosine regulated by NT5E might be a potential mechanism of immunotoxicity induced by EMB. Our study provides important insights for understanding and underlying mechanism of immunotoxicity exposed to EMB.

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

Peritoneal cancers present significant clinical challenges with poor prognosis. Understanding the role of cancer cell metabolism and cancer-promoting metabolites in peritoneal cancers can provide new insights into the mechanisms that drive tumor progression and can identify novel therapeutic targets and biomarkers for early detection, prognosis, and treatment response. Cancer cells dynamically reprogram their metabolism to facilitate tumor growth and overcome metabolic stress, with cancer-promoting metabolites such as kynurenines, lactate, and sphingosine-1-phosphate promoting cell proliferation, angiogenesis, and immune evasion. Targeting cancer-promoting metabolites could also lead to the development of effective combinatorial and adjuvant therapies involving metabolic inhibitors for the treatment of peritoneal cancers. With the observed metabolomic heterogeneity in cancer patients, defining peritoneal cancer metabolome and cancer-promoting metabolites holds great promise for improving outcomes for patients with peritoneal tumors and advancing the field of precision cancer medicine. This review provides an overview of the metabolic signatures of peritoneal cancer cells, explores the role of cancer-promoting metabolites as potential therapeutic targets, and discusses the implications for advancing precision cancer medicine in peritoneal cancers.

Comprehensive Analysis of Purine-Metabolism-Related Gene Signature for Predicting Ovarian Cancer Prognosis, Immune Landscape, and Potential Treatment Options

Purine metabolism is an important branch of metabolic reprogramming and has received increasing attention in cancer research. Ovarian cancer is an extremely dangerous gynecologic malignancy for which there are no adequate tools to predict prognostic risk. Here, we identified a prognostic signature consisting of nine genes related to purine metabolism, including ACSM1, CACNA1C, EPHA4, TPM3, PDIA4, JUNB, EXOSC4, TRPM2, and CXCL9. The risk groups defined by the signature are able to distinguish the prognostic risk and the immune landscape of patients. In particular, the risk scores offer promising personalized drug options. By combining risk scores with clinical characteristics, we have created a more detailed composite nomogram that allows for a more complete and individualized prediction of prognosis. In addition, we demonstrated metabolic differences between platinum-resistant and platinum-sensitive ovarian cancer cells. In summary, we have performed the first comprehensive analysis of genes related to purine metabolism in ovarian cancer patients and created a feasible prognostic signature that will aid in risk prediction and support personalized medicine.

Deregulated Metabolic Pathways in Ovarian Cancer: Cause and Consequence

Ovarian cancers are tumors that originate from the different cells of the ovary and account for almost 4% of all the cancers in women globally. More than 30 types of tumors have been identified based on the cellular origins. Epithelial ovarian cancer (EOC) is the most common and lethal type of ovarian cancer which can be further divided into high-grade serous, low-grade serous, endometrioid, clear cell, and mucinous carcinoma. Ovarian carcinogenesis has been long attributed to endometriosis which is a chronic inflammation of the reproductive tract leading to progressive accumulation of mutations. Due to the advent of multi-omics datasets, the consequences of somatic mutations and their role in altered tumor metabolism has been well elucidated. Several oncogenes and tumor suppressor genes have been implicated in the progression of ovarian cancer. In this review, we highlight the genetic alterations undergone by the key oncogenes and tumor suppressor genes responsible for the development of ovarian cancer. We also summarize the role of these oncogenes and tumor suppressor genes and their association with a deregulated network of fatty acid, glycolysis, tricarboxylic acid and amino acid metabolism in ovarian cancers. Identification of genomic and metabolic circuits will be useful in clinical stratification of patients with complex etiologies and in identifying drug targets for personalized therapies against cancer.