Formate overflow drives toxic folate trapping in MTHFD1 inhibited cancer cells

Nature Metabolism, Год журнала: 2023, Номер 5(4), С. 642 - 659

Опубликована: Апрель 3, 2023

Abstract Cancer cells fuel their increased need for nucleotide supply by upregulating one-carbon (1C) metabolism, including the enzymes methylenetetrahydrofolate dehydrogenase–cyclohydrolase 1 and 2 (MTHFD1 MTHFD2). TH9619 is a potent inhibitor of dehydrogenase cyclohydrolase activities in both MTHFD1 MTHFD2, selectively kills cancer cells. Here, we reveal that, cells, targets nuclear MTHFD2 but does not inhibit mitochondrial MTHFD2. Hence, overflow formate from mitochondria continues presence TH9619. inhibits activity occurring downstream release, leading to accumulation 10-formyl-tetrahydrofolate, which term ‘folate trap’. This results thymidylate depletion death MTHFD2-expressing previously uncharacterized folate trapping mechanism exacerbated physiological hypoxanthine levels that block de novo purine synthesis pathway, additionally prevent 10-formyl-tetrahydrofolate consumption synthesis. The described here differs other MTHFD1/2 inhibitors antifolates. Thus, our findings uncover an approach attack regulatory 1C metabolism.

Язык: Английский

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Nanomedicines Targeting Metabolic Pathways in the Tumor Microenvironment: Future Perspectives and the Role of AI

Metabolites, Год журнала: 2025, Номер 15(3), С. 201 - 201

Опубликована: Март 13, 2025

Background: Tumor cells engage in continuous self-replication by utilizing a large number of resources and capabilities, typically within an aberrant metabolic regulatory network to meet their own demands. This dysregulation leads the formation tumor microenvironment (TME) most solid tumors. Nanomedicines, due unique physicochemical properties, can achieve passive targeting certain tumors through enhanced permeability retention (EPR) effect, or active deliberate design optimization, resulting accumulation TME. The use nanomedicines target critical pathways holds significant promise. However, requires careful selection relevant drugs materials, taking into account multiple factors. traditional trial-and-error process is relatively inefficient. Artificial intelligence (AI) integrate big data evaluate delivery efficiency nanomedicines, thereby assisting nanodrugs. Methods: We have conducted detailed review key papers from databases, such as ScienceDirect, Scopus, Wiley, Web Science, PubMed, focusing on reprogramming, mechanisms action development metabolism, application AI empowering nanomedicines. integrated content present current status research metabolism potential future directions this field. Results: Nanomedicines possess excellent TME which be utilized disrupt cells, including glycolysis, lipid amino acid nucleotide metabolism. disruption selective killing disturbance Extensive has demonstrated that AI-driven methodologies revolutionized nanomedicine development, while concurrently enabling precise identification molecular regulators involved oncogenic reprogramming pathways, catalyzing transformative innovations targeted cancer therapeutics. Conclusions: great Additionally, will accelerate discovery metabolism-related targets, empower optimization help minimize toxicity, providing new paradigm for development.

Язык: Английский

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Proteomic Profiles of Neutrophils from Behcet’s Uveitis Patients and their Sex Differences

Inflammation, Год журнала: 2025, Номер unknown

Опубликована: Апрель 22, 2025

Язык: Английский

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Role of MTH1 in Oxidative Stress and Therapeutic Targeting of Cancer

Redox Biology, Год журнала: 2024, Номер 77, С. 103394 - 103394

Опубликована: Окт. 11, 2024

Cancer cells maintain high levels of reactive oxygen species (ROS) to drive their growth, but ROS can trigger cell death through oxidative stress and DNA damage. To survive enhanced levels, cancer activate antioxidant defenses. One such defense is MTH1, an enzyme that prevents the incorporation oxidized nucleotides into DNA, thus preventing damage allowing proliferate. MTH1 are often elevated in many cancers, thus, inhibiting attractive strategy for suppressing tumor growth metastasis. Targeted inhibition induce cells, exploiting vulnerability selectively targeting them destruction. Targeting promising treatment because normal have lower less dependent on these pathways, making approach both effective specific cancer. This review aims investigate potential as a therapeutic target, especially treatment, offering detailed insights its structure, function, role disease progression. We also discussed various inhibitors been developed though effectiveness varies. In addition, this provide deeper mechanistic prevention management diseases.

Язык: Английский

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The roles of lncRNAs in the development of drug resistance of oral cancers

Biomedicine & Pharmacotherapy, Год журнала: 2024, Номер 180, С. 117458 - 117458

Опубликована: Окт. 15, 2024

Язык: Английский

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Epigenetic–Metabolic Interplay in the DNA Damage Response and Therapeutic Resistance of Breast Cancer

Cancer Research, Год журнала: 2023, Номер 83(5), С. 657 - 666

Опубликована: Янв. 18, 2023

Abstract Therapy resistance is imposing a daunting challenge on effective clinical management of breast cancer. Although the development to drugs multifaceted, reprogramming energy metabolism pathways emerging as central but heterogenous regulator this therapeutic challenge. Metabolic heterogeneity in cancer cells intricately associated with alterations different signaling networks and activation DNA damage response pathways. Here we consider how dynamic metabolic milieu regulates their repair ability ultimately contribute therapy resistance. Diverse epigenetic regulators are crucial remodeling landscape This epigenetic–metabolic interplay profoundly affects genomic stability well genotoxic therapies. These observations identify defining mechanisms epigenetics–metabolism–DNA axis that can be critical for devising novel, targeted approaches could sensitize conventional treatment strategies.

Язык: Английский

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Understanding the interplay between dNTP metabolism and genome stability in cancer

Disease Models & Mechanisms, Год журнала: 2024, Номер 17(8)

Опубликована: Авг. 1, 2024

ABSTRACT The size and composition of the intracellular DNA precursor pool is integral to maintenance genome stability, this relationship fundamental our understanding cancer. Key aspects carcinogenesis, including elevated mutation rates induction certain types damage in cancer cells, can be linked disturbances deoxynucleoside triphosphate (dNTP) pools. Furthermore, approaches treat heavily exploit metabolic interplay between dNTP pool, with a long-standing example being use antimetabolite-based therapies, strategy continues show promise development new targeted therapies. In Review, we compile current knowledge on both causes consequences perturbations together their impact stability. We outline several outstanding questions remaining field, such as role catabolism stability expansion. Importantly, detail how mechanistic these processes utilised aim providing better informed treatment options patients

Язык: Английский

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A DNA damage-amplifying nanoagent for cancer treatment via two-way regulation of redox dyshomeostasis and downregulation of tetrahydrofolate

International Journal of Biological Macromolecules, Год журнала: 2024, Номер 277, С. 134276 - 134276

Опубликована: Окт. 1, 2024

Язык: Английский

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Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma

Frontiers in Genetics, Год журнала: 2025, Номер 15

Опубликована: Янв. 8, 2025

Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in world. Nucleotide metabolic processes are critical for cancer development, progression, alteration microenvironment. However, effect nucleotide metabolism on LUAD remains to be thoroughly investigated. Transcriptomic clinical data were downloaded organized from TCGA GEO databases. Genes related Msigdb database. associated prognosis identified using univariate COX analysis, prognostic risk model was constructed machine learning combination Lasso + Stepcox. The model's predictive validity evaluated KM survival timeROC curves. Based model, patients classified into different subtypes, differences between subtypes explored terms genomic mutations, functional enrichment, immune characteristics, immunotherapy responses. Finally, key gene SNRPA screened, series vitro experiments performed cell lines explore role LUAD. could accurately categorized based metabolism-related score (NMBRS). There significant NMBRS showed high accuracy predicting patients. In addition, mutation enrichment exhibited anti-tumor profiles. Importantly, can used predict responsiveness immunotherapy. results cellular indicate that plays an important development progression lung adenocarcinoma. This study comprehensively reveals value application A signature genes predicted patients, this as guide

Язык: Английский

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Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke

Frontiers in Immunology, Год журнала: 2025, Номер 16

Опубликована: Март 26, 2025

Background Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed identify metabolism-related genes associated with IS explore their roles in disease mechanisms for new diagnostic therapeutic strategies. Methods gene expression data were sourced from the GEO database. Differential analysis weighted co-expression network (WGCNA) conducted R, intersecting results genes. Functional enrichment connectivity map (cMAP) analyses identified key potential agents. Core immune-related determined using LASSO regression, SVM-RFE, Random Forest algorithms. Immune cell infiltration levels correlations analyzed via CIBERSORT. Single-cell RNA sequencing (scRNA-seq) molecular docking assessed expression, localization, gene-drug binding. In vivo experiments validated core expression. Results Thirty-three candidate identified, mainly involved immune inflammatory responses. CFL1, HMCES , GIMAP1 emerged as genes, showing high potential. cMAP indicated these drug targets. scRNA-seq clarified confirmed strong significant IS. Conclusion underscores role IS, identifying biomarkers targets, providing insights diagnosis therapy development.

Язык: Английский

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