bims-aspsyn 2025-08-24 papers

bioRxiv. 2025 Aug 12. pii: 2025.08.10.669191. [Epub ahead of print]

The mevalonate pathway couples lipid metabolism to amino acid synthesis via ubiquinone-dependent redox control.

Thi Thinh Nguyen, Mohit Bansal, Jane Ding, Sunil Sudarshan, Han-Fei Ding.

The mevalonate pathway produces sterols and isoprenoids that support cancer cell growth, yet its broader metabolic functions remain incompletely defined. Here, we show that this pathway sustains amino acid biosynthesis by promoting mitochondrial NAD⁺ regeneration through ubiquinone-dependent electron transport. Statin-mediated inhibition of the mevalonate pathway impairs oxidative phosphorylation, lowers the NAD⁺/NADH ratio, and suppresses de novo serine and aspartate synthesis, thereby activating the GCN2-eIF2α-ATF4 amino acid deprivation response. The resulting depletion of serine-derived glycine and one-carbon units, together with reduced aspartate availability, limits purine and pyrimidine nucleotide production. Expression of the bacterial NADH oxidase LbNOX or the alternative oxidase AOX restores NAD⁺ levels and rescues statin-induced growth inhibition. These findings suggest that impaired NAD⁺ regeneration is a key mechanism contributing to the anti-proliferative activity of statins, linking the mevalonate pathway to mitochondrial electron transport- dependent control of amino acid metabolism.
Significance: This study identifies the mevalonate pathway as a regulator of amino acid biosynthesis through mitochondrial electron transport-dependent NAD⁺ regeneration and reveals redox disruption as a key mechanism contributing to the anti-proliferative effects of statins.

DOI: https://doi.org/10.1101/2025.08.10.669191

Cell Death Discov. 2025 Aug 19. 11(1): 390

The ATF4-glutamine axis: a central node in cancer metabolism, stress adaptation, and therapeutic targeting.

Xing Yan, Changhong Liu.

At the center of tumor(neoplasm) metabolic adaptation lies activating transcription factor 4 (ATF4), a key regulator that orchestrates Glutamine (Gln) uptake, utilization, and redox balance under conditions of nutrient deprivation and oxidative stress. This review explores how ATF4 integrates environmental and cellular stress signals to drive Gln metabolic processes, enabling tumor survival, metabolic reprogramming, and immune evasion. The ATF4-Gln axis emerges as a pivotal vulnerability in cancer metabolic processes. Preclinical studies of small-molecule inhibitors and synthetic derivatives disrupting this pathway show promising results. Understanding the intricate interplay between ATF4, Gln metabolic processes, and cancer progression provides valuable insights for novel therapeutic strategies. Future research must address tumor heterogeneity and metabolic flexibility to fully harness the potential of ATF4-centered therapies. However, challenges such as off-target effects of ATF4 inhibitors and metabolic plasticity in tumors remain critical barriers. Future studies integrating multi-omics approaches and AI-driven drug discovery are warranted to overcome these hurdles.

DOI: https://doi.org/10.1038/s41420-025-02683-7

Eur J Drug Metab Pharmacokinet. 2025 Aug 19.

PEGylated Asparaginase in Children with Acute Lymphoblastic Leukemia Treated within the AIEOP-BFM ALL 2009 Trial: Population Pharmacokinetics and Drug Exposure.

AIEOP-BFM ALL 2009 Asparaginase Working Party

BACKGROUND AND OBJECTIVES: Focusing on pharmacokinetic-derived individual dose-intensity parameter values (DIPs), we modeled the pharmacokinetics of polyethylene glycol-conjugated asparaginase (PEG-ASNase) in all treatment phases and different trial groups of AIEOP-BFM ALL 2009.
METHODS: Children with acute lymphoblastic leukemia received 1-10 weekly or biweekly repetitive doses (2500 U/m2/dose intravenously). A population pharmacokinetic (popPK) model was extended to all phases to describe the pharmacokinetics and the impact of anti-PEG- and anti-asparaginase-antibodies in the German/Czech group (2535 patients, aspartic acid β-hydroxamate (AHA) assay) and validated the model in the Italian group (1603 patients, medac asparaginase activity test (MAAT) assay). DIPs, also for 279 Australian patients, were derived. Allergic reactions and silent inactivation were exclusion criteria.
RESULTS: Treatment phase dependency and drug accumulation were modeled by up to -60% lower clearance and -30% lower volume of distribution compared with the first administration in induction. Apart from the impact of high preexisting anti-PEG-antibody levels on clearance in induction, no further impact of antibodies was identified. Independent modelling of the Italian data (conversion factor 1.23/1.42: ≤ 600/> 600 U/L) confirmed the model. Time above 100 U/L correlated to the time-interval between the first and last dose within a phase, whereas the area under the concentration-time curve (AUC) was linked to the cumulative dose showing higher drug accumulation after repetitive doses than expected by linear extrapolation.
CONCLUSION: A popPK model was adapted to all phases and different trial groups integrating asparaginase antibodies as long as they did not lead to silent inactivation or allergic reaction. The model allows strategic development of trial schedules and the calculation of intended or realized individual DIPs.
TRIAL REGISTRATION: EU clinical trails register; European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) Number 2007-004270-43.

DOI: https://doi.org/10.1007/s13318-025-00962-3