ReviewProtein & cell2025
Amino acid metabolism in breast cancer: pathogenic drivers and therapeutic opportunities.
Review in Protein & cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Multidimensional molecular mechanisms of drug resistance in breast cancer: Implications for clinical decision‑making and treatment strategies (Review).Oncology reports · 2026Review
- Endogenous metabolite signaling orchestrates tumor immune evasion.Cell insight · 2026Review
- Tanshinone IIA in breast cancer: Molecular mechanisms, structural optimization and translational challenges (Review).Oncology reports · 2026Review
- Metabolomics in breast cancer: insights into treatment responses, disease progression, and prognostic assessment.Metabolomics : Official journal of the Metabolomic Society · 2026Review
- Multi-Omics Analysis Reveals Differentially Expressed Proteins and Metabolites in Malignant Pleural Effusion.Thoracic cancer · 2026Article
- Overview of glutamine metabolism in stromal components of the tumor microenvironment and potential anti-tumor therapies.Genes & diseases · 2026Review
- Colorimetric detection of amino acids enabled by functional nanomaterials: mechanisms, performance evaluation, and translational perspectives.Mikrochimica acta · 2026Review
- Enhanced glycolysis and nicotinamide metabolism in HPV-positive head and neck cancer.Scientific reports · 2025Article
- Decoding breast cancer: insights into molecular pathways & therapeutic approaches.Discover oncology · 2025Review
- Recent progress in serine metabolism reprogramming in tumors and strategies for serine deprivation.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amino acid metabolism plays a critical role in the progression and development of breast cancer. Cancer cells, including those in breast cancer, reprogram amino acid metabolism to meet the demands of rapid proliferation, survival, and immune evasion. This includes alterations in the uptake and utilization of amino acids, such as glutamine, serine, glycine, and arginine, which provide essential building blocks for biosynthesis, energy production, and redox homeostasis. Notably, the metabolic phenotypes of breast cancer cells vary across molecular subtypes and disease stages, emphasizing the need for patient stratification and personalized therapeutic strategies. Advances in multi-level diagnostics, including phenotyping and predictive tools, such as AI-based analysis and body fluid profiling, have highlighted the potential for tailoring treatments to individual metabolic profiles. Enzymes, such as glutaminase and serine hydroxymethyltransferase, often upregulated in breast cancer, represent promising therapeutic targets. Understanding the interplay between amino acid metabolism and breast cancer biology, alongside the integration of personalized medicine approaches, can uncover novel insights into tumor progression and guide the development of precision therapies. This review explores the metabolic pathways of amino acids in breast cancer, with a focus on their implications for personalized treatment strategies.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.