Evidence map›Paper›PMID 39973065›Full record

ReviewProtein & cell2025

Amino acid metabolism in breast cancer: pathogenic drivers and therapeutic opportunities.

Yawen Liu, Xiangyun Zong, Patricia Altea-Manzano, Jie Fu

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yawen LiuDepartment of Radiation Oncology, Shanghai Sixth People's Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.ORCID 0000-0001-8544-5006
Xiangyun ZongDepartment of Breast Surgery, Shanghai Sixth People's Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.ORCID 0000-0002-8673-9003
Patricia Altea-ManzanoAndalusian Molecular Biology and Regenerative Medicine Centre (CABIMER), Universidad de Sevilla-CSIC-Universidad Pablo de Olavide, Seville 41004, Spain.ORCID 0000-0002-7075-2051
Jie FuDepartment of Radiation Oncology, Shanghai Sixth People's Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.ORCID 0000-0002-3183-453X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Amino AcidsBreast NeoplasmsFemaleHumansAmino Acidsamino acid metabolismbreast cancercancer therapymetabolic reprogrammingpersonalized medicine

Identifiers

PMID39973065
PMCPMC12275100

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.