Evidence map›Paper›PMID 42418320›Full record

ArticleCell reports2026

Distinct metabolic dependency on BCAA defines cancer stemness and malignancy in human triple-negative breast cancer.

Kenkyo Matsuura, Ririko Shinonaga, Mizuki Yamamoto, Yoshiki Yamamoto, Hsin Chen, Ayaka Maeno, Kayo Okuda, Haruki Inoue, Sota Imotani, John Glushka and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Kenkyo MatsuuraDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan.
Ririko ShinonagaDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan; Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan.
Mizuki YamamotoInstitute of Medical Sciences, The University of Tokyo, Tokyo, Japan.
Yoshiki YamamotoDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan; Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan.
Hsin ChenDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan; Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Ayaka MaenoInstitute for Chemical Research, Kyoto University, Kyoto, Japan.
Kayo OkudaHacarus Inc., Kyoto, Japan.
Haruki InoueHacarus Inc., Kyoto, Japan.
Sota ImotaniHacarus Inc., Kyoto, Japan.
John GlushkaComplex Carbohydrate Research Center, The University of Georgia, Athens, GA, USA.
Koji MikiDepartment of Energy and Hydrocarbon Chemistry, Graduate School of Engineering, Kyoto University, Kyoto, Japan.
Yukako WatanabeDepartment of Breast Surgery, School of Medicine, International University of Health and Welfare, Chiba, Japan.
Mamoru TakadaDepartment of General Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
Hironori KajiInstitute for Chemical Research, Kyoto University, Kyoto, Japan.
Jun-Ichiro InoueThe University of Tokyo Pandemic preparedness, Infection and Advanced Research Center (UTOPIA), Tokyo, Japan.
Ayuna HattoriDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan.
Hiromi ImamuraGraduate School of Biostudies, Kyoto University, Kyoto, Japan; Organization for Research Initiatives, Yamaguchi University, Yamaguchi, Japan.
Takahiro ItoDivision of Cell Fate Dynamics and Therapeutics, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan. Electronic address: takahiro.ito@infront.kyoto-u.ac.jp.

Funding

National Metabolomics Data Repository - nextgen Metabolomics WorkbenchU2CDK119886 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2018 to 2021
$12.7M
Biomedical Data Commons Workbench (BDCW)OT2OD030544 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2020 to 2024
$3.2M
NIDDK NIH HHS U2C DK119886NIH HHS OT2 OD030544
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) lacks effective molecularly targeted therapies. Here, we identify branched-chain amino acid (BCAA) metabolism as a selective vulnerability in human TNBC, particularly in the claudin-low subtype. TNBC cells show greater dependence on BCAAs than other breast cancer subtypes, and intracellular BCAA levels are heterogeneous within tumors in vivo. Cells with high BCAA levels exhibit enhanced sphere formation and cancer stem cell potential in xenograft models. BCAT1, a cytoplasmic BCAA aminotransferase, is upregulated in claudin-low TNBC and enables tumor growth by promoting BCAA production from branched-chain ketoacids. BCAT1 knockdown impairs TNBC growth in vivo, and high BCAT1 expression predicts poor prognosis in patient cohorts. Conversely, BCAA catabolism via the BCKDH complex is suppressed in TNBC, and reactivation of BCKDH by BCKDK knockout blocks clonogenic growth. These findings reveal BCAA metabolic balance as a key regulator of TNBC stemness and malignancy.

Indexed as

Amino Acids, Branched-ChainNeoplastic Stem CellsTriple Negative Breast NeoplasmsAnimalsCell Line, TumorCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansMetabolic ReprogrammingMiceTransaminasesAmino Acids, Branched-ChainBCAT1 protein, humanTransaminasesbranched-chain amino acidclaudin-lowCP: cancermetabolic vulnerabilitymetabolite imagingTNBC

Identifiers

PMID42418320
PMCPMC13477800

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.