Evidence map›Paper›PMID 41382155›Full record

ArticleGenome medicine2025

Collateral metabolic vulnerabilities unveiled by loss of isozyme diversity in breast cancer.

Rui Ding, Tian-Jian Yu, Yi-Zhou Jiang, Yi Xiao, Zhi-Ming Shao

Abstract read
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Rui Ding *Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Tian-Jian Yu *Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Yi-Zhou JiangKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. yizhoujiang@fudan.edu.cn.
Yi XiaoKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. yixiao11@fudan.edu.cn.
Zhi-Ming ShaoKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. zhimingshao@fudan.edu.cn.

Funding

National Natural Science Foundation of China 82202883National Natural Science Foundation of China 92159301, 82341003the Seed Program for Research and Translation of Innovative Medical Technologies of Shanghai Municipal Commission of Health 2024ZZ2023
6 · The paper itself

Abstract

backgroundLoss of isozyme diversity (LID) refers to the selective dependency on a single isozyme following the functional collapse of its redundant counterparts, uncovering a metabolic vulnerability. This metabolic liability establishes LID as a novel framework for precision targeting strategy in cancer therapy.

methodsWe integrated a large-scale breast cancer multi-omics cohort to systematically delineate isozyme expression patterns and identify therapeutically promising LID targets across intrinsic molecular subtypes. Genomic and epigenetic data were employed to decipher the underlying causes of LID. Subsequent experiments were conducted to validate the collateral metabolic vulnerabilities arising from identified LID targets and investigate the associated mechanisms.

resultsOur analysis delineated the isozyme utilization patterns for metabolic reactions in breast cancer, which revealed widespread and significant LID phenomena. We further decoded the enrichment characteristics of these LID reactions and identified a set of potential clinically relevant LID targets across different subtypes. Further investigation revealed that copy number loss and epigenetic silencing predominantly drive these LIDs, as exemplified by luminal subtype-specific N-myristoyltransferase 2 (NMT2) deficiency caused by hypermethylation. Mechanistic studies demonstrated that NMT2 deficiency confers synthetic lethality with NMT1 inhibition, potentially through impaired myristoylation of the oncogenic effector FMR1 autosomal homolog 2 (FXR2). These findings underscored the potential of NMT inhibitors as viable therapeutic strategies for NMT2-deficient tumors.

conclusionsIn conclusion, this study constructed a comprehensive LID landscape across all breast cancer subtypes, advancing precision oncology through innovative metabolic targeting approaches.

Indexed as

Breast NeoplasmsAcyltransferasesDNA MethylationEpigenesis, GeneticFemaleGene Expression Regulation, NeoplasticHumansIsoenzymesAcyltransferasesIsoenzymesBreast cancerIsozymeLoss of isozyme diversitySynthetic lethalityTumor metabolism

Identifiers

PMID41382155
PMCPMC12817777

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