Evidence map›Paper›PMID 41786683›Full record

ReviewCell death & disease2026

Lactylation as a metabolic-epigenetic switch in cancer: dual roles in cell death resistance and therapeutic vulnerability.

Chengjiao Yang, Ruici Yang, Binbin Zheng, Hongxiao Jiang, Xianteng Wang, Weiren Huang

Abstract readReview
In one paragraph

Review in Cell death & disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
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

6 authors.

Chengjiao YangDepartment of Urology, Shenzhen Institute of Translational Medicine, Medical Innovation Technology Transformation Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Institute for Advanced Study, Synthetic Biology Research Center, International Cancer Center of Shenzhen University, Shenzhen, Guangdong Province, China.ORCID http://orcid.org/0009-0007-7289-7143
Ruici YangShenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, State Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China.
Binbin ZhengDepartment of Urology, Shenzhen Institute of Translational Medicine, Medical Innovation Technology Transformation Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Institute for Advanced Study, Synthetic Biology Research Center, International Cancer Center of Shenzhen University, Shenzhen, Guangdong Province, China.
Hongxiao JiangDepartment of Urology, Shenzhen Institute of Translational Medicine, Medical Innovation Technology Transformation Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Institute for Advanced Study, Synthetic Biology Research Center, International Cancer Center of Shenzhen University, Shenzhen, Guangdong Province, China.
Xianteng WangMolecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, Guangdong Province, China. wangxt87@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-5170-6973
Weiren HuangDepartment of Urology, Shenzhen Institute of Translational Medicine, Medical Innovation Technology Transformation Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Institute for Advanced Study, Synthetic Biology Research Center, International Cancer Center of Shenzhen University, Shenzhen, Guangdong Province, China. hwrpony@szu.edu.cn.ORCID http://orcid.org/0009-0003-8242-0518

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein lactylation emerges as a pivotal metabolic rheostat, translating microenvironmental lactate flux into stable programs that orchestrate cancer treatment resistance. This review synthesizes recent advances under the framework of "Lactylation Switch in Cancer Vulnerabilities." We dissect the dominant enzymatic pathways (AARS1/2, KATs, HDACs) and non-enzymatic mechanisms (MGO/LGSH), alongside their critical structural underpinnings. Furthermore, we delineate how lactylation signals are interpreted by specific readers (e.g., TRIM33), directly reprogram non-histone protein function through structural metamorphosis (e.g., disrupting p53, enhancing XLF), and engage in complex crosstalk with other PTMs, as exemplified by the synergistic interplay between histone H3 lysine 18 lactylation (H3K18la) and histone H3 lysine 27 acetylation (H3K27ac) in T-cell acute lymphoblastic leukemia (T-ALL). This interplay coordinately drives metabolic-epigenetic reprogramming, which specifically rewires intra- and extratumoral survival mechanisms. Lactylation fundamentally establishes a therapy-adaptive state by simultaneously enhancing intrinsic resistance (e.g., BLM K24la-mediated DNA repair) and extrinsic resistance (e.g., histone lactylation-driven PD-L1 upregulation). Critically, preclinical and clinical studies in validated models demonstrate that targeting this lactylation network (e.g., LDHA inhibition with stiripentol, KAT inhibitors, or site-specific blockers) yields striking synergistic effects, potentiating tumor sensitivity to chemotherapy, radiotherapy, and immunotherapy. Looking forward, we outline key translational paths, including deciphering stringent enzyme-substrate specificity for targeted inhibition, developing structure-based drug design, leveraging lactylomic signatures as predictive biomarkers, and addressing current mechanistic and technological gaps. This work not only establishes lactylation as a central mechanism of therapeutic resistance but also provides a novel conceptual paradigm for understanding how metabolic signals dynamically encode cancer cell vulnerabilities, offering transformative opportunities for precision oncology. Created in BioRender. Chengjiao, Y. (2026) https://BioRender.com/0lbu6jy .

Indexed as

Drug Resistance, NeoplasmEpigenesis, GeneticNeoplasmsAnimalsCell DeathHistonesHumansMetabolic ReprogrammingProtein Processing, Post-TranslationalHistones

Identifiers

PMID41786683
PMCPMC13039839

What OpenQuestion 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 OpenQuestion graph.