Evidence map›Paper›PMID 41275140›Full record

ArticleBMC cancer2025

Single-cell and spatial transcriptomics reveal lactylation-associated tumor cell clusters and define a prognostic risk model in glioblastoma.

Rui Han, Guangfan Chi, Dongjie Sun, Ziran Xu, Liangfu Zhou, Kan Xu

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Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rui HanDepartment of Neurovascular Surgery, The First Hospital of Jilin University, No. 71, Xinmin Street, Chaoyang District, Changchun City, Jilin Province, 130021, People's Republic of China.
Guangfan ChiThe Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, 130012, China.
Dongjie SunThe Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, 130012, China.
Ziran XuDepartment of Clinical Laboratory, Lequn Branch, The First Hospital of Jilin University, Changchun, Jilin, 130021, China.
Liangfu ZhouDepartment of Neurovascular Surgery, The First Hospital of Jilin University, No. 71, Xinmin Street, Chaoyang District, Changchun City, Jilin Province, 130021, People's Republic of China. lfzhouc@jlu.edu.cn.
Kan XuDepartment of Neurovascular Surgery, The First Hospital of Jilin University, No. 71, Xinmin Street, Chaoyang District, Changchun City, Jilin Province, 130021, People's Republic of China. Xukan@jlu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlioblastoma (GBM) is the most aggressive adult brain tumor, marked by intratumoral heterogeneity and therapy resistance. Metabolic reprogramming through histone lactylation has been linked to tumor progression and immune suppression. However, the spatial and single-cell landscape of lactylation in GBM and its prognostic significance remain poorly understood.

methodsWe employed a multi-omics approach integrating bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to investigate lactylation-related signatures in GBM. Differential expression and pathway analyses were performed using GEO and TCGA datasets. Cell clustering, SCENIC transcriptional network inference, CellChat intercellular communication modeling, and pseudotime analysis were conducted. A prognostic risk model was constructed using LASSO-Cox regression based on lactylation-associated genes. Experimental validation was performed using western blotting, immunohistochemistry, and functional assays in GBM cell lines.

resultsLactylation-related genes were significantly upregulated in GBM and associated with poor prognosis and immunosuppressive tumor microenvironments. Single-cell analysis revealed high-lactylation malignant subpopulations enriched in hypoxic tumor cores, exhibiting metabolic reprogramming and enhanced immune evasion. Spatial transcriptomics confirmed the localization of S100A6-high-lactylation GBM cells in aggressive tumor regions. A nine-gene lactylation-based risk model stratified patients into high- and low-risk groups with significantly different survival outcomes (AUC: 0.77-0.87). Experimental knockdown of S100A6 reduced GBM cell proliferation, migration, and invasion.

conclusionsLactylation defines distinct tumor cell clusters in GBM that are spatially localized, metabolically reprogrammed, and immunosuppressive. The S100A6-associated lactylation signature serves as a robust prognostic biomarker and potential therapeutic target in GBM.

Indexed as

Brain NeoplasmsGlioblastomaTranscriptomeBiomarkers, TumorCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorGlioblastoma multiformeLactylationSingle-cell RNA sequencingSpatial transcriptomics

Identifiers

PMID41275140
PMCPMC12750639

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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.