Glioblastoma (GBM) stands out as the most malignant and aggressive form of adult brain cancer, notorious for its remarkable intratumoral heterogeneity and resistance to conventional therapies. Despite ongoing advancements in neuro-oncology, the prognosis for GBM patients remains grim, with survival rates stubbornly low. A groundbreaking study published in BMC Cancer in 2025 has illuminated a novel facet of GBM biology—histone lactylation—and its profound implications for tumor progression, immune evasion, and patient prognosis. Utilizing cutting-edge single-cell and spatial transcriptomics technologies, researchers have begun to unravel the complex cellular and molecular landscape shaped by lactylation within GBM tumors.
Histone lactylation is an emerging epigenetic modification that links metabolic changes, particularly in the tumor microenvironment, to gene expression alterations driving cancer development. This study leverages a multi-omics approach, integrating bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics, to dissect the role of lactylation in GBM at unprecedented resolution. By probing datasets from GEO and TCGA, the team identified lactylation-related genes that are markedly upregulated in GBM tissues and are associated with immunosuppressive microenvironments and poor clinical outcomes.
A key finding centers around the discovery of distinct malignant tumor cell subpopulations exhibiting high levels of lactylation, which reside predominantly within hypoxic regions of the tumor core. These hypoxic niches are well-known for fostering aggressive tumor phenotypes that evade immune surveillance. Single-cell analyses revealed that these lactylated clusters undergo profound metabolic reprogramming, tailoring their gene expression to survive and thrive under oxygen-deprived conditions, while concurrently orchestrating mechanisms to suppress the surrounding immune response.
Spatial transcriptomics added another critical dimension to the findings by mapping the precise localization of these lactylated tumor cells within the heterogeneous tumor architecture. In particular, cells expressing high levels of S100A6, a gene intimately linked to lactylation, were found concentrated in aggressive tumor regions notorious for rapid proliferation and invasion. This spatial information underscores the functional heterogeneity within GBM and provides a tangible target for therapeutic interventions.
To translate these molecular insights into clinical practice, the researchers developed a prognostic risk model based on nine lactylation-associated genes. Using LASSO-Cox regression—a powerful statistical method for feature selection—they stratified GBM patients into distinct high- and low-risk groups. Strikingly, this model demonstrated impressive predictive accuracy with area under the curve (AUC) values ranging from 0.77 to 0.87, suggesting its potential utility as a robust biomarker panel for patient prognosis and treatment stratification.
The compelling prognostic value of the lactylation signature is further supported by experimental validation. In vitro functional assays targeting S100A6 demonstrated that silencing this gene significantly impaired GBM cell proliferation, migration, and invasion, highlighting its pivotal role in maintaining tumor aggressiveness. These findings position S100A6 not merely as a biomarker but as a potential therapeutic target for disrupting lactylation-driven malignant programs.
Underpinning these discoveries is the innovative application of SCENIC transcriptional network inference and CellChat intercellular communication modeling. These computational tools enabled the authors to uncover regulatory networks and cell-cell interactions modulated by lactylation, providing mechanistic insights into how tumor cells rewire signaling pathways to foster immune suppression and metabolic adaptation in GBM.
Pseudotime trajectory analyses further delineated the dynamic states of tumor cell populations, tracing the evolutionary paths from less aggressive to more malignant lactylated states. This temporal framework enriches our understanding of tumor progression and highlights critical junctures where therapeutic interventions might be most effective.
The study also sheds light on the tumor immune microenvironment, revealing that lactylation-associated clusters contribute to the establishment of immunosuppressive niches. This finding dovetails with accumulating evidence that metabolic reprogramming in tumors orchestrates immune evasion, a major challenge for immunotherapies in GBM.
Moreover, the emergence of lactylation as a key metabolic-epigenetic axis opens avenues for novel therapeutic strategies. Targeting enzymes responsible for lactylation or the downstream effectors, such as S100A6, could potentially disrupt malignant metabolic circuits, sensitize tumors to immune attack, or enhance the efficacy of existing treatments.
Beyond its immediate clinical relevance, this research marks a significant advance in cancer biology by employing integrated single-cell and spatial transcriptomics to parse tumor complexity. This multidimensional profiling affords a holistic view of cellular heterogeneity, spatial organization, and functional states within tumors—an approach likely to become foundational in precision oncology.
Despite these promising findings, challenges remain. Validation of the prognostic model and therapeutic targets in larger, independent patient cohorts and in vivo models will be essential to confirm their utility. Additionally, translating knowledge of lactylation into safe and effective clinical interventions will require comprehensive understanding of the broader systemic effects of modulating this epigenetic mark.
Nevertheless, this study underscores the transformative potential of marrying metabolic insights with high-resolution transcriptomic technologies to redefine our understanding of glioblastoma. By pinpointing lactylation as a central player in tumor cell clustering, metabolic adaptation, and immune modulation, it opens a new chapter in the fight against one of the deadliest brain cancers.
In summary, this pioneering work reveals that lactylation is more than a metabolic footnote in glioblastoma biology; it is a defining feature of tumor heterogeneity and aggressiveness. The identification of lactylation-enriched tumor cell clusters, spatially anchored in hypoxic niches and regulated by signatures including S100A6, provides a powerful prognostic tool and therapeutic target. This research paves the way for the development of lactylation-focused strategies that could revolutionize glioblastoma treatment and improve outcomes for patients facing this devastating disease.
Subject of Research: Metabolic reprogramming through histone lactylation in glioblastoma, its association with tumor heterogeneity, immune evasion, and prognosis.
Article Title: Single-cell and spatial transcriptomics reveal lactylation-associated tumor cell clusters and define a prognostic risk model in glioblastoma
Article References:
Han, R., Chi, G., Sun, D. et al. Single-cell and spatial transcriptomics reveal lactylation-associated tumor cell clusters and define a prognostic risk model in glioblastoma. BMC Cancer (2025). https://doi.org/10.1186/s12885-025-15291-6
Image Credits: Scienmag.com
DOI: https://doi.org/10.1186/s12885-025-15291-6
Tags: epigenetic modifications and cancerglioblastoma researchhistone lactylation in cancerimmune evasion in glioblastomaIntratumoral Heterogeneity in GBMlactylation-related genes in cancermetabolic changes in brain tumorsmulti-omics approach in oncologyprognosis of glioblastoma patientssingle-cell transcriptomics in glioblastomaspatial transcriptomics and tumor analysistumor microenvironment and gene expression
