Research advances of lactylation modification in breast cancer.

Introduction

Breast cancer, the most common malignancy in women worldwide, comprises over 25% of all new cancer cases and significantly contributes to cancer-related mortality [ 1 ]. Its etiology is complex, involving genetic and environmental factors, leading to pronounced heterogeneity. Currently, the treatment options for breast cancer include surgery, chemotherapy, radiotherapy, endocrine therapy, and targeted therapy. However, these treatments are often accompanied by significant side effects, and drug resistance remains a major challenge. This highlights the pressing need for novel therapeutic strategies to improve the treatment outcomes of breast cancer.

Aerobic glycolysis, a hallmark of cancer metabolism driven by increased ATP demand, fuels rapid tumor growth, migration, and tumor cell proliferation. Unlike normal cells, which primarily utilize oxidative phosphorylation for energy, tumor cells predominantly rely on glycolysis, even in the presence of oxygen, a metabolic shift termed the Warburg effect. This adaptation allows for faster, albeit less efficient, ATP production to meet heightened metabolic needs [ 2 ]. Consequently, lactic acid, traditionally viewed as a metabolic byproduct of intense activity or hypoxia, has emerged as a key multifaceted player within the tumor microenvironment [ 3 ]. Its acidic properties help regulate tumor pH, fostering a favorable environment for cancer cell survival and growth. Recent studies have revealed its role as a bridge molecule that facilitates signal transduction among immune cells, tumor cells, and surrounding tissues. Lactic acid also functions as a signaling molecule, influencing gene expression and driving functional changes in various cell types [ 4 ].

Protein post-translational modifications (PTMs), such as methylation, acetylation, phosphorylation, ubiquitination, and glycosylation, play crucial roles in epigenetic regulation by controlling protein activity, localization, folding, and interactions [ 5 ]. Notably, Zhang et al. discovered histone lactylation in human and mouse cells using high-sensitivity HPLC-MS/MS analysis in 2019 [ 6 ]. Since its discovery, lactic acid has become a key factor in epigenetics, uniquely bridging metabolism and epigenetics, distinguishing it from other post-translational modifications, and thus garnering significant attention. In addition to the initial histone modifications, non-histone modifications have also been identified. This modification has been observed in various cancers, and ongoing research is elucidating its potential mechanisms. However, the precise regulatory mechanisms and biological functions of lactylation are not fully understood and continue to be explored.

Machine learning and large models have significantly advanced lactylation research, providing valuable insights into the identification of lactylation sites and the prediction of patterns. This advancement has, in turn, bolstered our capacity to delve into the functional implications of this modification [ 7 ]. Our review explores the mechanisms of lactylation within cancer cells and the tumor microenvironment, with particular emphasis on breast cancer. Furthermore, it discusses the integration of omics technologies and machine learning for identifying targets and stratifying prognoses. We also summarize potential anti-lactylation drugs and their clinical impacts, with the aim of stimulating innovative research and facilitating the translation of lactylation-based machine learning, diagnosis, prognosis, and therapies into clinical practice.

Lactic acid metabolism

In normal cells, glucose undergoes glycolysis to generate pyruvate under aerobic conditions. Pyruvate is then transported into the mitochondria, converted to acetyl-CoA, and enters the citric acid cycle to produce NADH and FADH₂. These high-energy carriers are utilized in the electron transport chain to facilitate efficient ATP synthesis. Under hypoxic conditions, cells switch to anaerobic glycolysis, converting pyruvate to lactate catalyzed by lactate dehydrogenase A (LDHA), an LDH isoform that preferentially catalyzes pyruvate-to-lactate conversion [ 8 ], to maintain NAD + levels and sustain glycolysis, albeit with lower ATP efficiency. These metabolic processes are tightly regulated to meet the cellular energy demands and preserve homeostasis.

Compared with normal cells, malignant tumor cells exhibit the Warburg effect, a metabolic reprogramming phenomenon in which glucose is utilized for glycolysis to generate energy and produce lactic acid, even under aerobic conditions. In addition to glucose, glutamine serves as a substrate for lactate production in tumor cells. The resulting lactate is imported via monocarboxylate transporter 1 (MCT-1) and exported via MCT-4, helping to maintain intracellular pH homeostasis [ 9 ].

Glutamine-derived lactate production occurs via two major mitochondrial-cytosolic pathways. In the GLS-GDH-ME axis, glutaminase (GLS) converts glutamine to glutamate, which is then deaminated by glutamate dehydrogenase (GDH) to produce α-ketoglutarate (αKG). After undergoing TCA cycle metabolism to malate, mitochondrial malate is exported to the cytosol, where malic enzyme (ME) converts it to pyruvate [ 10 ]. In the GOT-MDH axis, mitochondrial glutamic-oxaloacetic transaminase (GOT) transaminates glutamate with oxaloacetate (OAA), generating αKG and aspartate (Asp). Aspartate is transported to the cytosol and reconverted by cytosolic GOT to OAA, which is reduced to malate via malate dehydrogenase (MDH) [ 11 ]. In both pathways, cytosolic malate is ultimately converted to pyruvate by ME. This pyruvate is then reduced to lactate by lactate dehydrogenase A (LDHA) (Fig. 1 ).

Mechanism of lactylation modification

Since its proposal in 2019 as a novel post-translational modification, protein lactylation has emerged as a pivotal regulatory mechanism in epigenetics, immunometabolism and cancer biology. This modification, characterized by the covalent attachment of lactate to lysine residues, occurs via two distinct mechanisms: enzymatic and non-enzymatic. A comprehensive overview of lactylation modification pathways is shown in Fig. 2 .

Enzymatic lactylation: key components and mechanisms

The enzymatic lactylation process relies on transferase enzymes that catalyze lactyl group transfer. Due to structural similarity between lactate and acetyl groups, the histone acetyltransferases EP300 (E1A-binding protein p300) and CREB-binding protein (CBP)—originally identified for acetylation—also function as primary lactyltransferases [ 6 ]. Their conserved acetyltransferase domain accommodates lactyl-CoA through hydrophobic interactions, enabling substrate promiscuity [ 12 ]. Lactylation reversibility is governed by the eraser enzymes. Histone deacetylases 1–3 (HDAC1-3) [ 13 ], HDAC6 [ 14 ], HDAC8 [ 15 ], and sirtuins SIRT1-3 [ 16 – 19 ] hydrolyze lactyl-lysine bonds, restoring unmodified lysine residues. Prior to modification, lactic acid is activated to lactyl-CoA via an ATP-dependent reaction mediated by acyl-CoA synthetases (ACSs) [ 20 ]. This “priming” step ensures thermodynamic feasibility, as the high-energy thioester bond of lactyl-CoA drives spontaneous group transfer.

In addition to classical writers/erasers, novel lactylation regulators have been identified. Elevated lysine lactylation correlates with poor prognosis in colorectal cancer. Lysine acetyltransferase 8 (KAT8), the first identified global lactyltransferase, promotes tumor progression by lactylating eukaryotic translation elongation factor 1A2 (eEF1A2) at K408, thereby enhancing protein translation efficiency [ 21 ]. Beyond oncology, KAT8 triggers latent TGF-β binding protein 1 (LTBP1) lactylation at K752, stimulating collagen synthesis and skin rejuvenation in fibroblasts [ 22 ] Similarly, KAT7 (histone acetyltransferase binding to ORC1, HBO1) has been characterized as a lactylation writer enzyme, expanding the regulatory scope of lactylation [ 23 ]. Aminoacyl-tRNA synthetases (AARS1 and AARS2) exhibit moonlighting functions during lactylation. These enzymes directly convert lactate and ATP into lactate-AMP, bypassing lactyl-CoA synthesis. Lactate-AMP is an energy-rich intermediate in lysine lactylation [ 24 – 26 ]. In Escherichia coli , lactylation is dynamically regulated by YiaC (a lactyl-CoA synthetase) and CobB (a sirtuin-like delactylase). YiaC synthesizes lactyl-CoA for lysine lactylation, while CobB removes lactyl groups to maintain metabolic homeostasis [ 27 ].

Non-enzymatic lactylation: MGO-GLO1 axis

Chemical lactylation occurs independently of enzyme activity. Methylglyoxal (MGO), a reactive glycolysis byproduct, reacts with glutathione to form lactoyl glutathione (LGSH) via glyoxalase 1 (GLO1). LGSH non-enzymatically transfers lactyl groups to lysine residues under pathological conditions such as hyperglycemia [ 28 ]. Tables 1 and 2 provide a comprehensive summary of lactylation writers and erasers.

Machine learning based on lactylation-related gene in cancer prognostics

Leveraging the sophisticated analytical prowess of machine learning, extensive datasets can be dissected to uncover complex lactylation patterns that may modulate tumor behavior and predict patient outcomes. Considering that recent foundational studies have identified numerous lactylation modification sites and enzymes involved in the reaction, the utilization of machine learning has significantly enhanced our ability to discover and exploit these sites. Moreover, with the progress of machine learning applications in cancer, researchers can more effectively understand and predict the progression and treatment of cancer. The sophisticated analytical capabilities of machine learning tools allow the analysis of large datasets to reveal complex patterns of lactylation that may influence tumor behavior and patient prognosis. The applications of lactylation are summarized in Fig. 3 .

Biomarker identification

The identification of novel biomarkers related to lactylation through machine learning holds great promise for uncovering potential mechanisms and drug targets in cancer. By analyzing large-scale multi-omics datasets encompassing gene expression, protein modification patterns, and clinical features, researchers can develop sophisticated models capable of pinpointing specific lactylation sites that are critical for tumor progression. These identified sites subsequently serve as promising targets for new drug development, potentially revolutionizing the therapeutic approaches.

Recent advances in proteomics have identified many lactylation modification sites across various cancer types. For example, in gastric cancer AGS cells, LC-MS/MS combined with machine learning found 2375 Kla sites in 1014 proteins, with KEGG and GO analyses indicating enrichment in spliceosome-related functions [ 29 ]. Similarly, 724 lactylated sites in 451 proteins were identified in human lungs, showing enrichment in RNA splicing, actin filament organization, and neutrophil degranulation [ 30 ]. In hepatocellular carcinoma (HCC), 2045 lactylation sites on 960 proteins were identified using machine learning and proteomic techniques, though further validation is needed for clinical relevance [ 31 ]. Notably, in hepatitis B virus-related HCC, 9275 Kla sites were detected [ 32 ]. In FHC and SW480 cells, 637 lysine lactylation sites in 444 proteins were found, with enrichment in glycolysis [ 33 ]. Proteomic analysis of oral squamous cell carcinoma (OSCC) tissue revealed 2765 lactylation sites on 1033 proteins [ 34 ].

In TNBC, 58 lactylation sites across 48 proteins were identified, delineating a distinct lactylation signature. Remarkably, H4K12lac has emerged as a potential biomarker in TNBC, providing critical insights into its lactylation profiles and highlighting the clinical significance of histone modifications [ 35 ]. Recent studies have shown that elevated H4K5lac levels in breast cancer correlate significantly with lymph node metastasis, advanced clinical stage, and adverse prognosis [ 36 ].

Traditional experimental approaches for identifying Kla sites, while somewhat successful, are labor-intensive, time-consuming, and resource-demanding processes. These limitations have driven the development of computational methods for predicting Kla sites, which offer greater efficiency and convenience than experimental methods. However, existing computational methods have limitations, such as prediction accuracy being influenced by specific conditions and the challenge of fully replicating complex experimental settings.

To address these challenges, researchers have developed various computational tools for the prediction of Kla sites. FSL-Kla, based on a Kla benchmark dataset and few-shot deep learning models, analyzes and assesses 11 types of feature encoding schemes [ 37 ]. DeepKla, a publicly available deep learning-based tool, demonstrates robustness in predicting Kla sites in rice [ 38 ]. Auto-Kla, a transformer-based model, outperforms existing methods in predicting Kla sites in gastric cancer cells [ 39 ]. Other approaches integrate sequence and structure features using attention-based natural language processing methods or employ multi-view feature fusion, such as the DeepKlapred framework, which combines sequence embeddings and descriptors with a BiGRU-Transformer architecture to achieve high prediction accuracy. The DeepKlapred framework, employing multi-view feature fusion, combines sequence embeddings and descriptors to enhance protein sequence feature representation [ 40 ]. Besides, Researchers integrated sequence and structure features, developing a predictor that uses attention-based NLP for Kla site prediction, outperforming sequence-only models [ 41 ].

Current Kla site prediction models trained on non-breast cancer datasets face limitations due to cross-species and cellular context differences. While tools like FSL-Kla, DeepKla, and Auto-Kla have shown effectiveness in their respective domains, they may not fully capture breast cancer’s unique features. Thus, the development of breast-specific Kla site prediction models is crucial. These models would better account for the genetic and molecular characteristics of breast cancer, enhancing prediction accuracy and providing more reliable support for research and clinical practice.

Predictive models and personalized medicine

Researchers have developed machine learning prognostic models based on known lactylation modifications, enabling personalized medicine by predicting tumor behavior using lactylation features. These models assist clinicians in making informed decisions by estimating patient prognosis and selecting appropriate treatments. Numerous prognostic models based on lactylation modification target genes have been developed for various cancers, including lymphomas, hepatocellular carcinoma, clear cell renal cell carcinoma, multiple myeloma, osteosarcoma, pancreatic adenocarcinoma, glioma, prostate cancer, colorectal cancer, gastric cancer, and breast cancer (Table 3 ).

In diffuse large B-cell lymphoma, lactylation influences prognosis, tumor immune function, and drug resistance. A lactylation-based risk score model helps predict prognosis and guides treatment choices. High-risk patients are more sensitive to Cisplatin and Etoposide, and thus may benefit more from the ESHAP (Etoposide + Methylprednisolone + High-dose Cytarabine + Cisplatin) protocol [ 42 ]. Similarly, an eight-gene model predicts hepatocellular carcinoma prognosis. High-risk patients show better responses to chemotherapy, whereas low-risk patients are more sensitive to targeted inhibitors. Notably, high-risk patients respond less favorably to immunotherapy [ 43 ].

In breast cancer research, machine learning has been used to predict prognosis and treatment responsiveness. One study developed a prognostic model using KLA-related lncRNAs via Cox regression and XGBoost. Patients were stratified by median risk score, revealing differences in survival, clinical characteristics, immune infiltration, treatment response, and drug sensitivity [ 44 ]. Another study created a predictive model based on 22 KLA-related genes, identifying potential drug targets and providing insights into the tumor immune microenvironment [ 45 ].

These models demonstrate the potential of lactylation-based methods for personalized cancer treatment. However, the current studies have some limitations. Most studies used TCGA and GEO data for validation. To enhance reliability, additional datasets from different sources are needed for external validation, broadening the applicability of the predicted signature. Moreover, it is vital to thoroughly verify and clarify the complex mechanisms of KLA-related lncRNAs and mRNAs in various cancers through further well-designed and rigorously controlled experiments [ 46 ].

Lactylation modification in tumor microenvironment

The role of lactylation in the tumor microenvironment is an intricate and multifaceted area of oncological biology. This dynamic and heterogeneous ecosystem, composed of cancer, stromal, and immune cells and the extracellular matrix, significantly impacts cancer growth and treatment response. Lactylation plays a key role in regulating the interactions and functions of various cells within this environment, offering promising prospects for targeted cancer therapy.

Direct effects on tumor cells

Tumor cells, central to the tumor microenvironment (TME), are both the source of elevated lactylation and the beneficiaries of the Warburg effect. Most studies have shown that increased lactylation in these cells is closely linked to enhanced malignant traits. Lactylation modifications in tumor cells reflect the complexity of cellular signaling. They are diverse and are crucial for cellular communication. Figure 4 visually synthesizes our current understanding of the signaling pathways influenced by lactylation in tumor cells. Table 4 provides a comprehensive overview of specific lactylation targets across various tumor types and their associated signaling pathways. These modifications are also associated with cancer progression, suggesting their potential as biomarkers and therapeutic targets. Next, we will detail histone modifications in gene expression and non-histone protein modifications in protein translational modifications (PTMs).

Histone lactylation modification

The nucleosome, the basic repeating unit of eukaryotic chromatin, consists of a histone octamer (H3, H4, H2A, and H2B) and 147 bp of DNA wrapped around it in a “beads-on-a-string” configuration [ 47 ]. Lactylation modifications are predominantly found on histones H3 and H4, with specific sites including H3K18la, H3K27la, H3K14la, H3K9la, H3K56la, and H4K12la. For examples:

Ocular Melanoma: Histone lactylation promotes tumorigenesis by upregulating YTHDF2 expression. YTHDF2 recognizes and degrades m6A-modified PER1 and TP53 mRNAs, accelerating tumorigenesis [ 48 ]. Additionally, histone lactylation enhances ALKBH3 expression, leading to SP100A m1A demethylation and reduced RNA and protein levels. This results in PML body loss, further driving ocular melanoma progression [ 49 ].

Glioblastoma: H3K9 lactylation enriches the LUC7L2 promoter, activating its transcription. Histone lactylation also drives NF-κB-related LINC01127 expression, promoting glioblastoma stem cell self-renewal via the MAP4K4/JNK/NF-κB axis [ 50 ]. Furthermore, lactate reprograms glioblastoma immunity through CBX3-regulated histone lactylation [ 51 ].

Lung cancer: H3K18 lactylation increases POM121 expression, enhancing MYC activity and PD-L1 expression, and causing immunosuppression in non-small cell lung cancer [ 52 ]. Additionally, LKB1 influences TERT expression through histone lactylation, promoting cellular senescence and telomerase regulation in NSCLC cells [ 53 ].

Colorectal cancer: Histone lactylation downregulates macrophage RARγ expression, promoting tumorigenesis via TRAF6-IL-6-STAT3 signaling [ 54 ]. GPR37 enhances glycolysis and histone lactylation, driving liver metastasis via the Hippo pathway [ 55 ]. Additionally, Enterobacterial LPS promotes histone lactylation, thereby upregulating the expression of LINC00152 to promote cancer cells invasion and migration [ 56 ].

Liver cancer: PYCR1 promotes liver cancer cell growth and metastasis via regulating IRS1 expression through lactylation modification [ 57 ]. In addition, histone lactylation facilitates hepatocellular carcinoma progression by upregulating endothelial cell-specific molecule 1(EMS1) expression [ 58 ]. H3K18 lactylation also accelerates liver fibrosis by promoting SOX9 transcription [ 59 ].

Esophageal cancer: Hypoxia induces H3K9 lactylation, enhancing LAMC2 transcription and promoting esophageal cancer invasion and migration [ 60 ].

Pancreatic ductal adenocarcinoma (PDAC): Lactate-induced H3K18la drives PDAC tumorigenesis and progression, correlating with adverse clinical outcomes [ 61 ].

Gastric cancer (GC): H3K18 lactylation upregulates VCAM1 transcription, activating AKT-mTOR signaling and promoting tumor cell proliferation, epithelial–mesenchymal transition (EMT), and metastasis. VCAM1 also increases CXCL1 expression via AKT-mTOR, recruiting hGC-MSCs and M2 macrophages [ 62 ].

Bladder cancer: CircXRN2 activates the Hippo pathway by stabilizing LATS1, suppressing H3K18 lactylation-driven tumor progression [ 63 ]. PFK-1 modulates histone lactylation to regulate ZEB1 transcriptional activity, inhibiting bladder cancer malignancy [ 64 ].

Clear cell renal cell carcinoma (ccRCC): Von Hippel-Lindau (VHL) inactivation triggers histone lactylation, creating a positive feedback loop with PDGFRβ signaling and driving ccRCC pathogenesis [ 65 ].

Head and neck squamous cell carcinoma (HNSCC): Lactate-induced H3K9la enrichment in the IL11 gene. IL-11 promotes CD8 T cell dysfunction via JAK2/STAT3 signaling, leading to poor immunotherapy responses [ 66 ].

Thyroid cancer: Oncogenic BRAFV600E enhances glycolysis and restructures the cellular lactylation landscape. This leads to H4K12La-driven gene transcription and cell cycle deregulation, boosting anaplastic thyroid carcinoma proliferation [ 67 ].

Non-histone lactylation

Numerous non-histone proteins undergo lactylation, a key post-translational modification (PTM) that plays crucial roles in cellular activities and is strongly associated with essential physiological and pathological processes. Many researchers are investigating non-histone protein lactylation sites to uncover their biological functions and potential applications (Table 5 ).

Lung cancer: Lactate-induced IGF1R protein lactylation drives lung cancer cell proliferation and metabolic reprogramming [ 68 ]. Additionally, hypoxia promotes SOX9 lactylation, enhancing glycolysis to boost cell stemness, migration, and invasion in NSCLC [ 69 ].

Colorectal cancer: Intra-tumoral bacteria boost lactate production, prompting M2 macrophage polarization. This occurs because RIG-I lactylation inhibits NF-κB signaling, reducing Nlrp3 transcription by blocking NF-κB recruitment to the Nlrp3 promoter in macrophages. The subsequent Nlrp3 reduction impacts Tregs’ immunosuppressive activities and CD8 + T cells’ antitumor functions, contributing to colorectal cancer liver metastasis [ 70 ]. Meanwhile, eEF1A2 K408 lactylation enhances translation elongation and protein synthesis, fueling colorectal carcinogenesis [ 21 ].

Hepatocellular carcinoma (HCC): CCNE2 lactylation promotes HCC cell proliferation, migration, and invasion [ 17 ]. Glypican-3 knockdown inhibits hepatocellular carcinoma cell growth, stemness, and glycolysis development under hypoxia via lactylation [ 71 ]. Additionally, CENPA lactylation may drive oncogene expression and accelerate HCC tumorigenesis [ 72 ].

Esophageal cancer: Hypoxia-induced Axin1 protein lactylation at K147 promotes its ubiquitination, enhancing glycolysis and cell stemness in TE1 and EC109 cells [ 73 ]. Additionally, hypoxia drives SHMT2 protein lactylation, upregulating MTHFD1L and thereby boosting the proliferation, migration, invasion, stemness, and glycolysis of esophageal cancer cells [ 74 ].

Pancreatic ductal adenocarcinoma: RHOF acts as an oncogene in PC, upregulating c-Myc to boost PKM2 transcription. PKM2 then induces glycolysis, whose lactate byproduct lactylates Snail1, promoting EMT [ 75 ]. NMNAT1 lactylation enhances its nuclear localization and enzymatic activity, supporting the nuclear NAD salvage pathway and cancer growth [ 76 ]. Additionally, lactate upregulates NUSAP1 expression by inhibiting its protein degradation through Kla modification, forming a feedforward loop that promotes the Warburg effect and metastasis in pancreatic ductal adenocarcinoma [ 77 ].

Gastric cancer: AARS1 promotes tumor cell proliferation by translocating into the nucleus and catalyzing lactylation of YAP at K90 and TEAD1 at K108, thereby activating downstream target gene expression [ 24 ].

Prostate cancer: HIF1α lactylation enhances KIAA1199 transcription to promote angiogenesis and vasculogenic mimicry in prostate cancer [ 78 ]

Cervical cancer: DCBLD1 lactylation stabilizes its expression, activates the PPP, and drives cervical cancer cell proliferation and metastasis [ 79 ]. Conversely, HPV16 E6 inhibits G6PD lactylation, promoting its dimerization and PPP activation, which fuels cervical cancer cell proliferation [ 80 ].

Lactylation modification is an emerging epigenetic regulatory mechanism that has attracted much attention in recent breast cancer studies. To date, studies have primarily focused on histone lactylation, especially at the critical sites H3K18 and H4K12.

Histone lactylation, driven by the elevated glycolytic rate in breast cancer cells, influences key oncogenes such as c-Myc, promoting tumor progression. C-Myc, crucial for cell proliferation and survival, is upregulated by lactylation and further activates SRSF10. This splicing factor modulates genes such as MDM4 and Bcl-x, linking metabolic changes to gene expression alterations and driving breast cancer development [ 81 ]. KCNK1 enhances glycolysis and lactate production through LDHA activation, leading to increased histone lactylation and altered downstream gene expression. This metabolic shift promotes the proliferation, invasion, and metastasis of breast cancer cells [ 82 ]. Additionally, H3K18la boosts PPARD expression, which subsequently activates the PI3K/AKT signaling pathway, maintaining cell survival and proliferation in BC [ 83 ]. In triple-negative breast cancer (TNBC), H4K12 lactylation is associated with tumor progression by downregulating SLFN5, a gene that protects against tumor growth and apoptosis [ 84 ].

Implications on immune cells

In the tumor microenvironment, elevated lactate concentrations exert a pronounced influence on immune cells by driving rapid phenotypic and functional alterations, thus identifying potential targets for immunotherapeutic intervention. We will focus on the effects of lactylation on immune cells, such as macrophages, T-reg cells, T cells, natural killer cells (NK), and Myeloid-derived suppressor cells (MDSCs) [ 85 ].

Lactylation modifications in tumor-associated cells can drive immune cells toward an immunosuppressive phenotype. Macrophages, which are key players in the immune response, primarily exist in the M1 or M2 phenotypes. M1 macrophages are involved in acute immune reactions, whereas M2 macrophages are associated with parasitic diseases and exhibit an immunosuppressive phenotype within the TME. Previous research has shown that lactate can polarize the M2 immunosuppressive phenotype by stabilizing HIF-1α and inducing M2 genes such as Arg-1, Fizz-1, Mgl-1, VEGF, and PPAR-γ, thereby promoting tumor growth, metastasis, and invasion [ 86 ]. Considering recent advances in lactylation modification, potential relationships in various cancers, such as colorectal cancer [ 54 ], cervical cancer [ 87 ], glioma [ 88 ], and pancreatic cancer [ 89 ], shown in Table 6 , may be verified by subsequent experiments.

Regulatory T (Treg) cells are crucial for maintaining immunosuppression in the tumor microenvironment. High lactate concentrations affect Treg cell differentiation, stability, and function, inhibiting anti-tumor immunity and accelerating tumor progression [ 90 ]. Lactate regulates Treg cell generation by lysine 72 lactylation of MOESIN, enhancing its interaction with the TGF-β receptor I and downstream SMAD3 signaling [ 88 ]. In malignant pleural effusion (MPE), overexpression of monocarboxylate transporter 1 (MCT1) and lactate dehydrogenase B maintains the immunosuppressive function and hyper-lactylation by facilitating lactate uptake and utilization in FOXP3 + NKT-like cells [ 91 ].

Comprehending these mechanisms is critical for developing strategies to overcome immunosuppression and augment immunotherapy effectiveness. By targeting lactylation-associated pathways, it may be possible to adjust the tumor immune microenvironment, reverse immunosuppressive phenotypes, and enhance patients’ responsiveness to immunotherapeutic treatments.

Treatment based on lactylation modification

The previous discussion identified numerous abnormal histone modification sites and alterations in the activity of histone-modifying enzymes in cancer. These aberrant modifications and changes in the expression of modifying enzymes can serve as valuable biomarkers for accurate screening, detection, diagnosis, and prognosis of tumors. Given that different enzymes catalyze modifications at specific histone sites, targeting these histone-modifying enzymes with oncogenic potential represents a promising strategy for cancer therapy. Targeted therapies based on lactylation modification are summarized in Fig. 5 .

Targeted lactylation modification enzymes

Post-translational modifications, such as lactylation, can be adjusted by targeting the responsible enzymes. Intracellular lactylation levels are regulated by targeting writers, such as p300, and erasers, such as HDACs and SIRT enzymes. C646, an inhibitor of the lactylation writer enzyme p300, inhibits breast cancer growth by promoting cellular apoptosis through reducing H3K27 lactylation [ 92 ]. HDAC1–3 and SIRT1–3, known for their deacetylase activity, also function as delactylases, creating potential competition among these modifications. Honokiol-induced SIRT3 activation induces HCC cell apoptosis and prevents HCC outgrowth in vivo by regulating CCNE2’s Kla levels [ 17 ]. These enzymes are crucial for gene expression, cell cycle regulation, and metabolic pathways. HDACs and SIRTs have attracted interest because of their role in epigenetic modifications that affect gene expression without changing the DNA sequence. However, the implications of these findings on lactylation modification require further research.

Targeting metabolic pathways related to lactylation modification

The metabolic changes in cancer cells, particularly increased glycolysis and lactate production, represent a unique vulnerability that can be exploited for therapeutic benefits. Targeting lactate production by inhibiting glycolytic enzymes and lactate transporters offers a multifaceted approach to combat cancer, underscoring the importance of metabolic research in developing novel cancer therapies. The primary ingredients extracted from traditional Chinese medicine, such as Royal jelly acid and Evodiamine, are used to regulate glycolytic lactylation modification to inhibit the growth, migration, and proliferation of tumor cells. Royal jelly acid inhibited HCC development through interfering with lactate production and inhibiting H3 histone lactylation at H3K9la and H3K14la sites [ 93 ]. Meanwhile, Evodiamine impairs HIF1A histone lactylation to inhibit Sema3A-mediated angiogenesis and PD-L1 by inducing ferroptosis in prostate cancer [ 94 ].

Emerging therapeutic strategies targeting lactylation modifications

Emerging antitumor strategies target lactylation modifications beyond traditional metabolic pathway inhibitors. Circular RNAs (circRNAs) play diverse roles in diseases [ 95 ]. For instance, CircXRN2 stabilizes LATS1 to activate the Hippo pathway, suppressing H3K18 lactylation-driven bladder cancer progression [ 63 ]. Additionally, circATXN7 transcription, activated by KRAS-mutant tumor cell-produced lactic acid, binds to NF-kB p65, sequestering it in the cytoplasm. Its upregulation in CTLs is linked to adverse prognosis and immunotherapy resistance [ 96 ]. It’s also revealed that a novel peptide encoded by circMETTL3, METTL3-156aa, binding with LDHA, promotes M1 macrophage polarization via enhancing its glycolysis. Subsequently, the expression of the cleavage factor SRSF10 is upregulated by the glycolysis metabolite lactate, resulting in increased splicing of the pre-METTL3 mRNA, leading to the rising production of cirMETTL3 [ 97 ]. EccDNA also plays an important role by promoting proteasome inhibitor resistance through KIF3C amplification, reducing MUC20 expression and repressing IGF-1R lactylation in resistant multiple myeloma cells [ 98 ].

The roles of circular RNA and eccDNAs in cancer lactylation modification are complex and not fully explored. Further research is necessary because of their significant potential for anti-tumor effects. Understanding their specific functions in cells and their effects on tumor development could reveal new treatment strategies, improve the survival and quality of life of cancer patients, and provide insights into the treatment of other diseases.

Discussion

Lactate, a pivotal byproduct of tumor glycolysis, and its derived lactylation modifications, are essential for numerous biological processes, including gene expression regulation, cell signaling transduction, and inflammatory response coordination, and significantly influence disease occurrence and development. Specifically, lactylation modifications can regulate the tumor microenvironment and reshape tumor metabolism. They can also lead to the lactylation of both histone and non-histone proteins under the influence of specific enzymes. These modifications play a significant role in tumor growth, proliferation, migration, drug resistance, and immune evasion, making them potential therapeutic targets for cancer treatment.

Current research is concentrated on several key areas, and details are provided in Fig. 6 .

Clarifying the mechanisms of lactylation modifications within tumor cells.

Utiliziing multi-omics and machine learning to identify lactylation sites and construct risk prediction models.

Exploring the role of lactylation modifications in the tumor microenvironment.

Developing novel drugs based on the identified targets.

Despite considerable progress, researchers still encounter emerging research directions and challenges in this field. In breast cancer, lactylation modifications constitute a nascent research frontier that offers novel insights. This review delineates the mechanisms of lactylation modifications in various cancers, including breast cancer, their influence on the tumor microenvironment, the application of machine learning, and progress in drug research. However, the clinical application of lactylation modifications requires further investigation to ensure their efficacy and safety. The key considerations are as follows:

Normal cell toxicity: Research should focus on understanding the potential toxicity of lactylation modifications in normal cells to ensure that therapeutic strategies do not harm healthy tissues.

Physiological impacts: Evaluate the effects of lactylation modifications on key physiological processes, such as growth metabolism and embryonic development, to ensure the safety of lactylation-targeted therapies.

Mechanisms and networks in breast cancer: Explore the mechanisms and epigenetic regulatory networks of lactylation modifications in breast cancer, including their regulation of tumor metabolic pathways and their influence on the tumor microenvironment.

Subtype-specific networks and sites: Identify specific regulatory networks and lactylation sites within different breast cancer subtypes to develop more precise therapeutic approaches.

Immunotherapy applications: Investigate the application of lactylation modifications in immunotherapy, given their role in tumor immune suppression, to develop novel combination therapies that enhance anti-tumor immune responses.

Clinical challenges: Address potential challenges in clinical practice, such as adverse drug reactions, resistance, side effects, and safety concerns, to ensure the effective and safe translation of lactylation-based therapies into clinical settings.

Gaining deeper insights into lactylation modifications within the tumor microenvironment will enhance our understanding of the biological mechanisms underlying tumorigenesis. This knowledge will pave the way for identifying new therapeutic targets and improving the outcomes of patients with cancer. Lactylation modifications are crucial for tumor metabolic reprogramming and immune evasion. As we expand our understanding of their roles in the tumor microenvironment, we will better understand the processes driving cancer development. This lays the foundation for developing novel therapies and enhancing the prognosis of cancer patients.

Author contributions

All authors have made substantial contributions to the conception, design, data analysis, manuscript writing, or revision. The specific contributions are as follows: Pu Shen: concept of theme, illustration design and manuscript writing and revision. Meng Yang: manuscript revision, Corresponding Author.

Funding

No.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Not applicable.

Consent for publication

Not applicable.

Competing interests

All authors have confirmed that there are no competing interests.

Footnotes

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Associated Data

Data Availability Statement

No datasets were generated or analysed during the current study.