Identification of protein lysine lactylation and potential targets in esophageal squamous cell carcinoma

Introduction

The 2022 Global Cancer Observatory (GLOBOCAN) report ranks esophageal cancer (EC) as the 11^th most prevalent cancer and the 7^th leading cause of cancer-related deaths (1). Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma are the two primary pathological subtypes of EC. About 85% of EC cases are ESCC and lack effective therapeutic targets (2). ESCC is an aggressive malignancy with poor outcomes. Therefore, to improve the survival outcomes of ESCC patients, new and efficient molecular therapies are required, which need a comprehensive understanding of the molecular characteristics of ESCC pathogenesis.

Previous literature suggests that ESCC is usually linked with an increased occurrence of lymph node metastasis (LNM). Even in the pT1 stage, the nodal metastasis risk is around 4% for pT1a ESCC and 30% for pT1b ESCC patients (3). LNM is considered an independent factor for ESCC patient’s prognosis (4). Thus, it is essential to elucidate the molecular pathways of ESCC metastasis.

Aerobic glycolysis is a common phenomenon of malignancy and produces large amounts of lactate (5). Lactate provides energy for rapid tumor proliferation, and plays key roles in metabolic remodeling and immunosuppression. Besides, lactate can induce protein lysine lactylation (Kla) in proteins, which alters protein structure and function. Kla is a novel posttranslational modification that has been linked with the progression of cancer cells, indicating its potential as a promising target for cancer treatment (6-12). However, the impact of Kla on ESCC cell’s pathogenic mechanism remains undetermined. This study aimed to investigate the effect of Kla on ESCC metastasis, specifically focusing on non-histone protein Kla. This comprehensive analysis will furnish evidence for future studies on the development of novel treatment modalities for ESCC patients. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2204/rc).

Methods

Patients and tissue samples

This research study included 14 ESCC patients who underwent radical surgery without neoadjuvant therapy at West China Hospital, Sichuan University, between April 2021 and July 2023. The ESCC tissue samples were prospectively collected from these patients, quickly snap-frozen in liquid nitrogen, and kept at −80 ℃. The patient’s ESCC diagnoses were pathologically confirmed. Furthermore, based on the pathological TNM staging, including pT1N0M0 and pT1N+M0 (American Joint Committee on Cancer, 8^th edition), all the participants were categorized into two groups. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Board of West China Hospital, Sichuan University (No. approval ID). All the patients were first informed about the study and then their consents were acquired.

Western blot assay

The primary ESCC cultured cells and tissues were lysed using RIPA buffer comprising a protease inhibitor cocktail. The lysates were then centrifuged at 4 ℃ for 10 min at 2,000 ×g to collect the supernatant and remove the cell debris. The protein was quantified via the BCA assay kit (PC0020, Solarbio) and then subjected to Western blotting, per the standard protocol (13). The antibodies employed included anti-L-Lactyl Lysine (PTM Biolabs; PTM-1401RM) and anti-enolase 1 (ENO1; Proteintech; 11204-1-AP).

LC-MS/MS analysis

Based on pan-Kla levels in 7 paired ESCC tissues (7 samples from pT1N0M0 and 7 samples from pT1N+M0), three pairs of ESCC tissue samples with significantly different Kla levels were selected for global lactylome analysis. Protein isolation and tryptic digestion were carried out as previously defined (14). For Kla affinity enrichment, tryptic peptides were dissolved in NETN buffer [Tris-HCl (50 mM), NaCl (100 mM), NP-40 (0.5%), EDTA (1 mM), pH 8.0)]. Then, the buffer-containing peptide was incubated with pre-washed antibody beads (PTM-402, PTM Bio) overnight at 4 ℃ with gentle shaking. Subsequently, the beads were rinsed with NETN buffer 4 times and with deionized water 4 times to eliminate unbound peptides. The bound peptides were eluted from the beads using trifluoroacetic acid (0.1%). Lastly, all the acquired fractions were mixed, and vacuum-dried, followed by subjecting them to desalting with C18 ZipTips (Millipore) per the kit’s protocol for liquid chromatography-tandem mass spectrometry (LC-MS/MS) assessment.

For lactylome analysis, 4-dimensional label-free quantitation was employed. First, the tryptic peptides were treated with solvent A [acetonitrile (2%) and formic acid (0.1%)] and then separated using the following gradient: 6–22% solvent B (formic acid (0.1%) in acetonitrile) for 0–44 min, 22–30% B for 44–54 min, 30–80% B for 54–57 min, 80% B for 57–60 min. The gradient flow rate was constant at 450 nL/min, and the NanoElute UHPLC system (Bruker Daltonics) was utilized. Before the timsTOF Pro mass spectrometry, the peptides were introduced into the capillary source and the applied electrospray voltage was maintained at 1.7 kV. Fragments and precursors were evaluated at the TOF detector, using a 100–1,700 MS/MS scan range. The parallel accumulation serial fragmentation (PASEF) mode was utilized for timsTOF Pro. For fragmentation, 0–5 charge state precursors were selected, and 10 PASEF-MS/MS scans were acquired per cycle. The dynamic exclusion was set to 24 s.

Database search

The MaxQuant search engine (v.1.6.15.0) processed the acquired MS/MS data. Tandem mass spectra were searched against Homo_sapiens_9606_SP_20230103.fasta (20389 entries) concatenated with a reverse decoy and contaminants database. Trypsin/P was utilized as a cleavage enzyme for up to 2 missing cleavages. The maximum number of modifications per peptide was 5, while the minimum length of peptide was 7. Furthermore, the mass tolerance of precursor ions for the first and main searches, as well as for fragment ions, was 20 ppm. The variable modifications included protein N-terminal acetylation, oxidation on Met, and Kla, whereas Carbamidomethyl on Cys was defined as the fixed modification. The peptide, protein, and (PSM)’s false discovery rate (FDR) was set as <1%.

ESCC cell culture

KYSE150, KYSE30, and KYSE510 (ESCC cell lineages) were maintained in the laboratory of thoracic surgery at West China Hospital, Sichuan University and grown in RPMI-1640 (Thermo Fisher Scientific Inc., Waltham, MA, USA) augmented with 100 µg/mL streptomycin, 100 U/mL penicillin, and 10% fetal bovine serum (Gibco, Grand Island, NY, USA) at 37 ℃ in 5% CO₂.

Immunoprecipitation

The tumor cells or tissues were lysed using lysis buffer [Tris-HCl (20 mM; pH 7.4), NaCl (150 mM), and Triton X-100 (1%)] comprising a cocktail of protease inhibitors for 30 min at 4 ℃. Then, the lysates were centrifuged to harvest the soluble supernatant fractions, which were utilized for immunoprecipitation with ENO1 beads. After binding, the non-specifically bound proteins were removed by rinsing the beads with immunoprecipitation lysis buffer thrice. Subsequently, a western blot was performed.

Wound healing and cell migration assays

Wound healing analysis: ESCC cells monolayer was serum-starved for 12 h. Then, a wound was created using a 200 µL pipette tip. After 24 h, the cells that migrated towards the wound surface were evaluated by a microscope.

Cell migration analysis: ESCC cells were starved for 12 h and then seeded (2×10⁵) into Transwells (BD Biosciences, San Jose, CA, USA) with 8-µm pore size membranes allowing migration. After 24 h, migrated cells at the Transwell bottom were dyed with crystal violet, while those within the remaining cells were removed. Furthermore, the association of ENO1’s Kla levels with ESCC cell metastasis was evaluated.

Immunofluorescence staining

The ESCC tissues were fixed in formalin for 24 to 48 hours immediately after the surgery. The samples were then submerged in paraffin for serial sectioning via the Opal^® multiplex IHC system (PerkinElmer), per the defined protocol. Then, the slides were baked, dewaxed using xylene and rehydrated in a series of ethanol (100%, 95%, and 75%) and ultrapure water solutions. Subsequently, the samples were subjected to microwave treatment for antigen retrieval. The primary antibodies and their corresponding detection channels were: pan-Kla (1:100, PTM BIO, PTM-1401RM) detected with Opal650 and ENO1 (1:1,000, Proteintech, 11204-1-AP) detected with Opal520. Cell nuclei were stained using DAPI (1:1,000). The samples were photographed by an Akoya Vectra Polaris Automated Imaging system (Akoya Biosciences).

Statistical analysis

The R package FactoMineR (version 2.3.0) was employed for principal component analysis (PCA). Heatmaps were drawn with the help of the pheatmap package (v.1.0.12; https://CRAN.R project.org). The subcellular localization was predicted by the WoLF PSORT (https://wolfpsort.hgc.jp/). The Motif-X software was employed to elucidate the model of 21 amino-acid-long sequences in distinct positions (10 amino acid residues upstream and 10 downstream of the Kla site) in all lactylated protein sequences. Furthermore, the IceLogo heatmap of 21 amino-acid compositions around Kla sites was acquired via IceLogo software (v1.0.2). The package ggplot2 (version 3.3.3) was utilized to generate the volcano plot. For the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment analysis, the R package clusterprofiler (version: 3.16.1) was used. The protein-protein interaction (PPI) networks of the differentially lactylated proteins were evaluated via the STRING database (http://string-db.org/) and visualized by the Cytoscape software (version 3.6.1). SPSS 24.0 software (SPSS, Inc., Chicago, IL, USA) was utilized for all the statistical assessments. The Student’s t-test was conducted to assess the statistical significance differences in the normally distributed data, while for the non-normal data, the Mann-Whitney test was carried out. Significant differences were indicated by Kla levels with a two-sided P value <0.05 and a fold change of >1.5.

Results

Kla induces ESCC metastasis

To investigate the level and function of Kla in ESCC metastasis, 14 treatment-naïve ESCC tissue samples were analyzed. Table 1 summarizes the baseline characteristics of the enrolled patients. The ESCC tissue samples were categorized into ESCC-LNM and ESCC-non-LNM (n=7/group). The levels of pan-Kla in ESCC tissues were confirmed via western blotting. Multiple protein bands with different molecular weights were observed, indicating the Kla of many proteins in ESCC samples. Furthermore, the ESCC-LNM samples indicated a higher abundance of Kla than ESCC-non-LNM samples (Figure 1), indicating that Kla was positively correlated with ESCC metastasis. This speculation was further confirmed by LC-MS/MS analysis. While, crotonylation, malonylation and β-hydroxybutyrylation did not change remarkably between the two groups (Figure S1).

Figure 1 (A) Coomassie-stained gel shows equal loading amounts; (B) Western blotting analysis for lysine lactylation between ESCC tissues with LNM (MEC) and ESCC tissues without LNM (NEC). ESCC, esophageal squamous cell carcinoma; Kla, lysine lactylation; LNM, lymph node metastasis; MEC, esophageal squamous cell carcinoma with lymph node metastasis; NEC, esophageal squamous cell carcinoma without lymph node metastasis.

Characterization of the lactylome in ESCC

For lactylome analysis (Figure 2A), three pairs of ESCC tissue samples with significantly different Kla levels were selected from each of the two groups (Table S1). The PCA showed a significant discrepancy between the two groups (Figure 2B).

Figure 2 (A) The schematic workflow of lactylome analysis employed in this study (n=3 per group); (B) PCA of lactylome in MEC and NEC; (C) column graph of omics data showing the number of spectrums, peptides, lactylation sites and lactylation-modified proteins identified by MS/MS; (D) heatmap of total 89 differentially modified proteins in MEC and NEC (fold change >1.5, P<0.05, by two-sided Student’s t-test); (E) the number of differentially modified proteins and Kla sites in NEC and MEC predicted by MS; (F) pie charts showing subcellar distribution of Kla-modified proteins; (G,H) sequence logo of the lactylation site motif and conservation of lactylation sites identified by the Motif-X software. Kla, lysine lactylation; LC-MS/MS, liquid chromatography-tandem mass spectrometry; LNM, lymph node metastasis; MEC, esophageal squamous cell carcinoma with lymph node metastasis; MS/MS, tandem mass spectrometry; NEC, esophageal squamous cell carcinoma without lymph node metastasis; PCA, principal component analysis.

Taking advantage of the high scanning speed provided by timsTOF Pro mass spectrometry, a total of 3,059 Kla sites were identified in 1,036 proteins (Figure 2C). The quantitative comparison of lactylome between ESCC-LNM and ESCC-non-LNM tissues revealed increased Kla on proteins in ESCC-LNM (Figure 2D). Moreover, there were 48 markedly downregulated Kla sites in 29 proteins and 91 significantly upregulated Kla sites in 60 proteins in ESCC-LNM vs. ESCC-non-LNM (P<0.05, fold change >1.5, Figure 2E). In addition, Kla was globally elevated in ESCC with LNM. The data also revealed that differentially lactylated proteins were localized in various cellular compartments, and about 46.07% of these proteins were localized in the cytoplasm, whereas 19.2% were found in the nucleus (Figure 2F). This indicates that both histone and non-histone Kla modulate ESCC metastasis by regulating various biological processes. The amino acid sequences around the confirmed Kla sites were also compared, which showed possible Kla motifs (Figure 2G,2H).

Kla of ENO1 potentially contributes to ESCC metastasis

To further understand the biological role of the differentially lactylated proteins, the PPI network of these proteins was established based on the STRING protein interaction database with the help of the Cytoscape software (Figure 3A). The KEGG enrichment assay showed that the differentially lactylated proteins were substantially enriched in multiple metabolism-related pathways, including carbon metabolism, pentose phosphate pathway, glycolysis, amino acids biosynthesis, and gluconeogenesis (Figure 3A).

Figure 3 (A) Protein-protein interaction network analysis of the lactylation-modified protein and these proteins were significantly associated with the pathways indicated in antigen processing and presentation, pentose phosphate pathway, biosynthesis of amino acids, carbon metabolism, glycolysis and gluconeogenesis; (B,C) all identified Kla sites of ENO1 exhibited statistically upregulated lactylation in ESCC tissues with LNM compared with those without LNM; (D) conversation analysis of ENO1 K64, K71, K80, K81, K262, K406 and K420 among different species; (E) volcano plot depicting differentially Kla sites of the PPI network related to ENO1; (F) heatmap of top 20 differentially lactylation sites ranked by P value; (G) heatmap of top 20 differentially lactylation sites ranked by fold change. ENO1, enolase 1; ESCC, esophageal squamous cell carcinoma; Kla, lysine lactylation; LNM, lymph node metastasis; PPI, protein-protein interaction.

Since metabolism dysregulation is crucial for ESCC metastasis and Kla is common in metabolic enzymes (15), a key cell metabolism enzyme, ENO1, which regulates glycolysis, was selected for further analysis. In ESCC-LNM tissues, all 7 identified Kla sites of ENO1 indicated upregulated Kla compared to ESCC-non-LNM samples (Figure 3B,3C), suggesting that its enzymatic activity might be elevated in ESCC with LNM. Moreover, ENO1 K71, K80, K262, K406, and K420 were highly evolutionarily conserved among different species (Figure 3D). It was inferred that Kla of ENO1 may promote ESCC metastasis. Figure S2 shows the representative MS/MS spectra of lactylated ENO1.

Figure 3E indicates a volcano plot depicting different Kla sites observed on the PPI network of ENO1. The top 20 differentially modified Kla sites were ranked according to the fold change (Figure 3F) and P values (Figure 3G) and showed that ENO1-K64, ENO1-K80, ENO1-K81, and ENO1-K262 might be essential for ESCC metastasis.

The relevance of ENO1’s Kla levels to ESCC metastasis

The immunoprecipitation analysis of the ENO1’s Kla levels was carried out using ESCC cells (KYSE30, KYSE150, and KYSE510). Both transwell and wound healing assays were carried out to assess ESCC cell migration ability, which showed that increased Kla levels were related to strong metastatic ability (Figure 4A,4B). Moreover, ESCC tissue samples (pT2N1 vs. pT2N0 and pT3N1 vs. pT3N0) were utilized for TSA (tyramide signal amplification) multiplex immunofluorescence staining to verify the relationship between the Kla level of ENO1 protein and ESCC metastasis. The results demonstrated that ESCC-LNM tissues had higher ENO1 Kla levels than ESCC-non-LNM tissues (Figure 4C).

Figure 4 (A) The ability of ESCC cell migration using wound-healing assay and migration assay; (B) IB analyses of ENO1 IP products derived from ESCC cells; (C) representative immunofluorescent images of Kla (red) and ENO1 (green). ENO1, enolase 1; ESCC, esophageal squamous cell carcinoma; IB, IP, Kla, lysine lactylation.

Discussion

ESCC with LNM is considered a high-risk malignancy necessitating aggressive treatment strategies (16). Conventional chemoradiotherapy is often limited by severe side effects and suboptimal efficacy. Recently, several studies have investigated the molecular mechanism of ESCC; however, there are currently no effective molecularly targeted therapies for ESCC (17). Therefore, an in-depth analysis of the ESCC metastasis pathways is critical for the development of novel treatments. Posttranslational modifications add tremendous complexity to proteomes, and the functions of newly discovered Kla in ESCC are poorly defined. Our study analyzed the landscape of Kla in ESCC and indicated that protein Kla is associated with ESCC metastasis. Studying the link between Kla and ESCC metastasis may help develop novel drugs and improve patient’s prognosis.

A major hallmark of cancer is metabolic reprogramming. Tumor cells preferentially utilize glycolysis even under aerobic conditions (18), and elevated glycolysis yields a large amount of lactate, a metabolic waste product. Recently, it was observed that lactate is the primary source of substrates for Kla (19,20). Previous studies suggest that Kla is associated with cancer biology (21). Therefore, it was hypothesized that Kla is a crucial link between lactate, tumor metabolism, and tumor progression.

Zhang et al. were the first to report Kla in histone, demonstrating its role in regulating cancer cell metabolism (7). It has been found that except for histone Kla, Kla can occur on the non-histone protein (15,22,23). Currently, studies on non-histone Kla in ESCC remain poorly explored. Qiao et al. showed that hypoxia-mediated glycolysis promoted SHMT2 protein Kla, which then enhanced MTHFD1L levels and accelerated EC cell’s malignant progression (24). Li et al. found that hypoxia treatment promotes Axin1 protein Kla, glycolysis, and cancer stemness in EC cells (25). Our study analyzed Kla in clinical ESCC samples and cell lines to validate its association with ESCC metastasis.

In our study, it was observed that about 46.07% of the lactylated proteins were localized in the cytoplasm, indicating that many non-histone proteins were lactylated in ESCC samples. Functional enrichment analysis revealed that differentially lactylated proteins are heavily involved in glycolysis, the pentose phosphate pathway, and carbon metabolism. This suggests that Kla may actively rewire tumor cell metabolism to support the biosynthetic and energetic demands of invasion. Our findings, in line with prior reports, confirm that Kla frequently targets metabolic enzymes (15,26). ENO1 is one of the rate-limiting enzymes of glycolysis and is involved in cancer development and progression. Thus, ENO1 may be a promising tumor therapy target. The MS spectra confirmed that ENO1’s Kla level was greater in ESCC-LNM tissues relative to that in ESCC-non-LNM tissues, which was also validated by TSA multiplex immunofluorescence staining. Moreover, the ENO1-Kla levels of ESCC cell lines were positively correlated with cell migration ability. In addition, all determined Kla sites of ENO1 indicated statistically enhanced Kla in ESCC-LNM tissues relative to ESCC-non-LNM tissues. These results demonstrate that ENO1-Kla may promote ESCC metastasis, and targeting ENO1-Kla might be a potential strategy for ESCC treatment.

Based on its location, ENO1 acts as a multifunctional oncoprotein. In the cytoplasm, it converts 2-phosphoglycerate to phosphoenolpyruvate and modulates the Warburg effect (27). The abnormally increased Kla levels of ENO1 in metastatic ESCC tissues may increase its glycolytic activity, which in turn promotes lactate production, creating a positive feedback loop between Kla and glycolysis and facilitating ESCC metastasis. On the cell surface, ENO1 acts as a plasminogen receptor and increases tumor cell migration and invasion by promoting the degradation of extracellular matrix (28). Upregulated ENO1-Kla may increase ENO1 levels at the cell surface, promoting invasion and metastasis of ESCC cells. Thus, ENO1-Kla likely promotes ESCC metastasis through both metabolic reprogramming and non-metabolic, extracellular matrix-remodeling mechanisms.

This study furnishes valuable evidence for future studies on the function of Kla in ESCC. The findings may help the development of targeted drugs for ESCC. However, there are some limitations, such as the sample size being small, and the specific modification sites in ENO1 may need further validation.

Conclusions

The study found a positive correlation between Kla and ESCC metastasis. Furthermore, ENO1-Kla potentially promotes esophageal cancer metastasis and it may be a promising treatment target and a predictive biomarker of ESCC metastasis.

Acknowledgments

We thank Li Li, Fei Chen and Chunjuan Bao from the Institute of Clinical Pathology, West China Hospital of Sichuan University, for the technical support in histological staining.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2204/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2204/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2204/prf

Funding: The study was approved by the Science and Technology Plan Project of Sichuan Province (No. 2023YFS0304) and “Qimingxing” Research Fund for Young Talents (No. HXQMX0097).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2204/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Board of West China Hospital, Sichuan University (No. approval ID). Informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Morgan E, Soerjomataram I, Rumgay H, et al. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology 2022;163:649-658.e2. [Crossref] [PubMed]
3. Akutsu Y, Kato K, Igaki H, et al. The Prevalence of Overall and Initial Lymph Node Metastases in Clinical T1N0 Thoracic Esophageal Cancer: From the Results of JCOG0502, a Prospective Multicenter Study. Ann Surg 2016;264:1009-15. [Crossref] [PubMed]
4. Yang Y, Xue L, Chen X, et al. Lymph Node Metastasis for pN+ Superficial Esophageal Squamous Cell Carcinoma. Thorac Cancer 2025;16:e15504. [Crossref] [PubMed]
5. Zhang Y, Wang J, Li C, et al. Protein lactylation in cancer and other pathologies: Epigenetic regulation of glycolysis and its therapeutic perspectives. Semin Cancer Biol 2026;118:28-43. [Crossref] [PubMed]
6. He Y, Song T, Ning J, et al. Lactylation in cancer: Mechanisms in tumour biology and therapeutic potentials. Clin Transl Med 2024;14:e70070. [Crossref] [PubMed]
7. Zhang D, Tang Z, Huang H, et al. Metabolic regulation of gene expression by histone lactylation. Nature 2019;574:575-80. [Crossref] [PubMed]
8. Chen H, Li Y, Li H, et al. NBS1 lactylation is required for efficient DNA repair and chemotherapy resistance. Nature 2024;631:663-9. [Crossref] [PubMed]
9. Jing F, Zhu L, Zhang J, et al. Multi-omics reveals lactylation-driven regulatory mechanisms promoting tumor progression in oral squamous cell carcinoma. Genome Biol 2024;25:272. [Crossref] [PubMed]
10. Li F, Si W, Xia L, et al. Positive feedback regulation between glycolysis and histone lactylation drives oncogenesis in pancreatic ductal adenocarcinoma. Mol Cancer 2024;23:90. [Crossref] [PubMed]
11. Li G, Wang D, Zhai Y, et al. Glycometabolic reprogramming-induced XRCC1 lactylation confers therapeutic resistance in ALDH1A3-overexpressing glioblastoma. Cell Metab 2024;36:1696-1710.e10. [Crossref] [PubMed]
12. Yang L, Niu K, Wang J, et al. Nucleolin lactylation contributes to intrahepatic cholangiocarcinoma pathogenesis via RNA splicing regulation of MADD. J Hepatol 2024;81:651-66. [Crossref] [PubMed]
13. Zhou J, Yang Y, Zhang H, et al. Overexpressed COL3A1 has prognostic value in human esophageal squamous cell carcinoma and promotes the aggressiveness of esophageal squamous cell carcinoma by activating the NF-κB pathway. Biochem Biophys Res Commun 2022;613:193-200. [Crossref] [PubMed]
14. Zhang H, Zhang Y, Wang H, et al. Global proteomic analysis reveals lysine succinylation contributes to the pathogenesis of aortic aneurysm and dissection. J Proteomics 2023;280:104889. [Crossref] [PubMed]
15. Wan N, Wang N, Yu S, et al. Cyclic immonium ion of lactyllysine reveals widespread lactylation in the human proteome. Nat Methods 2022;19:854-64. [Crossref] [PubMed]
16. Leng C, Cui Y, Yang H, et al. Development and validation of a nomogram for predicting long-term survival in pN + esophageal squamous cell carcinoma treated using radical resection without neoadjuvant therapy. Ann Med 2025;57:2568120. [Crossref] [PubMed]
17. Ooki A, Osumi H, Chin K, et al. Potent molecular-targeted therapies for advanced esophageal squamous cell carcinoma. Ther Adv Med Oncol 2023;15:17588359221138377. [Crossref] [PubMed]
18. Fendt SM. 100 years of the Warburg effect: A cancer metabolism endeavor. Cell 2024;187:3824-8. [Crossref] [PubMed]
19. Hu XT, Wu XF, Xu JY, et al. Lactate-mediated lactylation in human health and diseases: Progress and remaining challenges. J Adv Res 2025;75:229-48. [Crossref] [PubMed]
20. Zhang D, Gao J, Zhu Z, et al. Lysine L-lactylation is the dominant lactylation isomer induced by glycolysis. Nat Chem Biol 2025;21:91-9. [Crossref] [PubMed]
21. Li H, Sun L, Gao P, et al. Lactylation in cancer: Current understanding and challenges. Cancer Cell 2024;42:1803-7. [Crossref] [PubMed]
22. Yu H, Zhu T, Ma D, et al. The role of nonhistone lactylation in disease. Heliyon 2024;10:e36296. [Crossref] [PubMed]
23. Sun L, Zhang Y, Yang B, et al. Lactylation of METTL16 promotes cuproptosis via m(6)A-modification on FDX1 mRNA in gastric cancer. Nat Commun 2023;14:6523. [Crossref] [PubMed]
24. Qiao Z, Li Y, Li S, et al. Hypoxia-induced SHMT2 protein lactylation facilitates glycolysis and stemness of esophageal cancer cells. Mol Cell Biochem 2024;479:3063-76. [Crossref] [PubMed]
25. Li Q, Lin G, Zhang K, et al. Hypoxia exposure induces lactylation of Axin1 protein to promote glycolysis of esophageal carcinoma cells. Biochem Pharmacol 2024;226:116415. [Crossref] [PubMed]
26. Yang Z, Yan C, Ma J, et al. Lactylome analysis suggests lactylation-dependent mechanisms of metabolic adaptation in hepatocellular carcinoma. Nat Metab 2023;5:61-79. [Crossref] [PubMed]
27. Li Y, Liu L, Li B. Role of ENO1 and its targeted therapy in tumors. J Transl Med 2024;22:1025. [Crossref] [PubMed]
28. Principe M, Borgoni S, Cascione M, et al. Alpha-enolase (ENO1) controls alpha v/beta 3 integrin expression and regulates pancreatic cancer adhesion, invasion, and metastasis. J Hematol Oncol 2017;10:16. [Crossref] [PubMed]