Histone lactylation increases CXCL1 expression for neutrophil infiltration and immune escape in pancreatic cancer

Domain: neuroscience
Published: 2026-02-09
Editorial outcome: major_revision

Abstract
Aerobic glycolysis and lactate have been shown to modulate tumor microenvironment (TME) and disease progression. Lactate-mediated histone lysine lactylation (Kla) is a newly recognized epigenetic modification whose biological function remains poorly understood. Here, through integrated bioinformatic and experimental analyses, we demonstrate that glycolysis-derived lactate induces histone H3 lysine 18 lactylation (H3K18la) and up-regulates the expression of chemokine C-X-C motif Ligand 1 (CXCL1), thereby recruiting neutrophils and inducing immunosuppression in pancreatic cancer. Moreover, our data suggest that p300/CBP-associated factor (PCAF) functions as a histone lactyltransferase that transcriptionally activates CXCL1 expression. Finally, we reveal that combinational treatment with bromosporine (a PCAF inhibitor) and anti-PD-1 antibody exhibits a synergistic antitumor effect on both subcutaneous and orthotopic tumor models of pancreatic cancer. Taken together, our study not only identifies a mechanism by which the aerobic glycolysis-induced Lactate-PCAF-H3K18la-CXCL1 pathway mediates neutrophil infiltration and immunosuppression, but also develops a potential therapeutic strategy for pancreatic cancer.

Introduction
Pancreatic adenocarcinoma (PAAD), of which over 80% of cases are pancreatic ductal adenocarcinoma (PDAC), is the third-leading cause of cancer-related death due to limited therapeutic options1. Immune escape mediated by an immunosuppressive microenvironment is a key reason for the ineffective immune checkpoint blockade (ICB) therapy in PDAC2–4. Neutrophils, the most abundant myeloid cells in human blood and a critical component of the tumor microenvironment (TME), have been suggested to play important roles in tumor progression and therapy resistance5–7. Therefore, understanding the immune suppression mechanism may enhance the therapeutic effectiveness of ICB and develop novel therapeutic strategies against PDAC.

Metabolic reprogramming to aerobic glycolysis is a hallmark of tumor cells8. Accumulating evidence suggests that aerobic glycolysis may promote tumor immune escape through metabolic communication between tumor and immune cells, mediated by glycolytic products. For example, tumor-cell-derived lactate stimulates the differentiation of CD4+ T cells9,10, promotes the polarization of tumor-associated macrophage (TAM)9,11, and inhibits natural killer (NK) cells9,12 and effector T cells (Teffs)9,12. Moreover, glycolysis pathways in tumor cells may also regulate the expression of immunomodulators, such as CXCL1013, PD-L114, and TNF-α15. However, the potential roles of these glycolysis pathways in regulating neutrophil-mediated immune escape remain largely unclear.

Epigenetic remodeling has emerged as a newly recognized feature of tumors in recent years16. Histone modification is one of the most fundamental epigenetic types and plays a key role in physiological and pathological conditions17. As the end product of aerobic glycolysis, lactate was first identified as a mediator of histone L-lactylation in 2019, which promotes macrophage polarization18. Histone L-lactylation has been associated with tumor cell proliferation, metastasis, and immune escape in many tumors, such as ocular melanoma, lung cancer, head and neck squamous cell carcinoma, and colorectal cancer19–22. However, the function of histone L-lactylation in pancreatic cancer remains to be further elucidated. Another pivotal issue related to histone L-lactylation is the identification of its writer. Several histone acetyltransferases, such as P300/CBP18,23 and GCN523,24, along with alanyl-tRNA synthetase, AARS125,26, and AARS227,28 have been shown to function as lactyltransferase; whether there are new lactyltransferases in pancreatic cancer requires further investigation.

In this study, we conduct bioinformatic analysis and experimental studies to assess the effect of aerobic glycolysis on the tumor immune microenvironment, and comprehensively analyze the relationship between the levels of glycolysis and immune cell infiltrations. We reveal that aerobic glycolysis promotes tumor immune evasion by promoting neutrophil infiltration through lactate-mediated H3K18la in pancreatic cancer. In addition, our data suggest that PCAF functions as a potential histone lactyltransferase and directly activates the Cxcl1 expression at the transcriptional level. Furthermore, we demonstrate that a combinational treatment with a PCAF inhibitor and an anti-PD-1 antibody induced a synergistic antitumor efficacy in the orthotopic mouse model of pancreatic cancer. Our study has identified a novel mechanism that the Lactate-PCAF-H3K18la-CXCL1 pathway mediates the immune evasion in pancreatic cancer, which may also help develop novel therapeutic strategies against pancreatic cancer.

Results
Glycolysis mediates neutrophil recruitment and promotes the progression of pancreatic cancer
To evaluate the effect of glycolysis on the tumor immune microenvironment, we first comprehensively analyzed the relationship between the immune cell infiltration and glycolysis. The results showed that neutrophils were enriched in tumor patients with high glycolysis, whereas CD8+ T cells were enriched in patients with low glycolysis (Fig. 1A). Correlation analysis revealed that the infiltration of neutrophils and CD8+ T cells was positively and negatively correlated with glycolysis, respectively (Fig. 1B and Supplementary Fig. S1A). In addition, the levels of glycolysis and neutrophil infiltration were negatively correlated with patient survival probability (Fig. 1C). Interestingly, a worse prognosis was observed in patients with high neutrophil infiltration, along with high CD8+ T cell infiltration, but not in patients with low CD8+ T cell infiltration (Supplementary Fig. S1B). Moreover, in addition to pancreatic cancer, we also observed similar results in other tumor types (Supplementary Fig. S1C–F).

To further analyze whether glycolysis affects neutrophil infiltration in pancreatic cancer, we used a hexokinase (HK) inhibitor (2-deoxy-D-glucose, 2DG) and the shRNA targeting LDH (silenced both Ldha and Ldhb, LDH-knockdown) to inhibit glycolysis in tumor cells (Fig. 1D). We found that tumor growth in the 2DG treatment group was significantly inhibited compared to the control group in the KPC subcutaneous implantation tumor model (Supplementary Fig. S2A–G). Treatment with 2DG significantly decreased intratumoral lactate levels (Supplementary Fig. S2H). Then, we conducted mass cytometry (CyTOF) and identified 12 distinct cell clusters based on the differential expression profile of 41 markers (Supplementary Fig. S2I). The t-distributed stochastic neighbor embedding (t-SNE) analysis showed that tumor-infiltrating neutrophils decreased, whereas CD8+ T cells increased significantly in the 2DG-treatment group (Fig. 1E, F, and Supplementary Fig. S2J–L). Additional analysis by flow cytometry confirmed the reduction in tumor-infiltrating neutrophils after 2DG treatment (Supplementary Fig. S3A, C). In contrast, the proportions of CD8+ T cells were significantly enriched in tumor tissues treated with 2DG (Supplementary Fig. S3B, D). To rule out the influence of tumor size on the number of infiltrating immune cells, we examined the infiltration levels of neutrophils and CD8+ T cells at the early stage of 2DG treatment (Supplementary Fig. S2A). After 2 days of 2DG treatment, the tumor size showed little difference between the 2DG and control treatment groups (Supplementary Fig. S3E–G). However, the lactate levels had already decreased after 2 days of 2DG treatment (Supplementary Fig. S3H). Flow cytometry analysis showed that the proportion of neutrophils in the tumor microenvironment was significantly decreased following 2 days of 2DG treatment, whereas CD8+ T cells were markedly enriched in tumors (Supplementary Fig. S3I, J). Furthermore, in the orthotopic transplanted tumor model, we also found that 2DG treatment inhibited tumor growth, with reduced infiltration of neutrophils and increased infiltration of CD8+ T cells (Fig. 1G–K). Flow cytometry results revealed that the percentage of tumor-infiltrating GZMB+CD8+ T cells was significantly higher, but exhausted PD-1+CD8+ T cells were unchanged (Fig. 1L, M).

To exclude the effect of 2DG on non-tumor cells in vivo, we double-silenced Ldha and Ldhb (LDH-knockdown) in KPC cells using the shRNAs, and then subcutaneously injected control or LDH-knockdown KPC cells into the C57BL/6J mice (Supplementary Fig. S4A). Compared with the control group, mice that received LDH-knockdown KPC cells showed a significantly smaller tumor burden (Supplementary Fig. S4B–G). We also observed similar changes (i.e, reduced neutrophils and enriched CD8+ T cells) in tumor tissues from the subcutaneous tumor model of LDH knockdown KPC cells (Supplementary Fig. S4H, I). Therefore, our findings suggest that high glycolysis may enrich neutrophils and inhibit the infiltration of CD8+ T cells, subsequently altering the tumor microenvironment and promoting tumor progression in PDAC.

Glycolysis induces immunosuppression mediated by neutrophils
To further investigate whether glycolysis-induced immunosuppression depends on neutrophils in pancreatic cancer, we depleted CD11b+Ly6G+ neutrophils in an orthotopic transplanted tumor model using anti-Ly6G antibody (Fig. 1N). Similar to the results of subcutaneously transplanted tumors, the LDH-knockdown group showed a significant reduction in tumor burden (Fig. 1O, P). However, there was less change in tumor burden between the control and LDH-knockdown groups treated with anti-Ly6G antibody compared with their isotype control (Fig. 1O, P). Flow cytometry results showed that the proportion of neutrophils in the tumor microenvironment of the LDH knockdown group was significantly decreased, whereas CD8+ T cells and GZMB+CD8+ T cells were markedly enriched in tumors (Fig. 1Q–S). Furthermore, neutrophil depletion also restored the abundance and functional status of CD8+ T cells (Fig. 1Q–S). Previous studies have shown that neutrophils contribute to pancreatic cancer progression by inhibiting the recruitment and function of CD8+ T cells29,30. To examine whether neutrophil depletion can reverse glycolysis-mediated tumor-promoting effects through reactivating CD8+ T cells in vivo, we further depleted CD8+ T cells in mice (Fig. 1N). The results showed that depleting CD8+ T cells rescued the tumor-suppressing effect of neutrophil depletion (Fig. 1T, U, and Supplementary Fig. S4J, K). Taken together, these findings suggest that glycolysis may induce immunosuppression mediated by neutrophils and play an oncogenic role in the tumor progression of pancreatic cancer.

Glycolysis enhances neutrophil infiltration by up-regulation of Cxcl1 expression
We next investigated the mechanism underlying the recruitment of neutrophils induced by glycolysis. Since chemokines are well known to regulate the migration of immune cells31, we performed RNA-seq in PANC1 and BxPC3 cells with or without treatment of 2DG and found that Cxcl1 was the most significant differentially expressed chemokine (Fig. 2A). Additional analysis of TCGA data also revealed that Cxcl1 was highly expressed in pancreatic cancer patients and was associated with poor prognosis (Supplementary Fig. S5A, B). We also examined the expression level of Cxcl1 in vitro in human PANC1 and BxPC3 cell lines, as well as in mouse KPC and PANC02 cell lines, following glycolysis inhibition with either 2DG or shRNAs silencing of LDH (Supplementary Fig. S5C). The results indicated that inhibition of glycolysis significantly reduced the intracellular Cxcl1 mRNA levels (Fig. 2B, C) and extracellular CXCL1 protein levels (Fig. 2D, E). Immunohistochemical staining showed that CXCL1 expression was decreased in tumor tissues treated with 2DG or LDH-knockdown compared with the controls (Fig. 2F). We also found that secreted CXCL1 in the serum of tumor-bearing mice treated with 2DG or LDH-knockdown was significantly reduced compared with the control mice (Fig. 2G and Supplementary Fig. S5D). Moreover, the serum CXCL1 level in pancreatic cancer patients was significantly higher than in healthy controls (Fig. 2H). Taken together, these findings suggest that glycolysis may regulate Cxcl1 expression in pancreatic cancer cells.

Furthermore, we performed the cell migration assays to evaluate the ability of glycolytically regulated CXCL1 to recruit neutrophils (Fig. 2I). We isolated neutrophils from human peripheral blood and mouse bone marrow (Supplementary Fig. S5E). Firstly, we confirmed the immunosuppressive activity of neutrophils by measuring the T cell proliferation (Fig. 2J). The recombinant human and mouse CXCL1 proteins were confirmed by western blot, ELISA, and the migration ability of neutrophils (Supplementary Fig. S5F–I), respectively. Subsequent chemotaxis assays revealed that conditional culture medium from cancer cells treated with 2DG or LDH-knockdown recruited significantly fewer neutrophils compared to the control groups which could be effectively restored by the addition of recombinant human or mouse CXCL1 protein (Fig. 2K and Supplementary Fig. S6A). Moreover, the conditional culture medium from the treated cancer cells did not affect neutrophil survival, ROS production, and degranulation (Supplementary Fig. S6B–D). CXCL1 mainly mediates neutrophil migration through the receptor CXCR1/232,33. We found that following treatment with the CXCR1/2 inhibitor SX-682 or Navarixin, the difference in neutrophil migration between the 2DG treatment or LDH-knockdown group and the control group was significantly reduced or eliminated (Fig. 2L and Supplementary Fig. S6E). Furthermore, the tumor growth inhibition observed following LDH-knockdown could be partially reversed by restoring Cxcl1 expression in vivo (Fig. 2M and Supplementary Fig. S6F). Finally, flow cytometry results indicated that the reduction in neutrophil infiltration caused by LDH-knockdown was restored after overexpression of Cxcl1 (Fig. 2N). Collectively, our data suggest that up-regulation of Cxcl1 expression and secretion by glycolysis may enrich neutrophils in tumor tissues and induce an immunosuppressive tumor microenvironment.

Glycolysis-derived lactate enhances H3K18la modification and promotes the expression of Cxcl1
We next investigated the mechanism underlying the transcriptional activation of Cxcl1 by glycolysis. Lactate has been suggested to promote the expression of Cxcl134. In addition, recent studies have identified lactate-mediated histone lactylation as a post-transcriptional modification to direct activation of gene transcription18. There are two stereoisomeric forms of lysine lactylation (Kla): L-lactyl-lysine and D-lactyl-lysine35. Recent studies have clearly demonstrated that L-lactyl-lysine is the primary responder to glycolysis and the Warburg effect35. Therefore, we speculated that histone L-lactylation may directly activate Cxcl1 expression at the transcriptional level. Indeed, western blot showed increased L-lactyl-lysine (PanKla) in pancreatic cancer tissues compared with normal tissues, and H3K18la showed the most significant changes (Fig. 3A and Supplementary Fig. S7A). Immunohistochemical (IHC) results also showed that H3K18la levels were up-regulated in pancreatic cancer tissues and cell lines (Fig. 3B and Supplementary Fig. S7B). We then examined the effects of aerobic glycolysis on histone lactylation using glycolysis inhibitor (2DG), glycolysis agonist (rotenone), and LDH-knockdown in human and mouse pancreatic cancer cell lines, respectively (Fig. 3C). The levels of PanKla and H3K18la consistently reduced in the cancer cells treated with 2DG or LDH-knockdown (Fig. 3D and Supplementary Fig. S7C). In contrast, the levels of PanKla and H3K18la consistently increased in cancer cells treated with rotenone (Fig. 3E). Consistent with the results in vitro, PanKla and H3K18la levels were also significantly reduced in mouse tumor tissues treated with 2DG or LDH-knockdown (Fig. 3F, G and Supplementary Fig. S7D, E). Furthermore, the reduction in H3K18la levels induced by 2DG or LDH-knockdown was recovered after treatment with sodium lactate (Fig. 3H, I). These findings suggest that aerobic glycolysis-derived lactate can enhance H3K18la modification.

To understand the potential functional significance of H3K18la modification, we performed CUT&Tag assays using antibodies against PanKla and H3K18la to identify candidate genes regulated by H3K18la in pancreatic cancer (Fig. 3J). The 2DG-treated group showed a noticeable reduction of PanKla peaks and H3K18la peaks in the transcription start site (TSS) region compared with the control (Fig. 3K). KEGG analysis of the down-regulated H3K18la binding gene at the promoter regions in the 2DG-treated group revealed enrichment in the pathways associated with cancer (Supplementary Fig. S7F). Moreover, we identified 9 genes that exhibited significantly reduced mRNA levels and reduced enrichment of the H3K18la signal at the promoter region upon 2DG treatment but up-regulated mRNA levels in PDAC tissues by analyzing the overlapping genes among CUT&Tag, RNA-seq, and TCGA database (Fig. 3L). In particular, Cxcl1 was one of the most significantly changed genes. Furthermore, we investigated whether H3K18la could directly regulate Cxcl1 expression at the transcriptional level. Specifically, the called peaks showed that the levels of PanKla and H3K18la at the promoter regions of Cxcl1 were noticeably reduced in cancer cells treated with 2DG (Fig. 3M). A quantitative chromatin immunoprecipitation analysis indicated that the PanKla and H3K18la levels on Cxcl1 promoters were significantly enriched (Fig. 3N). In addition, the decreased mRNA levels of Cxcl1 by 2DG treatment could be recovered after sodium lactate treatment (Fig. 3O). We then performed IHC analyses of 21 human PDAC tissues and revealed that the levels of CXCL1 and H3K18la were positively correlated (Fig. 3P). These results indicate that H3K18la modification may directly activate the transcription of Cxcl1 in pancreatic cancer cells.

PCAF functions as a lactyltransferase for H3K18la modification
A number of histone acetyltransferases (HATs) have been reported to function as lactyltransferase23. However, the writer who promotes histone lactylation in pancreatic cancer cells remains unclear. Here, we screened the existing histone acetyltransferase inhibitors to identify lactyltransferase that may regulate H3K18la in pancreatic cancer cells (Supplementary Fig. S8A). The western blot results showed that the levels of H3K18la decreased significantly in tumor cells treated with bromosporine (Supplementary Fig. S8B), an inhibitor for PCAF, suggesting that PCAF may function as a potential lactyltransferase in pancreatic cancer. To further explore whether PCAF, a member of the GNAT (Gcn5-related N-acetyltransferase) sub-family of histone acetyltransferases, is a potential lactyltransferase, we performed in silico molecular docking analysis. We docked lactyl coenzyme A (lactyl-CoA) into the structure of PCAF (Protein Data Bank (PDB): 1CM0). Lactyl-CoA was well accommodated in the cofactor pocket of PCAF, similar to the structure of the acetyl coenzyme A (acetyl-CoA)–PCAF complex (Fig. 4A). The co-immunoprecipitation (Co-IP) assays showed that H3K18la interacted with PCAF (Fig. 4B). We then treated multiple pancreatic cancer cell lines with two inhibitors of PCAF, bromosporine and Embelin, and both of them exhibited a dose-dependent decrease in H3K18la (Fig. 4C, D). In addition, when Pcaf was knocked down in PANC1, BxPC3, and KPC cells, the levels of H3K18la were decreased (Fig. 4E and Supplementary Fig. S8C). Moreover, PCAF-mediated histone H3K18 lactylation was confirmed with an in vitro lactylation assay (Fig. 4F). Previous studies have reported that the acetyltransferases P300 and GCN5 can catalyze the lactylation of histone H3 K1823. Our findings demonstrated that PCAF exhibited similar enzymatic activity with P300 and GCN5, and was able to catalyze H3 K18 lactylation in pancreatic cancer cells (Supplementary Fig. S8D, E). The mRNA and secreted protein levels of Cxcl1 in the PCAF-inhibited group were also significantly reduced compared with the control (Fig. 4G, H), consistent with previous results. We also observed similar results in cancer cells after Pcaf knockdown (Fig. 4I and Supplementary Fig. S8F). In addition, we examined the effects of bromosporine on lysine lactylation and lysine acetylation. The western blot results indicated that the levels of H3K18la and H3K18ac decreased in a dose-dependent manner with the treatment of bromosporine, but the reduction level of H3K18la was the most significant (Supplementary Fig. S8G). Interestingly, H4K8ac remains unchanged at the current concentration gradient (Supplementary Fig. S8G). The role of H3K18la, H3K18ac, and H4K8ac in the direct transcriptional regulation of Cxcl1 was further analyzed following bromosporine treatment. The results showed that the enrichment effect of H3K18la on Cxcl1 was significantly reduced after bromosporine treatment (Supplementary Fig. S8H). However, H3K18ac and H4K8ac did not show any differences (Supplementary Fig. S8H).

We further explored the function of PCAF in vivo by an orthotopic transplantation tumor model of pancreatic cancer (Fig. 4J). The tumor growth in the bromosporine-treated group was significantly inhibited compared to that in the vehicle-treated group (Fig. 4K, L). Consistent with the results in vitro, H3K18la levels were also significantly reduced in bromosporine-treated mouse tumor tissues, while H3K18ac and H4K8ac showed no significant changes (Fig. 4M, and Supplementary Fig. S8I). We also found that the secreted CXCL1 in the serum of tumor-bearing mice treated with bromosporine decreased significantly compared with the vehicle (Fig. 4N). Flow cytometry analysis showed that the number of tumor-infiltrating neutrophils decreased significantly, whereas the number of CD8+ T cells increased in the bromosporine-treated group (Fig. 4O, P). Furthermore, flow cytometry results revealed that the percentage of tumor-infiltrating GZMB+CD8+ T cells was significantly higher, but exhausted PD-1+CD8+ T cells were unchanged (Fig. 4Q, R). Similar results were observed in the KPC subcutaneous implantation tumor model, and the mouse body weight was not affected (Supplementary Fig. S8J–U).

Cell migration assays indicated that the conditioned culture medium from cancer cells with Pcaf-knockdown recruited fewer neutrophils compared with the control, which could be rescued by recombinant human CXCL1 protein (Fig. 4S). Moreover, we performed IHC analyses of 21 human PDAC tissues and revealed that the levels of PCAF and H3K18la were positively correlated (Fig. 4T). Taken together, these data suggest that PCAF functions as a lactyltransferase for H3K18la in pancreatic cancer.

PCAF inhibitor combined with anti-PD-1 antibody may become a novel therapeutic strategy for pancreatic cancer
Clinical studies have shown that ICB therapy does not benefit patients with pancreatic cancer2,4, emphasizing the necessity of formulating rational combinational therapies. To visualize the immune contexture shaped by H3K18la, we performed multiplex immunofluorescence on human PDAC tissues and observed that regions with higher H3K18la and CXCL1 signals often coincided with increased neutrophils but fewer CD8+ T cells in the same patient tissue (Supplementary Fig. S9). Conversely, H3K18la-low regions showed the opposite immune cell landscape. We investigated whether the inhibition of PCAF could enhance the efficacy of anti-PD-1 antibodies in two pancreatic cancer mouse models. In the PANC02 subcutaneous implantation tumor model, we combined PCAF inhibitor bromosporine with anti-PD-1 antibody and revealed an additive effect on tumor growth inhibition (Fig. 5A–D), without affecting mouse body weight (Supplementary Fig. S10A–D). Consistently, IHC staining showed that combinational therapy with bromosporine and anti-PD-1 antibody synergistically suppressed Ki67 positive tumor cells (Supplementary Fig. S10E), decreased neutrophil infiltration, and enhanced CD8+ T cell infiltration in tumor tissues (Fig. 5E and Supplementary Fig. S10E). Moreover, bromosporine alone or in combination with anti-PD-1 antibody reduces the levels of H3K18la in tumor tissues (Fig. 5F) and the levels of secreted CXCL1 in serum (Fig. 5G).

Then, we further assessed the therapeutic effect of bromosporine combined with anti-PD-1 antibody in a pancreatic cancer orthotopic transplantation tumor model (Fig. 5H). Simultaneous blockade of PCAF and PD-1 could markedly attenuate the tumor burden compared to the monotherapy group (Fig. 5I, J). Flow cytometric analysis showed that the combination of bromosporine and PD-1 blockade synergistically decreased the proportion of infiltrated neutrophils and increased CD8+ T cell infiltration (Fig. 5K, L). Meanwhile, flow cytometric results revealed that the percentage of tumor-infiltrating GZMB+CD8+ T cells was significantly higher and exhausted PD-1+CD8+ T cells were significantly lower in the combinational therapy compared to control (Fig. 5M, N). Moreover, western blot analysis also showed that the levels of H3K18la were decreased in bromosporine alone or in combination with anti-PD-1 antibody in tumor tissues (Fig. 5O). Furthermore, compared to other groups, the survival time was also significantly prolonged after combinational treatment with bromosporine and anti-PD-1 antibody (Fig. 5P, Q). Taken together, our findings demonstrate that PCAF inhibitors could significantly enhance the efficacy of anti-PD-1 antibodies by reducing neutrophil infiltration in pancreatic cancer.

Methods
Mice
In this study, male C57BL/6J mice (6–8 weeks old) were obtained from GemPharmatech Co., Ltd. The mice were housed in the Specific Pathogen Free (SPF) animal facility at the First Affiliated Hospital of Nanchang University. Prior to the initiation of the experiments, a one-week acclimation period was allowed for the mice to adjust to the laboratory environment. All mice were housed under controlled conditions with a 12 h light/dark cycle, a temperature range of 22-24°C, and 40-70% humidity. Throughout the study, they had continuous free access to food (Beijing Keao Xieli Feed Co., Ltd.) and water. All the animal experiments were conducted in strict accordance with the ethical standards for the welfare of experimental animals and were approved by the Ethics Committee for Animal Welfare at the First Affiliated Hospital of Nanchang University (CDYFY-IACUC-202407QR128). The maximal tumor burden permitted was 1500 mm³ for subcutaneous tumors or a palpable diameter exceeding 1.5 cm or clear signs of abdominal distension for orthotopic tumors. According to our approved protocol, mice were monitored daily and euthanized immediately upon observation of predefined humane endpoints, including neurological deficits, persistent lethargy, impaired mobility, or seizures.

Subcutaneous pancreatic cancer mouse model
PDAC cells were mixed with Matrigel (Corning, #354234) at a ratio of 3:1, and 100 μL of the suspension was injected subcutaneously into the right flank of 6–8 weeks-old male C57BL/6J mice (PANC02 with 6×106 cells per mouse, KPC-luc with 3×106 cells per mouse). Treatment was initiated once the subcutaneous tumor volume reached 100–200 mm3. Tumor volume was measured daily using calipers and calculated using the formula: Volume = 0.52 × length × width2. Upon completion of the treatment, mice were euthanized, and the corresponding tissues were prepared for further recording or examination. The treatment schedule is depicted in the figures in the manuscript and described as following: (1) The treatments of vehicle/2DG (800 mg/kg, i.p., once daily) was initiated on day 7 post-implantation and continued for 2 or 8 days; (2) Administration of vehicle/bromosporine (30 mg/kg, i.p., once a day) was initiated on day 9 post-implantation and continued for a total of 11 doses; (3) For combinational treatment, the administration of bromosporine (30 mg/kg, i.p., 3 times a week) or anti-PD-1 antibody (200 μg/mouse, i.p., twice a week, BioXCell, #BE0146)/IgG2a antibody (200 μg/mouse, i.p., twice a week, BioXCell, #BE0089) began on day 13 post-implantation. Mice received two 5-day cycles of therapy, separated by a 2-day rest period; (4) For the shNTC/shLDH KPC-luc subcutaneous implantation model, shNTC/shLDH KPC-luc cells were implanted subcutaneously into C57BL/6J mice. The mice were euthanized on the 16th day after the implantation.

Orthotopic pancreatic cancer mouse model
Male C57BL/6J mice (6–8 weeks old) were implanted orthotopically with a 50 μL cell suspension containing 2×106 KPC-luc cells into the pancreas. Tumors were monitored by bioluminescence imaging (D-luciferin potassium salt, Biodragon, #BDXB0116, i.p., 150 mg/kg). The IVIS Lumina Series III in vivo imaging system was employed to capture the bioluminescent signals emitted by the tumors. Then, the mice were subjected to different treatments as shown in the figures and described as following: (1) Vehicle/2DG treatment was administered (800 mg/kg, i.p., once daily) from day 7 for 9 consecutive days; (2) For neutrophil depletion, these mice received anti-IgG2a (0.25 mg/mouse, i.p.) or anti-Ly6G antibody (0.25 mg/mouse, i.p., BioXCell, #BE0075-1) treatment once a day from day 3 post-implantation. After 11 consecutive days of antibody administration, the mice were euthanized, the peripheral blood was harvested for flow cytometry analysis to assess the efficiency of neutrophil depletion; (3) For CD8+ T cells depletion, mice received an intraperitoneal injection of anti-IgG2a or anti-CD8 antibody (Selleck, #A2102) treatment (0.2 mg/mouse, i.p.) 2 days before implantation. To sustain CD8+ T cells depletion, anti-IgG2a or anti-CD8 antibody was administered on day 3, 6, 10 and 13 post-implantation. To confirm the efficacy of CD8+ T cell depletion, mice were euthanized on the 14th day after implantation, and the peripheral blood was harvested for flow cytometry analysis; (4) The administration of vehicle/bromosporine (30 mg/kg, i.p., once a day) began on day 7 post-implantation with the treatment duration lasting for 7 consecutive days; (5) For combinational treatment with bromosporine and anti-PD-1 antibody, the administration of bromosporine (30 mg/kg, i.p., 3 times a week) or anti-PD-1 antibody (0.2 mg/mouse, i.p. twice a week) began on day 6 post-implantation. The tumor was detected through bioluminescence imaging on day 12. After the administration of two 5-day cycles of therapy, separated by a 2-day rest period, six mice per group were euthanized for western blot and flow cytometry analysis. The left 15 mice in each group were used for survival analysis; (6) For the orthotopic mouse model, shNTC, shLDH, and shLDH+CXCL1 KPC-luc cells were orthotopically injected into C57BL/6J mice. The mice were euthanized on the 16th day after the implantation.

Human samples
In this study, peripheral blood samples from one cohort (22 healthy donors and 27 patients with pancreatic cancer, aged 22–88 including 31 males and 18 females) and formalin-fixed paraffin-embedded (FFPE) PDAC tissues from a separate, non-overlapping cohort (3 male and 3 female patients, aged 54–72) were obtained from residual clinical specimens after routine diagnostic procedures at the First Affiliated Hospital of Nanchang University. The research protocol was approved by the Ethics Committee of the First Affiliated Hospital of Nanchang University ((2024) CDYFYYLK(08-099)). Human PDAC tissue microarrays consisting of 79 tumor and 79 adjacent normal tissues (aged 34–82, 40 males and 39 females) were purchased from Guilin Fanpu Biotech with the ethical approval through the Guilin Fanpu Biotech Ethics Committee (Fanpu-2018[23]). Written informed consent was obtained from all study participants.

Cell lines
PANC02 (STCC20054P) was purchased from Servicebio. BxPC3 (BNCC338477) was obtained from BNCC (Bena Culture Collection, China). PANC1 (CRL-1469) and MIAPaCa-2 (CRL-1420) were purchased from ATCC. The KPC-luc cell line was a generous gift from Prof. Baiyong Shen and Prof. Da Fu53. All the cell lines mentioned above were maintained in Dulbecco’s Modified Eagle Medium (DMEM, Servicebio, #4511) supplemented with 10% fetal bovine serum (FBS, ZETA LIFE #Z7181), 100 U/ml penicillin, and 100 mg/L streptomycin. The cells were maintained in a humidified incubator at 37°C with an atmosphere of 5% CO2.

Reagents, Primers and shRNAs
2DG (#HY-13966), bromosporine (#HY-15815), WM-1119 (#HY-102058), MG149 (#HY-15887), WM-3835 (#HY-134901), PF-9363 (#HY-132283), CPTH2 (#HY-W013274), PU139 (#HY-124696), and SGC-CBP30 (#HY-15826) were obtained from the MedChemExpress (MCE), China. Rotenone (#S2348) and Embelin (#S7025) were purchased from Selleck (Shanghai, China). The primers and shRNAs listed in Supplementary Table S1 were purchased from Sangon Biotech Co. Ltd., China.

Plasmids and establishment of stable cell lines
The synthetic shRNAs were annealed and cloned into the pLKO.1-TRC vector. This procedure resulted in the generation of several plasmids: pLKO.1-hPcaf, pLKO.1-mPcaf, pLKO.1-hLdha, pLKO.1-mLdha, pLKO.1-hLdhb, pLKO.1-mLdhb, pLKO.1-hGcn5, pLKO.1-mGcn5, pLKO.1-hP300, pLKO.1-mP300 and pLKO.1-NTC. Additionally, mCxcl1 was amplified by PCR using cDNA from KPC cells as a template. Subsequently, the mCxcl1 gene was inserted into the pLVX-IRES-G418 vector via 2× In-Fusion Cloning Mix (Servicebio, #G3350). All the constructed plasmids were verified by Sanger sequencing (Sangon Biotech Co. Ltd, China). A mixture of plasmids (psPAX2:pMD2.G:pLKO.1=1:1:2) was transfected into HEK293T cells using polyethylenimine (PEI). The supernatant containing virus particles was collected 48 h post-transfection and filtered through a 0.22 µm membrane to infect target cells at approximately 50% confluence. Twenty-four hours post-transfection, the supernatant was replaced with fresh medium containing puromycin (Selleck, #S7417) at a final concentration of 1.5 µg/mL for BxPC3, 2 µg/mL for PANC1, 0.75 µg/mL for KPC-luc, and 1.5 µg/mL for PANC02 to screen stably transfected cell lines.

Quantitative real-time PCR (qPCR) analysis
Total RNA from cultured cells was isolated using the RNA Easy Fast Tissue/Cell Kit (TIANGEN, #DP451). The quality and concentration of the isolated RNA were determined using a NanoDrop spectrophotometer (Thermo Fisher Scientific). The cDNA was generated with 1 µg of total RNA using the HiScript Q RT SuperMix for qPCR (+gDNA wiper) (Vazyme, #R123-01). The qPCR reactions were performed using 2× qPCR Master Mix (Vazyme, #Q711-02) on a Bio-Rad detection system (Bio-Rad; CFX96 Touch Real-Time PCR Detection System). The sequences of the qPCR primers used are listed in Supplementary Table S1. Data analysis was performed using the comparative Ct method, and the relative expression levels of the target genes were normalized to Actb mRNA levels. Statistical significance was determined using a t test.

Co-Immunoprecipitation (Co-IP)
For Co-IP, 60 µL Protein A+G beads (Beyotime, #P2108) were washed twice with 1× TBS and then incubated with 2 µg of anti-rabbit IgG (Abclonal, #WH220308) or anti-L-Lactyl-Histone H3K18 (PTMBIO, #PTM-1427RM) antibodies at 4°C for 4 h. BxPC3 or KPC cells were lysed, and 100 µL lysate was set aside as input, while the remainder was divided and incubated overnight at 4°C with the antibody-precoated beads. The next day, the beads were washed thrice with 1× TBS to remove unbound proteins. Elution was performed by adding 50 µL of 1× protein loading buffer and incubating at 95°C in a heating block for 10 min. The supernatant was then collected for the western blot.

ELISA
To examine the secreted CXCL1, 5×105 cells per well were cultured in six-well plates for 24 h. The cell culture supernatant was centrifuged at 400×g for 5 min and collected. The concentration of CXCL1 in cell culture supernatant and plasma of tumor-bearing mice was measured using a Mouse CXCL1 ELISA Kit (Proteintech, #KE10104). The concentration of CXCL1 from healthy individuals and PDAC patients’ plasma was measured using a Human CXCL1 ELISA Kit (Proteintech, #KE00133) according to the manufacturer’s instructions.

Protein extraction and western blot analysis
Proteins from cells and tumor tissues were extracted using RIPA lysis buffer (Beyotime, #P0013B) supplemented with Trichostatin A (TSA, Selleck, #S1045), a cocktail of protease inhibitors (Servicebio, #G2006), and phenylmethylsulfonyl fluoride (PMSF, Servicebio, #G2008). The proteins were then separated by electrophoresis on a 12% polyacrylamide gel and transferred onto a 0.45 µm PVDF membrane. The membrane was blocked with 5% skim milk in TBST to minimize non-specific binding. The membrane was incubated with the primary antibodies overnight at 4°C, followed by multiple washes with TBST. The primary antibodies used here included anti-LDHA antibody (Proteintech, #19987-1-AP, 1:3000), anti-LDHB antibody (Proteintech, #14824-1-AP, 1:5000), anti-H3 antibody (Proteintech, #17168-1-Ap, 1:3000), anti-PCAF antibody (Cell Signaling Technology, #3378S, 1:1000), anti-P300 antibody (Proteintech, #20695-1-AP, 1:500), anti-GCN5 antibody (Proteintech, #66575-1-Ig, 1:3000), anti-beta Actin antibody (PTMBIO, #PTM-5028, 1:1000), anti-human CXCL1 Polyclonal antibody (Proteintech, #12335-1-AP), anti-mouse CXCL1 Polyclonal antibody (Proteintech, #30322-1-AP), anti-L-Lactyl Lysine antibody (PTMBIO, #PTM-1401RM, 1:1000), anti-L-Lactyl-Histone H3K18 antibody (PTMBIO, #PTM-1406RM, 1:1000), anti-L-Lactyl-Histone H3K9 antibody (PTMBIO, #PTM-1419RM, 1:1000), anti-L-Lactyl-Histone H3K14 antibody (PTMBIO, #PTM-1414RM, 1:1000), anti-H4 antibody (PTMBIO, #PTM-1009, 1:1000), anti-L-Lactyl-Histone H4K12 antibody (PTMBIO, #PTM-1411RM, 1:1000), anti-L-Lactyl-Histone H4K8 antibody (PTMBIO, #PTM-1415RM, 1:1000), anti-Acetyl-Histone H3 (Lys18) antibody (PTMBIO, #PTM-114RM, 1:1000), anti-Acetyllysine antibody (PTMBIO, #PTM-101, 1:1000), and anti-Acetyl-Histone H4 (Lys8) antibody (PTMBIO, #PTM-190, 1:1000). After incubation with the secondary antibody for 1 h, the membrane was rewashed with TBST multiple times. The secondary antibodies included Goat Anti-Rabbit IgG H&L (HRP) pAb (PTMBIO, #PTM-6261, 1:5000) and Goat Anti-Mouse IgG H&L pAb (PTMBIO, #PTM-7168, 1:5000). The immunoreactive bands were visualized using Ultra-High-Sensitive ECL Kit (Servicebio, #G2020-25ML) on an iBright CL750 imaging system (Thermo Fisher Scientific).

Measurement of lactate levels
To measure lactate concentration in tumor tissue, the tissue was homogenized in ice-cold PBS buffer. Following centrifugation at 12000×g for 10 min at 4°C, the supernatants were collected, and lactate levels were determined using an L-Lactate Assay Kit (BioAssay Systems, ECLC-100) according to the manufacturer’s instructions. Lactate levels of tumor tissues were normalized to the tumor weight.

In vitro histone H3 lactylation assay
To analyze PCAF-catalyzed histone H3 lactylation, the reaction was performed in 20 μL of 1× reaction buffer (25 mM Tris-HCl (pH 7.5), 5 mM beta-glycerophosphate, 2 mM dithiothreitol (DTT), 0.1 mM Na3VO4, 10 mM MgCl2) containing 0.5 μg PCAF (Active Motif, #81142), 0.5 μg histone H3 (Active Motif, #31294) and 20 μM lactyl-CoA (MCE, #HY-141540) at 30°C for 30 min. Then, 5× SDS loading buffer was added to the reaction and boiled for 5 min at 95°C. The samples were separated by SDS-PAGE and immunoblotted with the indicated antibodies.

Neutrophil isolation and in vitro migration assay
The mouse neutrophils were isolated from the bone marrow of C57BL/6J mice using a mouse neutrophil enrichment kit (STEMCELL, #19762RF). The human neutrophils were isolated from the peripheral blood of healthy donors using the human peripheral blood neutrophil isolate kit (TBD Science, #LZS11131) and single nuclear cell isolate kit (TBD Science, #LDS1075) according to the manufacturer’s instructions. The neutrophils (1×105 cells per well) in RPMI 1640 (Servicebio, #G4535) supplemented with 10% FBS were seeded in the top chamber of the transwell (Corning, #3421). The conditional media from the cultured PANC1, KPC-luc, and PANC02 cell lines with treatments were collected and added to the bottom layer of the transwell.
For rescue experiments, recombinant human CXCL1/GRO-alpha (Abclonal, #RP01651, 2000 pg/mL) or mouse CXCL1/GRO-alpha (Abclonal, #RP01615, 1000 pg/mL) protein was supplemented in the medium of the bottom layer.
For treatment with inhibitor, purified neutrophils were pre-incubated for 1.5 hours in complete medium containing gradient concentrations of SX-682 (MCE, #HY-119339) and Navarixin (MCE, #HY-10198). Then, the pre-treated neutrophils were seeded in the top chamber of the transwell while the bottom layer was supplied with a corresponding dose of recombinant CXCL1. After incubation at 37°C for 4 h, cells migrated to the bottom chamber were counted.

Assessment of neutrophil viability, degranulation, and ROS
Purified mouse or human neutrophils were incubated in KPC-luc/PANC1 cell-conditional supernatant for 4 h. The cell viability and degranulation of the neutrophils were quantitatively assessed by flow cytometry after stained with the Zombie Aqua™ Fixable Viability Kit (Biolegend, #423102) and mouse or human anti-CD63 antibody (Biolegend, #353010, #143910). For ROS measurement, purified neutrophils were labeled with a fluorogenic ROS detection probe (YEASEN, #50101ES01) after incubation with the respective cell-conditional supernatant. The labeled neutrophils were then analyzed by flow cytometry.

CD8+ T cell isolation and suppression assay
Purified mouse neutrophils were incubated in KPC-luc cell-conditional supernatant or complete medium for 24 h. CD8+ T cells were isolated from C57BL/6J mouse spleens using positive magnetic selection kit (RWD, #K1303-10). The purified CD8+ T cells (1×105 cells per well) were then labeled with CFSE (YEASEN, #40714ES76) to track cell division. Following incubation, the cells were stimulated by 5 μg/mL anti-CD3/CD28 antibody (Selleck, #A2104, #A2166) and 20 ng/mL IL-2 (PeproTech, #212-12) in a 96-well plate at 37°C in 5% CO2. The aforementioned neutrophils and CD8+ T cells were mixed and co-cultured in different proportions. After 3 days of co-culture, the proliferation of CD8+ T cells was determined by measuring the dilution of CFSE using flow cytometry.

RNA sequencing and data analysis
Total RNA was extracted from BxPC3 and PANC1 cells treated with PBS or 2DG (20 mM for 24 h) using RNA easy Mini Kit (QIAGEN, #74104), according to the manufacturer’s protocol. Libraries for RNA sequencing were constructed using the Illumina Stranded Total RNA Prep with Ribo-Zero Plus kit (#20040525). The quality and size distribution of the amplified libraries were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific) and an Agilent 2100 Bioanalyzer, respectively. Sequencing was performed on Illumina Novaseq 6000 using a paired-end run, yielding approximately 30 million raw reads per sample. Raw sequencing data underwent quality control filtering to obtain high-quality reads. Differential gene expression analysis was performed using the DESeq2 R package. Genes with an adjusted p-value of less than 0.05 and an absolute log2 fold change greater than 1 were considered significantly differentially expressed.

CUT&Tag
The CUT&Tag experiment was performed utilizing the Hyperactive Universal CUT&Tag Assay Kit for Illumina (Vazyme, #TD903). In brief, 1×105 BxPC3 cells treated with or without 2DG were harvested and rinsed once with 500 μL wash buffer, followed by attachment to ConA beads at 25°C for 10 min. Subsequently, the cells were incubated overnight at 4°C with 1 μg of anti-L-Lactyl Lysine (PTMBIO, #PTM-1401RM) antibody or anti-L-Lactyl-Histone H3K18 (PTMBIO, #PTM-1427RM) antibody. On the following day, anti-rabbit IgG (Abclonal, #WH220308) was introduced and incubated at 25°C for 1 h. After washing with DIG wash buffer, the cells were exposed to 0.04 μM pA/G–Tn5 at 25°C for 1 h. The washing process was repeated before the cells were resuspended in tagmentation buffer and incubated at 37°C for 1 hour. Tagmentation was halted by adding proteinase K, buffer LB, and DNA extraction beads, followed by incubation at 55°C for 10 min. The beads were magnetically separated, washed twice with 80% ethanol, and the DNA was subsequently eluted with double-distilled water. Library preparation was carried out using the TD903 Hyperactive Universal CUT&Tag Assay Kit for Illumina, alongside the TD202 TruePrep Index Kit V2 for Illumina from Vazyme Biotech.

CUT&Tag data processing
Raw paired-end reads underwent adapter removal and quality trimming with trim_galore (v0.6.8). The cleaned FASTQ files were then aligned to the human reference genome sequences (hg38) using BWA (v2.2.9). Duplicate reads were marked and removed with Picard. Peak calling was performed with MACS2 (v2.2.9.1). For signal normalization, Deeptools (v2.5.4) was used to generate coverage tracks with bamCoverage and to calculate signal distributions around peak centers (identified by MACS2) using computeMatrix with the ‘reference-point’ model. The processed data were visualized with plotProfile and plotHeatmap from Deeptools.

Chromatin immunoprecipitation (ChIP)-qPCR
Cells were cultured to 70-80% confluence and crosslinked with 1% formaldehyde at 37°C for 10 min. Following the BeyoChIP™ ChIP Assay Kit (Protein A/G Bead) (Beyotime, #P2080S) protocol, cells were lysed and subjected to sonication to shear the chromatin. Then, the cell lysates were incubated with anti-L-Lactyl Lysine antibody (PTMBIO, #PTM-1401RM), anti-L-Lactyl-Histone H3K18 antibody (PTMBIO, #PTM-1406RM), anti-Acetyl-Histone H3 (Lys18) antibody (PTMBIO, #PTM-114RM), or anti-Acetyl-Histone H4 (Lys8) antibody (PTMBIO, #PTM-190) at 4°C overnight. The DNA interacting with the target protein was captured by magnetic beads and precipitated. The immunoprecipitated DNA was reverse crosslinked at 65°C for 4 hours in the presence of 0.1 M NaHCO3 and 1% SDS. DNA purification was performed using a phenol extraction-ethanol precipitation method, which involved mixing the sheared chromatin with an equal volume of phenol, vigorous vortexing, and subsequent centrifugation to separate phases. The aqueous phase containing DNA was transferred to a new tube, and an equal volume of chloroform mixture was added, followed by another centrifugation. The supernatant was collected, and DNA was precipitated by adding 2.5 volumes of cold 100% ethanol and incubating at −20°C overnight. The DNA pellet was collected after centrifugation, washed with 70% ethanol, air-dried, and resuspended in nuclease-free water. qPCR was conducted using the qPCR Master Mix (Vazyme, #Q711-02) on a Bio-Rad detection system (Bio-Rad; CFX96 Touch Real-Time PCR Detection System) with primers specific to the target genomic region. Relative enrichment was calculated using the 2-ΔΔCt method, normalized to input DNA and a negative control region. Statistical significance was assessed using a two-tailed unpaired Student’s t test.

Flow cytometry analysis
Fresh tumors were minced and incubated in RPMI 1640 medium containing mouse tissue digestive enzymes (RWD, #DHTE-5001) at 37°C for 40 min, followed by filtering through a 40 µm cell strainer (SAINING, #5021000) to prepare a single cell suspension. The cells were incubated with fixable zombie dyes (BioLegend, #423102) at room temperature in the dark for 15 min. Then the cells were rinsed and treated with Fc receptor (BioLegend, #101320) blocking solution for 15 min. Then, the cells were incubated in fluorescence-labeled extracellular antibodies at 4°C in the dark for 30 min followed by twice rinsing to remove unbound antibodies. For Granzyme B staining, the cells were incubated with the intracellular fixation/permeabilization buffer kit (Elabscience, #E-CK-A109). Finally, the cells were resuspended in 300 µL buffer (PBS+1% FBS) and subjected to flow cytometry analysis performed on a DxFLEX flow cytometer (Beckman Colter). The data was then analyzed using FlowJo software (Treestar). The antibodies used here included PerCP/Cyanine 5.5 anti-mouse CD45 antibody (BioLegend, #157208), Brilliant Violet 421 anti-mouse CD3 antibody (BioLegend, #100227), APC/Fire 750 anti-mouse CD8a antibody (BioLegend, #100766), PE anti-mouse CD279 (PD-1) antibody (BioLegend, #109104), APC anti-human/mouse Granzyme B Recombinant antibody (BioLegend, #372204), Brilliant Violet 421 anti-mouse/human CD11b antibody (BioLegend, #101236), APC anti-mouse Ly-6C antibody (BioLegend, #128016), PE anti-mouse Ly-6G antibody (BioLegend, #127608), APC anti-human CD45 antibody (BioLegend, #368512), FITC anti-human CD66b antibody (BioLegend, #305104), PE anti-human CD11b antibody (BioLegend, #301306), FITC anti-mouse/human CD11b antibody (BioLegend, #101206), and FITC anti-mouse CD3 antibody (BioLegend, #100204).

Mass cytometry by time of flight (CyTOF)
The subcutaneous tumor tissues were collected after vehicle/2DG treatment for 8 consecutive days. Tissues were then rinsed twice with cell culture medium. After sectioning the tissue into 1 mm³ fragments, samples were transferred to a C tube containing a digestive enzyme mixture (Miltenyi Biotec-mouse Tumor Dissociation Kit, #130-096-730) and cell culture medium, adjusted to a total volume of 5 mL. The tissue suspensions were incubated in a shaking incubator at 37°C for 1 h, then filtered through a 70 μm cell strainer. Cells were collected by centrifugation at 300×g for 5 min at 2–8°C. The supernatant was removed, and cells were resuspended in CSB for counting before proceeding with staining. Cells were washed in PBS, stained with 250 nM cisplatin (Fluidigm, #201194) for 5 min on ice to exclude dead cells, and treated with Fc receptor blocking solution before incubation with a surface antibody cocktail on ice for 30 min. Following two washes with FACS buffer (PBS+0.5% BSA), cells were fixed overnight in 200 µL intercalation solution (Maxpar Fix and Perm Buffer with 250 nM 191/193Ir, Fluidigm, #201067). Post-fixation, cells were washed sequentially with FACS buffer and perm buffer before staining with intracellular antibody cocktails listed in Supplementary Table S2 on ice for 30 minutes. Each antibody was labeled with specific metal tags using the MaxPAR Antibody Labeling Kit (Fluidigm, #201300) and titrated to determine optimal concentrations prior to use. After final washes, cells were resuspended in deionized water, combined with 20% EQ beads (Fluidigm, #201078), and analyzed on a Helios mass cytometer (Fluidigm, Helios).
Raw data for each sample were first debarcoded using a doublet-filtering scheme54 with unique mass-tagged barcodes. To account for batch effects, .fcs files from different batches were normalized through the bead normalization method55. Data were then manually gated using FlowJo software to exclude debris, dead cells, and doublets, isolating only live, single immune cells. Following this, the X-shift clustering algorithm56 was applied to partition cells into distinct phenotypes based on marker expression levels. Each cluster was annotated by cell type according to its unique marker expression pattern, with visualizations displayed on a heatmap. To facilitate the interpretation of high-dimensional data, the dimensionality reduction algorithm t-SNE57 was employed to create two-dimensional plots showing the distribution of clusters, marker expression, and differences among groups or sample types. Finally, statistical analyses of cell population frequencies were performed using a t test to evaluate significant differences between annotated cell populations.

Immunohistochemistry (IHC) analysis
Tumor tissues were captured and fixed in 10% formalin overnight and embedded in paraffin for H&E staining, immunohistochemistry (IHC), and immunofluorescence (IF). The IHC analysis of H3K18la expression in PDAC TMA (79 paired human PDAC tumor and adjacent normal tissues) was performed by Servicebio (Wuhan, China) with anti-L-Lactyl-Histone H3K18 antibody (PTMBIO, #PTM-1406RM, 1:500). For IHC, tumor tissues were captured and fixed in 10% formalin overnight and embedded in paraffin. Next, the embedded tissues were cut into 4 mm slices, and endogenous peroxidase was eliminated with 3% hydrogen peroxide. These sections were boiled for 5 min in an electric pressure cooker for antigen retrieval in citric acid repair solution (pH 6.0) and then blocked using 3% BSA for 30 min. Then, sections were incubated with primary antibody at 4°C overnight, followed by incubation with HRP-conjugated secondary antibody for 50 min at room temperature prior to DAB solution. The antibodies used here included anti-L-Lactyl-Histone H3K18 antibody (1:500, PTMBIO, #PTM-1406RM), anti-GRO antibody (1:200, AFFINITY, #AF5403), Ki-67 (1:400, Servicebio, #GB111499), anti-Ly6G antibody (1:500, Servicebio, #GB11229), and anti-CD8 antibody (1:200, Cell Signaling Technology, #70306), and anti-PCAF antibody (1:200, Cell Signaling Technology, #3378).

Multiplex immunofluorescence (IF) analysis
The embedded tissues were sectioned into 4 mm slices, deparaffinized, rehydrated, and antigen retrieved in citric acid repair solution (pH=6.0) for 3 min under a pressure steam condition. The sections were blocked with 3% hydrogen peroxide and 3% bovine serum albumin (BSA) at room temperature for 30 min respectively, and incubated with anti-CXCL1 antibody (1:200, AFFINITY, #AF5403), anti-CK19 antibody (1:2000, Servicebio, #GB15198), anti-L-Lactyl-Histone H3K18 antibody (1:1000, PTM BIO, #PTM-1406RM), anti-MPO antibody (1:2000, Abcam, #ab208670) and anti-CD8 alpha antibody (1:2000, Abcam, #ab237709) overnight at 4°C. The sections were washed with PBS and incubated with fluorescein-conjugated secondary antibody at room temperature for 1 h. The slides were imaged and visualized using a digital slide scanner (3DHISTECH, Hungary).

Bioinformatics analysis
Clinical information and RNA sequencing data for pancreatic cancer were obtained from The Cancer Genome Atlas (TCGA-PAAD, n=179) and CPTAC Pancreatic Cancer dataset (n=140)58, accessible via cBioPortal (https://www.cbioportal.org). Additionally, pan-cancer cohorts comprising transcriptomic data from 33 cancer types and comprehensive survival information were retrieved from TCGA. The glycolysis-related genes used in this study originated from previously published research59 and are listed in Supplementary Table S3. Based on the expression of the glycolysis-related genes, samples were classified into high and low glycolysis-level groups according to the Single-sample Gene Set Enrichment Analysis (ssGSEA) scores, implemented via the GSEAR package. The QUANTISEQ60 algorithm was employed to estimate the infiltration proportions of various immune cells for each sample based on gene expression profiling data. Then, differences in the infiltration proportions of neutrophils and CD8+ T cells between high and low glycolysis-level groups were visualized using the ggplot2 R package. The survival and survminer R packages were utilized to compare survival probabilities. The relationships between immune cell infiltration and the expression of core glycolysis-related genes were assessed using Spearman’s correlation coefficient.

Molecular docking
The structures of acetyl-CoA and lactyl-CoA were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Using Open Babel 3.1.1, the structures were converted from SDF format to MOL2 format, then imported into AutoDock Tools 1.5.7 and saved as PDBQT files. The protein structure (PDB ID: 1CM0) was downloaded from the PDB database, and PyMOL was used to remove unnecessary molecules, saving the processed protein as a PDB file for molecular docking. AutoDock Tools 1.5.7 was used to prepare the protein structure by adding hydrogens and charges, and the result was saved as a PDBQT file. Molecular docking was performed using the semi-flexible docking method in AutoDock. Based on the binding affinity calculated by the scoring function, the top-ranked compound with the highest docking score was selected for visualization and analysis.

Statistics and reproducibility
Statistical analyses were conducted using a two-tailed unpaired Student’s t test to assess significant differences between groups. Survival analysis p-values were determined using the log-rank test. All statistical tests were carried out using Prism 9 software (GraphPad Software) or R version 4.4.1. The respective figure legends provide comprehensive details regarding the statistical methods, the number of observations or replicates, and definitions of center and dispersion. No data were excluded from the analyses. The data used for analysis were from three or more independent experiments.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Summary:\nThe authors identify a cancer cell derived mediator of the immune microenvironment in pancreatic cancer. Using in vivo\nmodels, the authors identify that dysregulation of glycolysis dysregulates CXCL1-driven neutrophil recruitment and\nconsequently, reduces tumor growth and survival of mice with a sub-cutaneous model of syngeneic pancreatic cancer. They\nfurther mechanistically define the role of lactate and identify that PCAF mediated lacytlation of H3K181a is involved in\nthe control of CXCL1 production and neutrophil recruitment. The authors also demonstrate increased efficacy of anti-PD1\ntherapy in controlling orthotopic pancreatic tumor when used in combination with a drug targeting lactylation. The authors\nadd translational significance in the form of mining publicly available bulk RNAseq data and IF & IHC staining of the different\nproteins under investigation in tumor sections from patients with PDAC.\nStrengths:\n• Comprehensive analysis of the signaling cascade using different cell lines, techniques and including both human and\nmurine neutrophils.\nWeakness:\n• Some confirmatory experiments lacking.\nComments:\nAbstract: (line 37) PCAF needs to defined\nIntroduction\n• (line 54-55): TANs and PMN-MDSCs are defined differently in literature. While TANs are infiltrating neutrophils that have\nsuppressive functions, PMN-MDSCs are described to be intrinsically suppressive, arising from disordered granulopoiesis.\n• (line 86-88): sounds disjointed\nMethods\n• (line 393 – 395): need to specify number of repeats for experiments carried out for rigor; specifically, mouse experiments\nsince figures only show n = 5 to 6 most of the time and that would be far too few (for power and rigor) if experiments are\ncarried out only once.\nResults:\n• Fig 1E: the difference in glycolysis (at least ex vivo) needs to be quantified to make sure addition of 2DG is working as\nexpected (a supplementary figure).\n• Fig 1I: Two clusters of neutrophils observed – what differentiates them, how are the clusters defined? This is important\nsince the neutrophil cluster that is enriched seems to be the exact opposite between the untreated and 2DG treated.\n• Fig S3a: would ideally include Ly6C- as part of the neutrophil definition by flow.\n• Line 439-441: mentions testing re-activation of CD8s – we see differences in infiltration of CD8s with 2DG treatment, but\nactivation status is not addressed. Surface marker analysis for activation by flow is a simple solution. Would be specifically\nimportant as authors attempt to target PD-1 (expressed on activation/exhaustion) in later figures.\n• line 443-445: Need to analyze neutrophil effects on T cells (suppression assay) to show that they are truly\nimmunosuppressive as claimed (can possibly go with the experiment from Fig 2I.\n• Fig 2I: schematic seems to be labelled wrong – human neutrophils do not express Ly6G and murine neutrophils do not\nhave CD66b expression.\n• Fig 2I: In addition to migration, other activation markers need to be studied (including neutrophil survival, ROS activation,\ndegranulation) since 2DG is not a cancer specific drug and can affect metabolism and function of the neutrophil itself.\n• Fig 2: need to add a CXCL1 inhibitor (or CXCR1/CXCR2 inhibitor) to confirm results.\n• Line 472-474: to claim that CXCL1 secretion by cancer cells enriches neutrophil population requires experimental\nverification in mice. This is specifically important since there are several alternative chemoattracts for neutrophils that\ninclude leukoterineB4, C3a, C5a.\n• Fig 3b: tissue labelled as “normal” needs to be labelled as “adjacent normal”. Specifically in the context of this work where\nthe metabolic microenvironment is being investigated, the “normal” tissue adjacent to the tumor can be influenced by the\ntumor itself.\n• Line 565-567: CXCL1 has been so far been described in the context of cancer cell mediated production, neutrophil\nmediated CXCL1 production has not been discussed or addressed yet here, the authors claim that CXCL1 co-localizes with\nneutrophils. Careful examination of Fig S8 (associated with the described data) does not show a clear co-localization either.\nFurther quantification of co-localization and number is required for this claim to be validated.\n• Fig 5a: experimental schedule shows a break on D18, 19 – please explain the reason. The sub-cue model needs to be\nvalidated with KPC line as well since all experiments prior to this was conducted in the same.", "reviewer_2": "General Point:\nThis manuscript investigates a novel glycolysis-driven signaling pathway¡ªLactate-PCAF-H3K18la-CXCL1¡ªthat promotes\nneutrophil infiltration and immune evasion in pancreatic cancer. The authors combine bioinformatics analysis, CUT&Tag\nprofiling, and in vivo models to propose that PCAF functions as a histone lactyltransferase catalyzing H3K18la, thereby\ntranscriptionally activating CXCL1 expression. The study also suggests a combinatorial therapeutic strategy using PCAF\ninhibition and anti-PD-1 immunotherapy. The topic is highly timely and relevant, given the current focus on metabolic-\nepigenetic crosstalk and its implications for immunotherapy resistance in tumors such as PDAC.\nDespite these strengths, the manuscript has several notable methodological weaknesses. Key experimental details are\neither missing or insufficiently described, particularly in the immunological depletion assays and CXCL1 rescue\nexperiments. Additionally, the role of PCAF is likely overstated, as the supporting biochemical evidence is limited. These\nissues undermine the central conclusions and should be addressed to enhance the rigor and clarity of the study.\nMajor Points:\n1. The manuscript consistently refers to ¡°lysine lactylation (Kla)¡± without distinguishing between its two stereoisomeric\nforms: L-lactyllysine (KL-la) and D-lactyllysine (KD-la). Recent studies have clearly identified KL-la as the dominant\nintracellular form, originating from L-lactate through enzymatic processes, while KD-la arises from methylglyoxal\ndetoxification via D-lactoylglutathione and is largely non-enzymatic [PMID: 39030363]. This distinction is essential for\ncorrectly interpreting the role of glycolysis and LDH in histone L-lactylation. The stereospecificity of the H3K18L-la antibody\nused in the study must be explicitly stated in the Methods section, and all references to \"Kla\" should be revised accordingly.\n2. Figure 1A-C: The criteria used to define \"high glycolysis\" based on ssGSEA scores are not detailed. Specifically, the list\nof glycolysis-related genes used for enrichment scoring is not provided, nor is a reference cited. These omissions hinder\nreproducibility and raise concerns about the validity of the inferred glycolysis¨Cimmune correlations. Please include\nreferences to prior studies substantiating your method used in this paper.\n3. The manuscript states that CD11b+Ly6G+ neutrophils and CD8+ T cells were depleted in vivo using specific antibodies\nbut provides no details in the Methods section. The dosing regimen, administration route, depletion efficiency validation, and\nrelevant references are all missing. This lack of information undermines the credibility of key in vivo conclusions. Please\ninclude references to prior studies substantiating your method used in this paper.\n4. Fig. 2J, 2K, 4P: The term ¡°rescued by recombinant CXCL1 protein¡± is vague. The source, concentration, method of\nadministration, and whether protein expression was validated (e.g., via immunoblot) are not reported. Without these\nmethodological details, the experimental design is not interpretable. Please include references to prior studies\nsubstantiating your method used in this paper.\n5. The text refers generically to ¡°LDH knockdown,¡± without specifying whether LDHA, LDHB, or both were targeted. Given\nthat LDHA and LDHB have different substrate specificities and cellular functions, this ambiguity must be resolved throughout\nthe manuscript.\n6. Multiple studies, including recent biochemical evidence, identify p300/CBP and GCN5 as the primary H3K18la writers.\nThe claim that PCAF is the key lactyltransferase in PDAC contradicts these findings. Moreover, unpublished data from other\nlabs indicate that PCAF has little to no in vitro histone lactylation activity. The molecular docking and Co-IP evidence\nprovided here are not sufficient to support the enzymatic function of PCAF. The authors should remove Figure 4A and\ntemper conclusions from Figure 4B, which lacks controls to demonstrate specificity for H3K18la over other acyl\nmodifications.\n7. The IP experiment using H3K18la antibody is potentially confounded by coexisting acyl modifications (e.g., acetylation or\nother lactylation sites) and cannot specifically demonstrate a direct interaction between PCAF and H3K18la. Additional\ncontrols would be necessary to support the conclusion.\nMinor Points:\n1. Statements such as ¡°promotes the polarization of tumor-associated macrophages (TAM), and inhibits NK and effector T\ncells (Teffs)¡± are not supported by citations. Please include references to prior studies substantiating these claims.\n2. The sentence ¡°Several histone acetyltransferases function as lactyltransferases¡± should be made more precise by\nnaming the specific enzymes (e.g., p300, CBP, GCN5) and providing appropriate citations.", "reviewer_3": "Zhang et al, identified a novel mechanism by which the aerobic glycolysis-induced Lactate-PCAF-H3K18la-CXCL1 pathway\nmediate neutrophil infiltration and immunosuppression in TME. They also developed a potential therapeutic strategy for\npancreatic cancer. While the findings are intriguing, several major concerns should be addressed to strengthen the\nmanuscript:\nMAJOR POINTS:\nHow do the author define neutrophils in fig1A and immune cell in fig.1B-C? This is unclear.\nTumors treated with 2DG grow more slowly, and immune cell infiltration was analyzed at day 15, when tumor sizes differ\nsignificantly. Since immune infiltration is known to correlate with tumor size, a more rigorous and size-matched approach is\nnecessary to draw valid conclusions about immune cell dynamics.\nGiven that T cells rely on glucose for their function and survival, the authors should explain why T cells appear unaffected by\n2DG treatment in vivo. Additional data or discussion is needed to address this apparent discrepancy.\nThe study would benefit from the use of more physiologically relevant models, such as orthotopic pancreatic tumor models,\nto better validate the proposed mechanism.\nThe rationale behind the experimental design and selection of assays in Figures 1M–Q should be clearly explained to help\nreaders understand their relevance to the central hypothesis and the interpretation of the results.\nGlycolysis-driven Kla is important for the immunosuppressive activity of intratumoral neutrophils/macrophages as well as for\nthe function of T cells, but the authors did not address and discuss this critical point in their study. Since 2DG may affect both\ntumor and immune cells, the authors should analyze Kla levels and functional consequences in immune cells to substantiate\nthe claim that the PCAF–H3K18la–CXCL1 pathway in tumor cells is the primary mechanism.\nAs bromosporine may influence both lysine acetylation (Kac) and lysine lactylation (Kla), the authors should delineate the\nrelative contributions of Kla versus Kac to chemokine expression, both in vitro and in vivo\nLine 65-68, please add references."}, "author_response": "Point-by-point responses\nSeptember 16, 2025\nRe: NCOMMS-25-29863\nReviewer #1 (Remarks to the Author):\nSummary:\nThe authors identify a cancer cell derived mediator of the immune microenvironment in pancreatic\ncancer. Using in vivo models, the authors identify that dysregulation of glycolysis dysregulates\nCXCL1-driven neutrophil recruitment and consequently, reduces tumor growth and survival of\nmice with a sub-cutaneous model of syngeneic pancreatic cancer. They further mechanistically\ndefine the role of lactate and identify that PCAF mediated lactylation of H3K181a is involved in\nthe control of CXCL1 production and neutrophil recruitment. The authors also demonstrate\nincreased efficacy of anti-PD1 therapy in controlling orthotopic pancreatic tumor when used in\ncombination with a drug targeting lactylation. The authors add translational significance in the\nform of mining publicly available bulk RNAseq data and IF & IHC staining of the different\nproteins under investigation in tumor sections from patients with PDAC.\nStrengths:\n• Comprehensive analysis of the signaling cascade using different cell lines, techniques and\nincluding both human and murine neutrophils.\nWeakness:\n• Some confirmatory experiments lacking.\nMany thanks for the insightful summary as well as the strengths and weakness of this study.\nComments:\n1. Abstract: (line 36-37) PCAF needs to defined\nMany thanks for the suggestion and we have made the changes to define PCAF (p300/CBP-\nassociated factor) clearly (page 2, line 37).\n2. (line 54-55): TANs and PMN-MDSCs are defined differently in literature. While TANs are\ninfiltrating neutrophils that have suppressive functions, PMN-MDSCs are described to be\nintrinsically suppressive, arising from disordered granulopoiesis.\nMany thanks for raising this point, and we have made the changes accordingly (page 3, line 54-\n56).\n3. (line 86-88): sounds disjointed\nMany thanks for the comment and we have made the changes accordingly (page 4, line 86-87).\n4. (line 393 – 395): need to specify number of repeats for experiments carried out for rigor;\nspecifically, mouse experiments since figures only show n = 5 to 6 most of the time and that would\nbe far too few (for power and rigor) if experiments are carried out only once.\nMany thanks for raising this point. The data used for analysis were from three or more independent\nexperiments. We have made the changes accordingly in the statistical analysis of Methods (page\n26, line 852). Moreover, all experiments in mice were performed in two tumor models:\nsubcutaneous and orthotopic transplanted models, with at least five mice per group (page 16, lines\n452-454).\n5. Fig 1E: the difference in glycolysis (at least ex vivo) needs to be quantified to make sure addition\nof 2DG is working as expected (a supplementary figure).\nMany thanks for the comment and suggestion. We have measured the lactate levels of tumor tissues\nafter 2DG treatment for 2 and 8 days, respectively, and revealed a significant decrease compared\nto the control group (Fig. S3H and Fig. S2H).\n6. Fig 1I: Two clusters of neutrophils observed – what differentiates them, how are the clusters\ndefined? This is important since the neutrophil cluster that is enriched seems to be the exact\nopposite between the untreated and 2DG treated.\nMany thanks for the comment and suggestion. Based on the antibody panel we used for mass\ncytometry (CyTOF) (Supplementary Table S2), further analysis indeed identified two distinct\nneutrophil subsets: one characterized by high CD95 and low Ki67 expression (the upper cluster,\nFig. 1E), and the other exhibiting low CD95 and high Ki67 expression (the lower cluster, Fig. 1E).\nThe results showed that the proportion of CD95-high/Ki67-low neutrophils was significantly\ndecreased upon 2DG treatment (Vehicle vs 2DG, 18.68% vs 1.32%). Although the CD95-\nlow/Ki67-high subset also showed a moderate decrease after treatment (Vehicle vs 2DG, 28.79%\nvs 20.1%), both subsets clearly declined in proportion following 2DG treatment. However,\nwhether these two subsets differ functionally remains unclear based on the current data.\n7. Fig S3a: would ideally include Ly6C- as part of the neutrophil definition by flow.\nMany thanks for the suggestion. We did analyze the Ly6C by flow cytometry, but the data were not\nshown. When we employed the gating strategy for neutrophil using Ly6C, we found that almost all\nneutrophils are Ly6C+ (Fig. S3A).\n8. Line 439-441: mentions testing re-activation of CD8s – we see differences in infiltration of\nCD8s with 2DG treatment, but activation status is not addressed. Surface marker analysis for\nactivation by flow is a simple solution. Would be specifically important as authors attempt to target\nPD-1 (expressed on activation/exhaustion) in later figures.\nMany thanks for raising this important question. We have performed the experiment with the\northotopic transplanted tumor model and conducted the flow cytometry analysis. The results\nshowed the proportion of activated CD8+ T cells (GZMB+CD8+ T cells) was significantly higher\nand exhausted CD8+ T cells (PD-1+CD8+ T cells) was unchanged after 2DG treatment (Fig. 1, L\nand M).\n9. line 443-445: Need to analyze neutrophil effects on T cells (suppression assay) to show that they\nare truly immunosuppressive as claimed (can possibly go with the experiment from Fig 2I.\nMany thanks for this great suggestion. We have performed additional experiments and the results\nindicated that the neutrophils indeed could inhibit the proliferation of CD8+ T cells (Fig. 2J).\n10. Fig 2I: schematic seems to be labelled wrong – human neutrophils do not express Ly6G and\nmurine neutrophils do not have CD66b expression.\nMany thanks for bringing this labeling error to our attention. Fig. 2I has now been corrected.\n11. Fig 2I: In addition to migration, other activation markers need to be studied (including\nneutrophil survival, ROS activation, degranulation) since 2DG is not a cancer specific drug and\ncan affect metabolism and function of the neutrophil itself.\nMany thanks for the comment and suggestion. We have performed additional experiments and the\nresults indicated that the conditioned culture medium from cancer cells treated with 2DG did not\naffect neutrophil survival and degranulation, but it exhibited a certain inhibitory effect on the\nproduction of ROS (Fig. S6, B to D). In addition, to rule out the non-specific effects of 2DG, we\nhave also treated neutrophils with the conditioned culture medium from LDH-knockdown tumor\ncells. The results showed that the conditioned culture medium from the LDH-knockdown tumor\ncells did not affect neutrophil survival, ROS production and degranulation, excepting for affecting\nthe migration of neutrophils (Fig. S6, B to D and Fig. 2K).\n12. Fig 2: need to add a CXCL1 inhibitor (or CXCR1/CXCR2 inhibitor) to confirm results.\nMany thanks for this great suggestion. We have conducted additional experiments and the results\nindicated that the difference in neutrophil migration between the 2DG treatment or LDH-\nknockdown group and the control group was significantly reduced or eliminated following\ntreatment with the CXCR1/2 inhibitor SX682 or Navarixin (Fig. 2L and Fig. S6E).\n13. Line 472-474: to claim that CXCL1 secretion by cancer cells enriches neutrophil population\nrequires experimental verification in mice. This is specifically important since there are several\nalternative chemoattracts for neutrophils that include leukoterineB4, C3a, C5a.\nMany thanks for the excellent comment and suggestion. We have done additional experiments, and\nthe new data showed that the tumor growth inhibition observed following LDH-knockdown could\nbe partially reversed by restoring CXCL1 expression in vivo (Fig. 2M and Fig. S6F). In addition,\nflow cytometry results indicated that the reduction in neutrophil infiltration caused by LDH-\nknockdown was restored after overexpression of CXCL1 (Fig. 2N).\n14. Fig 3b: tissue labelled as “normal” needs to be labelled as “adjacent normal”. Specifically in\nthe context of this work where the metabolic microenvironment is being investigated, the “normal”\ntissue adjacent to the tumor can be influenced by the tumor itself.\nWe fully agree with your comment and suggestion. The tissues in Fig 3b have been re-labeled as\n“adjacent normal.\n15. Line 565-567: CXCL1 has been so far been described in the context of cancer cell mediated\nproduction, neutrophil mediated CXCL1 production has not been discussed or addressed yet here,\nthe authors claim that CXCL1 co-localizes with neutrophils. Careful examination of Fig S8\n(associated with the described data) does not show a clear co-localization either. Further\nquantification of co-localization and number is required for this claim to be validated.\nMany thanks for the excellent comment and suggestion. We sincerely apologize for the confusion\ncaused by our use of \"co-localize\". Our initial intention was not to definitively determine the\ncellular origin of CXCL1 or provide robust quantitative co-localization metrics, but rather to\nillustrate the spatial patterns that exist in the PDAC tumor microenvironment.\nTo better illustrate this point, we have provided the multiplex immunofluorescence images in\nanother manner (Fig. S9) as a representative visualization. It shows a compelling example where\nareas with higher H3K18la and CXCL1 signals appear to harbor more neutrophils (MPO+ cells)\nand fewer CD8+ T cells in the same patient tissue. Conversely, another area shows the opposite\npattern. We have also revised the text as following (page 12, lines 323-327): “To visualize the\nimmune contexture shaped by H3K18la, we performed multiplex immunofluorescence on human\nPDAC tissues. We observed that regions with higher H3K18la and CXCL1 signals often coincided\nwith increased neutrophils (MPO+ cells) but fewer CD8+ T cells in the same patient tissue (Fig.\nS9). Conversely, H3K18la-low regions showed the opposite immune landscape”. We therefore\nbelieve that these representative images effectively illustrate the spatial relationship we wish to\ndescribe. We opted for this qualitative approach because standard co-localization metrics are\npoorly suited for a diffuse, secreted chemokine like CXCL1 and would not meaningfully capture\nthis biological pattern. We hope this additional information could adequately address your\nconcern.\n16. Fig 5a: experimental schedule shows a break on D18, 19 – please explain the reason. The sub-\ncue model needs to be validated with KPC line as well since all experiments prior to this was\nconducted in the same.\nMany thanks for the comment and suggestion. The anti-PD-1 antibody was administered twice a\nweek. Bromosporine was discontinued at D18 and D19 to prevent or reduce the potential toxic\nand side effects caused by combined treatment. Here, we followed your advice and the in vivo\nassay was validated with KPC line as well. The new data showed that simultaneous blockade of\nPCAF and PD-1 could markedly attenuate the tumor burden compared to the monotherapy group\n(Fig. 5, I and J). Flow cytometric analysis showed that the combination of bromosporine and PD-\n1 blockade synergistically decreased the proportion of infiltrated neutrophils and increased CD8+\nT cells infiltration (Fig. 5, K and L). Meanwhile, flow cytometric results revealed that the\npercentage of tumor-infiltrating GZMB+CD8+ T cells was significantly higher and exhausted PD-\n1+CD8+ T cell was significantly lower in combination therapy compared to control (Fig. 5 M and\nN). Moreover, western blot analysis also showed that the levels of H3K18la was decreased in\nbromosporine alone or in combination with anti-PD-1 antibody in tumor tissues (Fig. 5O).\nReviewer #2 (Remarks to the Author):\nGeneral Point:\nThis manuscript investigates a novel glycolysis-driven signaling pathway Lactate-PCAF-\nH3K18la-CXCL1 that promotes neutrophil infiltration and immune evasion in pancreatic cancer.\nThe authors combine bioinformatics analysis, CUT&Tag profiling, and in vivo models to propose\nthat PCAF functions as a histone lactyltransferase catalyzing H3K18la, thereby transcriptionally\nactivating CXCL1 expression. The study also suggests a combinatorial therapeutic strategy using\nPCAF inhibition and anti-PD-1 immunotherapy. The topic is highly timely and relevant, given the\ncurrent focus on metabolic-epigenetic crosstalk and its implications for immunotherapy resistance\nin tumors such as PDAC. Despite these strengths, the manuscript has several notable\nmethodological weaknesses. Key experimental details are either missing or insufficiently\ndescribed, particularly in the immunological depletion assays and CXCL1 rescue experiments.\nAdditionally, the role of PCAF is likely overstated, as the supporting biochemical evidence is\nlimited. These issues undermine the central conclusions and should be addressed to enhance the\nrigor and clarity of the study.\nWe highly appreciate your positive comments on the novelty and significance of this study, and\nmany thanks for your insightful and critical comments on the methodological weaknesses.\nMajor Points:\n1. The manuscript consistently refers to lysine lactylation (Kla) without distinguishing between its\ntwo stereoisomeric forms: L-lactyllysine (KL-la) and D-lactyllysine (KD-la). Recent studies have\nclearly identified KL-la as the dominant intracellular form, originating from L-lactate through\nenzymatic processes, while KD-la arises from methylglyoxal detoxification via D-\nlactoylglutathione and is largely non-enzymatic [PMID: 39030363]. This distinction is essential\nfor correctly interpreting the role of glycolysis and LDH in histone l-lactylation. The\nstereospecificity of the H3K18L-la antibody used in the study must be explicitly stated in the\nMethods section, and all references to \"Kla\" should be revised accordingly.\nMany thanks for raising this important issue, and we totally agree with your comment. We did\nemphasize that the lactylation involved in this study was l-lactylation in the Introduction and\nResults section (page 3 and page 8). All the lactylation antibodies used in this study have been\ncarefully described in Methods section accordingly.\n2. Figure 1A-C: The criteria used to define \"high glycolysis\" based on ssGSEA scores are not\ndetailed. Specifically, the list of glycolysis-related genes used for enrichment scoring is not\nprovided, nor is a reference cited. These omissions hinder reproducibility and raise concerns about\nthe validity of the inferred glycolysis-immune correlations. Please include references to prior\nstudies substantiating your method used in this paper.\nMany thanks for the comment and suggestion. As described in the Methods section (Bioinformatics\nanalysis, page 25, lines 819-823), the glycolysis gene set was obtained from the report by\nZappasodi R et al [CTLA-4 blockade drives loss of T(reg) stability in glycolysis-low tumors.\nNature, 591, 652-658, doi:10.1038/s41586-021-03326-4 (2021)], which includes 24 genes:\nSLC16A3, PFKP, PFKL, ENO3, SLC2A1, HK2, ENO2, PKM, BSG, PKLR, PGAM1, ALDOA,\nPGK1, SLC16A1, LDHA, PFKM, TPI1, LDHB, ENO1, GAPDH, HK1, GPI, PGK2 and PGAM2.\nFor clarity, we have provided the following information:\n1. Explicitly listed the full gene set in Supplementary Table 3;\n2. Revised this part in Method as following (page 25, lines 819-823):\n“The glycolysis-related genes used in this study were originated from previously published\nresearcha and listed in table S3. Based on the expression levels of the glycolysis-related genes,\nsamples were classified into high- and low-glycolysis-level groups according to the Single-sample\nGene Set Enrichment Analysis (ssGSEA) scores, implemented via the GSEA R package.\n3. The manuscript states that CD11b+Ly6G+ neutrophils and CD8+ T cells were depleted in vivo\nusing specific antibodies but provides no details in the Methods section. The dosing regimen,\nadministration route, depletion efficiency validation, and relevant references are all missing. This\nlack of information undermines the credibility of key in vivo conclusions. Please include\nreferences to prior studies substantiating your method used in this paper.\nMany thanks for the comment and suggestion. Per your advice, we have provided the detailed\ninformation of CD11b+Ly6G+ neutrophils and CD8+ T cells clearance in vivo in the Methods\nsection (page 17, line 488-498).\n4. Fig. 2J, 2K, 4P: The term rescued by recombinant CXCL1 protein is vague. The source,\nconcentration, method of administration, and whether protein expression was validated (e.g., via\nimmunoblot) are not reported. Without these methodological details, the experimental design is\nnot interpretable. Please include references to prior studies substantiating your method used in this\npaper.\nMany thanks for the comment and suggestion. Per your advice, we have provided the detailed\ninformation of CXCL1 in the Methods (page 21, line 631-639). In addition, the recombinant\nCXCL1 proteins from human and mouse were confirmed by western blot, ELISA and migration\nability of neutrophils, respectively (Fig. S5, F to I).\n5. The text refers generically to LDH knockdown, without specifying whether LDHA, LDHB, or\nboth were targeted. Given that LDHA and LDHB have different substrate specificities and cellular\nfunctions, this ambiguity must be resolved throughout the manuscript.\nMany thanks for raising this important issue, and we sincerely apologize for the confusion. Per\nyour advice, we have carefully edited the text throughout the manuscript that LDH-knockdown\nindicated the silencing of both LDHA and LDHB (page 5, line 113).\n6. Multiple studies, including recent biochemical evidence, identify p300/CBP and GCN5 as the\nprimary H3K18la writers. The claim that PCAF is the key lactyltransferase in PDAC contradicts\nthese findings. Moreover, unpublished data from other labs indicate that PCAF has little to no in\nvitro histone lactylation activity. The molecular docking and Co-IP evidence provided here are not\nsufficient to support the enzymatic function of PCAF. The authors should remove Figure 4A and\ntemper conclusions from Figure 4B, which lacks controls to demonstrate specificity for H3K18la\nover other acyl modifications.\nWe highly appreciate your comment and suggestion. To address your concern, we have conducted\nadditional experiments and our new data suggested that, similar to P300 and GCN5, PCAF also\nexhibit similar enzymatic activity, capable of catalyzing H3K18 lactylation in pancreatic cancer\ncells (Fig. S8, D and E).\nIn addition, we are very grateful to you for sharing the unpublished data from other labs, which\nindicated that PCAF has little to no in vitro histone lactylation activity. PCAF and GCN5 both\nbelong to the GNAT (Gcn5-related N-acetyltransferase) sub-family of histone acetyltransferases,\nwith an amino acid sequence similarity of 71.27% (human，data from uniprot). Additionally,\nmolecular docking analysis also showed that lactyl-CoA was well accommodated in the cofactor\npocket of PCAF, similar to the structure of the acetyl coenzyme A (acetyl-CoA)–PCAF complex\n(Fig. 4A). All these evidences strongly suggest that PCAF may functions as a lactyltransferase. To\ndirectly test this hypothesis, we have performed in vitro enzyme activity experiments. H4K8ac was\nused as a positive control (Fig. 4F). The in vitro lactylation assay results showed that PCAF can\ndirectly catalyze the lactylation modification of histone H3 K18 (Fig. 4F). We have repeated this\nexperiment three times and obtained the same result. For details of the experiment, please refer to\nthe in vitro histone H3 lactylation assay of the Methods section. Therefore, our new data clearly\ndemonstrate that PCAF functions as a lactyltransferase for H3K18la modification. However, how\nPCAF, P300 and GCN5 collectively regulate H3K18la in pancreatic cancer remains unclear. We\nalso discussed this point in the Discussion section.\n7. The IP experiment using H3K18la antibody is potentially confounded by coexisting acyl\nmodifications (e.g., acetylation or other lactylation sites) and cannot specifically demonstrate a\ndirect interaction between PCAF and H3K18la. Additional controls would be necessary to support\nthe conclusion.\nMany thanks for the comment and suggestion. Per your advice, we have conducted in vitro\nlactylation assay and demonstrated that PCAF may interact directly with H3K18la (Fig. 4F).\nMinor Points:\n1. Statements such as promotes the polarization of tumor-associated macrophages (TAM), and\ninhibits NK and effector T cells (Teffs) are not supported by citations. Please include references\nto prior studies substantiating these claims.\nMany thanks for the suggestion. We have added the references accordingly (page3, line 62-65).\n2. The sentence Several histone acetyltransferases function as lactyltransferases should be made\nmore precise by naming the specific enzymes (e.g., p300, CBP, GCN5) and providing appropriate\ncitations.\nMany thanks for the suggestion. We have revised this sentence as following: Several histone\nacetyltransferases, such as p300/CBP18,23 and GCN523,24, along with alanyl-tRNA synthetase,\nAARS125,26, and AARS227,28 have been shown to function as lactyltransferase, whether there are\nnew lactyltransferases in pancreatic cancer requires further investigation (page 4, line 78-82).\nReviewer #3 (Remarks to the Author):\nZhang et al, identified a novel mechanism by which the aerobic glycolysis-induced Lactate-\nPCAF-H3K18la-CXCL1 pathway mediate neutrophil infiltration and immunosuppression in\nTME. They also developed a potential therapeutic strategy for pancreatic cancer. While the\nfindings are intriguing, several major concerns should be addressed to strengthen the manuscript.\nWe thank you for your insightful comments and criticisms.\nMAJOR POINTS:\n1. How does the author define neutrophils in fig1A and immune cell in fig.1B-C? This is unclear.\nMany thanks for raising this question. As described in the Methods section (page 25, Line 824-\n825), neutrophil abundance was quantified using the QUANTISEQ computational deconvolution\nmethod [PMID: 31126321], which estimates immune cell fractions from bulk RNA-seq data based\non cell-type-specific gene expression signatures which can be sourced from\nhttps://pmc.ncbi.nlm.nih.gov/articles/instance/6534875/bin/13073_2019_638_MOESM1_ESM.xl\nsx. Specifically, the neutrophil signature was defined by a gene panel with 144 genes whereas\nCD8+ T cells were defined by another gene panel with 152 genes. The immune cell in Fig.1B-C\nrefers to neutrophils and CD8+ T cells marked in red and blue, respectively. For clarity, we have\nnow added a reference to the QUANTISEQ method validation study.\n2. Tumors treated with 2DG grow more slowly, and immune cell infiltration was analyzed at day\n15, when tumor sizes differ significantly. Since immune infiltration is known to correlate with\ntumor size, a more rigorous and size-matched approach is necessary to draw valid conclusions\nabout immune cell dynamics. Given that T cells rely on glucose for their function and survival, the\nauthors should explain why T cells appear unaffected by 2DG treatment in vivo. Additional data\nor discussion is needed to address this apparent discrepancy.\nMany thanks for the comment and suggestion. Per your advice, we have conducted additional\nexperiment to address this issue. After 2 days of 2DG treatment, the tumor size did not exhibit\nmuch difference between the 2DG and control treatment groups (Fig. S3, E to G). However, flow\ncytometry analysis showed that the proportion of neutrophils in the tumor microenvironment was\nsignificantly decreased following 2 days of 2DG treatment, whereas the CD8+ T cells were\nmarkedly enriched in the tumors (Fig. S3, I and J). Therefore, the above results indicate that the\nalteration of immune infiltration by 2DG treatment is not due to differences in tumor size.\nAs suggested, we also discussed why T cells appear unaffected by 2DG treatment in vivo in the\nDiscussion section (page 14).\n3. The study would benefit from the use of more physiologically relevant models, such as\northotopic pancreatic tumor models, to better validate the proposed mechanism.\nMany thanks for the suggestion. Per your advice, All the experiments conducted in the\nsubcutaneous transplanted tumor model have been repeated in the orthotopic transplanted tumor\nmodel.\n4. The rationale behind the experimental design and selection of assays in Figures 1M–Q should\nbe clearly explained to help readers understand their relevance to the central hypothesis and the\ninterpretation of the results.\nMany thanks for the suggestion. We have added the results of the orthotopic transplanted tumor\nand have carefully revised the description of the experimental design and selection of assays\naccordingly (page 6).\n5. Glycolysis-driven Kla is important for the immunosuppressive activity of intratumoral\nneutrophils/macrophages as well as for the function of T cells, but the authors did not address and\ndiscuss this critical point in their study. Since 2DG may affect both tumor and immune cells, the\nauthors should analyze Kla levels and functional consequences in immune cells to substantiate the\nclaim that the PCAF–H3K18la–CXCL1 pathway in tumor cells is the primary mechanism.\nMany thanks for the comment and suggestion. We have conducted additional experiment to address\nthis concern. Our new data indicated that the lactylation modification level in KPC cells was the\nhighest compared with that in CD8+ T cells and neutrophils (Fig. S7G). Secondly, after 2DG\ntreatment in vitro, the H3K8la level of KPC cells decreased, while the H3K8la of CD8+ T cells and\nneutrophils remained unchanged (Fig. S7H), suggesting that KPC cells is more sensitive to 2DG\ncompared to CD8+ T cells and neutrophils. Therefore, we speculate that at the concentration of\n2DG used in this experiment, KPC cells were the primary cells affected in vivo. Moreover, to\nfurther exclude the effect of 2DG on non-tumor cells in vivo, we double silenced LDHA and LDHB\nusing shRNA in KPC cells, and obtained similar results to those of 2DG treatment in the KPC\nsubcutaneous implantation tumor model and the KPC orthotopic transplanted tumor model (Fig.\n1, N to S, and Fig. S4, A to I). As suggested, we also discussed this critical point in the Discussion\nsection (page 14).\n6. As bromosporine may influence both lysine acetylation (Kac) and lysine lactylation (Kla),\nthe authors should delineate the relative contributions of Kla versus Kac to chemokine expression,\nboth in vitro and in vivo.\nMany thanks for the comment and suggestion. We have analyzed the effects of bromosporine on\nlysine lactylation and lysine acetylation in PANC1 and KPC cells. Previous studies have shown\nthat PCAF can acetylate H4K8 [PMID: 32966758], and H3K18ac shares the same lysine site with\nH3K18la. The western blot results indicated that the levels of H3K18la and H3K18ac decreased\nin a dose-dependent manner with the increase of bromosporine concentration, but the reduction\nlevel of H3K18la was the most significant. Interestingly, H4K8ac remains unchanged at the\ncurrent concentration gradient (Fig. S8G). These results indicate that H3K18la may be more\nsensitive to bromosporine compare to H3K18ac and H4K8ac. We have further analyzed the effects\nof H3K18la, H3K18ac and H4K8ac on the direct transcriptional regulation of CXCL1 after\nbromosporine treatment by ChIP-qPCR. The results showed that the enrichment effect of H3K18la\non CXCL1 was significantly reduced after bromosporine treatment. However, H3K18ac and\nH4K8ac did not show any differences (Fig. S8H).\nIn addition, we observed a significant reduction in H3K18la in bromosporine-treated mouse tumor\ntissues, while H3K18ac and H4K8ac showed no significant changes (Fig. 4M and Fig. S8I).\nTherefore, our results suggested that bromosporine may mainly regulates the expression of CXCL1\nby influencing H3K18la.\nWe have also discussed this result in the Discussion section (page 15, line 418-425). The latest\nresearch reports that the same family protein GCN5 of PCAF executes distinct histone acylation\nin different protein complexes [PMID: 39561764]. We speculate that PCAF may also exhibit\ndifferent responses to bromosporine due to different acylase activities in different protein\ncomplexes, which warrant additional studies in future to test this hypothesis.\n7. Line 65-68, please add references.\nMany thanks for your close attention to this point. We have added the references accordingly\n(page3, line 62-65)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The reviewers have thoroughly addressed my initial comments, I have no additional concerns", "reviewer_2": "The authors have largely addressed my concerns. Please ask the authors to address the two minor concerns described\nbelow before its publication:\n1. The Western blot data for LDHA and LDHB knockdown should be provided, including the sequences used, which ought\nto be described in detail in the Methods section.\n2. For Figure S8E, please provide the expression levels of PCAF, GCN5, and p300 before and after knockdown of each\ngene.", "reviewer_3": "No Further experiments and clarifications are required"}, "author_response": "Point-by-point responses\nDecember 10, 2025\nRe: NCOMMS-25-29863A\nReviewer #2 (Remarks to the Author):\nThe authors have largely addressed my concerns. Please ask the authors to address the\ntwo minor concerns described below before its publication:\n1. The Western blot data for LDHA and LDHB knockdown should be provided, including the\nsequences used, which ought to be described in detail in the Methods section.\nWe appreciate the comment and apologize for any confusion. The requested Western blot data for\nLDHA and LDHB knockdown are presented in Supplementary Fig. S5C and S7C. The\ncorresponding sequences for the knockdown are listed in Supplementary Table S1. In addition,\nthese information have been described in details in the Methods: Reagents, Primers and shRNAs\nsection on page 18, Line 540-555 and Protein extraction and western blot analysis section on page\n20, Line 586-614.\n2. For Figure S8E, please provide the expression levels of PCAF, GCN5, and p300 before\nand after knockdown of each gene.\nMany thanks for the suggestion. Per your advice, the expression levels of PCAF, GCN5, and p300\nbefore and after knockdown have been added to Figure S8E."}]

Decision letter