Functional Reprogramming of Neutrophils within the Brain Tumor Microenvironment by Hypoxia-Driven Histone Lactylation

Abstract

Despite functional heterogeneity, the high frequency of intratumoral neutrophils predicts poor clinical outcomes. The tumor microenvironment reprograms neutrophils into immunosuppressive subsets that hinder anticancer immunity, thereby contributing to tumor growth and resistance to immunotherapies. However, the mechanisms underlying neutrophil reprogramming remain elusive. In this study, we report that the immunosuppressive ability of brain tumor-infiltrating neutrophils was restricted to a highly glycolytic and long-lived subset expressing CD71, which acquired immunosuppressive properties in response to hypoxia. Mechanistically, hypoxia boosted glucose metabolism in CD71+ neutrophils, leading to high lactate production. Lactate caused histone lactylation, which subsequently regulated arginase-1 expression, required for T-cell suppression. Targeting histone lactylation with the antiepileptic drug isosafrole blocked CD71+ neutrophil immunosuppressive ability, delayed tumor progression, and sensitized brain tumors to immunotherapy. A distinctive gene signature characterizing immunosuppressive CD71+ neutrophils correlated with adverse clinical outcomes across diverse human malignancies. This study identifies histone lactylation as a potential therapeutic target to counteract neutrophil-induced immunosuppression within tumors.

Significance: Neutrophils are critical contributors to the immunosuppressive microenvironment that restricts the effects of promising immunotherapies in glioblastoma. Our study identifies hypoxia-driven histone lactylation as a potential target to block immunosuppressive neutrophils and boost the effects of immunotherapy in glioblastoma and in other cancer settings beyond brain tumors.

Figure 1 -. Neutrophils infiltrate brain tumors acquiring immunosuppressive features.

(A). Example of murine brain tumor derived neutrophils gating strategy by FACS, on live CD45⁺ CD11b⁺ F4/80^lo/−cells. (B). Frequency of neutrophils out of live CD45⁺ cells in the brain of vehicle (RPMI) vs GBM-bearing mice by FACS. Vehicle n=9, GL261 n=35, SB28 n=24. (C). Frequency of neutrophils out of live CD45⁺ cells in SB28 bearing mice by FACS in blood (left) vs tumor (right). n = 6. (D). Frequency of Neutrophils out of live CD45⁺ cells in GL261 bearing mice by FACS in blood (left) vs tumor (right). n=6. (E). Absolute numbers of neutrophils per mg of tumor in SB28-bearing mice at the endpoint (n=4–5), by FACS (left) and Kaplan-Meier representation of SB28-bearing mice survival (right) after treatment with the isotype control (n = 7) or the Neutrophils depleting strategy (n = 6) (αLy6G). (F). Frequencies of different immune cells populations out of live CD45⁺ cells in tumor of SB28-bearing mice at day 14 after neutrophils depletion by FACS. n=4. (G). Absolute numbers of CD4⁺ (left) and CD8⁺ (right) T cells per mg of tumor in SB28-bearing mice at day 14, by FACS. n=4. (H). Suppressive ability of SB28 bearing mice derived neutrophils on CD8⁺ and CD4⁺ T cells proliferation, measured as CFSE dilution by FACS. n=4. (I). Example of human brain tumor derived neutrophils gating strategy by FACS, on live CD45⁺ cells (left) and frequencies of different immune cells populations out of live CD45⁺ cells in brain cancer patients from Moffitt Cancer Center (USA) and Policlinico Umberto I (Ita) by FACS (right, n=44). (J). Frequency of neutrophils out of live CD45⁺ cells in brain cancer patients divided based on the diagnosis from Moffitt Cancer Center (USA) and Policlinico Umberto I (Ita) by FACS. Oligodendroglioma n=8, astrocytoma n=6, glioblastoma n=30. (K) Survival analysis based on CD15 expression in TCGA GBM dataset. Patients were divided into high and low groups based on optimal cutoff (L). Suppressive ability of human brain tumor derived neutrophils on CD8⁺ and CD4⁺ T cells proliferation, measured as CFSE dilution by FACS. n=4. (M). Correlation between the presence of neutrophils and T cells in the tumor of brain cancer patients by FACS. n=25. All data are presented as mean ± SEM. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc test (B, C, D, H and J), Kaplan-Meier method and log-rank test (E), unpaired two-sided Student’s t-tests (E and G), paired two-sided Student’s t-tests (L) and Pearson Correlation Coefficient with the associated two-tailed p value (M).

Figure 2 -. A population of glycolytic neutrophils expressing the CD71 receptor is expanded in brain tumors where it acquires a hypoxic signature.

(A). Schematic representation of the step-by-step process to isolate and sequence neutrophils from brain tumor-bearing mice for single-cell RNA sequencing with 10x Genomics. Created in https://BioRender.com. (B). UMAP projection of Neutrophils with cells colored by clusters N1, N2, and N3 (left) and cluster composition in Tumor vs. Blood samples (right). (C). Heatmap of signature genes exclusively expressed in each Neutrophils cluster. Shown are Z-scales gene expression levels. (D). Gene set enrichment analysis showing enriched Hallmark pathway in each neutrophils cluster, including both blood and tumor clusters. Shown are normalized enrichment scores. (E). CD71 (Tfrc), LDHA (Ldha), GLUT-1 (Slc2a1), glycolysis and hypoxia expression on UMAP, separating blood from tumor clusters. Glycolysis and hypoxia overall expression were derived using Glucose_metabolism gene set in REACTOME and Hypoxia gene set in HALLMARK database, respectively.

Figure 3 –. CD71⁺ neutrophils are long-lived, immunosuppressive and mature cells localized in the hypoxic glycolytic areas within the brain tumor microenvironment.

(A). Example of murine brain tumor derived neutrophils gating strategy based on CD71 expression (left) and frequencies of CD71⁺ and CD71⁻ neutrophils in different murine organs (right) by FACS. naïve n=6, tumor n=8. (B). Frequency of CD71⁺ Neutrophils out of live CD45⁺ cells in blood (left) and tumor (right) of SB28-bearing mice over time by FACS. n=5. (C). Heatmap of differentially expressed genes (30 up and 30 down) in CD71⁻ and CD71⁺ neutrophils (FACS sorted from SB28 brain tumors) by bulk RNA sequencing. Shown are Z-scales gene expression levels. (D). 2-NDGB uptake in murine tumor (SB28) derived neutrophils measured by FACS and expressed as Geom. Mean fold change to CD71⁻ neutrophils. n=10. (E). GLUT-1 expression in murine tumor (SB28) derived Neutrophils measured by FACS and expressed as Geom. Mean fold change to CD71⁻ neutrophils. n=12. (F). WB of indicated markers in tumor (SB28) derived Neu. n=10. (G). Intracellular lactate levels in in vivo neutrophils (Lactate assay kit). Each replicate (n=3) represents cumulative results of neutrophils from 2 – 3 mice pulled together, for a total of n=8 mice. (H). Localization of neutrophils in specific areas on brain tumors. Scale bar: 100 μm. In the left panel, CD73 single staining is shown to identify hypoxic areas. In the middle panel, GLUT-1 single staining is shown to identify glycolytic areas. In the right panel, CD71⁻ neutrophils (LY6G⁺CD71⁻, purple), CD71⁺ neutrophils (LY6G⁺CD71⁺, yellow) and CD71⁺ non-neutrophils cells (LY6G⁻CD71⁺, red) were identified using the Nikon Nis-Elements AR (Ver. 6.02.01) Build 1973, and the Bright Spot Detection tool (nuclei are shown in blue). (I). Frequency of neutrophils (LY6G⁺ cells) in indicated areas of GBM tumors. Cells were counted with the auto measurement tool using the Nikon Nis-Elements AR (Ver. 6.02.01) Build 1973, and the Bright Spot Detection tool.(n=4). (J) Frequency of neutrophils subsets in indicated areas of GBM tumors. Cells were counted with the auto measurement tool using the Nikon Nis-Elements AR (Ver. 6.02.01) Build 1973, and the Bright Spot Detection tool. (n=4). (K). Giemsa staining (left) and proportion of mature/immature cells (right) in tumor (SB28) derived Neu. (L). CXCR2 (left) and CXCR4 (right) expression by tumor (SB28) derived Neutrophils by FACS. n=8. (M). Analysis of BrdU⁺ neutrophils subsets in SB28 brain tumors over time after a single injection of BrdU (D0). Shown is the calculated half-life (t_1/2) of each subset after reaching the BrdU peak at D4. n=5 mice per time-point. (N). Suppressive ability of mouse tumor (SB28) derived CD71⁺ and CD71⁻ Neutrophils on CD8⁺ and CD4⁺ T cells proliferation, measured as CFSE dilution by FACS. Each replicate (n=7) represents cumulative results of neutrophils from 2 – 3 mice pulled together, for a total of n=18 mice. (O) Localization of neutrophils around CD3⁺ T cells in radius below 30μm. A merged image of DAPI, LY6G, CD71 and CD3 staining is shown. (P) Frequencies of neutrophils subsets out of total neutrophils per single CD3⁺ T cell. 13 CD3⁺ T cells were identified in 6 different sections, from 2 different tumors and neutrophils were counted in the surrounding area within a radius of 30μm. All data are presented as mean ± SEM. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc test (B), paired two-sided Student’s t-tests (D, E, G, L and N), and the mathematical model of the nonlinear regression to calculate cells’ K constant and half-life with the associated p value (M).

Figure 4 -. Hypoxia drives the immunosuppressive functions of CD71⁺ neutrophils.

(A). Example of in vitro neutrophils gating strategy based on CD71 expression (left) and frequencies of CD71⁺ and CD71⁻ neutrophils in vitro (right) by FACS. n=14 (TES, n=4). (B) Gating strategy used to identify and sort neutrophils progenitors (proNeu). (C) LY6G and CD71 expression by proNeu before in vitro culture with GM-CSF, by FACS. (D) Analysis of the frequencies of total neutrophils and neutrophils subsets out of live cells overtime during the in vitro differentiation with GM-CSF, by FACS. n=2. (E) Analysis of the frequencies of neutrophils subsets out of total neutrophils during the in vitro differentiation with GM-CSF, by FACS. n=2. (F). Heatmap of differentially expressed genes (30 up and 30 down) in CD71⁻ and CD71⁺ neutrophils (FACS sorted from in vitro cultures under hypoxic conditions) by bulk RNA sequencing. Shown are Z-scales gene expression levels. (G) Overlap of significantly differentially expressed genes between neutrophils FACS sorted from the in vitro model under hypoxic conditions and from brain tumors. (H) Similarity between in vitro CD71⁺ and in vivo CD71⁺neutrophils, as well as between CD71⁻ in vitro and CD71⁻ in vivo neutrophils. (I). Suppressive ability of in vitro CD71⁺ and CD71⁻ neutrophils on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=6. (J). Suppressive ability of in vitro CD71⁺ and CD71⁻ neutrophils on CD4⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=6. All data are presented as mean ± SEM. Statistical analysis was performed using Spearman correlation coefficients with the associated p value (H) and two-way ANOVA with Tukey’s post hoc test (I and J). In panel G, a permutation test was performed to calculate an empirical p value.

Figure 5 –. Hypoxia-driven glucose metabolism and intracellular lactate production govern the immunosuppressive functions of CD71⁺ neutrophils through ARG1.

(A). Arg1 expression by RT-qPCR in in vitro Neu. Normoxia n=4, hypoxia n=7. (B). WB of indicated markers in in vitro Neu. (C). Suppressive ability of in vitro hypoxic CD71⁺ and CD71⁻ neutrophils treated with nor-NOHA on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (D). Suppressive ability of in vitro hypoxic CD71⁺ and CD71⁻ neutrophils treated with nor-NOHA on CD4⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (E). Arg1 expression by tumor (SB28) derived neutrophils by RT-qPCR. Each replicate (n=14) represents cumulative results of neutrophils from 2 – 3 mice pulled together, for a total of n=35 mice. (F). WB of indicated markers in tumor (SB28) derived Neu. n=10. (G) Gating strategy used to identify and sort by FACS CD45.1 CD71⁺ and CD71⁻ neutrophils adoptively transferred intratumorally into SB28 (s.c.) tumor-bearing CD45.2 mice and Arg1 expression by RT-qPCR in CD71⁺ and CD71⁻ neutrophils before (D0) and after (D3) the intratumor adoptive transfer. (H). Suppressive ability of CD71⁺ neutrophils FACS-sorted from vehicle vs. nor-NOHA treated mice on CD4⁺ (left) and CD8⁺ (right) T cells proliferation, measured as CFSE dilution by FACS. n=3. (I) Violin plots comparing Glucose metabolism and hypoxia gene set expression between Blood vs. Tumor samples in different Neutrophils clusters. (J). Representative Glyco Stress Test kinetic plot wherein values for extracellular acidification rate (ECAR, mpH/min) are plotted versus time (left, note that glucose was injected at 18 min followed by oligomycin A injection at 36 min and 2-DG injection at 54 min); summaries of ECAR data representative of the Glycolytic capacity (middle) and glycolysis (right). n=3. (K). WB of indicated markers in in vitro Neu. (L). Intracellular lactate levels in in vitro Neutrophils (Lactate assay kit). n=4. (M). Suppressive ability of CD71⁺ and CD71⁻ neutrophils FACS-sorted from control (Slc2a1^f/f Lyz2 Cre-) vs. GLUT-1 CKO (Slc2a1^f/f Lyz2 Cre+) mice on CD8⁺ (left) and CD4⁺ (right) T cells proliferation, measured as CFSE dilution by FACS. n=3. (N). Suppressive ability of in vitro CD71⁺ and CD71⁻ Neutrophils treated with 2-DG on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (O). Suppressive ability of in vitro CD71⁺ and CD71⁻ Neutrophils treated with GNE-140 on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (P). Arg1 expression by RT-qPCR in in vitro hypoxic CD71⁺ and CD71⁻ Neutrophils treated with 2-DG (left, n=3) and GNE-140 (right, n=4). (Q). WB of indicated markers in in vitro hypoxic Neutrophils treated with 2-DG and GNE-140. All data are presented as mean ± SEM. Statistical analysis was performed using two-way ANOVA with Tukey’s post hoc test (A, C, D, G, H, J, L, M, N, O and P), paired two-sided Student’s t-tests (E) and one-way ANOVA with Tukey’s post hoc test (H).

Figure 6 -. Histone lactylation governs ARG1 expression in CD71⁺ neutrophils.

(A). WB of indicated markers in tumor (SB28) derived Neu. n=10. (B). CUT&RUN-RT-qPCR analysis for the association of Kla with the promoter of Arg1 gene in tumor derived Neu. Each replicate (n=2) represents cumulative results of neutrophils from 5 mice pulled together, for a total of n=10 mice. (C). WB of indicated markers in in vitro Neu. (D). WB of indicated markers in in vitro hypoxic Neutrophils treated with 2-DG and GNE-140. (E). CUT&RUN-RT-qPCR analysis for the association of Kla with the promoter of Arg1 gene in in vitro hypoxic Neutrophils treated with 2-DG and GNE-140. Each replicate (ctrl n=3, 2-DG and GNE-140 n=2) represents cumulative results of neutrophils from 2 mice pulled together, for a total of n=6 mice (ctrl) and n=4 mice (2-DG and GNE-140). (F) ¹³C incorporation in lysin-lactylated histone 3 in in vitro Neutrophils loaded with U-¹³C₆-glucose. Neutrophils from 4 different mice were pulled together and lysin-lactylated histones were isolated. Cumulative results of total heavy Kla H3 (normalized per million of cells) are shown. n=4. (G). WB of indicated markers in in vitro hypoxic neutrophils treated with CPI1612. (H). Arg1 expression by RT-qPCR in in vitro hypoxic CD71⁺ and CD71⁻ neutrophils treated with CPI1612. n=4. (I). Suppressive ability of in vitro CD71⁺ and CD71⁻ Neutrophils treated with CPI1612 on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (J). CUT&RUN-RT-qPCR analysis for the association of Kla with the promoter of Arg1 gene in in vitro hypoxic neutrophils treated with CPI1612. Each replicate (n=2) represents cumulative results of neutrophils from 2 mice pulled together, for a total of n=4 mice. (K). WB of indicated markers in in vitro hypoxic Neutrophils after treatment with Isosafrole. (L). Suppressive ability of in vitro CD71⁺ and CD71⁻ neutrophils treated with Isosafrole on CD8⁺ T cells proliferation (left, measured as CFSE dilution) and IFN-γ production (right), by FACS. n=3. (C). Kaplan-Meier representation of SB28-bearing mice survival treated with Vehicle (n=12), α4–1BB (n=10) and Isosafrole (n=10) alone or in combination (n = 8). The dashed line indicates the end of treatment. All data are presented as mean ± SEM. Statistical analysis was performed using two-way ANOVA with Holm-Šidák’s post hoc test (B, E and J), two-way ANOVA with Tukey’s post hoc test (H, I and L) and Kaplan-Meier method and log-rank test (M).

Figure 7 –. Human CD71⁺ neutrophils are immunosuppressive cells associated with a reduced survival in different cancer types.

(A). Example of human brain tumor derived Neutrophils gating strategy based on CD71 expression (left) and frequencies of CD71⁺ and CD71⁻ neutrophils in human blood and tumor (right), by FACS. n=7. (B). Frequency of CD71⁺ Neutrophils out of live CD45⁺ cells in the blood of healthy donors (HD, n=7) vs brain cancer patients (PT, n=20), by FACS. (C). Frequency of CD71⁺ neutrophils out of live CD45⁺ cells in human brain cancers, based on the diagnosis. Oligodendroglioma n=8, astrocytoma n=6, glioblastoma n=30. (D). 2-NDGB uptake in human tumor derived neutrophils, measured by FACS and expressed as Geom. Mean fold change to CD71⁻ neutrophils. n=6. (E). GLUT-1 expression in human tumor derived neutrophils, measured by FACS and expressed as Geom. Mean fold change to CD71⁻ neutrophils. n=10. (F). WB of indicated markers in human brain tumor derived Neu. n=5. (G). Suppressive ability of human tumor derived CD71⁺ and CD71⁻ Neutrophils on CD8⁺ (top) and CD4⁺ (bottom) T cells proliferation, measured as CFSE dilution by FACS. n=5. (H). Correlation between the frequencies of CD71⁺ neutrophils (top) and CD71⁻ neutrophils (bottom) and PD1⁺CD137⁺CD8⁺ T cells out of CD45⁺ cells in the tumor of brain cancer patients by FACS. n=18. (I). Kaplan-Meier representation of the overall survival (OS, top) or disease-free survival (DFS) in our cohort of GBM patients, based on the high (≥1.5% out of CD45⁺ cells) or low (<1.5% out of CD45⁺ cells) accumulation of CD71⁺ neutrophils in the tumor, by FACS. high, n=7; low, n=6. (J). N3 unique neutrophils gene signature association with patient OS (top) and DFS (bottom) in GBM cancer. Kaplan-Meier plots show OS and DFS for patients in the TCGA GBM cohort. Patients were split into high and low expression of the N3 signature based on optimal cutoff (See Methods). Events are represented by vertical lines and were defined from days to death (from initial pathological diagnosis) or days to first event (from initial treatment and from clinical disease-free diagnosis). (K). N3 unique neutrophils gene signature association with patients’ OS in different solid human cancer. Optimal cutoff was used to separate patients into high vs. low expression of N3 signature. (L). Forest plots show N3 signature hazard ratio (HR) scores associated with patient OS that were significant (p<0.05) by Cox proportional hazards test. Dots indicate the calculated HR and whiskers indicate 95% CIs. All data are presented as mean ± SEM. Statistical analysis was performed using unpaired two-sided Student’s t-tests (B), one-way ANOVA with Tukey’s post hoc test (C), paired two-sided Student’s t-tests (D, E and G), Pearson Correlation Coefficient with the associated two-tailed p value (H), Kaplan-Meier method and log-rank test (I, J and K) and Cox proportional hazards test (L). GBM = Glioblastoma; PAAD = PanCreatic adenocarcinoma; CESC = Cervical squamous cell carcinoma and endocervical adenocarcinoma; MESO = Mesothelioma; KIRP = Kidney renal papillary cell carcinoma; HNSC = Head and Neck squamous cell carcinoma; LIHC = Liver hepatocellular carcinoma; UVM = Uveal Melanoma.