Wrecking neutrophil extracellular traps and antagonizing cancer-associated neurotransmitters by interpenetrating network hydrogels prevent postsurgical cancer relapse and metastases

Abstract

Tumor-promoting niche after incomplete surgery resection (SR) can lead to more aggressive local progression and distant metastasis with augmented angiogenesis-immunosuppressive tumor microenvironment (TME). Herein, elevated neutrophil extracellular traps (NETs) and cancer-associated neurotransmitters (CANTs, e.g., catecholamines) are firstly identified as two of the dominant inducements. Further, an injectable fibrin-alginate hydrogel with high tissue adhesion has been constructed to specifically co-deliver NETs inhibitor (DNase I)-encapsulated PLGA nanoparticles and an unselective β-adrenergic receptor blocker (propranolol). The two components (i.e., fibrin and alginate) can respond to two triggers (thrombin and Ca²⁺, respectively) in postoperative bleeding to gelate, shaping into an interpenetrating network (IPN) featuring high strength. The continuous release of DNase I and PR can wreck NETs and antagonize catecholamines to decrease microvessel density, blockade myeloid-derived suppressor cells, secrete various proinflammatory cytokines, potentiate natural killer cell function and hamper cytotoxic T cell exhaustion. The reprogrammed TME significantly suppress locally residual and distant tumors, induce strong immune memory effects and thus inhibit lung metastasis. Thus, targetedly degrading NETs and blocking CANTs enabled by this in-situ IPN-based hydrogel drug depot provides a simple and efficient approach against SR-induced cancer recurrence and metastasis.

Keywords: Cancer-associated neurotransmitters; Immunosuppressive tumor microenvironment; Interpenetrating network hydrogels; Neutrophil extracellular traps; Postsurgical cancer relapse and metastases.

Graphical abstract

Fig. 1

Schematic of preparing PR@DnaseI-PLGA@Gel for wrecking neutrophil extracellular traps and antagonizing cancer-associated neurotransmitters to prevent postsurgical tumor relapse and metastases. The hydrogel platform can reshape tumor microenvironment by decreasing microvessel density, blocking myeloid-derived suppressor cells, up-regulating the production of various proinflammatory cytokines, enhancing natural killer cell function and relieving cytotoxic T cell exhaustion.

Fig. 2

SR promoting tumor progression and inducing angiogenesis-immunosuppression niche. (a) Schematic illustration of SR treatment; (b) Residual tumor growth kinetics of mice in untreated, sham operation and SR groups (n = 5); (c) Weight of the excised tumor on day 17 after varied treatments (n = 5); (d) Photographs of excised tumors at the end of treatments; (e) Significant enrichment in gene ontology (GO) terms (top 30, n = 3); (f) Reactome analysis for uncovering the affected pathways by above differential genes (top 20, n = 3); (g) Heat map of mean fold-change in gene expression of chemokines and immune suppression (n = 3); (h,i) Quantification of the secretion of NE (h) and EPI (i) in serum from mice in different groups as indicated (n = 3); (j,k) Representative flow cytometric analysis (j) and quantification (k) of MDSCs (CD45⁺CD11b⁺Ly6G⁺) (n = 3); (l) Representative images of MPO (green) and Ly6G (red) immunofluorescence staining and DAPI (blue) nuclear staining after various treatments as indicated; (m,n) Quantification of MPO (m) and Ly6G (n) positive staining signals from the images shown in l (n = 9). Data are expressed as the mean ± standard deviation (SD). Statistical significances were calculated via two-tailed Student's t-tests, *p < 0.05 and ***p < 0.001.

Fig. 3

Synthesis and characterization of in situ formed bioresponsive scaffold. (a,b) Photographs of hydrogel formation without (a) or with (b) drugs; (c,d) Representative SEM image of hydrogels including blank gel (c) and PR@DNaseI-PLGA@Gel (d). (e) Steady shear rheology of different hydrogels; and (f) Compressive stress-strain curves of different hydrogels. (g,h) Rheological behaviors of blank gel (g) and PR@DNaseI-PLGA@Gel (h) as the functions of strain, angular frequency and time. (i) In vitro degradation photos of PR@DNase I@Fibrinogen Gel, PR@DNase I-PLGA@Fibrinogen Gel and PR@DNase I-PLGA@Gel in PBS solution over 14 days; and (j) Time-dependent weight loss of PR@DNase I-PLGA@Fibrinogen Gel and PR@DNase I-PLGA@Gel in PBS solution. (k) In vivo degradation behavior and tissue biocompatibility of in situ formed PR@DNaseI-PLGA@Gel hydrogel with H&E staining of the surrounding skin at different testing time; (l) The cytotoxicity of lyophilized PR@DNaseI-PLGA@Gel with different dilution; (m,n) Accumulative release of PR (m) and DNase I (n) from PR@DNaseI-PLGA@Gel in PBS solution. Data are presented as means ± SD (n = 3). N/A means no significance.

Fig. 4

PR@DNaseI-PLGA@Gel treatment against postsurgical tumor recurrence. (a) Schematic illustration of the experiment design to assess the in vivo PR@DNaseI-PLGA@Gel treatment and its triggered immune responses (PR, 25 mg•kg⁻¹; DNase I, 200 U per mouse); (b) Representative bioluminescence images of fLuc-4T1 tumor after varied treatments as indicated; (c–f) Individual tumor growth kinetics (c), average tumor growth curves (d), Kaplan-Meier survival curves (e) and body weight fluctuation curves (f) of 4T1 tumor-bearing mice after varied treatment strategies (n = 6); (g) Representative H&E histopathological images of 4T1 tumors harvested from mice in different groups: 10x (top) and 30x (bottom) fold magnifications; (h) Representative TUNEL (green) immunofluorescence images of the of 4T1 tumors from mice in different groups. Data are expressed as the mean ± SD. Statistical difference was calculated using two-tailed unpaired student's t-test (d) and Log-rank (Mantel-Cox) test (e), ****p < 0.0001.

Fig. 5

Sequencing analysis of tumor tissues after PR@Dnase I-PLGA@Gel treatment and Gene Set Enrichment Analysis (GSEA) validations. (a) Volcano plot of treated samples after mRNA sequencing of indicated groups (n = 5); (b) KEGG pathway classification analysis of treated samples after mRNA sequencing of indicated groups; (c) Enrichment results for G protein signaling pathways via GSEA; (d) Enrichment results for positive regulation of angiogenesis via GSEA; (e) Enrichment results for neutrophil extracellular trap formation via GSEA; (f) Enrichment results for cAMP signaling pathway via GSEA.

Fig. 6

The robust antitumor immune responses triggered by PR@DNaseI-PLGA@Gel treatment. (a–c) Representative images of MPO (green) (a), CD34 (red) (b) and TH (red) (c) immunofluorescence straining and DAPI (blue) nuclear staining after various treatments as indicated; (d–f) Quantification of MPO (d), CD34 (e), TH (f) positive staining signals from the images shown in a-c (n = 9); (g–i) Representative flow cytometric analysis of CD8⁺ T cells (CD45⁺CD3⁺CD8⁺) (g), NK cells (CD45⁺CD3⁻CD49b⁺) (h) and MDSCs (CD45⁺CD11b⁺Ly6G⁺) (i); (j–l) Corresponding flow cytometric quantification of CD8⁺ T cells (j), NK cells (k) and MDSCs (l) (n = 3). (m–o) Cytokine levels of secreted IFN-γ (m), IL-6 (n), IL-12 (o) in serum from mice after various treatments as indicated in the figure (n = 3). Data are expressed as the mean ± SD. Statistical significances were calculated via two-tailed Student's t-tests and One-way ANOVA, *p < 0.05, **p < 0.01 and ****p < 0.0001.

Fig. 7

PR@DNaseI-PLGA@Gel stimulating the systemic immune memory effects to oppose tumor challenge and lung metastasis. (a) Schematic illustration of PR@DNaseI-PLGA@Gel therapy to inhibit distant tumor growth in a mouse model of SR; (b) Representative bioluminescence images of fLuc-4T1 tumor bearing mice from each group after varied treatments every 6 days from days 3–15; (c,d) Average tumor growth curves of primary (c) and distant (d) tumors (n = 5); (e) Representative flow cytometric analysis and (f) quantification of CD8⁺ T cells (CD45⁺CD3⁺CD8⁺); (g) Representative flow cytometric analysis and (h) quantification of NK cells (CD45⁺CD3⁻CD49b⁺); (i) Representative flow cytometric analysis and (j) quantification of MDSCs (CD45⁺CD11b⁺Ly6G⁺). (k) Fluorescence images of metastatic lungs ex vivo; (l) The relative luciferase intensity in the excised lung tissues from different groups (n = 5). Data are expressed as the mean ± SD. Statistical significances were calculated via two-tailed Student's t-tests and One-way ANOVA, *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001.