NEK2 inhibition triggers anti-pancreatic cancer immunity by targeting PD-L1

Abstract

Despite the substantial impact of post-translational modifications on programmed cell death 1 ligand 1 (PD-L1), its importance in therapeutic resistance in pancreatic cancer remains poorly defined. Here, we demonstrate that never in mitosis gene A-related kinase 2 (NEK2) phosphorylates PD-L1 to maintain its stability, causing PD-L1-targeted pancreatic cancer immunotherapy to have poor efficacy. We identify NEK2 as a prognostic factor in immunologically "hot" pancreatic cancer, involved in the onset and development of pancreatic tumors in an immune-dependent manner. NEK2 deficiency results in the suppression of PD-L1 expression and enhancement of lymphocyte infiltration. A NEK binding motif (F/LXXS/T) is identified in the glycosylation-rich region of PD-L1. NEK2 interacts with PD-L1, phosphorylating the T194/T210 residues and preventing ubiquitin-proteasome pathway-mediated degradation of PD-L1 in ER lumen. NEK2 inhibition thereby sensitizes PD-L1 blockade, synergically enhancing the anti-pancreatic cancer immune response. Together, the present study proposes a promising strategy for improving the effectiveness of pancreatic cancer immunotherapy.

Fig. 1. NEK2 is a prognostic factor for immunologically “hot” pancreatic cancer.

a–c Expression profile of NEK2 in pancreatic cancer. Relative NEK2 expression in pancreatic cancer was analyzed using large-scale RNA-Seq datasets of PDAC from the TCGA database (n (T) = 179, n (N) = 171; n: number of patients) (a). NEK2 expression was measured in paired tumor and normal pancreatic tissues by IHC staining, with representative images (b) and statistical results (c) shown (n = 30; n: number of patients) (N: Normal pancreatic tissue; T: Pancreatic tumor tissue). Scale bars: 100 μm. d Correlation of NEK2 with prognostic factors in pancreatic cancer. Tissue microarray analysis of the prognostic role of NEK2 in pancreatic cancer (n = 64 weakly positive; n = 50 strongly positive) (p < 0.0001). e Overall survival (OS) of patients with pancreatic cancer with high or low expression of NEK2 (n = 177). f Overall survival (OS) of pancreatic cancer patients with high numbers of CD8⁺ T cells and with high or low expression of NEK2 (n = 76). g Overall survival (OS) of pancreatic cancer patients with decreased CD8⁺ T cells and with high or low expression of NEK2 (n = 101). h Bioinformatics analysis of the correlation between NEK2 and immune effector cells using TCGA datasets. In a, data are represented as boxplots where the middle line is the median; the lower and upper hinges correspond to the first and third quartiles; the upper whisker extends from the hinge to the largest value no further than 1.5 × IQR from the hinge (where IQR is the inter-quartile range); the lower whisker extends from the hinge to the smallest value at most 1.5 × IQR of the hinge, while data beyond the end of the whiskers are outlying points that are plotted individually. *P < 0.05, **P < 0.01, ***P < 0.001 using a two-tailed t-test; ns: not significant. Kaplan–Meier method and a Gehan–Breslow–Wilcoxon test are indicated in d. The Hazard Ratios (HR) and p-values by the log-rank (Mantel–Cox) test are indicated in e–g.

Fig. 2. NEK2 deficiency improves pancreatic cancer immunogenicity.

a, c Schematic protocols displaying WT and NEK2-depleted pancreatic cancer cells separately, and s.c. injection into immunocompetent and immunodeficient mice (n = 7). b, e Representative images of tumors and growth curves of immunocompetent mice. Tumors were measured at specified time points then dissected at the endpoint (n = 7). d, f Representative images of tumors and growth curves of tumors from immunodeficient mice. Tumors were measured at specified time points and dissected at the endpoint (n = 7). g, h The weight of tumors from immunocompetent and immunodeficient mice was reported at the endpoint (n = 7). i, j Representative images and statistical results of tumor-infiltrating lymphocytes (n = 7). k Schematic protocols showing WT and NEK2-depleted pancreatic cancer cells separately injected into immunocompetent and immunodeficient mice (n = 13). l, m Survival of immunocompetent and immunodeficient mice bearing NEK2-depleted pancreatic cancer cells (n = 13). Kaplan–Meier survival curves with log-rank test assessing the significance between WT and NEK2 KD immunocompetent (l) (p < 0.0001) and immunodeficient (m) (p = 0.33) mice. Results represent means ± SD of one representative experiment in e–j. All data are representative of three independently performed experiments. *P < 0.05, **P < 0.01, ***P < 0.001 using a two-tailed t-test; ns: not significant. Kaplan–Meier method and a Gehan–Breslow–Wilcoxon test are indicated in m and l.

Fig. 3. NEK2 inhibition enhances the anti-pancreatic cancer immune response.

a, c Schematic protocols of pancreatic cancer cells with or without pretreatment with a kinase-specific inhibitor of NEK2 (10 μM, 24 h) separately and s.c. injected into immunocompetent and immunodeficient mice (n = 7). b, d Tumor incidence in immunocompetent and immunodeficient mice was recorded at the times indicated. Tumors were further treated using an NEK2 inhibitor (100 μg/mouse, 2 weeks). e, f Schematic protocol of the treatment schedule and tumor growth curve in immunocompetent mice (n = 5). Tumors were measured at the time points indicated and removed at the endpoint. (h, i) Schematic protocol of the treatment schedule and tumor growth curve in immunodeficient mice (n = 5). Tumors were measured at specified time points and dissected at the endpoint. Tumor and mouse weight of immunocompetent (g, k) (n = 5) and immunodeficient mice (j, l) (n = 5) as reported at the endpoint. m–o Representative images and further quantification of tumor-infiltrating lymphocytes. Scale bars: 100×: 50 μm; 200×: 100 μm. Kaplan–Meier method and a Gehan–Breslow–Wilcoxon test are indicated in b and d. Results represent means ± SD of one representative experiment in f, g, i, j, k, l, m, and n. All data are representative of three independently performed experiments. *P < 0.05, **P < 0.01, ***P < 0.001 using a two-tailed t-test; ns: not significant.

Fig. 4. NEK2 positively correlates and interacts with PD-L1 in pancreatic cancer.

a Western blot analysis of NEK2 and PD-L1 in clinical pancreatic tissue samples from patients (n = 20) (N: Normal pancreatic tissue; T: Pancreatic tumor tissue). b–d Representative images and statistical results of IHC staining of NEK2 and PD-L1 in a tissue microarray (n = 156). e–g Cell lysates from SW1990, KPC, and CFPAC-1 separately analyzed by IP and Western blotting using the antibodies indicated. Representative image is shown n = 3 independent experiments. h GST-pull down assay of NEK2-His and GST-PD-L1 protein. Representative image is shown n = 3 independent experiments. i Representative images of individual immunofluorescence staining of NEK2 and PD-L1 interaction in KPC cells by Duolink assay. The red dots (NEK2/PD-L1 interaction) indicate their interaction. Representative image is shown n = 3 independent experiments. The Spearman correlations and p-values by Spearman’s test are indicated in d.

Fig. 5. NEK2 inhibits ubiquitination-mediated proteasomal degradation of PD-L1.

a, b Western blot analysis and flow cytometry of PD-L1 expression in pancreatic cancer cell lines after treatment with NEK2 inhibitor (10 μM, 24 h) and NEK2 knockdown. Representative image is shown n = 3 independent experiments. c LC–MS proteomics quantitative analysis of pancreatic cancer cells overexpressing NEK2. d Western blot analysis of PD-L1 expression in KPC cells treated with NEK2 inhibitor (10 μM, 24 h) after treatment with MG132 (100 μM, 24 h). Representative image is shown n = 3 independent experiments. e Western blot analysis of PD-L1 expression in WT and NEK2 KD KPC cells treated with MG132 (100 μM, 24 h). Representative image is shown n = 3 independent experiments. f Stability analysis of PD-L1 in KPC cells treated with NEK2 inhibitor (10 μM, 24 h) after treatment with cycloheximide (CHX) (20 μg/mL). Representative image is shown n = 3 independent experiments. g Stability analysis of PD-L1 in WT and NEK2 KD KPC cells treated with CHX (20 μg/mL). Representative image is shown n = 3 independent experiments. h, i Statistical analysis of three independent experiments is displayed. The intensity of PD-L1 protein expression was quantified using a densitometer. j Ubiquitination assay of PD-L1 in KPC cells treated with NEK2 inhibitor (10 μM, 24 h), subjected to anti-PD-L1 IP and anti-ubiquitin Western blot analysis after treatment with MG132 (50 μM, 24 h). k Ubiquitination assay of PD-L1 in WT and NEK2 KD KPC cells treated with MG132. Results represent means ± SD of one representative experiment in h and i. All data are representative of three independently performed experiments. *P < 0.05, **P < 0.01, ***P < 0.001 using a two-tailed t-test; ns: not significant.

Fig. 6. NEK2 phosphorylates PD-L1 at T194/T210 to maintain protein stability.

a Schematic diagram of the NEK-binding motif (F/LXXS/T) in the glycosylation-rich region and amino acid sequences around the potential binding sites of PD-L1 were aligned in evolutionarily divergent species. The F/LXXS/T motifs are highlighted in blue. b Generation of site-specific antibodies against T194 and T210 (Mus musculus: T193 and T209)-phosphorylated PD-L1. c Western blot analysis of T193 and T209-phosphorylated PD-L1 in KPC cells with NEK2 inhibitor (10 μM, 24 h) and NEK2 KD KPC. Representative image is shown n = 3 independent experiments. d In vitro kinase assay and western blot analysis of pT193-PD-L1 and pT209-PD-L1 expression of recombinant PD-L1 WT and NEK2 (active) protein. Representative image is shown, n = 3 independent experiments. e, f Western blot analysis of PD-L1 expression in flag-PD-L1 WT and T193/209A or T193/209D-transfected KPC cells with or without MG132 treatment. Representative image is shown n = 3 independent experiments. g Western blot analysis of pT193-PD-L1, pT209-PD-L1, and PD-L1 expression in WT and K37R transfected NEK2 KD KPC cells. Representative image is shown n = 3 independent experiments. h Ubiquitination assay of PD-L1 in Flag-PD-L1 WT and T193/209A or T193/209D-transfected KPC cells, subjected to anti-PD-L1 IP and anti-ubiquitin Western blot analysis after treatment with MG132 (50 μM, 24 h). Representative image is shown n = 3 independent experiments. i Ubiquitination assay of PD-L1 in WT and K37R transfected NEK2 KD-KPC cells subjected to PD-L1 IP and Western blot analysis with anti-ubiquitin after treatment with MG132 (50 μM, 24 h). Representative image is shown n = 3 independent experiments.

Fig. 7. NEK2 inhibition sensitizes PD-L1-targeted pancreatic cancer immunotherapy.

a Schematic protocol of the combination of anti-PD-L1 antibody and NEK2 inhibitor therapy. b Tumor growth curve of mice treated with anti-PD-L1 antibody (200 μg/mouse), NEK2 inhibitor (100 μg/mouse), or their combination (n = 5). c Representative images displaying tumors harvested from mice bearing KPC cells treated with anti-PD-L1 antibody, NEK2 inhibitor, or their combination (n = 5). d, e Tumor weight and mouse body weight (n = 5). f, g Flow cytometric analysis and statistical results of lymphocytes that have infiltrated the tumors (n = 5). Results are presented as means ± SD from one representative experiment in b, d, e, and g. All data are representative of three independently performed experiments. *P < 0.05, **P < 0.01, ***P < 0.001 using a two-tailed t-test; ns: not significant.

Fig. 8. Predicted model of the NEK2–PD-L1 signaling pathway in pancreatic cancer.

A schematic model is proposed to illustrate how PD-L1 protein stability is regulated by NEK2 in pancreatic cancer. NEK2 positively regulates and interacts with PD-L1 largely through PD-L1 phosphorylation at the T194/T210 residue in ER of pancreatic cancer. Therefore, treatment with NEK2 inhibitor unexpectedly suppressed PD-L1 protein expression, largely by inhibition of PD-L1 phosphorylation that promotes its degradation.