Targeting AQP5-mediated arginine deprivation in gastric cancer stem cells restores NK cell anti-tumor immunity

Abstract

Natural killer (NK) cells exhibit impaired anti-tumor activity upon entering the tumor microenvironment (TME); however, the precise mechanism(s) remains elusive. In this study, we demonstrate that AQP5⁺ gastric cancer stem cells contribute to the dysfunction of NK cells by reprogramming the urea cycle (UC). Mechanistically, AQP5 competitively binds ATP-dependent RNA helicase A (DHX9) over karyopherin subunit beta 1 (KPNB1), inhibiting DHX9 nuclear translocation and transcriptionally down-regulating argininosuccinate synthase 1 (ASS1). Low-arginine condition in the TME reshaped by AQP5⁺ tumor cells weakens NK cell function by limiting NO synthesis. Notably, preclinical murine models confirm that oral arginine supplements improve the NK cell-directed killing against organoids generated by AQP5^High GC (gastric cancer) tissues. Besides, AQP5⁺ tumor cells also redirect the UC to the TCA cycle, which stores the saved nitrogen in glutamine by promoting glutamate-ammonia ligase (GLUL) stability. This study uncovers the evidence of AQP5⁺ cancer stem cells impairing NK cell cytotoxicity by changing self-metabolism patterns.

Keywords: AQP5; NK cell; TCA cycle; cancer stem cell; urea cycle.

Graphical abstract

Figure 1

AQP5⁺ GC cells create a favorable immune microenvironment (A) Seven clusters with distinct transcriptional profiles in subcutaneous tumors established with 5 × 10⁶ AQP5⁺ or AQP5⁻ MFC cells in C57BL/6J mice visualized using tSNE (t-distributed stochastic neighbor embedding) plots. (B) Flow cytometry analysis of the proportion of NK (CD3⁻NK1.1⁺) cells in AQP5⁺ or AQP5⁻ tumors (subcutaneous tumors in C57/B6J mice, AQP5⁺ group n = 6, AQP5⁻ group n = 4). (C and D) NK cells isolated from AQP5⁺ or AQP5⁻ tumors (subcutaneous tumors in C57/B6J mice, AQP5⁺ group n = 6, AQP5⁻ group n = 4); proliferation of NK cells was assessed by carboxyfluorescein succinimidyl ester (CFSE) assay (C); cytotoxic activity of NK cells was measured by LDH (lactate dehydrogenase) release assay (D). (E) Expression of NK cell-related genes in subcutaneous tumors from (A). (F–H) NK cells separated from peripheral blood of healthy volunteers and co-cultured with AQP5⁺ or AQP5⁻ AGS (adenocarcinoma gastric stomach) cells in transwell chamber for 48 h; then, proliferation detected by CCK8 (F), relative expression of IFN-γ, TNF-α, and granzyme A (Gzma) (G), and cytotoxicity (H) in NK cells were performed (n = 3). (I) Flow cytometry analysis of the proportion of NK (CD3⁻CD56⁺) cells in gastric cancer tissues with high or low AQP5 expression (n = 7/group). (J) Representative images of immunofluorescence staining of AQP5, EPCAM, CD3, and CD56 in gastric cancer tissue microarrays (n = 95). Scale bar: 500 and 200 μm. (K) Proportion of cells with high and low NK cell infiltration grouped by the median in each group. (L–N) Isolation and culture of NK cells derived from gastric cancer tissues of patients with high or low AQP5 expression. Relative IFN-γ and TNF-α expression (L) and cytotoxicity (M) in NK cells isolated from GC tissues with high or low AQP5 expression (n = 3). NK cells (green) infiltrating PDOs (red) were evaluated by microscopy after 10⁵ NK cells were co-cultured with PDOs in matrix gel for 48 h; the NK cells per organoid were calculated (n = 5) (N). Scale bar: 100 μm. (O) PBS or 10⁵ NK cells separated from the spleen of C57BL/6J mice and injected intravenously into NSG mice to reestablish anti-tumor immunity the day before injecting MFC cells. After the 5 × 10⁶ AQP5⁺ or AQP5⁻ MFC cell subcutaneous injection, NK cells or PBS were intravenously injected on days 7, 14, and 21. Images and volume of subcutaneous tumors (n = 6/group). (P) NSG mice were treated with PBS or 10⁵ NK cells as in (O); representative images and statistical analysis of metastatic nodules in the lungs established with 5 × 10⁶ AQP5⁺ or AQP5⁻ MFC cells (n = 3/group). Scale bar: 2 mm. p values in (B)–(D), (G)–(I), (L)–(N), and (P) were calculated using a two-tailed Student’s t test; those in (F) and (O) were calculated using two-way ANOVA. Data in (C)–(H) and (L)–(P) are represented as mean ± SD; violin plot shows all points in (B) and (I).

Figure 2

Explore how AQP5⁺ GC cells blunt the anti-tumor activity of NK cells by decreasing the arginine production (A) KEGG enrichment analysis of metabolic pathways for differential metabolites in AQP5⁺ and AQP5⁻ AGS cells. (B) L-glutamate, L-glutamine, L-arginine, and L-ornithine levels in AQP5⁺ and AQP5⁻ AGS cells detected by targeted metabolic mass spectrometry (n = 5). (C) Schematic diagram of amino acid metabolism; blue: decreased in AQP5⁺ AGS cells; red: increased in AQP5⁺ AGS cells. (D) L-arginine, L-ornithine, L-glutamate, and L-glutamine levels in the medium of AQP5⁺ and AQP5⁻ gastric cancer cells detected by targeted metabolic mass spectrometry (n = 3). (E) Targeted metabolic mass spectrometry detection of L-arginine in GC tissues with different AQP5 expressions (n = 22). (F–H) Images (F), tumor volume (G), and tumor incidence (H) in subcutaneous tumors established with 5 × 10⁶ AQP5⁺ or AQP5⁻ MFC cells in C57BL/6J mice treated with daily oral gavage of different concentrations of L-arginine or PBS (n = 6/group). (I and J) Lung metastatic models established with AQP5⁺ and AQP5⁻ MFC cells (GFP-labeled) in C57BL/6J mice by tail vein injection; mice received daily oral gavage of different concentrations of L-arginine or PBS. Images (I) and statistical analysis (J) of metastatic nodules in the lungs (n = 3/group). Scale bar: 2 mm. (K) Proportion of NK cells in subcutaneous tumors corresponding to (F) detected by flow cytometry (AQP5⁺, n = 6); AQP5⁺+L-arginine (1 g/kg daily oral gavage), n = 6; AQP5⁺ + L-arginine (2 g/kg daily oral gavage), n = 4; AQP5⁻, n = 4). (L and M) Subcutaneous tumors established with 5 × 10⁶ AQP5⁺ MFC cells in C57BL/6J mice treated with anti-NK1.1 antibody (200 μg per mouse, twice weekly) or isotype control, followed by daily oral administration of L-arginine (2 g/kg) or PBS. (L) NK cell depletion efficiency was validated by flow cytometry analysis of peripheral blood (n = 12/group). (M) Representative images and tumor volume measurements of subcutaneous tumors are shown (n = 6/group). (N and O) NK cells co-cultured with AQP5⁺ AGS cells, AQP5⁻ AGS cells, or AQP5⁺ AGS cells supplemented with 40 nmol/mL L-arginine for 48 h and co-cultured with AGS cells. Images detected by live cell workstation (N); NK cells were labeled green by CFSE, and AGS cells were labeled red; statistical analysis for the mortality rates of tumor cells (O) (n = 3). Scale bar: 20 μm. (P–S) NK cells separated from the peripheral blood of healthy volunteers co-cultured with AQP5⁺ AGS cells, AQP5⁻ AGS cells, and AQP5⁺ AGS cells supplemented with 40 nmol/mL L-arginine in transwell chamber for 48 h. The L-arginine levels detected by ELISA (P), proliferative capacity detected by CFSE (Q), cytotoxicity (R), and relative expression of IFN-γ, TNF-α, and Gzma (S) in NK cells (n = 3). Statistical analyses, p values in (B), (D), (E), (J), (K), (L), and (P)–(S) were calculated using a two-tailed Student’s t test; in (G), (O), and (M) by two-way ANOVA test; and in (H) by log rank test. Data in (B), (D), (G), (J), (M), and (O)–(S) are represented as mean ± SD; violin plot shows all points in (K) and (L).

Figure 3

Analysis of the mechanism of AQP5 down-regulating ASS1 expression in GC (A) Schematic diagram of the urea cycle. (B) Proteomics analysis of the expression of the key enzyme in the UC (ASS1, CPS1, ASL, and OTC) in AQP5-OE and Ctrl (control group) AGS cells (n = 1). (C) Expression of ASS1 and ARG in AQP5⁺ and AQP5⁻ AGS cells detected by western blotting. (D) NK cells treated with supernatant collected from AQP5⁺ AGS cells, AQP5⁻ AGS cells, and ASS1-OE-AQP5⁺ AGS cells. Proliferative capacity (left) and cytotoxicity (right) in different groups of NK cells were evaluated (n = 3). (E–G) Images (E), tumor volume (F), and proportion of infiltrating NK cells (G) in subcutaneous tumors established with 5 × 10⁶ Ctrl AQP5⁺ or ASS1-OE AQP5⁺ MFC cells in C57BL/6 mice (n = 6/group). (H) Immunohistochemical analysis of ASS1 expression in gastric cancer tissues stratified by AQP5 expression levels (the same patient cohort as in Figure 1K). Scale bar: 500 and 200 μm. (I) qPCR detection of ASS1 expression in AQP5 AGS-knockdown (KD) cells or AQP5-KD AGS cells transfected with siRNA targeting DDX21, DDX5, DDX3X, DDX17, DHX9, DDX46, or FUS (n = 3). (J and K) Expression of ASS1 (J) and L-arginine levels in the medium (K) of AQP5-KD AGS cells or AQP5-KD AGS cells transfected with DHX9-KD siRNA or corresponding control cells (n = 3). (L) Confocal microscopy analysis of the location of AQP5 (red) and DHX9 (green) in AGS cells transfected with Ctrl or AQP5-OE lentivirus (n = 1). Scale bar: 20 μm. (M) Western blot analysis of DHX9 in the nucleus and cytoplasm of AGS cells transfected with Ctrl or AQP5-OE lentivirus (n = 1). (N and O) AQP5-overexpressing (N) and AQP5-knockdown (O) AGS cells co-transfected with DHX9-HA and KPNB1-Myc. Cell lysates were subjected to immunoprecipitation (IP) with anti-HA agarose and immunoblotted (n = 1). (P and Q) Gradient overexpression of AQP5 (P) or KPNB1 (Q) in 293T cells co-transfected with KPNB1-Myc or AQP5-FLAG and DHX9-HA. The cell lysates were subjected to IP with anti-HA agarose and immunoblotted (n = 1). (R and S) Western blotting (R) and confocal microscopy (S) detection of DHX9 (green) expression in the nucleus and cytoplasm of Ctrl or AQP5-OE AGS cells transfected with Ctrl or KPNB1-OE plasmid (n = 1). Scale bar: 50 μm. (T) Diagram summarizing the mechanism of AQP5 downregulation of L-arginine. AQP5 competitively binds DHX9 with KPNB1 to inhibit the nuclear translocation of the transcriptional regulatory protein, DHX9, and downregulate the expression of the key enzyme ASS1 and L-arginine production. p values in (D), (G), and (K) were calculated using a two-tailed Student’s t test and in (F) with a two-way ANOVA. Data in (D), (F), (I), and (K) are represented as mean ± SD; violin plot shows all points in (G).

Figure 4

Explore the mechanism of AQP5⁺ GC cells influencing anti-tumor activity of NK (A) NO OD(optical density) value in NK cells co-cultured with AQP5⁺ or AQP5⁻ AGS cells in transwell chamber treated with PBS or 40 nmol/mL L-arginine (n = 3). (B–D) NO OD value (B); proliferative capacity (C); and cytotoxicity (D) in NK cells co-cultured with AQP5⁺ AGS cells, AQP5⁻ AGS cells, or AQP5⁺ AGS cells with 40 nmol/mL L-arginine in transwell chamber and treated with DMSO or SMT (S-methylisothiourea, iNOS inhibitor) (n = 3). (E–K) Images (E), tumor volume (F), tumor incidence (G), L-arginine levels (H), NK cell proportion (I), proportion of TNF-α⁺ NK cells (J), and proportion of IFN-γ⁺ NK cells (K) in subcutaneous tumors established with AQP5-overexpressed MFC cells in Inos^fl/fl Ctrl mice and Inos^fl/flNcr1^cre mice or with AQP5-overexpressed MFC cells in Inos^fl/fl Ctrl mice and Inos^fl/flNcr1^cre mice receiving daily oral gavage of L-arginine (2 g/kg; n = 6/group). (L and M) Representative images (L) and statistical analysis (M) of metastatic nodules in the lungs established with AQP5-overexpressed MFC cells in Inos^fl/fl Ctrl mice and Inos^fl/flNcr1^cre mice or with AQP5-overexpressed MFC cells (GFP-labeled) in Inos^fl/fl Ctrl mice and Inos^fl/flNcr1^cre mice receiving daily oral gavage of L-arginine (2 g/kg; n = 3/group). Scale bar: 2 mm. p values in (A)–(D), (H)–(K), and (M) were calculated using a two-tailed Student’s t test; in (F) with two-way ANOVA; and in (G) with log rank test. Data in (A)–(D), (F), (H)–(K), and (M) are represented as mean ± SD.

Figure 5

Evaluate the effect of AQP5 on the bioenergy of GC cells (A) L-Arginine uptake ratio in AQP5⁺ AGS cells and AQP5⁻ AGS cells calculated by evaluating the L-arginine concentration in media by ELISA (n = 3). (B) Intracellular ATP levels in AQP5⁺ AGS cells and AQP5⁻ AGS cells at 72 h (n = 3). (C and D) Oxygen consumption rates (OCRs) of AQP5⁺ and AQP5⁻ AGS cells cultured under the same conditions as described for (B) (n = 3). (E) L-glutamic acid level detected by targeted metabolic mass spectrometry in tumor tissues expressing AQP5 (n = 22). (F) Amino acid levels in AQP5⁺ AGS cells and AQP5⁻ AGS cells detected by targeted metabolic mass spectrometry (n = 5). (G) Schematic diagram of the TCA cycle and UC. (H) Schematic diagram of intracellular fluxes in AGS cells quantified using U-13C6 glutamate tracer. Red circles, 13C atoms. (I) Bar charts represent the relative abundance of metabolites between AQP5⁺ AGS cells and AQP5⁻ AGS cells (n = 5 independent biological replicates). p values in (A), (B), (D)–(F), and (I) were calculated using a two-tailed Student’s t test. Data in (A)–(D), (F), and (I) are represented as mean ± SD; violin plot shows all points in (E).

Figure 6

Explore how AQP5 influences glutamine level in GC cells (A) L-glutamine levels detected by targeted metabolic mass spectrometry in tumor tissues expressing AQP5 (n = 22). (B) Schematic diagram of glutamate metabolism. (C and D) L-glutamine level was detected by ELISA (C) and intracellular ATP levels (D) in AQP5⁺ AGS cells, AQP5⁻ AGS cells, and AQP5⁺ AGS cells transfected with GLUL-KD or GLS-KD siRNA for 24 or 48 h (n = 3). (E) Western blot detection of GLUL and GLS expression in AQP5⁺ AGS cells and AQP5⁻ AGS cells (n = 1). (F and G) L-glutamine level (F) and L-arginine level (G) were detected by ELISA in AQP5⁺ AGS cells, AQP5⁻ AGS cells, and AQP5⁺ AGS cells transfected with GLUL-KD siRNA (n = 3). (H and I) AGS cells transfected with Ctrl or AQP5-OE lentivirus were treated with cycloheximide (CHX) for the indicated times (n = 1). (H) Western blots detect GLUL expression and (I) the quantification of relative GLUL levels (n = 3). (J–L) AQP5 overexpressed or knocked down in AGS cells, which were transfected with GLUL-HA. The cell lysates were subjected to immunoprecipitation (IP) with anti-HA agarose and immunoblotted. (M) AGS cells transfected with Ctrl or AQP5-OE lentivirus were co-transfected with UBB/UBC siRNA, K63-Ub-HA, or K63R-HA. IP assay was performed with anti-HA agarose, followed by immunoblotting (n = 1). (N) AGS cells transfected with Ctrl or AQP5-OE lentivirus were co-transfected with GLUL-HA and TRIM21-KD siRNA; cells were analyzed by IP assays with anti-HA agarose and immunoblotted (n = 1). (O) L-Glutamine level was detected by ELISA in AGS cells co-transfected with AQP5-OE lentivirus and TRIM21-KD siRNA or corresponding controls (n = 3). (P and Q) AQP5-knockdown (P) and AQP5-overexpressing (Q) AGS cells were co-transfected with GLUL-HA and TRIM21-Myc (n = 1). Cell lysates were subjected to IP with anti-HA agarose and immunoblotted. (R) Gradient overexpression of AQP5 in 293T cells co-transfected with TRIM21-Myc and GLUL-HA. The cell lysates were subjected to an IP assay with anti-HA agarose and immunoblotted (n = 1). p values in (A), (C), (D), (F), (G), and (O) were calculated using a two-tailed Student’s t test. Data in (C), (D), (F), (G), (I), and (O) are represented as mean ± SD; violin plot shows all points in (A).

Figure 7

Validation of anticancer effects of L-arginine and ULK1 inhibitors on PDO and PDOX models (A) Schematic diagram of PDO and PDOX model construction. (B) Snapshots of NK-92 cells co-cultured with PDOs generated with gastric tissues with AQP5 high or low expression were performed by microscopy in 24 h (left), and the NK cells per organoid were calculated (right) (n = 3). PDOs pre-labeled with red dye were inlaid in Matrigel, and NK cells were pre-labeled with CFSE. Scale bar: 100 μm. (C and D) PDOs generated with gastric tissues with AQP5 high or low expression were injected subcutaneously into mice (3–4 million cells per mice). When the tumor grew to 0.15–0.2 cm³, the mice were randomly grouped, and the drug treatment started. Tumors were examined over 27 days (n = 6/group); the tumor volume (left: images, right: the statistical analysis) (C) and tumor inhibition rate (D) were evaluated in the indicated groups at the indicated time points. (E) Proportion of NK cells in different groups of subcutaneous tumors detected by flow cytometry. Statistical analyses, p values in (B), (C), (D), and (E) were calculated using two-tailed Student’s t test. Data in (B–D) are represented as mean ± SD; violin plot shows all points in (E).