Glycolysis drives STING signaling to facilitate dendritic cell antitumor function
Zhilin Hu, … , Jiayuan Sun, Qiang Zou
Zhilin Hu, … , Jiayuan Sun, Qiang Zou
Published February 23, 2023
Citation Information: J Clin Invest. 2023;133(7):e166031. https://doi.org/10.1172/JCI166031.
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Research Article Immunology Metabolism

Glycolysis drives STING signaling to facilitate dendritic cell antitumor function

Abstract

Activation of STING signaling in DCs promotes antitumor immunity. Aerobic glycolysis is a metabolic hallmark of activated DCs, but how the glycolytic pathway intersects with STING signaling in tumor-infiltrating DCs remains elusive. Here, we show that glycolysis drives STING signaling to facilitate DC-mediated antitumor immune responses. Tumor-infiltrating DCs exhibited elevated glycolysis, and blockade of glycolysis by DC-specific Ldha/Ldhb double deletion resulted in defective antitumor immunity. Mechanistically, glycolysis augmented ATP production to boost STING activation and STING-dependent DC antitumor functions. Moreover, DC-intrinsic STING activation accelerated HIF-1α–mediated glycolysis and established a positive feedback loop. Importantly, glycolysis facilitated STING-dependent DC activity in tissue samples from patients with non–small cell lung cancer. Our results provide mechanistic insight into how the crosstalk of glycolytic metabolism and STING signaling enhances DC antitumor activity and can be harnessed to improve cancer therapies.

Authors

Zhilin Hu, Xiaoyan Yu, Rui Ding, Ben Liu, Chuanjia Gu, Xiu-Wu Pan, Qiaoqiao Han, Yuerong Zhang, Jie Wan, Xin-Gang Cui, Jiayuan Sun, Qiang Zou

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Figure 2

Blockade of glycolysis inhibits DC antitumor function.

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Blockade of glycolysis inhibits DC antitumor function. (A and B) Tumor g...
(A and B) Tumor growth (n = 10; A) and survival curves (n = 10; B) of mice inoculated s.c. with MC38 cells. Representative data shown in A and B are from different experiments. (C) The numbers of DCs in the draining lymph nodes (dLN) and tumors of tumor-bearing mice on day 14 after tumor inoculation (n = 4). (D) Flow cytometry analysis of CD80 and MHC-I expression in tumor-infiltrating DCs from tumor-bearing mice (n = 3). (E) Flow cytometric analysis of the division of CTV-labeled OT-I T cells cocultured with tumor-infiltrating DCs (n = 3). (F) ECAR of tumor-infiltrating DCs from tumor-bearing mice (n = 4). (G) Immunoblot analysis of tumor-infiltrating DCs from tumor-bearing mice. The numbers indicate the relative densities of indicated protein bands normalized to β-actin. (H) qRT-PCR analysis of isolated tumor-infiltrating DCs from tumor-bearing mice. (I and J) Flow cytometry analysis of T cells from tumor-bearing mice on day 14. (K) Tumor growth of MC38 tumor-bearing WT mice transferred with cGAMP-stimulated BMDCs on day 3 after tumor injection (n = 9). (L) Flow cytometry analysis of tumor-infiltrating T cells of the mice from K. (M) Tumor growth of mice after i.p. injection with 500 μg DMXAA on day 7 after MC38 tumor injection (n = 7). Ctrl, without DMXAA injection. (N) Flow cytometry analysis of tumor-infiltrating T cells of the mice from M. Representative data are shown from 3 independent experiments. Data are shown as the mean ± SEM. Statistical analysis was performed using 2-way ANOVA (A, K, and M), log-rank (Mantel-Cox) test (B), 1-way ANOVA (N), and 2-tailed Student’s t test (C–F, H–J, and L); *P < 0.05; **P < 0.01.