Gut microbial metabolite 4-hydroxybenzeneacetic acid drives colorectal cancer progression via accumulation of immunosuppressive PMN-MDSCs
Qing Liao, … , Yanqing Ding, Liang Zhao
Qing Liao, … , Yanqing Ding, Liang Zhao
Published April 3, 2025
Citation Information: J Clin Invest. 2025;135(11):e181243. https://doi.org/10.1172/JCI181243.
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Research Article Gastroenterology Immunology Oncology

Gut microbial metabolite 4-hydroxybenzeneacetic acid drives colorectal cancer progression via accumulation of immunosuppressive PMN-MDSCs

Abstract

Colorectal cancer (CRC) is characterized by an immune-suppressive microenvironment that contributes to tumor progression and immunotherapy resistance. The gut microbiome produces diverse metabolites that feature unique mechanisms of interaction with host targets, yet the role of many metabolites in CRC remains poorly understood. In this study, the microbial metabolite 4-hydroxybenzeneacetic acid (4-HPA) promoted the infiltration of PMN myeloid-derived suppressor cells (PMN-MDSCs) in the tumor microenvironment, consequently inhibiting the antitumor response of CD8+ T cells and promoting CRC progression in vivo. Mechanistically, 4-HPA activates the JAK2/STAT3 pathway, which upregulates CXCL3 transcription, thereby recruiting PMN-MDSCs to the CRC microenvironment. Selective knockdown of CXCL3 resensitized tumors to anti-PD-1 immunotherapy in vivo. Chlorogenic acid reduces the production of 4-HPA by microbiota, likewise abolishing 4-HPA–mediated immunosuppression. The 4-HPA content in CRC tissues was notably increased in patients with advanced CRC. Overall, the gut microbiome uses 4-HPA as a messenger to control chemokine-dependent accumulation of PMN-MDSC cells and regulate antitumor immunity in CRC. Our findings provide a scientific basis for establishing clinical intervention strategies to reverse the tumor immune microenvironment and improve the efficacy of immunotherapy by reducing the interaction among intestinal microbiota, tumor cells, and tumor immune cells.

Authors

Qing Liao, Ximing Zhou, Ling Wu, Yuyi Yang, Xiaohui Zhu, Hangyu Liao, Yujie Zhang, Weidong Lian, Feifei Zhang, Hui Wang, Yanqing Ding, Liang Zhao

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Figure 3

Knockdown CXCL3 inhibits tumor growth by preventing PMN-MDSC accumulation and activating CD8+ T-cell infiltration.

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Knockdown CXCL3 inhibits tumor growth by preventing PMN-MDSC accumulatio...
(A) Knockdown of Ccl20 and Cxcl3 inhibits the growth of CT26 subcutaneous tumors in nude mice (n = 5). A photograph of CT26 subcutaneous tumors in nude mice and a graph of tumor growth are shown. (B) Knockdown of Ccl20 and Cxcl3 inhibits the growth of CT26 subcutaneous tumors in BALB/c mice (n = 5). A photograph of CT26 subcutaneous tumors in BALB/c mice and a graph of tumor growth are shown. (C) Neutralizing antibodies of Ccl20 and Cxcl3 inhibited subcutaneous tumors in BALB/c mice(n = 6). A photograph of CT26 subcutaneous tumors in BALB/c mice and a graph of tumor growth are shown. (D) Knockdown of Ccl20 and Cxcl3 inhibits the progression of CT26 orthotopic implanted tumor in BALB/c mice (n = 5). Representative tumor images and tumor load are shown. (E) The percentage of PMN-MDSCs (CD11b+Ly6G+Ly6Clow) in TILs (CD45+) of orthotopic implanted CRC mice detected by flow cytometry sorting. A bar chart indicating statistical values is presented (n = 5). (F) The percentage of Tregs (CD4+Foxp3+) in TILs (CD45+) of orthotopic implanted CRC mice detected by flow cytometry sorting. A bar chart indicating statistical values is presented (n = 5). (G and H) Tumor-infiltrating CD8+T cells and their granule production (GzmB+) in TILs (CD45+) of orthotopic implanted CRC mice detected by flow cytometry sorting. Bar charts indicating statistical values are presented (n = 5). (I) MDSCs (Gr-1+), Tregs (CD4+, Foxp3+), and CD8+ T-cell infiltration in tumor tissues of orthotopic implanted CRC mice. Representative IHC images are shown. (J) Histogram showing the number of Gr-1+, CD4+, Foxp3+, and CD8+ cells per ×20 objective lens visual field (n = 5). Data represent the mean ± SD of 3 independent experiments. We used 2-way ANOVA to determine statistical significance of subcutaneous tumor volume. The remaining statistical methods were conducted using 1-way ANOVA with Dunnett’s T3 correct multiple-comparison test. *P < 0.05, **P < 0.005, ***P < 0.0005. sh, short hairpin.