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Usage Information

Targeting TNF-α–producing macrophages activates antitumor immunity in pancreatic cancer via IL-33 signaling
Ajay Dixit, Aaron Sarver, Jon Zettervall, Huocong Huang, Kexin Zheng, Rolf A. Brekken, Paolo P. Provenzano
Ajay Dixit, Aaron Sarver, Jon Zettervall, Huocong Huang, Kexin Zheng, Rolf A. Brekken, Paolo P. Provenzano
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Research Article Oncology

Targeting TNF-α–producing macrophages activates antitumor immunity in pancreatic cancer via IL-33 signaling

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Abstract

Pancreatic ductal adenocarcinoma (PDA) remains resistant to immune therapies, largely owing to robustly fibrotic and immunosuppressive tumor microenvironments. It has been postulated that excessive accumulation of immunosuppressive myeloid cells influences immunotherapy resistance, and recent studies targeting macrophages in combination with checkpoint blockade have demonstrated promising preclinical results. Yet our understanding of tumor-associated macrophage (TAM) function, complexity, and diversity in PDA remains limited. Our analysis reveals significant macrophage heterogeneity, with bone marrow–derived monocytes serving as the primary source for immunosuppressive TAMs. These cells also serve as a primary source of TNF-α, which suppresses expression of the alarmin IL-33 in carcinoma cells. Deletion of Ccr2 in genetically engineered mice decreased monocyte recruitment, resulting in profoundly decreased TNF-α and increased IL-33 expression, decreased metastasis, and increased survival. Moreover, intervention studies targeting CCR2 with a new orthosteric inhibitor (CCX598) rendered PDA susceptible to checkpoint blockade, resulting in reduced metastatic burden and increased survival. Our data indicate that this shift in antitumor immunity is influenced by increased levels of IL-33, which increases dendritic cell and cytotoxic T cell activity. These data demonstrate that interventions to disrupt infiltration of immunosuppressive macrophages, or their signaling, have the potential to overcome barriers to effective immunotherapeutics for PDA.

Authors

Ajay Dixit, Aaron Sarver, Jon Zettervall, Huocong Huang, Kexin Zheng, Rolf A. Brekken, Paolo P. Provenzano

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Usage data is cumulative from August 2025 through August 2026.

Usage JCI PMC
Text version 2,238 234
PDF 278 70
Figure 1,021 5
Table 103 0
Supplemental data 616 34
Citation downloads 256 0
Totals 4,512 343
Total Views 4,855

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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