Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

ST2 as checkpoint target for colorectal cancer immunotherapy
Kevin Van der Jeught, Yifan Sun, Yuanzhang Fang, Zhuolong Zhou, Hua Jiang, Tao Yu, Jinfeng Yang, Malgorzata M. Kamocka, Ka Man So, Yujing Li, Haniyeh Eyvani, George E. Sandusky, Michael Frieden, Harald Braun, Rudi Beyaert, Xiaoming He, Xinna Zhang, Chi Zhang, Sophie Paczesny, Xiongbin Lu
Kevin Van der Jeught, Yifan Sun, Yuanzhang Fang, Zhuolong Zhou, Hua Jiang, Tao Yu, Jinfeng Yang, Malgorzata M. Kamocka, Ka Man So, Yujing Li, Haniyeh Eyvani, George E. Sandusky, Michael Frieden, Harald Braun, Rudi Beyaert, Xiaoming He, Xinna Zhang, Chi Zhang, Sophie Paczesny, Xiongbin Lu
View: Text | PDF
Research Article Immunology Inflammation

ST2 as checkpoint target for colorectal cancer immunotherapy

  • Text
  • PDF
Abstract

Immune checkpoint blockade immunotherapy delivers promising clinical results in colorectal cancer (CRC). However, only a fraction of cancer patients develop durable responses. The tumor microenvironment (TME) negatively impacts tumor immunity and subsequently clinical outcomes. Therefore, there is a need to identify other checkpoint targets associated with the TME. Early-onset factors secreted by stromal cells as well as tumor cells often help recruit immune cells to the TME, among which are alarmins such as IL-33. The only known receptor for IL-33 is stimulation 2 (ST2). Here we demonstrated that high ST2 expression is associated with poor survival and is correlated with low CD8+ T cell cytotoxicity in CRC patients. ST2 is particularly expressed in tumor-associated macrophages (TAMs). In preclinical models of CRC, we demonstrated that ST2-expressing TAMs (ST2+ TAMs) were recruited into the tumor via CXCR3 expression and exacerbated the immunosuppressive TME; and that combination of ST2 depletion using ST2-KO mice with anti–programmed death 1 treatment resulted in profound growth inhibition of CRC. Finally, using the IL-33trap fusion protein, we suppressed CRC tumor growth and decreased tumor-infiltrating ST2+ TAMs. Together, our findings suggest that ST2 could serve as a potential checkpoint target for CRC immunotherapy.

Authors

Kevin Van der Jeught, Yifan Sun, Yuanzhang Fang, Zhuolong Zhou, Hua Jiang, Tao Yu, Jinfeng Yang, Malgorzata M. Kamocka, Ka Man So, Yujing Li, Haniyeh Eyvani, George E. Sandusky, Michael Frieden, Harald Braun, Rudi Beyaert, Xiaoming He, Xinna Zhang, Chi Zhang, Sophie Paczesny, Xiongbin Lu

×

Usage data is cumulative from March 2025 through March 2026.

Usage JCI PMC
Text version 1,251 136
PDF 136 31
Figure 463 0
Supplemental data 172 6
Citation downloads 120 0
Totals 2,142 173
Total Views 2,315
(Click and drag on plot area to zoom in. Click legend items above to toggle)

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.

Advertisement

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts