Background
Decitabine is an anticancer medicine that acts by epigenetic regulation of DNA. It activates viral elements in the human genome called endogenous retroviruses which, in turn, induce the expression of interferon-β that is designed to combat viruses and suppress cancer growth. However, this mechanism, known as the viral mimicry hypothesis, was drawn from studies using cell cultures. The contribution of this mechanism to the anticancer effect of decitabine in the human body is still uncertain.
What We Studied
This study aimed to investigate viral mimicry in mice. The mouse mammary tumor virus (MMTV) is an endogenous retrovirus of the mouse. We inoculated mice with cancer cells which grew into tumors and subsequently treated the mice with decitabine.
Key Findings
Decitabine slowed down the growth of the tumors with a concomitant enhancement of the expression of MMTV and interferon-β in tumor tissues. Knocking down either MMTV or interferon-β rendered the tumors resistant to decitabine. We also discovered an upregulation of the interferon regulatory factor 7 (IRF7) in the tumors by decitabine treatment. Importantly, expression of IRF7 decreased over the course of treatment.
What It Means
These findings indicate that viral mimicry is a major mechanism of the anticancer effect of decitabine in live animals, and interferon-β is a major mediator. The temporal decline of IRF7 expression suggests negative feedback or “burnout” in the action of interferon-β and provides an explanation for the eventual failure of decitabine in cancer treatment.
Clinical Implication
Because interferons are known to activate immune checkpoints, this study strengthens the theoretical basis for combining decitabine with immune checkpoint inhibitors.
Reference:
Ryan Johnson, Andrew Brola, Cade Wycoff, William Wycoff, Seth Neumeyer, Richard Tuttle, Sarah Light, Jiayi Li, Stephen Christensen, Yingguang Liu
Decitabine suppresses tumor growth by activating mouse mammary tumor virus and interferon-β pathways.
Biomol Biomed [Internet]. 2025 Aug. 27 [cited 2025 Oct. 30];26(3):424–432.
Available from: https://www.bjbms.org/ojs/index.php/bjbms/article/view/12852
Additional information:
We invite submissions for our upcoming thematic issues, including:
- Immune Prediction and Prognostic Biomarkers in Immuno-Oncology
- Artificial Intelligence and Machine Learning in disease diagnosis and treatment target identification
More news: Blog
Editor: Merima Hadžić
Leave a Reply