# Trained immunity in cancer and autoimmunity: a double-edged sword in immune memory reprogramming

**Authors:** Nasrin Salari, Mehrshad Shams, Fatemeh Tavassoli Razavi, Esmaeil Yazdanpanah, Valentyn Oksenych, Dariush Haghmorad

PMC · DOI: 10.3389/fimmu.2026.1782830 · Frontiers in Immunology · 2026-03-18

## TL;DR

Trained immunity can help fight cancer but also worsen autoimmune diseases, making it a complex target for immune therapies.

## Contribution

This review highlights the dual role of trained immunity in cancer and autoimmunity and proposes therapeutic strategies to modulate it.

## Key findings

- Trained immunity enhances antitumor responses through innate cell cytotoxicity and tumor microenvironment remodeling.
- Maladaptive trained immunity can drive autoimmune diseases like rheumatoid arthritis and lupus.
- Therapeutic modulation of trained immunity offers potential for cancer immunotherapy and autoimmunity control.

## Abstract

Trained immunity, characterized by the long-term functional reprogramming of innate immune cells through epigenetic and metabolic modifications, has emerged as a pivotal concept bridging innate and adaptive immune responses. This review explores the dual role of trained immunity as both a protective mechanism in cancer and a pathogenic driver in autoimmune diseases. We first discuss the underlying mechanisms involving histone modifications, chromatin remodeling, and metabolic pathways such as glycolysis and the mTOR/HIF-1α axis, alongside key regulators including NOD2 and pattern recognition receptors. The contribution of trained immunity to antitumor responses is highlighted through its ability to enhance innate cell cytotoxicity, remodel the tumor microenvironment, and synergize with immune checkpoint blockade and BCG immunotherapy. Conversely, we examine how infections, dysbiosis, and dietary factors can induce maladaptive trained immunity, leading to persistent hyperinflammatory states and exacerbation of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis. Furthermore, we address therapeutic strategies to modulate trained immunity, including small molecules, β-glucan, statins, and BCG derivatives, emphasizing their potential applications in cancer immunotherapy and autoimmunity control. We also underscore the risks of unintended immune activation, such as autoimmune flare-ups during cancer treatment or compromised host defense during immunosuppression. Finally, we discuss future directions, including the development of trained immunity-based vaccines, personalized immunomodulatory approaches, and the integration of multi-omics and artificial intelligence to design patient-specific interventions. Understanding the complex interplay between trained immunity, cancer, and autoimmunity will be crucial for translating these insights into innovative therapeutic strategies.

## Linked entities

- **Proteins:** NOD2 (nucleotide binding oligomerization domain containing 2), MTOR (mechanistic target of rapamycin kinase), HIF1A (hypoxia inducible factor 1 subunit alpha)
- **Diseases:** cancer (MONDO:0004992), rheumatoid arthritis (MONDO:0008383), systemic lupus erythematosus (MONDO:0007915), multiple sclerosis (MONDO:0005301)

## Full-text entities

- **Genes:** NOD2 (nucleotide binding oligomerization domain containing 2) [NCBI Gene 64127] {aka ACUG, BLAU, BLAUS, CARD15, CD, CLR16.3}, MTOR (mechanistic target of rapamycin kinase) [NCBI Gene 2475] {aka FRAP, FRAP1, FRAP2, RAFT1, RAPT1, SKS}, HIF1A (hypoxia inducible factor 1 subunit alpha) [NCBI Gene 3091] {aka HIF-1-alpha, HIF-1A, HIF-1alpha, HIF1, HIF1-ALPHA, MOP1}
- **Diseases:** cancer (MESH:D009369), multiple sclerosis (MESH:D009103), systemic lupus erythematosus (MESH:D008180), autoimmune diseases (MESH:D001327), infections (MESH:D007239), rheumatoid arthritis (MESH:D001172), dysbiosis (MESH:D064806)
- **Chemicals:** beta-glucan (MESH:D047071)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13038919/full.md

## References

153 references — full list in the complete paper: https://tomesphere.com/paper/PMC13038919/full.md

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Source: https://tomesphere.com/paper/PMC13038919