Baseline profile peripheral Tfh cells predict immune-related adverse events in immune checkpoint inhibitor therapy of gastrointestinal cancer
Frontiers in Immunology, 2025
Wang Y., Zhang Z., Xie T., Liu Y., Zhang C., Li H., Feng R., Huang B., Liu Q., Wang N., Xing X., Han Y., Li X., Wang R., He J., Peng Z.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Oncology Immunotherapy | Pathophysiology | Serum |  Olink Target 96 |
Abstract
Background
Immune checkpoint inhibitors (ICIs) have transformed cancer therapy but are limited by immune-related adverse events (irAEs). This study aimed to assess peripheral T cell profiles to identify irAEs biomarkers and construct predictive models.
Methods
In our study, we enrolled and followed 51 gastrointestinal cancer patients receiving anti-PD-1/PD-L1 therapies, with 22 developed irAEs (AE) and 29 didn’t (NAE). We examined their peripheral blood using Olink technology, RNA-seq, and flow cytometry to explore the immunological characteristics of their circulating environment before and after early stages of ICIs treatment.
Results
Our study discovered after early stages of ICIs treatment, a stronger upregulation of T cell activation genes, particularly Tfh-associated genes, was observed in AE patients. Flow cytometry result confirmed that AE patients exhibited elevated CD4+CXCR5–ICOS+ cells (p<0.01), CD4+CXCR5+ICOS+ cells (p<0.05) and Th1/Th2 ratio (p<0.05) after early stages. At baseline, AE patients had higher levels of serum inflammatory proteins including IL-12β, IL-15RA and CXCL9 (p<0.05). Higher peripheral Tfh (p<0.05), Tph (p<0.001) were also observed in the baseline flow cytometry result of AE patients compared to NAE patients. Based on these findings, predictive models for both irAEs and grade 2–4 irAEs were established, demonstrating good discriminatory ability.
Conclusion
This study demonstrates that high-dimensional immune profiling can uncover novel blood-based immune signatures associated with the risk and mechanism of severe irAEs are effective biomarkers for predicting irAEs at both baseline and early stages of ICIs treatment.