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Skin Abnormalities at Checkpoint Inhibitor Therapy Initiation Are Associated With Skin Rash Development in Oncology
Taras Lyubchenko1, Evgeny Berdyshev1, Ryan M Weight2
1National Jewish Health, Denver, Colorado, USA.
Allergy
|July 25, 2026
Summary
Skin lipid abnormalities and increased inflammatory cytokines in the skin, but not plasma, predict immune-related cutaneous adverse events (ircAEs) in cancer patients receiving checkpoint inhibitor (CPI) immunotherapy.
Area of Science:
- Oncology
- Immunotherapy
- Dermatology
Background:
- Immune-related cutaneous adverse events (ircAEs) are common side effects of checkpoint inhibitor (CPI) immunotherapy.
- Early detection and monitoring of 7ircAEs are crucial for patient adherence to cancer treatment.
- Novel biomarkers are needed to predict and manage ircAE development.
Purpose of the Study:
- To identify biomarkers for early prediction of ircAEs.
- To investigate changes in skin lipids and cytokines before and during CPI therapy.
- To differentiate between skin and plasma biomarkers for ircAE prediction.
Main Methods:
- Prospective collection of skin tape strips (STS) and plasma from 22 cancer patients undergoing CPI therapy.
- Analysis of STS for cytokines and lipids, and plasma for cytokines at baseline and 6 weeks.
- Correlation of molecular findings with the development of 7ircAEs over a 6-month follow-up period.
Main Results:
- Patients who developed 7ircAEs showed increased stratum corneum (SC) ceramides with short-chain fatty acids prior to CPI treatment.
- These SC lipid abnormalities were exacerbated after 6 weeks of CPI therapy.
- Elevated levels of skin cytokines (IL-8, IL-18, IP-10, IL-12, IFNa, MDC, TARC) were observed in patients who developed 7ircAEs, but not in plasma.
Conclusions:
- STS analysis can reveal pre-existing SC lipid abnormalities that predict 7ircAE development.
- CPI therapy can worsen these skin barrier defects and increase local inflammatory cytokine production.
- These findings suggest potential for early 7ircAE risk identification and monitoring through skin-based biomarkers.
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