Transcriptomic Analysis of T cell Exhaustion Signatures Reveals a Severity Spectrum in Chronic Skin Diseases
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://data.mendeley.com/datasets/c297bm6k96
下载链接
链接失效反馈官方服务:
资源简介:
Transcriptomic analysis was performed on publicly available skin biopsy datasets of melanoma, plaque psoriasis, rosacea, cutaneous lupus erythematosus, leprosy, leishmaniasis, and diabetic foot ulcer patients. Immune cell proportions were estimated using CIBERSORTx with the LM22 signature matrix. A panel of 42 T cell exhaustion–related genes was extracted to construct a matrix for Principal Component Analysis (PCA), enabling comparison of exhaustion signatures.
T cell infiltration and transcriptomic profiling revealed three core exhaustion patterns: γδ T cell expansion, CD4⁺ memory imbalance, and Treg depletion. PCA stratified diseases by exhaustion severity, with melanoma, psoriasis, and leishmaniasis showing terminal exhaustion signatures, while rosacea and lupus subtypes exhibited intermediate profiles.
创建时间:
2025-09-23



