bioRxivImmunologyPreprint
IGF1 modulates lesional skin inflammation in checkpoint inhibitor-induced lichen planus
Noah I. HornickiD, Avery BilloiD, Rosalyn M. FeyiD, Reed M. HawkinsiD, Fiorinda F. MuhajiD, Kristen N. RichardsiD, Anisha B. PateliD, Jason M. SchenkeliD, Kristen E. PaukeniD, Amy E. MoraniD
Abstract
Immune checkpoint inhibitor-induced lichen planus (ICI-LP) is a cutaneous immune related adverse event (irAE) that shares key clinicopathologic features with spontaneous lichen planus (LP) but differs histologically and in the sex distribution of its incidence, and may therefore reflect a distinct tissue inflammatory state. To define the cellular programs that distinguish ICI-LP from LP, we profiled lesional skin by single cell and spatial transcriptomic approaches. We found few differences in the T cell and keratinocyte compartments between ICI-LP and LP, which shared similar inflammatory signatures. Rather, the dominant transcriptional features differentiating these two eruptions occurred within the fibroblast and myeloid cell compartments. Fibroblasts in ICI-LP were enriched for IGF1, FGF7, and androgen-response-associated programs, whereas myeloid cells exhibited amplified JAK-STAT and interferon-responsive states spanning both type I and type II interferon signatures. The potential role of androgen response in shaping lichenoid inflammation was supported by a striking loss of androgen receptor expression in lesional keratinocytes by immunohistochemistry. Furthermore, using spatial RNA and transcriptomic approaches, we identified anatomically segregated IFNG, IL17A, and IL13 niches within lesional skin, suggesting that regional immune compartmentalization with differences in local immunoregulation may explain the mixed inflammatory features reported in both ICI-LP and LP. Collectively, these data indicate that ICI-LP is not simply a more inflamed form of LP, but a distinct form of the disease with more prominent inflammatory perturbations within stromal and innate immune cell populations.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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