Computational discovery of precision therapeutics for hidradenitis suppurativa

Abstract Hidradenitis suppurativa (HS) is an underdiagnosed chronic, immune-mediated inflammatory skin disease that causes severe pain, drainage, and scarring, leading to significant physical and psychosocial burdens. HS is characterized by heterogenous molecular changes that are poorly understood, posing a significant challenge for drug development. Therapeutic options remain limited, and many patients experience disease relapse despite treatment. Therefore, precision medicine approaches are urgently needed to identify new therapies for HS. Here, we combine integrative transcriptomics, large-scale drug perturbational datasets, and translational immunology to identify sirolimus, pioglitazone, and fulvestrant as novel therapies for HS that can directly target and reverse the HS disease gene signature in immune cell types relevant to HS pathogenesis. Using a novel ex vivo HS skin model, sirolimus, pioglitazone, and fulvestrant inhibited T cell proliferation and activation, and suppressed the production of pro-inflammatory cytokines from HS skin. These results show that unbiased data-driven precision medicine approaches can identify novel therapies for HS and can serve more generally as a model approach for therapeutic discovery in other chronic inflammatory diseases. One Sentence Summary Data-driven precision medicine approach identifies sirolimus, pioglitazone, and fulvestrant as novel therapies for hidradenitis suppurativa