Psoriasis affects more than 125 million people worldwide, and while biologic therapies that block the IL-17 pathway have transformed treatment, they remain expensive, require injection, and suppress the immune system systemically. A new study published in Nature Communications on July 6 opens the door to a different approach: topical creams that achieve the same effect through entirely different molecular targets.
Researchers at Biohub Chicago and Northwestern University used a genome-wide CRISPR knockout screen in primary human keratinocytes, the skin cells that drive psoriatic inflammation, and combined it with an artificial intelligence framework called VirtualCRISPR to identify two unexpected drug targets: ALOX5 (arachidonate 5-lipoxygenase) and OXTR (the oxytocin receptor).
When the team tested existing drugs that block these targets, zileuton (an FDA-approved ALOX5 inhibitor for asthma) and cligosiban (an OXTR antagonist previously developed for premature ejaculation), as topical treatments in a mouse model of psoriasis, both matched the efficacy of a systemic anti-IL17RA antibody.
How the screen worked
The researchers used the Brunello sgRNA library, targeting roughly 19,000 genes, to knock out each gene in primary human keratinocytes. After five population doublings, they sorted cells by surface IL17RA expression, the receptor for the key inflammatory signal in psoriasis, and sequenced the sgRNA representation in the top and bottom 5% of cells. This revealed which genes, when disrupted, caused keratinocytes to express more or less IL17RA.
But a genome-wide screen produces thousands of candidate hits, most of them already known regulators. To separate signal from noise, the team deployed VirtualCRISPR, a large language model trained on functional genomics data. The AI framework answers the question: “Does perturbation of gene X in cell type Y result in phenotype Z?” By prioritizing genes that showed high experimental enrichment but low VirtualCRISPR probability, meaning their role in IL17RA regulation was genuine but not previously understood, the team zeroed in on ALOX5 and OXTR in a fraction of the time traditional methods would require.
Two targets, two mechanisms
ALOX5 produces lipid mediators called leukotrienes, which were found to stabilize IL17RA on the keratinocyte surface. OXTR, through calcium-dependent signaling, reprograms cellular metabolism to regulate IL17RA expression. Both targets converge on the same receptor but through distinct, cell-intrinsic pathways.
In the mouse model of imiquimod-induced psoriasiform dermatitis, topical zileuton and topical cligosiban each suppressed skin inflammation, reduced pathogenic Th17 and Tc17 responses, polarized macrophages toward anti-inflammatory phenotypes, and normalized epidermal hyperproliferation. Proteomic profiling confirmed on-target pharmacology and revealed that both drugs converged on suppressing neutrophil-keratinocyte inflammatory circuits.
“The fact that topical drugs can match a systemic biologic is encouraging,” the authors note. “It suggests we may be able to treat psoriasis locally, avoiding the side effects and inconvenience of injections.”
Caveats
The study is preclinical. The imiquimod mouse model is an acute model of skin inflammation, not a direct recapitulation of chronic human psoriasis. Zileuton is currently only approved as an oral tablet for asthma, a topical formulation for psoriasis would require separate clinical development. Cligosiban previously failed a Phase IIb trial for premature ejaculation, though its safety profile was deemed acceptable and its mechanism of action in skin is distinct.
Human clinical trials for topical use have not yet been conducted. The team has filed a provisional patent (US 63/944,804) covering the methods and findings.
Sources
- Zhao, C., Shih, M., Ahmed, S., et al. “AI-guided CRISPR screening reveals therapeutic targets in psoriasis.” Nature Communications (2026). DOI: 10.1038/s41467-026-75249-5. https://www.nature.com/articles/s41467-026-75249-5
- LifeScience.net: Preprint listing. https://www.lifescience.net/preprints/10105/ai-guided-crispr-screen-accelerates-discovery-of-n/