Transcriptome-guided drug repurposing of aggressive SCCs

The incidence of cutaneous squamous cell carcinomas (SCCs) has risen remarkably in recent years, however, most of these tumors are well treatable at an early stage of diagnosis. In contrast, SCCs arising in patients suffering from the recessive-dystrophic subtype of the rare genetic skin disease epidermolysis bullosa (RDEB, butterfly children) take a particularly aggressive course. The low number of patients suffering from RDEB poses a big challenge for traditional drug-discovery approaches and efficient treatment options for RDEB-SCCs urgently awaited. Here, we aim at identifying novel anti-cancer drugs for RDEB patients by virtually screening compounds that are already approved for other diseases. Such drug repurposing offers a cheaper and faster route to clinical application than a novel medicine, as safety and interaction studies are typically available. We mined a publicly accessible data repository, comprising transcriptome profiles from drug perturbation experiments on human cells, to identify drugs predicted to affect the characteristic SCC-gene expression profile, thereby reversing the tumor state towards that of healthy tissue. In order to provide proof-of-concept of the applied computational drug discovery approach and to demonstrate efficacy of the drug candidates, a xenograft model as well as cell-based in vitro assays will be applied. Our project will provide the basis for the timely clinical translation of the tested drugs, if we can demonstrate their efficacy against RDEB-SCCs. Moreover, given a first successful identification of promising drugs, our project will encourage the implementation of such in silico tools also for other rare diseases.