Transcriptome-Guided Drug Repurposing for Aggressive SCCs

• Published in: International journal of molecular sciences Vol. 23; no. 2; p. 1007
• Main Authors: Zauner, Roland, Wimmer, Monika, Dorfer, Sonja, Ablinger, Michael, Koller, Ulrich, Piñón Hofbauer, Josefina, Guttmann-Gruber, Christina, Bauer, Johann W., Wally, Verena
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 17.01.2022; MDPI
• Subjects: Antineoplastic Agents - pharmacology; Antineoplastic Agents - therapeutic use; Cancer therapies; Carcinoma, Squamous Cell - drug therapy; Carcinoma, Squamous Cell - etiology; Carcinoma, Squamous Cell - genetics; Computational Biology - methods; Data Mining; Datasets; Drug Repositioning; Drugs; Epidermolysis Bullosa Dystrophica - complications; Epidermolysis Bullosa Dystrophica - genetics; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic - drug effects; Gene Regulatory Networks - drug effects; Growth factors; Human papillomavirus; Humans; Immunocompetence; Kinases; Metastasis; Mutation; Organ Transplantation - adverse effects; Proteins; RNA-Seq; Skin Neoplasms - drug therapy; Skin Neoplasms - etiology; Skin Neoplasms - genetics; Tumors; organ transplant recipients; drug repurposing; epidermolysis bullosa; squamous cell carcinoma
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms23021007

Despite a significant rise in the incidence of cutaneous squamous cell carcinoma (SCC) in recent years, most SCCs are well treatable. However, against the background of pre-existing risk factors such as immunosuppression upon organ transplantation, or conditions such as recessive dystrophic epidermolysis bullosa (RDEB), SCCs arise more frequently and follow a particularly aggressive course. Notably, such SCC types display molecular similarities, despite their differing etiologies. We leveraged the similarities in transcriptomes between tumors from organ transplant recipients and RDEB-patients, augmented with data from more common head and neck (HN)-SCCs, to identify drugs that can be repurposed to treat these SCCs. The in silico approach used is based on the assumption that SCC-derived transcriptome profiles reflect critical tumor pathways that, if reversed towards healthy tissue, will attenuate the malignant phenotype. We determined tumor-specific signatures based on differentially expressed genes, which were then used to mine drug-perturbation data. By leveraging recent efforts in the systematic profiling and cataloguing of thousands of small molecule compounds, we identified drugs including selumetinib that specifically target key molecules within the MEK signaling cascade, representing candidates with the potential to be effective in the treatment of these rare and aggressive SCCs.