Emerging Gene Therapeutics for Epidermolysis Bullosa under Development.
Johannes BischofMarkus HierlUlrich KollerPublished in: International journal of molecular sciences (2024)
The monogenetic disease epidermolysis bullosa (EB) is characterised by the formation of extended blisters and lesions on the patient's skin upon minimal mechanical stress. Causal for this severe condition are genetic mutations in genes, leading to the functional impairment, reduction, or absence of the encoded protein within the skin's basement membrane zone connecting the epidermis to the underlying dermis. The major burden of affected families justifies the development of long-lasting and curative therapies operating at the genomic level. The landscape of causal therapies for EB is steadily expanding due to recent breakthroughs in the gene therapy field, providing promising outcomes for patients suffering from this severe disease. Currently, two gene therapeutic approaches show promise for EB. The clinically more advanced gene replacement strategy was successfully applied in severe EB forms, leading to a ground-breaking in vivo gene therapy product named beremagene geperpavec (B-VEC) recently approved from the US Food and Drug Administration (FDA). In addition, the continuous innovations in both designer nucleases and gene editing technologies enable the efficient and potentially safe repair of mutations in EB in a potentially permanent manner, inspiring researchers in the field to define and reach new milestones in the therapy of EB.
Keyphrases
- gene therapy
- genome wide
- copy number
- drug administration
- genome wide identification
- end stage renal disease
- early onset
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- soft tissue
- type diabetes
- genome wide analysis
- small molecule
- stem cells
- peritoneal dialysis
- gene expression
- mesenchymal stem cells
- risk assessment
- adipose tissue
- big data
- machine learning
- case report
- rectal cancer
- skeletal muscle
- heat stress
- deep learning
- binding protein
- transcription factor
- artificial intelligence
- smoking cessation