FAK Signaling in Rhabdomyosarcoma.
Clara PerroneSilvia PomellaMatteo CassandriMaria Rita BraghiniMichele PezzellaFranco LocatelliRossella RotaPublished in: International journal of molecular sciences (2020)
Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of children and adolescents. The fusion-positive (FP)-RMS variant expressing chimeric oncoproteins such as PAX3-FOXO1 and PAX7-FOXO1 is at high risk. The fusion negative subgroup, FN-RMS, has a good prognosis when non-metastatic. Despite a multimodal therapeutic approach, FP-RMS and metastatic FN-RMS often show a dismal prognosis with 5-year survival of less than 30%. Therefore, novel targets need to be discovered to develop therapies that halt tumor progression, reducing long-term side effects in young patients. Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that regulates focal contacts at the cellular edges. It plays a role in cell motility, survival, and proliferation in response to integrin and growth factor receptors' activation. FAK is often dysregulated in cancer, being upregulated and/or overactivated in several adult and pediatric tumor types. In RMS, both in vitro and preclinical studies point to a role of FAK in tumor cell motility/invasion and proliferation, which is inhibited by FAK inhibitors. In this review, we summarize the data on FAK expression and modulation in RMS. Moreover, we give an overview of the approaches to inhibit FAK in both preclinical and clinical cancer settings.
Keyphrases
- cell migration
- tyrosine kinase
- cell therapy
- growth factor
- signaling pathway
- small cell lung cancer
- squamous cell carcinoma
- poor prognosis
- papillary thyroid
- biofilm formation
- transcription factor
- single cell
- ejection fraction
- epidermal growth factor receptor
- newly diagnosed
- end stage renal disease
- chronic kidney disease
- escherichia coli
- stem cells
- pi k akt
- long non coding rna
- machine learning
- young adults
- deep learning
- staphylococcus aureus
- pain management
- pseudomonas aeruginosa
- candida albicans
- bone marrow
- patient reported outcomes
- lymph node metastasis
- data analysis
- study protocol
- artificial intelligence