Predicting Radioresistant Biomarkers in Nasopharyngeal Carcinoma Patients Via Protein-Protein Interaction Network Analysis.
Mostafa Rezaei TaviraniFarshad OkhovatianMohammad Rostami-NejadBabak ArjmandZahra RazzaghiPublished in: Journal of lasers in medical sciences (2021)
Introduction: Radiotherapy as the first-line nasopharyngeal carcinoma (NPC) treatment provides different responses including radioresistant and radiosensitive states. In order to investigate the molecular basis of radioresistancy, protein-protein interaction network analysis of proteome data prior to therapy was performed. Methods: 20 dysregulated proteins of the patients who were radioresistant were extracted from the literature. Cytoscape and its plug-ins were used for the resistant network construction and its centrality analysis. Furthermore, ClueGO+ CluePedia application determined the most statistically significant biological processes (BP) related to the hubs. Results: Fourteen hubs were concluded and no differentially expressed protein (DEP) was among these agents. Among the hubs, albumin (ALB) and fibronectin (FN1) were the hub-bottlenecks, and the Serpin family was present. What is more, SERPIND1 was the highest degree-valued DEP in the network. Conclusion: It can be concluded that the central elements of the NPC network could be noteworthy for improving the radiotherapy outcome and overcoming its limitations. However, complementary studies are required for a better understanding of their major role.
Keyphrases
- protein protein
- network analysis
- small molecule
- early stage
- end stage renal disease
- radiation therapy
- chronic kidney disease
- ejection fraction
- systematic review
- stem cells
- electronic health record
- squamous cell carcinoma
- big data
- prognostic factors
- peritoneal dialysis
- patient reported outcomes
- artificial intelligence
- binding protein
- replacement therapy