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Introduction: Conventional fractionation (CF) and hypofractionation (HF) are two radiotherapy methods against cancer, which are applied in medicine. Understanding the efficacy and molecular mechanism of the two methods implies more investigations. In the present study, proteomic findings about the mentioned methods relative to the controls were analyzed via network analysis. Methods: The significant differentially expressed proteins (DEPs) of prostate cancer (PCa) cell line DU145 in response to CF and HF radiation therapy versus controls were extracted from the literature. The protein-protein interaction (PPI) networks were constructed via the STRING database via Cytoscape software. The networks were analyzed by "NetworkAnalyzer" to determine hub DEPs. Results: 126 and 63 significant DEPs were identified for treated DU145 with CF and HF radiation respectively. The PPI networks were constructed by the queried DEPs plus 100 first neighbors. ALB, CD44, THBS1, EPCAM, F2, KRT19, and MCAM were highlighted as common hubs. VTM, OCLN, HSPB1, FLNA, AHSG, and SERPINC1 appeared as the discriminator hub between the studied cells. Conclusion: 70% of the hubs were common between CF and HF conditions, and they induced radio-resistance activity in the survived cells. Six central proteins which discriminate the function of the two groups of the irradiated cells were introduced. On the basis of these findings, it seems that DU145-CF cells, relative to the DU145-UF cells, are more radio-resistant. [ABSTRACT FROM AUTHOR]

Introduction: Radiation therapy (RT) as a common method for cancer treatment could result in some side effects. The molecular investigation is one of the approaches that could assist in decrypting the molecular mechanisms of this incident. For this aim, protein-protein interaction (PPI) network analysis as a complementary study of the proteome is conducted to explore the RT effect on brain cancer after the early stage of exposure prior to the appearance of the skin lesion. Methods: Cytoscape 3.7.2 and its plug-ins were used to analyze the network of differential expression of proteins (DEPs) in the treatment condition, and the centrality and pathway enrichment was conducted by the use of NetworkAnalyzer and ClueGO+CluePedia. Results: A network of 15 DEPs indicated that 6 nodes were key players in the network stability and SERPINC1 and F5 were from the query proteins. The pathways of post-translational protein phosphorylation, platelet degranulation, and complement and coagulation cascades were the most highlighted ones for the central nodes that could be affected in RT. Conclusion: The central proteins of the network of early-stage treatments could have additional importance in the mechanisms of radiotherapy response prior to skin lesions. Introduced biomarkers can be used for the patients' follow-up. These candidates are worth precise attention for this type of therapy after approving by validation studies. [ABSTRACT FROM AUTHOR]

Introduction: Obsessive-Compulsive Disorder (OCD) is a disabling mental condition that its proteomic profiling is not yet investigated. Proteomics is a valuable tool to discover biomarker approaches. It can be helpful to detect protein expression changes in complex disorders such as OCD. Methods: Here, by the application of 2D gel electrophoresis (2DE), a pilot study of serum proteome profile of females with washing subtype of OCD was performed. Serum samples were obtained from females with washing subtype of OCD. Following the protein extraction from the serum with acetone perception, the samples were subjected to 2DE for separation based on pI and molecular weight (MW) with triple replications. Finally, the protein spots were visualized using Coomassie blue staining method and analyzed by Progenesis SameSpots software. Furthermore, proteinprotein interaction (PPI) network analysis was handled by the application of Cytoscape software. Results: The results suggested that 41 matched spots demonstrated significant expression alterations among which 5 proteins including immunoglobulin heavy constant alpha-1 (IGHA1), apolipoprotein A-4 (APOA4), haptoglobin (HP), protein a-1-antitrypsin (SERPINA1), and component 3 (C3) were identified by database query. Additionally, PPI network analysis indicated the central role of SERPINA1 and C3 in the network integrity. However, albumin (ALB), amyloid precursor protein (APP), and protein a-1-antitrypsin (APOA1) proteins were important in OCD PPI network as well. The identified proteins were related to 3 processes: acute-phase response, hydrogen peroxide catabolic process, and regulation of triglyceride metabolic process. Conclusion: It was concluded that these proteins may have a fundamental role in OCD pathogenesis. Moreover, the dysregulation of inflammatory and antioxidant systems in OCD risk was suggested by the current study. However, evaluation of bigger sample sizes and application of mass spectrometry are essential requirements to confirm this preliminary evaluation. [ABSTRACT FROM AUTHOR]