B. Arjmand, M. Rezaei-Tavirani, Maryam Hamzeloo-Moghadam3, Z. Razzaghi, M. Rezaei-Tavirani
{"title":"Molecular Analysis of Radiation Resistance Process in Radioresistant Oesophageal Adenocarcinoma Cells","authors":"B. Arjmand, M. Rezaei-Tavirani, Maryam Hamzeloo-Moghadam3, Z. Razzaghi, M. Rezaei-Tavirani","doi":"10.5812/ijcm-134017","DOIUrl":null,"url":null,"abstract":"Background: The radiation resistance process is a major problem in radiotherapy. Proteomics is a useful method to determine the molecular mechanism of biological and medical events. Protein-protein interaction (PPI) network is a suitable method for proteomics data interpretation. Objectives: Assessment of proteomics data about the radiation resistance process in human cell lines via PPI network analysis is the aim of this study. Methods: Proteomic data were extracted from literature and the differentially expressed proteins (DEPs) were included in the PPI network via the STRING database by Cytoscape software. The network was analyzed and the central nodes were introduced. The central nodes were assessed via action map analysis and gene ontology enrichment. Results: Among the 251 queried DEPs, 171 individuals were included in the PPI network. EGFR, FN1, CD44, PTGS2, NFKBIA, KEAP1, CTSD, PHGDH, and NT5E were introduced as the critical DEPs. Eight groups of biological terms were attributed to the introduced critical DEPs. EGFR, FN1, CD44, and PTGS2 were discriminated among the critical DEPs as the key dysregulated proteins. Conclusions: The results indicate that EGFR, FN1, CD44, and PTGS2 are the four essential proteins that are involved in radiation resistance in the radioresistant cells.","PeriodicalId":44764,"journal":{"name":"International Journal of Cancer Management","volume":"45 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cancer Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5812/ijcm-134017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The radiation resistance process is a major problem in radiotherapy. Proteomics is a useful method to determine the molecular mechanism of biological and medical events. Protein-protein interaction (PPI) network is a suitable method for proteomics data interpretation. Objectives: Assessment of proteomics data about the radiation resistance process in human cell lines via PPI network analysis is the aim of this study. Methods: Proteomic data were extracted from literature and the differentially expressed proteins (DEPs) were included in the PPI network via the STRING database by Cytoscape software. The network was analyzed and the central nodes were introduced. The central nodes were assessed via action map analysis and gene ontology enrichment. Results: Among the 251 queried DEPs, 171 individuals were included in the PPI network. EGFR, FN1, CD44, PTGS2, NFKBIA, KEAP1, CTSD, PHGDH, and NT5E were introduced as the critical DEPs. Eight groups of biological terms were attributed to the introduced critical DEPs. EGFR, FN1, CD44, and PTGS2 were discriminated among the critical DEPs as the key dysregulated proteins. Conclusions: The results indicate that EGFR, FN1, CD44, and PTGS2 are the four essential proteins that are involved in radiation resistance in the radioresistant cells.
期刊介绍:
International Journal of Cancer Management (IJCM) publishes peer-reviewed original studies and reviews on cancer etiology, epidemiology and risk factors, novel approach to cancer management including prevention, diagnosis, surgery, radiotherapy, medical oncology, and issues regarding cancer survivorship and palliative care. The scope spans the spectrum of cancer research from the laboratory to the clinic, with special emphasis on translational cancer research that bridge the laboratory and clinic. We also consider original case reports that expand clinical cancer knowledge and convey important best practice messages.