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- W2914601885 abstract "Introduction: One of the major challenges in cancer treatment is the lack of specific and accurate treatment incancer. Data analysis can help to understand the underlying molecular mechanism that leads to better treatment.Increasing availability and reliability of DNA microarray data leads to increase the use of these data in a variety ofcancers. This study aimed at applying and evaluating microarray data analyzing, identification of important pathwaysand gene network for medulloblastoma patients to improve treatment approaches especially target therapy. Methods:In the current study, Microarray gene expression data (GSE50161) were extracted from Geo datasets and then analyzedby the affylmGUI package to predict and investigate upregulated and downregulated genes in medulloblastoma. Then,the important pathways were determined by using software and gene enrichment analyses. Pathways visualizationand network analyses were performed by Cytoscape. Results: A total number of 249 differentially expressed genes(DEGs) were identified in medulloblastoma compared to normal samples. Cell cycle, p53, and FoxO signaling pathwayswere indicated in medulloblastoma, and CDK1, CCNB1, CDK2, and WEE1 were identified as some of the importantgenes in the medulloblastoma. Conclusion: Identification of critical and specific pathway in any disease, in our casemedulloblastoma, can lead us to better clinical management and accurate treatment and target therapy." @default.
- W2914601885 created "2019-02-21" @default.
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- W2914601885 date "2019-01-01" @default.
- W2914601885 modified "2023-10-14" @default.
- W2914601885 title "Bioinformatics Analysis of Key Genes and Pathways for Medulloblastoma as a Therapeutic Target" @default.
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- W2914601885 doi "https://doi.org/10.31557/apjcp.2019.20.1.221" @default.
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