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Zhongguo Shi Yan Xue Ye Xue Za Zhi ; 29(4): 1101-1108, 2021 Aug.
Artigo em Chinês | MEDLINE | ID: mdl-34362488

RESUMO

OBJECTIVE: To screen the core genes of Philadelphia chromosome positive/Ph like T-cell acute lymphoblastic leukemia (Ph+/Ph like T-ALL) using bioinformatics methods, and analyze the core sub-networks for exploration of the development process of Ph+/Ph like T-ALL, so as to find the molecular targets that may be used in clinical diagnosis and treatment. METHODS: The WES/RNA-seq examination results of Ph+/Ph-like T-ALL children had be collected in our hospital, the genetic data that met the requirements had be downloaded from GEO database, then GRO2R online differentially expressed gene screening program was used to screen differentially expressed genes, finally, GO function enrichment analysis and KEGG pathway enrichment analysis were performed to compare differentially expressed genes. At the same time, STRING database and Cytoscape software were used to build protein interaction network and screen hub genes and core sub-networks. RESULTS: For Ph+/Ph like T-ALL, a total of 84 differentially expressed genes had been found, for Ph+ ALL a total of 249 differentially expressed genes, and for T-ALL a total of 175 differentially expressed genes. Based on the results of GO function enrichment, KEGG pathway enrichment analysis and protein interaction network, RPA1, POLD1, POLE and SOCS1 were selected as hub genes. DNA damage repair and JAK/STAT signal transduction pathway were the main functional sub-networks. CONCLUSION: There are obviously abnormal DNA damage repair pathways in children with Ph+/Ph like T-ALL. RPA1, POLD1 and POLE may be important relevant biomarkers for the occurrence and development of Ph+/Ph like T-ALL, which can provide a basis for further research.


Assuntos
Leucemia-Linfoma Linfoblástico de Células T Precursoras , Criança , Biologia Computacional , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Leucemia-Linfoma Linfoblástico de Células T Precursoras/genética , Transdução de Sinais , Software
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