Identification of Differentially Expressed Gene Core Genes in Early T-Cell Precursor Acute Lymphoblastic Leukemia and Its Regulatory Network Analysis.
10.19746/j.cnki.issn.1009-2137.2019.03.007
- Author:
Yong-Zhi LUN
1
;
Jie SUN
2
;
Zeng-Guo YU
2
Author Information
1. Department of Laboratorial Medicine, School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China,E-mail: lunyz@163.com.
2. Department of Laboratorial Medicine, School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China.
- Publication Type:Journal Article
- MeSH:
Humans;
MicroRNAs;
Precursor Cells, T-Lymphoid;
Precursor T-Cell Lymphoblastic Leukemia-Lymphoma;
RNA, Long Noncoding;
RNA, Messenger
- From:
Journal of Experimental Hematology
2019;27(3):673-684
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To identify the differentially expressed gene (DEG) core genes in early T-cell precursor acute lymphoblastic leukemia (ETP ALL) and to analyze their interactions with upstream miRNAs, lncRNAs and involved pathways; to clarify the regulatory mechanism of ETP ALL development; and to explore the molecular targets for clinical diagnosis and treatment.
METHODS:The DEG of ETP ALL were screened based on the intersection of GEO database and TCGA database. The functional enrichment analysis and interaction analysis were carried out for DEG. Next, MCODE algorithm was used to screen core genes of DEG, and the mirDIP online tool and starBase online tool were utilized to predict upstream miRNA and lncRNA of the core genes.
RESULTS:A total of 424 DEG with a high credibility were identified, which were mainly enriched in the biological activity, such as transcriptional regulation, signaling pathway and protein function activation according to GO function, and the KEGG pathway was enriched in hematopoiesis, anoxic stress response, transcriptional misregulation, immunity and other functions, which interrelated each other 7 core genes were identified. Subsequently, 7 miRNAs and 19 lncRNAs were predicted to meet screening criteria. Finally, a lncRNA-miRNA-mRNA-pathway regulatory network was constructed.
CONCLUSION:The DEG in ETP ALL has been identified based on data mining methods; the core genes have been gained by co-expression analysis, and their upstream miRNA and lncRNA can be predicted for the early diagnosis of ETP ALL, thus providing a theoretical basis for the early diagnosis and reasonable treatment of ETP ALL, and helping to look for new tumor biomarkers of ETP ALL different from classical T-ALL.
