Identification of key genes affecting disease free survival time of pediatric acute lymphoblastic leukemia based on bioinformatic analysis

The poor prognosis of pediatric acute lymphoblastic leukemia (ALL) indicates the existence of key candidate genes that affect pediatric ALL and its prognosis. The limma package in R was applied to screen differentially expressed genes (DEGs), and the Survival package and KMsurv package in R were use...

Full description

Saved in:
Bibliographic Details
Published in:Blood cells, molecules, & diseases molecules, & diseases, 2015-01, Vol.54 (1), p.38-43
Main Authors: Gao, Hai-Yan, Luo, Xin-Guo, Chen, Xi, Wang, Jing-Hua
Format: Article
Language:English
Subjects:
Adolescent
Child
Child, Preschool
Computational Biology
Differentially expressed genes
Disease free survival time
Disease-Free Survival
Female
Function enrichment
Gene Expression Regulation, Leukemic
Genes, Neoplasm
Humans
Infant
Male
Neoplasm Proteins - biosynthesis
Neoplasm Proteins - genetics
Pathway–pathway interactions
Pediatric acute lymphoblastic leukemia
Precursor Cell Lymphoblastic Leukemia-Lymphoma - genetics
Precursor Cell Lymphoblastic Leukemia-Lymphoma - metabolism
Precursor Cell Lymphoblastic Leukemia-Lymphoma - mortality
Survival Rate
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The poor prognosis of pediatric acute lymphoblastic leukemia (ALL) indicates the existence of key candidate genes that affect pediatric ALL and its prognosis. The limma package in R was applied to screen differentially expressed genes (DEGs), and the Survival package and KMsurv package in R were used to screen disease free survival time related genes (prognosis genes). Then, based on latent pathway identification analysis (LPIA), latent pathways were identified, and pathway–pathway interaction network was constructed and visualized by Cytoscape. Based on the expression values of 8284 genes in 126 chips, 2796 DEGs and 353 prognosis genes were screened out. After overlapping DEGs and prognosis genes, 75 key genes were identified, which were most significantly enriched in 25 GO functions and chronic myeloid leukemia pathway. For the 75 key genes, 27 disease risk sub-pathways were identified, and HK3, HNMT, SULT2B1, KYNU, and PTGS2 were the significant key genes which were enriched in these sub-pathways. Furthermore, based on pathway–pathway interaction analysis, HK3 and PTGS2 were predicted as the most important genes. Through glycolysis and arachidonic acid metabolism, HK3 and PTGS2 might play important roles in pediatric ALL and its prognosis, and thus, might be potential targets for therapeutic intervention to suppress pediatric ALL.
ISSN:1079-9796
1096-0961
DOI:10.1016/j.bcmd.2014.08.002