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Published on: March 31, 2015
[A comprehensive analysis of potential prognostic biomarkers for MYCN-amplified neuroblastoma]
Xu Fan1, Hong-Ting Lu, Lin Hou
1Department of Pediatric Surgery, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, China. luhongting@126.com.
Objective:
To study the differentially expressed mRNAs between MYCN-amplified neuroblastoma (NB) and non-amplified NB, to screen out the genes which can be used to predict the prognosis of MYCN-amplified NB, and to analyze their value in predicting prognosis.
Methods:
NB transcriptome data and the clinical data of children were obtained from the TARGET database. According to the presence or absence of MYCN amplification, the children were divided into two groups: MYCN amplification (n=33) and non-MYCN amplification (n=121). The expression of mRNAs was compared between the two groups to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analysis was performed to investigate the main functions of DEGs. The Cox proportional-hazards regression model analysis was used to investigate the genes influencing the prognosis of MYCN-amplified NB. The children were divided into a high-risk group (n=77) and a low-risk group (n=77) based on the median of risk score. A survival analysis was used to compare survival rate between the two groups. The receiver operating characteristic (ROC) curve was used to investigate the value of risk score in predicting the prognosis of children with MYCN-amplified NB.
Results:
A total of 582 DEGs were screened out, and they were involved in important biological functions such as ribosome composition, expression of cell adhesion molecules, and activity of membrane receptor protein. The multivariate Cox regression model analysis showed that FLVCR2, SCN7A, PRSS12, NTRK1, and XAGE1A genes had a marked influence on the prognosis of the children with NB in the MYCN amplification group (P<0.05). The survival analysis showed that the high-risk group had a significantly lower overall survival rate than the low-risk group (P<0.05). The ROC curve analysis showed that risk score had a certain value in predicting the prognosis of the children with NB in the MYCN amplification group (P<0.05), with an area under the ROC curve of 0.729, an optimal cut-off value of 1.316, a sensitivity of 53.2%, and a specificity of 84.4%.
Conclusions:
The mRNA expression of FLVCR2, SCN7A, PRSS12, NTRK1, and XAGE1A genes can be used as biomarkers to predict the prognosis of MYCN-amplified NB, which can help to refine clinical risk stratification.
