To identify biomarkers that can predict the recurrence of the central nervous system (CNS) in children with acute lymphoblastic leukemia (ALL).
The transcriptome and clinical data of ALL in children were downloaded from the TARGET database. Transcriptome data were analyzed by bioinformatics method to identify core (hub) genes and establish a risk assessment model. Univariate Cox analysis was performed on each clinical data, and multivariate Cox regression analysis was performed on the obtained results and risk score. The children ALL phase I samples from TARGET database were used for validation.
Univariate multivariate Cox analysis of 10 hub genes identified showed that (HR = 0.78, 95%CI = 0.67-0.91,  = 0.007), (HR = 1.15, 95%CI = 1.05-1.26,  = 0.003) and (HR = 1.25, 95%CI = 1.04-1.51,  = 0.017) had statistical differences. The risk score was statistically significant in univariate (HR = 3.06, 95%CI = 1.30-7.19,  = 0.011) and multivariate (HR = 1.81, 95%CI = 1.16-2.32,  = 0.046) Cox regression analysis. The survival analysis results of the high and low-risk groups were different when the validation dataset was substituted into the model ( = 0.018). Then, we constructed a Nomogram which had a concordance index of survival prediction of 0.791(95%CI= 0.779-0.803). In addition, the CNS involvement grading status at first diagnosis CNS3 vs. CNS1 (HR = 5.74, 95%CI = 2.01-16.4,  = 0.001), T cell vs B cell (HR = 1.63, 95% CI = 1.06-2.49,  = 0.026) were also statistically significant.
, , and may be predictors of CNS relapse in childhood ALL.