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ABSTRACT
Objective
To identify biomarkers that can predict the recurrence of the central nervous system (CNS) in children with acute lymphoblastic leukemia (ALL).
Materials and Methods
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.
Results
Univariate multivariate Cox analysis of 10 hub genes identified showed that PPARG (HR = 0.78, 95%CI = 0.67–0.91, p = 0.007), CD19 (HR = 1.15, 95%CI = 1.05–1.26, p = 0.003) and GNG12 (HR = 1.25, 95%CI = 1.04–1.51, p = 0.017) had statistical differences. The risk score was statistically significant in univariate (HR = 3.06, 95%CI = 1.30–7.19, p = 0.011) and multivariate (HR = 1.81, 95%CI = 1.16–2.32, p = 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 (p = 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, p = 0.001), T cell vs B cell (HR = 1.63, 95% CI = 1.06-2.49, p = 0.026) were also statistically significant.
Conclusions
PPARG, GNG12, and CD19 may be predictors of CNS relapse in childhood ALL.
Acknowledgments
We acknowledge the TARGET database for providing their platforms and contributors for uploading their meaningful datasets.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement and ethical approval
The results published here are in whole based upon data generated by the Therapeutically Applicable Research to Generate Effective Treatments (https://ocg.cancer.gov/programs/target) initiative, phs000218. The patients involved in the database have obtained ethical approval. Users can download relevant data for free for research and publish relevant articles, so there are no ethical issues and other conflicts of interest. The data used for this analysis are available at https://portal.gdc.cancer.gov/projects.