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. 2022 Aug 16:2022:7904293.
doi: 10.1155/2022/7904293. eCollection 2022.

Genomic and Clinical Analysis of Children with Acute Lymphoblastic Leukemia

Yu Liu  1 , Hailiqiguli Nuriding  1 , Li Zhao  1 , Xuemei Wang  1 , Yingbin Yue  1 , Yue Song  2 , Mei Yan  1
Affiliations

Genomic and Clinical Analysis of Children with Acute Lymphoblastic Leukemia

Yu Liu et al. Comput Math Methods Med. .

Retraction in

Abstract

Objective: This study investigated the types and significance of mutant genes in children with acute lymphoblastic leukemia (ALL).

Methods: The gene sequencing data of 89 ALL children were retrospectively analyzed. Log-rank test was used to analyze the effect of different numbers of mutant genes on the clinical characteristics of the patients and disease.

Results: Known gene mutations were detected in 64% (57/89) of the children, including one gene mutation in 31% and two or more gene mutations in 33% of the patients. Gene sequencing showed that most mutations occurred in KRAS (17%), NRAS (15%), FLT3 (7%), TP53 (7%), and PTPN11 (7%), and functional clustering analysis showed that most were signaling pathway genes (50%). In the overall cohort, no association was found between clinical characteristics and gene mutation. The children were then classified into three groups: group A (no gene mutation), group B (one gene mutation), and group C (two or more gene mutations). Correlation analysis showed that group A had significantly more children with medium risk ALL (P = 0.037), and group C had markedly more children with high risk ALL (P = 0.001). Further analysis showed that children with mutant genes took significantly more time to enter the maintenance phase than children without mutations.

Conclusion: Children with ALL had a high gene mutation rate, especially in KRAS and NRAS genes, and the mutant genes were mainly signal pathway-related. The gene mutations were significantly correlated with clinical phenotype and the time taken to enter the maintenance phase.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Illustration showing the percentage of patients (y-axis) with the indicated gene mutations (x-axis). The colored bars represent the mutation type of the indicated genes based on functional clustering analysis. The numbers above the bars represent the percentage of patients with that mutated gene.
Figure 2
Figure 2
Correlation analysis of mutant genes in children with acute lymphoblastic leukemia. (a) Distribution of the number of mutant genes in children with acute lymphoblastic leukemia; (b) correlation analysis of mutant genes in children with acute lymphoblastic leukemia showing significant comutations in SETD2 with PAX5, CREBBP with FLT3, NSD2 with PTPN11, WT1 with FLT3, and MYC with TP53 genes.
Figure 3
Figure 3
Effect of gene mutation on the survival rate of children with acute lymphoblastic leukemia.
See this image and copyright information in PMC

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