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. 2022 Nov 3:10:1036312.
doi: 10.3389/fcell.2022.1036312. eCollection 2022.

Novel gene signature reveals prognostic model in acute lymphoblastic leukemia

Panpan Chen  1 , Guanfei Gao  1 , Yuanlin Xu  1 , Peijun Jia  1 , Yan Li  1 , Yating Li  1 , Jiaming Cao  1 , Jiangfeng Du  1 , Shijie Zhang  1 , Jingxin Zhang  1
Affiliations

Novel gene signature reveals prognostic model in acute lymphoblastic leukemia

Panpan Chen et al. Front Cell Dev Biol. .

Abstract

Acute lymphoblastic leukemia (ALL) is a type of hematological malignancy and has a poor prognosis. In our study, we aimed to construct a prognostic model of ALL by identifying important genes closely related to ALL prognosis. We obtained transcriptome data (RNA-seq) of ALL samples from the GDC TARGET database and identified differentially expressed genes (DEGs) using the "DESeq" package of R software. We used univariate and multivariate cox regression analyses to screen out the prognostic genes of ALL. In our results, the risk score can be used as an independent prognostic factor to predict the prognosis of ALL patients [hazard ratio (HR) = 2.782, 95% CI = 1.903-4.068, p < 0.001]. Risk score in clinical parameters has high diagnostic sensitivity and specificity for predicting overall survival of ALL patients, and the area under curve (AUC) is 0.864 in the receiver operating characteristic (ROC) analysis results. Our study evaluated a potential prognostic signature with six genes and constructed a risk model significantly related to the prognosis of ALL patients. The results of this study can help clinicians to adjust the treatment plan and distinguish patients with good and poor prognosis for targeted treatment.

Keywords: acute lymphoblastic leukemia; bioinformatics analysis; database; prognostic value; risk model.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The workflow of the model construction process.
FIGURE 2
FIGURE 2
Identification of differentially expressed genes. (A) Heat map of differentially expressed gene expression levels in the GDC TARGET-ALL dataset. (B) Volcano plot for differentially expressed gene expression levels in GDC TARGET-ALL dataset.
FIGURE 3
FIGURE 3
Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. (A) The GO analysis of 461 up-regulated genes. (B) The GO analysis of 551 down-regulated genes. (C) KEGG analysis of 461 up-regulated genes. (D) KEGG analysis of 551 down-regulated genes.
FIGURE 4
FIGURE 4
Survival analysis of ALL prognostic genes. (A) BAALC. (B) HGF. (C) CPXM1. (D) CCL4. (E) ZBTB10. (F) B3GNT2.
FIGURE 5
FIGURE 5
Regression analysis and characteristics of prognostic gene signatures. (A) Forest map of six prognostic genes by univariate cox regression. (B) Distributions of risk scores in all samples. (C) Distribution of follow-up times in the training samples. (D) Heat map of gene expression in the prognostic signature of ALL.
FIGURE 6
FIGURE 6
Cox proportional hazard regression analysis of ALL risk factors. (A) Univariate cox regression analysis of risk score and other indicators. (B) Multivariate cox regression analysis of risk score and other indicators. (C) Kaplan-Meier analysis of ALL patients grouped according to median risk. (D) Multi-index receiver operating characteristic (ROC) curve of risk score and other indicators.
FIGURE 7
FIGURE 7
Gene set enrichment analysis (GSEA) of the prognostic signature. GSEA shows the GO (A) and KEGG pathways (B) enriched in the high-risk group of the ALL gene signatures. GSEA reveals the GO (C) and KEGG pathways (D) enriched in the low-risk group of the ALL gene signatures.
FIGURE 8
FIGURE 8
External verification of the prognostic ALL gene signature. (A) Risk scores distribution. (B) Survival status of patients. (C) Heat map of gene expression pattern. (D) Kaplan-Meier plot for overall survival (OS) of patients in different risk groups. (E) ROC curve of risk score.
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