Identification of a Seven-lncRNA-mRNA Signature for Recurrence and Prognostic Prediction in Relapsed Acute Lymphoblastic Leukemia Based on WGCNA and LASSO Analyses

Abstract

Abnormal expressions of long noncoding RNAs (lncRNAs) and protein-encoding messenger RNAs (mRNAs) are important for the development of childhood acute lymphoblastic leukemia (ALL). This study developed an lncRNA-mRNA integrated classifier for the prediction of recurrence and prognosis in relapsed childhood ALL by using several transcriptome data. Weighted gene coexpression network analysis revealed that green, turquoise, yellow, and brown modules were preserved across the TARGET, GSE60926, GSE28460, and GSE17703 datasets, and they were associated with clinical relapse and death status. A total of 184 genes in these four modules were differentially expressed between recurrence and nonrecurrence samples. Least absolute shrinkage and selection operator analysis showed that seven genes constructed a prognostic signature (including one lncRNA: LINC00652 and six mRNAs: INSL3, NIPAL2, REN, RIMS2, RPRM, and SNAP91). Kaplan-Meier curve analysis observed that patients in the high-risk group had a significantly shorter overall survival than those of the low-risk group. Receiver operating characteristic curve analysis demonstrated that this signature had high accuracy in predicting the 5-year overall survival and recurrence outcomes, respectively. LINC00652 may function by coexpressing with the above prognostic genes (INSL3, SNAP91, and REN) and lipid metabolism-related genes (MIA2, APOA1). Accordingly, this lncRNA-mRNA-based classifier may be clinically useful to predict the recurrence and prognosis for childhood ALL. These genes represent new targets to explain the mechanisms for ALL.

Figure 1

The correlation between any two datasets (TARGET, GSE60926, GSE28460, and GSE17703) in the RNA expression levels (a) and connectivity (b).

Figure 2

Selection graphs of the soft-thresholding power β in the adjacency matrix (a) and schematic diagram of the mean connectivity of RNA under various power values (b).

Figure 3

Clustering dendrograms of gene modules screened from the datasets TARGET (a), GSE28460 (b), GSE17703 (c), and GSE60926 (d) and the association between functional modules of RNAs in the TARGET dataset and the clinical characteristics of acute lymphoblastic leukemia patients (e). In the module-trait heat map, each column corresponds to clinical parameters and each row corresponds to a module eigengene. The correlation coefficients are shown at the top of each row. The corresponding p values for each module are displayed at the bottom of each row within parentheses. WBC: white blood cell; MLL: mixed lineage leukemia.

Figure 4

Identification of differentially expressed module genes. (a) Heat map of differentially expressed RNAs; (b) Venn diagram to show the overlap between differentially expressed RNAs and module genes.

Figure 5

The prognostic performance of the risk score model established by the seven-lncRNA-mRNA signature genes. (a) Kaplan-Meier survival curve of the training dataset, TARGET; (b) Kaplan-Meier survival curve of validation dataset 1, E-MTAB-1216; (c) Kaplan-Meier survival curve of validation dataset 2, E-MTAB-1205; (d) ROC of the training dataset, TARGET; (e) ROC curve of validation dataset 1, E-MTAB-1216; (f) ROC curve of validation dataset 2, E-MTAB-1205. HR: hazard ratio; ROC: receiver operator characteristic curve; AUC: area under the ROC curve.

Figure 6

The predictive performance of the seven-lncRNA-mRNA signature for recurrence outcomes in different datasets: (a) ROC curve of TARGET; (b) receiver operator characteristic curve of GSE60926; (c) ROC of GSE28460; (d) ROC curve of GSE17703; (e) ROC curve of E-MTAB-1216; (f) ROC curve of E-MTAB-1205. ROC: receiver operating characteristic curve; AUC: area under the ROC curve.

Figure 7

A coexpression network between prognostic LINC00652 and its differentially expressed mRNAs. Triangle indicates the upregulated RNAs; inverted triangle indicates the downregulated RNAs; the color of nodes is corresponding to the module color (turquoise, green, yellow, and brown); the nodes with larger font are prognostic signature RNAs.