Construction of a 14-lncRNA risk score system predicting survival of children with acute myelocytic leukemia

Abstract

Acute myelocytic leukemia (AML) is a frequent type of acute leukemia. The present study was performed to build a risk score system for the prognostic prediction of AML. AML RNA-sequencing data from samples from 111 children were downloaded from The Cancer Genome Atlas database. Using the DEseq and edgeR packages, the differentially expressed long non-coding RNAs (DE-lncRNAs) between bad and good prognosis groups were identified. A survival package was used to screen prognosis-associated lncRNAs and clinical factors. The optimal lncRNA combination was selected using the penalized package, and the risk-score system was built and evaluated. After the lncRNA-mRNA expression correlation network was constructed, the potential pathways involving the key lncRNAs were enriched using Gene Set Enrichment Analysis. Among the 61 DE-lncRNAs, 48 lncRNAs were significantly associated with prognosis. Relapse was an independent prognostic factor. The optimal 14-lncRNA risk score system was constructed. After 730 differentially expressed mRNAs were identified between the good and bad prognosis groups divided using a prognostic index, the lncRNA-mRNA expression correlation network was constructed. Enrichment analysis showed that semaphorin-3C [SEMA3C; regulated by probable leucine-tRNA ligase, mitochondrial (LARS2-AS1)] and secreted frizzled-related protein 5 [SFRP5; mediated by WASH complex subunit 5 (WASHC5)-antisense RNA 1 (AS1)] were involved in axon guidance and the Wnt signaling pathway, respectively. A 14-lncRNA (including paired box protein Pax8-AS1 and MYB AS1) risk-score system might be effective in predicting the prognosis of AML. Axon guidance (involving SEMA3C and LARS2-AS1) and the Wnt signaling pathway (involving SFRP5 and WASHC5-AS1) might be two important pathways affecting the prognosis of AML.

Keywords: acute myelocytic leukemia; enrichment analysis; expression correlation network; long non-coding RNA; risk score system; survival analysis.

Figure 1

Differential expression analysis between good and bad prognosis groups. (A) Dysregulated lncRNAs identified separately by the DEseq package (top) and edgeR package (bottom). Red and green represent upregulated and downregulated lncRNAs in the good prognosis group, respectively. (B) Venn diagram for comparing the results of the two screening methods. (C) Clustering heatmap of the 61 intersected lncRNAs. Red and green indicate bad and good prognosis groups, respectively. FDR, false discovery rate; FC, fold change; lncRNA, long non-coding RNA.

Figure 2

Kaplan-Meier curves and the selection of the optimal combination. (A) Kaplan-Meier curves for relapse in the training set (left), the validation set (middle), and the entire set (right). (B) Curve for selecting the optimal parameter ‘λ’ using cvl (the junction of the red dashed lines indicates the value of lambda is 24.34156 when the maximum value-108.177 is obtained for cvl). (C) Coefficient distribution diagram of the 14 optimal lncRNAs. cvl, cross-validation likelihood; lncRNA, long non-coding RNA.

Figure 3

KM curves and AUROC curves. (A) KM curves showing the OS (left) and RFS (middle), and the AUROC curve (right) for the training set. (B) KM curves showing the OS (left) and RFS (middle) and the AUROC curve (right) for the validation set. (C) KM curves showing the OS (left) and RFS (middle) and the AUROC curve (right) for the entire set. KM, Kaplan-Meier; AUROC, area under the received operating characteristic; AUC, area under curve; OS, overall survival; RFS, relapse-free survival.

Figure 4

Expression levels of the 14 optimal lncRNAs. (A) Expression levels of the 14 optimal lncRNAs in the training set. (B) Expression levels of the 14 optimal lncRNAs in the validation set. (C) Expression levels of the 14 optimal lncRNAs in the entire set. Green and red represent good and bad prognosis groups, respectively. ^*P<0.05; ^**P<0.01 and ^***P<0.005 vs. respective good prognostic group. lncRNA, long non-coding RNA.

Figure 5

PIs, OS and expression heatmap of the 14 optimal lncRNAs. (A) PIs (top), OS (middle) and expression heatmap (bottom) of the 14 optimal lncRNAs in the training set. (B) PIs (top), OS (middle) and expression heatmap (bottom) of the 14 optimal lncRNAs in the validation set. (C) PIs (top), OS (middle) and expression heatmap (bottom) of the 14 optimal lncRNAs in the entire set. PI, prognostic index; OS, overall survival; lncRNA, long non-coding RNA.

Figure 6

Clustering heatmap for the top 100 differentially expressed mRNAs with higher absolute value of Pearson correlation coefficient.

Figure 7

lncRNA-mRNA expression correlation network. Circles and squares represent mRNAs and lncRNAs, respectively. The colors ranging from light to dark indicate the increased degree of upregulation in the good prognosis group. lncRNA, long non-coding RNA; FC, fold change.