Identification of the Integrated Prognostic Signature Associated with Immuno-relevant Genes and Long Non-coding RNAs in Acute Myeloid Leukemia

Abstract

Background

Like other cancers, considerable effort has been made in acute myeloid leukemia (AML) to identify prognostic genes and long noncoding RNAs (lncRNAs) with their potential clinical applications. However, to date, no integrated prognostic model has been developed that combines both gene expression and lncRNAs as a singular approach in AML.

Method

Comprehensive bioinformatic approaches (Weighted gene co-expression network analysis, Univariate Cox regression analyses, Pearson correlation, LASSO-Cox regression, Wilcoxon test) were used to construct the signature and to define high- and low-risk groups in AML datasets. ESTIMATE and CIBERSORT algorithms were applied to investigate the potential impact of infiltrating immune cells based on the obtained signature in tumor microenvironment. In addition, gene ontology (GO) and KEGG enrichment were applied to explore the potential function of the signature.

Results

Herein, we focused on immune-related genes (IRGs) and immune-related long noncoding RNAs (IRlncRNAs) and constructed an integrated prognostic immunorelevant signature in AML. The obtained signature exhibit five IRGs (DAXX, PSMB8, CSRP1, RAC2 and PTPN6) and one IRlncRNA (AC080037.2) and is strictly associated with age and FAB (French–American–British classification). Importantly, the high-risk AML group (defined by the signature) correlated positively with three types of scores (immune score, stroma score, and ESTIMATE score). We also identified a few immune cells (resting mast cells and monocytes) potentially involved in the correlation between signature and survival of AML patients. The prognostic ability of the obtained signature was tested in the training cohort and then validated in both test and total cohorts. The pathway enrichment analysis confirmed the possible immune- related role of the signature.

Conclusion

We constructed an integrated prognostic signature comprising five immune-related protein-coding genes (IRPCG) (DAXX, PSMB8, CSRP1, RAC2, and PTPN6) and one immune-related lncRNA (AC080037.2) that may serve as potential biomarkers for predicting survival and further stratifying AML patients.

Keywords:

• Acute myeloid leukemia
• lncRNAs
• tumor microenvironment
• prognosis
• signature
• The Cancer Genome Atlas Program (TCGA)

Author contributions

Conceptualization, C.Z., Y.W., and F.T.; statistical analysis, Y.W and C.Z; formal analysis, Y.W, C.Z and A.S; writing—original draft preparation, Y.W, A.S. and C.Z.; writing—review and editing, all co-authors; supervision, C.Z., Z.W., Y.W., Y.W., P.L., J.L., X.Z., I.G.H.S-W; project administration, F.T. All authors have read and agreed to the published version of the manuscript.

Declaration of Interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Data availability statement

The data set in this study can be found in the https://xenabrowser.net/datapages/. The TCGA-LAML dataset is GDC TCGA Acute Myeloid Leukemia (LAML) (15 datasets).

Additional information

Funding

This research received no external funding.