Construction and validation of an NAD + metabolism-related lncRNA signature for predicting the prognosis and immune landscape of acute myeloid leukemia

Abstract

Background

This study aimed to investigate the potential of a NAD⁺ metabolism-related lncRNA signature as a reliable prognostic biomarker for acute myeloid leukemia (AML).

Methods

Transcriptome profiles and clinical data of AML patients were obtained from The Cancer Genome Atlas (TCGA) database. NAD+ metabolism-related genes (NMRGs) were identified from the KEGG and Reactome databases. Coexpression analysis was used to screen NAD⁺ metabolism-related lncRNAs. The NAD⁺ metabolismrelated lncRNA signature was constructed using univariate analysis, LASSO regression, and multivariate analysis. High- and low-risk groups were compared for survival, tumor mutation burden, immune cell infiltration, and response to immunotherapy. Enrichment analysis explored the biological functions.

Results

LINC01679, AC079922.2, TRAF3IP2-AS1, and LINC02465 were identified to construct the risk model. The model exhibited good predictive power and outperformed age and gender as an independent prognostic marker. High-risk patients showed poorer survival, distinct TP53 mutations, and altered immune cell infiltration compared to low-risk patients. Additionally, low-risk patients exhibited greater sensitivity to immunotherapy. Enriched biological functions included leukocyte migration and positive regulation of cytokine production.

Conclusions

The NAD⁺ metabolism-related lncRNA signature shows promise in predicting clinical outcomes for AML patients.

KEYWORDS:

• Acute myeloid leukemia₁
• NAD⁺ metabolism₂
• prognostic signature₃
• immune landscape₄
• lncRNA₅

Acknowledgments

Thanks to the support of the Department of Hematology, the First Affiliated Hospital of Lanzhou University.

Author contributions

(I) Conception and design: YZ, JJ and YN. (II) Download and collection of data: YZ, XY, and JJ. (III) Data analysis and interpretation: YZ, YG, and LZ. (IV) Production of table and figure: YZ, JJ and YN. (V) Manuscript writing: All authors. (VI) Final approval of manuscript: All authors.

Data availability statement

All data related to this manuscript can be downloaded online for free from the TCGA database in the GDC Data Portal (https://portal.gdc.cancer.gov/) and UCSC Xena (https://xenabrowser.net/datapages/).

Disclosure statement

No potential conflict of interest was reported by the author(s).