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Novel Prognostic Biomarkers Indicate Prognosis in Acute Myeloid Leukemia


A novel prognostic model based on N 6-methyladenosine-associated long non-coding RNAs demonstrated accuracy in determining high- and low-risk disease, suggesting the associated risk value may have potential as a novel biomarker.

While research in recent years has led to a better understanding of acute myeloid leukemia (AML), there remains a need to gain more insight on disease markers and improve the poor prognosis AML patients currently face. There is potential in N 6-methyladenosine-associated long non-coding RNAs (lncRNAs) as prognostic tools, as evidenced by a recent study published in Frontiers in Genetics.

Large-scale genomic research has helped characterize the genetic and molecular pathogenesis of AML, and targeted therapies have expanded the treatment landscape. However, AML still has a poor 5-year overall survival (OS) rate. Thus, there is a significant need for further research.

N 6-methyladenosine (m6A) RNA modification is thought to play a key role in AML, with certain subtypes of AML displaying upregulated m6A binding proteins, for example. More research is needed to clarify their role in the underlying mechanisms of AML, however. Several lncRNAs have been associated with AML growth, metastasis, and apoptotic cell death. The current study explored the potential of m6A-associated lncRNAs, which are suspected to have a role in AML but are not fully understood.

The study used data from The Cancer Genome Atlas and the Gene Expression Omnibus databases to establish an m6A-related lncRNA-based prognostic model. First, AML samples into were stratified into subgroups based on m6A-related lncRNA expression.

Biological function, tumor immune microenvironment, copy number variation (CNV), and drug sensitivity differences between these AML subgroups were examined, and the model was constructed with 9 prognosis-related m6A-related lncRNAs.

Kaplan-Meier analysis and time-dependent receiver operating characteristic curve analysis tested the model’s accuracy, and samples of AML were classified into either high- or low-risk cohorts based on the median value of each sample’s risk scores. Gene set enrichment analysis (GSEA) showed that samples in the high-risk group had abnormal immune-related biological processes and signaling pathways. Belonging to the high-risk group also correlated with higher ImmuneScore and StromalScore — meaning more immune and stromal components in the tumor microenvironment — as well as immune cell infiltration. A nomogram was depicted and showed that the model was reliably accurate as a prognostic tool.

Univariate and multivariate Cox regression analyses showed that m6A-related lncRNA risk scores, age, and belonging to the M5 subgroup of AML were each independent prognostic markers for OS. The high-risk group in this study also had higher IC50 values of chemotherapeutic and small-molecule drugs.

This study was the first to systematically screen and perform a comprehensive analysis of m6A-related lncRNAs in AML, and the novel prognostic model the authors developed showed accuracy. Therefore, they conclude the associated risk score has potential as a novel biomarker.

“For the first time, the research of m6A-related lncRNAs has been published to exert essential roles in the immune infiltration and CNV of AML. The present study offered a potentially theoretical basis for further research demonstrating the role of m6A-related lncRNAs in AML, which provided new guidance for the valid treatment guidelines for AML.”


Zhang L, Ke W, Hu P, et al. N6-Methyladenosine-related lncRNAs are novel prognostic markers and predict the immune landscape in acute myeloid leukemia. Front Genet. Published online May 9, 2022. doi:10.3389/fgene.2022.804614

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