ArticleCancer medicine2022
Immune-relatedlncRNAs can predict the prognosis of acute myeloid leukemia.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comprehensive lincRNA Transcriptome in Acute Myeloid Leukemia: Integrating Known and Newly Identified lincRNAs Across Pediatric and Adult Cohorts.Non-coding RNA · 2026Article
- Prime-time for LncRNA signatures in acute myeloid leukemia?Annals of hematology · 2025Review
- The HNRNPC/CELF2 signaling pathway drives glycolytic reprogramming and mitochondrial dysfunction in drug-resistant acute myeloid leukemia.Cell & bioscience · 2025Article
- Article
- Computational analysis of heat shock proteins and ferroptosis-associated lncRNAs to predict prognosis in acute myeloid leukemia patients.Frontiers in genetics · 2023Article
- Immune-relatedlncRNAs can predict the prognosis of acute myeloid leukemia.Cancer medicine · 2022Article
- A Novel Prognostic Model for Acute Myeloid Leukemia Based on Gene Set Variation Analysis.Journal of oncology · 2022Article
- The tip of the iceberg-The roles of long noncoding RNAs in acute myeloid leukemia.Wiley interdisciplinary reviews. RNAReview
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The immune microenvironment in acute myeloid leukemia (AML) is closely related to patients' prognosis. Long noncoding RNAs (lncRNAs) are emerging as key regulators in immune systems. In this study, we established a prognostic model using an immune-related lncRNA (IRL) signature to predict AML patients' overall survival (OS) through Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis. Kaplan-Meier analysis, receiver operating characteristic (ROC) analysis, univariate Cox regression, and multivariate Cox regression analyses further illustrated the reliability of our prognostic model. An IRL signature-based nomogram consisting of other clinical features efficiently predicted the OS of AML patients. The incorporation of the IRL signature improved the ELN2017 risk stratification system's prognostic accuracy. In addition, we found that monocytes and metabolism-related pathways may play a role in AML progression. Overall, the IRL signature appears as a novel effective model for evaluating the OS of AML patients and may be implemented to contribute to the prolonged OS in AML patients.
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