Immune‐relatedlncRNAs can predict the prognosis of acute myeloid leukemia

Li, Ran; Wu, Shishuang; Wu, Xiaolu; Zhao, Ping; Li, Jingyi; Xue, Kai

doi:10.1002/cam4.4487

Cited by 5 publications

(4 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Subsequent stratification analysis demonstrated that IRL‐score could be applied to different clinicopathological subgroups and maintained its predictive power, with the exception of senior patients >65 years old. Finally, IRL‐score was able to predict prognosis independently of blast count and ELN risk stratification system, further demonstrating the prognostic potential of lncRNA signature in AML (R. Li et al, 2022 ). Comparably, Liu et al recently identified a prognostic 7‐lncRNA signature for AML which consisted of lncRNAs identified as highly expressed in AML in the TARGET dataset.…”

Section: Lncrna Function In Cancer and Amlmentioning

confidence: 81%

The tip of the iceberg—The roles of long noncoding RNAs in acute myeloid leukemia

Connerty

Lock

2023

WIREs RNA

View full text Add to dashboard Cite

Long noncoding RNAs (lncRNAs) are traditionally defined as RNA transcripts longer than 200 nucleotides that have no protein coding potential. LncRNAs have been identified to be dysregulated in various types of cancer, including the deadly hematopoietic cancer—acute myeloid leukemia (AML). Currently, survival rates for AML have reached a plateau necessitating new therapeutic targets and biomarkers to improve treatment options and survival from the disease. Therefore, the identification of lncRNAs as novel biomarkers and therapeutic targets for AML has major benefits. In this review, we assess the key studies which have recently identified lncRNAs as important molecules in AML and summarize the current knowledge of lncRNAs in AML. We delve into examples of the specific roles of lncRNA action in AML such as driving proliferation, differentiation block and therapy resistance as well as their function as tumor suppressors and utility as biomarkers.This article is categorized under: RNA in Disease and Development > RNA in Disease

show abstract

Section: Lncrna Function In Cancer and Amlmentioning

confidence: 81%

The tip of the iceberg—The roles of long noncoding RNAs in acute myeloid leukemia

Connerty

Lock

2023

WIREs RNA

View full text Add to dashboard Cite

show abstract

“…This means that incorporating lncRNA into preclinical models is essential for the discovery of prognostic biomarkers. Indeed, growing evidence has revealed that lncRNAs are intimately implicated in tumorigenesis, progression, prognosis, and drug resistance/sensitivity [ 15 ], and they are emerging as key regulators in the immune system, especially in inflammatory immune responses and immune-related pathways [ 16 ]. Although research on lncRNAs in AML is still in its infancy, evidence of their involvement as essential mediators and effectors of epigenetic changes has spurred epigenetics research [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

“…LncRNAs in the immune microenvironment are one of the most extensively studied kinds, regulating gene expression at the epigenetic, transcriptional, and post-transcriptional stages [ 15 ]. In AML, lncRNAs regulate the inflammatory immune response, B-cell activation, and vaccination response-related immunological pathways [ 16 ]. However, there is insufficient evidence for immune-related lncRNAs to predict AML prognosis and therapy, and their roles in the AML immune microenvironment has not received sufficient attention and warrant additional study.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers

Zhang,

et al. 2024

Heliyon

View full text Add to dashboard Cite

“…Previous studies on prognosis assessment in AML have mainly focused on a single gene or a group of genes related to specifc biological processes [4][5][6], instead of comprehensively integrating multiple pathways in AML expression gene sets. For example, autophagy-related signatures [7], ferroptosis-related genes [8], and immune-related signatures [9] were reported to be related to the prognosis of AML, respectively. Here, we applied gene set variation analysis (GSVA) to detect subtle changes in the pathway within an entire gene expression set [10], and then the patients were classifed according to the enrichment score (ES) of gene sets in an unsupervised manner.…”

Section: Introductionmentioning

confidence: 99%

A Novel Prognostic Model for Acute Myeloid Leukemia Based on Gene Set Variation Analysis

Zhang

Wang

Xia

et al. 2022

Journal of Oncology

View full text Add to dashboard Cite

Acute myeloid leukemia (AML) is a malignant hematological malignancy with a poor prognosis. Risk stratification of patients with AML is mainly based on the characteristics of cytogenetics and molecular genetics; however, patients with favorable genetics may have a poor prognosis. Here, we focused on the activity changes of immunologic and hallmark gene sets in the AML population. Based on the enrichment score of gene sets by gene set variation analysis (GSVA), we identified three AML subtypes by the nonnegative matrix factorization (NMF) algorithm in the TCGA cohort. AML patients in subgroup 1 had worse overall survival (OS) than subgroups 2 and 3 ( P < 0.001 ). The median overall survival (mOS) of subgroups 1–3 was 0.4, 2.2, and 1.7 years, respectively. Clinical characteristics, including age and FAB classification, were significantly different among each subgroup. Using the least absolute shrinkage and selection operator (LASSO) regression method, we discovered three prognostic gene sets and established the final prognostic model based on them. Patients in the high-risk group had significantly shorter OS than those in the low-risk group in the TCGA cohort ( P < 0.001 ) with mOS of 2.2 and 0.7 years in the low- and high-risk groups, respectively. The results were further validated in the GSE146173 and GSE12417 cohorts. We further identified the key genes of prognostic gene sets using a protein-protein interaction network. In conclusion, the study established and validated a novel prognostic model for risk stratification in AML, which provides a new perspective for accurate prognosis assessment.

show abstract

Immune‐relatedlncRNAs can predict the prognosis of acute myeloid leukemia

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 5 publications

References 46 publications

The tip of the iceberg—The roles of long noncoding RNAs in acute myeloid leukemia

The tip of the iceberg—The roles of long noncoding RNAs in acute myeloid leukemia

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers

A Novel Prognostic Model for Acute Myeloid Leukemia Based on Gene Set Variation Analysis

Contact Info

Product

Resources

About