m6A-related lncRNAs predict prognosis and indicate immune microenvironment in acute myeloid leukemia

Zhong, Fangchuan; Yao, Fangyi; Cheng, Ying; Liu, Jing; Zhang, Nan; Li, Shuqi; Li, Meiyong; Huang, Bo; Wang, Xiaozhong

doi:10.1038/s41598-022-05797-5

Cited by 18 publications

(12 citation statements)

References 78 publications

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“…For example, in hepatocellular carcinoma, tumor typing based on ferroptosis-related lncRNAs (FR-lncRNAs) provided better predictions of prognosis and efficacy of immunotherapy and targeted therapy ( 26 ). In head and neck squamous cell carcinoma (HNSC), the signatures of FR-lncRNAs could also predict patient outcomes ( 27 ), while in acute myeloid leukemia, m 6 A-related lncRNAs could predict the tumor microenvironment (TME) and survival ( 28 ). In addition, lncRNAs also participate in tumor progression by regulating cuprotosis genes.…”

Section: Introductionmentioning

confidence: 99%

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs

Zheng¹,

Zhou²,

Xie³

et al. 2022

J Thorac Dis

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Background: Previous research has shown the heterogeneity of lung adenocarcinoma (LUAD) accounts for the different effects and prognoses of the same treatment. Cuprotosis is a newly discovered form of programmed cell death involved in the development of tumors. Therefore, it is important to study the long non-coding RNAs (lncRNAs) that regulate cuprotosis to identify molecular subtypes and predict survival of LUAD. Methods: The expression profile, clinical, and mutation data of LUAD were downloaded from The Cancer Genome Atlas (TCGA), and the "ConsensusClusterPlus" package was used to cluster LUADs based on cuprotosis-related lncRNAs (CR-lncRNAs). The least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression were used to construct a prognostic model. CIBERSORT and singlesample gene set enrichment analysis (ssGSEA) were used for assessing immune cells infiltration and immune function. The tumor microenvironment (TME) score was calculated by ESTIMATE, and the tumor mutational burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) were used to evaluate the efficacy of immunotherapy.Results: Firstly, 501 CR-lncRNAs were identified based on the co-expression relationship of 19 cuprotosis genes. And univariate Cox further obtained 34 prognosis-related CR-lncRNAs. The unsupervised consensus clustering divided LUAD samples into cluster A and cluster B, and showed cluster A had better prognosis, more immune cells infiltration, stronger immune function, and a higher TME score. Subsequently, we used Lasso Cox regression to construct a prognostic model, and univariate and multivariate Cox analyses showed the risk score could be an independent prognostic indicator. Immune cells infiltration, immune function, and TME score were increased markedly in the low-risk group, while TMB and TIDE suggested the efficacy of immunotherapy might be increased in high-risk group.Conclusions: Our research identified two new molecular subtypes and constructed a novel prognostic model of LUAD which could provide new direction for its diagnosis, treatment, and prognosis.

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Section: Introductionmentioning

confidence: 99%

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs

Zheng¹,

Zhou²,

Xie³

et al. 2022

J Thorac Dis

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“…With the advancement of high-throughput sequencing methods and their widespread use in oncology, disclosing epigenomic irregularities during tumor onset and progression opens the door to the proof of identity of targeted therapies and predictive biomarkers in a range of tumors [ 23 ]. Current attention has been focused on the comprehensive detection of high sequencing results using publicly available databases, which has resulted in several major findings in the diagnosis and therapy of malignancies [ 17 , 24 ]. Conversely, the involvement of m6A regulators in lncRNA deregulation in human cancer is unknown.…”

Section: Discussionmentioning

confidence: 99%

m6A-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Osteosarcoma

Meng

Wei

et al. 2022

Computational Intelligence and Neuroscience

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Background. m6A-related lncRNAs have demonstrated great potential tumor diagnostic and therapeutic targets. The goal of this work was to find m6A-regulated lncRNAs in osteosarcoma patients. Method. The Cancer Genome Atlas (TCGA) database was used to retrieve RNA sequencing and medical information from osteosarcoma sufferers. The Pearson’s correlation test was used to identify the m6A-related lncRNAs. A risk model was built using univariate and multivariable Cox regression analysis. Kaplan–Meier survival analysis and receiver functional requirements were used to assess the risk model's performance (ROC). By using the CIBERSORT method, the associations between the relative risks and different immune cell infiltration were investigated. Lastly, the bioactivities of high-risk and low-risk subgroups were investigated using Gene Set Enrichment Analysis (GSEA). Result. A total of 531 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs have demonstrated prognostic values. A total of 88 OS patients were separated into cluster 1, cluster 2, and cluster 3. The overall survival rate of OS patients in cluster 3 was more favorable than that of those in cluster 1 and cluster 2. The average Stromal score was much higher in cluster 1 than in cluster 2 and cluster 3 ( P < 0.05 ). The expression levels of lncRNAs used in the construction of the risk prediction model in the high-risk group were generally lower than those in the low-risk group. Analysis of patient survival indicated that the survival of the low-risk group was higher than that of the high-risk group ( P < 0.0001 ) and the area under the curve (AUC) of the ROC curve was 0.719. Using the CIBERSORT algorithm, the results revealed that Macrophages M0, Macrophages M2, and T cells CD4 memory resting accounted for a large proportion of immune cell infiltration. By GSEA analysis, our results implied that the high-risk group was mainly involved in unfolded protein response, DNA repair signaling, and epithelial-mesenchymal transition signaling pathway and glycolysis pathway; meanwhile, the low-risk group was mainly involved in estrogen response early and KRAS signaling pathway. Conclusion. Our investigation showed that m6A-related lncRNAs remained tightly connected to the immunological microenvironment of osteosarcoma tumors, potentially influencing carcinogenesis and development. The immune microenvironment and immune-related biochemical pathways can be changed by regulating the transcription of M6A modulators or lncRNAs. In addition, we looked for risk-related signaling of m6A-related lncRNAs in osteosarcomas and built and validated the risk prediction system. The findings of our current analysis will facilitate the assessment of outcomes and the development of immunotherapies for sufferers of osteosarcomas.

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“…FM Zhong et al identified the risk signals related to prognosis of AML patients by using LASSO regression and then constructed a risk model for independent prediction of overall survival in AML patients based on 15 m 6 A-related lncRNAs, including AC025430.1, AFF2-IT1, LINC02593, AC000120.2, AL158163.1, AC048382.1, AL391834, AC008770.3, AL133492.1, AC020916.2 and AJ239328.1. This risk model showed great correlation with clinicopathological factors and immune infiltration levels, which could independently predict AML prognosis, indicating a novel insight in AML treatment [ 182 ].…”

Section: A Modified Lncrnas In Cancersmentioning

confidence: 99%

Novel insights into the multifaceted roles of m6A-modified LncRNAs in cancers: biological functions and therapeutic applications

Tang

Zhang

et al. 2023

Biomark Res

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N6-methyladenosine (m6A) is considered as the most common and important internal transcript modification in several diseases like type 2 diabetes, schizophrenia and especially cancer. As a main target of m6A methylation, long non-coding RNAs (lncRNAs) have been proved to regulate cellular processes at various levels, including epigenetic modification, transcriptional, post-transcriptional, translational and post-translational regulation. Recently, accumulating evidence suggests that m6A-modified lncRNAs greatly participate in the tumorigenesis of cancers. In this review, we systematically summarized the biogenesis of m6A-modified lncRNAs and the identified m6A-lncRNAs in a variety of cancers, as well as their potential diagnostic and therapeutic applications as biomarkers and therapeutic targets, hoping to shed light on the novel strategies for cancer treatment.

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m6A-related lncRNAs predict prognosis and indicate immune microenvironment in acute myeloid leukemia

Cited by 18 publications

References 78 publications

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs

m6A-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Osteosarcoma

Novel insights into the multifaceted roles of m6A-modified LncRNAs in cancers: biological functions and therapeutic applications

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