scholarly journals Association Analyses of TP53 Mutation With Prognosis, Tumor Mutational Burden, and Immunological Features in Acute Myeloid Leukemia

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiang-mei Wen ◽  
Zi-jun Xu ◽  
Ye Jin ◽  
Pei-hui Xia ◽  
Ji-chun Ma ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Enrichment Analysis ◽  
Predictive Biomarker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Association Analyses ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is a heterogeneous disease related to a broad spectrum of molecular alterations. The successes of immunotherapies treating solid tumors and a deeper understanding of the immune systems of patients with hematologic malignancies have promoted the development of immunotherapies for the treatment of AML. And high tumor mutational burden (TMB) is an emerging predictive biomarker for response to immunotherapy. However, the association of gene mutation in AML with TMB and immunological features still has not been clearly elucidated. In our study, based on The Cancer Genome Atlas (TCGA) and BeatAML cohorts, 20 frequently mutated genes were found to be covered by both datasets in AML. And TP53 mutation was associated with a poor prognosis, and its mutation displayed exclusiveness with other common mutated genes in both datasets. Moreover, TP53 mutation correlated with TMB and the immune microenvironment. Gene Set Enrichment Analysis (GSEA) showed that TP53 mutation upregulated signaling pathways involved in the immune system. In summary, TP53 mutation is frequently mutated in AML, and its mutation is associated with dismal outcome, TMB, and immunological features, which may serve as a biomarker to predict immune response in AML.

Identification of Aberrantly Methylated and Silenced Genes in Acute Myeloid Leukemia by Combined Methylation/expression Analysis

2020 ◽  
Author(s):  
Chao Guo ◽  
Qian-qian Ju ◽  
Chun-xia Zhang ◽  
Ming Gong ◽  
Ya-yue Gao ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Subgroup Analysis ◽  
Myeloid Leukemia ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Aberrant Methylation ◽  
Acute Myeloid

Abstract Background Aberrant genomic methylation plays an important role in pathogenic process of acute myeloid leukemia (AML) by silencing tumor suppressor genes (TSG). While the key aberrantly methylated genes and related pathways have not been well understood yet, which we aimed to reveal by combined analysis of methylation and expression datasets. The prognostic significance was validated by survival analysis derived from TCGA database. Methods Micro-array data of GSE 15061 and GSE58477 were downloaded from Gene Expression Omnibus (GEO) database. The differentially methylated regions (DMR) and differentially expressed genes (DEG) were identified using R program (R 3.6.1). Over-representation analysis was performed to obtain the enriched biological processes and pathways. Cox hazards analysis was employed to select the genes significantly associated with AML survival, using the data derived from the Cancer Genome Atlas (TCGA) database. Subgroup analysis, regarding induction type, was conducted to identify biomarkers for HMA treatment. Furthermore, SYNJ2 associated genome-wide gene/miRNA expression and methylation profile were explored. Results A total of 198 aberrant methylation related underexpressed genes were identified. Univariable analysis revealed methylation level of 6 out of 198 genes (CORO1A/MPO/SYNJ2/EHD1/GAS2L1/SLC11A1) were significantly associated with AML survival. SYNJ2 methylation was an independent predictor for OS. Notably, subgroup analysis revealed hypermethylation of CORO1A predicted better OS in HMA group. Further gene set enrichment analysis indicated SYNJ2-associated activation of PI3K-Akt/NF-kappaB/JAK-STAT signaling and checkpoint pathway. The microRNAs, such as miR217/miR485-3p/miR-889-3p, were downregulated in SYNJ2-hypermethylated group, leading to potential HOXA13 upregulation. Conclusion The prognostic methylation signature was revealed in our studies, and SYNJ2 was proved as an independent prognostic factor. Methylation of CORO1A may serve as biomarker for HMA treatment in AML.

scholarly journals Identification of Seven Novel Ferroptosis-Related Long Non - Coding RNA Signatures as a Diagnostic Biomarker for Acute Myeloid Leukemia

2021 ◽  
Author(s):  
Zhiyuan Zheng ◽  
Wei Wu ◽  
Zehang Lin ◽  
Shuhan Liu ◽  
Qiaoqian Chen ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier ◽  
Acute Myeloid

Abstract Background: Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model.Methods: RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs.Results: Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity.Conclusions: In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

scholarly journals Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

2020 ◽  
Author(s):  
Zhixiang Chen ◽  
Luya Ye ◽  
Xuechun Wang ◽  
Fuquan Tu ◽  
Xuezhen Li ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Profiles ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Risk Scores ◽  
Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is a common hematologic malignancy with poor prognosis. Accumulating reports have indicated that the tumor microenvironment (TME) performs a critical role in the progress of the disease and the clinical outcomes of patients. To date, the role of TME in AML remains clouded due to the complex regulatory mechanisms in it. In this study, We identified key prognostic genes relate to TME in AML and developed a novel gene signature for individualized prognosis assessment. Methods: The expression profiles of AML samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was applied to calculate the TME relevant immune and stromal scores. The differentially expressed genes (DEGs) were selected based on the immune and stromal scores. Then, the survival analysis was applied to select prognostic DEGs, and these genes were annotated by functional enrichment analysis. A TME relevant gene signature with predictive capability was constructed by a series of regression analyses and performed well in another cohort from the Gene Expression Omnibus (GEO) database. Moreover, we also developed a nomogram with the integration of the gene signature and clinical indicators to establish an individually quantified risk-scoring system. Results: In the AML microenvironment, a total of 181 DEGs with prognostic value were clarified. Then a seven-gene ( IL1R2, MX1, S100A4, GNGT2, ZSCAN23, PLXNB1 and DPY19L2 ) signature with robust prediction was identified, and was validated by an independent cohort of AML samples from the GSE71014. Gene set enrichment analysis (GSEA) of genes in the gene signature revealed these genes mainly enriched in the immune and inflammatory related processes. The correlation between the signature-calculated risk scores and the clinical features indicated that patients with high risk scores were accompanied by adverse survival. Finally, a nomogram with clinical utility was constructed. Conclusion: Our study explored and identified a novel TME relevant seven-gene signature, which could serve as a prognostic indicator for AML. Meanwhile, we also establish a nomogram with clinical significance. These findings might provide new insights into the diagnosis, treatment and prognosis of AML.

scholarly journals The Multi-Omic Prognostic Model of Oxidative Stress-Related Genes in Acute Myeloid Leukemia

2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Dong ◽  
Naijin Zhang ◽  
Lijun Zhang
Keyword(s):  
Oxidative Stress ◽  
Acute Myeloid Leukemia ◽  
Signaling Pathways ◽  
Myeloid Leukemia ◽  
Risk Model ◽  
Enrichment Analysis ◽  
Chemotherapeutic Agents ◽  
The Cancer Genome Atlas ◽  
Stress Genes ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) is one of the most common cancers in the world, and oxidative stress is closely related to leukemia. A lot of effort has been made to improve the prognosis of AML. However, the situation remains serious. Hence, we focused on the study of prognostic genes in AML.Materials and Methods: Prognostic oxidative stress genes were screened out. The gene expression profile of AML patients was downloaded from the The Cancer Genome Atlas (TCGA) database. The oxidative stress-related model was constructed, by which the prognosis of AML patients was predicted using the two GEO GSE23143 datasets and the stability of the GSE71014 authentication model.Results: The prognostic oxidative stress genes were screened out in AML, and the prognostic genes were significantly enriched in a large number of pathways based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. There was a complex interaction between prognostic genes and transcription factors. After constructing the prediction model, the clinical predictive value of the model was discussed in a multi-omic study. We investigated the sensitivity of risk score to common chemotherapeutic agents, the influence of signaling pathways on the prognosis of AML patients, and the correlation of multiple genes with immune score and immune dysfunction.Conclusions: A highly effective prognostic risk model for AML patients was established and validated. The association of prognostic oxidative stress genes with drug sensitivity, signaling pathways, and immune infiltration was explored. The results suggested that oxidative stress genes promised to be potential prognostic biomarkers for AML, which may provide a new basis for disease management.

scholarly journals Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Mahmoud S Alghamri ◽  
Rohit Thalla ◽  
Ruthvik P Avvari ◽  
Ali Dabaja ◽  
Ayman Taher ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Low Grade Gliomas ◽  
Mutational Burden ◽  
Gene Sets ◽  
Tumor Mutational Burden ◽  
Cancer Genome Atlas ◽  
Gene Ontologies

Abstract Background Gliomas are the most common primary brain tumors. High-Grade Gliomas have a median survival (MS) of 18 months, while Low-Grade Gliomas (LGGs) have an MS of approximately 7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH) enzyme. Survival of these patients ranges from 1 to 15 years, and tumor mutational burden ranges from 0.28 to 3.85 somatic mutations/megabase per tumor. We tested the hypothesis that the tumor mutational burden would predict the survival of patients with tumors bearing mIDH. Methods We analyzed the effect of tumor mutational burden on patients’ survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Glioma Longitudinal AnalySiS consortium. Results High tumor mutational burden negatively correlates with the survival of patients with LGG harboring mIDH (P = .005). This effect was significant for both Oligodendroglioma (LGG-mIDH-O; MS = 2379 vs 4459 days in high vs low, respectively; P = .005) and Astrocytoma (LGG-mIDH-A; MS = 2286 vs 4412 days in high vs low respectively; P = .005). There was no differential representation of frequently mutated genes (eg, TP53, ATRX, CIC, and FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to cell cycle, DNA-damage response in high versus low tumor mutational burden. Finally, we identified 6 gene sets that predict survival for LGG-mIDH-A and LGG-mIDH-O. Conclusions we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of MS in mIDH patients.

scholarly journals Chemoresponse of de novo Acute Myeloid Leukemia to “7+3” Induction can Be Predicted by c-Myc-facilitated Cytogenetics

2021 ◽  
Vol 12 ◽  
Author(s):  
Tzu-Hung Hsiao ◽  
Ren Ching Wang ◽  
Tsai-Jung Lu ◽  
Chien-Hung Shih ◽  
Yu-Chen Su ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
High Risk ◽  
Myeloid Leukemia ◽  
De Novo ◽  
Enrichment Analysis ◽  
Standard Of Care ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Myc Gene ◽  
Acute Myeloid

Background: Identifying patients with de novo acute myeloid leukemia (AML) who will probably respond to the “7 + 3” induction regimen remains an unsolved clinical challenge. This study aimed to identify whether c-Myc could facilitate cytogenetics to predict a “7 + 3” induction chemoresponse in de novo AML.Methods: We stratified 75 untreated patients (24 and 51 from prospective and retrospective cohorts, respectively) with de novo AML who completed “7 + 3” induction into groups with and without complete remission (CR). We then compared Myc-associated molecular signatures between the groups in the prospective cohort after gene set enrichment analysis. The expression of c-Myc protein was assessed by immunohistochemical staining. We defined high c-Myc-immunopositivity as &gt; 40% of bone marrow myeloblasts being c-Myc (+).Results: Significantly more Myc gene expression was found in patients who did not achieve CR by “7 + 3” induction than those who did (2439.92 ± 1868.94 vs. 951.60 ± 780.68; p = 0.047). Expression of the Myc gene and c-Myc protein were positively correlated (r = 0.495; p = 0.014). Although the non-CR group did not express more c-Myc protein than the CR group (37.81 ± 25.13% vs. 29.04 ± 19.75%; p = 0.151), c-Myc-immunopositivity could be a surrogate to predict the “7 + 3” induction chemoresponse (specificity: 81.63%). More importantly, c-Myc-immunopositivity facilitated cytogenetics to predict a “7 + 3” induction chemoresponse by increasing specificity from 91.30 to 95.92%.Conclusion: The “7 + 3” induction remains the standard of care for de novo AML patients, especially for those without a high c-Myc-immunopositivity and high-risk cytogenetics. However, different regimens might be considered for patients with high c-Myc-immunopositivity or high-risk cytogenetics.

scholarly journals Identification of seven novel ferroptosis-related long non-coding RNA signatures as a diagnostic biomarker for acute myeloid leukemia

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Zhiyuan Zheng ◽  
Wei Wu ◽  
Zehang Lin ◽  
Shuhan Liu ◽  
Qiaoqian Chen ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier ◽  
Acute Myeloid

Abstract Background Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model. Methods RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs. Results Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan–Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity. Conclusions In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

scholarly journals Tumor Mutational Burden Predicts Survival In Patients With Low Grade Gliomas Expressing Mutated IDH1

2020 ◽  
Author(s):  
Mahmoud S Alghamri ◽  
Rohit Thalla ◽  
Ruthvik Avvari ◽  
Ali Dabaja ◽  
Ayman Taher ◽  
...  
Keyword(s):  
Median Survival ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Low Grade Gliomas ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Genome Atlas

ABSTRACTGliomas are the most common primary brain tumors. High Grade Gliomas have a median survival of 18 months, while Low Grade Gliomas (LGG) have a median survival of ∼7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH1) enzyme (IDH1R132H). Survival of these patients ranges from 1-15 years, and tumor mutational burden ranges from 8 to 447 total somatic mutations per tumor. We tested the hypothesis that the tumor mutational burden would predict survival of patients with tumors bearing mIDH1R132H. We analyzed the effect of tumor mutational burden on patients’ survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Chinese Glioma Genome Atlas. High tumor mutational burden negatively correlates with survival of patients with LGG harboring IDH1R132H (p<0.0001). This effect was significant for both Oligodendroglioma and Astrocytoma LGG-mIDH1 patients. In the TCGA data, median survival of the high mutational burden group was 76 months, while in the low mutational burden group it was 136 months; p<0.0001. There was no differential representation of frequently mutated genes (e.g., TP53, ATRX, CIC, FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to Cell cycle, DNA damage response in high vs low tumor mutational burden. Finally, we identified a 19 gene signature that predicts survival for patients from both databases. In summary, we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of median survival in mIDH1 patients.

scholarly journals The Prognostic Value and Function of HOXB5 in Acute Myeloid Leukemia

2021 ◽  
Vol 12 ◽  
Author(s):  
Miao Chen ◽  
Yi Qu ◽  
Pengjie Yue ◽  
Xiaojing Yan
Keyword(s):  
Dna Methylation ◽  
Acute Myeloid Leukemia ◽  
Cell Differentiation ◽  
Myeloid Leukemia ◽  
Hox Genes ◽  
Interaction Analysis ◽  
Quantitative Polymerase Chain Reaction ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Acute Myeloid

BackgroundCurrently, cytogenetic and genetic markers are the most important for risk stratification and treatment of patients with acute myeloid leukemia (AML). Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Therefore, the identification of new AML biomarkers is useful in the prognosis and monitoring of AML and contributes to a better understanding of the molecular basis of the disease. Homeobox (HOX) genes are transcription factors that lead to cell differentiation blockade and malignant self-renewal. However, the roles of HOX genes in AML are still not fully understood and need further exploration, which may provide new strategies for the prognosis and monitoring of AML.MethodsWe analyzed the RNA sequencing and clinical data from The Cancer Genome Atlas (TCGA), VIZOME, GSE13159, and GSE9476 cohorts. Analyses were performed with GraphPad 7, the R language, and several online databases. We applied quantitative polymerase chain reaction, Western Blotting, CCK8 cell proliferation assays, and flow cytometry to verify the conclusions of the bioinformatics analysis.ResultsWe identified HOXB5 as the only gene among the HOX family that was not only elevated in AML but also a significant prognostic marker in AML patients. HOXB5 was highly expressed in AML patients with NPM1, FLT3, or DNMT3A mutations and was expressed at the highest level in patients with NPM1-FLT3-DNMT3A triple-mutant AML. Gene Ontology analysis and gene set enrichment analysis revealed that HOXB5 showed a negative correlation with the myeloid cell differentiation signature and that the tumor necrosis factor/nuclear factor κB signaling pathway was involved in the molecular mechanism. Moreover, we performed in silico protein–protein interaction analysis and 450K TCGA DNA methylation data analysis and found that HOXB5 interacted with two HOX genes (HOXA7 and HOXB4) that were commonly regulated by DNA methylation levels.ConclusionHOXB5 is associated with the malignant development of AML and may be a treatment target and biomarker for AML prognosis prediction.

scholarly journals Identification and validation of obesity-related gene LEP methylation as a prognostic indicator in patients with acute myeloid leukemia

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Ting-juan Zhang ◽  
Zi-jun Xu ◽  
Yu Gu ◽  
Ji-chun Ma ◽  
Xiang-mei Wen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Related Gene ◽  
Targeted Bisulfite Sequencing ◽  
Specific Pcr ◽  
Frequent Event ◽  
Acute Myeloid

Abstract Background Obesity confers enhanced risk for multiple diseases including cancer. The DNA methylation alterations in obesity-related genes have been implicated in several human solid tumors. However, the underlying role and clinical implication of DNA methylation of obesity-related genes in acute myeloid leukemia (AML) has yet to be elucidated. Results In the discovery stage, we identified that DNA methylation-associated LEP expression was correlated with prognosis among obesity-related genes from the databases of The Cancer Genome Atlas. In the validation stage, we verified that LEP hypermethylation was a frequent event in AML by both targeted bisulfite sequencing and real-time quantitative methylation-specific PCR. Moreover, LEP hypermethylation, correlated with reduced LEP expression, was found to be associated with higher bone marrow blasts, lower platelets, and lower complete remission (CR) rate in AML. Importantly, survival analysis showed that LEP hypermethylation was significantly associated with shorter overall survival (OS) in AML. Moreover, multivariate analysis disclosed that LEP hypermethylation was an independent risk factor affecting CR and OS among non-M3 AML. By clinical and bioinformatics analysis, LEP may be also regulated by miR-517a/b expression in AML. Conclusions Our findings indicated that the obesity-related gene LEP methylation is associated with LEP inactivation, and acts as an independent prognostic predictor in AML.

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