scholarly journals A hypoxia risk signature for the tumor immune microenvironment evaluation and prognosis prediction in acute myeloid leukemia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Feng Jiang ◽  
Yan Mao ◽  
Binbin Lu ◽  
Guoping Zhou ◽  
Jimei Wang
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Risk Model ◽  
Prognostic Indicator ◽  
Gene Expression Omnibus ◽  
Risk Scores ◽  
Immune Microenvironment ◽  
Clinical Prognosis ◽  
Tumor Immune Microenvironment ◽  
Acute Myeloid

AbstractAcute myeloid leukemia (AML) is the most prevalent form of acute leukemia. Patients with AML often have poor clinical prognoses. Hypoxia can activate a series of immunosuppressive processes in tumors, resulting in diseases and poor clinical prognoses. However, how to evaluate the severity of hypoxia in tumor immune microenvironment remains unknown. In this study, we downloaded the profiles of RNA sequence and clinicopathological data of pediatric AML patients from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, as well as those of AML patients from Gene Expression Omnibus (GEO). In order to explore the immune microenvironment in AML, we established a risk signature to predict clinical prognosis. Our data showed that patients with high hypoxia risk score had shorter overall survival, indicating that higher hypoxia risk scores was significantly linked to immunosuppressive microenvironment in AML. Further analysis showed that the hypoxia could be used to serve as an independent prognostic indicator for AML patients. Moreover, we found gene sets enriched in high-risk AML group participated in the carcinogenesis. In summary, the established hypoxia-related risk model could act as an independent predictor for the clinical prognosis of AML, and also reflect the response intensity of the immune microenvironment in AML.

scholarly journals m6A-Related lncRNAs Affect Tumor Immune Microenvironment And Prognosis In Acute Myeloid Leukemia

2021 ◽  
Author(s):  
Fangmin Zhong ◽  
Fangyi Yao ◽  
Ying Cheng ◽  
Jing Liu ◽  
Nan Zhang ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Risk Scores ◽  
In Vitro Assays ◽  
Immune Microenvironment ◽  
Cox Regression Analysis ◽  
Tumor Immune Microenvironment ◽  
The Relationship ◽  
Acute Myeloid

Abstract Acute myeloid leukemia (AML) is a complex hematologic malignancy. Survival rate of AML patients is low. N6-methyladenosine (m6A) and long-chain non-coding RNAs (lncRNAs) play important roles in AML tumorigenesis and progression. However, the relationship between lncRNAs and biological characteristics of AML, as well as how lncRNAs influence the prognosis of AML patients, remain unclear. In this study, we identified m6A-related lncRNAs, and analyzed their roles and prognostic values in AML. m6A-related lncRNAs associated with patient prognosis were screened using univariate Cox regression analysis, followed by systematic analysis of the relationship between these genes and AML clinicopathologic and biologic characteristics. Furthermore, we examined the characteristics of tumor immune microenvironment (TIME) using different IncRNA clustering models. Using LASSO regression, we identified the risk signals related to prognosis of AML patients. We then constructed and verified a risk model based on m6A-related lncRNAs for independent prediction of overall survival in AML patients. Our results indicate that risk scores, calculated based on risk-related signaling, were related to the clinicopathologic characteristics of AML and level of immune infiltration. Finally, we examined the expression level of TRAF3IP2-AS1 in patient samples through real-time polymerase chain reaction analysis and in GEO datasets, and we identified SRSF10 as a regulator of TRAF3IP2-AS1 through in vitro assays. Our study shows that m6A-related lncRNAs, evaluated using the risk prediction model, can potentially be used to predict prognosis and design immunotherapy in AML patients.

scholarly journals The establishment of a prognostic scoring model based on the new tumor immune microenvironment classification in acute myeloid leukemia

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Tiansheng Zeng ◽  
Longzhen Cui ◽  
Wenhui Huang ◽  
Yan Liu ◽  
Chaozeng Si ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Prognostic Model ◽  
Prognostic Significance ◽  
The Cancer Genome Atlas ◽  
Prognostic Models ◽  
Clustering Methods ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Acute Myeloid

Abstract Background The high degree of heterogeneity brought great challenges to the diagnosis and treatment of acute myeloid leukemia (AML). Although several different AML prognostic scoring models have been proposed to assess the prognosis of patients, the accuracy still needs to be improved. As important components of the tumor microenvironment, immune cells played important roles in the physiological functions of tumors and had certain research value. Therefore, whether the tumor immune microenvironment (TIME) can be used to assess the prognosis of AML aroused our great interest. Methods The patients’ gene expression profile from 7 GEO databases was normalized after removing the batch effect. TIME cell components were explored through Xcell tools and then hierarchically clustered to establish TIME classification. Subsequently, a prognostic model was established by Lasso-Cox. Multiple GEO databases and the Cancer Genome Atlas dataset were employed to validate the prognostic performance of the model. Receiver operating characteristic (ROC) and the concordance index (C-index) were utilized to assess the prognostic efficacy. Results After analyzing the composition of TIME cells in AML, we found infiltration of ten types of cells with prognostic significance. Then using hierarchical clustering methods, we established a TIME classification system, which clustered all patients into three groups with distinct prognostic characteristics. Using the differential genes between the first and third groups in the TIME classification, we constructed a 121-gene prognostic model. The model successfully divided 1229 patients into the low and high groups which had obvious differences in prognosis. The high group with shorter overall survival had more patients older than 60 years and more poor-risk patients (both P< 0.001). Besides, the model can perform well in multiple datasets and could further stratify the cytogenetically normal AML patients and intermediate-risk AML population. Compared with the European Leukemia Net Risk Stratification System and other AML prognostic models, our model had the highest C-index and the largest AUC of the ROC curve, which demonstrated that our model had the best prognostic efficacy. Conclusion A prognostic model for AML based on the TIME classification was constructed in our study, which may provide a new strategy for precision treatment in AML.

scholarly journals The characteristics of circRNA as competing endogenous RNA in pathogenesis of acute myeloid leukemia

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Siyuan Zhang
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
The Novel ◽  
Competing Endogenous Rna ◽  
Regulatory Modules ◽  
Cerna Network ◽  
Regulatory Module ◽  
Acute Myeloid

Abstract Background As one of the novel molecules, circRNA has been identified closely involved in the pathogenesis of many diseases. However, the function of circRNA in acute myeloid leukemia (AML) still remains unknown. Methods In the current study, the RNA expression profiles were obtained from Gene Expression Omnibus (GEO) datasets. The differentially expressed RNAs were identified using R software and the competing endogenous RNA (ceRNA) network was constructed using Cytoscape. Functional and pathway enrichment analyses were performed to identify the candidate circRNA-mediated aberrant signaling pathways. The hub genes were identified by MCODE and CytoHubba plugins of Cytoscape, and then a subnetwork regulatory module was established. Results A total of 27 circRNA-miRNA pairs and 208 miRNA-mRNA pairs, including 12 circRNAs, 24 miRNAs and 112 mRNAs were included in the ceRNA network. Subsequently, a subnetwork, including 4 circRNAs, 5 miRNAs and 6 mRNAs, was established based on related circRNA-miRNA-mRNA regulatory modules. Conclusions In summary, this work analyzes the characteristics of circRNA as competing endogenous RNA in AML pathogenesis, which would provide hints for developing novel prognostic, diagnostic and therapeutic strategy for AML.

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.

A novel prognostic model in elderly patients with acute myeloid leukemia: results of 909 patients entered into the prospective AML96 trial

Blood ◽  
2010 ◽  
Vol 116 (6) ◽  
pp. 971-978 ◽  
Author(s):  
Christoph Röllig ◽  
Christian Thiede ◽  
Martin Gramatzki ◽  
Walter Aulitzky ◽  
Heinrich Bodenstein ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Risk Model ◽  
Cox Model ◽  
Prognostic Significance ◽  
Disease Free Survival ◽  
Intermediate Risk ◽  
Npm1 Mutation ◽  
Prognostic Groups ◽  
Acute Myeloid

Abstract We present an analysis of prognostic factors derived from a trial in patients with acute myeloid leukemia older than 60 years. The AML96 trial included 909 patients with a median age of 67 years (range, 61-87 years). Treatment included cytarabine-based induction therapy followed by 1 consolidation. The median follow-up time for all patients is 68 months (5.7 years). A total of 454 of all 909 patients reached a complete remission (50%). Five-year overall survival (OS) and disease-free survival were 9.7% and 14%, respectively. Multivariate analyses revealed that karyotype, age, NPM1 mutation status, white blood cell count, lactate dehydrogenase, and CD34 expression were of independent prognostic significance for OS. On the basis of the multivariate Cox model, an additive risk score was developed that allowed the subdivision of the largest group of patients with an intermediate-risk karyotype into 2 groups. We are, therefore, able to distinguish 4 prognostic groups: favorable risk, good intermediate risk, adverse intermediate risk, and high risk. The corresponding 3-year OS rates were 39.5%, 30%, 10.6%, and 3.3%, respectively. The risk model allows further stratification of patients with intermediate-risk karyotype into 2 prognostic groups with implications for the therapeutic strategy. This study was registered at www.clinicaltrials.gov as #NCT00180115.

scholarly journals A Predictor Combining Clinical and Genetic Factors for AML1-ETO Leukemia Patients

2022 ◽  
Vol 11 ◽  
Author(s):  
Min Yang ◽  
Bide Zhao ◽  
Jinghan Wang ◽  
Yi Zhang ◽  
Chao Hu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Somatic Mutations ◽  
Genetic Factors ◽  
Risk Model ◽  
Core Binding Factor ◽  
Kit Mutation ◽  
Binding Factor ◽  
Prognostic Prediction ◽  
Acute Myeloid

Core Binding Factor (CBF)-AML is one of the most common somatic mutations in acute myeloid leukemia (AML). t(8;21)/AML1-ETO-positive acute myeloid leukemia accounts for 5-10% of all AMLs. In this study, we consecutively included 254 AML1-ETO patients diagnosed and treated at our institute from December 2009 to March 2020, and evaluated molecular mutations by 185-gene NGS platform to explore genetic co-occurrences with clinical outcomes. Our results showed that high KIT VAF(≥15%) correlated with shortened overall survival compared to other cases with no KIT mutation (3-year OS rate 26.6% vs 59.0% vs 69.6%, HR 1.50, 95%CI 0.78-2.89, P=0.0005). However, no difference was found in patients’ OS whether they have KIT mutation in two or three sites. Additionally, we constructed a risk model by combining clinical and molecular factors; this model was validated in other independent cohorts. In summary, our study showed that c-kit other than any other mutations would influence the OS in AML1-ETO patients. A proposed predictor combining both clinical and genetic factors is applicable to prognostic prediction in AML1-ETO patients.

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 Identification of TFE3/TFEB and its Related Genes as Prognostic Biomarkers in Acute Myeloid Leukemia

2021 ◽  
Author(s):  
Qiaoli Li
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Prognostic Factors ◽  
Cell Fate ◽  
Protein Interactions ◽  
Myeloid Leukemia ◽  
Sequence Data ◽  
Gene Expression Omnibus ◽  
Prognostic Biomarkers ◽  
Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is one of the most common hematologic malignances with an ever-increasing incidence and high mortality. TFE3 and TFEB, two transcription factors that mediate cellular adaptation to stress by simultaneously promoting lysosomal biogenesis, autophagy induction, as well as expression of critical mitochondrial and metabolic regulators, which are substantial contributors to cell fate and cancer progress. However, the expression and prognostic values of TFE3/TFEB in AML have not been clarified.Objective: To explore the expression and role of TFE3/TFEB in AML and thus to find potential therapy. Methods: RNA sequence data from AML patients and healthy donors were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis were performed by GEO2R. TFE3/TFEB related genes were obtained from UALCAN. Gene ontology (GO) and KEGG pathway were analyzed by WEB-based GEne SeT AnaLysis Toolkit (WebGestalt) and DAVID. Protein-protein interactions (PPIs) network construction and module analysis were performed by STRING and Cytoscape. The Kaplan-Meier survival curves were drawn in TCGA portal. Results: We found TFE3 and TFEB can be used prognostic factors for AML, and most of their positively related genes were worse prognostic factors too. ITGB2, FGR, ITGAM, ITGAX and SELPLG were identified as the most significant genes in survival-related genes contributed by TFE3 and TFEB.Conclusions: In this study, we performed a comprehensive analysis of gene expression and gene function to identify key prognostic biomarkers in AML.

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