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 Identification of m6A-Related lncRNAs Associated With Prognoses and Immune Responses in Acute Myeloid Leukemia

2021 ◽  
Vol 9 ◽  
Author(s):  
Ding Li ◽  
Jiaming Liang ◽  
Cheng Cheng ◽  
Wenbin Guo ◽  
Shuolei Li ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Pearson Correlation ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Risk Scores ◽  
Hematopoietic Malignancy ◽  
Cox Regression Analysis ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) remains the most common type of hematopoietic malignancy in adults and has an unfavorable outcome. Herein, we aimed to construct an N6-methylandenosine (m6A)-related long noncoding RNAs (lncRNAs) signature to accurately predict the prognosis of patients with AML using the data downloaded from The Cancer Genome Atlas (TCGA) database.Methods: The RNA-seq and clinical data were obtained from the TCGA AML cohort. First, Pearson correlation analysis was performed to identify the m6A-related lncRNAs. Next, univariate Cox regression analysis was used to determine the candidate lncRNAs with prognostic value. Then, feature selection was carried out by Least absolute shrinkage and selection operator (LASSO) analysis, and seven eligible m6A-related lncRNAs were included to construct the prognostic risk signature. Kaplan–Meier and receiver operating characteristic (ROC) curve analyses were performed to evaluate the predictive capacity of the risk signature both in the training and testing datasets. A nomogram was used to predict 1-year, 2-year, and 3-year overall survival (OS) of AML patients. Next, the expression levels of lncRNAs in the signature were validated in AML samples by qRT-PCR. Functional enrichment analyses were carried out to identify probable biological processes and cellular pathways. The ceRNA network was developed to explore the downstream targets and mechanisms of m6A-related lncRNAs in AML.Results: Seven m6A-related lncRNAs were identified as a prognostic signature. The low-risk group hold significantly prolonged OS. The nomogram showed excellent accuracy of the signature for predicting 1-year, 2-year and 3-year OS (AUC = 0.769, 0.820, and 0.800, respectively). Moreover, the risk scores were significantly correlated with enrichment in cancer hallmark- and malignancy-related pathways and immunotherapy response in AML patients.Conclusion: We developed and validated a novel risk signature with m6A-related lncRNAs which could predict prognosis accurately and reflect the immunotherapy response in AML patients.

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 Mutant DNMT3A: a marker of poor prognosis in acute myeloid leukemia

Blood ◽  
2012 ◽  
Vol 119 (24) ◽  
pp. 5824-5831 ◽  
Author(s):  
Ana Flávia Tibúrcio Ribeiro ◽  
Marta Pratcorona ◽  
Claudia Erpelinck-Verschueren ◽  
Veronika Rockova ◽  
Mathijs Sanders ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Multivariable Analysis ◽  
Gene Expression Signature ◽  
Mutation Status ◽  
Cox Regression Analysis ◽  
Prognostic Effect ◽  
Or Gene ◽  
Acute Myeloid

Abstract The prevalence, the prognostic effect, and interaction with other molecular markers of DNMT3A mutations was studied in 415 patients with acute myeloid leukemia (AML) younger than 60 years. We show mutations in DNMT3A in 96 of 415 patients with newly diagnosed AML (23.1%). Univariate Cox regression analysis showed that patients with DNMT3Amutant AML show significantly worse overall survival (OS; P = .022; hazard ratio [HR], 1.38; 95% confidence interval [CI], 1.04-1.81), and relapse-free survival (RFS; P = .005; HR, 1.52; 95% CI, 1.13-2.05) than DNMT3Awild-type AMLs. In a multivariable analysis, DNMT3A mutations express independent unfavorable prognostic value for OS (P = .003; HR, 1.82; 95% CI, 1.2-2.7) and RFS (P < .001; HR, 2.2; 95% CI, 1.4-3.3). In a composite genotypic subset of cytogenetic intermediate-risk AML without FLT3-ITD and NPM1 mutations, this association is particularly evident (OS: P = .013; HR, 2.09; 95% CI, 1.16-3.77; RFS: P = .001; HR, 2.65; 95% CI, 1.48-4.89). The effect of DNMT3A mutations in human AML remains elusive, because DNMT3Amutant AMLs did not express a methylation or gene expression signature that discriminates them from patients with DNMT3Awild-type AML. We conclude that DNMT3A mutation status is an important factor to consider for risk stratification of patients with AML.

scholarly journals Expression Levels of Human Equilibrative Nucleoside Transporter 1 and Deoxycytidine Kinase Enzyme as Prognostic Factors in Patients with Acute Myeloid Leukemia Treated with Cytarabine

Chemotherapy ◽  
2016 ◽  
Vol 61 (6) ◽  
pp. 313-318 ◽  
Author(s):  
Myrna Candelaria ◽  
Carmen Corrales-Alfaro ◽  
Olga Gutiérrez-Hernández ◽  
José Díaz-Chavez ◽  
Juan Labardini-Méndez ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Performance Status ◽  
Deoxycytidine Kinase ◽  
Nucleoside Transporter ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Equilibrative Nucleoside Transporter ◽  
Acute Myeloid

Background: Cytarabine (Ara-C) is the primary drug in different treatment schemas for acute myeloid leukemia (AML) and requires the human equilibrative nucleoside transporter (hENT1) to enter cells. The deoxycytidine kinase (dCK) enzyme limits its activation rate. Therefore, decreased expression levels of these genes may influence the response rate to this drug. Methods: AML patients without previous treatment were enrolled. The expression of hENT1 and dCK genes was analyzed using RT-PCR. Clinical parameters were registered. All patients received Ara-C + doxorubicin as an induction regimen (7 + 3 schema). Descriptive statistics were used to analyze data. Uni- and multivariate analyses were performed to determine factors that influenced response and survival. Results: Twenty-eight patients were included from January 2011 until December 2012. Median age was 36.5 years. All patients had an adequate performance status (43% with ECOG 1 and 57% with ECOG 2). Cytogenetic risk was considered unfavorable in 54% of the patients. Complete response was achieved in 53.8%. Cox regression analysis showed that a higher hENT1 expression level was the only factor that influenced response and survival. Conclusions: These results highly suggest that the pharmacogenetic analyses of Ara-C influx may be decisive in AML patients.

scholarly journals High Expression of PXN Predicts a Poor Prognosis in Acute myeloid leukemia

2021 ◽  
Author(s):  
xinwen zhang ◽  
Hao Xiong ◽  
Jialin Duan ◽  
Xiaomin Chen ◽  
Yang Liu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Receive Treatment ◽  
To Receive ◽  
Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is one of the common malignant diseases of hematopoietic system. Paxillin ( PXN ) is an important part of focal adhesions (FAs), which is related to the poor prognosis of many kinds of malignant tumors. However, no research has focused on the expression of PXN in AML. We aimed to investigate the expression of PXN in AML and its prognostic significance. Methods: Using GEPIA and UALCAN database to analyze the expression of PXN in AML patients and its prognostic significance. Bone marrow samples of newly diagnosed AML patients were collected to extract RNA, and qRT-PCR was used to detect the expression of PXN . The prognosis was followed up. Chi-square test was used to analyze the relationship between PXN expression and clinical laboratory characteristics. Kaplan-Meier analysis was used to draw survival curve, and Cox regression analysis was used to analyze the independent factors affecting the prognosis of patients with AML. The co-expression genes of PXN were analyzed by LinkedOmics to explore its biological significance in AML. Results: Kaplan-Meier analysis showed that the overall survival time of AML patients was related to whether to receive treatment and PXN expression(P<0.05). COX regression analysis showed that whether to receive treatment (HR=0.227，95%CI=0.075-0.689， P =0.009) and high expression of PXN (HR=4.484，95%CI=1.449-13.889， P =0.009) were independent poor prognostic factors in patients with AML. Conclusion: PXN is highly expressed in AML patient, and high PXN expression is an indicator of poor prognosis in AML patient.

scholarly journals Rebound Thrombocytosis following Induction Chemotherapy Is an Independent Predictor of a Good Prognosis in Acute Myeloid Leukemia Patients Attaining First Complete Remission

2015 ◽  
Vol 134 (1) ◽  
pp. 32-37 ◽  
Author(s):  
Umit Yavuz Malkan ◽  
Gursel Gunes ◽  
Ayse Isik ◽  
Eylem Eliacik ◽  
Sezgin Etgul ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Recovery Time ◽  
Cox Regression ◽  
De Novo ◽  
Statistical Significance ◽  
Good Prognosis ◽  
Platelet Recovery ◽  
Cox Regression Analysis ◽  
Acute Myeloid

There are very few data about the relationship between acute myeloid leukemia (AML) prognosis and bone marrow recovery kinetics following chemotherapy. In this study, we aimed to assess the prognostic importance and clinical associations of neutrophil and platelet recovery rates and rebound thrombocytosis (RT) or neutrophilia (RN) in the postchemotherapy period for newly diagnosed AML patients. De novo AML patients diagnosed between October 2002 and December 2013 were evaluated retrospectively. One hundred patients were suitable for inclusion. Cox regression analysis using need for reinduction chemotherapy as a stratification parameter revealed RT as the only parameter predictive of OS, with borderline statistical significance (p = 0.06, OR = 7; 95% CI 0.92-53), and it was the only parameter predictive of DFS (p = 0.024, OR = 10; 95% CI 1.3-75). In order to understand whether RT or RN was related to a better marrow capacity or late consolidation, we considered neutrophil recovery time and platelet recovery time and nadir-first consolidation durations in all patients in the cohort. Both the marrow recovery duration and the time between marrow aplasia and first consolidation were shorter in RT and RN patients. To our knowledge, this is the first study to report a correlation between RT/RN and prognosis in AML.

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 Construction of a novel ferroptosis-related gene signature for predicting prognosis and immune microenvironment in acute myeloid leukemia

2021 ◽  
Author(s):  
Xianbo Huang ◽  
De Zhou ◽  
Xiujin Ye ◽  
Jie Jin
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Risk Model ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Risk Groups ◽  
Low Risk ◽  
Cox Regression Analysis ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is a highly heterogeneous hematopoietic malignancy that strongly correlates with poor clinical outcomes. Ferroptosis is an iron-dependent, non-apoptotic form of regulated cell death which plays an important role in various human cancers. Nevertheless, the prognostic significance and functions of ferroptosis-related genes (FRGs) in AML have not received sufficient attention. The aim of this article was to evaluate the association between FRGs levels and AML prognosis using publicly available RNA-sequencing datasets. The univariate Cox regression analysis identified 20 FRGs that correlate with patient overall survival. The LASSO Cox regression model was used to construct a prognostic 12-gene risk model using a TCGA cohort, and internal and external validation proved the signature efficient. The 12-FRGs signature was then used to assign patients into high- and low-risk groups, with the former exhibiting markedly reduced overall survival, compared to the low-risk group. ROC curve analysis verified the predictive ability of the risk model. Functional analysis showed that immune status and drug sensitivity differed between the 2 risk groups. In summary, FRGs is a promising candidate biomarker and therapeutic target for AML.

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