Identification of Prognostic-Related Genes in Acute Myeloid Leukemia: A Study Based on TCGA Data Analysis.

IF 1.6 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Fatemeh Sadat Shafiei, Saeid Abroun, Sadaf Vahdat, Ali Arash Anoushirvani, Mohammad Rafiee
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引用次数: 0

Abstract

Acute myeloid leukemia (AML) is the most common type of leukemia in adults, primarily caused by multiple gene mutations and abnormal gene expression. Molecular heterogeneity among AML patients can lead to the variation of treatment outcomes, and the prognostic significance of genetic disruptions is crucial for treatment decisions. Therefore, in this study, we intended to identify novel potential prognosis-related genes in AML patients. This study comprehensively assessed transcriptomic data of primary AML patients from TARGET and BEAT-AML cohorts from the TCGA database. The common differentially expressed mRNAs (DEmRNAs) of the study groups were determined and screened to identify genes that indicated a correlation between their expression levels and the overall survival (OS) of AML patients. Moreover, RT-PCR was used to compare the expression of the identified prognosis-related genes between AML patients and non-leukemic groups to confirm the obtained bioinformatics data. The analysis resulted in the identification of 39 common significant DEmRNAs in both cohorts. Moreover, among the identified common genes, the expression levels of two genes, MME and RBM11, significantly correlated with the OS of AML patients; it was revealed that there was a significant negative correlation between a higher survival rate in AML patients and the lower expression of MME (log-rank P = 1.3*10-7 and Hazard Ratio (HR = 1.38 (1.22-1.56)) and RBM11 (log-rank P = 0.016 and HR = 1.25 (1.04-1.5)). Furthermore, RT-PCR data confirmed the expected differential expression of identified genes between patient and control samples. In conclusion, our investigation resulted in the identification of two potential prognosis-related genes that can be used in further prognostic evaluation studies.

基于TCGA数据分析的急性髓系白血病预后相关基因鉴定
急性髓系白血病(AML)是成人最常见的白血病类型,主要由多基因突变和基因表达异常引起。AML患者的分子异质性可能导致治疗结果的变化,基因破坏的预后意义对治疗决策至关重要。因此,在这项研究中,我们打算在AML患者中发现新的潜在预后相关基因。本研究全面评估了TCGA数据库中TARGET和BEAT-AML队列中原发性AML患者的转录组学数据。对研究组的共同差异表达mrna (demrna)进行测定和筛选,以确定其表达水平与AML患者总生存期(OS)相关的基因。此外,利用RT-PCR比较鉴定的预后相关基因在AML患者和非白血病组之间的表达,以证实获得的生物信息学数据。分析结果在两个队列中鉴定出39个共同的重要demrna。此外,在鉴定的常见基因中,MME和RBM11两个基因的表达水平与AML患者的OS显著相关;发现AML患者较高的生存率与较低的MME表达(log-rank P = 1.3*10-7,风险比(HR = 1.38(1.22-1.56))、RBM11 (log-rank P = 0.016, HR = 1.25(1.04-1.5))呈显著负相关。此外,RT-PCR数据证实了患者和对照样本之间鉴定基因的预期差异表达。总之,我们的研究发现了两个潜在的预后相关基因,可用于进一步的预后评估研究。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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