The prognostic value of RASGEF1A RNA expression and DNA methylation in cytogenetically normal acute myeloid leukemia

髓系白血病 DNA甲基化 癌症研究 医学 甲基化 恶性肿瘤 肿瘤科 白血病 淋巴瘤 基因 内科学 生物 基因表达 遗传学
作者
Xue He,Weilong Zhang,Wei Fu,Xiaoni Liu,Ping Yang,Jing Wang,Mingxia Zhu,Shaoxiang Li,Wei Zhang,Xiuru Zhang,Gehong Dong,Changjian Yan,Yali Zhao,Zeng Zhi-ping,Hongmei Jing
出处
期刊:Cancer Biomarkers [IOS Press]
卷期号:36 (2): 103-116
标识
DOI:10.3233/cbm-210407
摘要

BACKGROUND: Acute myeloid leukemia (AML) is a significantly heterogeneous malignancy of the blood. Cytogenetic abnormalities are crucial for the prognosis of AML. However, since more than half of patients with AML are cytogenetically normal AML (CN-AML), predictive prognostic indicators need to be further refined. In recent years, gene abnormalities are considered to be strong prognostic factors of CN-AML, already having clinical significance for treatment. In addition, the relationship of methylation in some genes and AML prognosis predicting has been discovered. RASGEF1A is a guanine nucleotide exchange factors of Ras and widely expressed in brain tissue, bone marrow and 17 other tissues. RASGEF1A has been reported to be associated with a variety of malignant tumors, examples include Hirschsprung disease, renal cell carcinoma, breast cancer, diffuse large B cell lymphoma, intrahepatic cholangiocarcinoma and so on [1, 2]. However, the relationship between the RASGEF1A gene and CN-AML has not been reported. METHODS: By integrating the Cancer Genome Atlas (TCGA) database 75 patients with CN-AML and 240 Gene Expression Omnibus (GEO) database CN-AML samples, we examined the association between RASGEF1A’s RNA expression level and DNA methylation of and AML patients’ prognosis. Then, we investigated the RASGEF1A RNA expression and DNA methylation’s prognostic value in 77 patients with AML after allogeneic hematopoietic stem cell transplantation (Allo-HSCT) as well as 101 AML patients after chemotherapy respectively. We investigated the association between sensitivity to Crenolanib and expression level of RASGED1A in patients by integrating 191 CN-AML patients from BeatAML dadataset. We integrated the expression and methylation of RASGEF1A to predict the CN-AML patients’ prognosis and investigated the relationship between prognostic of AML patients with different risk classification and expression levels or methylation levels of RASGEF1A. RESULTS: We found that RASGEF1A gene high expression group predicted poorer event-free survival (EFS) (P< 0.0001) as well as overall survival (OS) (P< 0.0001) in CN-AML samples, and the identical results were found in AML patients receiving chemotherapy (P< 0.0001) and Allo-HSCT (P< 0.0001). RASGEF1A RNA expression level is an CN-AML patients’ independent prognostic factor (EFS: HR = 5.5534, 95% CI: 1.2982–23.756, P= 0.0208; OS: HR = 5.3615, 95% CI: 1.1014–26.099, P= 0.0376). The IC50 (half maximal inhibitory concentration) of Crenolanib of CN-AML samples with RASGEF1A high expression level is lower. In addition, patients with high RASGEF1A methylation level had significant favorable prognosis (EPS: P< 0.0001, OS: P< 0.0001). Furthermore, the integrative analysis of expression and methylation of RASGEF1A could classify CN-AML patients into subgroups with different prognosis (EFS: P= 0.034, OS: P= 0.0024). Expression levels or methylation levels of RASGEF1A help to improve risk classification of 2010 European Leukemia Net. CONCLUSION: Higher RASGEF1A RNA expression and lower DNA methylation predicts CN-AML patients’ poorer prognosis. The RASGEF1A high expression level from patients with CN-AML have better sensitivity to Crenolanib. The integrative analysis of RASGEF1A RNA expression and DNA methylation can provide a more accurate classification for prognosis. Lower RASGEF1A expression is a favorable prognostic factor for AML patients receiving chemotherapy or Allo-HSCT. 2010 European Leukemia Net’s risk classification can be improved by RASGEF1A expression levels or methylation levels.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
cdercder应助无聊的依白采纳,获得10
1秒前
1秒前
tomas完成签到,获得积分10
2秒前
JSYSM完成签到,获得积分10
2秒前
大呆呆的小萌萌完成签到,获得积分10
2秒前
angle关注了科研通微信公众号
2秒前
cdercder应助NN采纳,获得10
3秒前
GTY完成签到,获得积分10
3秒前
yygdfw发布了新的文献求助10
4秒前
4秒前
4秒前
小run发布了新的文献求助10
4秒前
dynamo完成签到,获得积分10
5秒前
stella应助标致的问芙采纳,获得10
6秒前
6秒前
热情的修哥完成签到 ,获得积分10
6秒前
7秒前
7秒前
Iris发布了新的文献求助10
7秒前
花花发布了新的文献求助10
8秒前
9秒前
PanY完成签到 ,获得积分10
9秒前
wendy发布了新的文献求助10
9秒前
领导范儿应助无聊的依白采纳,获得10
10秒前
青芸完成签到 ,获得积分10
11秒前
11秒前
大个应助负责的问雁采纳,获得10
11秒前
11秒前
12秒前
renerxiao发布了新的文献求助10
13秒前
要减肥的觅山完成签到,获得积分10
14秒前
14秒前
DHQ完成签到,获得积分10
14秒前
一呆发布了新的文献求助10
14秒前
yyyyy发布了新的文献求助10
14秒前
15秒前
bkagyin应助青松果采纳,获得10
15秒前
yygdfw完成签到,获得积分20
15秒前
inp完成签到 ,获得积分10
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Photothermal Science and Techniques 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7724467
求助须知:如何正确求助?哪些是违规求助? 9277191
关于积分的说明 20120586
捐赠科研通 7301064
什么是DOI,文献DOI怎么找? 3301418
关于科研通互助平台的介绍 2454892
邀请新用户注册赠送积分活动 2309110