已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

CPLX2 is a novel tumor suppressor and improves the prognosis in glioma

作者
Yuanbing Chen,Jieling Ning,Long Shu,Lingzhi Wen,Bokang Yan,Zuli Wang,Junhong Hu,Xiaokun Zhou,Yongguang Tao,Xuewei Xia,Jun Huang
出处
期刊:Research Square
标识
DOI:10.21203/rs.3.rs-3359257/v1
摘要

Abstract Background: Glioma is a type of malignant cancer in the central nervous system. New predictive biomarkers have been investigated in recent years, but the clinical prognosis in glioma remains poor. The function of CPLX2 in glioma and the probable molecular mechanism of tumor suppression was the focus of this investigation. Methods: The glioma transcriptome profile is downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were performed to analyze the expression of CPLX2 in glioma. RT-qPCR was performed to detect the expression of CPLX2 in 68 glioma subjects, these patients who have been followed up. Kaplan-Meier survival analyses were done to evaluate the effect of CPLX2 on the prognosis of glioma patients. The CPLX2 knockdown and overexpressed cell lines were constructed to investigate the effect of CPLX2 on glioma. The cell growth, colony formation, and tumor formation in xenograft were performed. Results: The expression of CPLX2 was downregulated in glioma and negatively correlated to the grade of glioma. The higher expression of CPLX2 predicted a longer survival through the analysis of Kaplan-Meier survival curves. Overexpressed CPLX2 impaired tumorigenesis in glioma progression both in vivo and in vitro. Knocking down of CPLX2 promoted the proliferation of the glioma cells. The analysis of GSEA and co-expression analysis revealed that CPLX2 may affect the malignancy of glioma by regulating hypoxia and inflammation pathway. Conclusions: Our data indicated that CPLX2 functioned as a tumor suppressor and could be used as a potential prognostic marker in glioma.

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
刚刚
lpp完成签到 ,获得积分10
刚刚
1秒前
hhh完成签到 ,获得积分10
1秒前
燚槿完成签到 ,获得积分10
2秒前
lucky完成签到 ,获得积分10
2秒前
坚强素完成签到 ,获得积分10
2秒前
fufu完成签到,获得积分10
3秒前
Ryan完成签到 ,获得积分10
4秒前
4秒前
tomqas完成签到,获得积分20
5秒前
Orange应助llli采纳,获得10
5秒前
干净的灵萱完成签到 ,获得积分10
5秒前
秋千完成签到,获得积分10
5秒前
Ellen发布了新的文献求助10
5秒前
勤恳飞珍发布了新的文献求助10
5秒前
6秒前
xuan发布了新的文献求助10
6秒前
说好不吃肥肉的完成签到 ,获得积分10
6秒前
7秒前
团宝妞宝完成签到,获得积分10
9秒前
秋千发布了新的文献求助10
9秒前
9秒前
heekkll完成签到,获得积分10
10秒前
10秒前
阿南完成签到 ,获得积分0
11秒前
甜蜜的大象完成签到 ,获得积分10
11秒前
Ania99完成签到 ,获得积分10
12秒前
YZCN完成签到 ,获得积分10
12秒前
12秒前
13秒前
123完成签到 ,获得积分10
13秒前
linglingling完成签到 ,获得积分10
13秒前
13秒前
几两完成签到 ,获得积分10
14秒前
林七七发布了新的文献求助10
14秒前
lan__完成签到,获得积分10
14秒前
tomas完成签到,获得积分20
14秒前
填海完成签到,获得积分10
15秒前
蜗牛完成签到 ,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
Römisch-Germanische Forschungen 1000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Electric machines: theory, operating applications, and controls 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 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 7604501
求助须知:如何正确求助?哪些是违规求助? 9180493
关于积分的说明 19661576
捐赠科研通 7179682
什么是DOI,文献DOI怎么找? 3269423
关于科研通互助平台的介绍 2433381
邀请新用户注册赠送积分活动 2263445

今日热心研友

学术孤儿
4 30
Correna
2 10
yjh123
30
heekkll
2
注:热心度 = 本日应助数 + 本日被采纳获取积分÷10