A Novel Cuprotosis-Related lncRNA Signature Effectively Predicts Prognosis in Glioma Patients

胶质瘤 比例危险模型 癌变 肿瘤科 长非编码RNA 生物 内科学 计算生物学 癌症 生物信息学 医学 基因 癌症研究 核糖核酸 遗传学
作者
Shuaishuai Wu,Augustine K. Ballah,Wenqiang Che,Xiangyu Wang
出处
期刊:Journal of Molecular Neuroscience [Springer Science+Business Media]
卷期号:73 (2-3): 185-204 被引量:2
标识
DOI:10.1007/s12031-023-02102-5
摘要

Cuprotosis is a novel and different cell death mechanism from the existing known ones that can be used to explore new approaches to treating cancer. Just like ferroptosis and pyroptosis, cuprotosis-related genes regulate various types of tumorigenesis, invasion, and metastasis. However, the relationship between cuprotosis-related long non-coding RNA (cuprotosis-related lncRNA) in glioma development and prognosis has not been investigated. We obtained relevant data from the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and published articles. First, we identified 365 cuprotosis-related lncRNAs based on 10 cuprotosis-related differential genes (|R2|> 0.4, p < 0.001). Then using Lasso and Cox regression analysis methods, 12 prognostic cuprotosis-related lncRNAs were obtained and constructed the CuLncSigi risk score formula. Our next step was to divide the tumor gliomas into two groups (high risk and low risk) based on the median risk score, and we found that patients in the high-risk group had a significantly worse prognosis. We used internal and external validation methods to simultaneously analyze and validate that the risk score model has good predictive power for patients with glioma. Next, we also performed enrichment analyses such as GSEA and aaGSEA and evaluated the relationship between immune-related drugs and tumor treatment. In conclusion, we successfully constructed a formula of cuprotosis-related lncRNAs with a powerful predictive function. More importantly, our study paves the way for exploring cuprotosis mechanisms in glioma occurrence and development and helps to find new relevant biomarkers for glioma early identification and diagnosis and to investigate new therapeutic approaches.

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
2秒前
cookiezhu01完成签到 ,获得积分10
3秒前
yqx完成签到 ,获得积分10
3秒前
7秒前
10秒前
xun完成签到,获得积分10
11秒前
等等发布了新的文献求助10
18秒前
22秒前
zaixiaPPL完成签到 ,获得积分10
25秒前
Jerry20184完成签到 ,获得积分10
26秒前
DungHoang完成签到,获得积分10
35秒前
诺亚方舟哇哈哈完成签到 ,获得积分0
35秒前
41秒前
Yan完成签到 ,获得积分10
52秒前
霸气剑通完成签到 ,获得积分10
52秒前
又又完成签到,获得积分0
53秒前
56秒前
雪山飞龙完成签到,获得积分10
57秒前
笨笨忘幽完成签到,获得积分0
58秒前
1分钟前
CLTTT完成签到,获得积分0
1分钟前
AX完成签到,获得积分10
1分钟前
Tong完成签到,获得积分0
1分钟前
1分钟前
顺利问玉完成签到 ,获得积分10
1分钟前
1分钟前
CGFHEMAN完成签到 ,获得积分10
1分钟前
puritan完成签到 ,获得积分10
1分钟前
LiShan完成签到 ,获得积分10
1分钟前
maun222完成签到,获得积分10
1分钟前
Hades完成签到 ,获得积分10
1分钟前
忧心的藏鸟完成签到 ,获得积分10
1分钟前
cy应助雪山飞龙采纳,获得10
1分钟前
沐雨微寒完成签到,获得积分10
1分钟前
单纯的忆安完成签到 ,获得积分10
1分钟前
1分钟前
陈陈完成签到 ,获得积分10
1分钟前
暴躁的冬菱完成签到,获得积分10
1分钟前
资格丘二完成签到 ,获得积分10
1分钟前
吃的饱饱呀完成签到 ,获得积分10
1分钟前
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
Elements of Propulsion: Gas Turbines and Rockets, Second Edition 1000
卤化钙钛矿人工突触的研究 1000
Engineering for calcareous sediments : proceedings of the International Conference on Calcareous Sediments, Perth 15-18 March 1988 / edited by R.J. Jewell, D.C. Andrews 1000
Wolffs Headache and Other Head Pain 9th Edition 1000
Continuing Syntax 1000
Signals, Systems, and Signal Processing 510
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6246669
求助须知:如何正确求助?哪些是违规求助? 8070096
关于积分的说明 16845843
捐赠科研通 5322862
什么是DOI,文献DOI怎么找? 2834283
邀请新用户注册赠送积分活动 1811763
关于科研通互助平台的介绍 1667516