Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma

队列 肿瘤科 列线图 医学 免疫系统 免疫疗法 内科学 基因签名 基因 癌症 免疫学 基因表达 生物 遗传学
作者
Wenjun Zhu,Ziqi Chen,Min Fu,Qianxia Li,Xin Chen,Xiaoyu Li,Na Luo,Wilkin Tang,Yang Feng,Yiling Zhang,Yuanyuan Zhang,Xiaohong Peng,Guangyuan Hu
出处
期刊:Apoptosis [Springer Nature]
卷期号:29 (1-2): 169-190 被引量:4
标识
DOI:10.1007/s10495-023-01880-y
摘要

Abstract Cuprotosis, an emerging mode of cell death, has recently caught the attention of researchers worldwide. However, its impact on low-grade glioma (LGG) patients has not been fully explored. To gain a deeper insight into the relationship between cuprotosis and LGG patients’ prognosis, we conducted this study in which LGG patients were divided into two clusters based on the expression of 18 cuprotosis-related genes. We found that LGG patients in cluster A had better prognosis than those in cluster B. The two clusters also differed in terms of immune cell infiltration and biological functions. Moreover, we identified differentially expressed genes (DEGs) between the two clusters and developed a cuprotosis-related prognostic signature through the least absolute shrinkage and selection operator (LASSO) analysis in the TCGA training cohort. This signature divided LGG patients into high- and low-risk groups, with the high-risk group having significantly shorter overall survival (OS) time than the low-risk group. Its predictive reliability for prognosis in LGG patients was confirmed by the TCGA internal validation cohort, CGGA325 cohort and CGGA693 cohort. Additionally, a nomogram was used to predict the 1-, 3-, and 5-year OS rates of each patient. The analysis of immune checkpoints and tumor mutation burden (TMB) has revealed that individuals belonging to high-risk groups have a greater chance of benefiting from immunotherapy. Functional experiments confirmed that interfering with the signature gene TNFRSF11B inhibited LGG cell proliferation and migration. Overall, this study shed light on the importance of cuprotosis in LGG patient prognosis. The cuprotosis-related prognostic signature is a reliable predictor for patient outcomes and immunotherapeutic response and can help to develop new therapies for LGG.

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
Febridge完成签到,获得积分10
1秒前
王京华完成签到,获得积分10
2秒前
yznfly应助化简为繁采纳,获得30
3秒前
乐观海云完成签到 ,获得积分10
3秒前
陈咪咪完成签到,获得积分10
3秒前
Ares完成签到,获得积分10
4秒前
浮游应助imi采纳,获得10
5秒前
Jasper应助科研通管家采纳,获得10
7秒前
Greg应助科研通管家采纳,获得10
7秒前
科研通AI6应助科研通管家采纳,获得10
7秒前
所所应助科研通管家采纳,获得10
7秒前
科研通AI6应助科研通管家采纳,获得10
7秒前
Lucas应助科研通管家采纳,获得10
7秒前
科研通AI6应助科研通管家采纳,获得10
7秒前
科研通AI6应助科研通管家采纳,获得10
7秒前
ding应助科研通管家采纳,获得10
7秒前
科研通AI6应助科研通管家采纳,获得10
7秒前
7秒前
张庭豪完成签到,获得积分10
7秒前
9秒前
sdjjis完成签到 ,获得积分10
9秒前
Snail6完成签到,获得积分10
10秒前
研友_LX7zK8完成签到,获得积分10
11秒前
简奥斯汀完成签到 ,获得积分10
11秒前
wxp5294完成签到,获得积分10
11秒前
11秒前
寒冷丹雪完成签到,获得积分10
11秒前
缺缺完成签到,获得积分10
12秒前
牛仔完成签到 ,获得积分10
13秒前
14秒前
时有落花至完成签到,获得积分10
15秒前
可靠的千凝完成签到 ,获得积分10
15秒前
量子星尘发布了新的文献求助10
15秒前
清爽朋友完成签到,获得积分10
15秒前
QQ完成签到 ,获得积分10
16秒前
化简为繁完成签到,获得积分10
16秒前
金桔希子完成签到,获得积分10
17秒前
19秒前
青青完成签到,获得积分10
19秒前
量子星尘发布了新的文献求助10
19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
Digitizing Enlightenment: Digital Humanities and the Transformation of Eighteenth-Century Studies 1000
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Real World Research, 5th Edition 680
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 660
Handbook of Migration, International Relations and Security in Asia 555
Between high and low : a chronology of the early Hellenistic period 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5671607
求助须知:如何正确求助?哪些是违规求助? 4920377
关于积分的说明 15135208
捐赠科研通 4830460
什么是DOI,文献DOI怎么找? 2587117
邀请新用户注册赠送积分活动 1540692
关于科研通互助平台的介绍 1499071