Prognostic necroptosis-related gene signature aids immunotherapy in lung adenocarcinoma

坏死性下垂 免疫疗法 基因签名 医学 列线图 肿瘤科 癌症研究 肺癌 比例危险模型 腺癌 生存分析 癌症 基因 内科学 生物 基因表达 程序性细胞死亡 细胞凋亡 生物化学
作者
Yuqi Song,Jinming Zhang,Linan Fang,Wei Liu
出处
期刊:Frontiers in Genetics [Frontiers Media]
卷期号:13 被引量:4
标识
DOI:10.3389/fgene.2022.1027741
摘要

Background: Necroptosis is a phenomenon of cellular necrosis resulting from cell membrane rupture by the corresponding activation of Receptor Interacting Protein Kinase 3 (RIPK3) and Mixed Lineage Kinase domain-Like protein (MLKL) under programmed regulation. It is reported that necroptosis is closely related to the development of tumors, but the prognostic role and biological function of necroptosis in lung adenocarcinoma (LUAD), the most important cause of cancer-related deaths, is still obscure. Methods: In this study, we constructed a prognostic Necroptosis-related gene signature based on the RNA transcription data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as well as the corresponding clinical information. Kaplan-Meier analysis, receiver operating characteristic (ROC), and Cox regression were made to validate and evaluate the model. We analyzed the immune landscape in LUAD and the relationship between the signature and immunotherapy regimens. Results: Five genes (RIPK3, MLKL, TLR2, TNFRSF1A, and ALDH2) were used to construct the prognostic signature, and patients were divided into high and low-risk groups in line with the risk score. Cox regression showed that risk score was an independent prognostic factor. Nomogram was created for predicting the survival rate of LUAD patients. Patients in high and low-risk groups have different tumor purity, tumor immunogenicity, and different sensitivity to common antitumor drugs. Conclusion: Our results highlight the association of necroptosis with LUAD and its potential use in guiding immunotherapy.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
wujuan1606完成签到 ,获得积分10
1秒前
废羊羊完成签到 ,获得积分10
1秒前
小魏哥完成签到,获得积分10
1秒前
allzzwell完成签到 ,获得积分10
2秒前
沛沛完成签到,获得积分10
2秒前
英勇雅琴完成签到,获得积分10
2秒前
3秒前
小太阳红红火火完成签到,获得积分10
3秒前
加载文献别卡了完成签到,获得积分10
4秒前
傻傻的咖啡豆完成签到,获得积分10
4秒前
沉默的尔槐完成签到,获得积分10
4秒前
孙皓然完成签到 ,获得积分10
4秒前
5秒前
小超人到海底捉虫完成签到,获得积分10
6秒前
LZL完成签到 ,获得积分10
7秒前
窝窝头完成签到,获得积分10
7秒前
8秒前
薄荷味完成签到 ,获得积分10
9秒前
moxisi完成签到,获得积分10
9秒前
9秒前
12秒前
XieQinxie发布了新的文献求助10
12秒前
zyc1111111应助司空蓝采纳,获得20
14秒前
情怀应助111采纳,获得10
14秒前
美海与鱼完成签到,获得积分10
14秒前
顺顺利利完成签到,获得积分10
14秒前
111完成签到,获得积分10
14秒前
15秒前
典雅葶完成签到 ,获得积分10
15秒前
斯奈克发布了新的文献求助10
15秒前
POWER完成签到,获得积分10
18秒前
11完成签到,获得积分20
18秒前
Hello应助pufanlg采纳,获得10
18秒前
美丽凡阳完成签到,获得积分10
19秒前
科研顺利完成签到,获得积分10
19秒前
撑住完成签到,获得积分10
20秒前
聆琳完成签到 ,获得积分10
20秒前
汤圆完成签到,获得积分10
21秒前
Spiderman完成签到,获得积分10
21秒前
22秒前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Social Research Methods (4th Edition) by Maggie Walter (2019) 2390
A new approach to the extrapolation of accelerated life test data 1000
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 390
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 360
Atlas of Interventional Pain Management 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4008933
求助须知:如何正确求助?哪些是违规求助? 3548669
关于积分的说明 11299538
捐赠科研通 3283228
什么是DOI,文献DOI怎么找? 1810311
邀请新用户注册赠送积分活动 886034
科研通“疑难数据库(出版商)”最低求助积分说明 811259