A novel basement membrane-related gene signature for prognosis of lung adenocarcinomas

比例危险模型 腺癌 肿瘤科 基因 免疫系统 内科学 单变量 生存分析 多元统计 肺癌 多元分析 生物 单变量分析 医学 免疫学 癌症 遗传学 计算机科学 机器学习
作者
Zhenxing Zhang,Haoran Zhu,Xiaojun Wang,Shanan Lin,Chenjin Ruan,Qiang Wang
出处
期刊:Computers in Biology and Medicine [Elsevier]
卷期号:154: 106597-106597 被引量:27
标识
DOI:10.1016/j.compbiomed.2023.106597
摘要

Lung adenocarcinoma (LUAD) remains a global health concern with its poor prognosis and high mortality. Whether tumor cells invade through the basement membrane (BM) is the key factor to determine the prognosis of LUAD. This study aimed to identify the BM-related gene signatures to improve the overall prognosis of LUAD.A series of bioinformatics analyses were conducted based on TCGA and GEO datasets. Unsupervised consistent cluster analysis was performed, and 500 LUAD patients were assigned to two different groups according to expressions of 222 BM-related genes. The differentially expressed genes (DEGs) between the two clusters were identified, and Lasso regression, ROC curve, univariate and multivariate Cox regression analyses and enrichment analysis were conducted. Besides, ssGSEA, CIBERSORT and ESTIMATE algorithmwere were employed to understand the relationship between the tumor microenvironment (TME) and risk scores. Moreover, single cell clustering and trajectory analyses were performed to further understand the significance of BM-related genes. Finally, qRT-PCR was used to verify the prognosis model.A total of 31 prognostic BM-related genes were determined for LUAD, and a novel 17-mRNA prognostic model named BMsocre was successfully established to predict the overall survival of LUAD patients. The high BMscore group indicated worse prognosis. Seventeen DEGs were enriched mainly in metabolism, ECM-receptor interaction and immune response. In addition, the high-risk group showed higher TMB and lower immune score. The low-risk group had a better immunotherapeutic response where immune escape was less likely. The BMscore model was verified in our patient cohort. Furthermore, NELL2 was mainly expressed in clusters of T cells, and was identified to play a critical role in T-cell differentiation.A novel BMscore model was successfully established and might be effective for providing guidance to LUAD therapy.

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
沏茶关注了科研通微信公众号
刚刚
1秒前
奥特曼发布了新的文献求助10
1秒前
Kelly1426完成签到,获得积分10
1秒前
1秒前
1秒前
书晗发布了新的文献求助10
1秒前
天天快乐应助成就的觅风采纳,获得10
2秒前
B612小行星发布了新的文献求助10
2秒前
有魅力曼易完成签到,获得积分10
2秒前
叶轮机械完成签到,获得积分10
2秒前
嘻嘻发布了新的文献求助10
3秒前
恩雅完成签到,获得积分10
3秒前
Anyixx完成签到,获得积分10
3秒前
3秒前
hyc完成签到,获得积分10
3秒前
汉堡包应助西瓜汁采纳,获得10
3秒前
4秒前
tangyuan发布了新的文献求助10
4秒前
WZH完成签到,获得积分10
4秒前
软语完成签到,获得积分10
4秒前
小帅完成签到,获得积分10
5秒前
伶俐芷珊完成签到,获得积分10
5秒前
5秒前
科研通AI6应助山头虎采纳,获得100
5秒前
JTB完成签到,获得积分10
5秒前
5秒前
5秒前
丘比特应助了了采纳,获得10
5秒前
在水一方应助ying采纳,获得10
5秒前
5秒前
bkagyin应助有魅力的灭绝采纳,获得10
6秒前
yuxiao发布了新的文献求助10
6秒前
王能行完成签到,获得积分10
6秒前
王哲发布了新的文献求助10
6秒前
ding应助忆修采纳,获得10
6秒前
科研通AI6应助aaa采纳,获得10
6秒前
未来EBM发布了新的文献求助10
7秒前
7秒前
7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
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
化妆品原料学 1000
小学科学课程与教学 500
Study and Interlaboratory Validation of Simultaneous LC-MS/MS Method for Food Allergens Using Model Processed Foods 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 5645586
求助须知:如何正确求助?哪些是违规求助? 4769324
关于积分的说明 15030847
捐赠科研通 4804312
什么是DOI,文献DOI怎么找? 2568910
邀请新用户注册赠送积分活动 1526066
关于科研通互助平台的介绍 1485676