Telomere length-related signature as a novel biomarker of prognosis and immune response in non-small cell lung cancer.

肿瘤科 比例危险模型 肺癌 医学 内科学 接收机工作特性 生存分析 生物标志物 免疫系统 多元分析 免疫学 生物 生物化学
作者
Liu Xg,M Li,S-J Mai,R-J Cai
出处
期刊:DOAJ: Directory of Open Access Journals - DOAJ 卷期号:26 (4): 1304-1319 被引量:6
标识
DOI:10.26355/eurrev_202202_28124
摘要

Telomere length-related genes (TLRGs) play an important role in multiple tumors; however, there is a lack of systematic reporting about their relevance in non-small cell lung cancer (NSCLC). This study investigated the relation between TLRG gene expression and the immunotherapeutic response of patients with NSCLC.Differentially expressed TLRGs in tumor tissues and normal tissues were screened using Gene Expression Omnibus (GEO) datasets. A univariate Cox regression analysis was performed to identify the optimal prognosis-related genes. A prognostic risk model was constructed by using least absolute shrinkage, selection operator, and multivariate Cox regression analysis results. The model was then evaluated by a Kaplan-Meier analysis, functional enrichment annotation, and a receiver operating characteristic curve analysis; after which, it was validated in the TCGA dataset. The model was used to predict immunotherapeutic response and drug sensitivity.An 18-gene prognostic signature was developed and used to stratify NSCLC patients into a low- or high-risk group in GEO cohorts. Patients in the low-risk group had better survival possibilities than those in the high-risk group, and showed significantly higher overall survival times in the TCGA cohort. The risk score was identified as an independent prognostic factor, when compared with other clinical factors. ssGSEA scores showed that the risk model was mainly linked to cancer- and immune-related pathways. Importantly, the candidate risk model was linked to tumor immunity and predicted a patient's response to PDL-1 blockade immune therapy. Several potential drugs that might target this model were identified.This study provides broad molecular signatures that can be used in further functional and therapeutic studies of the telomere system, and also represents an integrated approach for characterizing key protein complexes when creating a prognosis and identifying new targets for cancer immunotherapy.

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
刚刚
刚刚
EKKO完成签到,获得积分10
1秒前
糖炒栗子完成签到,获得积分10
1秒前
刘凯发布了新的文献求助10
1秒前
皮皮完成签到 ,获得积分10
1秒前
至幸发布了新的文献求助10
1秒前
2秒前
2秒前
LZS完成签到,获得积分10
3秒前
小波发布了新的文献求助10
3秒前
科研通AI2S应助ji采纳,获得10
4秒前
落后寒凡发布了新的文献求助10
4秒前
快乐紫菜完成签到,获得积分10
5秒前
卡西法发布了新的文献求助10
5秒前
6秒前
Dore发布了新的文献求助10
6秒前
PengqianGuo完成签到,获得积分10
6秒前
6秒前
含蓄凡桃发布了新的文献求助10
6秒前
xxx1234发布了新的文献求助10
7秒前
无极微光应助橘子柚子采纳,获得20
7秒前
金鱼发布了新的文献求助10
7秒前
Gilbert发布了新的文献求助10
7秒前
互助应助满意日记本采纳,获得20
8秒前
乐乐应助Ljynb采纳,获得10
8秒前
隐形的凡阳完成签到,获得积分10
9秒前
斯文败类应助JiaJiaQing采纳,获得10
9秒前
10秒前
机灵安白完成签到,获得积分10
10秒前
10秒前
所所应助学术laji采纳,获得10
10秒前
11秒前
科研通AI6.1应助bleh采纳,获得10
11秒前
superxin发布了新的文献求助10
12秒前
不安忆寒完成签到,获得积分10
13秒前
13秒前
丘比特应助娜是五月天采纳,获得10
13秒前
13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
The Organometallic Chemistry of the Transition Metals 800
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 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 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 6439261
求助须知:如何正确求助?哪些是违规求助? 8253192
关于积分的说明 17565440
捐赠科研通 5497439
什么是DOI,文献DOI怎么找? 2899260
邀请新用户注册赠送积分活动 1875976
关于科研通互助平台的介绍 1716631