Identification of an EMT-related Gene Signature Predicting Recurrence in Stage II/III Colorectal Cancer

医学 列线图 肿瘤科 比例危险模型 结直肠癌 内科学 基因签名 阶段(地层学) 队列 癌症 基因 基因表达 生物 生物化学 古生物学 化学
作者
Haoyu Ren,Florian Bösch,Elise Pretzsch,Sven Jacob,C. Benedikt Westphalen,Julian Walter Holch,Jens Werner,Martin K. Angele
出处
期刊:Annals of Surgery [Ovid Technologies (Wolters Kluwer)]
卷期号:276 (5): 897-904 被引量:10
标识
DOI:10.1097/sla.0000000000005644
摘要

To identify a prognostic significant gene signature for predicting colorectal cancer (CRC) recurrence.Traditional prognostic risk assessment in stage II/III CRC patients remains controversial. Epithelial-mesenchymal transition is thought to be closely related to the malignant progression of tumors. Thus, it is promising to establish a prognostic model based on epithelial-mesenchymal transition-related gene (ERG) signature.We retrospectively analyzed transcriptome profiles and clinical information of 1780 stage II/III CRC patients from 15 public datasets. Coefficient variant analysis was used to select reference genes for normalizing gene expression levels. Univariate, LASSO, and multivariate Cox regression analyses were combined to develop the ERG signature predicting disease-free survival (DFS). The patients were divided into high-risk and low-risk based on the ERG signature recurrence risk score. The survival analysis was performed in different CRC cohorts.The proposed ERG signature contained 7 cancer-related ERGs and 3 reference genes. The ERG signature recurrence risk score was prognostically relevant in all cohorts ( P <0.05) and proved as an independent prognostic factor in the training cohort. In the pooled cohort, high-risk CRC patients exhibited worse DFS ( P <0.0001) and overall survival ( P =0.0058) than low-risk patients. The predictive performance of the ERG signature was superior to Oncotype DX colon cancer. An integrated decision tree and nomogram were developed to improve prognosis evaluation.The identified ERG signature is a promising and powerful biomarker predicting recurrence in CRC patients. Moreover, the presented ERG signature might help to stratify patients according to their tumor biology and contribute to personalized treatment.
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
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
饭神仙鱼完成签到,获得积分10
1秒前
KBYer发布了新的文献求助20
1秒前
Jzhang应助tmpstlml采纳,获得10
2秒前
YoYo发布了新的文献求助10
2秒前
豌豆发布了新的文献求助10
4秒前
5秒前
言叶完成签到,获得积分10
5秒前
6秒前
CipherSage应助清新的冷松采纳,获得10
6秒前
JamesPei应助Poyd采纳,获得10
7秒前
科目三应助药学牛马采纳,获得10
8秒前
lixm发布了新的文献求助10
9秒前
NAA完成签到,获得积分10
10秒前
10秒前
tao_blue完成签到,获得积分10
10秒前
荔枝完成签到,获得积分20
10秒前
10秒前
11秒前
许多知识完成签到,获得积分10
11秒前
缓慢的战斗机完成签到,获得积分20
12秒前
圣晟胜发布了新的文献求助10
12秒前
科研通AI5应助nextconnie采纳,获得10
13秒前
陈朝旧迹完成签到,获得积分10
13秒前
无花果应助虚心海燕采纳,获得10
14秒前
sun发布了新的文献求助30
15秒前
15秒前
KBYer完成签到,获得积分10
15秒前
FashionBoy应助阳阳采纳,获得10
15秒前
许多知识发布了新的文献求助10
16秒前
苏源智完成签到,获得积分10
16秒前
Andy完成签到 ,获得积分10
18秒前
明理晓霜发布了新的文献求助10
20秒前
ZHANGMANLI0422关注了科研通微信公众号
20秒前
M先生发布了新的文献求助30
21秒前
FashionBoy应助许多知识采纳,获得10
22秒前
Poyd完成签到,获得积分10
25秒前
25秒前
故意的傲玉应助tao_blue采纳,获得10
26秒前
26秒前
kid1912完成签到,获得积分0
26秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
Luis Lacasa - Sobre esto y aquello 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527998
求助须知:如何正确求助?哪些是违规求助? 3108225
关于积分的说明 9288086
捐赠科研通 2805889
什么是DOI,文献DOI怎么找? 1540195
邀请新用户注册赠送积分活动 716950
科研通“疑难数据库(出版商)”最低求助积分说明 709849