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 [Lippincott Williams & Wilkins]
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
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
刚刚
你长得很下饭所以完成签到,获得积分10
刚刚
马成双完成签到 ,获得积分10
刚刚
猫好好完成签到,获得积分10
刚刚
刚刚
在水一方应助纯真雁菱采纳,获得10
1秒前
科研通AI2S应助咯咯哒采纳,获得10
1秒前
Fengyun发布了新的文献求助10
1秒前
1秒前
1秒前
妮妮完成签到 ,获得积分10
2秒前
醉熏的似狮完成签到,获得积分20
2秒前
啾啾发布了新的文献求助10
2秒前
2秒前
KK发布了新的文献求助10
3秒前
南予安完成签到 ,获得积分10
3秒前
朴素青雪发布了新的文献求助10
3秒前
笑点低的静竹完成签到,获得积分10
3秒前
5秒前
zero37发布了新的文献求助30
5秒前
5秒前
5秒前
5秒前
斯文败类应助乔治采纳,获得10
5秒前
微风418完成签到,获得积分10
5秒前
CNX完成签到,获得积分10
6秒前
大力方盒完成签到,获得积分20
6秒前
6秒前
上官若男应助果果采纳,获得40
7秒前
跳跃的蝴蝶完成签到,获得积分10
7秒前
7秒前
123完成签到,获得积分10
7秒前
文曲星完成签到 ,获得积分10
8秒前
8秒前
熊大帅发布了新的文献求助10
8秒前
大方白枫发布了新的文献求助10
9秒前
自信寒蕾完成签到,获得积分10
9秒前
hys完成签到,获得积分10
9秒前
ding应助zyx采纳,获得10
9秒前
量子星尘发布了新的文献求助10
9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
Acute Mountain Sickness 2000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5068023
求助须知:如何正确求助?哪些是违规求助? 4289750
关于积分的说明 13365025
捐赠科研通 4109504
什么是DOI,文献DOI怎么找? 2250387
邀请新用户注册赠送积分活动 1255727
关于科研通互助平台的介绍 1188244