LncRNA expression signature identified using genome-wide transcriptomic profiling to predict lymph node metastasis in patients with stage T1 and T2 gastric cancer

医学 转移 长非编码RNA 肿瘤科 生物信息学 癌症 内科学 计算生物学 生物信息学 生物 基因 核糖核酸 生物化学
作者
Zhebin Dong,Hanting Xiang,Hengmiao Wu,Zheng-Wei Chen,Sangsang Chen,Yicheng He,Hong Li,Weiming Yu,Chao Liang
出处
期刊:Research Square - Research Square
标识
DOI:10.21203/rs.3.rs-2618696/v1
摘要

Abstract Background: Lymph node (LN) status is vital to indicate and evaluate the curative potential of relatively early gastric cancer (GC; T1–T2) treatment (endoscopic or surgery). Currently, there is a lack of robust and convenient methods to identify such metastasis before therapeutic decision-making; therefore, there is an urgent need to identify biomarkers that could aid the identification of patients with LN metastasis. Methods: Genome-wide expression profiles of long noncoding RNA (lncRNA) in primary T1 gastric cancer data from The Cancer Genome Atlas (TCGA) was used to identify an lncRNA‑expression signature capable of detecting LN metastasis of GC, and establish a 10-lncRNA risk‑prediction model based on deap learning. The performance of the lncRNA panel in diagnosing LN metastasis was evaluated using both in silico and clinical validation methods. In silico validation was conducted using TCGA and Asian Cancer Research Group (ACRG) datasets. Clinical validation was performed on T1 and T2 patients, and the panel's efficacy was compared with that of traditional tumor markers and computed tomography (CT) scans. Results: Profiling of genome-wide RNA expression identified a panel of lncRNA to predict LN metastasis in T1 stage gastric cancer (area under the curve (AUC) = 0.961). A 10-lncRNA risk-prediction model was then constructed, which was validated successfully in T1 and T2 datasets (TCGA, AUC = 0.852; ACRG, AUC = 0.834). Thereafter, the clinical performance of the lncRNA panel was validated in clinical cohorts (T1, AUC = 0.812; T2, AUC = 0.805; T1+T2, AUC = 0.764). Notably, the 10-lncRNA panel demonstrated significantly better performance compared with CT and conventional tumor markers (carcinoembryonic antigen and carbohydrate antigen 19-9). Conclusions: The novel 10-lncRNA could diagnose LN metastasis robustly in relatively early gastric cancer (T1–T2), with promising clinical potential.
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
大幅提高文件上传限制,最高150M (2024-4-1)

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
MoodMeed完成签到,获得积分10
2秒前
2秒前
18135175733完成签到 ,获得积分10
4秒前
新野完成签到,获得积分10
8秒前
12秒前
16秒前
yqhide完成签到,获得积分10
17秒前
二娃发布了新的文献求助10
18秒前
20秒前
hakuna_matata完成签到 ,获得积分10
21秒前
木木木完成签到,获得积分10
22秒前
jeronimo完成签到,获得积分10
23秒前
领导范儿应助陈陈陈采纳,获得10
26秒前
Murray完成签到,获得积分10
28秒前
小居很哇塞完成签到,获得积分10
29秒前
小雅完成签到 ,获得积分10
30秒前
32秒前
36秒前
peike完成签到,获得积分10
37秒前
陈陈陈发布了新的文献求助10
41秒前
wickedzz发布了新的文献求助10
41秒前
没那么简单完成签到,获得积分20
41秒前
42秒前
ywsss完成签到,获得积分10
43秒前
韭菜发布了新的文献求助10
44秒前
45秒前
Jennifer完成签到 ,获得积分10
48秒前
xu完成签到 ,获得积分10
56秒前
陈陈陈完成签到,获得积分10
56秒前
外向的凝阳完成签到 ,获得积分10
1分钟前
使命完成签到 ,获得积分10
1分钟前
为你等候完成签到,获得积分10
1分钟前
嘟嘟豆806完成签到 ,获得积分10
1分钟前
鲜于白玉完成签到 ,获得积分10
1分钟前
找文献呢完成签到,获得积分10
1分钟前
Kamal完成签到,获得积分10
1分钟前
糟糕的树叶完成签到 ,获得积分10
1分钟前
谨慎秋寒完成签到 ,获得积分20
1分钟前
摆哥完成签到,获得积分10
1分钟前
1分钟前
高分求助中
Sustainable Land Management: Strategies to Cope with the Marginalisation of Agriculture 1000
Corrosion and Oxygen Control 600
Yaws' Handbook of Antoine coefficients for vapor pressure 500
Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields 500
Heterocyclic Stilbene and Bibenzyl Derivatives in Liverworts: Distribution, Structures, Total Synthesis and Biological Activity 500
重庆市新能源汽车产业大数据招商指南(两链两图两池两库两平台两清单两报告) 400
Division and square root. Digit-recurrence algorithms and implementations 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 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 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2551338
求助须知:如何正确求助?哪些是违规求助? 2177614
关于积分的说明 5609591
捐赠科研通 1898547
什么是DOI,文献DOI怎么找? 947853
版权声明 565519
科研通“疑难数据库(出版商)”最低求助积分说明 504201