Development and validation of a transcriptomics-based gene signature to predict distant metastasis and guide induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma

鼻咽癌 肿瘤科 列线图 医学 转移 内科学 转录组 基因签名 单变量分析 化疗 队列 放射治疗 多元分析 癌症 基因 基因表达 生物 生物化学
作者
Sai‐Lan Liu,Xue-Song Sun,Qiuyan Chen,Zexian Liu,Lijuan Bian,Yuan Li,Bei-Bei Xiao,Zi-Jian Lu,Xiaoyun Li,Jin‐Jie Yan,Shumei Yan,Jianming Li,Jin‐Xin Bei,Hai‐Qiang Mai,Lin‐Quan Tang
出处
期刊:European Journal of Cancer [Elsevier BV]
卷期号:163: 26-34 被引量:19
标识
DOI:10.1016/j.ejca.2021.12.017
摘要

Metastasis is the primary cause of treatment failure in nasopharyngeal carcinoma (NPC); however, the current tumour-node-metastasis staging system has limitations in predicting distant metastasis and guiding induction chemotherapy (IC) application. Here, we established a transcriptomics-based gene signature to assess the risk of distant metastasis and guide IC in locoregionally advanced NPC.Transcriptome sequencing was performed on NPC biopsy samples from 12 pairs of patients with different metastasis risks. Bioinformatics and qPCR were used to identify differentially expressed genes (DEGs), while univariate and multivariate analyses were used to select prognostic indicators for the gene signature. A signature-based nomogram was established in a training cohort (n = 191) and validated in an external cohort (n = 263).Eleven DEGs were identified between metastatic and non-metastatic NPC. Four of these (AK4, CPAMD8, DDAH1 and CRTR1) were used to create a gene signature that effectively categorised patients into low- and high-risk metastasis groups (training: 91.1 versus 70.4%, p < 0.0001, C-index = 0.752; validation: 88.4 versus 73.9%, p = 0.00057, C-index = 0.741). IC with concurrent chemoradiotherapy (CCRT) improved distant metastasis-free survival in low-risk patients (94.4 versus 85.0%, p = 0.043), whereas patients in the high-risk group did not benefit from IC (72.6 versus 74.9%, p = 0.946).Our transcriptomics-based gene signature was able to reliably predict metastasis in locoregionally advanced NPC and could be used to identify candidates that could benefit from IC + CCRT.
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
刚刚
简单发布了新的文献求助10
1秒前
Lbw完成签到,获得积分10
2秒前
Ww发布了新的文献求助10
3秒前
天天快乐应助王浩喆采纳,获得10
3秒前
ShyLibra应助任旭东采纳,获得30
4秒前
ShyLibra应助任旭东采纳,获得30
4秒前
ShyLibra应助任旭东采纳,获得30
4秒前
yjh123应助任旭东采纳,获得30
4秒前
丘比特应助任旭东采纳,获得30
5秒前
情怀应助任旭东采纳,获得10
5秒前
yjh123应助任旭东采纳,获得30
5秒前
小二郎应助任旭东采纳,获得30
5秒前
Kityee应助任旭东采纳,获得30
5秒前
yjh123应助任旭东采纳,获得30
5秒前
6秒前
6秒前
LLL发布了新的文献求助10
7秒前
7秒前
小潘完成签到 ,获得积分10
8秒前
寻雯静应助wish采纳,获得10
8秒前
作业对不起完成签到,获得积分10
9秒前
啵啵应助Yolotto3采纳,获得10
9秒前
10秒前
zxx完成签到 ,获得积分0
11秒前
1assss发布了新的文献求助10
11秒前
兴十一应助Gwen采纳,获得20
12秒前
钦白AZURE完成签到,获得积分10
14秒前
逃不开夏天完成签到,获得积分10
14秒前
guojingjing发布了新的文献求助30
15秒前
WEI发布了新的文献求助10
16秒前
weifengzhong发布了新的文献求助20
16秒前
并不浓妆的狸猫完成签到,获得积分10
17秒前
17秒前
huau完成签到,获得积分10
18秒前
19秒前
19秒前
20秒前
万能图书馆应助dadada采纳,获得10
21秒前
二橦发布了新的文献求助10
21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
Organic Reactions, Volume 116 1500
VALIDATION OF THE TAYLOR, ALAMEL AND VPSC MODELS FOR PLASTIC ANISOTROPY MODELING OF SHEET METALS 1000
Geist der Kunst und Kultur 1000
Middleton's Allergy Principles and Practice 10th Edition(Middleton's Allergy 2-Volume Set, 10th Edition) 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
日本現代怪異事典 副読本 700
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7403385
求助须知:如何正确求助?哪些是违规求助? 9008033
关于积分的说明 19180702
捐赠科研通 7036983
什么是DOI,文献DOI怎么找? 3231578
关于科研通互助平台的介绍 2393827
邀请新用户注册赠送积分活动 2213331