Salivary metabolite signatures of oral cancer and leukoplakia

代谢组 代谢组学 唾液 代谢物 白斑 医学 接收机工作特性 癌症 内科学 病理 肿瘤科 生物信息学 生物
作者
Jie Wei,Guoxiang Xie,Zengtong Zhou,Shi Peng,Yunping Qiu,Xiaojiao Zheng,Tianlu Chen,Mingming Su,Aihua Zhao,Wei Jia
出处
期刊:International Journal of Cancer [Wiley]
卷期号:129 (9): 2207-2217 被引量:245
标识
DOI:10.1002/ijc.25881
摘要

Oral cancer, one of the six most common human cancers with an overall 5-year survival rate of <50%, is often not diagnosed until it has reached an advanced stage. The aim of the current study is to explore salivary metabolomics as a disease diagnostic and stratification tool for oral cancer and leukoplakia and evaluate the potential of salivary metabolome for detection of oral squamous cell carcinoma (OSCC). Saliva metabolite profiling for a group of 37 OSCC patients, 32 oral leukoplakia (OLK) patients and 34 healthy subjects was performed using ultraperformance liquid chromatography coupled with quadrupole/time-of-flight mass spectrometry in conjunction with multivariate statistical analysis. The OSCC, OLK and healthy control groups demonstrate characteristic salivary metabolic signatures. A panel of five salivary metabolites including γ-aminobutyric acid, phenylalanine, valine, n-eicosanoic acid and lactic acid were selected using OPLS-DA model with S-plot. The predictive power of each of the five salivary metabolites was evaluated by receiver operating characteristic curves for OSCC. Valine, lactic acid and phenylalanine in combination yielded satisfactory accuracy (0.89, 0.97), sensitivity (86.5% and 94.6%), specificity (82.4% and 84.4%) and positive predictive value (81.6% and 87.5%) in distinguishing OSCC from the controls or OLK, respectively. The utility of salivary metabolome diagnostics for oral cancer is successfully demonstrated in this study and these results suggest that metabolomics approach complements the clinical detection of OSCC and stratifies the two types of lesions, leading to an improved disease diagnosis and prognosis.
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
小子完成签到,获得积分20
刚刚
我能私信骂你吗应助临晨采纳,获得10
刚刚
脑洞疼应助嘻嘻嘻采纳,获得10
1秒前
mrzyfsci完成签到,获得积分10
1秒前
可可完成签到,获得积分10
2秒前
呆萌的忆山完成签到,获得积分10
2秒前
刘雪发布了新的文献求助10
2秒前
胜天半子完成签到,获得积分10
2秒前
Cheng9nine完成签到,获得积分10
3秒前
3秒前
binshier完成签到,获得积分10
4秒前
雨点完成签到,获得积分10
4秒前
小子发布了新的文献求助10
4秒前
疯狂的巨蟹完成签到,获得积分10
4秒前
4秒前
关耳完成签到,获得积分10
4秒前
李健的小迷弟应助开开采纳,获得10
5秒前
Shan5完成签到,获得积分10
5秒前
思源应助君临天下采纳,获得10
6秒前
jll完成签到 ,获得积分10
6秒前
大方逊完成签到,获得积分10
6秒前
ZQJ完成签到,获得积分10
6秒前
chenc应助绿色瓶子采纳,获得10
7秒前
7秒前
7秒前
传奇3应助稳重沁采纳,获得10
8秒前
赵童童童完成签到,获得积分10
8秒前
ZQJ发布了新的文献求助10
8秒前
9秒前
追寻听云完成签到,获得积分10
9秒前
droo完成签到,获得积分10
10秒前
宠仙完成签到,获得积分10
11秒前
12秒前
ww完成签到,获得积分10
12秒前
慈祥的元珊完成签到,获得积分10
12秒前
木木发布了新的文献求助10
13秒前
13秒前
CodeCraft应助今日赢耶采纳,获得10
13秒前
深情安青应助阿郑采纳,获得10
14秒前
稳重沁完成签到,获得积分20
14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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7750148
求助须知:如何正确求助?哪些是违规求助? 9297699
关于积分的说明 20242286
捐赠科研通 7331789
什么是DOI,文献DOI怎么找? 3309515
关于科研通互助平台的介绍 2461118
邀请新用户注册赠送积分活动 2321877