清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

A Robust Metabolic Enzyme-Based Prognostic Signature for Head and Neck Squamous Cell Carcinoma

头颈部鳞状细胞癌 基因签名 列线图 癌症研究 癌变 肿瘤科 头颈部癌 生物 医学 癌症 内科学 生物信息学 计算生物学 基因 基因表达 遗传学
作者
Zizhao Mai,Huan Chen,Mingshu Huang,Xinyuan Zhao,Li Cui
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:11: 770241-770241 被引量:9
标识
DOI:10.3389/fonc.2021.770241
摘要

Background Head and neck squamous cell carcinoma (HNSCC) is still a menace to public wellbeing globally. However, the underlying molecular events influencing the carcinogenesis and prognosis of HNSCC are poorly known. Methods Gene expression profiles of The Cancer Genome Atlas (TCGA) HNSCC dataset and GSE37991 were downloaded from the TCGA database and gene expression omnibus, respectively. The common differentially expressed metabolic enzymes (DEMEs) between HNSCC tissues and normal controls were screened out. Then a DEME-based molecular signature and a clinically practical nomogram model were constructed and validated. Results A total of 23 commonly upregulated and 9 commonly downregulated DEMEs were identified in TCGA HNSCC and GSE37991. Gene ontology analyses of the common DEMEs revealed that alpha-amino acid metabolic process, glycosyl compound metabolic process, and cellular amino acid metabolic process were enriched. Based on the TCGA HNSCC cohort, we have built up a robust DEME-based prognostic signature including HPRT1 , PLOD2 , ASNS , TXNRD1 , CYP27B1 , and FUT6 for predicting the clinical outcome of HNSCC. Furthermore, this prognosis signature was successfully validated in another independent cohort GSE65858. Moreover, a potent prognostic signature-based nomogram model was constructed to provide personalized therapeutic guidance for treating HNSCC. In vitro experiment revealed that the knockdown of TXNRD1 suppressed malignant activities of HNSCC cells. Conclusion Our study has successfully developed a robust DEME-based signature for predicting the prognosis of HNSCC. Moreover, the nomogram model might provide useful guidance for the precision treatment of HNSCC.

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
白格完成签到,获得积分10
10秒前
兴奋平露完成签到,获得积分10
12秒前
wsr完成签到,获得积分10
15秒前
荣幸完成签到 ,获得积分10
16秒前
srwang_lakeeco完成签到,获得积分10
25秒前
aajhajkahna应助科研通管家采纳,获得10
32秒前
乐乐应助科研通管家采纳,获得10
32秒前
WSR完成签到,获得积分20
41秒前
changfox完成签到,获得积分10
57秒前
逍遥子完成签到,获得积分10
1分钟前
西山菩提完成签到,获得积分10
1分钟前
科研通AI6.2应助西山菩提采纳,获得30
1分钟前
Lucas应助旧同学采纳,获得30
1分钟前
JamesPei应助旧同学采纳,获得10
1分钟前
共享精神应助旧同学采纳,获得10
1分钟前
1分钟前
JamesPei应助旧同学采纳,获得10
1分钟前
李健的小迷弟应助旧同学采纳,获得10
1分钟前
田様应助旧同学采纳,获得10
1分钟前
Owen应助旧同学采纳,获得10
1分钟前
SciGPT应助旧同学采纳,获得10
1分钟前
科研通AI6.2应助旧同学采纳,获得10
1分钟前
cq_2完成签到,获得积分0
1分钟前
Jasper应助旧同学采纳,获得10
1分钟前
丘比特应助旧同学采纳,获得10
1分钟前
乐乐应助旧同学采纳,获得10
1分钟前
搜集达人应助旧同学采纳,获得10
1分钟前
赘婿应助旧同学采纳,获得10
1分钟前
彭于晏应助旧同学采纳,获得10
1分钟前
完美世界应助旧同学采纳,获得10
1分钟前
今后应助旧同学采纳,获得10
1分钟前
FashionBoy应助研友_Z1eDgZ采纳,获得10
1分钟前
五五帅完成签到 ,获得积分10
1分钟前
赘婿应助旧同学采纳,获得10
1分钟前
科研通AI2S应助旧同学采纳,获得10
1分钟前
Hello应助旧同学采纳,获得10
1分钟前
田様应助旧同学采纳,获得10
1分钟前
大模型应助旧同学采纳,获得10
1分钟前
科研通AI6.2应助旧同学采纳,获得10
1分钟前
Lucas应助旧同学采纳,获得10
1分钟前
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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 500
Auslegungsgeschichte 500
Transdermal drug delivery systems market size report 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
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 7640486
求助须知:如何正确求助?哪些是违规求助? 9213478
关于积分的说明 19763511
捐赠科研通 7206379
什么是DOI,文献DOI怎么找? 3276086
关于科研通互助平台的介绍 2437732
邀请新用户注册赠送积分活动 2273531