A prognostic model built on amino acid metabolism patterns in HPV-associated head and neck squamous cell carcinoma

头颈部鳞状细胞癌 列线图 免疫组织化学 基因 生物 癌症研究 肿瘤科 头颈部癌 内科学 计算生物学 癌症 医学 免疫学 遗传学
作者
Fengyang Jing,Li Zhu,Jiwei Bai,Xuan Zhou,Lisha Sun,Heyu Zhang,Tiejun Li
出处
期刊:Archives of Oral Biology [Elsevier BV]
卷期号:163: 105975-105975
标识
DOI:10.1016/j.archoralbio.2024.105975
摘要

To compare amino acid metabolism patterns between HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) patients and identify key genes for a prognostic model. Utilizing the Cancer Genome Atlas dataset, we analyzed amino acid metabolism genes, differentiated genes between HPV statuses, and selected key genes via LASSO regression for the prognostic model. The model's gene expression was verified through immunohistochemistry in clinical samples. Functional enrichment and CIBERSORTx analyses explored biological functions, molecular mechanisms, and immune cell correlations. The model's prognostic capability was assessed using nomograms, calibration, and decision curve analysis. We identified 1157 key genes associated with amino acid metabolism in HNSCC and HPV status. The prognostic model, featuring genes like IQCN, SLC22A1, SYT12, and TLX3, highlighted functions in development, metabolism, and pathways related to receptors and enzymes. It significantly correlated with immune cell infiltration and outperformed traditional staging in prognosis prediction, despite immunohistochemistry results showing limited clinical identification of HPV-related HNSCC. Distinct amino acid metabolism patterns differentiate HPV-positive from negative HNSCC patients, underscoring the prognostic model's utility in predicting outcomes and guiding therapeutic strategies.

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
基质发布了新的文献求助30
1秒前
1秒前
健康的谷芹完成签到,获得积分10
1秒前
FashionBoy应助lixueao采纳,获得10
2秒前
3秒前
3秒前
3秒前
3秒前
op118no2发布了新的文献求助10
3秒前
3秒前
ding应助无语的无施采纳,获得10
4秒前
Conan发布了新的文献求助10
5秒前
5秒前
5秒前
Yong发布了新的文献求助10
6秒前
6秒前
善学以致用应助沉静丹寒采纳,获得10
6秒前
6秒前
6秒前
科目三应助SUN采纳,获得10
7秒前
7秒前
耍酷的镜子完成签到,获得积分10
7秒前
soo完成签到,获得积分20
7秒前
7秒前
lili发布了新的文献求助10
7秒前
8秒前
xdfn发布了新的文献求助10
8秒前
shancui发布了新的文献求助10
8秒前
8秒前
KMidly发布了新的文献求助10
8秒前
9秒前
9秒前
无极微光应助YaoHui采纳,获得20
9秒前
9秒前
10秒前
旱钮发布了新的文献求助10
10秒前
wanci应助nssm采纳,获得10
10秒前
在水一方应助YNWAlxh采纳,获得10
10秒前
Ava应助YNWAlxh采纳,获得10
10秒前
11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
Kinesiophobia : a new view of chronic pain behavior 2000
Burger's Medicinal Chemistry, Drug Discovery and Development, Volumes 1 - 8, 8 Volume Set, 8th Edition 1800
Cronologia da história de Macau 1600
Contemporary Debates in Epistemology (3rd Edition) 1000
International Arbitration Law and Practice 1000
文献PREDICTION EQUATIONS FOR SHIPS' TURNING CIRCLES或期刊Transactions of the North East Coast Institution of Engineers and Shipbuilders第95卷 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 计算机科学 化学工程 生物化学 物理 复合材料 内科学 催化作用 物理化学 光电子学 细胞生物学 基因 电极 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6154268
求助须知:如何正确求助?哪些是违规求助? 7982921
关于积分的说明 16586105
捐赠科研通 5264786
什么是DOI,文献DOI怎么找? 2809427
邀请新用户注册赠送积分活动 1789662
关于科研通互助平台的介绍 1657380