比例危险模型
接收机工作特性
肿瘤科
单变量分析
医学
内科学
生存分析
免疫疗法
单变量
免疫系统
基因
多元分析
癌症研究
生物
癌症
免疫学
多元统计
机器学习
计算机科学
遗传学
作者
Tian Lan,Siqi Ren,Huijun Hu,Ruixin Wang,Qian Chen,Fan Wu,Qiuping Xu,Yanyan Li,Lingyun Shao,Liansheng Wang,Xin Liu,Hanwen Cao,Jinsong Li
出处
期刊:Recent Patents on Anti-cancer Drug Discovery
[Bentham Science]
日期:2024-08-01
卷期号:19 (3): 354-372
标识
DOI:10.2174/1574892818666230602112042
摘要
Background: Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy. Objective: In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC). Methods: The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model’s capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model’s predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells. Results: A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis. Conclusion: We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.
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