肿瘤科
比例危险模型
队列
头颈部鳞状细胞癌
基因签名
内科学
列线图
弗雷明翰风险评分
接收机工作特性
间质细胞
生存分析
医学
癌症
头颈部癌
生物
疾病
基因
基因表达
遗传学
作者
Feinan He,Zhigang Chen,Wen‐Ting Deng,Ting Zhan,Xin Huang,Yiqing Zheng,Haidi Yang
标识
DOI:10.1016/j.intimp.2021.107789
摘要
Ferroptosis plays an important role across variable cancer types. However, few studies have focused on the prognostic patterns of ferroptosis-related genes in HNSCC. Cohorts with mRNA expression profiles, as well as corresponding clinical data of HNSCC patients from published studies, were collected and consolidated from public databases. We performed random survival forest analysis, Kaplan-Meier (KM) analysis of best combinations, and Cox regression analysis on 231 ferroptosis-related genes to construct a gene signature in the discovery cohort (TCGA), and later validated it in the validation cohort (GEO). The 7-gene signature was constructed to stratify patients into two groups according to their level of risk. Poorer overall survival (OS) was detected in the high risk (HRisk) group than in the low risk (LRisk) group in both the TCGA cohort (P < 0.0001, HR = 1.71, 95%CI:1.41-2.07) and the GEO cohort (P < 0.001, HR = 1.68, 95%CI:1.32-2.13). The risk score was identified as an independent predictive factor of OS in multivariate Cox regression analyses (HR > 1, P < 0.0001) in both cohorts. The signature's predictive capacity was proven by the time-dependent receiver operating characteristic (ROC) curve analysis and nomogram analysis. Functional enrichment analysis revealed that immunosuppressive pathways such as matrix extracellular space, and (transforming growth factor-β)TGF-β were enriched. The HRisk group was strongly associated with upregulation of both cancer-related pathways and stromal scores, while higher proportions of anti-tumor immune cells and immune signatures were enriched in the LRisk group. In conclusion, the signature based on 7 ferroptosis-related genes could be applicable for predicting the prognosis of HNSCC, indicating that ferroptosis may be a potential therapeutic target for HNSCC.
科研通智能强力驱动
Strongly Powered by AbleSci AI