利用编程细胞死亡模式来预测OSCC的预后和治疗敏感性
An Wang1,2, Chi Zhang1,2, Yuhan Wang1,2
1Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
Oral diseases
|September 24, 2024
概括
一个新的细胞死亡指数 (CDI) 生物标志物预测了口腔状细胞癌 (OSCC) 的结果. 该指数有助于预后和治疗预测,提供有关癌症细胞分化的见解.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 生物标志物发现发现
背景情况:
- 编程细胞死亡 (PCD) 在癌症的发展和治疗反应中起着关键作用.
- 了解这些复杂的关联对于改善口腔状细胞癌 (OSCC) 患者的治疗结果至关重要.
研究的目的:
- 通过整合多种编程细胞死亡模式来开发OSCC的新型预后和预测生物标志物.
- 建立细胞死亡指数 (CDI) 来评估患者的预后,并预测OSCC的治疗反应.
主要方法:
- 在12个PCD模式上使用单变Cox回归,Kaplan-Meier存活率和LASSO分析构建了CDI.
- 通过多变量考克斯回归,开发了一种将CDI与临床病理参数结合在一起的名图.
- 使用scRNA-seq数据分析了CDI,免疫格局和治疗敏感性之间的关联.
主要成果:
- 一个包括10个选定的PCD基因的预后签名是OSCC的衍生.
- 在独立的患者队列中,CDI和nomogram表现出强大而优异的预后性能.
- CDI显示与瘤透免疫细胞和免疫治疗结果的负相关性,其中关键基因参与细胞分化.
结论:
- 细胞死亡指数 (CDI) 已被确立为OSCC预后和治疗反应的强大预测指标.
- 这项研究表明CDI在癌细胞分化过程中的潜在作用.
- 在OSCC治疗中,CDI为个性化医疗方法提供了一个新的工具.
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