程序性细胞死亡（PCD）与癌症发展和治疗结果之间错综复杂的关联越来越受到人们的重视。在这里，我们整合了 12 个 PCD 模式来构建一个新的生物标志物，细胞死亡指数 (CDI)，用于口腔鳞状细胞癌 (OSCC) 的预后和治疗预测。进行单变量 Cox 回归、Kaplan-Meier 生存和 LASSO 分析来构建CDI。通过多元 Cox 回归建立结合 CDI 和选定的临床病理学参数的列线图。估计了 CDI 与免疫景观和治疗敏感性之间的关联。 OSCC 的单细胞 RNA-seq 数据用于推断选定细胞类型中的 CDI 基因，并确定它们沿细胞分化轨迹的表达。十个选定的 PCD 基因衍生出 OSCC 的新预后特征。 CDI 和列线图的预测预后性能在多个独立患者队列中稳健且优越。 CDI 与肿瘤浸润免疫细胞丰度和免疫治疗结果呈负相关。此外，scRNA-seq 数据再分析显示，该特征中的 GSDMB、IL-1A、PRKAA2 和 SFRP1 主要在癌细胞中表达并参与细胞分化。我们的研究结果表明，CDI 是 OSCC 预后和治疗反应的新型强大预测因子并提出其可能参与癌细胞分化。© 2024 John Wiley

Intricate associations between programmed cell death (PCD) and cancer development and treatment outcomes have been increasingly appreciated. Here, we integrated 12 PCD patterns to construct a novel biomarker, cell death index (CDI), for oral squamous cell carcinoma (OSCC) prognostication and therapeutic prediction.Univariate Cox regression, Kaplan-Meier survival, and LASSO analyses were performed to construct the CDI. A nomogram combining CDI and selected clinicopathological parameters was established by multivariate Cox regression. The associations between CDI and immune landscape and therapeutic sensitivity were estimated. Single-cell RNA-seq data of OSCC was used to infer CDI genes in selected cell types and determine their expression along cell differentiation trajectory.Ten selected PCD genes derived a novel prognostic signature for OSCC. The predictive prognostic performance of CDI and nomogram was robust and superior across multiple independent patient cohorts. CDI was negatively associated with tumor-infiltrating immune cell abundance and immunotherapeutic outcomes. Moreover, scRNA-seq data reanalysis revealed that GSDMB, IL-1A, PRKAA2, and SFRP1 from this signature were primarily expressed in cancer cells and involved in cell differentiation.Our findings established CDI as a novel powerful predictor for prognosis and therapeutic response for OSCC and suggested its potential involvement in cancer cell differentiation.© 2024 John Wiley & Sons Ltd.