利用程序性细胞死亡模式预测口腔鳞状细胞癌的预后和治疗敏感性

Leveraging programmed cell death patterns to predict prognosis and therapeutic sensitivity in OSCC

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ORAL DISEASES

影响因子:2.9

分区:医学3区 / 牙科与口腔外科4区

发表日期:2025 Feb

作者: An Wang, Chi Zhang, Yuhan Wang, Pengfei Diao, Jie Cheng

DOI: 10.1111/odi.15139

keywords: chemotherapeutic response; immune landscape; immunotherapy response; oral squamous cell carcinoma; programmed cell death

摘要

程序性细胞死亡（PCD）与癌症发展及治疗结果之间的复杂关系日益受到重视。在本研究中，我们整合了12种PCD模式，构建了一种用于口腔鳞状细胞癌（OSCC）预后和治疗预测的新型生物标志物——细胞死亡指数（CDI）。通过单变量Cox回归、Kaplan-Meier生存分析和LASSO分析，建立了CDI模型。利用多变量Cox回归，结合临床病理参数建立了一个结合CDI的列线图。评估了CDI与免疫景观和治疗敏感性之间的关系。利用OSCC的单细胞RNA测序（scRNA-seq）数据，推断了不同细胞类型中的CDI基因及其在细胞分化轨迹中的表达变化。结果显示，十个选定的PCD相关基因组成了一个新的预后签名，对多个独立患者队列的预后预测表现稳健且优越。CDI与肿瘤浸润免疫细胞的丰度和免疫治疗效果呈负相关。此外，scRNA-seq分析表明，GSDMB、IL-1A、PRKAA2和SFRP1等基因主要在癌细胞中表达，参与细胞分化过程。我们的研究确立了CDI作为预测OSCC预后和治疗反应的强有力指标，并提示其可能在癌细胞分化中发挥作用。

Abstract

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.