多种形式的程序性细胞死亡（PCD）共同调控肿瘤的发生、发展和转移。然而，目前缺乏对肺腺癌（LUAD）中不同类型PCD的综合分析。该研究总共涵盖了 1481 个与 13 种不同 PCD 模式调节相关的基因。十种机器学习算法被合并为 101 种组合，从中选择最佳算法来根据四个多中心队列的平均 C 指数制定人工智能衍生的预后特征。建立的最佳细胞死亡指数（CDI）模型成为总体生存的独立危险因素，表现出稳健且一致的性能。值得注意的是，与传统的临床变量和分子特征相比，CDI 表现出明显更高的准确性。它表现出比其他已发布模型更优越的性能。通过将 CDI 与相关临床特征相结合，开发了具有出色预测性能的列线图。 CDI评分较低的LUAD患者的免疫调节剂、TIDE评分和免疫评分较高，表明免疫治疗获益较好。更重要的是，我们发现抗原呈递的调节是PCD的关键机制。 SCG2是抑制LUAD恶性进展的关键分子。 CDI 作为增强 LUAD 患者临床结果的强大且有前途的工具具有巨大潜力。© 2024。作者，获得 Springer Nature Limited 的独家许可。

Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and metastasis of tumors. Nevertheless, a comprehensive analysis of the diverse types of PCD in lung adenocarcinoma (LUAD) is currently lacking. The study encompassed a total of 1481 genes associated with the regulation of 13 distinct PCD patterns. Ten machine learning algorithms were amalgamated into 101 combinations, from which the optimal algorithm was chosen to formulate an artificial intelligence-derived prognostic signature based on the average C-index across four multicenter cohorts. The established optimal cell death index (CDI) model emerged as an independent risk factor for overall survival, demonstrating robust and consistent performance. Notably, CDI exhibited significantly higher accuracy compared to traditional clinical variables and molecular features. It exhibited superior performance than other published models. By integrating CDI with relevant clinical features, a nomogram with excellent predictive performance was developed. LUAD patients with low CDI score had a higher immune modulators, TIDE scores and immune scores, indicating a better immunotherapy benefit. More importantly, we found that the regulation of antigen presentation is the crucial mechanism of PCD. SCG2 is a key molecule that inhibits the malignant progression of LUAD. CDI holds great potential as a robust and promising tool for enhancing clinical outcomes in patients with LUAD.© 2024. The Author(s), under exclusive licence to Springer Nature Limited.