Pan Shize, Meng Heng, Fan Tao, Hao Bo, Song Congkuan, Li Donghang, Li Ning, Geng Qing
Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China.
Front Genet. 2022 May 18;13:900159. doi: 10.3389/fgene.2022.900159. eCollection 2022.
Programmed cell death (PCD) is a process that regulates the homeostasis of cells in the body, and it plays an important role in tumor immunity. However, the expression profile and clinical characteristics of PCD-related genes remain unclear. In this study, we comprehensively analysed the PCD genes with the tumor microenvironment (TME), drug sensitivity, immunothearapy response, and evaluated their prognostic value through systematic bioinformatics methods.We identified 125 PCD-related regulatory factors, which were expressed differently in lung adenocarcinoma (LUAD) and normal lung tissues. 32 PCD related prognostic genes associated with LUAD were identified by univariate Cox analysis. 23 PCD-related gene signature was constructed, and all LUAD patients in the Cancer Genome Atlas (TCGA) dataset were stratified as low-risk or high-risk groups according to the risk score. This signature had a powerful prognostic value, which was validated in three independent data sets and clinical subtypes. Additionally, it has unique properties in TME. Further analysis showed that different risk groups have different immune cell infiltration, immune inflammation profile, immune pathways, and immune subtypes. In addition, the low-risk group had a better immunotherapy response with higher levels of multiple immune checkpoints and lower Tumor immune dysfunction and exclusion (TIDE) score, while the high-risk group was sensitive to multiple chemotherapeutic drugs because of its lower IC50. In short, this is the first model to predict the prognosis and immunological status of LUAD patients based on PCD-related genes. It may be used as a predictor of immunotherapy response to achieve customized treatment of LUAD.
程序性细胞死亡（PCD）是一种调节体内细胞稳态的过程，在肿瘤免疫中发挥着重要作用。然而，PCD相关基因的表达谱和临床特征仍不清楚。在本研究中，我们通过系统的生物信息学方法全面分析了PCD基因与肿瘤微环境（TME）、药物敏感性、免疫治疗反应的关系，并评估了它们的预后价值。我们鉴定出125个PCD相关调节因子，它们在肺腺癌（LUAD）和正常肺组织中的表达存在差异。通过单因素Cox分析确定了32个与LUAD相关的PCD预后基因。构建了23个PCD相关基因特征，并根据风险评分将癌症基因组图谱（TCGA）数据集中的所有LUAD患者分为低风险或高风险组。该特征具有强大的预后价值，在三个独立数据集和临床亚型中得到验证。此外，它在TME中具有独特的特性。进一步分析表明，不同风险组具有不同的免疫细胞浸润、免疫炎症谱、免疫途径和免疫亚型。此外，低风险组对免疫治疗反应更好，多个免疫检查点水平更高，肿瘤免疫功能障碍和排除（TIDE）评分更低，而高风险组由于其较低的半数抑制浓度（IC50）对多种化疗药物敏感。简而言之，这是第一个基于PCD相关基因预测LUAD患者预后和免疫状态的模型。它可作为免疫治疗反应的预测指标，以实现LUAD的个体化治疗。
