Mao Miaobin, Ling Hongjian, Lin Yuping, Chen Yanling, Xu Benhua, Zheng Rong
The Graduate School, Fujian Medical University, Fuzhou, China.
Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.
Front Genet. 2021 Jul 14;12:702102. doi: 10.3389/fgene.2021.702102. eCollection 2021.
Pancreatic adenocarcinoma (PAAD) is a highly lethal and aggressive tumor with poor prognoses. The predictive capability of immune-related genes (IRGs) in PAAD has yet to be explored. We aimed to explore prognostic-related immune genes and develop a prediction model for indicating prognosis in PAAD.
The messenger (m)RNA expression profiles acquired from public databases were comprehensively integrated and differentially expressed genes were identified. Univariate analysis was utilized to identify IRGs that related to overall survival. Whereafter, a multigene signature in the Cancer Genome Atlas cohort was established based on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Moreover, a transcription factors regulatory network was constructed to reveal potential molecular processes in PAAD. PAAD datasets downloaded from the Gene Expression Omnibus database were applied for the validations. Finally, correlation analysis between the prognostic model and immunocyte infiltration was investigated.
Totally, 446 differentially expressed immune-related genes were screened in PAAD tissues and normal tissues, of which 43 IRGs were significantly related to the overall survival of PAAD patients. An immune-based prognostic model was developed, which contained eight IRGs. Univariate and multivariate Cox regression revealed that the risk score model was an independent prognostic indicator in PAAD (HR > 1, < 0.001). Besides, the sensitivity of the model was evaluated by the receiver operating characteristic curve analysis. Finally, immunocyte infiltration analysis revealed that the eight-gene signature possibly played a pivotal role in the status of the PAAD immune microenvironment.
A novel prognostic model based on immune genes may serve to characterize the immune microenvironment and provide a basis for PAAD immunotherapy.
胰腺腺癌（PAAD）是一种具有高度致死性和侵袭性的肿瘤，预后较差。免疫相关基因（IRGs）在PAAD中的预测能力尚未得到探索。我们旨在探索与预后相关的免疫基因，并建立一个预测模型来指示PAAD的预后。
综合整合从公共数据库获取的信使（m）RNA表达谱，并鉴定差异表达基因。利用单因素分析来鉴定与总生存期相关的IRGs。此后，基于最小绝对收缩和选择算子（LASSO）Cox回归分析在癌症基因组图谱队列中建立多基因特征。此外，构建转录因子调控网络以揭示PAAD中的潜在分子过程。从基因表达综合数据库下载的PAAD数据集用于验证。最后，研究预后模型与免疫细胞浸润之间的相关性分析。
共在PAAD组织和正常组织中筛选出446个差异表达的免疫相关基因，其中43个IRGs与PAAD患者的总生存期显著相关。开发了一种基于免疫的预后模型，该模型包含8个IRGs。单因素和多因素Cox回归显示，风险评分模型是PAAD中的独立预后指标（HR>1，<0.001）。此外，通过受试者工作特征曲线分析评估模型的敏感性。最后，免疫细胞浸润分析表明，八基因特征可能在PAAD免疫微环境状态中起关键作用。
一种基于免疫基因的新型预后模型可能有助于表征免疫微环境，并为PAAD免疫治疗提供依据。
