Zhou Yuan, Tang Lu, Chen Yuqiao, Zhang Youyu, Zhuang Wei
Department of Thoracic Surgery, Xiangya Hospital of Central South University, Changsha, China.
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University,Changsha, China.
Front Cell Dev Biol. 2021 Dec 21;9:797984. doi: 10.3389/fcell.2021.797984. eCollection 2021.
Lung cancer, especially lung adenocarcinoma (LUAD) with high incidence, seriously endangers human life. The immune microenvironment is one of the malignant foundations of LUAD, but its impact at the molecular level is incompletely understood. A total of 34 LUAD samples from Xiangya Hospital were collected for immune oncology (IO) profiling. Univariate Cox analysis was performed to profile prognostic immune genes based on our immune panel sequencing data. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to construct a risk signature. The cut-off threshold of risk score was determined using X-tile software. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves were employed to examine the performance of this risk signature for predicting prognosis. The immune infiltration was estimated using a single-sample gene set enrichment analysis (ssGSEA) algorithm. Thirty-seven immune genes were profiled to be significantly correlated with the progression-free survival (PFS) in our cohort. Among them, , , , , , and were selected to construct a risk signature. Patients with a higher risk score had a significantly shorter PFS ( = 0.007). Time-dependent ROC curves indicated that our risk signature had a robust performance in accurately predicting survival. Specifically, the 6-, 12-, and 18-month area under curve (AUC) was 0.800, 0.932, and 0.912, respectively. Furthermore, the risk signature was positively related to N stage, tumor stage, and tumor malignancy. These results were validated using two external cohorts. Finally, the risk signature was ignificantly and uniquely correlated with abundance of neutrophil. Our study revealed an immune panel-based signature that could predict the prognosis of LUAD patients and was associated with the infiltration of neutrophils.
肺癌，尤其是高发病率的肺腺癌（LUAD），严重危及人类生命。免疫微环境是LUAD的恶性基础之一，但其在分子水平上的影响尚未完全了解。收集了来自湘雅医院的34例LUAD样本进行免疫肿瘤学（IO）分析。基于我们的免疫组测序数据进行单变量Cox分析以分析预后免疫基因。应用最小绝对收缩和选择算子（LASSO）算法构建风险特征。使用X-tile软件确定风险评分的截止阈值。采用Kaplan-Meier生存曲线和受试者工作特征（ROC）曲线来检验该风险特征预测预后的性能。使用单样本基因集富集分析（ssGSEA）算法估计免疫浸润。在我们的队列中，有37个免疫基因被分析与无进展生存期（PFS）显著相关。其中，选择了 、 、 、 、 、 和 来构建风险特征。风险评分较高的患者PFS显著缩短（ = 0.007）。时间依赖性ROC曲线表明我们的风险特征在准确预测生存方面具有强大的性能。具体而言，6个月、12个月和18个月的曲线下面积（AUC）分别为0.800、0.932和0.912。此外，风险特征与N分期、肿瘤分期和肿瘤恶性程度呈正相关。这些结果在两个外部队列中得到了验证。最后，风险特征与中性粒细胞的丰度显著且独特相关。我们的研究揭示了一种基于免疫组的特征，它可以预测LUAD患者的预后，并与中性粒细胞的浸润有关。
