Zhang Hang, Zhao Xudong, Wang Jin, Ji Wenyue
Department of Otolaryngology Head and Neck Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
Front Oncol. 2021 Dec 16;11:683915. doi: 10.3389/fonc.2021.683915. eCollection 2021.
Our purpose was to develop and verify an immune-related signature for predicting recurrence risk of patients with laryngeal cancer.
RNA-seq data of 51 recurrence and 81 non-recurrence laryngeal cancer samples were downloaded from TCGA database, as the training set. Microarray data of 34 recurrence and 75 non-recurrence cancer samples were obtained from GEO dataset, as the validation set. Single factor cox regression was utilized to screen prognosis-related immune genes. After LASSO regression analysis, an immune-related signature was constructed. Recurrence free survival (RFS) between high- and low- recurrence risk patients was presented, followed by ROC. We also evaluated the correlation between immune infiltration and the signature using the CIBERSORT algorithm. The genes in the signature were validated in laryngeal cancer tissues by western blot or RT-qPCR. After RCN1 knockdown, migration and invasion of laryngeal cancer cells were investigated.
Totally, 43 prognosis-related immune genes were identified for laryngeal cancer. Among them, eight genes were used for constructing a prognostic signature. High risk group exhibited a higher recurrence risk than low risk group. The AUC for 1-year was separately 0.803 and 0.715 in the training and verification sets, suggesting its well efficacy for predicting the recurrence. Furthermore, this signature was closely related to distinct immune cell infiltration. RCN1, DNAJA2, LASP1 and IBSP were up-regulated in laryngeal cancer. RCN1 knockdown restrained migrated and invasive abilities of laryngeal cancer cells.
Our findings identify a reliable immune-related signature that can predict the recurrence risk of patients with laryngeal cancer.
我们的目的是开发并验证一种免疫相关特征,用于预测喉癌患者的复发风险。
从TCGA数据库下载51例复发和81例未复发喉癌样本的RNA测序数据作为训练集。从GEO数据集获取34例复发和75例未复发癌症样本的微阵列数据作为验证集。采用单因素cox回归筛选与预后相关的免疫基因。经过LASSO回归分析,构建免疫相关特征。呈现高复发风险和低复发风险患者之间的无复发生存期(RFS),随后进行ROC分析。我们还使用CIBERSORT算法评估免疫浸润与该特征之间的相关性。通过蛋白质免疫印迹或RT-qPCR在喉癌组织中验证该特征中的基因。在敲低RCN1后,研究喉癌细胞的迁移和侵袭情况。
总共为喉癌鉴定出43个与预后相关的免疫基因。其中,8个基因用于构建预后特征。高风险组的复发风险高于低风险组。训练集和验证集中1年的AUC分别为0.803和0.715,表明其在预测复发方面具有良好的效果。此外,该特征与不同的免疫细胞浸润密切相关。RCN1、DNAJA2、LASP1和IBSP在喉癌中上调。敲低RCN1可抑制喉癌细胞的迁移和侵袭能力。
我们的研究结果确定了一种可靠的免疫相关特征,可预测喉癌患者的复发风险。