Department Oncology, Tianjin Medical University General Hospital, Tianjin 300052, China.
Radiotherapy Department, Tianjin Medical University General Hospital, Tianjin 300052, China.
Biomed Res Int. 2021 Sep 2;2021:5963868. doi: 10.1155/2021/5963868. eCollection 2021.
Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases.
The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature.
WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT.
We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.
非小细胞肺癌（NSCLC）是一种常见的恶性肿瘤，死亡率和预后都很差。放射治疗是 NSCLC 最常见的治疗方法之一，患者的放射敏感性会影响 NSCLC 的个体预后。然而，与放疗反应相关的预后标志物仍然有限。在这里，我们探索了与放疗敏感性相关的基因，并构建了 NSCLC 病例的预后预测模型。
从癌症基因组图谱数据库中获取有放疗记录的 NSCLC 样本，从基因表达综合数据库中获取 NSCLC 患者的 mRNA 表达谱来自 GSE30219 和 GSE31210 数据集。使用加权基因共表达网络分析（WGCNA）、单变量、最小绝对值收缩和选择算子（LASSO）、多变量 Cox 回归分析和列线图来识别和验证与放疗敏感性相关的特征。
WGCNA 显示 365 个基因与放疗反应显著相关。LASSO Cox 回归分析确定了 8 个基因，包括 FOLR3、SLC6A11、ALPP、IGFN1、KCNJ12、RPS4XP22、HIST1H2BH 和 BLACAT1。基于这 8 个基因的风险评分，低风险组的总生存率（OS）明显好于高风险组。此外，免疫浸润分析表明，低风险组与高风险组相比，单核细胞和激活的记忆 CD4 T 细胞的相对比例不同。风险评分与免疫检查点，包括 CTLA4、PDL1、LAG3 和 TIGIT 相关。
我们确定了 365 个可能与 NSCLC 患者放疗反应相关的基因。基于鉴定出的 8 个基因的风险评分模型可以预测 NSCLC 患者的预后。
