摘要
作为发病率和死亡率较高的恶性肿瘤，肺腺癌由于异质性和早期诊断不足，导致其预后差。本文从癌症基因组图谱数据库下载了576个肺腺癌患者样本的临床信息和转录组数据，通过免疫分析和加权基因共表达网络分析，从与肺腺癌相关的差异表达基因中识别出149个与基质评分、免疫评分及肿瘤纯度高度关联的肿瘤免疫浸润相关基因。在此基础上，基于生存分析和LASSO回归分析，3个与免疫浸润相关的肺腺癌驱动基因（IL16、P2RY13和HLA-DPB1）被识别，并用于构建风险评估模型。ROC曲线显示，该模型可较好地模拟肺腺癌患者一年、三年和五年的生存率，预测的AUC值分别为0.74、0.68和0.70。免疫分析显示，相较于高风险组，低风险组有更高的基质评分与免疫评分以及更低的肿瘤纯度，并且低风险组的免疫细胞富集程度显著高于高风险组。总之，这些结果有望为肺腺癌的临床研究提供理论帮助。
关键词： 肺腺癌；免疫浸润；肺腺癌驱动基因
Abstract
As a malignancy with high morbidity and mortality, lung adenocarcinoma (LUAD) has a poor prognosis due to its heterogeneity and inadequate early diagnosis. Clinical information and transcriptomic data of 576 LUAD patients were downloaded from the TCGA database, 149 immune-infiltrated genes highly associated with stromal score, immune score and tumor purity were extracted from the LUAD-related differentially expressed genes via performing immunoanalysis and weighted gene co-expression networkanalysis. On this basis, survival analysis and LASSO regression analysis were applied to these genes. Three LUAD driving genes (IL16, P2RY13 and HLA-DPB1) related to immune infiltration were obtained and subsequently transformed into a risk assessment model. ROC curve showed that the model could effectively simulate the survival rates of LUAD patients at one-year, three-year and five-year, and the predicted AUC results were 0.74, 0.68 and 0.70, respectively. Immunoanalysis displayed that the low-risk group got higher stromal and immune scores and lower tumor purity than those in the high-risk group, and the enrichment of immune cells in the low-risk group was significantly higher than that in the high-risk group. In summary, these results may provide theoretical guidance for the clinical studies of LUAD.
Key words： Lung adenocarcinoma; Immune infiltration; Lung adenocarcinoma driving gene
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