Wang Han, Wang Meng-Sen, Wang Ying, Huang Yue-Qing, Shi Jian-Ping, Ding Zhi-Liang, Wang Wen-Jie
Department of Oncology, Jining Cancer Hospital, Jining, Shandong 272011, P.R. China.
Department of Oncology, Jining First People's Hospital, Jining, Shandong 272011, P.R. China.
Oncol Lett. 2020 Nov;20(5):259. doi: 10.3892/ol.2020.12122. Epub 2020 Sep 18.
Lung cancer has the highest incidence and mortality rates of all cancers in China. Immune-related genes and immune infiltrating lymphocytes are involved in tumor growth, and in the past decade, immunotherapy has become increasingly important in the treatment of lung cancer. Using the package, differentially expressed genes and immune-related genes (DEIRGs) were identified in patients with lung adenocarcinoma (LUAD). Functional enrichment analysis of DEIRGs was performed using Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Survival-associated immune-related genes (IRGs) were selected using univariate Cox regression analysis and the prognostic model was assessed using multivariate Cox regression analysis. Overall, 273 DEIRGs were identified in LUAD, and KEGG pathway analysis of IRGs showed that 'cytokine-cytokine receptor interaction' was the most significantly enriched pathway. Furthermore, six survival associated IRGs were screened to establish a prognostic model; patients in the high risk score group had less favorable survival times, and the prognostic model was negatively associated with B cell infiltration. The present study established a prognostic model using analysis of survival-related immune-related genes, which were associated with B cell infiltration.
肺癌在中国所有癌症中发病率和死亡率最高。免疫相关基因和免疫浸润淋巴细胞参与肿瘤生长,在过去十年中,免疫疗法在肺癌治疗中变得越来越重要。使用该软件包,在肺腺癌(LUAD)患者中鉴定出差异表达基因和免疫相关基因(DEIRGs)。使用基因本体注释和京都基因与基因组百科全书(KEGG)通路分析对DEIRGs进行功能富集分析。使用单变量Cox回归分析选择生存相关免疫相关基因(IRGs),并使用多变量Cox回归分析评估预后模型。总体而言,在LUAD中鉴定出273个DEIRGs,IRGs的KEGG通路分析表明“细胞因子-细胞因子受体相互作用”是最显著富集的通路。此外,筛选出六个生存相关IRGs以建立预后模型;高风险评分组患者的生存时间较差,并且预后模型与B细胞浸润呈负相关。本研究通过分析与B细胞浸润相关的生存相关免疫相关基因建立了预后模型。