作者：贾雷，于新颖，徐丽娟，徐有青

单位：首都医科大学附属北京天坛医院 消化内科，北京 100070

Authors:  Jia Lei, Yu Xinying, Xu Lijuan, Xu Youqing

Unit:  Department of Gastroenterology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China

摘要：

目的 探索ⅡB期胰腺癌的免疫微环境特征,为胰腺癌的免疫治疗和预后预测提供理论依据。方法 从癌症基因组图谱(The Cancer Genome Atlas, TTGA)和基因表达综合数据库(Gene Expression Omnibus database, GEO)中下载Ⅱ B期胰腺癌患者的转录组数据,并通过R分析,鉴别免疫亚型及不同亚型的免疫反应、差异表达基因、免疫细胞和免疫调节分子的相互作用以及其对预后的影响。使用免疫细胞和检查点基因风险评分来评估Ⅱ B期胰腺癌患者的预后,并通过独立数据集进行验证。结果 鉴别出3种免疫亚型(M1-M3),表现出不同的免疫反应,代表3种不同的免疫微环境。3种免疫亚型在特异性免疫特性上有显著差异,并鉴定出在M2亚型(预后最差的亚型)中显著差异表达的12个基因。此外,M1亚型(预后最好的亚型)和M2亚型免疫细胞与检查点基因的相互作用不同,M1亚型的相互作用系数高于M2亚型。其中CD47、ICOS和LAG3处于相互作用网络中心,在不同免疫亚型中的相互作用强度不同。结论 免疫细胞与检查点基因作用紊乱可以导致免疫微环境的改变,进而影响胰腺癌患者的预后。

关键词：  胰腺癌; 生物信息学; 免疫微环境; 预后

Abstract：

Objective To provide a theoretical basis for immunotherapy and prognosis prediction of pancreatic adenocarcinoma (PAAD), we explored the immune microenvironment characteristics of stage ⅡB PAAD. Methods The transcriptome data of stage ⅡB PAAD patients were downloaded from The Cancer Genome Atlas (TTGA) and Gene Expression Omnibus database (GEO), and the R software was used to identify the immune subtype. Then the characteristics of different immune microenvironments were compared, including immune subtypes, expressed genes and the interaction between immune cells and checkpoint genes. We used immune cells and checkpoint gene risk scores to evaluate the prognosis of patients with stage ⅡB PAAD patients, and verified with independent data sets. Results We identified 3 immune subtypes (M1~M3), showing different immune responses, representing different immune microenvironments. The 3 subtypes were significantly different in terms of specific immune characteristics. In additional, 12 genes were identified related to M2 subtype (the worst prognosis subtype) in the microenvironment. More importantly, the interactions between immune cells and checkpoint genes in M1 subtype (the best prognosis subtype) and M2 subtype were different, and the interaction coefficient was higher in M1 subtype than M2 subtype. CD47, ICOS and LAG3 were at the center of the network, and the intensity of interaction was different in different immune subtypes. Conclusion The dysfunction of immune cells and checkpoint genes can lead to changes in immune microenvironment, thereby affecting the prognosis of patients with PAAD.

Key Words:  Pancreatic adenocarcinoma; Bioinformatics; Immune microenvironment; Prognosis