基于生物信息学方法鼻咽癌预后和免疫相关细胞轨迹差异表达基因的筛选  

Screening of differentially expressed genes of cell locus related to the prognosis and immunity of nasopharyngeal carcinoma based on bioinformatics

作　　者：问静[1] 吴婧[1] 罗燕红 樊琰鑫 姜雪松[1] Wen Jing;Wu Jing;Luo Yanhong;Fan Yanxin;Jiang Xuesong(Department of Radiotion Oncology,Jiangsu Cancer Hospital&Jiangsu Institute of Cancer Research&The Affiliated Cancer Hospital of Nanjing Medical University,Nanjing 210009,China)

机构地区：[1]江苏省肿瘤医院、江苏省肿瘤防治研究所、南京医科大学附属肿瘤医院肿瘤放射治疗科,南京210009

出　　处：《肿瘤研究与临床》2024年第4期268-274,共7页Cancer Research and Clinic

基　　金：国家自然科学基金青年基金(81702692)。

摘　　要：目的基于生物信息学方法筛选鼻咽癌预后和免疫相关的细胞轨迹差异表达基因。方法从基因表达综合(GEO)数据库下载鼻咽癌单细胞测序数据集(GSE150825)和转录组测序数据集(GSE102349)。GSE150825数据集包括11例鼻咽癌和3例鼻咽淋巴增生(NLH)组织共66627个细胞的单细胞RNA测序结果,数据更新时间为2021年3月。GSE102349数据集包括113例鼻咽癌患者临床信息,数据更新时间为2017年。将GSE150825数据集中数据进行标化和重新聚类,并选取髓系细胞进行重新聚类,采用moncle2法进行拟时序分析。计算不同细胞状态的差异基因(细胞轨迹差异基因),并取并集得到并集基因。采用ClusterProfiler和ConsensusClusterPlus包对并集基因进行基因本体(GO)富集分析和临床分型。在GSE102349数据集中,根据细胞轨迹差异基因的并集基因,将患者分为两个亚组,分析两个亚组无进展生存(PFS)、临床分期、肿瘤免疫微环境的差异;CIBERSORT分析两个亚组免疫细胞浸润差异。使用LASSO回归构建预后预测模型。收集江苏省肿瘤医院2018年1月至2023年12月收治的经病理检查证实为鼻咽癌(14例)和正常鼻咽上皮(4例)的病理组织切片,采用免疫组织化学法检测筛选出的靶基因在正常鼻咽上皮和鼻咽癌肿瘤组织中的表达,并根据患者治疗前后核磁共振成像结果分析靶基因表达与鼻咽癌患者淋巴结治疗效果关系。结果对单细胞测序数据集GSE150825数据进行过滤和质控,共64312个细胞(48604个来自鼻咽癌,15798个来自NLH)进行后续分析。对质控后的细胞进行重新聚类分析,主要分为8种细胞类型:B细胞、T细胞、先天淋巴细胞、髓样细胞、成纤维细胞、肥大细胞和肿瘤细胞。髓样细胞特异性地分布在鼻咽癌患者中。拟时序变化的细胞轨迹差异基因主要富集在细胞质翻译、核糖体、局灶黏附、钙黏蛋白结合和细胞因子受体结合。在验证集GSE1Objective To screen differentially expressed genes of cell locus related to the prognosis and immunity of nasopharyngeal carcinoma based on bioinformatics.Methods The nasopharyngeal carcinoma single cell sequencing dataset(GSE150825)and transcriptome sequencing dataset(GSE102349)were downloaded from the Gene Expression Synthesis(GEO)database.The GSE150825 dataset included single-cell RNA sequencing results from a total of 66,627 cells in 11 cases of nasopharyngeal carcinoma and 3 cases of nasopharyngeal lymphatic hyperplasia(NLH),and the data was updated in March 2021.The GSE102349 dataset included clinical information of 113 patients with nasopharyngeal carcinoma and the data was updated in 2017.The data in the GSE150825 dataset were standardized and re-clustered,and myeloid cells were selected for re-clustering,and moncle2 method was used for pseudotime analysis.The differential genes of cell locus with different cell status were calculated and pooled to obtain pooled genes.ClusterProfiler and ConsensusClusterPlus packages were performed to make gene ontology(GO)enrichment analysis and clinical typing analysis on pooled genes.In the GSE102349 dataset,all patients were divided into 2 subgroups based on the pooled genes of differentially expressed genes of cell locus,and the differences in the progression-free survival(PFS),the clinical staging and tumor immune microenvironment of the 2 subgroups were analyzed.CIBERSORT was used to analyze the difference in immune cell infiltration of the 2 subgroups.LASSO regression was used to construct a prognostic predictive model.Pathological tissue sections of 14 patients with nasopharyngeal carcinoma and 4 patients with normal nasopharyngeal epithelium according to the pathological diagnosis were collected from Jiangsu Cancer Hospital from January 2018 to December 2023.Immunohistochemistry method was used to detect the expressions of screened target genes in normal nasopharyngeal epithelium and nasopharyngeal carcinoma tissues.The relationship between target gene expressio

关 键 词：鼻咽癌 单细胞分析 转录组测序 预后 免疫 肿瘤标志物 

分 类 号：R739.63[医药卫生—肿瘤] Q811.4[医药卫生—临床医学]