结直肠癌免疫细胞浸润模式及其与患者临床特征和总生存的相关性分析

Analyses of infiltration patterns of immune cells in colorectal cancer and its correlation with clinical characteristics and overall survival of patients

目的探讨结直肠癌免疫细胞浸润模式,分析免疫细胞浸润与患者临床特征及总生存(OS)的相关性。方法在癌症基因组图谱(TCGA)数据库中下载615例结直肠癌RNA测序数据,数据更新于2019年7月19日。包括结直肠癌肿瘤组织571例、癌旁组织44例,其中具有临床资料552例,包括生存时间、生存状态、年龄、性别、临床分期、分级、肿瘤部位等信息。采用CIBERSORT工具反卷积算法,基于标准化的基因表达数据计算出22种免疫细胞的相对含量。根据CIBERSORT算法的结果验证,选取反卷积结果准确性高的样本(P<0.05),用于分析和绘图。分析免疫细胞浸润模式与患者临床特征及OS的相关性。结果采用CIBERSORT方法运行后过滤去除P≥0.05的样本,共筛选出肿瘤组织样本282例,癌旁组织样本16例;其中有临床信息者共293例,包括肿瘤组织样本277例、癌旁组织样本16例。293例样本中M0巨噬细胞、M1巨噬细胞、M2巨噬细胞、CD8^(+)T细胞及未活化的CD4记忆性T细胞占总免疫细胞的比例较高;在肿瘤组织样本中,M0巨噬细胞、M1巨噬细胞、活化的CD4记忆性T细胞、未活化的自然杀伤(NK)细胞表达量较高;在癌旁组织中,初始B细胞、M2巨噬细胞、活化的NK细胞、未活化的树突细胞、未活化的肥大细胞及浆细胞等表达量较高;随着临床分期的升高,滤泡辅助性T细胞、活化的CD4记忆性T细胞、活化的NK细胞、M1巨噬细胞表达量降低,浆细胞、调节性T细胞表达量升高,差异均有统计学意义(均P<0.05)。M1巨噬细胞、未活化的肥大细胞、活化的CD4记忆性T细胞、CD8^(+)T细胞、滤泡辅助性T细胞在右半结肠癌中表达量较高,而M0巨噬细胞、活化的肥大细胞在左半结肠和直肠癌中表达量较高,差异均有统计学意义(均P<0.05)。以浸润的免疫细胞的中位表达水平将患者分为高浸润组和低浸润组进行生存分析,结果显示初始B细胞浸润程度高的患者OS较好,而M2巨噬细胞、活化的肥大细胞、中性粒细胞浸润程度高的患者OS较差。结论结直肠癌中不同分期、部位的样本中存在不同类型的免疫细胞浸润模式,且与肿瘤进展及患者OS密切相关,有望用于治疗靶点开发及预后预测。

Objectvie To investigate the infiltration patterns of immune cells in colorectal cancer,and to explore the correlation of immune cells infiltration with clinical characteristics and overall survival(OS)of patients.Methods The RNA sequencing data of 615 patients with colorectal cancer were downloaded from The Cancer Genome Atlas(TCGA)database.The data was updated on July 19,2019,and included 571 colorectal cancer tissues and 44 paracancerous tissues.There were 552 cases with clinical data,such as survival time,survival status,age,gender,clinical stage,grade,tumor location and so on.Using CIBERSORT deconvolution algorithm,the relative amounts of 22 immune cell types were calculated based on standardized gene expression data.According to the results of CIBERSORT algorithm,the samples with high accuracy of deconvolution result were selected(P<0.05),and they were used for analysis and graphing.The correlations between the infiltration patterns of immune cells and the clinical characteristics and OS of patients were analyzed.Results After the CIBERSORT method was used to filter and remove samples with P≥0.05,a total of 282 tumor tissue samples and 16 paracancerous tissue samples were screened.In 293 cases with clinical information,there were 277 tumor tissue samples and 16 paracancerous tissue samples.In 293 samples,M0 macrophages,M1 macrophages,M2 macrophages,CD8^(+)T cells and unactivated CD4 memory T cells accounted for a higher proportion of total immune cells;in tumor tissue samples,the expressions of M0 macrophages,M1 macrophages,activated CD4 memory T cells,and unactivated natural killer(NK)cells were higher;in paracancerous tissues,the expressions of naive B cells,M2 macrophages,activated NK cells,unactivated dendritic cells,unactivated mast cells and plasma cells were higher;with the increase of clinical stage,the expressions of follicular helper T cells,activated CD4 memory T cells,activated NK cells,M1 macrophages decreased,and the expressions of plasma cells and regulatory T cells increased,and the differences were statistically significant(all P<0.05).M1 macrophages,unactivated mast cells,activated CD4 memory T cells,CD8^(+)T cells,and follicular helper T cells were highly expressed in right colon cancer,while M0 macrophages and activated mast cells were highly expressed in left colon and rectal cancer,and the differences were statistically significant(all P<0.05).The patients were divided into high infiltration group and low infiltration group based on the median expression level of infiltrated immune cells,and the survival analysis was performed.The result of survival analysis showed that patients with high initial B cell infiltration had good OS;however,patients with high infiltration of M2 macrophages,activated mast cells,and neutrophils had poor OS.Conclusions There are different types of immune cell infiltration patterns in the colorectal cancer samples of different stages and locations,which are closely related to tumor progression and OS of patients.They are expected to be applied to the development of therapeutic targets and prognosis prediction.