多组学数据解析循环及浸润性B细胞在结直肠癌免疫微环境中的作用

doi:10.3969/j.issn.1674-8115.2022.04.009

摘要/Abstract

摘要：

目的·探究循环及浸润性B细胞亚群在结直肠癌免疫微环境中的作用，探寻B细胞发育的潜在驱动机制，分析免疫微环境中B细胞与其他免疫细胞的互作关系及通信分子的功能，并寻找可能的调控途径以促进B细胞的抗肿瘤效应。方法·收集3例结直肠癌患者的癌旁（正常）、肿瘤和外周血共计9份样本，分别制备单细胞悬液。通过多色流式细胞仪分选免疫细胞后，利用10X Genomics平台进行单细胞转录组和B细胞受体组库（B cell receptor repertoire，BCR）测序，并使用Seurat等生信工具进行数据分析，从肿瘤与正常组织中B细胞的浸润数量及功能方面的差异、B细胞亚群与T细胞以及与髓系细胞亚群的互作关系、B细胞亚群的转录因子调控网络等角度进行探索分析。结果·与正常组织相比较，CD20⁺B细胞亚群在肿瘤组织中的浸润数量显著上升；其中，以生发中心B细胞（germinal center B cells，GCB）的作用最突出，发生积极的克隆扩增和重链突变水平的提升，并且向记忆B细胞分化的趋势增加。然而，浆细胞在肿瘤微环境中的数量大幅减少，以分泌IgA类抗体的浆细胞减少最为明显。此外，相较正常组织的免疫微环境，肿瘤组织中的GCB细胞与T细胞等其他免疫细胞的联系变得更加紧密，正向调控免疫功能的通信分子对显著富集。结论·GCB在结直肠癌肿瘤微环境中的作用大幅提升，以自身显著提升的重链突变水平来提高其对肿瘤抗原的亲和力，同时和微环境中的免疫细胞联系增强，发挥着积极的抗肿瘤效应。

关键词: 生物信息学, 单细胞测序, 结直肠癌, 免疫学, B细胞

Abstract:

Objective·To explore the role of circulating and infiltrating B cell subsets in the immune microenvironment of colorectal cancer and discover the potential molecular-driving mechanisms behind the above transformation. Then to analyze the interaction patterns between B cell subsets and other immune cells in the microenvironment, including the function analysis of communicating molecules. All these steps assist to find possible regulatory ways to augment the anti-tumor effect of B cells.

Methods·Paired tumor, normal and peripheral blood tissues were collected from three patients with colorectal cancer. A total of 9 samples were applied to prepare the single-cell suspension. Then all immune cells were sorted by flow cytometry. 10X Genomics platform was applied for single-cell transcriptome and B cell receptor repertoire (BCR) sequencing. Bioinformatic tools such as Seurat etc. were taken to analyze scRNA and BCR data. The downstream analysis includes differential analysis of B cell in tumor versus normal tissues, cell interaction analysis in the immune microenvironment and regulatory networks of B cell subsets.

Results·CD20⁺B cells were significantly increased in tumor versus normal tissues, especially germinal center B cells (GCB), which showed positively clonal amplification and high mutation level. Besides, GCB showed the tendency of transformation into memory B cells. On the contrary, plasma cells significantly reduced their activity in tumor, which was dominated by the IgA class. In addition, comparing with the immune microenvironment in normal tissues, GCB in tumor tissues are more closely connected with T cells and other immune cells, and the communication molecule pairs that positively regulate immune function were significantly enriched.

Conclusion·The importance of GCB in the immune microenvironment of colorectal cancer is greatly increased. And they exert a positive anti-tumor effect through the up-regulated heavy-chain mutation level and their close association with surrounding immune cells.

Key words: bioinformatics, single cell sequencing, colorectal cancer, immunology, B cell

中图分类号:

R735.3

龚其雨, 陈磊. 多组学数据解析循环及浸润性B细胞在结直肠癌免疫微环境中的作用[J]. 上海交通大学学报（医学版）, 2022, 42(4): 472-481.

GONG Qiyu, CHEN Lei. Role of circulating and infiltrating B cells in immune microenvironment of colorectal cancer by multi-omics data profiling[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2022, 42(4): 472-481.

图/表 6

图1 免疫细胞全局转录组图谱Note：A. Distribution of main immune cell clusters. B. Marker genes' expression of main clusters. C. Cluster proportion among patients and samples. D. Total collected 88 04 B cells for paired BCR.

Fig 1 Transcriptome map of main immune cells

图2 B细胞亚群转录组图谱Note：A. Distribution of 13 B cell subclusters. B. Marker genes' expression of subgroups. C. Proportion of B cell subclusters among PBMC, normal and tumor samples.

Fig 2 Atlas of B cell subclusters in CRC

图3 TCGA-COAD数据分析B细胞亚群在肿瘤与正常组织的组成差异Note： A. Composition scores of B cell subsets in tumor versus normal tissues of TCGA-COAD data. B. GCB composition scores among progressing stages. C. Pathway enrichment analysis of GCB cluster. The red notes up-regulated pathways, and the blue marks down-regulated pathways.

Fig 3 Composition of B cell subsets in tumor and normal tissues by TCGA-COAD data profiling

图4 B细胞亚群与T细胞亚群及髓系细胞亚群的通信分子对Note： A. Significant protein-protein interaction pairs between B cell subsets and T cell subsets. B. Significant protein-protein interaction pairs between B cell subsets and myeloids subsets.

Fig 4 Interecting pairs between B cell subsets with T cells and myeloid cells

图5 B细胞各亚群的克隆扩增情况及GCB在组织的突变水平比较Note： A. Zscored clonal expansion index among three samples. B. Comparsion of clonal expansion between normal and tumor tissues. C. Heavy chain mutation level of GCB among samples.

Fig 5 Clonal expansion index of B cell subsets and mutation level of GCB

图6 B细胞各亚群在正常(A)、肿瘤(B)和外周血(C)组织中的克隆型迁移指数比较

Fig 6 Transition index of B cell subsets among normal (A), tunor (B) and PBCM (C) sample

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