Action of circulating and infiltrating B cells in the immune microenvironment of colorectal cancer by single-cell sequencing analysis

Abstract

Background: The complexity of the immune microenvironment has an impact on the treatment of colorectal cancer (CRC), one of the most prevalent malignancies worldwide. In this study, multi-omics and single-cell sequencing techniques were used to investigate the mechanism of action of circulating and infiltrating B cells in CRC. By revealing the heterogeneity and functional differences of B cells in cancer immunity, we aim to deepen our understanding of immune regulation and provide a scientific basis for the development of more effective cancer treatment strategies.

Aim: To explore the role of circulating and infiltrating B cell subsets in the immune microenvironment of CRC, explore the potential driving mechanism of B cell development, analyze the interaction between B cells and other immune cells in the immune microenvironment and the functions of communication molecules, and search for possible regulatory pathways to promote the anti-tumor effects of B cells.

Methods: A total of 69 paracancer (normal), tumor and peripheral blood samples were collected from 23 patients with CRC from The Cancer Genome Atlas database (https://portal.gdc.cancer.gov/). After the immune cells were sorted by multicolor flow cytometry, the single cell transcriptome and B cell receptor group library were sequenced using the 10X Genomics platform, and the data were analyzed using bioinformatics tools such as Seurat. The differences in the number and function of B cell infiltration between tumor and normal tissue, the interaction between B cell subsets and T cells and myeloid cell subsets, and the transcription factor regulatory network of B cell subsets were explored and analyzed.

Results: Compared with normal tissue, the infiltrating number of CD20⁺B cell subsets in tumor tissue increased significantly. Among them, germinal center B cells (GCB) played the most prominent role, with positive clone expansion and heavy chain mutation level increasing, and the trend of differentiation into memory B cells increased. However, the number of plasma cells in the tumor microenvironment decreased significantly, and the plasma cells secreting IgA antibodies decreased most obviously. In addition, compared with the immune microenvironment of normal tissues, GCB cells in tumor tissues became more closely connected with other immune cells such as T cells, and communication molecules that positively regulate immune function were significantly enriched.

Conclusion: The role of GCB in CRC tumor microenvironment is greatly enhanced, and its affinity to tumor antigen is enhanced by its significantly increased heavy chain mutation level. Meanwhile, GCB has enhanced its association with immune cells in the microenvironment, which plays a positive anti-tumor effect.

Keywords: Colorectal cancer; Immune microenvironment; Infiltrating B cells; Multi-omics analysis; Single-cell sequencing analysis.

Figure 1

Transcriptome map of main immune cells. 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 B cell anti receptor library. BCR: B cell anti receptor library.

Figure 2

Atlas of B cell subclusters in colorectal cancer. A: Distribution of 13 B cell subclusters; B: Marker genes' expression of subgroups; C: Proportion of B cell subclusters among peripheral blood mononuclear cells, normal and tumor samples.

Figure 3

Composition of B cell subsets in tumor and normal tissues by The Cancer Genome Atlas colon cancer data profiling. A: Composition scores of B cell subsets in tumor vs normal tissues of The Cancer Genome Atlas-colon cancer data; B: Germinal center B cell (GCB) composition scores among progressing stages; C: Pathway enrichment analysis of GCB cluster. ^aP < 0.01; ^bP < 0.05.

Figure 4

Interecting pairs between B cell subsets with T cells and myeloid cells. 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.

Figure 5

Clonal expansion index of B cell subsets and mutation level of germinal center B cell. A: Zscored clonal expansion index among three samples; B: Comparsion of clonal expansion between normal and tumor tissues; C: Heavy chain mutation level of germinal center B cell among samples.

Figure 6

Transition index of B cell subsets. A: Normal tissue; B: Tunor tissue; C: Peripheral blood mononuclear cell sample.

Figure 7

Comparison of the number of T-cell receptor clonotypes between tumor and adjacent normal tissues. A: Estimation of the number of T-cell receptor (TCR) clonotypes in tumor and adjacent normal tissues; B: Comparison of TCR clonotypes between tumor and adjacent normal tissues; C: Comparison of the number of TCR clonotypes occupying 10% of repertoire between tumor and adjacent normal tissues; D: Comparison of TCR clonotypes with different CDR3 sequence lengths between tumor and adjacent normal tissues. ^aP < 0.01.

Figure 8

Comparison of proportion of T-cell receptor clonotypes with different amplification levels between tumor and adjacent normal tissues. ^aP < 0.01.

Figure 9

Comparison of relative abundances in different T-cell receptor clonotypes with specific frequencies between tumor and adjacent normal tissues. ^aP < 0.01.