生物
滤泡性淋巴瘤
免疫系统
CD52型
B细胞
豁免特权
癌症研究
人口
抗体
免疫学
淋巴瘤
医学
阿勒姆图祖马
环境卫生
作者
Noemi Andor,Erin F. Simonds,Debra K. Czerwinski,Jiamin Chen,Susan M. Grimes,Christina Wood-Bouwens,Grace Zheng,Matthew Kubit,Stephanie Greer,William A. Weiss,Ronald Levy,Hanlee P. Ji
出处
期刊:Blood
[Elsevier BV]
日期:2018-12-27
卷期号:133 (10): 1119-1129
被引量:126
标识
DOI:10.1182/blood-2018-08-862292
摘要
Follicular lymphoma (FL) is a low-grade B-cell malignancy that transforms into a highly aggressive and lethal disease at a rate of 2% per year. Perfect isolation of the malignant B-cell population from a surgical biopsy is a significant challenge, masking important FL biology, such as immune checkpoint coexpression patterns. To resolve the underlying transcriptional networks of follicular B-cell lymphomas, we analyzed the transcriptomes of 34 188 cells derived from 6 primary FL tumors. For each tumor, we identified normal immune subpopulations and malignant B cells, based on gene expression. We used multicolor flow cytometry analysis of the same tumors to confirm our assignments of cellular lineages and validate our predictions of expressed proteins. Comparison of gene expression between matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin (Ig) light chain expression (either Igκ or Igλ), as well the expected upregulation of the BCL2 gene, but also downregulation of the FCER2, CD52, and major histocompatibility complex class II genes. By analyzing thousands of individual cells per patient tumor, we identified the mosaic of malignant B-cell subclones that coexist within a FL and examined the characteristics of tumor-infiltrating T cells. We identified genes coexpressed with immune checkpoint molecules, such as CEBPA and B2M in regulatory T (Treg) cells, providing a better understanding of the gene networks involved in immune regulation. In summary, parallel measurement of single-cell expression in thousands of tumor cells and tumor-infiltrating lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.
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