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 co-expression patterns. To resolve the underlying transcriptional networks of follicular B cell lymphomas we analyzed the transcriptomes of 34,188 cells derived from six 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 light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC 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 co-expressed with immune checkpoint molecules, such as CEBPA and B2M in Tregs, 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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