Single-cell analysis can define distinct evolution of tumor sites in follicular lymphoma

Abstract

Tumor heterogeneity complicates biomarker development and fosters drug resistance in solid malignancies. In lymphoma, our knowledge of site-to-site heterogeneity and its clinical implications is still limited. Here, we profiled two nodal, synchronously-acquired tumor samples from ten follicular lymphoma patients using single cell RNA, B cell receptor (BCR) and T cell receptor sequencing, and flow cytometry. By following the rapidly mutating tumor immunoglobulin genes, we discovered that BCR subclones were shared between the two tumor sites in some patients, but in many patients the disease had evolved separately with limited tumor cell migration between the sites. Patients exhibiting divergent BCR evolution also exhibited divergent tumor gene expression and cell surface protein profiles. While the overall composition of the tumor microenvironment did not differ significantly between sites, we did detect a specific correlation between site-to-site tumor heterogeneity and T follicular helper (Tfh) cell abundance. We further observed enrichment of particular ligand-receptor pairs between tumor and Tfh cells, including CD40 and CD40LG, and a significant correlation between tumor CD40 expression and Tfh proliferation. Our study may explain discordant responses to systemic therapies, underscores the difficulty of capturing a patient's disease with a single biopsy, and furthers our understanding of tumor-immune networks in follicular lymphoma.

Germinal centre-driven maturation of B cell response to SARS-CoV-2 vaccination

“…For these two subjects, we analyzed two separate relatively early time points -weeks 5 and 7 for participant 02a, and weeks 4 and 7 for participant 04. Single-cell transcriptome analysis of lymph nodes revealed distinct populations of T and B cells, NK cells, monocytes, plasmacytoid dendritic cells, and follicular dendritic cells, as previously described [18][19][20][21] 5). Consistent with our flow cytometry results, considerable numbers of cells clustered into transcriptional groups defining GC B cells (33.8%) and LNPCs (7%) in the lymph node.…”

“…Cluster identities were assigned by examining the expression of a set of marker genes for different cell types (Extended Data Fig. 2c): MS4A1, CD19 and CD79A for B cells; CD3D, CD3E, CD3G, IL7R and CD4 or CD8A for CD4 + or CD8 + T cells, respectively; GZMB, GNLY, NKG7 and NCAM1 for natural killer (NK) cells; CD14, LYZ, CST3 and MS4A7 for monocytes; IL3RA and CLEC4C for plasmacytoid dendritic cells (pDCs); and FDCSP, CXCL14 20 and FCAMR 21 for follicular dendritic cells (FDCs).…”

B cell/stromal cell crosstalk in health, disease, and treatment: Follicular lymphoma as a paradigm

“…However, other studies propose either that copy number variations could represent an important layer of transcriptional heterogeneity and drug-response 105 or that patients exhibiting divergent BCR evolution between 2 distant tumor sites also exhibit divergent tumor gene expression and cell surface protein profiles. 106 An interesting finding is that FL tumor B cells are not, at the single-cell level, frozen in a specific GC stage of differentiation and could thus not be directly compared with the different subsets of normal GC B cells recently identified. 104 Yet, FL B cell transcriptomic profile within a single biopsy dynamically spans a continuum of transitional states between proliferating GC-like and quiescent memorylike states, with rare cells carrying a plasma cell-like profile.…”

“…Tracking subclonal divergences through the analysis of BCR diversification reveals that B‐cell subclones do not massively differ at the transcriptional levels, 12,104 suggesting that other drivers of phenotypic diversity are stronger than genetic events. However, other studies propose either that copy number variations could represent an important layer of transcriptional heterogeneity and drug‐response 105 or that patients exhibiting divergent BCR evolution between 2 distant tumor sites also exhibit divergent tumor gene expression and cell surface protein profiles 106 . An interesting finding is that FL tumor B cells are not, at the single‐cell level, frozen in a specific GC stage of differentiation and could thus not be directly compared with the different subsets of normal GC B cells recently identified 104 .…”

Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

“…In line with this, leukemia samples as well as lymphoma cells circulating in the peripheral blood were the subjects in hematology-focused projects of early days [ 26 , 27 ], with acute myeloid leukemia (AML) being the most frequently published oncohematological entity [ 28 ]. To date, SCS datasets have been generated for a wide range of blood cancers, including chronic myeloid leukemia [ 29 ], myeloproliferative neoplasms [ 30 , 31 ], myelodysplastic syndrome/acute myeloid leukemia [ 21 , 27 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ], acute lymphoblastic leukemia (ALL) [ 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ], chronic lymphocytic leukemia [ 59 , 60 , 61 ], mantle cell lymphoma [ 61 , 62 , 63 ], follicular lymphoma [ 61 , 64 , 65 , 66 ], diffuse large B-cell lymphoma [ 61 ], multiple myeloma [ 26 , 67 ], Hodgkin lymphoma […”