Genetic analysis of B and T cell subsets from CLL patients prior to and at Richter's transformation

Abstract Introduction: A subset of patients with chronic lymphocytic leukemia (CLL) experiences disease progression from CLL to Richter transformation (RT), characterized by the occurrence of a high-grade lymphoma. The outcomes of patients with RT are typically dismal and identifying better therapeutic strategies remains critically important for these patients. To discern the biologic underpinnings driving this transformation, we studied immune changes and genetic evolution in samples from CLL patients who developed RT. Methods: We identified 18 patients with CLL who developed RT; and performed single cell (sc) RNA-sequencing(seq) on sorted B and T cells from peripheral blood mononuclear cells (PBMCs) at the time of RT (n=18) and at the earlier time of CLL diagnosis (n=11). The median time between the CLL sample and the one closest to RT was 4.3 years (range, 0.2-7.3); and patients received a median of 1 CLL directed treatment (range, 0 – 7). A total of 749,906 cells and 36,601 genes were captured during scRNAseq and 720,580 cells and 21,892 genes were retained for downstream analysis, respectively. Analysis was performed using the immunopipe (https://github.com/pwwang/immunopipe) that wraps around Seurat (v5.1.0) and identified enriched pathways using Enrichr service. The sc-T cell receptor (TCR)-repertoire(R)-seq data was analyzed and visualized using scplotter (). The whole exome sequencing (WES) analysis with tumor B-cells from same patients of CLL & RT stages were done using the Agilent sureselect Human all exon v5 + UTR capture kit. Reads from paired end sequencing were processed with the sarek pipeline. Results: Analysis of 720,580 cells from 11 CLL and 18 RT samples showed 16 distinct cell types- 3 B and 13 T cell subtypes. We observed an increasing trend of CD8 TEM [mean 0.548 vs. 0.384, p = 0.12 (Wilcoxon test)] but a decreasing trend of CD4 TCM (mean 0.236 vs. 0.337, p = 0.08) and B-memory (mean 0.0085 vs. 0.0195, p = 0.51) subsets in RT compared to their CLL stage. When comparing transcriptional changes, we found that among the top 18 highly variable genes, the expression of FP236383.3 (lncRNA) and TCL1A was significantly higher (p<0.0001) in the B cell subsets of patients with RT vs. CLL stage. Additionally, in T cell subsets—primarily dnT, γδT, and CD8/CD4 naïve cells—the expression of FP236383.3, NKG7, GNLY, and CCL5 was significantly higher (p<0.0001), while the expression of LDHB, GZMK, and IL32 was significantly lower (p<0.0001) in RT vs. CLL stage samples. Comparison of specific gene set enrichment analysis showed significantly increased expression of GZMB in gdT (p<0.001) and decreased expression of GZMA, GZMK, TIGIT and TCF7 in dnT and CD8 Naïve cells (p<0.001) for RT vs. CLL stage. The top 10 differentially expressed pathways in RT included oxidative phosphorylation, allograft rejection, IFN-α/-γ responses, TNF-α signaling via NF-κβ, complement, Myc targets V1, mTORC1, hypoxia, and p53 signaling across various B and T cell subsets compared to the CLL stage. Initial analysis of TCR-R data showed that patients with RT stage have lower number of unique clones (p<0.5) and reduced clonal diversity (p<0.5), and a higher number of large and hyperexpanded clones compared to their CLL stage. Additionally, WES data indicated that the most frequently mutated gene is TP53 in tumor B cells of both CLL and RT stages. However, a higher percentage of RT-stage samples carry mutations in MGA, ATM, and IRF2BP2 genes compared to their CLL-stage. WES data also showed a trend toward differing frequencies of copy number amplification at 19q12 (p=0.10) and 4q13.1 (p=0.52) between RT and CLL stages. Conclusions: The main findings of our study are as follows:The transcriptional landscape showed significant changes in multiple genes and pathway enrichment related to cell growth, differentiation and immune response in RT vs. CLL stage.A decreased fraction of CD4 TCM cells and reduced TCR clonal diversity were observed in samples at the RT stage and may indicate a poor prognosis for the patients at this stage. WES data of tumor B cells also indicated possible genetic alterations in the RT vs. CLL stage. Data from in-depth analyses on understanding of the dynamics of T cell response and additional experiments on these patients are expected to provide valuable insights into tumor genetic heterogeneity, transcriptional and immune regulation in blood-based immune subsets.