Citations

Abstract Bruton tyrosine kinase (BTK) is central to chronic lymphocytic leukemia (CLL) biology, yet the regulatory programs that depend on BTK remain poorly defined. Here, we used acute NX-5948 (Bexobrutideg)-mediated BTK degradation to define BTK-dependent regulatory circuitry in CLL. Integrating early transcriptional and chromatin responses with chromatin-state annotation, target-gene linkage, and transcription factor assignment, we resolved a chromatin-informed framework linking BTK loss to downstream gene-regulatory output. This framework is separated into two directional programs: a dominant BTK-maintained network that collapsed after BTK degradation and a smaller BTK-released network that emerged upon BTK loss. BTK-responsive elements were concentrated in promoter- and enhancer-linked chromatin compartments, consistent with a model in which BTK-dependent transcriptional output is mediated through specific active regulatory elements. Functional validation in a CLL-like cell model provided orthogonal support for the NFAT-linked component of the BTK-maintained regulatory circuitry. BTK-dependent regulon activity was associated with clinical outcome, and projection of bulk-derived programs into longitudinal single-cell RNA-seq resolved malignant CLL cells into distinct regulatory states with maintained-like and released-like features. Together, this work defines BTK-dependent regulatory programs in CLL through a chromatin-informed framework linking BTK activity to gene-regulatory output. These findings lay the foundation for understanding how BTK-dependent circuitry contributes to malignant cell-state diversity, clinical outcome, and remodeling during therapy.

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.

Abstract Despite the advent of novel targeted therapies with high overall response rates, chronic lymphocytic leukemia (CLL) is still largely incurable due to the development of resistance. The bone marrow microenvironment (BMME) plays an important role in the survival and drug resistance in CLL. BM stromal cells (BMSCs) are considered a key component of BMME. Our long-term goal is to gain further insights of BMSCs-CLL crosstalk influencing both survival and drug resistance in CLL. To understand the global biologic changes that occur in leukemic CLL cells when in contact with BMSCs, we assessed RNA-seq in paired CLL cells isolated from untreated blood and BM and in untreated patients’ CLL cells cultured alone or with BMSCs. CLL cells from blood/BM and cultured alone/with BMSCs were also examined by Immunoprecipitation (IP), Western blot (WB), untargeted metabolomics (LCMS+GCMS), and preclinical drug sensitivity assays. We detected only 13 upregulated genes that overlap between CLL cells from BM and cocultured with BMSCs (p&lt0.05, fold change &gt1.5). When we analyzed the expression of these 13 genes in CLL cells from a cohort of 162 untreated patients by RNA-seq, we found associations between 4 genes (PNP, C16orf54, MOB3A, CDK2AP2) and clinical outcomes including overall survival (OS), progression free survival (PFS), and time to first treatment (TTFT) [multivariable Cox proportional hazards models, p&lt0.05]. Of the 4 genes, purine nucleoside phosphorylase (PNP), an enzyme in the purine pathway, had the most significant association with OS, PFS, and TTFT. Metabolomic profiling indicated an increased level of purine pathway metabolites adenosine, adenine, inosine, and hypoxanthine in cocultured CLL cells. WB analysis showed variable baseline PNP protein expression with 2 cohorts: low /no (L) and high (H) PNP using CLL blood cells. An induction in PNP protein levels were noticed in CLL cells expressing only LPNP when cocultured. Given the association of HPNP with adverse clinical outcomes, we tested for L vs. HPNP cohorts drug sensitivity to known BTK inhibitors(is) or Bcl2is. Treatment of CLL cells from untreated patients with Bcl2is venetoclax, S55746, and LP-118 (Bcl2-Bclxli, Newave) showed increased sensitivity to the Bcl2/Bclxlis in HPNP but not in LPNP cells. In addition, BTKis showed no difference in drug sensitivity associated with CLL PNP levels. To explain this discrepancy, WB and IP analyses were conducted in L vs. HPNP leukemic cells for apoptotic profiles, where we found increased phosphorylated-Bcl2(S70) and an increased association of Bcl2 with Bax in LPNP-expressing CLL cells compared to HPNP. These findings support increased resistance to apoptosis afforded by inhibiting Bcl2 for LPNP vs. HPNP-expressing CLL cells. Our future goals are to continue to understand the prognostic significance of the 4 genes with adverse clinical outcomes and to investigate how best to exploit the peculiar, enhanced sensitivity to Bcl2/Bclxlis found in the HPNP CLL cells. Citation Format: Sutapa Sinha, Weiguo Han, Zhiquan Wang, Brianna M. Finke, Heather C. Darby, Kari G. Rabe, Susan L. Slager, Chantal E. McCabe, Daniel R. O'Brien, Sameer A. Parikh, Esteban Braggio, Yi Chen, Fenlai Tan, Stephen P. Anthony, Yu Chen, Bing Dai, Yue Shen, Neil E. Kay. CLL drug resistance- A multifaceted mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4423.

AbstractMonoclonal B‐cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL) are clonal B‐cell disorders associated with an increased risk of infections and impaired vaccination responses. We investigated the immunogenicity of recombinant zoster vaccine (RZV) in these patients. Individuals with MBL/untreated CLL and Bruton tyrosine kinase inhibitor (BTKi)‐treated CLL patients were given two doses of RZV separated by 2 months. Responses assessed at 3 and 12 months from the first dose of RZV by an anti‐glycoprotein E ELISA antibody assay and by dual‐color Interferon‐γ and Interleukin‐2FLUOROSPOT assays were compared to historic controls matched by age and sex. About 62 patients (37 MBL/untreated CLL and 25 BTKi‐treated CLL) were enrolled with a median age of 68 years at vaccination. An antibody response at 3 months was seen in 45% of participants, which was significantly lower compared to historic controls (63%, p = .03). The antibody response did not significantly differ between MBL/untreated CLL and BTKi‐treated CLL (51% vs. 36%, respectively, p = .23). The CD4+ T‐cell response to vaccination was significantly lower in study participants compared to controls (54% vs. 96%, p < .001), mainly due to lower responses among BTKi‐treated patients compared to untreated MBL/CLL (32% vs. 73%, p = .008). Overall, only 29% of participants achieved combined antibody and cellular responses to RZV. Among participants with response assessment at 12 months (n = 47), 24% had antibody titers below the response threshold. Hypogammaglobulinemia and BTKi therapy were associated with reduced T‐cell responses in a univariate analysis. Strategies to improve vaccine response to RZV among MBL/CLL patients are needed.

Introduction: In 2017, a two-dose recombinant zoster vaccine (RZV) containing glycoprotein E (gE) and a novel adjuvant was approved to prevent herpes zoster and its complications in adults ≥50 years of age in the US. There are limited data on the immunogenicity and safety of RZV in patients with chronic lymphocytic leukemia (CLL). Methods: Between 8/15/2018 and 11/4/2019, RZV-naïve patients with CLL and monoclonal B-cell lymphocytosis (MBL) seen at Mayo Clinic, Rochester, MN were enrolled in this IRB-approved study. All participants received two doses of vaccine, at 0 and 2 months after enrollment. Cell-mediated immunity was measured by dual-color interferon γ (IFN- γ) and interleukin 2 (IL-2) FLUOROSpot in peripheral blood mononuclear cells (PBMC) after depletion of ≥50% leukemic B cells. Results were reported in spot forming cells (SFC)/106 PBMC in wells stimulated with gE overlapping peptides or varicella zoster virus (VZV) inactivated cell lysate. Response rate was defined as the proportion of participants who achieved a ≥2-fold increase in IFN- γ or IL-2 SFC/106 PBMC one month after the second dose of vaccine compared with pre-vaccination baseline levels. We also determined the geometric mean fold rise (GMFR) and geometric mean count (GMC) of SFC /106 PBMC at baseline and 90 days after the first dose of vaccine. Two cohorts were enrolled: Cohort 1 consisted of individuals with previously untreated MBL and CLL; and Cohort 2 consisted of CLL participants who were on Bruton tyrosine kinase inhibitor (BTKi) therapy. We compared the response data to historic age-and sex-matched healthy controls who received RZV. Chi-square or Fisher's exact tests measured differences in response rates and Kruskall-Wallis tested for differences in continuous variables. Among CLL participants, multivariable regression analysis was used to investigate the association between day 90 SFC and prior BTKi treatment, accounting for age at RZV, age at CLL diagnosis, sex, and day 0 SFC. Results: Sixty-one participants were enrolled. Paired samples were available for 41 participants (22 in Cohort 1 and 19 [18 ibrutinib and 1 acalabrutinib] in Cohort 2), and 68 age- and sex-matched healthy controls. Baseline characteristics of MBL/CLL participants are shown in Table 1. Compared to healthy controls, participants with MBL/CLL had a significantly lower IFN-γ VZV-specific response rate (41% vs. 63%, p=0.03) and IFN-γ gE-specific response (56% vs. 96%, p&lt;0.001); although there were no differences in IL-2 response rates to VZV (51% vs 68%, p=0.09) or gE (95% vs. 100%, p=0.14, Table 2). There were differences in GMFR between participants with MBL/CLL and controls that reached statistical significance for IFN-γ and IL-2 gE-specific responses and borderline significance for IFN-γ VZV-specific responses (Table 2). VZV-specific response rates did not significantly differ between individuals with untreated MBL/CLL and those receiving BTKi (52% vs. 28%, p=0.12 for IFN- γ; (62% vs. 39%, p=0.15 for IL-2), nor did IL-2 gE-specific responses (96% vs. 95%, p=1.0). However, untreated MBL/CLL participants had significantly higher IFN- γ gE-specific response rate compared to BTKi-treated individuals (73% vs. 37%, p=0.02, Table 2). IFN- γ and IL-2 VZV- and gE-specific SFC GMC was significantly higher at Day 90 compared to Day 0 in all vaccinees, although the magnitude of response was significantly lower in MBL/CLL participants compared to healthy controls (Table 3). Among participants with MBL/CLL, age at diagnosis, age at receipt of RZV, and sex did not predict response to vaccination after accounting for prevaccination values. No serious adverse events were noted among MBL/CLL participants while on this study. Additional analyses including determination of humoral immunogenicity and long-term follow up to ascertain risk of herpes zoster infection are ongoing at this time. Conclusion: RZV was associated with lower cell mediated immunogenicity in MBL/CLL participants compared to healthy older adults. Among individuals with CLL, BTKi treatment was associated with decreased cell mediated immunogenicity of the vaccine. Given the inferior response rates, an additional dose of RZV may be considered to boost responses and should be studied in this patient population. Disclosures Johnson: GSK: Research Funding. Ding:Abbvie: Research Funding; Astra Zeneca: Research Funding; DTRM: Research Funding; alexion: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees. Kenderian:Humanigen: Consultancy, Patents & Royalties, Research Funding; Torque: Consultancy; Novartis: Patents & Royalties, Research Funding; Kite: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Mettaforge: Patents & Royalties; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Kay:Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding. Levin:GSK: Research Funding. Kennedy:ICW Ventures: Research Funding. Weinberg:GSK: Research Funding. Parikh:GlaxoSmithKline: Honoraria; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; MorphoSys: Research Funding; Verastem Oncology: Honoraria; Pharmacyclics: Honoraria, Research Funding; Genentech: Honoraria; Ascentage Pharma: Research Funding.