Secreto, Charla

Despite notable advancements in treating chronic lymphocytic leukemia (CLL) with targeted therapies, a significant clinical challenge arises as a subset of CLL patients progress and develop Richter's transformation (RT), an aggressive form of lymphoma. While immune cell dysfunction and T cell defects are well-known characteristics of CLL, the alterations in immune cell subsets during CLL progression to RT remain largely unexplored. While CLL patients typically fail to respond to anti-PD1 pembrolizumab, a positive response has been observed in 20-40% of RT patients. Previously, our study involving three RT patients (1 responder and 2 progressors) revealed enriched regulatory T cells (Tregs) in the responders compared to progressors after pembrolizumab treatment (Iyer et al, ASH2020). Hence, we propose that dynamic changes in T cell subsets at baseline may be associated with response to pembrolizumab treatment. To this end, we performed single-cell RNA sequencing on sorted T cells (CD3 +) from PBMCs derived from 20 patients (responders (RES), n=5; stable disease (SD), n=5; progressive disease/progressors (PD), n=10). A total of 408,627 cells were captured, and an average of 1,393 genes were detected per cell per patient. Using a graph-based clustering approach (Seurat V4.3), we identified 19 clusters based on marker genes and transcriptional signatures and identified enriched pathways using Enrichr analysis. Our results showed that RES had an increased Th17 subset at baseline compared to PD (15% vs. 5%, p=0.01) and reduced Th2 T cells compared to SD (p=0.004) and PD (p=0.05). The Th17/Th2 ratio was higher in RES at baseline (Th17/Th2 R: 1.24, PD: 0.21, SD: 0.25, p0.05) and post-pembrolizumab (Th17/Th2 RES: 1.31, PD: 0.34, SD: 0.30, p0.05). Furthermore, RES had an increased fraction of proliferating CD4 T cells at baseline (4% RES vs. 0.4% SD and 0.4% PD, p=0.02) and post-treatment (1.9% RES vs. 0.8% PD and 0.34% SD, p=0.02). Although we observed an increasing trend in the fraction of Tregs in the RES at baseline [(7.6% RES vs.6.1% PD and 6.5% SD, p=0.4; ns) and post-treatment (10.3% RES vs. 8.3% PD and 5.8% SD, p= 0.2; ns] compared to PD and SD, the difference was not significant. Similarly, among CD8+ T cells, we observed an increasing trend in CD8+ effector T cell fraction in the responders at baseline (29.8% RES vs. 21% PD and 15.6% SD, p=0.9, ns) and post-treatment (30.1% RES vs. 21.2% PD and 19.9% SD, p=0.44, ns). However, the difference was not statistically significant. These findings highlight the dynamic changes in T cell subsets associated with pembrolizumab response. In terms of transcriptional changes in Tregs following pembrolizumab treatment among RES, PD, and SD, we observed dynamic changes on a few Treg marker genes, including TIGIT and TOX. TIGIT and TOX expression drastically decreased after treatment in RES (p < 0.0001), while expression did not change in PD and SD. There were no significant changes in the expression of FOXP3 or CD27 in RES, PD, and SD before and after the treatment. In CD8 effector T cells, GZMK, GZMA (granzymes), and PRF1 (perforin) are marker genes. We observed higher expression of GZMK and GZMA in RES (p <0.0001) at the baseline compared to SD and PD. In the proliferating CD4 T cells, we observed increased expression of IDH2 (Isocitrate dehydrogenase 2-key enzyme of TCA cycle) in RES at the baseline, as compared to PD and SD, indicating increased TCA cycle activity in the proliferating T cells. Pathway analysis of T cell clusters using the Enrichr database showed TNFA-IFNG-MYC targets are enriched in CD8 + cells, IL2-STAT5 signaling is upregulated in Th17, TREGs, and E2F cell cycle associated pathways enriched in CD4 + proliferation cluster. In conclusion, our study unveils significant baseline differences in CD4 subsets between RES and PD/SD subjects and dynamic changes in T cell subsets and transcriptional signatures. These findings offer potential predictors of pembrolizumab response in RT, such as increased Th17/Th2 ratio, enriched proliferating CD4 + T cells, and elevated TIGIT, TOX gene expression in Tregs, GZMK, and GZMA in CD8 effector cells. This deeper understanding of the immunological landscape in RT patients sheds light on the interplay between T cell subsets and treatment response in RT, paving the way for personalized therapeutic strategies. Further validation and exploration can lead to improved outcomes and tailored interventions for RT.

Abstract The consequences of immune dysfunction in B-Chronic Lymphocytic Leukemia (CLL) likely relate to the incidence of serious recurrent infections and second malignancies that plague CLL patients. The known immune abnormalities are not able to consistently explain these complications and it is not easy to correct their immune status. Here, we report bone marrow (BM) hematopoietic dysfunction in early and late stage untreated CLL patients. We found reduced functional capacity of hematopoietic progenitors in BM using colony forming unit assays and flow cytometry revealed significant reductions in frequencies of hematopoietic stem and progenitor cell (HSPC) populations. Consistent with the reduction in HSPCs, monocytes and natural killer cells in BM were reduced and the reduction in BM was recapitulated in blood. Finally, we report imbalances in protein levels of the transcriptional regulators HIF-1α, PU.1, and GATA-2 in CLL patient BM, providing molecular insight into the basis of HSPC dysfunction. Importantly, PU.1 and GATA-2 were rapidly increased when healthy HSPCs were exposed in vitro to TNFα, a cytokine constitutively produced by CLL B cells. Together, these findings reveal BM hematopoietic dysfunction in untreated CLL patients, adding to the complex immunodeficiency state of these patients and the reduced capacity of the innate immune system.

Abstract Introduction: CLL is the most common leukemia in the U.S. and characterized by constitutively activated BCR signaling pathway, which has a crucial role both in normal B cell development and B cell malignancies. The biological events controlled by BCR signaling in CLL are not fully understood. Active BCR signaling is mediated through activation of the downstream kinase Bruton tyrosine kinase (BTK), which has become a key therapeutic target to inhibit BCR signaling for the treatment of B cell malignancies. We reasoned that blood samples from CLL patients before and after Bruton's tyrosine kinase inhibitors (BTKi) treatment would provide a valuable resource in the study of BCR modulation of epigenetic machinery in leukemic B cells. Methods: We obtained blood samples from CLL patients before and after BTKi ibrutinib treatment and used them to study BCR signaling regulated genes (n = 8 patients, after one-year of continuous ibrutinib treatment). Gene expression profile of CLL B cells from patients before and after one-year ibrutinib treatment was analyzed by mRNA-seq seq. Genome wide Histone H3K4me1, H3K27ac, and H3K4me3 profile was determined by CUT&tag. Chromatin accessibility was determined by ATAC-seq. Putative enhancers were deleted by CRISPR-Cas9. Results: Notably BTKi treatment led to the reduction of expression in genes associated with single strand DNA deamination (Fig. 1A) The BTKi regulated genes involved in this process mainly contains the APOBEC3 family genes (APOBEC3C, APOBEC3D APOBEC3F, APOBEC3G, APOBEC3H), and their expression levels showed a consistent reduction in CLL B cells from ibrutinib treated patients (Fig. 1B). We then confirmed the reduction of APOBEC3 levels by western blot in CLL B cells from four patients before and after one-year of continuous ibrutinib treatment (Fig. 1C). We hypothesized that BCR signaling regulates APOBEC3 expression by modifying the local chromatin around the APOBEC3 gene cluster and performed CUT&Tag to map the histone marks including H3K4me1, H3K4me3, H3K27ac and ATAC-seq. This approach permitted us to examine the chromatin accessibility of the leukemic cells from CLL patients before and then after one-year of continuous ibrutinib treatment. We found that BTKi treatment caused reductions of H3K4me1, H3K27ac, and chromatin accessibility at these regions in ibrutinib treated patients ( 7 of the 8 samples tested), however, there was no change of the promoter marker H3K4me3 (Fig. 1D), which indicated that BTKi treatment leads to APOBEC3 genes expression change via the regulation of their enhancer regulation (APOBEC3 enhancers, AEs). Based on the enrichment of H3K4me1, H3K27ac and chromatin accessibility, AE regions of the ibrutinib native samples contain three active enhancer modules, we designated these modules as AE1, AE2, and AE3 (Fig. 1D). To assess the functional activity of these enhancers on the expression of APOBEC3 genes, we investigated the consequence of deletion of each one of these AEs in the MEC1 cell line by CRISPR-Cas9. PCR analysis showed very robust deletion of AE1, AE2, and AE3 (Fig. 1E). Both deletion of AE1 or AE2 reduced the expression of APOBEC3 genes, while AE3 deletion suppressed the expression of APBEC3C, APOBEC3D, APOBEC3F and APOBEC3G, but not APOBEC3H, which is in closest proximity to AE3 (Fig. 1F, G). Together, we identified the BCR signaling dependent enhancers that regulate APOBEC3 expression. Since APOBEC3 deaminates ssDNA, we reasoned that APOBEC3 in CLL B cells may also contribute to replication stress and DNA instability. We found that MEC1 cells have a high level of spontaneous DNA damage in the S phase cells (Fig. 1H). which is associated with replication stress. However, AE2 deleted MEC cells showed decreased γH2Ax in the S phase cells (Fig. 1H). Edu/PI assay showed that MEC1 cells had a fraction of S phase cells with low Edu incorporation during S phase, also indicating DNA replication stress (Fig. 1I); however, AE2 deletion greatly increased Edu incorporation (Fig. 1I). Taken together, these data suggest that increased expression of APOBEC3 may be involved in DNA replication stress and drives genomic instability in malignant B cells. Conclusion: We demonstrate a novel mechanism for BTKi suppression of APOBEC3 expression via direct enhancer regulation in CLL B cells, implicating BCR signaling as a potential regulator of leukemic genomic instability. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sunesis: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Targeted 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; MEI Pharma: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; Tolero Pharmaceuticals: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Abstract Chronic lymphocytic leukemia (CLL) is a neoplastic disease of mature B-cells with a highly heterogeneous clinical course. While European ancestry (EA) populations present an increased incidence of CLL, African ancestry (AA) populations have a younger median age of onset, higher frequency of adverse prognostic factors, and inferior clinical outcomes. Despite the considerable effort to characterize the genetic landscape of CLL, AA are overwhelmingly underrepresented. Our hypothesis is that the clinical differences observed between AA and EA populations are, in part, explained by underlying genetic features. To address this imbalance, we identified 90 AA patients diagnosed with CLL, 64% of which were untreated at sample collection. RNA and DNA were extracted from CD5+/CD19+ clonal B-cells. We performed mRNA-seq and targeted sequencing in 59 recurrently mutated somatic CLL driver genes. Differentially expressed genes were identified using edgeR. Data was compared to our previously analyzed EA CLL cohort (N=445). The median age at diagnosis was 59 years for AA and 66 for EA and 74% of AA and 50% of EA had unmutated IGHV (u-IGHV) status. When evaluating the entire AA and EA cohorts, there was a significant increased frequency of mutations in TP53, SF3B1, and NFKBIE, identified in 29%, 24%, and 20% of AA CLLs, compared to 5%, 9%, and 9%, respectively, in EA CLLs (p<0.01). When exclusively evaluating the untreated and u-IGHV cases, AA CLLs showed greater proportion of TP53 (30% vs 12%; p=0.0145), NFKBIE (30% vs 15%; p=0.0492), BIRC3 (21% vs 10%; p=0.0697), and KRAS (15% vs 7%; p=0.1683). Furthermore, there was an increase in mutations targeting relevant molecular pathways, such as NF-κB (42% vs 15%) and MAPK (18% vs 8%). Upregulation MAPK pathway was also confirmed by mRNA-seq analysis in the AA u-IGHV CLLs. Because of the high prevalence of TP53 mutations in the AA cohort, we further evaluated differential gene expression in the DNA Damage/Telomere Stress-Induced Senescence pathway. AA CLLs presented a significant downregulation of multiple genes associated with genome stability and cellular DNA damage response - DDR (including TP53 and ATM), double strand break repair (H2AFX and RAD50), telomere maintenance (POT1 and ACD), and cell cycle regulation (RB1, CCNA1, and CCNE2) (FDR<0.05). DDR is responsible for DNA repair or induction of apoptosis, with its deficiency resulting in the accumulation of chromosomal aberrations, negatively impacting clinical outcome in CLL. Disparities in cancer are influenced by numerous factors that affect disease risk, screening and diagnosis, access to treatment, and survival. We identified an increased number of genomic alterations in the AA CLL cohort, primarily inducing activation of NF-κB and MAPK pathways and DDR impairment, with the increased frequency of mutations, notably in TP53 and BIRC3, expected to negatively impact prognosis. Citation Format: Cecilia Bonolo de Campos, Daniel R. O'Brien, Chantal E. McCabe, Huihuang Yan, Geffen Kleinstern, Zhiquan Wang, Laura A. Bruins, Cristine Allmer, Nicholas J. Boddicker, Charla R. Secreto, Aaron D. Norman, Shulan Tian, Kari G. Rabe, Timothy G. Call, Sameer A. Parikh, Jose F. Leis, Wei Ding, Richard Furman, J Brice Weinberg, James R. Cerhan, Celine M. Vachon, Neil E. Kay, Susan L. Slager, Esteban Braggio. Characterization of underlying genomic features among African ancestry populations diagnosed with chronic lymphocytic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2209.

Abstract Richter's transformation (RT) is a clinically challenging and aggressive transformation of CLL (Chronic lymphocytic leukemia) to lymphoma. Immune-checkpoint therapy has improved outcomes in selective lymphoma types. Nearly 40% of RT patients respond to anti-PD1, while the underlying CLL do not show any response, and 10% of CLL patients progress post-anti-PD1 treatment. Previous studies mostly focused on T-cell responses elicited by anti-PD1, however, intrinsic changes in CLL and RT B-cells induced by the treatment remains elusive. We hypothesized that pre-existing active transcriptional circuitry and distinct B-cell subsets in the CLL and RT B-cells may determine the response to anti-PD1 treatment. Peripheral blood mononuclear cells (PBMCs) from 3 patients who received pembrolizumab(anti-PD1) as a single agent. Samples were obtained at baseline and 3 months post-treatment initiation. Among these patients, 2 are progressors while 1 is a responder. We performed single-cell RNAseq (10X Genomics) on B-cells enriched from PBMCs derived from 3 samples (1 Responder: RS2, 2 progressors: CLL14 and CLL17) before and after treatment using chromium single cell 3' gene expression library. A total of ~10000 cells were captured with an average detection of 1000 genes/sample. To delineate the transcriptional changes upon the anti-PD1 treatment, we first integrated the single-cell data from 6 samples (before and after Pembro) and performed unsupervised clustering analysis using UMAP (Uniform Manifold Approximation and projection). We identified 8 different clusters based on highly expressed marker genes. Cluster 2(C2) was increased in the responder as compared to the progressors post-pem treatment. To determine the activated pathways in each cluster, we performed gene-set enrichment analysis (GSEA) using the Enrichr method. This analysis revealed upregulation of distinct pathways related to IFNG/MYC(C1), IFNG(C2), ER stress(C3), B-cell dependent T cell activation related pathway(C4), MYC targets/TNFα(C5,6,7) indicating intra-tumor transcriptional heterogeneity. To decipher the intratumor cell differentiation changes, we performed pseudotime trajectory analysis using Monocle 2 coupled with B cell developmental stage markers. We identified 7 different states, with distinct changes of state in responder sample RS2 (State 4,5, 6, and 7 were increased in RS2 post-treatment) while CLL samples(progressors) did not have distinct changes. Integration with B cell development revealed that aggressive B cells with CD38 expression were highly induced upon anti-PD1 in responder RS2 while regulatory (CD1d) and memory B cells (CD27) remained the same, suggesting PD1 induced intrinsic changes contributing to the disease response. We identified distinct transcriptional states in B cells within responders and progressors which may govern the intra-tumor and inter-tumor heterogeneity to the anti-PD1 response. Citation Format: Prajish Sundaram Iyer, Lu Yang, Yang Zhi Zhang, Hyo Jin Kim, Charla Secreto, Sutapa Sinha, Neil Kay, Stephen Ansell, Wei Ding, Lili Wang. Tumor intrinsic changes determine immune-checkpoint response in Richter's transformation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1612.

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; 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. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; 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; Acerta Pharma: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab

Introduction: PD-1 inhibits the cytotoxic T-cell functions via the interaction with its ligands (PDL1 and PDL2). Recently, our group showed a selective response (~40%) with PD-1 blocking antibody pembrolizumab in patients with Richter transformation (RT), particularly after prior exposure to ibrutinib (Wei Ding et al, Blood, 2017). Additionally, PD-1 showed an increased expression in tumor B-cells of patients with RT (Rong He et al, AJSP, 2018). Here we investigated the functional implications of the PD-1 signaling axis in lymphoma B-cell pathobiology. Methods: 26 CLL-involved lymph node (LN) and 20 RT-involved LN samples were tested for PD-1 expression by immunohistochemistry (mouse clone NAT105, Abcam). Then, we checked PD-1 expression in 10 lymphoma cell lines and 1 CLL cell line (MEC-1) by both, flow cytometry and Western blot (WB) analysis. Over-expression of PD-1 using pLEX-lentiviral system (Thermo Scientific) was evaluated for in vitro cell cycle regulation and in vivo tumor growth. Overexpression of PD-1 was further examined on the regulation of cell signaling pathways using human phospho kinase array kit (R&D) and WB analysis. Gene expression signatures in CLL and RT patients were also identified by Illumina-based RNA sequencing using Formalin-Fixed Paraffin-embedded (FFPE)-nodal tissue obtained by clinical biopsy (Tempus Labs; Chicago, IL). Results: The expression of PD-1 was significantly increased in RT-LN compared to CLL-LN (mean ± SEM in RT vs. CLL, 30.6% ± 4.7% vs. 11.5% ± 2.8%, p < 0.001) [Fig 1A]. PD-1 expression was highest in patients with RT where the last prior CLL therapy was ibrutinib. To test the role of PD-1 in lymphoma B-cells, its expression was assessed in lymphoma and CLL cell lines. The expression of PD-1 was found to be variable, but at very low-levels in lymphoma lines OCI-LY7 and OCI-LY19 (data not shown). Constitutive lentiviral (pLEX-PD-1)-mediated overexpression of PD-1 in OCI-LY7 and OCI-LY19 cells led to increased cell growth (1.4 and 1.9 fold compared to original lines on day 4, respectively, Fig 1BI-II), which was further confirmed by cell cycle analysis which showed an increase in S phase by 20.4% and 24.53% in OCI-LY7 and OCI-LY19 cells (Fig 1B III), respectively. When the luciferase + PD-1 expressing OCI-LY7 cells were injected intravenously (1X106 cells) into NSG mice, increased tumor growth was observed at 22 days of follow up by bioluminescence imaging (p<0.01, Fig 1C). Using phospho-kinase array, an overall decrease of phosphorylation was detected on multiple sites of p53 (S392, S15, S46) and CHK2 (T68) (data not shown). This finding was further confirmed by WB analyses (Fig1DI). In addition, decreased of total p53 and increased phosphorylation on both SHP-1 and SHP-2 were found in PD-1 overexpressing OCI-LY19 and OCI-LY17 cell lines (Fig 1DI). Immunoprecipitation experiments with anti-PD1 antibody showed that PD-1 was in the same complex with SHP-1 and SHP-2 in OCI-LY7 cells but only with SHP-2 in OCI-LY19 cells (Fig 1DII). In parallel, mRNA sequencing was performed on 11 nodal tissues from either RT (n=8) or progressive CLL (n=3) after they developed clinical progression. The expression of PD-1 (PDCD1) was positively correlated with the expression of SHP-1 (PTPN6, r=0.56) and Cyclin E1 (CCNE1, r=0.62), implicating a direct role of PD-1 in regulating cellular proliferation and the induction in phosphatase expression in RT and CLL. Conclusion: Our data support the notion that PD-1 overexpression in lymphoma cells modifies cell proliferation in vitro and in vivo and regulates the function of phosphatase SHP and p53- pathways. These findings also indicate that aggressive lymphoma or CLL leukemic cells have the ability to hijack the PD-1 pathway and may result in downregulation of the p53 mediated DNA repair. This novel information provide for new strategies to further evaluate the interaction of checkpoint signals with DNA repair pathway, and possibly provide novel targets for Richter's transformation. Disclosures Ding: alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Astra Zeneca: Research Funding; 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; DTRM: Research Funding; MEI Pharma: Membership on an entity's Board of Directors or advisory committees. Sakemura:Humanigen: Patents & Royalties. Parikh:Janssen: Honoraria, Research Funding; Merck: Research Funding; Pharmacyclics: Honoraria, Research Funding; Ascentage Pharma: Research Funding; GlaxoSmithKline: Honoraria; MorphoSys: Research Funding; AstraZeneca: Honoraria, Research Funding; Verastem Oncology: Honoraria; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; TG Therapeutics: Research Funding. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Liu:Eisal: Research Funding; Genentech: Research Funding; GRAIL: Research Funding; Menarini Silicon Biosystems: Research Funding; Merck: Research Funding; Seattle Genetics: Research Funding; Tesaro: Research Funding. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ansell:Seattle Genetics: Research Funding; Takeda: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol Myers Squibb: Research Funding. Kenderian:Sunesis: Research Funding; Tolero: Research Funding; Torque: Consultancy; BMS: Research Funding; Gilead: Research Funding; Kite: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties; Novartis: Patents & Royalties, Research Funding; MorphoSys: Research Funding; Lentigen: Research Funding; Juno: Research Funding. Kay:Acerta Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Sunesis: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; 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; Rigel: Membership on an entity's Board of Directors or advisory committees.