Citations

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.

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly isolated lung fibroblasts using ATAC-seq. We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known profibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Genome occupancy analysis using ChIP-seq confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and profibrotic transcriptional regulators. Using loss- and gain-of-function studies, we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis, and contractile function. Together, these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.

Introduction: Novel targeted therapies have revolutionized treatments for both upfront and relapsed CLL. However, effective therapies have not been established for progressive CLL after developing resistance to both BTK inhibitor and BCL-2 inhibitors. Similarly, Richter's transformation (RS) remains an area of unmet clinical need. Hypothesizing that progressive CLL and RS possess significant but differential molecular abnormalities, we aimed to dissect the initial genomic profiles in a clinical cohort of patients seen in our routine clinical practice using targeted DNA sequencing and transcriptome analysis. Methods: Twelve CLL patients who had lymph node biopsies for evaluation of clinical progression at Mayo Clinic were included in this study. RNA sequencing and targeted DNA sequencing on a focused oncology panel of 1,711 genes were performed on Illumina HiSeq through Tempus Labs, Inc. (Chicago, IL). Differentially expressed (DE) genes were identified using edgeR at the cutoff of FDR <=0.05 and fold-change >=2. Somatic mutations and copy number alternations (CNAs) were identified through Mutect2 and PatternCNV, respectively. CN loss was defined to have log2(ratio) <=-0.93 and CN gain to have log2(ratio) >= 0.585. Pathway analysis was done through the Enrichr package. Results: Among the 12 patients, 7 had confirmed RS (large cell lymphoma histology) and 5 had CLL based on pathological findings. The clinical and therapeutic history for each patient is illustrated in Fig 1A. FISH results from 11 of the patients showed chromosomal abnormalities including del(13q), del(11q), del(17p) and tri(12) (Fig 1A). Hierarchical clustering of expression profiles from the top 10,000 most variable genes in expression revealed two major clusters (Fig 1A). Cluster C1 contains five RS cases, of which case S207 did not receive ibrutinib, S256 was on high-dose steroid and anti-CD20 post-ibrutinib therapy for >1 year before biopsy, and case S025 was treated for < 6 months with ibrutinib. These three form a subgroup separate from the other two RS in C1 who had 8 and 42 months of continuous ibrutinib therapy pre-biopsy, respectively. C2 contains two RS and five CLL cases. Within C2, CLL and RS cases showed similar transcriptomic profiles. Over 90% of the DE genes showed an overall increase of expression in C1, particularly within the 3-sample subgroup (Fig 1B). These genes are enriched in pathways known to play key roles in CLL, including PI3K-AKT signaling, NOTCH signaling and RAS/MAPK signaling, while genes up-regulated in C2 are enriched in WNT signaling. The results suggest marked differences in gene expression profiles and indicate molecular heterogeneity among RS and CLL patients. In addition, targeted DNA sequencing data were analyzed to identify somatic mutations and CNAs. The analysis confirmed the FISH results of del(13q), del(11q), del(17p) or tri(12) in 8 of the cases (Fig 1A). The mutation profiles are similar between C1 and C2 for the recurrently mutated genes published in CLL. However, we identified recurrent CNAs that occurred preferentially in C1 (covering 9 genes) or C2 (48 genes) (Fig 1C). Manual inspections of the reads coverage revealed that 5 of the 9 genes are from chr1q21.1 to chr1q22 that showed clear CN gains largely in C1. Of the 48 genes, 6 are from chrXp11 that showed CN losses, and 27 are from chr17q12 to chr17q25 that showed CN gains. Therefore, the majority of the 57 genes are from large-scale CNAs. Notably, for the CNAs mostly occurring in C2, the affected genes are enriched in WNT signaling, Cell cycle/protein kinase activity and chromatin modifying enzymes. Collectively, the results support the variability of transcriptomic signatures and genetic lesions between RS and CLL. Conclusion: This study revealed a noticeable heterogeneity in gene expression and genetic variation between RS and CLL, albeit in a small cohort. The vast majority of the DE genes showed elevated expression in C1 containing only RS cases, and these genes are enriched in PI3K-AKT signaling, NOTCH signaling, and RAS/MAPK signaling. The pattern is more pronounced for a subgroup in C1 who were overall less exposed to ibrutinib. For somatic variation, there is a strong tendency of occurrence of recurrent CNAs towards C2 cohort, mainly involving gains of chr17q and deletions of chrXp11. Given these advances we are encouraged to further pursue the genetic abnormalities with defined roles in aggressive and transformed CLL. Disclosures 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. Parikh:Genentech: Honoraria; Ascentage Pharma: Research Funding; AbbVie: Honoraria, Research Funding; Verastem Oncology: Honoraria; Pharmacyclics: Honoraria, Research Funding; GlaxoSmithKline: Honoraria; Merck: Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Wang:Incyte: Research Funding; Innocare: Research Funding; Novartis: Research Funding. Kenderian:Gilead: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; MorphoSys: Research Funding; Lentigen: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Mettaforge: Patents & Royalties; BMS: Research Funding; Tolero: Research Funding; Sunesis: Research Funding; Juno: Research Funding; Kite: Research Funding. Kay:Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Theraputics: 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; 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; MEI Pharma: Research Funding; Acerta Pharma: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Bristol Meyer Squib: 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; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:Astra Zeneca: Research Funding; DTRM: Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees; 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; 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; Abbvie: Research Funding.

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.

Introduction: Chronic Lymphocytic Leukemia (CLL) is characterized by the accumulation of mature-appearing malignant lymphocytes (CLL B-cells) in the blood, marrow, lymph nodes, and spleen. Despite improved outcome with the introduction of novel BCR and BCL-2 inhibitors, disease progression is still a therapeutic challenge from either differential responses or acquired drug resistance. Recent studies in CLL reported alterations of the epigenetic landscape as well as mutations of genes encoding key chromatin machineries. These aberrant chromatin structures may provide novel therapeutic targets for CLL. Here, we identify aberrant chromatin features in CLL B-cells as novel therapeutic targets. Methods: Histones were extracted by acid from B cells derived from 10 random selected CLL patients and 10 normal donors and histone modifications were checked by western blot. For ChIP-seq study, published H3K27me3 ChIP-seq data (GSE113336) were downloaded from and analyzed (Control samples, n= 6; CLL samples, n=16). Gene ontology analysis used the Panther Classification System. Cell Survival was determined by CellTiter 96® AQueous Assay (Promega). Results: While most histone modifications do not vary between CLL and controls, H3K27me3 and H3.3S31ph are increased and decreased respectively, albeit variably, in CLL B-cells (Fig1. A and B). Notably, the low level of H3.3S31ph was observed in a subset of samples (7 of 10 CLL samples tested). To further investigate the biology and role of H3K27me3 in CLL, we analyzed its genome-wide distribution by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Our analysis showed that the genes with increased H3K27me3 occupancy were mostly enriched in tumor suppression pathways (e.g., negative regulation of PI3K-Akt pathway) or down-regulated genes in CLL such as genes involved in the pro-apoptotic pathway (FAS) (Fig1. C and D). These results suggested that high enrichment of H3K27me3 may regulate the expression of these genes, contributing to CLL survival. H3K27 methylation, an important suppressive histone modification that is associated with transcription repression, is catalyzed by Polycomb Repressive Complex 2 (PRC2). Therefore, inhibition of Enhancer of Zeste Homolog 2 (EZH2), the catalytic subunit of PRC2, could be explored as a therapy approach in CLL. However, feedback activation of H3K27 acetylation (H3K27ac) can promote expression of pro-survival genes that confers EZH2 inhibitor (EZH2i) resistance, which limits its use in human malignancy. Thus, the epigenetic determinants that reliably overcome EZH2i resistance or sensitize cells to EZH2 inhibition have yet to be identified. As we observed that the CLL B-cells in a subset of CLL patients have low levels of H3.3S31ph, and a recent study showed the importance of H3.3S31ph for the enzymatic activity of p300 to acetylate H3 at lysine 27(Martire S et al., Nat Genet. 2019), we assessed the role of H3.3S31ph in the process of EZH2 inhibitor-mediated H3K27ac. Our results showed that inhibition of H3.3S31ph by CHK1 inhibitor MK-8776 abolished the activation of H3K27ac by EZH2i in MEC1 cells, which represents the patients who have CLL cells with relatively high level H3.3S31ph. However, we did not see a major increase of H3K27ac and H3.3S31ph in primary CLL B-cells with EZH2 inhibition (Fig. 1E), consistent with the relatively low expression of CHK1 protein in these cells (Fig. 1F). Because our data shows the requirement of H3.3S31ph in H3K27ac activation by EZH2 inhibition, we next tested if H3.3S31ph inhibition could overcome H3K27ac induced EZH2 inhibition resistance. We found that suppression of H3.3S31ph by CHK1 inhibitor MK-8776 sensitizes the CLL-like line MEC1 to EZH1/2 inhibition (Fig. 1 G). We then showed that an EZH2 inhibitor, Valemetostat, reduce the survival of the primary CLL B-cells (Fig. 1 H). These results suggest that the low level of H3.3S31ph may provide a therapeutic opportunity for CLL treatment with EZH inhibition. Conclusion: In summary, we have elucidated how epigenetic features in leukemic CLL B-cells (H3K27me3 and H3.3S31ph), can provide novel treatment targets for CLL (Fig. 1 I). Moreover, this study may provide a proof of concept to develop new treatment strategies based on epigenetic vulnerabilities in other hematological malignancies. Disclosures Parikh: GlaxoSmithKline: Honoraria; MorphoSys: Research Funding; Genentech: Honoraria; Ascentage Pharma: Research Funding; AbbVie: Honoraria, Research Funding; TG Therapeutics: Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Verastem Oncology: Honoraria; Merck: Research Funding. Kenderian:Kite: Research Funding; MorphoSys: Research Funding; Tolero: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; BMS: Research Funding; Gilead: Research Funding; Juno: Research Funding; Lentigen: Research Funding; Mettaforge: Patents & Royalties; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Sunesis: Research Funding. Ding:Beigene: Membership on an entity's Board of Directors or advisory committees; 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; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra Zeneca: Research Funding; DTRM: Research Funding; Abbvie: Research Funding. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Kay: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; 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; MEI Pharma: Research Funding; Abbvie: Research Funding; Pharmacyclics: 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; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding.

Abstract Background: The four most commonly-mutated genes in clear cell renal cell carcinoma (ccRCC) tumors are BAP1, PBRM1, SETD2 and VHL. And, there are currently 14 known RCC germline variants that have been reproducibly shown to be associated with RCC risk. However, the association of germline genetics with tumor genetics and clinical aggressiveness are unknown.Methods: We analyzed 420 ccRCC patients from The Cancer Genome Atlas (TCGA). Molecular subtype was determined based on acquired mutations in BAP1, PBRM1, SETD2 and VHL. Aggressive subtype was defined clinically using Mayo SSIGN score and molecularly using the ccA/ccB gene expression subtype. Publically-available Hi-C data were used to link germline risk variants with candidate target genes. Results: The 8q24 variant rs35252396 was significantly associated with VHL mutation status (OR=1.6, p=0.0037) and SSIGN score (OR=1.9, p=0.00094), after adjusting for multiple comparisons. We observed that, while some germline variants have interactions with nearby genes, some variants demonstrate long-range interactions with target genes.Conclusions: These data further demonstrate the link between rs35252396, HIF pathway and ccRCC clinical aggressiveness, providing a more comprehensive picture of how germline genetics and tumor genetics interact with respect to tumor development and progression.

Abstract Background The four most commonly-mutated genes in clear cell renal cell carcinoma (ccRCC) tumors are BAP1 , PBRM1 , SETD2 and VHL . And, there are currently 14 known RCC germline variants that have been reproducibly shown to be associated with RCC risk. However, the association of germline genetics with tumor genetics and clinical aggressiveness are unknown. Methods We analyzed 420 ccRCC patients from The Cancer Genome Atlas (TCGA). Molecular subtype was determined based on acquired mutations in BAP1 , PBRM1 , SETD2 and VHL . Aggressive subtype was defined clinically using Mayo SSIGN score and molecularly using the ccA/ccB gene expression subtype. Publically-available Hi-C data were used to link germline risk variants with candidate target genes. Results The 8q24 variant rs35252396 was significantly associated with VHL mutation status (OR=1.6, p=0.0037) and SSIGN score (OR=1.9, p=0.00094), after adjusting for multiple comparisons. We observed that, while some germline variants have interactions with nearby genes, some variants demonstrate long-range interactions with target genes. Conclusions These data further demonstrate the link between rs35252396, HIF pathway and ccRCC clinical aggressiveness, providing a more comprehensive picture of how germline genetics and tumor genetics interact with respect to tumor development and progression.

Abstract Adenosquamous cancer of the pancreas (ASCP) is a subtype of pancreatic cancer that has a worse prognosis and greater metastatic potential than the more common pancreatic ductal adenocarcinoma (PDAC) subtype. To distinguish the genomic landscape of ASCP and identify actionable targets for this lethal cancer, we applied DNA content flow cytometry to a series of 15 tumor samples including five patient-derived xenografts (PDX). We interrogated purified sorted tumor fractions from these samples with whole-genome copy-number variant (CNV), whole-exome sequencing, and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) analyses. These identified a variety of somatic genomic lesions targeting chromatin regulators in ASCP genomes that were superimposed on well-characterized genomic lesions including mutations in TP53 (87%) and KRAS (73%), amplification of MYC (47%), and homozygous deletion of CDKN2A (40%) that are common in PDACs. Furthermore, a comparison of ATAC-seq profiles of three ASCP and three PDAC genomes using flow-sorted PDX models identified genes with accessible chromatin unique to the ASCP genomes, including the lysine methyltransferase SMYD2 and the pancreatic cancer stem cell regulator RORC in all three ASCPs, and a FGFR1-ERLIN2 fusion associated with focal CNVs in both genes in a single ASCP. Finally, we demonstrate significant activity of a pan FGFR inhibitor against organoids derived from the FGFR1-ERLIN2 fusion–positive ASCP PDX model. Our results suggest that the genomic and epigenomic landscape of ASCP provide new strategies for targeting this aggressive subtype of pancreatic cancer. Significance: These data provide a unique description of the ASCP genomic and epigenomic landscape and identify candidate therapeutic targets for this dismal cancer.

Abstract Immune dysfunction is a hallmark of CLL/MBL; ~25% individuals with newly diagnosed CLL have hypogammaglobulinemia at diagnosis. In this study of newly diagnosed CLL/MBL, we sought to a) investigate the association between serum immunoglobulins and specific mutations identified by next generation sequencing, and b) determine if serum immunoglobulin levels predict TFT, independent of the CLL-International Prognostic Index (CLL-IPI) and tumor mutational load (TML). We used the Mayo Clinic CLL Resource to identify newly diagnosed CLL/MBL individuals consented within 2 years of diagnosis. Baseline clinical characteristics and the CLL-IPI score was ascertained on all individuals. DNA was extracted from peripheral blood CD5+/CD19+ clonal B-cells; and the entire coding regions of 60 somatically recurring mutated CLL driver genes were enriched using a customized Agilent SureSelect gene panel and sequenced in Illumina Hiseq4000. Serum immunoglobulins were quantitated by radial immunodiffusion using Immunoplates. The relationship between serum immunoglobulins was assessed: a) with individual gene mutations (mutated vs. not); and b) using the TML score (using a value of 0, 1, and 2 or greater [2+] mutated genes). The impact of serum immunoglobulin levels on TFT was analyzed for all individuals. Of 356 individuals identified, 80 (22%) had MBL, median age was 63 years (28-87), 261 (73%) were male, and the CLL-IPI distribution was: low risk (n=149, 42%), intermediate risk (n=112, 32%), and high/very high risk (n=94, 26%). We observed 43%, 39%, and 18% individuals with 0, 1, or 2+ mutated genes, respectively. The most commonly mutated genes were NOTCH1 (13%), SF3B1 (13%), TP53 (8%), ATM (8%), BIRC3 (7%), and NFKBIE (7%). Using standard cutoffs, 135 (38%) individuals had low serum IgG, 73 (21%) had low serum IgA, and 154 (44%) had low serum IgM at diagnosis. There were no differences in individual gene mutation frequencies between individuals with low and normal serum IgG. In contrast, individuals with low serum IgA were more likely to have mutations in NOTCH1 (25% vs 10%) and ATM (14% vs 7%) compared to those with normal IgA, and individuals with low serum IgM were more likely to have mutations in NOTCH1 (19% vs 9%) and BIRC3 (11% vs 4%) compared to those with normal IgM (all p-values <0.05). There were no significant differences in individuals with low serum IgG based on TML scores of 0, 1, and 2+ (31%, 35%, 40%, respectively, p=0.28). However, individuals with low serum IgA and low serum IgM were more likely to have a higher TML (8%, 20%, 36% for IgA, p<0.0001; and 35%, 45%, 54% for IgM, p<0.0001, for TML scores of 0, 1, and 2+, respectively). After a median follow-up of 6.9 years, 157 individuals required CLL therapy. After adjusting for CLL-IPI and TML, low serum IgG, low serum IgA, and low serum IgM (hazard ratio [HR]: 1.8, 2.3, and 2.4, respectively, all p-values <0.05) were independently associated with a shorter TFT. Our study shows that individuals with CLL/MBL who harbor mutations in NOTCH1, ATM and BIRC3 are more likely to have low serum IgA and IgM at diagnosis. Serum IgA and IgM (but not serum IgG) levels decrease with an increase in the TML score. Finally, low serum immunoglobulins can predict TFT, independent of the CLL-IPI and TML, which has important implications for risk stratification in newly diagnosed CLL/MBL. Citation Format: Sameer A. Parikh, Cristine Allmer, Geffen Kleinstern, Nicholas J. Boddicker, Shulan Tian, Cecilia B. De Campos, Laura A. Bruins, Daniel R. o"brien, Brian F. Kabat, Kari G. Rabe, Aaron D. Norman, Huihuang Yan, Xing Li, Timothy G. Call, Wei Ding, Jose F. Leis, Saad J. Kenderian, Celine M. Vachon, James R. Cerhan, Neil E. Kay, Susan L. Slager, Esteban Braggio. Serum immunoglobulins are an independent prognostic marker of time to first therapy in newly diagnosed chronic lymphocytic leukemia (CLL) and monoclonal B-cell lymphocytosis (MBL) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6466.

Abstract Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in western countries that has a strong genetic basis. Using data from both chromatin immunoprecipitation and sequencing (ChIP-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq), recent studies have uncovered alterations of chromatin landscape in CLL. However, the spectrum of epigenetic changes and the mechanisms of casualtyare only partially understood. In this study, we used ATAC-seq to profile chromatin accessibility across the two major CLL subtypes, IGHV-mutated (n=19) and IGHV-unmutated (n=22). DNA library of accessible chromatin regions was generated from purified CD5+/CD19+ leukemiacells. All libraries were assessed to have high data quality based on the ENCODE quality metrics. Additionally, publicly available ATAC-seq data (GSE118189 and GSE111015) from total (n=5), memory (n=6) and naïve B cells (n=6) were analyzed in parallel and used as normal reference. ATAC-seq peaks from CLL and normal B cells were merged to generate a consensus list of 107,928 high-confidence peaks that did not overlap ENCODE blacklisted regions, were present in at least two CLL or two normal B-cell samples, and had ≥1 counts-per-million in at least 10% of the samples. Raw read counts were Trimmed Mean of M-values normalized and log2 transformed. K-means clustering of differential peaks revealed an extensive reprogramming of chromatin accessibility landscape in CLL, with over 11,000 lost and nearly 9,000 gained open chromatin regions relative to normal B-cells. In particular, we identified two clusters comprising 1,401 regions that were largely open either in IGHV-mutated(571 peaks) or in IGHV-unmutated CLL (830 peaks). Open chromatin regions gained in IGHV-mutatedwere preferentially linked to genes in the B cell receptor signaling pathway and those in IGHV-mutatedto genes enriched in the interferon type I signaling pathway. These discriminatory regions are highly enriched with DNA binding motifs for transcription factors (TFs) with key roles in B cell development, such as PU.1, AP-1, c-Jun, BATF, and TCF family. In addition, 94% of the 1,401 peaks were located in distal regulatory regions, being ≥2.5 kb away from transcription start sites of genes; two-third of these distal regulatory regions overlapped H3K27ac peaks from CLL patients or immune cell types in the Roadmap reference epigenomes,indicating that enhancers are the prime sites of epigenetic differentiation between the two subtypes. Together, our analyses provide new insights into the global alterations of regulatory regions in CLL. Given the noticeable heterogeneity of chromatin landscape, further integration with histone modifications, TF binding, chromatin interaction, gene expression and genetic variation data are needed to understand the roles of epigenetic dysregulation and its interaction with genetic lesions in CLL pathogenesis. Citation Format: Huihuang Yan, Zhiquan Wang, Shulan Tian, Geffen Kleinstern, Nicholas Boddicker, Xing Li, Susan Slager, Esteban Braggio. Widespread alterations of chromatin accessibility in chronic lymphocytic leukemia (CLL) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1256.