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Abstract An ongoing outbreak of Coronavirus Disease 2019 (COVID-19) has spread around the world. However, the clinical characteristics and outcomes of patients with COVID-19 related to different modes of exposure have not been well defined. We aimed to explore the clinical features and outcomes of COVID-19 related to one-time community exposure versus continuous household exposure. Retrospective case–control study involving COVID-19 patients admitted to a tertiary designated center in China was performed. Patients were enrolled if they had known exposure history of one-time community exposure or continuous household exposure. Twenty patients were compared in terms of demographic characteristics, clinical presentation, chest CT images, laboratory results, treatments, and clinical outcomes at 1-month follow-up. There were 10 patients in one-time community and continuous household exposure groups respectively. Males compromised 80% and 40% while the median ages were 37.5 and 51 years old in the 2 groups, respectively. Fever and cough were most common symptoms. Ground-glass opacities were presented on chest CT scan in 90% and 70% of the patients, and the median CT scores were 7 and 16 on admission, respectively. Three patients ranked severe in the community exposure group while 7 patients were severe or critical in household exposure group. On 1-month follow-up, all patients were improved clinically but COVID-19 IgG antibody detected positive. Median follow-up CT scores were 0 and 13 while pulmonary function test abnormalities were 0/9 and 2/7 in the 2 groups, respectively. COVID-19 patients with one-time community exposure tended to be mild in severity and had better outcomes, comparing to those with continuous household exposure.

Abstract Background: Cetuximab, an EGFR inhibitor used to treat multiple cancer types, including colon cancer, causes severe skin toxicity in 5%–20% of patients, leading to decreased quality of life and treatment delays. Our understanding of which patients have an increased risk of severe toxicities is limited. We conducted a genome-wide association study to identify germline variants predictive of cetuximab-induced severe skin toxicity. Methods: Our study included 1,209 patients with stage III colon cancer randomized to receive cetuximab plus 5-fluorouracil and oxaliplatin as part of the NCCTG N0147 (Alliance) clinical trial. Skin toxicity outcomes were collected using the Common Toxicity Criteria for Adverse Events version 3.0. We performed genotyping, evaluating approximately 10 million genetic variants. We used logistic regression to evaluate the association of each genetic variant and severe (grade ≥ 3) skin toxicity, adjusting for age, sex, and genetic ancestry. Genome-wide significance was defined as P < 5 × 10−8. Results: Participants were predominantly middle-aged white men; 20% (n = 243) experienced severe skin toxicity. Two genetic variants in the retinoic acid receptor alpha (RARA) gene were significantly associated with severe skin toxicity [OR, 3.93; 95% confidence interval (CI), 2.47–6.25; P < 7.8 × 10−9]. Functional annotations indicate these variants are in the RARA promoter. Additional significantly associated variants were identified in chromosome 2 intergenic regions. Conclusions: Identified variants could represent a potential target for risk stratification of patients with colon cancer receiving cetuximab. Impact: Retinoids have shown promise in the treatment of cetuximab-induced skin toxicity, so follow-up work could evaluate whether individuals with the RARA variant would benefit from retinoid therapy.

Background: Increased parasympathetic activity is thought to play important roles in syncope events of patients with vasovagal syncope (VVS). However, direct measurements of the vagal control are difficult. The novel deceleration capacity (DC) of heart rate measure has been used to characterize the vagal modulation. This study aimed to assess vagal control in patients with VVS and evaluate the diagnostic value of the DC in VVS. Methods: Altogether, 161 consecutive patients with VVS (43±15 years; 62 males) were enrolled. Tilt table test was positive in 101 and negative in 60 patients. Sixty-five healthy subjects were enrolled as controls. DC and heart rate variability in 24-hour ECG, echocardiogram, and biochemical examinations were compared between the syncope and control groups. Results: DC was significantly higher in the syncope group than in the control group (9.6±3.3 versus 6.5±2.0 ms, P <0.001). DC was similarly increased in patients with VVS with a positive and negative tilt table test (9.7±3.5 and 9.4±2.9 ms, P =0.614). In multivariable logistic regression analyses, DC was independently associated with syncope (odds ratio=1.518 [95% CI, 1.301–1.770]; P =0.0001). For the prediction of syncope, the area under curve analysis showed similar values when comparing single DC and combined DC with other risk factors ( P =0.1147). From the receiver operator characteristic curves for syncope discrimination, the optimal cutoff value for the DC was 7.12 ms. Conclusions: DC>7.5 ms may serve as a good tool to monitor cardiac vagal activity and discriminate VVS, particularly in those with negative tilt table test.

Background and Aims During liver fibrosis, liver sinusoidal endothelial cells (LSECs) release angiocrine signals to recruit inflammatory cells into the liver. p300, a master regulator of gene transcription, is associated with pathological inflammatory response. Therefore, we examined how endothelial p300 regulates angiocrine signaling and inflammation related to portal hypertension and fibrogenesis. Approach and Results CCl4 or partial inferior vena cava ligation (pIVCL) was used to induce liver injury. Mice with LSEC‐specific p300 deletion (p300 LSECΔ/Δ) or C‐C motif chemokine ligand 2 (Ccl2) deficiency, nuclear factor kappa B (NFκB)–p50 knockout mice, and bromodomain containing 4 (BRD4) inhibitors in wild‐type mice were used to investigate mechanisms of inflammation regulation. Leukocytes were analyzed by mass cytometry by time‐of‐flight. Epigenetic histone marks were modified by CRISPR endonuclease‐deficient CRISPR‐associated 9‐fused with the Krüppel associated box domain (CRISPR‐dCas9‐KRAB)–mediated epigenome editing. Portal pressure and liver fibrosis were reduced in p300 LSECΔ/Δ mice compared to p300 fl/fl mice following liver injury. Accumulation of macrophages was also reduced in p300 LSECΔ/Δ mouse livers. Ccl2 was the most up‐regulated chemokine in injured LSECs, but its increase was abrogated in p300 LSECΔ/Δ mice. While the macrophage accumulation was increased in NFκB‐p50 knockout mice with enhanced NFκB activity, it was reduced in mice with LSEC‐specific Ccl2 deficiency and mice treated with specific BRD4 inhibitors. In vitro, epigenome editing of CCL2 enhancer and promoter regions by CRISPR‐dCas9‐KRAB technology repressed TNFα‐induced CCL2 transcription through H3K9 trimethylation. In contrast, TNFα activated CCL2 transcription by promoting p300 interaction with NFκB and BRD4, leading to histone H3 lysine 27 acetylation at CCL2 enhancer and promoter regions. Conclusions In summary, endothelial p300 interaction with NFκB and BRD4 increases CCL2 expression, leading to macrophage accumulation, portal hypertension, and liver fibrosis. Inhibition of p300 and its binding partners might serve as therapy in the treatment of liver diseases.

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.

Background: Clinical factors including previous history of AF, heart failure, hypertension, valvular heart disease, increased age and male gender increase the risk of AF in CLL patients (Shanafelt, Leukemia and Lymphoma 2017). Treatment with Bruton tyrosine kinase inhibitors (BTKi) such as ibrutinib has also been associated with an increased risk of AF in CLL. We evaluated the role of artificial intelligence electrocardiography (AI-ECG) in predicting ibrutinib-induced AF (and, for reference, AF unrelated to ibrutinib) in patients with CLL. Methods: We identified two cohorts of CLL patients using the Mayo Clinic CLL Database. Cohort 1 included patients evaluated within 12 months of CLL diagnosis who did not ever receive ibrutinib. Cohort 2 included patients who were treated with ibrutinib. The electrocardiographic signature of AF in sinus rhythm was detected by an AI-ECG algorithm previously developed using a convolutional neural network (Attia, Lancet 2019). The baseline AI-ECG AF score (positive defined as &gt;0.10 on a scale of 0-1 which offers best balance between sensitivity and specificity per Attia et al.) was computed based on ECGs obtained within 10 years prior to CLL diagnosis (Cohort 1) or 10 years prior to initiation of ibrutinib therapy (Cohort 2). Patients with AF at baseline, missing data, or with ECGs previously used to train the AI algorithm were excluded. Reverse Kaplan Meier diagrams were plotted for both cohorts grouped by AI-ECG positivity. Cox proportional hazards were fitted to assess the predictive ability of AI-ECG in both cohorts. Results: After screening 2,739 patients and applying exclusion criteria (126 patients had baseline AF) a total of 1,149 patients with median 4 (interquartile range [IQR] 2-9) baseline ECGs were included in the analysis (Figure 1A). Cohort 1 included 951 patients with a median follow up of 3.0 (IQR 0.6-7.0) years and positive baseline AI-ECG in 546 (57%) patients. Cohort 2 included 198 patients with a median follow up of 1.6 (IQR 0.7-3.2) years and positive baseline AI-ECG in 91 (46%) patients. In Cohort 1, the median age was 67 years (IQR 58-72), 681 (72%) of patients were men, 68% had low/intermediate risk CLL-International Prognostic Index (IPI), and 32% had high/very high-risk CLL-IPI. In Cohort 2, the median age was 69 years (IQR 62-75), 139 (70%) of patients were men, 13% had low/intermediate risk CLL-IPI, and 87% had high/very high-risk CLL-IPI. AF occurred during follow up in 164 patients (17%) in Cohort 1 and 46 patients (23%) in Cohort 2. In both Cohorts 1 and 2, a positive baseline AI-ECG significantly increased the incidence of AF during follow up (log rank &lt;0.001) (Figure 1B and C). Hazard ratios (for positive vs. negative AI-ECG) were 33.9 (95% confidence interval [CI] 15.0-76.6) for Cohort 1 and 14.8 (95% CI 5.3-41.3) for Cohort 2. Conclusion: The addition of AI to a standard 12-lead ECG obtained during normal sinus rhythm - an inexpensive and ubiquitous test - predicts the occurrence of future AF in patients with CLL. This holds true irrespective of BTKi -based therapy and has important implications for the management of CLL patients. Disclosures Ding: Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; DTRM: Research Funding; 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. Kenderian:BMS: Research Funding; Gilead: Research Funding; Novartis: Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties; Juno: Research Funding; MorphoSys: Research Funding; Lentigen: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; Kite: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Torque: Consultancy. Wang:Novartis: Research Funding; Innocare: Research Funding; Incyte: 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; 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. Kapoor:Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Celgene: Honoraria; GlaxoSmithKline: Research Funding. Parikh:MorphoSys: Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; TG Therapeutics: Research Funding; Pharmacyclics: Honoraria, Research Funding.

Heparin-induced thrombocytopenia (HIT) is a serious reaction to heparin treatment characterized by antibodies that recognize a complex formed between heparin and platelet factor 4 (PF4/H) and are capable of activating platelets and inducing a pro-thrombotic state. Although a high percentage of heparin-treated patients produce antibodies to PF4/H, only a subset of these antibodies are platelet-activating (pathogenic) and capable of causing HIT. We previously reported that we cloned B cells from six patients experiencing HIT and identified two types of PF4/H-binding antibodies: seven platelet-activating (PA) and 48 non-activating (NA). Comparison of the structural features in the PA, NA, and non PF4/H-binding (NB) clones showed that the length and the number of basic amino acid and tyrosine residue in the heavy chain complementarity determining region 3 (HCDR3) were significantly different, and was in the order of PA&gt;NA&gt;NB. Most significantly, the seven platelet-activating antibodies each have one of the two pathogenic motifs: RX1-2 R/KX1-2 R/H and YYYYY in an unusually long HCDR3 (≥ 20 residues). In the current study, we attempt to understand the origin of the B cells that produce the PA and NA antibodies and the nature of the immune response in HIT through analyzing somatic hypermutation and biological property of such antibodies. Longer HCDR3 and more basic Aas and Tyr residues in the HCDR3 are features of autoreactive and polyreactive antibodies. With this in mind, we tested PA and NA clones in a standard antinuclear antibody (ANA) assay and found that these clones were significantly more reactive than NB antibodies, and the plasma of HIT patients were significantly more reactive than normal plasma (Figure1). We then compared reactions of PA, NA and NB clones against a group of self and foreign antigens commonly used in polyreactivity assays: dsDNA, ssDNA, LPS, insulin, and keyhole limpet hemocyanin (KLH). About 90% of PA and NA clones were reactive to at least two antigens, this was true of only 20% of the NB clones, and the latter is consistent with the frequency of polyreactive clones in the IgG+ B cells (Figure2). Taken together, these data indicate that PA and NA antibodies are largely polyreactive. We then investigated the development of the PA and NA B cells through analyzing somatic hypermutation in the antibodies. Through analyzing the HCDR3 nucleotide insertion, trimming and VDJ segment usage, we found that longer HCDR3 typical of PF4/H-binding clones and the RKH and Y5 motifs identified in PA clones were the result of original recombination not somatic hypermutation. Consistently, the average number of nucleotide mutations in the VH genes of the binding clones was lower (PA and NA, 9.4 ± 9.5) compared to that of peripheral blood IgG+ memory B cells in healthy subjects (~18) (Figure3). Total mutation frequency in the VH and Vk CDRs of the PF4/H-binding PA and NA clones was comparable to that of the framework regions. This finding contrasts with findings made in peripheral blood IgG+ memory B cells of healthy subjects showing that the mutation frequencies are much higher in the CDRs than in the FRs of VH. Taken together, these findings suggest that affinity maturation plays a limited role in the evolution PF4/H-binding antibodies during the immune response that leads to HIT. In this study, we showed thay PF4/H-binding PA and NA IgGs are largely polyreactive antibodies and contain lower levels of mutations compared to IgG+ memory B cells. B1 and MZ B cells are innate B cells that are main producers of polyreactive natural antibodies and can respond to toll-like receptor signaling, quickly differentiate into antibody-secreting cells, and undergo IgG class switch extrafollicularly. Polyreactivity identified in the PF4/H-binding PA and NA IgGs supports the possibility that human B cells producing PF4/H-binding antibodies are innate B cells akin to MZ B cells shown to be a source of PF4/H antibodies in mice. A mutation rate lower than that of IgG+ memory cells in the PF4/H-binding IgGs is also consistent with an extrafollicular response typical of innate B cells. These observations would help to improve our understanding of the immunological responses and B cell origin in HIT patients. Disclosures Padmanabhan: Retham Technologies: Current equity holder in private company; Veralox Therapeutics: Membership on an entity's Board of Directors or advisory committees; Versiti Blood Research Institute: Patents & Royalties.

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 T-cell prolymphocytic leukemia (T-PLL) is a rare, aggressive malignancy of mature T-cells. Although responses may been seen with initial alemtuzumab-based therapy, relapse is inevitable and relapsed/refractory disease carries a dismal prognosis. T-PLL has shown in vitro sensitivity to venetoclax, and short-lived clinical responses to venetoclax monotherapy (Smith, Blood Advances 2020; Boidol, Blood 2017) or when given in combination with pentostatin (Alfayez, Leukemia & Lymphoma 2020). Given the lack of standard treatment options, we reviewed the outcomes of patients (pts) with relapsed T-PLL on venetoclax-based therapy. METHODS Using an institutional clinical database of pts with T-PLL seen in the Division of Hematology at Mayo Clinic, Rochester, MN, all pts treated with venetoclax or venetoclax-based therapies in a relapsed/refractory setting were identified. Clinical, laboratory, and pathology data, as well as treatment dosing and toxicity were ascertained retrospectively from the medical records. Diagnostic criteria and response definitions were utilized as per the T-PLL International Study Group (Staber, Blood 2019). RESULTS Between 8/2017 and 5/2020, 9 pts with relapsed/refractory T-PLL treated with venetoclax were identified. The median age was 63 years (range 49-75), and one-third were male. Baseline characteristics are detailed in Table 1. Rearrangement of TCL1 family genes was present in all 8 pts evaluated with fluorescence in situ hybridization (FISH). Using conventional cytogenetics, a complex karyotype was present in 4/6 pts tested. The median prior lines of therapy was 3 (range 1-4), including alemtuzumab in 8 of 9 pts (intravenous 7/8); and two pts had undergone prior hematopoietic stem cell transplantation (1 allogeneic; 1 autologous) after achieving a complete remission. Additional individual pt details are included in Table 2. Prior to venetoclax therapy initiation, 2 pts had B-symptoms (2 night sweats; 1 fever) and 6 pts had an ECOG score ≥ 2. Lymphadenopathy and splenomegaly were present in 6 and 9 pts, respectively. Extranodal involvement included 3 pts with cutaneous involvement and 5 pts with effusions (4 ascites; 1 pleural). The target maximum dose of venetoclax (800 mg [n=4]; 400 mg [n=1]) was reached by 5 pts at a median of 12 days (range 7-40 days). The other 4 pts had disease progression after a median of 10 days (range 5-22 days) during the dose ramp-up, including 2 pts undergoing rapid dose escalation. Altogether, 6 of the 9 pts initiated venetoclax with a rapid dose escalation. Bendamustine was given with venetoclax in 5/9 pts; median number of cycles 1 (range 1-4) with variable starting dosing (range 60-100 mg/m2). The disease control rate was 56%; best response was partial remission (PR) in 4 (44%) pts and stable disease (SD) in 1 (11%) pt. The 1 pt with SD received venetoclax monotherapy; however, the overall response rate among pts who received the combination of venetoclax and bendamustine was 80% (4/5 pts). One pt with a partial remission met all criteria for complete remission but did not have a confirmatory bone marrow biopsy. Cutaneous disease improved in 2 of 3 pts (both with PR as best response), and effusions improved in 2 of 5 pts (1 PR and 1 SD as best response). Among those in PR, the median decrease in absolute lymphocyte count was 67x109/L and the median decrease in lactate dehydrogenase was 1,162 U/L (normal range 122-222 U/L). Median duration of treatment for all pts was 42 days (range 4-201 days). All pts ultimately died during follow-up with a median overall survival of 53 days (range 4-464 days); Figure 1. All pts experienced at least one adverse event and 8 of 9 pts had a grade ≥ 3 toxicity, most commonly edema (n=7) and neutropenia (n=6). Five pts required dose interruptions due to neutropenia (n=3), tumor lysis syndrome (n=1), and edema (n=1). Three pts had dose reductions, all from 800 mg dosing, due to hematologic toxicity (n=2) and nausea (n=1). No pts discontinued venetoclax as a result of adverse events. CONCLUSION Treatment of pts with relapsed/refractory T-PLL remains a significant unmet need. The 9 pts described herein represent the largest cohort of pts treated with venetoclax-based therapy in this setting to the current date. Despite initial reports of clinical efficacy, our results show that venetoclax (with or without bendamustine) has modest efficacy in the treatment of relapsed/refractory T-PLL after prior alemtuzumab exposure. Disclosures Parikh: TG Therapeutics: Research Funding; Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; AbbVie: Honoraria, Research Funding; Genentech: Honoraria; Merck: Research Funding; MorphoSys: Research Funding; Pharmacyclics: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Ascentage Pharma: Research Funding; AstraZeneca: Honoraria, Research Funding. Shah:Dren Bio: Consultancy. Bennani:Verastem: Other: Advisory Board; Affimed: Research Funding; Purdue Pharma: Other: Advisory Board; Kite/Gilead: Research Funding. Wang:Incyte: Research Funding; Novartis: Research Funding; Innocare: Research Funding. Kenderian:MorphoSys: Research Funding; Lentigen: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Sunesis: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties. Kay:MEI Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Cytomx: 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; 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; Rigel: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: 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; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees. Ding:Octapharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: 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; DTRM: Research Funding; Abbvie: Research Funding. OffLabel Disclosure: Venetoclax: off-label use in treatment of relapsed/refractory T-cell prolymphocytic leukemia

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 &lt;=0.05 and fold-change &gt;=2. Somatic mutations and copy number alternations (CNAs) were identified through Mutect2 and PatternCNV, respectively. CN loss was defined to have log2(ratio) &lt;=-0.93 and CN gain to have log2(ratio) &gt;= 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 &gt;1 year before biopsy, and case S025 was treated for &lt; 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.