Citations

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 Nearly 20% of patients (pts) are ≥ 80 years (yrs) of age at the time of CLL diagnosis. Increased medical comorbidities, as well as declining functional status and organ function, often accompany advanced age. However, clinical trials often enroll a disproportionally low number of people from this age demographic due to stringent eligibility parameters, which provides limited evidence to guide decisions. Here, we report clinical characteristics and outcomes of pts ≥ 80 yrs of age at the time of CLL diagnosis. METHODS Between 1/1995 and 3/2020, we identified previously untreated CLL pts from the Mayo Clinic CLL Database who were ≥ 80 yrs of age at the time of CLL diagnosis, and seen within 3 yrs of diagnosis. Baseline characteristics, treatments administered, and time to first treatment (TFT) were analyzed for all pts. Overall survival (OS) was measured from diagnosis date in all pts and separately from treatment date for treated pts. Time to next treatment (TTNT) was measured in treated pts from first treatment date to date of second treatment or last known treatment. TFT and TTNT were analyzed accounting for competing risk of death. Standardized mortality ratio (SMR) compared observed survival to survival in a Minnesota population. Cox multivariable regression models were used to determine which factors were associated with OS (treatment as a time-dependent covariate) and TTNT (accounting for competing risk of death). RESULTS Among the 213 pts identified, the median age was 83 yrs (range 80-97); baseline characteristics are summarized in Table 1. The median number of medical comorbidities among all pts was 4 (range 0-8). At least 1 comorbidity was present in 97% of pts, most commonly hypertension (57%), genitourinary (n=48%), rheumatological (46%), and dyslipidemia (n=43%). Median follow-up was 3.8 yrs. A total of 56 pts received treatment and the median TFT was 6.7 yrs. Over this 25 year interval, the treatment approaches included monoclonal antibody alone (n=17), chemotherapy alone (n=17), or chemoimmunotherapy (n=14), novel agents (n=3), and multi-agent Richter's transformation regimens (n=5). Chlorambucil-based treatments (chlorambucil n=13, chlorambucil, prednisone n=3) were the most frequently used chemotherapy regimens. The most common chemoimmunotherapy regimens included rituximab, cyclophosphamide, prednisone (RCP) with (n=3) or without vincristine (n=6), and chlorambucil with an anti-CD20 monoclonal antibody (n=4; obinutuzumab n=2, rituximab n=2). Among 17 pts who received monoclonal antibody alone, treatments included rituximab alone (n=11), rituximab plus methylprednisolone (n=2), obinutuzumab (n=2), and rituximab with alemtuzumab (n=2). Frontline novel agent treatments included ibrutinib alone (n=1), acalabrutinib alone (n=1), and ibrutinib, obinutuzumab, venetoclax (n=1). Five pts with Richter's transformation (diagnosed concurrent with CLL n=4) received multi-agent chemotherapy. Among the 56 treated pts, 22 pts received second line therapy after a median TTNT of 2.8 yrs from start of first therapy. The most common second line treatments were chlorambucil-based (n=6) and rituximab-based (n=6) regimens. Age, sex, absolute lymphocyte count, del17p, and unmutated IGHV were not predictive of TTNT. The median OS among all 213 pts was 4.6 yrs. SMR was 1.2 (p=0.008) when excluding pts with Richter's transformation. In univariable analyses, receipt of therapy (HR 3.92, 95%CI 2.11-7.28; p<0.001), age (per 5 year increase; HR 1.84, 95%CI 1.43-2.38; p<0.001) and unmutated IGHV (HR 2.03, 95%CI 1.12-3.67; p=0.02) were predictors of shorter OS. The OS among pts who received treatment (Figure 1) was similar when compared across time periods of treatment start year grouped as 1995-2001 (n=10), 2002-2013 (n=32), and 2014-2020 (n=14). Treatment categories by time period are shown in Table 2. CONCLUSIONS In this study of 213 pts ≥ 80 yrs of age at time of CLL diagnosis, the median time to first therapy was ~7 yrs. Although survival outcomes did not differ by era across the 25-year span of this study, pts treated with novel agents were underrepresented and are a patient population which warrants additional evaluation. The finding that pts with CLL in this cohort had a 20% higher risk of death compared to an age- and sex-matched population emphasize the need for ongoing efforts to improve clinical outcomes for CLL pts in this demographic category. Disclosures Kenderian: Torque: Consultancy; Mettaforge: Patents & Royalties; Humanigen: Consultancy, Patents & Royalties, Research Funding; Novartis: Patents & Royalties, Research Funding; Kite: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Sunesis: Research Funding; MorphoSys: Research Funding; Lentigen: Research Funding. Wang:Incyte: Research Funding; Innocare: Research Funding; Novartis: Research Funding. Shanafelt:Genentech, Pharmacyclics LLC, an AbbVie Company, AbbVie, GlaxoSmithKline, and Merck: Research Funding; Mayo Clinic: Patents & Royalties: and other intellectual property. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Kay:Morpho-sys: 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; 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; Rigel: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: 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; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees. Ding: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; Abbvie: Research Funding; Astra Zeneca: Research Funding; 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. Parikh:Merck: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; Pharmacyclics: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; TG Therapeutics: Research Funding.

Background: Cytogenetic abnormalities detected by fluorescence in situ hybridization (FISH) are known to differentially impact prognosis in patients with chronic lymphocytic leukemia (CLL). Deletion6q23 (del6q23) has been reported in ~2-3% of CLL patients at diagnosis; however, its prognostic significance remains indeterminate. Methods: We identified previously untreated CLL patients from the Mayo Clinic CLL Database seen between 1/1995 - 2/2020 who had FISH performed. The clinical characteristics, concomitant cytogenetic abnormalities, time to first therapy (TTFT), and overall survival (OS) were compared between patients with del6q23 to those without this abnormality. TTFT was analyzed from FISH date until treatment or last known untreated date, accounting for competing risk of death. OS was analyzed using Kaplan-Meier methods from FISH date. In a matched (CLL-IPI risk score and sex) analysis, Cox regression analysis was used to determine the association between TTFT/OS and presence of del6q23. The Mayo Clinic IRB approved this study. Results: A total of 3101 CLL patients were identified; their median age at diagnosis was 64 years and 66% were male. Of these patients, 42 (1.3%) had evidence of del6q23 by FISH. Compared to patients without del6q23, patients with del6q23 carried a more adverse clinical and cytogenetic profile at the time of diagnosis including advanced Rai stage (22% Rai III/IV vs. 9% Rai III/IV; P = 0.002), unmutated IGHV genes (91% vs. 43%; P < 0.001), and high/very high risk CLL-IPI (50% vs. 27%; P < 0.001). Del6q23 was the sole abnormality in 13 patients (31%). Of the remaining patients, del6q23 was concomitantly present with del13q in 8 patients (19%), and with either del11q or del17p in 21 patients (50%). Of the 42 patients with del6q23, 29 received first line therapy: chemoimmunotherapy in 16 patients, BTK inhibitor in 7 patients, and an anti-CD20 monoclonal antibody alone in 6 patients. The median follow-up of the entire cohort was 7.3 years. The median TTFT in patients with del6q23 was 0.7 years while the 5-year OS was 76%. Patients with del6q23 demonstrated significantly shorter TTFT and reduced OS when compared to patients without del6q23 (Figures 1A and 1B). The shorter TTFT was also evident for patients with del6q23 compared to patients without del6q23 divided according to the Dohner risk category (Figure 2A), although there was no difference in OS between these groups of patients (Figure 2B). Because del6q23 patients were enriched for other unfavorable prognostic markers, we identified four control patients without del6q23, matched by CLL-IPI risk score and sex, to each treatment-naïve patient with del6q23. Patients with del6q23 showed a borderline statistically significant shorter TTFT (median 0.7 years versus 3.9 years; P = 0.07) and a nonsignificant association with OS (median 10.9 years versus 10.3 years; P = 0.28). Conclusion: Del6q23 by FISH in previously untreated CLL represents an uncommon abnormality. When compared to patients without del6q23, patients with del6q23 tend to have more adverse clinical and cytogenetic profiles at baseline, which likely confer a worse prognosis as reflected by shorter TTFT compared to patients without this abnormality. Figure Disclosures Ding: Merck: Membership on an entity's Board of Directors or advisory committees, 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; Octapharma: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Astra Zeneca: Research Funding. Wang:Novartis: Research Funding; Innocare: Research Funding; Incyte: Research Funding. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Kay:Sunesis: Research Funding; Abbvie: 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; 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; 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; Acerta Pharma: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees. Kenderian:Juno: Research Funding; Gilead: Research Funding; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties; Tolero: Research Funding; BMS: Research Funding. Parikh:Ascentage Pharma: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; TG Therapeutics: Research Funding; Pharmacyclics: Honoraria, Research Funding; GlaxoSmithKline: Honoraria; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria.

Introduction: Multiple myeloma (MM) is a genetically complex and clinically heterogeneous disease. Disease biology and phenotype is heavily influenced by the tumor microenvironment and the interaction between the immune milieu and malignant plasma cell population. Understanding the molecular profile of tumor along with the immune ecosystem can provide insights into key pathways that are important in disease pathobiology. Therefore, in this study, we have used single-cell RNA-Seq (scRNA-Seq) to compare the detailed maps of the bone marrow microenvironment of patients with rapid progressing disease (PFS < 18 months) with those whose disease had not progressed at the time of analysis (PFS < 4 years) Methods: MM patients (n=18) with rapid and no progression were identified from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, a longitudinal genomic study of patients with newly diagnosed, active multiple myeloma (NCT01454297). To generate a robust scRNA-Seq profile with minimal false positive, we profiled multiple technical replicates/aliquots of viably frozen CD138-negative bone marrow cells from each patient at three medical centers/universities (Beth Israel Deaconess Medical Center, Boston, Washington University in St. Louis and Mount Sinai School of Medicine, NYC using droplet-based single-cell barcoding technique. After batch correction and normalization, the cellular clusters were identified using principal component analysis and Uniform Manifold Approximation and Projection (UMAP) approach (Becht et al, 2018). Differential expression, pathways and systems biology analysis between rapid and non-progressors revealed differences for specific cell clusters (Panigrahy, Gartung et al. 2019). To determine association of plasma cell overexpressed genes with survival in CoMMpass study, survival analysis was performed using Kaplan-Meier (K-M) approach. Results: In this study, comparative analysis was performed of the bone marrow microenvironment of patients with aggressive and indolent disease by generating single-cell profiles of ~102,207 cells from 48 samples of 18 patients with MM. The UMAP approach identified multiple transcriptionally diverse clusters of plasma (CD138+), immune (PTPRC+) and erythroid (GYPA1/2+) cells (Fig 1a). Interestingly, the analysis identified CD138+ plasma/tumors cells clusters in a subset of samples from patients with rapid -progression and these clusters depicted a high degree of inter-patient heterogeneity (Fig 1a). Further characterization of plasma tumor cells depicted significant activation (Z score >2 and P-value <.001) of pathway related to "Unfolded protein response", epithelial-mesenchymal transition (EMT), and "p38 MAPK Signaling". These rapid progressions associated with plasma cells overexpressing multiple genes (e.g., Hazard ratio (HR) CCL3=1.9 95% CI= (1.5-3.9) log-rank P=0.0004, HSPA5 HR=1.4 (1-2.6), P=0.03) that are associated with poor outcome in multiple myeloma based CoMMpass data. The bone marrow microenvironment cells formed 22 clusters, comprising of cells from myeloid, macrophages, T cells, B cells, dendritic cells, Natural Killer T (NKT) cells, and erythroid lineages. The Non-progressive patients depicted enrichment of GZMB+ T and NKT cells with overexpression of genes associated with "Natural Killer Cell Signaling", "CD28 Signaling in T Helper Cells", "NF-kB Signaling" and "Th17 Activation Pathway" (Fig1b, c). Systems biology analysis depicted significant activation of TNF, STAT4, and NFATC2 regulatory signatures in NKT cells. The analysis also observed enrichment of macrophages, several types of monocytes, and myeloid cells in the samples from patients with non-progressive disease (Fig 1d). The myeloid/monocytes cluster depicted significant activation of multiple metabolic (i.e., Glycolysis, Gluconeogenesis) and immune response (i.e. IL8) pathways (Fig 1e). In summary, this multi-site study provides insights into potentially significant differences in the transcriptomic landscape of multiple myeloma patients with rapid and non-progression of disease. The non-progressive patients depict significant enrichment of activated T cells and myeloid lineage populations, suggesting their role toward better outcomes. These findings will be further expanded by ongoing single cell analyses of the CoMMpass tissue bank under the MMRF Immune Atlas initiative. Figure 1 Disclosures Bhasin: Canomiiks Inc: Current equity holder in private company, Other: Co-Founder. Dhodapkar:Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Cellectar: Other; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding.

Compared with traditional bulk sequencing technologies, single-cell technologies have advantages to evaluate cellular heterogeneity and investigate the evolution of cellular subpopulations from the tumor and microenvironment. Application of single-cell sequencing in Multiple Myeloma (MM) is especially beneficial given MM is a highly heterogeneous disease with uncontrolled clonal expansion of plasma cells. Single-cell RNA sequencing (scRNA-seq) has been previously utilized to understand this hematopoietic malignancy in both tumor and immune populations in MM (Ledergor G. et al., 2018, Zavidij, O. et al., 2020). Mass cytometry (CyTOF) has also been used to identify the expansion of novel memory B cells in MM. (Hansmann, L. et al., 2015). Among the various single cell techniques, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a multimodal approach with simultaneous quantification of single-cell transcriptomes and surface proteins. Since these three single-cell approaches enable the identification of cell types, cell states and characterization of cellular heterogeneity at transcriptomic and/or protein levels, understanding the concordance of the measurements among these three modalities is of great interest. We applied scRNA-seq, CyTOF and CITE-seq on four baseline samples of CD138-negative 'immune cell' fractions from patients enrolled in the MMRF CoMMpass study (NCT01454297). Two subjects were fast progressors (PFS < 18 months) and two subjects were non-progressors (PFS not reached). With multi-center collaboration coordinated by Multiple Myeloma Research Foundation (MMRF), each sample was subject to scRNA-seq and CyTOF by 3 independent centers. All sites received aliquots of the same sample. On average, 1,060 immune cells were detected in each sample using scRNA-seq and >64K CD45+ cells were detected using CyTOF. CITE-seq was performed in one center and 4,805 CD138-negative immune cells were identified on average. To compare cell type abundance between scRNA-seq, CyTOF and CITE-seq, we calculated the cell subset frequency of each immune population relative to the CD45+ populations. Overall, all three approaches were concordant while there is a stronger concordance between scRNA-seq and CyTOF. Cell type abundance is especially consistent for B cells, monocytes/macrophages, and plasmacytoid dendritic cells (pDC) among the 3 methods. For the same patient of interest, natural killer (NK) cell frequency was detected at the lowest level in CyTOF relative to scRNA and CITE-seq. The T cell population showed the highest discrepancy among techniques, with highest abundance in scRNA-seq followed by CyTOF and lowest abundance in CITE-seq. Interestingly, CITE-seq detected far less CD4 T cells compared to the other two techniques while CD8 T cell frequency did not show drastic differences. In addition to cell type abundance, we further examined the concordance of expression of cell type signature genes between scRNA-seq and CyTOF. Overall, expression between RNA-level and protein-level is positively correlated with typical cell type markers highly expressed in both techniques, especially in the following cell populations: CD8+ T cells (CD3, CD8), NK cells (CD56, GranzymeB/GZMB, NKG2A/KLRC1), B cells (CD19, CD38), Monocytes (CD14, CD11c/ITGAX, CD33). To note, although the concordance in CD4+ T cells is generally good, we found the expression of CD4 is higher in CyTOF compared to scRNA-seq whereas CD127/IL7R tends to be overexpressed in scRNA-seq. This could explain why IL7R is often identified as a differentially expressed gene (DEG) in CD4+ T cell population while CD4 is barely seen in DEG list in scRNA-seq analysis. It is also interesting to notice that the expression of most NK cell markers has strong concordance between scRNA-seq and CyTOF except NKG2D/KLRK1, which has much higher expression in CyTOF relative to scRNA-seq. Our preliminary results suggested good concordance of immune cell type abundance identified in CyTOF, scRNA-seq and CITE-seq as well as concordant expression of some canonical cell type markers between RNA level and protein level. This work provides the field with reference data sets and shows more detailed examination of NK and T cell subsets is needed when handling single cell sequencing with different modalities. Disclosures Dhodapkar: Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:MedImmune: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria. Gnjatic:Neon Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; OncoMed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Genentech: Research Funding; Immune Design: Research Funding; Agenus: Research Funding; Janssen R&D: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bhasin:Canomiiks Inc: Current equity holder in private company, Other: Co-Founder.

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.

Recent successes and FDA approvals of CD19 redirected chimeric antigen receptor T cell (CART19) therapy have been achieved in pivotal clinical trials in patients with B cell malignancies. However, durable response rates in non-Hodgkin B cell lymphoma (B-NHL) and chronic lymphocytic leukemia (CLL) are low. Tumor-associated macrophages have emerged as key mediators of tumor-induced CART cell immunosuppression. Axl receptor tyrosine kinase (Axl-RTK) is overexpressed in various human cancers including B-NHL or CLL and correlates with poor overall survival. Thus, several Axl-RTK inhibitors are currently being investigated in clinical trials. We have previously reported that the Axl-RTK inhibitor TP-0903 modulates CART19 function by Th1 polarization. Moreover, we observed a significant reduction in myeloid-derived cytokines in preclinical models. This led us to hypothesize that Axl-RTK inhibition also modulates monocytes which in turn affects CART function. To test our hypothesis, we interrogated the interactions between Axl-RTK inhibition, monocytes, and CART. First, we isolated CD14+ monocytes from peripheral mononuclear cells (PBMCs) from healthy donors by magnetic negative selection. Flow cytometric analysis revealed a robust Axl expression on monocytes (Fig.1A). Monocytes were maintained in ImmunoCult Macrophage Medium (STEMCELL Technologies) and differentiated with lipopolysaccharide and interferon-γ for M1-type and interleukin (IL)-4 for M2-type macrophages. After confirming the macrophage phenotypes, cells were assessed for Axl expression. Flow cytometric analysis demonstrated that M2-type macrophages expressed higher Axl compared to M1 macrophages (Fig.1B). Then, we treated PBMCs from healthy donors with TP-0903 for 24 hours to determine the specific cell types affected by Axl-RTK inhibition. Flow cytometric analysis revealed that monocytes were significantly inhibited by TP-0903 compared to B cells or T cells (Fig.1C). Having demonstrated that TP-0903 strongly suppresses monocytes and that M2-type macrophages express Axl on their surface, we then performed a cytotoxicity assay against CD19+ mantle cell lymphoma cell line, JeKo-1, to study the impact of Axl-RTK inhibition on monocyte-induced CART suppression. We used CART19 generated in our laboratory (FMC63-41BBζ). CART19, JeKo-1, and M2-type macrophages were co-cultured at 1:2:1 ratio and incubated for 3 days. The data revealed that M2-type macrophages strongly suppress CART19 killing (Fig.1D) which could be overcome with TP-0903 (Fig.1E). Next we studied monocyte-induced CART19 suppression with antigen-specific proliferation. CART19, JeKo-1, and monocytes were co-cultured at 1:5:1 ratio and incubated for 5 days. Flow cytometric analysis revealed that in the presence of monocytes, antigen-specific proliferation of CART19 was significantly suppressed, which was reversed in the presence of TP-0903 (Fig.1F). To assess how Axl inhibition modulates myeloid cell-derived cytokines/chemokines, we performed Multiplex (Millipore-Sigma) with the supernatants obtained from these co-culture assays. The presence of monocytes resulted in a significant increase in IL-17a, IL-6, IL-1 receptor agonist, IL-1β, and soluble CD40 ligand. However, Axl-RTK inhibition resulted in selective reduction of those cytokines/chemokines (Fig.1G) while preserving other effector cytokines. Finally, we tested whether Axl-RTK inhibition with TP-0903 could overcome the negative effects of monocytes in vivo. Here, immunocompromised NSG mice were injected with 1x106 luciferase+ JeKo-1 cells intravenously. Ten days later, mice were injected with freshly isolated monocytes derived from a healthy donor. Two weeks after JeKo-1 inoculation, tumor burden was assessed with bioluminescence imaging. Mice were then randomized according to the tumor burden to receive 0.5x106 CART19 as a monotherapy or in combination with 20 mg/kg/day of oral TP-0903. The combination therapy resulted in superior anti-tumor effects and overall survival compared to CART19 monotherapy (Fig.1H-I). In summary, Axl-RTK inhibition with TP-0903 demonstrates a direct suppression of inhibitory monocytes, which in turn enhances CART cell function. Our findings support the strategy of further refining and testing the novel and potent combination of Axl-RTK inhibition and CART cell therapy for the treatment of B cell malignancies. Figure 1 Disclosures Sakemura: Humanigen: Patents & Royalties. Cox:Humanigen: Patents & Royalties. Mouritsen:Sumitomo Dainippon Pharma Oncology, Inc.: Current Employment. Foulks:Tolero Pharmaceuticals, Inc.: Current Employment. Warner:Tolero Pharmaceuticals, Inc.: Current Employment. 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. Parikh:GlaxoSmithKline: Honoraria; Verastem Oncology: Honoraria; Genentech: Honoraria; Ascentage Pharma: Research Funding; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; Pharmacyclics: Honoraria, Research Funding. Kay:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; MEI Pharma: Research Funding; Abbvie: 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; 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; Rigel: 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; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees. Kenderian:Mettaforge: Patents & Royalties; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; BMS: Research Funding; Juno: Research Funding; Gilead: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding.

Introduction: With a median overall survival (OS) measured in months, successful treatment of Richter's transformation (RT) of chronic lymphocytic leukemia (CLL) to diffuse large B-cell lymphoma (DLBCL) remains a major unmet medical need. While targeted agents, such as Bruton tyrosine kinase inhibitor (BTKi) monotherapy, have greatly improved outcomes for patients (pts) with CLL and some B-cell lymphomas, available BTKi therapies have been ineffective for RT, as well as for large cell transformation of indolent B-cell lymphomas and relapsed/refractory (r/r) DLBCL, which rapidly develop mechanisms of resistance by activation of downstream targets of BTKi or upregulation of alternative/parallel pathways. Focusing on a synthetic lethality approach via in vitro and in vivo studies, we discovered that concurrent inhibition of BTK & mTOR targets plus an IMiD synergistically kill malignant B-cells. DTRM-555 is an optimized oral triple combination of a novel irreversible BTKi DTRMWXHS-12 (DTRM-12), everolimus (EV) and pomalidomide (POM). This once daily therapy was tested in a stepwise, phase I, multicenter study in pts with the greatest unmet medical needs. Here we present results for this novel combination therapy in pts with RT, and r/r DLBCL. Methods: We conducted a phase I (3+3 design), first in human trial exploring DTRM-555 in adult pts with B-cell lymphomas with no available standard therapies (NCT02900716) at 6 US cancer centers. Our goal was to determine the optimal dose for DTRM-555. In phase Ia, an MTD was not reached for DTRM-12 monotherapy; In phase Ib and expansion cohorts, we evaluated double (DTRM-12/EV at 200mg/5mg or 300mg/5mg) and triple combinations (DTRM-12/EV/POM at 200mg/5mg/2mg or 300mg/5mg/2mg) administered once daily for 21 days of a 28-day cycle, until disease progression or unacceptable toxicity. The primary endpoint was safety and the dose limiting toxicity (DLT) period was cycle 1 (28 days). Secondary endpoints included overall response rate (ORR; Cheson 2014), duration of response (DOR), and DTRM-12 pharmacokinetics. The trial began on 9/27/2016 and completed enrollment with evaluable follow-up data cut-off date on 08/06/2020. Results: 39 pts were enrolled and treated, including 24 with RT (n=12) or r/r DLBCL (n=12). The safety analyses included all 39 pts treated with combination therapies while efficacy analyses were focused on RT and r/r DLBCL. Baseline characteristics (n=39): 66% male, median age 71 years (range 43-94) and 94% white. For the entire study cohort, median number of prior therapies was 3 (range 1-10), 49% had been treated with prior BTKi monotherapy,13% prior CAR-T or stem cell transplant (SCT) and 59% ≥1 prior small molecule targeted agent. For pts with RT and r/r DLBCL (n=24), median prior therapies were 5 (range 1-10) and 2 (range 10), respectively. Table 1 summarizes prior therapies for the 24 RT and r/r DLBCL pts. Table 2 describes Grade 3 and 4 related AEs for 39 pts treated with the combination therapies. AEs were manageable and similar to known AEs for BTKi, EV or POM, with a total of 4 DLTs observed with combination therapies. The most common AEs were hematological events; specifically, thrombocytopenia, neutropenia, and anemia. The MTD of DTRM-555 was determined to be DTRM-12 200mg, EV 5mg, & POM 2mg. For 11 evaluable RT pts, ORR was 45% (1 CR, 4 PR); 1 RT pt has not undergone first response assessment. For 10 evaluable DLBCL pts, ORR was 60% (2 CR, 4 PR). Responders with RT or r/r DLBCL have durable responses (Figure 1). Kaplan Meier estimated median duration of response for RT and DLBCL pts was 15 months as of the cut-off. Dose dependent DTRM-12 drug plasma levels were observed in all arms with minimal inter-pt variability. Conclusions: This clinical trial met its primary endpoint. The once-daily oral triple combination therapy DTRM-555 has an acceptable safety profile. Encouraging clinical activity was observed in several high-risk, multi-refractory pts with RT (median 5 prior therapies, ORR 45%) or r/r DLBCL (median 2 prior therapies, ORR 60%), including pts previously treated with targeted therapies, cellular therapies, checkpoint inhibitors and other experimental agents. A phase II US expansion study is underway targeting pts with RT, r/r DLBCL, r/r transformed follicular lymphoma and BTKi/BCL2 inhibitor exposed r/r CLL pts. Disclosures Mato: Adaptive: Consultancy, Research Funding; TG Therapeutics: Consultancy, Other: DSMB, Research Funding; AbbVie: Consultancy, Research Funding; AstraZeneca: Consultancy, Research Funding; BeiGene: Consultancy; LOXO: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding. Schuster:AlloGene, AstraZeneca, BeiGene, Genentech, Inc./ F. Hoffmann-La Roche, Juno/Celgene, Loxo Oncology, Nordic Nanovector, Novartis, Tessa Therapeutics: Consultancy, Honoraria; Novartis, Genentech, Inc./ F. Hoffmann-La Roche: Research Funding. Ding: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; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. Brander:Tolero: Research Funding; NCCN: Other; Teva: Consultancy, Honoraria; Novartis: Consultancy, Other; NCCN: Other; Verastem: Consultancy, Honoraria, Other, Research Funding; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Pfizer: Consultancy, Other; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Other, Research Funding; MEI Pharma: Other, Research Funding; Juno/Celgene/BMS: Other, Research Funding; Genentech: Consultancy, Honoraria, Other, Research Funding; DTRM: Other, Research Funding; AstraZeneca: Consultancy, Honoraria, Other, Research Funding; BeiGene: Other, Research Funding; Ascentage: Other, Research Funding; ArQule: Consultancy, Other, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Tolero: Research Funding; Teva: Consultancy, Honoraria; Novartis: Consultancy, Other. Tun:Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Mundipharma: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding; Acrotech: Research Funding; DTRM Biopharma: Research Funding. He:DTRM Biopharma LLC: Current Employment. Kearney:DTRM Biopharma LLC: Current Employment. Gui:DTRM Biopharma LLC: Current Employment. McKinlay:DTRM Biopharma LLC: Current Employment. Roeker:American Society of Hematology: Research Funding; AbbVie: Other: spouse with minority ownership interest ; Abbott Laboratories: Other: spouse with minority ownership interest . Huntington:Pharmacyclics: Honoraria; Novartis: Consultancy; Genentech: Consultancy; DTRM: Research Funding; AbbVie: Consultancy; Astrazeneca: Honoraria; Bayer: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; TG Therapeutics: Research Funding.

Abstract The purpose of this scoping review by the American Society for Parenteral and Enteral Nutrition (ASPEN) Coronavirus Disease 2019 (COVID‐19) Nutrition Task Force was to examine nutrition research applicable to the COVID‐19 pandemic. The rapid pace of emerging scientific information has prompted this activity to discover research/knowledge gaps. This methodology adhered with recommendations from the Joanna Briggs Institute. There were 2301 citations imported. Of these, there were 439 articles fully abstracted, with 23 main topic areas identified across 24 article types and sourced across 61 countries and 51 specialties in 8 settings and among 14 populations. Epidemiological/mechanistic relationships between nutrition and COVID‐19 were reviewed and results mapped to the Population, Intervention, Comparator, Outcome, and Time (PICO‐T) questions. The aggregated data were analyzed by clinical stage: pre–COVID‐19, acute COVID‐19, and chronic/post–COVID‐19. Research gaps were discovered for all PICO‐T questions. Nutrition topics meriting urgent research included food insecurity/societal infrastructure and transcultural factors (pre–COVID‐19); cardiometabolic‐based chronic disease, pediatrics, nutrition support, and hospital infrastructure (acute COVID‐19); registered dietitian nutritionist counseling (chronic/post–COVID‐19); and malnutrition and management (all stages). The paucity of randomized controlled trials (RCTs) was particularly glaring. Knowledge gaps were discovered for PICO‐T questions on pediatrics, micronutrients, bariatric surgery, and transcultural factors (pre–COVID‐19); enteral nutrition, protein‐energy requirements, and glycemic control with nutrition (acute COVID‐19); and home enteral and parenteral nutrition support (chronic/post–COVID‐19). In conclusion, multiple critical areas for urgent nutrition research were identified, particularly using RCT design, to improve nutrition care for patients before, during, and after COVID‐19.

AbstractMolecular prognostic factors for individualized treatment of squamous cell carcinoma (SCC) are poorly defined. Our study developed and validated a novel molecular tools aid in preinguinal and postinguinal lymphadenectomy risk stratification in node‐positive penile SCC. Patients with node‐positive penile SCC who underwent inguinal or ilioinguinal lymphadenectomy were divided into three cohorts: a discovery set, a development set and a validation set. The local ethics committee approved the study. The primary endpoint was cancer‐specific survival (CSS). At the discovery stage, 17 CpG sites were significantly associated with CSS. In the development set, we constructed a 3‐CpG‐based prognostic score for survival prediction. The hazard ratio (HR) of the panel (dichotomized using the optimal cutoff) was 5.8 in the multivariate analyses (P < .001). The addition of the methylation score significantly improved the pN‐stage C‐index from 0.70 to 0.79 (incremental C = 0.09, P < .001). In the validation set, the methylation panel showed a HR of 9.9 in the multivariate analyses. The addition of the molecular marker improved the pN‐stage C‐index from 0.69 to 0.78 (incremental C = 0.09, P < .001). The methylation score remarkably separated survival curves in different pN stages, which indicate that the tool can be applied to tailor the treatment in both preinguinal and postinguinal lymphadenectomy settings. We developed and validated a prognostic methylation panel for node‐positive penile SCC. The tool may aid in the risk stratification of the population with heterogeneous outcomes and needs prospective validation. Patients in high‐risk group may benefit from more aggressive therapy or clinical trials.