Citations

Background: Axi-cel, an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy, is approved for treatment of adult pts with R/R LBCL after ≥ 2 lines of systemic therapy. In the pivotal ZUMA-1 study, axi-cel demonstrated durable responses and a largely manageable safety profile (Locke FL, et al. Lancet Oncol. 2019). ZUMA-9 (NCT03153462), a multicenter, open-label study, provided pts with R/R LBCL with expanded access to axi-cel until commercial availability (Cohort 1 [C1]) and later, if commercially manufactured product did not meet commercial release specification(s) (Cohort 2 [C2]). Safety and efficacy of axi-cel (C1 and C2) and translational analyses (C2) are presented. Methods: Eligible adults had histologically confirmed R/R LBCL, ECOG ≤ 1, and received prior CD20-targeting and an anthracycline-containing regimen. C2 pts must have had commercial OOS product. Pts underwent leukaphersis and conditioning chemotherapy (cyclophosphamide 500 mg/m2/day and fludarabine 30 mg/m2/day) for 3 days followed by a single axi-cel infusion (target dose, 2 × 106 CAR T cells/kg). C1 and C2 pts with high disease burden could receive bridging therapy before conditioning at investigator's discretion. Endpoints included frequency of adverse events (AEs), objective response rate (ORR) per standard-of-care imaging assessment, overall survival (OS) for C1 and C2, and blood CAR T cells levels and serum cytokines for C2 only. Outcomes were contextualized with the primary analysis of ZUMA-1 C1+2 (n = 101; ≥ 6 mo of follow-up; Neelapu SS, et al. NEJM. 2017). Results: As of 11/29/2019 (C1) and 3/15/2020 (C2), 25 C1 pts and 36 C2 pts received axi-cel with a median follow-up of 27.1 mo (range, 23.6 - 29.6) and 13.2 mo (range, 0.4 - 25.7), respectively. In C1, median age was 56 y (range, 28 - 76), 60% were male, 80% had DLBCL, 48%/0% had ECOG1/≥2, 44% had IPI ≥3, and 64% had ≥ 3 prior lines of therapy. In C2, median age was 61 y (range, 24 - 81), 75% were male, 78% had DLBCL, 58%/17% had ECOG 1/≥2, 56% had IPI ≥3, and 69% had ≥ 3 prior lines of therapy. In C2, 50% of pts had OOS product with low viability, 28% had high IFN-γ, 14% had low IFN-γ, 14% received a low dose, and 6% had high transduction ratio. The ORR was 76% (64% complete response [CR]) for C1, 53% (36% CR) for C2, and 82% (54% CR) for ZUMA-1 C1+2. Median OS was 23.8 mo (95% CI, 13.5 - NE) for C1 and not reached (95% CI, 3.4 - NE) for C2, respectively. ORR and OS were consistent in C2 OOS subgroups (Table). Grade ≥ 3 AEs were reported in 88% and 89% of C1 and C2 pts, respectively. Grade ≥ 3 CRS (Lee et al, Blood. 2014) was not observed in C1 but was reported in 3% of C2 pts (13% in ZUMA-1 C1+2). Grade ≥ 3 neurologic events (NEs) occurred in 36% and 19% of pts in C1 and C2, respectively, and 28% of pts in ZUMA-1 C1+2. No Grade 5 CRS or NEs occurred in C1 or C2. All CRS and NEs resolved in C1, and most CRS (29/30) and NEs (19/24) resolved in C2 as of the data cutoff. Of 3 Grade 5 AEs in C1, 2 were unrelated to axi-cel (clostridial sepsis [on Day (D) 6] and respiratory failure [on D212]) and 1 was related to conditioning (myelodysplastic syndrome [on D563]). Of 3 Grade 5 AEs in C2, 2 were unrelated to axi-cel (multiple organ dysfunction syndrome [on D6] and cardiac arrest [on D482]) and 1 was related to axi-cel (systemic mycosis [on D30]). Median peak CAR T cell levels and median CAR T cell expansion (area under the curve in the first 28 days) were lower in ZUMA-9 C2 (n = 32/36; 12 cells/µL [range, 0 - 442] and 112 cells/µL × days [range, 0 - 3413]) vs ZUMA-1 C1+2 (n = 96/101; 42 cells/µL [range, 1 - 1514] and 462 cells/µL × days [range, 5 - 14,329]). Serum IFN-γ levels peaked within 8 days after axi-cel infusion (median, 170 pg/mL [range, 8 - 1876]) and were lower vs ZUMA-1 C1+2 (median, 477 pg/mL [range, 8 - 8209]). Axi-cel in ZUMA-9 C2 contained fewer, less differentiated CCR7+ naïve and central memory T cells, and a greater proportion of more differentiated CCR7- effector memory and effector T cells vs ZUMA-1 C1+2. No cases of replication-competent retroviruses were reported in C1 or C2. Conclusion: Axi-cel treatment demonstrated a manageable safety profile and meaningful clinical benefit in this expanded access and OOS product study. While CAR T cell therapy showed clinical benefit in C2 (OOS product), the lower CR rate was corroborated by lower CAR T cell expansion and a more differentiated product vs ZUMA-1 C1+2, warranting further investigation. ZUMA-9 C2 is enrolling pts and evaluation is ongoing. Disclosures Jacobson: Precision Biosciences: Consultancy, Honoraria, Other: travel support; Celgene/BMS: Consultancy, Honoraria, Other: travel support; Novartis: Consultancy, Honoraria, Other: travel support; AXIS: Speakers Bureau; Nkarta: Consultancy, Honoraria, Other: travel support; Clinical Care Options: Speakers Bureau; Pfizer: Research Funding; Lonza: Consultancy, Honoraria, Other: travel support; Kite, a Gilead Company: Consultancy, Honoraria, Other: travel support. Locke:Calibr: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Wugen: Consultancy; GammaDelta Therapeutics: Consultancy; Celgene/Bristol-Myers Squibb: Consultancy; Novartis: Consultancy; Cellular Biomedicine Group: Other: Consultancy with grant options; Allogene: Consultancy. Miklos:Adaptive Biotech: Consultancy, Other: Travel support, Research Funding; Novartis: Consultancy, Other: Travel support, Research Funding; Pharmacyclics: Consultancy, Other: Travel support, Patents & Royalties, Research Funding; Juno-Celgene-Bristol-Myers Squibb: Consultancy, Other: Travel support, Research Funding; Allogene Therapeutics Inc.: Research Funding; Miltenyi Biotec: Research Funding; Janssen: Consultancy, Other: Travel support; Kite-Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding. Vose:Incyte: Research Funding; Novartis: Research Funding; Bristol-Myers Squibb: Research Funding; Karyopharm Therapeutics: Consultancy, Honoraria; Allogene: Honoraria; Loxo: Consultancy, Honoraria, Research Funding; Seattle Genetics: Research Funding; Miltenyi Biotec: Honoraria; Janssen: Honoraria; Epizyme: Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Kite, a Gilead Company: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding; Verastem: Consultancy, Honoraria; Wugen: Honoraria; Celgene: Honoraria; Roche/Genetech: Consultancy, Honoraria, Other. Lin:Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Vineti: Consultancy; Gamida Cells: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding. Budde:Roche: Consultancy; Merck: Research Funding; Amgen: Research Funding; Kite, a Gilead Company: Consultancy; Gilead Sciences: Consultancy; Mustang Therapeutics: Research Funding; AstraZeneca: Research Funding. Maloney:Celgene: Consultancy, Honoraria, Research Funding; A2 Biotherapeutics: Consultancy, Current equity holder in publicly-traded company, Honoraria; Gilead Sciences: Consultancy, Honoraria; Juno Therapeutics: Consultancy, Honoraria, Patents & Royalties: Patents are pending, but not issued, licensed, no royalties, no licensees., Research Funding; Bioline Rx: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria; Genentech: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding. Jaglowski:Juno: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; CRISPR: Consultancy; Novartis: Consultancy, Research Funding. Riedell:MorphoSys: Research Funding; Kite/Gilead: Research Funding, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Karyopharm Therapeutics: Consultancy; Celgene/Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Honoraria, Research Funding. Perales:Celgene: Honoraria; MolMed: Membership on an entity's Board of Directors or advisory committees; Omeros: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bellicum: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Honoraria, Research Funding; Miltenyi Biotec: Research Funding; Merck: Consultancy, Honoraria; Nektar Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Cidara Therapeutics: Other; Servier: Membership on an entity's Board of Directors or advisory committees, Other; Medigene: Membership on an entity's Board of Directors or advisory committees, Other; NexImmune: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Honoraria, Research Funding. Kim:Gilead Sciences: Current equity holder in publicly-traded company; Kite, a Gilead Company: Current Employment. Kawashima:Kite, a Gilead Company: Current Employment; Gilead Sciences: Other: stock or other ownership . Yang:Kite, a Gilead Company: Current Employment. Rossi:Kite, a Gilead Company: Current Employment; Gilead Sciences: Current equity holder in publicly-traded company. Goyal:Kite, a Gilead Company: Current Employment. Neelapu:Legend Biotech: Other; Allogene Therapeutics: Other: personal fees, Research Funding; Cell Medica/Kuur: Other: personal fees; Incyte: Other: personal fees; Unum Therapeutics: Other, Research Funding; Adicet Bio: Other; Novartis: Other: personal fees; Bristol-Myers Squibb: Other: personal fees, Research Funding; Merck: Other: personal fees, Research Funding; Kite, a Gilead Company: Other: personal fees, Research Funding; Precision Biosciences: Other: personal fees, Research Funding; Poseida: Research Funding; Calibr: Other; Acerta: Research Funding; Takeda Pharmaceuticals: Patents & Royalties; Celgene: Other: personal fees, Research Funding; Pfizer: Other: personal fees; Karus Therapeutics: Research Funding; Cellectis: Research Funding; N/A: Other.

Background The importance of the immune system in modulating the trajectory of lymphoma outcomes has been increasingly recognized. We recently showed that CD4+ cells are associated with clinical outcomes in a prospective cohort of almost 500 patients with follicular lymphoma (FL). Specifically, we showed that the absence of CD4+ cells inside follicles was independently associated with increased risk of early clinical failure. These data suggest that the composition, as well as the spatial distribution of immune cells within the tumor microenvironment (TME), play an important role in FL. To further define the architecture of the TME in FL we analyzed a FL tumor section using the Co-Detection by Indexing (CODEX) multiplex immunofluorescence system. Methods An 8-micron section from a formalin-fixed paraffin-embedded block containing a lymph node specimen from a patient with FL was stained with a cocktail of 15 CODEX antibodies. Five regions of interest (ROIs) were imaged using a 20X air objective. Images underwent single-cell segmentation using a Unet neural network, trained on manually segmented cells (Fig 1A). Cell type assignment was done after scaling marker expression and clustering using Phenograph. Each ROI was manually masked to indicate areas inside follicles (IF) and outside follicles (OF). Relative and absolute frequencies of cell types were calculated for each region. Cellular contacts were measured as number and types of cell-cell contacts within two cellular diameters. To identify proximity communities, we clustered cells based on number and type of neighboring masks using Phenograph. The number of cell types and cellular communities were calculated inside and outside follicles after adjustment for total IF and OF areas. The significance of cell contact was measured using a random permutation test. Results We identified 13 unique cell subsets (11 immune, 1 endothelial, 1 unclassified) in the TME of our FL section (Fig. 1A). The unique phenotype of each subset was confirmed using a dimensionality reduction tool (t-SNE). The global composition of the TME varied minimally across ROIs and consisted primarily of B cells, T cells, and macrophages subsets - in decreasing order of frequency. Higher spatial heterogeneity across ROIs was observed in the frequency of T cell subsets in comparison to B cells subsets. Inspecting the spatial distribution of T cell subsets (Fig. 1B), we observed that cytotoxic T cells were primarily located in OF areas, whereas CD4+ T cells were found in both IF and OF areas. Notably, the majority of CD4+ T cells inside the follicles expressed CD45RO (memory phenotype), while most of the CD4+ T cells outside the follicles did not. Statistical analysis of the spatial distribution of CD4+ memory T cell subsets confirmed a significant increase in their frequency inside follicles compared to outside (20.4% vs 11.2%, p < 0.001; Fig. 1D). Cell-cell contact analysis (Fig 1C) showed increased homotypic contact for all cell types. We also found a higher frequency of heterotypic contact between Ki-67+CD4+ memory T cells and Ki-67+ B cells. Pairwise analysis showed these findings were statistically significant, indicating these cells are organized in niches rather than randomly distributed across image. Analysis of cellular communities (Fig. 1C) identified 13 niches, named according to the most frequent type of cell-cell contact. All CD4+ memory T cell subsets were found to belong to the same neighborhood (CD4 Memory community). Analysis of the spatial distribution of this community confirmed that these niches were more frequently located inside follicles rather than outside (26.3±4% vs 0.004%, p < 0.001, Fig. 1D). Conclusions Analysis of the TME using CODEX provides insights on the complex composition and unique architecture of this FL case. Cells were organized in a pattern characterized by (1) high degree of homotypic contact and (2) increased heterotypic interaction between activated B cells and activated CD4+ memory T cells. Spatial analysis of both individual cell subsets and cellular neighborhoods demonstrate a statistically significant increase in CD4+ memory T cells inside malignant follicles. This emerging knowledge about the specific immune-architecture of FL adds mechanistic details to our initial observation around the prognostic value of the TME in this disease. These data support future studies using modulation of the TME as a therapeutic target in FL. Figure 1 Disclosures Galkin: BostonGene: Current Employment, Patents & Royalties. Svekolkin:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Postovalova:BostonGene: Current Employment, Current equity holder in private company. Bagaev:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Ovcharov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Varlamova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Novak:Celgene/BMS: Research Funding. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding. Nowakowski:Nanostrings: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Kymera: Consultancy; Denovo: Consultancy; Kite: Consultancy; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Ansell:Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding.

Background: Ide-cel, a BCMA-directed CAR T cell therapy, showed tolerability and promising efficacy in patients with relapsed and/or refractory multiple myeloma (RRMM) in the first-in-human phase 1 CRB-401 study (Raje et al. N Engl J Med. 2019;380:1726) and the pivotal phase 2 KarMMa study (Munshi et al. J Clin Oncol. 2020;38[suppl, abstr]:8503). Ide-cel demonstrated a favorable benefit-risk profile with an overall response rate (ORR) of 85%, a complete response (CR) rate of 45%, and a median progression-free survival (PFS) of 11.8 months in the first 33 patients treated in CRB-401. Reported here are updated safety and efficacy results for 62 patients who received ide-cel in the ongoing CRB-401 study. Methods: CRB-401 (NCT02658929) is a 2-part, phase 1 dose-escalation and -expansion study. The expansion phase enrolled patients who had received ≥3 prior lines of therapy, including a proteasome inhibitor, an immunomodulatory drug, and an anti-CD38 antibody, and were refractory to their last line of therapy. Eligibility criteria for the dose-escalation phase were described previously (Raje et al. N Engl J Med. 2019;380:1726). After lymphodepletion with fludarabine (30 mg/m2/day) and cyclophosphamide (300 mg/m2/day) for 3 days followed by 2 days of rest, patients received ide-cel at target doses of 50, 150, 450, or 800 × 106 CAR+ T cells in the dose-escalation phase and 150 to 450 × 106 CAR+ T cells in the dose-expansion phase. The primary endpoint was safety. Secondary endpoints included tumor response according to the International Myeloma Working Group criteria. Exploratory endpoints included PFS, overall survival (OS), and minimal residual disease (MRD). Results: As of January 14, 2020, 21 patients had received ide-cel in the dose-escalation phase, and 41 patients received ide-cel in the dose-expansion phase. The median age was 61 years, and 44% of patients had high tumor burden (≥50% bone marrow CD138+ plasma cells). Of the 62 patients, 45% received >6 prior regimens, 90% were daratumumab-exposed, and 77% were daratumumab-refractory. As of the cutoff date, 13 patients were ongoing, and 49 patients had discontinued the study. Reasons for study discontinuation were progressive disease (58%), withdrawal by patients (10%), and death (10%). Based on safety and efficacy in the dose-escalation phase, target dose levels of 150 to 450 × 106 CAR+ T cells were selected for the dose-expansion phase. The most frequent adverse events (AEs) were neutropenia (92%), cytokine release syndrome (CRS; 76%), anemia (76%), and thrombocytopenia (74%). The most frequent grade 3/4 AEs were neutropenia (89%), leukopenia (61%), anemia (57%), and thrombocytopenia (57%). Most CRS events were grade 1 or 2 (Table). Four patients (7%) had grade 3 CRS; there were no grade >3 CRS events. The incidence of CRS generally increased with target dose level. Neurologic toxicity (NT; clustered term) occurred in 27 patients (44%) and was primarily grade 1/2 with 1 patient having grade 3 and 1 patient having grade 4 NT. Among all 62 patients in the dose-escalation and -expansion phases, the ORR was 76%, including 24 patients (39%) with a CR or better and 40 patients (65%) with a very good partial response or better. The median duration of response was 10.3 months. Of 37 responders evaluable for MRD, 30 were MRD negative (≤10−4 nucleated cells) at 1 or more time point, and 7 responders were MRD positive. With a median follow-up of 14.7 months for all patients in the dose-escalation and dose-expansion phases, median PFS was 8.8 months and median OS was 34.2 months. Overall, a dose-dependent effect was observed on responses and survival outcomes, with greater efficacy reported at ≥150 × 106 CAR+ T cells (Table). Conclusions: Ide-cel demonstrated deep and durable responses in heavily-pretreated RRMM patients. Efficacy and safety reflect prior reports and support a favorable clinical benefit-risk profile for ide-cel at target dose levels ≥150 × 106 CAR+ T cells. Table Disclosures Lin: Novartis: Consultancy; Janssen: Consultancy, Research Funding; Vineti: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy; Takeda: Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Raje:Caribou: Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy; Bluebird, Bio: Consultancy, Research Funding; Takeda: Consultancy; Immuneel: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Astrazeneca: Consultancy; Amgen: Consultancy. Berdeja:Abbvie: Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Vivolux: Research Funding; Genentech, Inc.: Research Funding; Bluebird: Research Funding; Lilly: Research Funding; Constellation: Research Funding; Glenmark: Research Funding; Janssen: Consultancy, Research Funding; Legend: Consultancy; Novartis: Research Funding; Poseida: Research Funding; Prothena: Consultancy; Teva: Research Funding; Servier: Consultancy; Takeda: Consultancy, Research Funding; Bioclinica: Consultancy; EMD Sorono: Research Funding; Acetylon: Research Funding; Celgene: Consultancy, Research Funding; Cellularity: Research Funding; Kesios: Research Funding; CURIS: Research Funding; Kite Pharma: Consultancy; CRISPR Therapeutics: Consultancy, Research Funding; Amgen: Consultancy, Research Funding. Siegel:Karyopharma: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Merck: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Celulatiry: Consultancy. Jagannath:Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Legend Biotech: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Madduri:Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Celgene: Consultancy, Honoraria; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Foundation Medicine: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau. Liedtke:Pfizer: Honoraria; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees. Rosenblatt:Celgene: Research Funding. Maus:arcellx: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; kite: Consultancy, Research Funding. Massaro:bluebird, bio: Current Employment, Current equity holder in publicly-traded company. Petrocca:bluebird, bio: Current Employment, Current equity holder in publicly-traded company. Caia:Celgene a BMS company: Current Employment, Current equity holder in publicly-traded company. Yang:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company; Celgene: Ended employment in the past 24 months. Campbell:BMS: Current Employment, Current equity holder in publicly-traded company. Hege:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Patents & Royalties: numerous, Research Funding; Celgene (acquired by Bristol Myers Squibb): Ended employment in the past 24 months; Mersana Therapeutics: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Arcus Biosciences (Former Board of Directors): Divested equity in a private or publicly-traded company in the past 24 months. Munshi:BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; Amgen: Consultancy; Legend: Consultancy. Kochenderfer:Celgene: Patents & Royalties, Research Funding; bluebird, bio: Patents & Royalties; Kite, a Gilead company: Patents & Royalties, Research Funding.

Abstract In response to the coronavirus disease 2019 (COVID-19) pandemic, the Cardio-Oncology and Imaging Councils of the American College of Cardiology offers recommendations to clinicians regarding the cardiovascular care of cardio-oncology patients in this expert consensus statement. Cardio-oncology patients—individuals with an active or prior cancer history and with or at risk of cardiovascular disease—are a rapidly growing population who are at increased risk of infection, and experiencing severe and/or lethal complications by COVID-19. Recommendations for optimizing screening and monitoring visits to detect cardiac dysfunction are discussed. In addition, judicious use of multimodality imaging and biomarkers are proposed to identify myocardial, valvular, vascular, and pericardial involvement in cancer patients. The difficulties of diagnosing the etiology of cardiovascular complications in patients with cancer and COVID-19 are outlined, along with weighing the advantages against risks of exposure, with the modification of existing cardiovascular treatments and cardiotoxicity surveillance in patients with cancer during the COVID-19 pandemic.

Abstract Background Autoimmunity is an increasingly recognized cause of encephalitis with a similar prevalence to that of infectious etiologies. Over the past decade there has been a rapidly expanding list of antibody biomarker discoveries that have aided in the identification and characterization of autoimmune encephalitis. As the number of antibody biomarkers transitioning from the research setting into clinical laboratories has accelerated, so has the demand and complexity of panel-based testing. Clinical laboratories are increasingly involved in discussions related to test utilization and providing guidance on which testing methodologies provide the best clinical performance. Content To ensure optimal clinical sensitivity and specificity, comprehensive panel-based reflexive testing based on the predominant neurological phenotypic presentation (e.g., encephalopathy) is ideal in the workup of cases of suspected autoimmune neurological disease. Predictive scores based on the clinical workup can aid in deciding when to order a test. Testing of both CSF and serum is recommended with few exceptions. Appropriate test ordering and interpretation requires an understanding of both testing methodologies and performance of antibody testing in different specimen types. Summary This review discusses important considerations in the design and selection of neural antibody testing methodologies and panels. Increased collaboration between pathologists, laboratorians, and neurologists will lead to improved utilization of complex autoimmune neurology antibody testing panels.

Objective To comprehensively explore contemporary differences between bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV) patients with chronic haemodynamically significant aortic regurgitation (AR). Methods Consecutive patients with chronic ≥moderate-severe AR from a tertiary referral centre (2006–2017) were included. All-cause mortality, surgical indications and aortic valve surgery (AVS) were analysed. Results Of 798 patients (296 BAV-AR, age 46±14 years; 502 TAV-AR, age 67±14 years, p<0.0001) followed for 5.5 (IQR: 2.9–9.2) years, 403 underwent AVS (repair in 96) and 154 died during follow-up. The 8-year AVS incidence was 60%±3% versus 53%±3% for BAV-AR and TAV-AR, respectively (p=0.014). The unadjusted (real-life) 8-year total survival was 93%±7% versus 71%±2% for BAV-AR and TAV-AR, respectively (p<0.0001), and became statistically insignificant after sole adjustment for age (p=0.14). The within-group relative risk of death in BAV-AR patients demonstrated a large age-dependent increase (two fold at 50–55 years, up to 10-fold at 70 years). The presence of baseline symptoms was significantly associated with death for both BAV-AR (p=0.039) and TAV-AR (p<0.0001), but the strength of the association decreased with age adjustment for BAV-AR (age-adjusted HR 2.43 (0.92–6.39), p=0.07) and not for TAV-AR (age-adjusted HR, 2.3 (1.6–3.3), p<0.0001). As compared with general population, TAV-AR exhibited baseline excess risk which further increased at left ventricular ejection fraction (LVEF) <60% and left ventricular end-systolic dimension index (LVESDi) >20 mm/m2; similar thresholds were observed for BAV-AR patients. Conclusion BAV-AR patients were two decades younger than TAV-AR and underwent AVS more frequently, resulting in a considerable real-life survival advantage for BAV-AR that was determined primarily by age and not valve anatomy. Pragmatically, regardless of valve anatomy, patients with haemodynamically significant AR and age >50–55 years require a low-threshold for surgical referral to prevent symptom development where LVEF <60% and LVESDi >20 mm/m2 seem appropriate referral thresholds.

Abstract Scientists debate where, when, and how different visual, orthographic, lexical, and semantic features are involved in visual word recognition. In this study, we investigate intracranial neurophysiology data from 151 patients engaged in reading single words. Using representational similarity analysis, we characterize the neural representation of a hierarchy of word features across the entire cerebral cortex. We find evidence of both feed-forward and feedback processing, with early representation of visual and lexical information in lingual gyrus followed by lexical representation in fusiform gyrus and semantic sensitivity in inferior frontal gyrus, with letter representation emerging later in fusiform gyrus. Furthermore, we observed a variety of anatomically heterogeneous temporal response shapes, and these functional populations had significant feature sensitivity. Taken together, our results demonstrate the early influence of lexical, phonological, and semantic features in visual word recognition and reveal feed-forward, feed-back, and anatomically distributed processing mechanisms that contribute to visual word recognition.

Abstract Extramedullary multiple myeloma (EMM) is a subset of multiple myeloma with a poor prognosis. We report a rare case with biopsy-proven concurrent liver and mesentery primary EMM at the time of initial staging after serologic diagnosis of multiple myeloma. 18F-FDG PET/CT is valuable in detection of EMM when the patient has no osseous lesions and a negative bone marrow biopsy.