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Background Bortezomib (BTZ) is highly effective in the treatment of multiple myeloma; however, emergent drug resistance is common. The underlying mechanisms of such proteasome inhibitor resistance are still incompletely understood. Methods To further understand its resistant mechanism, we generated eight multiple myeloma (MM) cell lines resistant to bortezomib (BTZ) by exposure to increasing drug concentration: five of them acquired novel PSMB5 mutations. Given the rarity of similar mutations in over 1,500 analyzed MM patients, we explored in depth the role of the proteasome on MM cell viability and BTZ sensitivity by systematically deleting the major proteasome targets of BTZ by CRISPR. Results We demonstrated that MM cell lines without PSMB5 were surprisingly viable (mutation corresponding yeast gene pre2 is lethal). PSMB5 mutated, BTZ resistant, MM cell lines were re-sensitized to BTZ when PSMB5 was experimentally deleted, implying that this mutation is activating in its drug resistance function. In contrast PSMB6 knockout was lethal to MM cell lines, which were efficiently rescued by re-introduction of wild type PSMB6. Interestingly, reduction in PSMB6 levels also prevented the splicing of the major catalytic subunits PSMB5, PSMB7, PSMB8 and PSMB10. PSMB6 engineered with no splicing function or catalytic activity, also restored viability, inferring that the contribution of PSMB6 to proteasome structure is more important than functional activity. Supporting this observation, BTZ sensitivity was restored in resistant MM cells line by introducing low level expression of mutated PSMB6 lacking splicing function. As with PSMB6, PSMB7 knockout was lethal to MM cell lines. In contrast, loss of immunoproteasome subunits PSMB8 and PSMB9 was neither lethal nor restored sensitivity to BTZ. Our results demonstrate that expression of the three constitutive proteasome subunits PSMB5, PSMB6 and PSMB7 is highly co-dependent. This dependence is relying on the structure, but not the function, of PSMB5 and PSMB6. Conclusions In summary, PSMB5 and PSMB6, but not PSMB8 and PSMB9, are highly relevant for BTZ sensitivity in MM. Absence of PSMB6 or PSMB7, but not PSMB5, was lethal in MM cell lines. Expression of PSMB5, PSMB6 and PSMB7 was highly co-dependent. Together these findings suggest that the modulation of expression rather than function of PSMB5, PSMB6 or PSMB7 may be a new therapeutic strategy. Disclosures No relevant conflicts of interest to declare.

Background: Multiple myeloma (MM) is a heterogeneous disease with varying survival outcomes depending on the presence of certain genetic abnormalities. Common abnormalities include trisomies, translocations involving the chromosome 14, and amplifications or deletions of chromosomes 1, 13, and 17. t(11;14), occurring in 15% of patients with myeloma, had been considered a standard risk abnormality, but recent data suggest inferior outcome. This is important as new therapeutic options such as the BCL-2 inhibitor venetoclax has been shown to be particularly effective in t(11;14) patients. Methods: This was a multicenter study to identify the outcomes of patients with t(11;14), using a retrospectively assembled cohort. Patients with MM diagnosed between 2005 and 2015 with t(11;14) identified on FISH performed within six months of diagnosis, and with treatment details available and if alive, a minimum of 12 months of follow up, were enrolled. Results: The current analysis includes 1216 patients; median age of 62.56 years; 58.7% male. The median follow-up from diagnosis for the entire cohort was 51.9 months; 69.1% of the patients were alive at the last follow up. ISS stage distribution included: Stage I (35.7%), Stage II (34.0%) and Stage III (15.1%), data was missing for the rest. The distribution of concurrent FISH abnormalities included: trisomies (3.5%), del 13q (13.3%), 1q amp (8.8%), and del 17p or monosomy 17 (5.8%). Initial regimen included: 27.2% had an immunomodulatory (IMiD), 45.9% had a proteasome inhibitor (PI), 17.7% had both, and 9.0% had no novel agent. The drug classes by line of therapy are shown in Table 1. An early stem cell transplant (defined as within 12 months of start of first line treatment) was used in 49.4% of patients. The median time to next treatment (TTNT) after starting initial treatment was 26.6 (95% CI: 23.9 to 29.2) months. The median overall survival (OS) from diagnosis for the entire cohort was 95.1 (95% CI: 85.9 to 105.9) months; 4-year estimates for those diagnosed from January 2005 to December 2009, and from January 2010 to December 2014 were 77.5% and 78.6%, respectively. The median OS for those with any one high risk FISH lesion (del 17p/ 1q amp) was 67.5 (55.2, 97.1) versus 101.7 (89.7, 107.3) months. Patients with early SCT (within 12 months of diagnosis) had better OS: 108.3 (103.8, 133.0) vs. 69.8 (61.5, 80.3) months. Conclusion: Patients with t(11;14) without high risk FISH abnormalities have an excellent survival. Patients receiving a PI + IMiD combination and those receiving autologous SCT as part of initial therapy had best survival. Though numbers are limited, patients in the later lines receiving newer drugs such as venetoclax and daratumumab had high response rates and durable responses. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Bittrich:Celgene: Other: Travel Funding, Research Funding; Else Kröner Fresenius Foundation: Research Funding; Otsuka Pharmaceuticals Europe: Other: N/A; SANOFI Aventis: Membership on an entity's Board of Directors or advisory committees, N/A, Research Funding; University Hospital Wuerzburg: Employment; Bristol Myers Squibb: Research Funding; Pfizer: Other: Travel Funding; AMGEN: Other: Travel Funding; JAZZ Pharmaceuticals: Other: Travel Funding; Wilhelm Sander Foundation: Research Funding; German Research Foundation (DFG): Other: N/A; University of Würzburg: Other: N/A. Goldschmidt:Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; John-Hopkins University: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; John-Hopkins University: Research Funding; Amgen: Consultancy, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Reece:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Otsuka: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; BMS: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Research Funding. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: 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; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees. Ludwig:Celgene: Speakers Bureau; Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; PharmaMar: Consultancy; Janssen: Speakers Bureau; BMS: Speakers Bureau. Mangiacavalli:celgene: Consultancy; Amgen: Consultancy; Janssen cilag: Consultancy. Dimopoulos:Sanofi Oncology: Research Funding. Kastritis:Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria. Yee:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Karyopharm: Consultancy; Adaptive: Consultancy. Raje:Amgen Inc.: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene Corporation: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Merck: Consultancy. Rosta:Cornerstone Research Group: Employment. Haltner:Cornerstone Research Group: Employment. Cameron:Cornerstone Research Group: Employment, Equity Ownership. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy.

Introduction. Our previous flow cytometry-based comparison of HIV(+) and HIV(-) autologous hematopoietic stem cell transplant (auto-HSCT) recipient immunomes at 56, 180 and 365 days post-transplant to each other and to healthy controls (HCs) showed that both sets of auto-HSCT recipient immunomes approached HCs over time, but retained significant differences. HIV(+), but not HIV(-), auto-AHCT recipients retained pro-inflammatory features consistent with chronic HIV infection. Here, we report the results of a quantitative and functional analysis of immune reconstitution in HIV(+) patients treated with allogeneic hematopoietic stem cell transplant (allo-HSCT), in comparison with HIV(+) auto-HSCT recipients and HCs. Methods. Blood samples were collected for analysis at days 56, 180 and 365 post-transplant from HIV(+) transplant recipients and at 1 time point from HCs. Whole blood analysis was performed by five-color flow cytometry across 100 immune marker combinations. Comparisons were made between HIV(+) allo-HSCT recipients (n=17, acute myeloid leukemia, acute lymphocytic leukemia, myelodysplastic syndrome, Hodgkin and non-Hodgkin lymphoma that received myeloablative or reduced intensity conditioning on the BMT-CTN-0903/AMC-080 trial), HIV(+) auto-HSCT recipients (n=36, aggressive B cell non-Hodgkin lymphoma or Hodgkin lymphoma that received myeloablative conditioning on the BMT-CTN-0803/AMC-071 trial) and 71 HCs. Unsupervised principal component analysis (PCA) examined differences in immune cell proportions, identified by flow cytometry across 100 cell subsets at each time point. Wilcoxon rank-sum tests compared median absolute counts and median proportions of cell subsets. An independent feature importance score analysis (FIS) identified contributions of immune cell populations expressing specific immune marker combinations to the differences between HIV(+) auto-HSCT recipients, HIV(+) allo-HSCT recipients and HCs. Functional responsiveness of HIV(+) allo-HSCT recipients' T cells to stimulation with CD3- and CD28-directed antibodies, NK cells to stimulation with IL-12 and IL-18 and monocytes to stimulation with lipopolysaccharide (LPS) was assessed in a preliminary mass cytometry on peripheral blood mononuclear cells isolated at the same time points (n=2) and compared to HCs (n=2). Results. PCA showed that immunomes of HIV(+) allo-HSCT recipients and HIV(+) auto-HSCT recipients clustered together with each other, but away from HCs at all time points throughout the post-transplant year. FIS identified: 1) 13 cell subsets that defined the difference between HIV(+) allo-HSCT recipients (all visits) and HCs, and 2) 11 immune cell subsets that defined the difference between HIV(+) auto-HSCT recipients (all visits) and HCs; in both of these comparisons, activated CD3+/HLA-DR+ T cells had the greatest impact on the difference between HIV(+) and HC immunomes. At 1 year, both HIV(+) transplant recipient cohorts had higher absolute numbers of activated T cells, effector T cells and CD8+ T cells than HCs (Wilcoxon rank-sum test, p<0.0031). HIV(+) autologous and allogeneic HSCT recipients also had lower numbers of CD4+ T cells, naïve T cells and activated NK cells compared to HCs (p<0.0031). FIS also identified 20 immune cell subsets that defined the difference between HIV(+) autologous and allogeneic HSCT recipients immunomes at 1 year, with CD8+/CD27- effector T cell subset exerting the highest impact on the difference. Preliminary functional mass cytometry analysis of 2 HIV(+) allo-HSCT recipients and 2 HCs showed that: 1) IFNʏ production by CD8+ T cells was increased above that of HCs at all time points. 2) Expanded populations of CD4+/T-bet+ cytotoxic cells expressing granzyme B and perforin, and CD8+ cytotoxic T cells expressing granzyme B and perforin, persisted in HIV(+) allo-HSCT recipients at all time points, but not in HCs. 3) NK cells retained an ability to produce IFNʏ in response to stimulation with IL-12 and IL-18 in HIV(+) allo-SCT recipients. 4) Monocytes showed an enhanced production of TNFα in response to stimulation with LPS in HIV(+) allo-HSCT recipients compared to HCs at 1 year post-HSCT. Conclusion. Chronic HIV infection confers the pro-inflammatory immune features on the phenotypic and functional profiling of the T lymphocyte immunome of stem cell transplant recipients, irrespective of allogeneic or autologous stem cell donor source. Disclosures Devine: Bristol Myers: Other: Grant for monitoring support & travel support; Kiadis Pharma: Other: Protocol development (via institution); Magenta Therapeutics: Other: Travel support for advisory board; My employer (National Marrow Donor Program) has equity interest in Magenta. Noy:Janssen: Consultancy; Medscape: Honoraria; Prime Oncology: Honoraria; NIH: Research Funding; Pharamcyclics: Research Funding; Raphael Pharma: Research Funding. Popat:Bayer: Research Funding; Incyte: Research Funding; Jazz: Consultancy. Hofmeister:Celgene: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Nektar: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Imbrium: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees. Navarro:Atara Biotherapeutics: Employment, Equity Ownership. Behbehani:Fluidigm corporation: Other: Travel funding. Lozanski:Boehringer Ingelheim: Research Funding; Beckman Coulter: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentec: Research Funding. Baiocchi:Prelude: Consultancy.

Abstract BACKGROUND Molecular testing (MT) is utilized in neuro-oncology with increasing frequency. Multiple molecular panels are available providing a spectrum of information. We were interested in learning how this information is acquired, what are the practice patterns regarding this type of testing, how are the results utilized in patient care and how prepared neuro-oncologists are to interpret these results. METHODS We conducted a survey using the Society for Neuro-Oncology membership database. We developed a set of 13 questions and administered the survey to 2022 members using the online platform. RESULTS We received 153 responses (7.5% of membership). 89% percent of responders routinely order MT. Of those who do not order MT on all patients, 50% test younger patients and 57% midline tumors. 83% use MT in recurrent glioma. Other common indications for MT included: metastatic tumors, meningioma, medulloblastoma, ATRT. Majority (60%) use in-house panels, followed by Foundation One (35%), TEMPUS (13%), CARIS (10%) and other panels (23%). For 57% of respondents, the data from MT was somewhat useful and for 41% it was very useful. 78% used the results of MT for clinical decision-making. BRAF, EGFR/ALK, H3K27 mutations were most commonly used for treatment decisions. 50% of respondents have molecular tumor boards at their institutions and a majority of practitioners share the results of MT with their patients (95%). Respondents would like to see SNO-endorsed official guidelines on MT, organized lists of targeted agents available for specific mutations, a database of targetable mutations and clinical trials and more educational programs on the subject. CONCLUSIONS Molecular testing is neuro-oncology is commonly done. Many providers rely on the information for clinical decision making where appropriate. In-house and commercial genetic panels are equally used in practice. There continues to be a need for more education on the subject and development of neuro-oncology specific guidelines.

Abstract INTRODUCTION Glioblastoma has a poor prognosis, further complicated by postoperative seizures. We analyzed various factors associated with postoperative seizures in glioblastoma. METHODS Retrospective chart review of 932 patients who underwent craniotomy for glioblastoma (777=83.4% newly diagnosed; 155=16.6% recurrent) at our institution (2002–2014). Postoperative seizures were defined as those occurring within 14 days of surgery. RESULTS Our cohort consisted of 49.9% (n=465) males with mean age of 55.8 (range 9–91) years. In total, 69 (7.4%) had postoperative seizures with mean time from surgery to seizure of 3.1 days (IQR=1–4). Of 536 patients (57.5%) receiving seizure prophylaxis, those treated with Keppra were more likely to have postoperative seizures compared to those on Dilantin (10.9% vs 5.0%; p=0.022). Primary tumor patients were less likely to seize postoperatively compared to recurrent tumor patients (9.7% vs 19%; p=0.016). Patients presenting with seizure as chief complaint (12.1% vs 5.1%; p=0.025) and those with >20% of Chromosome 10 deletion were more likely to have seizures postoperatively (12.4% vs 6.1%; p=0.0029). Risk factors for postop seizures for newly-diagnosed patients included subtotal resection versus gross total resection (28.0% vs 7.1%; p=0.022). Risk factors for postop seizures for recurrent patients were >5% EGFR amplification (23.5% vs 5.8%; p=0.0021) and hyponatremia within mean 2.5 days (IQR 0–1) after surgery (20.8% vs 7.1%; p=0.035). CONCLUSION We identified several risk factors for postoperative seizures in glioblastoma patients, most of which were clinical (seizure as chief complaint, the antiepileptic chosen for prophylaxis, and extent of resection), while some were molecular and linked to genes whose products have demonstrated links to epileptogeneicity (Chromosome 10, EGFR). These findings may assist physicians in detecting glioblastoma patients that are at higher risk for postoperative seizures and in providing prophylaxis to reduce morbidity.

Abstract BACKGROUND A major impediment to improving neuro-oncology outcomes is poor clinical trial accrual. METHODS We convened a multi-stakeholder group including Society for Neuro-Oncology, Response Assessment in Neuro-Oncology, patient advocacy groups, clinical trial cooperative groups, and other partners to determine how we can improve trial accrual. RESULTS We described selected factors contributing to poor trial accrual and possible solutions. We focused on patient and community factors, disparities, physician and provider factors, clinical trial factors, and site and organizational factors CONCLUSIONS We will implement strategies with the intent to double accrual to neuro-oncology trials over the next 5 years.

AbstractA 36‐year‐old man was treated for several years with multiple agents for ankylosing spondylitis based on positive human leukocyte antigen‐B27 and sacroiliitis. He was also diagnosed with osteoporosis and hypophosphatemia. Over these years, from being an avid runner, he became dependent on a walker for ambulation. The lack of treatment response and the low phosphorus were clues that eventually led to a diagnosis of tumor‐induced osteomalacia. This case discusses the importance of not solely relying on genetic markers and sacroiliitis for diagnosing ankylosing spondylitis as other conditions can cause similar presentations.

Study Design: Retrospective review. Objectives: (1) Identify the 90-day rate of readmission following revision lumbar fusion, (2) identify independent risk factors associated with increased rates of readmission within 90 days, (3) and identify the hospital costs associated with revision lumbar fusion and subsequent readmission within 90 days. Methods: Utilizing 2014 data from the Nationwide Readmissions Database, patients undergoing elective revision lumbar fusion were identified. With this sample, multivariate logistic regression was utilized to identify independent predictors of readmission within 90 days. An analysis of total hospital costs was also conducted. Results: In 2014, an estimated 14 378 patients underwent elective revision lumbar fusion. The readmission rate at 90 days was 3.1% (n = 446). Diabetes with chronic complications was the only comorbidity found to carry significantly increased odds of readmission. Surgical complications such as deep venous thrombosis, surgical wound disruption, hematoma, and pneumonia (experienced during the index admission) were also independent predictors of readmission. Anterior approaches were associated with increased odds of readmission. The most common related diagnoses on readmission were hardware issues, postoperative infection, and disc herniation. Readmissions were associated with an average of $96 152 in increased hospital costs per patient compared with those not readmitted. Conclusion: Relevant patient comorbidities and surgical complications were associated with increased readmission within 90 days. Readmission within 90 days was associated with significant increases in hospital costs.