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Due to frequent abnormal breathing events and their effects on sleep architecture, patients with obstructive sleep apnea (OSA) exhibit decreased amounts of slow wave sleep (SWS). Reduced SWS has been linked to hypertension in community-based studies. We sought to investigate whether SWS percentage modifies the association between OSA and prevalent hypertension. We studied 7107 patients with OSA and 1118 primary snorers who underwent in-laboratory polysomnography. Patients were classified into quartiles of percent SWS. Hypertension was defined based either on clinic blood pressure measures or on physician diagnosis. Multivariable logistic regression model showed a significant interaction effect of OSA and SWS on prevalent hypertension ( P =0.002). Decreased SWS was associated with higher odds for hypertension in OSA but not in primary snoring, with patients with OSA exhibiting <0.1% SWS (OR, 1.44 [95% CI, 1.21–1.70]; P =0.001) and those with 0.1% to 4.8% SWS (OR, 1.20 [95% CI, 1.03–1.40]; P =0.02) being more likely to have hypertension compared with those with >11.1% SWS. In analysis stratified by OSA severity, significant associations between percent SWS and blood pressure emerged only in moderate and severe OSA. Effect modifications by sex ( P =0.040) and age ( P =0.007) were also only evident in OSA, indicating that decreased SWS was associated with hypertension only in men and in patients <60 years old. Decreased SWS is associated with a dose-dependent increase in odds of prevalent hypertension in patients with OSA. The effects of SWS are likely to be modulated by OSA severity. SWS may be implicated in the heightened risk of cardiovascular diseases exhibited by patients with OSA.

Purpose: To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. Methods: The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equivalent distance was used to compensate for inhomogeneous geometry. Twelve patients representing different disease sites were selected for validation. Dose calculation results in water were compared to a fast Monte Carlo code and ionization chamber array measurements using dose planes and dose profiles as well as 2-dimensional–3-dimensional and 3-dimensional–3-dimensional γ-index analysis. Results in patient geometry were compared to Monte Carlo simulation using dose–volume histogram indices, 3-dimensional–3-dimensional γ-index analysis, and inpatient dose profiles. Results: Dose engine model parameters were tuned to achieve 1.5% agreement with measured point doses. The in-water γ-index passing rates for the 12 patients using 3%/2 mm criteria were 99.5% ± 0.5% compared to Monte Carlo. The average inpatient γ-index analysis passing rate compared to Monte Carlo was 95.8% ± 2.9%. The average difference in mean dose to the clinical target volume between the dose engine and Monte Carlo was −0.4% ± 1.0%. For a typical plan, dose calculation time was 2 minutes on an inexpensive workstation. Conclusions: Following our commissioning process, the analytical dose engine was validated for all treatment sites except for the lung or for calculating dose–volume histogram indices involving point doses or critical structures immediately distal to target volumes. Monte Carlo simulations are recommended for these scenarios.

Abstract The IGHV4-34 gene is very frequent (~10%) in the B cell receptor immunoglobulin (BcR IG) gene repertoire of chronic lymphocytic leukemia (CLL). Over 30% of IGHV4-34 CLL cases can be assigned to different subsets with stereotyped BcR IG. The largest is subset #4 which represents ~1% of all CLL and ~10% of IGHV4-34 CLL and is considered a prototype for indolent disease. The BcR IG of a great majority (~85%) of IGHV4-34 CLL cases carry a significant load of somatic hypermutation (SHM), often with distinctive SHM patterns. This holds especially true for stereotyped subsets and is suggestive of particular modes of interactions with the selecting antigen(s). In detail, subsets #4 and #16, both involving IgG-switched cases (IgG-CLL), exhibit the greatest sequence similarity in SHM profiles, whereas they differ in this respect from IgM/D subsets #29 and #201. Prompted by these observations, here we explored the extent that these subset-biased SHM profiles in different IGHV4-34 stereotyped subsets were reflected in distinct demographics, clinical presentation, genomic aberrations and outcomes. Within a multi-institutional series of 20,331 CLL patients, 1790 (8.8%) expressed IGHV4-34 BcR IG. Following established bioinformatics approaches for the identification of BcR IG stereotypy, 573/1790 IGHV4-34 CLL cases (32%) were assigned to stereotyped subsets; of these, 340 cases (19% of all IGHV4-34 CLL and 60% of stereotyped IGHV4-34 cases) belonged to subsets #4, #16, #29 and #201, all concerning IGHV-mutated CLL (M-CLL). Clinicobiological information was available for 275/340 patients: #4, n=150; #16, n=44; #29, n=39; and #201, n=42. Comparisons between subsets revealed no differences in gender and age distribution. Interestingly, however, 36-43% of each subset cases were young for CLL (defined as patients aged ≤55 years), which is higher compared to general CLL cohorts, where young patients generally account for ~25% of cases. In contrast, significant differences were identified between subsets regarding: (i) disease stage at diagnosis, with >90% of IgG subsets #4 and #16 diagnosed at Binet stage A versus 83% in subset #201 and 74% in subset #29 (p=0.029); (ii) CD38 expression, ranging from 1% in subset #4 to 10% in subset #201 (p=0.013); (iii) the distribution of del(13q), peaking at a remarkable 92% in subset #29 versus only 37% in subset #16 (p<0.0001). Regarding other genomic aberrations, they were either absent (NOTCH1 mutations) or rare (SF3B1 mutations, trisomy 12, del(11q), TP53 aberrations due to either del(17p) and/or TP53 mutations). The sole exception concerned a high frequency (14%) of TP53 aberrations in subset #29 (p<0.05 compared with the other subsets), which is notable for M-CLL cases in general. Time to first treatment (TTFT) could be analyzed in 228 cases. IgG subsets #4 and #16 had significantly (p=0.036) longer TTFT (median TTFT: not yet reached) compared to the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). In conclusion, we have identified distinct clinicobiological profiles for different stereotyped IGHV4-34 M-CLL subsets, highlighting subsets #4 and #16 as particularly indolent, which is important for both medical and social reasons, especially considering that a significant proportion of patients in these subsets are diagnosed at younger ages. Our findings support the notion that BcR IG stereotypy refines prognostication in CLL, superseding the crude immunogenetic distinction based on SHM load only. Additionally, the observed heterogeneity suggests that not all M-CLL are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Disclosures Tausch: Gilead: Other: Travel support. Shanafelt:Glaxo-Smith_Kline: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Polyphenon E Int'l: Research Funding; Hospira: Research Funding; Janssen: Research Funding; Pharmactckucs: Research Funding; Cephalon: Research Funding. Niemann:Gilead: Consultancy; Janssen: Consultancy; Roche: Consultancy; Novartis: Other: Travel grant. Langerak:InVivoScribe: Patents & Royalties: Licensing of IP and Patent on BIOMED-2-based methods for PCR-based Clonality Diagnostics.; DAKO: Patents & Royalties: Licensing of IP and Patent on Split-Signal FISH. Royalties for Dept. of Immunology, Erasmus MC, Rotterdam, NL; Roche: Other: Lab services in the field of MRD diagnostics provided by Dept of Immunology, Erasmus MC (Rotterdam). Hallek:Celgene: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; AbbVie: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Roche: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Boehringher Ingelheim: Honoraria, Other: Speakers Bureau and/or Advisory Boards; Pharmacyclics: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Mundipharma: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Janssen: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Gilead: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding. Ghia:Janssen Pharmaceuticals: Research Funding.

Patients who develop therapy-related myelodysplastic syndromes (t-MDSs) or acute myeloid leukemia (t-AML) following prior chemotherapy or an autologous hematopoietic cell transplant (HCT), have a poor prognosis. An earlier analysis of allogeneic HCT (n=868, 1990-2004) showed 5-year overall survival (OS) and disease free survival (DFS) were 22% and 21% (reference). Furthermore, older age, graft source other than a HLA-matched sibling or HLA well matched unrelated donor (URD), t-AML not in remission or advanced t-MDS, and poor risk cytogenetics were associated with worse outcomes. Modern supportive care and conditioning regimens including reduced intensity (RIC) regimens may have improved outcomes. Therefore we analyzed 1531 HCT for t-AML (n = 772) or t-MDS (n = 759) performed from 2000 to 2014. The median age at transplant was 52 (18-77) for t-AML and 59 (18-74) for t-MDS. Eleven percent of patient with t-AML and 24% of patient with t-MDS had a prior autologous transplant. A myeloablative regimen was used for conditioning in 61% of patients with t-AML and 49% of patients with t-MDS (Table 1). For t-AML, the 5-year non-relapse mortality (NRM) and relapse rates (RR) were 33% (95% confidence interval [CI], 30-36) and 43% (40-47), respectively. For t-MDS, the 5 year TRM and RR were 32% (29-36) and 46% (43-50), respectively. Five year DFS and OS were 24% (21-27) and 25% (22-28), respectively, for patients with t-AML. Five year DFS and OS were 21% (18-24) and 27% (23-31), respectively, for patients with t-MDS. In multivariate analysis, t-AML OS and DFS was worse for: previous autologous transplant, relapsed disease at HCT, intermediate or adverse cytogenetics, partially matched and cord blood grafts, and RIC. For t-MDS: age greater than 60, previous autologous transplant, very high IPSS score, and use of HLA-partially matched unrelated grafts. A significant minority of patients with t-AML and t-MDS can achieve long-term remission with allogeneic HCT, yet risks of both NRM and relapse are still excessive. Relapse is the major cause of treatment failure. Disclosures Metheny: Takeda: Speakers Bureau; Incyte: Speakers Bureau. Weisdorf:Incyte: Research Funding; Fate Therapeutics: Consultancy; Pharmacyclics: Consultancy. Kebriaei:Jazz: Consultancy; Amgen: Research Funding; Pfizer: Honoraria; Kite: Honoraria.

Cancer cells have altered energy demand due to their increased proliferative capacity. In Waldenstrom Macroglobulinemia (WM), an indolent yet incurable B-cell lymphoma, the homeostasis of the bone marrow (BM) environment is disturbed due to the infiltration of the lymphoplamacytic cells that continuously produce monoclonal IgM. An alteration in energy demand could skew the balance of key proteins and metabolites towards a permissive niche for WM tumor cells growth, and unfavorably effect on the immune response against tumor cells. Therefore, the aim of our study was to identify how changes in certain metabolites and/or proteins could contribute to the pathobiology of WM and whether the cytokine and chemokine composition of the BM microenvironment play a role in such changes. WM patient's samples including BM plasma, peripheral blood serum and BM cells (n=101) as well as equivalent normal counterparts (n=86) were collected and used for metabolomics analysis. Comprehensive targeted metabolomics analysis was performed using Capillary Electrophoresis Time-of-Flight Mass spectrometry (CE-TOFMS), CE-triple quadrupole mass spectrometry (CE-qQqMS) and Liquid Chromatography (LC-TOFMS). Normal and WM peripheral blood serums samples were also used for untargeted proteomics analysis using a fully automated proteomic technology platform that includes an Agilent 1200 Series Quaternary HPLC system connected to a Q Exactive Plus mass spectrometer. Real-time PCR analysis was performed to detect the gene expression of the relevant metabolite transporters located on the cell membrane. BM cells from control and WM patients' samples were used for flow cytometry analysis. IHC was used to detect the proteins on the BM tissues. Principal Component Analysis (PCA) and Hierarchal Clustering Analysis (HCA) on both metabolomics and proteomics data identified two distinct clusters for disease and normal samples, indicating that there are differentially expressed proteins and metabolites in WM versus normal samples. Furthermore, pathway analysis showed that the majority of the altered metabolites were the members of the glutathione (GSH) metabolism pathway. This finding was further validated not only by data obtained from metabolomics analysis of BM cells and BM plasma, but also by proteomic data WM patients serum, implying that GSH metabolism is key to the biology of WM. Moreover, stimulation of WM cell lines by IL-6 and IL-21, cytokines involved in inducing WM cell proliferation and IgM secretion, resulted in increased gene expression of the transporters mediating uptake of metabolites required for GSH synthesis, including SLC7A11, 4F2HC and LAT1, indicating that cytokines in the WM BM could modulate GSH metabolism. In addition, IHC staining of the BM tissues as well as flow cytometry analysis of patients' lymphoplasmacytic cells identified glutathione peroxidase as one of the major proteins modulating GSH metabolism in WM. In summary, our data highlight a central role for GSH metabolism in WM disease biology and indicate that intervening with the metabolic processes could be a potential therapeutic strategy for patients with WM. Disclosures Ansell: AI Therapeutics: Other: research funding for clinical trials; Seattle Genetics: Other: research funding for clinical trials; Regeneron: Other: research funding for clinical trials; Affimed: Other: research funding for clinical trials; Bristol Myers Squibb: Other: research funding for clinical trials; Pfizer: Other: research funding for clinical trials; Merck: Other: research funding for clinical trials; Takeda: Other: research funding for clinical trials.

Myeloid derived suppressor cells (MDSC) are a heterogeneous population of undifferentiated myeloid cells that are expanded and activated in pathological conditions and have the ability to potently suppress T-cell function and thereby contribute to immunosuppression and tumor progression. While there have been studies showing a role for MDSC in a variety of hematological malignancies, no data is available indicating that MDSCs contribute to the tumor progression in Waldenstrom's Macroglobulinemia (WM), an indolent lymphoma characterized by bone marrow (BM) infiltration of lymphoplasmacytic (LPL) cells and increased secretion of monoclonal IgM. In previous work, we have found increased GM-CSF and reduced arginine and cysteine in the BM microenvironment in WM. We hypothesized that this was due to the presence and activity of MDSCs in WM. BM aspirates from WM patients (n=17) were therefore processed to isolate LPL (CD19+/CD138+) cells from the rest of the BM cells (CD19-/CD138-). Sorted (CD19-/CD138-) cells from BM of patients with WM were studied with flow cytometry. Using a sequential gating strategy (lack of lineage markers, low levels of HLADR, CD33+, CD11b+) we identified a population of MDSCs that were then subdivided using CD14 and CD15 expression into total-, monocytic-, or granulocytic- MDSCs (m-MDSC, g-MDSC). We also analyzed unsorted BM cells using cytometry by time-of-flight (CyTOF) in order to further identify and phenotypically characterize the BM MDSC population in a group of WM patients with smoldering (asymptomatic) disease, symptomatic disease, or in remission post-treatment. BM samples from normal subjects were used as a control. Flow cytometry data showed significant higher numbers of MDSC subsets expressing PD-L1 and Arginase1 in WM patients when compared to the normal samples. BM cells from WM patients (n=18) then were compared to controls (n=11), and the absolute number of the total MDSC (p=0.05), m-MDSC (p=0.002), g-MDSC (p=0.02) was increased in WM specimens. When MDSCs from WM or normal monocytes from healthy controls were co-cultured with activated T-cells, the proliferation of activated T-cells in the presence of MDSCs from WM patients was impaired compared to controls, confirming the suppressive role of MDSCs. We then performed high dimensional analysis of the total BM MDSC cells using t-SNEand identified phenotypically distinct MDSC cell populations in the BM that were differentially present when healthy controls were compared to patients with smoldering WM or those with WM needing treatment. Specifically, WM patients needing treatment had increased numbers of a distinct MDSC population that was highly positive for CD163, and CD138. Moreover, conventional markers denoting m-MDSC and g-MDSC, such as CD14 and CD15, were highly expressed in all populations and their pattern of expression did not specifically define the MDSC subtypes, indicating that high dimensional phenotyping further details the MDSC sub-compartments beyond the conventional categorization of MDSC using conventional cytometry. In summary, we find that MDSCs are increased in the BM of WM patients compared to controls. MDSCs expressing CD163 and CD138 increase when WM patients become symptomatic and require therapy. Furthermore, MDSCs in the BM of WM patients suppress T-cell function and likely contribute to progression of the disease. MDSCs in the BM therefore present a therapeutic target that should be explored in WM patients. Disclosures Ansell: Bristol Myers Squibb: Other: research funding for clinical trials; Merck: Other: research funding for clinical trials; AI Therapeutics: Other: research funding for clinical trials; Affimed: Other: research funding for clinical trials; Takeda: Other: research funding for clinical trials; Pfizer: Other: research funding for clinical trials; Regeneron: Other: research funding for clinical trials; Seattle Genetics: Other: research funding for clinical trials.

Although some data (Scott, JCO 2017) suggest that myeloablative conditioning (MAC) is preferred for allogeneic hematopoietic cell transplantation (HCT) in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS), these data were not informed by analysis of disease specific risk factors. We analyzed AML and MDS HCT outcomes stratified by the disease risk index (DRI) in order to identify the preferred transplant conditioning intensity (reduced-intensity conditioning [RIC] vs. MAC). In this large CIBMTR registry study we identified 4387 adult patients (age 40-65 years) who received HCT for AML (68%) or MDS (32%) between 2009 and 2015. DRI was stratified as low/ intermediate risk (1539 MAC and 999 RIC) and high/ very high risk (1121 MAC and 728 RIC). Examining the low/ intermediate risk DRI cohort (Table), RIC was associated with lower risk of TRM (HR=0.74, 95% CI 0.62-0.88; p<0.001) but significantly higher risk of relapse (HR=1.54, 95% CI 1.35-1.76; p<0.001). As a result, RFS in this cohort was significantly worse with RIC (HR=1.19, 95% CI 1.07-1.33; p=0.001). In the high/ very high risk DRI cohort, RIC resulted in similar TRM (HR=0.83, 95% CI 0.68-1.00; p=0.051) but again significantly higher risk of relapse (HR=1.23, 95% CI 1.08-1.41; p=0.002). RFS in high/ very high risk DRI cohort was similar between RIC and MAC. Adjusted outcome curves for the 3 endpoints are shown in the Figure. In this large study of HCT for AML or MDS stratified by DRI, RIC was independent predictor of lower TRM, but significantly higher risk of relapse. The MAC was an independent predictor of lower relapse in both low/ intermediate and high/very high DRI groups. However, MAC only resulted in RFS benefit in the low/ intermediate group where the magnitude of impact on relapse was not offset by the higher TRM. In adults with AML or MDS aged 40-65 years, these data support MAC as the preferred conditioning intensity for low/ intermediate risk DRI, whereas MAC does not provide significant benefit in those with high/ very high risk DRI. Safer, yet still potent MAC regimens could benefit this higher risk group. Disclosures Bejanyan: Kiadis Pharma: Other: advisory board. Brunstein:Gamida: Research Funding; Astex: Research Funding; Magenta: Research Funding. Kebriaei:Amgen: Research Funding; Jazz: Consultancy; Pfizer: Honoraria; Kite: Honoraria; Pfizer: Honoraria; Kite: Honoraria. Weisdorf:Fate Therapeutics: Consultancy; Pharmacyclics: Consultancy; Incyte: Research Funding.

Introduction: AML patients with intermediate or high-risk features often undergo allogeneic hematopoietic cell transplantation (alloHCT) during first complete remission (CR). The 2017 European LeukemiaNet guidelines for AML specify categories of CR: both with and without count recovery (CR vs. CRi) and with and without measurable residual disease (MRD). Previous smaller retrospective studies have suggested poorer survival outcomes after alloHCT for patients with responses less than CR. Methods: Eligible cases were determined using the CIBMTR registry. Each had AML in CR1, was ≥ 18 years, and underwent alloHCT between January 1, 2007 and December 31, 2015. MRD was defined based on the answers to qualitative questions on standard clinical reporting forms that ask if the patient is in either molecular or cytogenetic remission and if disease is detected in marrow by flow cytometry at time of HCT. The primary outcome was overall survival (OS), and secondary outcomes were non-relapse mortality (NRM), relapse and disease-free survival (DFS). The Kaplan-Meier method was used to estimate survival and cumulative incidence function was used to estimate relapse and NRM. Multivariable analysis (MVA) was performed using the Cox proportional hazards model to adjust for patient-, disease-, and transplant-related factors. Adjusted probabilities of DFS and OS, adjusted cumulative incidence curves of NRM and relapse were generated from final Cox regression models stratified on CR vs. CRi and weighted averages of covariate values using pooled sample proportion as weight function. Results: We identified 2492 cases (CR, n=1799; CRi, n=693). The main effect variable (CR vs. CRi) was missing in 262 additional patients; these patients were excluded when univariate analysis confirmed no significant associations, suggesting a random distribution of missing data. Patient characteristics are summarized in Table 1. Compared with patients with CR, patients with CRi were more likely to have a Karnofsky score <90 (38% vs. 31%) and an HCT-CI score 3+ (47% vs. 40%). Other variables were well matched between the groups. MVA demonstrated significantly increased likelihood of mortality in patients with CRi compared to those with CR with hazard ratio (HR) 1.27; 95% confidence interval (CI) (1.13-1.43) (Figure 1A). Other covariates significantly associated with shorter OS included older age, poor-risk cytogenetics, lower Karnofsky score, higher HCT-CI score, and higher white blood cell count at diagnosis. The adjusted OS probabilities at 5 year post-HCT accounted for factors from MVA model are 50% (95%CI 47-52) for patients with CR and 43% (95%CI 39-47) for patients with CRi. CRi was also associated with significantly increased NRM [HR 1.33, 95%CI(1.11-1.59)] with only a trend in increased relapse [HR 1.15, 95% CI(0.99-1.34), p=0.07] resulting in inferior DFS [HR 1.20, 95%CI(1.07-1.35)]. MRD status was available in a subset of 2297 patients, and pairwise comparison demonstrated that presence of MRD was associated with shorter OS, shorter DFS, higher NRM, and increased relapse compared to absence of MRD (Figure 1B). Pairwise interaction between the main effects (CR vs. CRi) and MRD status were tested with no significant findings at a level of 0.01, demonstrating that the effects of incomplete count recovery and MRD are independent of each other. Conclusions: Analysis of this large CIBMTR cohort demonstrates that survival outcomes differ among AML patients nominally in CR at the time of alloHCT. Patients with CRi and/or MRD have significantly shorter OS after alloHCT compared to those in CR, as well as shorter DFS and higher NRM. Further studies should focus on limiting NRM and reducing relapse to optimize post-alloHCT outcomes for patients with responses less than CR. Disclosures Percival: Pfizer Inc.: Research Funding; Nohla Therapeutics: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees. Kebriaei:Jazz: Consultancy; Pfizer: Honoraria; Amgen: Research Funding; Kite: Honoraria. Weisdorf:Fate Therapeutics: Consultancy; Incyte: Research Funding; Pharmacyclics: Consultancy.