Citations

Abstract Background. The strongest established prognostic factors for follicular lymphoma are age and clinical factors. Biologic studies suggest a major role for the host immunologic environment in follicular lymphomagenesis, which is in part determined by host genetic background. Cytokines are key regulators of immune function and regulation, are highly polymorphic, and have been implicated in lymphoma etiology and prognosis. We evaluated the hypothesis that inherited variability in cytokine and related immune genes impact overall survival in follicular lymphoma. Methods. We genotyped 73 single nucleotide polymorphisms (SNPs) from 44 candidate cytokine and immune genes in 278 follicular lymphoma patients who participated in a population-based case-control study conducted from 1998–2000 in the Detroit, Iowa, Los Angeles and Seattle SEER (Surveillance, Epidemiology and End Results) cancer registries. Baseline clinical data and survival through early 2005 were obtained from cancer registry files. Cox proportional hazards analysis was used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for the association between individual SNPs and overall survival, adjusting for age, demographic and clinical factors. We also used parallel modeling strategies to identify the best summary multi-SNP risk score to predict survival, and applied these results in a time-dependent receiver-operator characteristics (ROC) analysis. Results. The median age at diagnosis was 57 years (range, 25–74), and 59 (21%) of the patients died during follow-up, with a median follow-up of 59 months (range, 27 – 78 months) for surviving patients. In multivariate modeling, SNPs in IL8 (rs4073; HRTT=2.14, 1.26–3.63), IL2 (rs2069762; HRGT/TT=1.80, 1.06–3.05), IL12B (rs3212227; HRAA/CC=1.83, 1.06–3.06), and IL1RN (rs454078; HRAA=1.93, 1.11–3.34) were the strongest and most robust predictors of survival. A summary score of the number of deleterious genotypes from these four genes was strongly associated with survival (p=1.4 × 10−5) after accounting for demographic and clinical variables (HR=2.06 per deleterious genotype, 1.52–2.79). A combination of the four SNPs and the demographic and clinical risk scores was strongly associated with survival (p=1.8 × 10−11); the 5-year Kaplan Meier survival estimates were 96% (93%–100%), 72% (62%–83%) and 58% (48%–72%) for low, intermediate, and high risk groups respectively. In a time-dependent ROC analysis the three risk groups had an area under the curve (AUC) of 0.83 at 72 months of follow-up (95% CI 0.72–0.93). Conclusion: Host genetic variability in immune genes, particularly IL8, IL2, IL12B, and IL1RN, individually and particularly in combination, was associated with overall survival in follicular lymphoma after accounting for demographic and clinical factors. Host immunogenetics is a promising class of prognostic factors in follicular lymphoma that warrants further evaluation.

Abstract Background: Several studies suggest that smoking and obesity may increase the risk of developing NHL, but the impact of these factors on survival is relatively unexplored. One recent population-based Italian study found that smoking may negatively impact overall survival. Methods: We evaluated the association of body mass index (BMI) and cigarette smoking on overall survival in 1,286 patients who participated in a population-based case-control study conducted through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Iowa, Seattle and Los Angeles. BMI (on 1189 participants) and a smoking history (on 471 participants) were obtained through in-person interviews. Histology, stage, presence of B symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site in the spring of 2005. Hazard Ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards models, while adjusting for demographic and clinical factors. Results: The median age at diagnosis was 58 years (range: 16 – 74), and the most common histologies were DLBCL (33%), follicular (25%), SLL/CLL (12%), marginal zone (9%), mantle cell (4%) and Peripheral T-cell (3%). The median BMI was 26.6 (range: 16.2 – 47.3), and 26% of patients were classified as obese (i.e. BMI >30). Of patients with a smoking history, 47% had never smoked, 19% were active smokers at diagnosis, and 34% were former smokers. No significant differences were observed between those with and without tobacco use data in terms of primary lymphoma characteristics. Overall survival (OS) was defined as time from diagnosis to death due to any cause. Median follow-up on all living patients was 58 months (range: 4 – 78), and 333 patients had died. When BMI was assessed as a continuous measure, it was borderline significantly associated with OS (p=0.050). An indicator of whether or not BMI > 30 was also significantly associated with OS (HR=1.30; 95% CI: 1.01 – 1.68; p=0.042). Ever vs. never smokers also exhibited a survival disadvantage (HR=1.66; 95% CI: 1.12 – 2.44; p=0.011). When broken down further, former smokers who had smoked for >10 years (HR=1.61; 95% CI: 1.02 – 2.52; p=0.039) and current smokers (HR=1.79; 95% CI: 1.07 – 3.02; p=0.028) were at a survival disadvantage over those who had never smoked. When both smoking and BMI status were included in the model, only the indicator of being a current smoker remained statistically significant (p=0.031), with a trend toward decreased survival for former smokers who had smoked >10 years (p=0.061) and those with BMI >30 (p=0.058). Conclusions: NHL patients who smoke or are obese had a poorer overall survival. These observations warrant further investigation, including whether interventions for smoking cessation or weight loss can impact NHL survival.

Abstract Background: Mantle cell lymphoma (MCL) is an incurable non-Hodgkin lymphoma. MCL is characterized by the chromosomal translocation t(11;14) leading to overexpression of cyclin D1 (CCND1), a regulator of the cell cycle. NF-κB plays a central role in key cellular processes, including cell cycle regulation and apoptosis, and it has been shown to be constitutively activated in MCL cell lines and in patient biopsy samples and to play a key role in the growth and survival of MCL cells. In an exploratory study, we evaluated the hypothesis that germline variation in candidate genes from the cell cycle and NF-κB pathways predict overall survival in MCL. Methods: We genotyped 235 SNPs from 29 cell cycle genes and 447 SNPs from 55 NF-κB genes in 39 MCL patients aged 38–64 years who participated in a population-based study conducted from 1998–2000 through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles county. Tagging single nucleotide polymorphisms (SNPs) were selected from HapMap. Stage, presence of B-symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site. To assess the statistical significance of a gene, we first used principal components analysis to capture the genetic variation of the SNPs within a gene. Cox proportional hazards analysis was then used to assess the association between the top principal components from a gene with overall survival. Results: Through early 2005, there were 22 deaths in 39 patients (56%). The median follow-up of the 17 surviving patients was 56 months (range 36–70). Eleven of the 55 genes (TNFSF14 p=0.0007, NF-κBIA p=0.003, IL1R2 p=0.01, TNFRSF25 p=0.02, TNFSF13B p=0.02, FAS p=0.03, TLR2 p=0.04, TNFSF10D p=0.04, TNFSF10 p=0.06, MAP3K2 p=0.06) in the NF-κB pathway were associated with overall survival. In the cell cycle pathway, only 3 of the 29 genes (CASP5 p=0.06, CASP9 p=0.09, BCL2 p=0.09) were associated with overall survival, and a previously reported SNP in CCND1 (rs603965) showed no association (p=0.5). Permutation p-values for observing at least this number of associated tests in each pathway due to chance (from multiple testing) was p=0.8 for the cell cycle pathway and p=0.03 for NF-κB pathway. The small sample size precluded multi-gene modeling. Conclusion: In a population series of MCL patients, we found suggestive evidence that host genetic variation in candidate NF-κB pathway genes affects overall survival. These results complement tumor expression data implicating this pathway in the pathogenesis of MCL. In addition, such findings further support the value of developing therapeutic targets from this pathway.

Abstract Background. Intracellular one-carbon transfer reactions are essential for nucleotide synthesis and methylation of biologic compounds including DNA. Previous studies have linked genetic variants in one-carbon metabolism genes with risk of developing NHL, but little is known regarding the impact of these variants on disease outcome. We evaluated the hypothesis that inherited genetic variation in genes involved in one-carbon metabolism is associated with overall survival in DLBCL. Methods. We genotyped 30 single nucleotide polymorphisms (SNPs) from 18 candidate one-carbon metabolism genes in 215 DLBCL patients who participated in a population-based case-control study conducted from 1998–2000 using the SEER (Surveillance, Epidemiology and End Results) cancer registries in the Detroit, Iowa, Los Angeles and Seattle. Stage, B-symptoms, first course of therapy, date of last follow-up and vital status through early 2005 were obtained from cancer registry files. Cox proportional hazards analysis was used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for the association between individual SNPs and overall survival, adjusting for age, demographic and clinical factors. We also used parallel modeling strategies to identify the best summary multi-SNP risk score to predict survival. Results. The median age at diagnosis was 57 years (range, 20–74), and 50 (23%) of the patients died during follow-up, with a median follow-up of 57 months (range, 31–78 months) for surviving patients. After adjusting for demographic and clinical variables, SNPs in SHMT1 (rs1979276; HRCT/TT=2.47, 1.31–4.67), BHMT (rs585800; HRAT/TT=2.02, 1.16–3.54), and TCN1 (rs526934; HRTT=1.86, 1.04–3.33) were the strongest and most robust predictors of survival. A summary score of the number of deleterious genotypes (0–3) from these three genes was strongly associated with survival (p=7.9 x 10−5) after accounting for demographic and clinical variables (HR=2.58 per deleterious genotype, 95% CI 1.75–3.80). A risk score combining the three SNPs with clinical and demographic variables (score of 0 to 5) was even more strongly associated with survival (p=1.4 x 10−13); the Kaplan Meier survival curves are shown in the Figure. In a time-dependent ROC analysis, the combined risk score had a concordance index of 0.75 at 5 years of follow-up (95% CI 0.69–0.81). Conclusion: Host genetic variation in the one-carbon metabolism genes SHMT1, BHMT, and TCN1, individually and particularly in combination, was associated with overall DLBCL survival after accounting for clinical and demographic factors, supporting a role for this pathway in disease progression. Future work should evaluate interactions of genes from this pathway with dietary nutrients and therapeutic agents in DLBCL prognosis. Figure Figure

4127 Background: The MMRpredict model, developed at the University of Edinburgh, is a web-based model developed to predict which patients diagnosed with colorectal cancer (CRC) under age 55 years have germline mutations in a DNA mismatch repair (MMR) gene [Barnetson et al., NEngJMed 2006;354:2751–63]. Stage 1 MMRpredict estimates the carrier probability for MMR mutations from clinical parameters (age of diagnosis of colorectal cancer, proximal vs distal site, family history, multiple primary CRCs). We evaluated the performance of Stage 1 of this model in a well characterized cohort of colorectal cancer patients. Methods: Cases with CRC were identified through the Minnesota Cancer Surveillance System (MCSS), a population based registry and Mayo Clinic Rochester, a clinical practice. All were consented participants in the Mayo Colon Cancer Family Registry. Of 342 cases tested for MMR mutations (MLH1, MSH2, MSH6), 45 had insufficient information on colon site and 62 were older than 55 and could not be used in the study. The remaining 235 included 110 females/125 males; 90 cases with proximal site/145 with distal site; 229/235 were self-identified as White. Results: We defined 5 probability risk groups based on output from the MMRpredict web model Stage 1: 1–10%, 11–25%, 26–50%, 51–75%, and 76–100%. In our study, the number of cases in each of these groups was 60, 45, 65, 34, and 31, respectively. The corresponding number of mutations in each group was 1 (1.7%), 4 (8.9%), 9 (13.8%), 3 (8.8%), and 11 (35.5%). Overall, 28/235 patients were found to have mutations (11.9%), compared to predicted range of 62–107 (26–45%). Conclusion: MMRpredict Stage 1 over-estimated the probability of detecting a MMR gene mutation in this study. This may reflect ascertainment issues or genetics of different populations. No significant financial relationships to disclose.

Introduction: Anti-PD-1 monoclonal antibodies (mAbs) are highly active in relapsed/refractory classical Hodgkin lymphoma (cHL), but most patients (pts) will still relapse. Given this, allogeneic stem cell transplantation (alloHSCT) remains an important option for pts after PD-1 blockade, as it offers the possibility of cure. Prior reports have suggested that alloHSCT after PD-1 mAbs may be associated with severe immune-related complications including acute graft-versus-host disease (GVHD), veno-occlusive disease (VOD) and cytokine release/febrile non-infectious syndrome (CRS). Prior studies of alloHSCT after PD-1 blockade in cHL have been limited by the small number of pts and short follow-up, preventing an accurate assessment of long-term outcomes and complications, risk factors for early toxicity, and the impact of transplant strategies such as choice of GVHD prophylaxis. We therefore assembled a large retrospective international cohort of cHL pts who underwent alloHSCT after PD-(L)1 blockade to better answer these questions, including an assessment of the impact of post-transplant cyclophosphamide (PTCy) on efficacy and toxicity. Methods: Medical records and databases were reviewed at 26 European and United States transplant centers to identify pts with cHL who underwent an alloHSCT any time after receiving a PD-1 or PD-L1 mAb. Response assessment was performed by local investigators according to Lugano 2014 criteria. Overall survival (OS), progression-free survival (PFS), cumulative incidence (CumInc) of relapse (CIR), non-relapse mortality (NRM), acute (a) and chronic (c) GVHD were estimated, as was the association between baseline variables and these outcomes. Results: Between 2014 and 2019, 150 pts were identified who underwent alloHSCT after a median of 10 (range, 1-74) doses of nivolumab (n=118), pembrolizumab (n=31), or avelumab (n=1). The median age was 31 (range 17-68) and pts had received a median of 4 (range, 2-11) lines of therapy prior to PD-(L)1 blockade. 138 pts (92%) had failed BV and 111 (74%) autologous HSCT. The best overall response to PD-(L)1 mAbs was CR for 62 pts (41%), PR for 55 (37%), SD for 17 (11%), PD for 15 (10%) and unknown for 1 (1%). Median time from last dose of PD-(L)1 mAb to alloHSCT was 80 days (range, 17-756) with 70 pts (47%) receiving intervening systemic therapy. At alloHSCT, 90 pts were in CR (60%), 45 in PR (30%), 5 in SD (3%), and 10 in PD (7%). Donors were haploidentical (n=71, 47%), matched sibling (n=29, 19%), matched unrelated (n=39, 26%), mismatched unrelated (n=7, 5%), cord blood (n=2, 1%), or unknown (n=2, 1%). Stem cell source was bone marrow (n=38, 25%), peripheral blood (n=110, 73%), or cord blood (n=2, 1%). GVHD prophylaxis included PTCy in 88 pts (59%) (69/71 (97%) with haploidentical donors; 19/79 (24%) with other donors). With a median post-alloHSCT follow-up for survivors of 23.8 months (range, 1-67), the 2y OS and PFS were 79% (95CI 71-86%) and 65% (95CI 55-73%), respectively, while the 2y CumIncs of relapse and NRM were 21% (95CI 13-29%) and 14%, (95CI, 8-22%), respectively (Fig. 1A-B). 27 pts have died, 3 due to disease and 24 to NRM, including aGVHD (n=7) and VOD (n=2). Veno-occlusive disease (VOD) occurred in 5 pts (day 100 CumInc 4%) and 29 pts (19%) developed CRS (grade 1 n=16; grade 2 n=7; grade 3 n=4; grade 4 n=2). The 6-month CumIncs of grade 2-4, grade 3-4 and grade 4 aGVHD were 39%, 16% and 8%, respectively. Hyperacute GVHD (onset ≤ 14 days after alloHSCT) occurred in 4% of pts and was fatal in 2 pts. The 2y CumInc of cGVHD was 45%. Neither receipt of > 10 doses (median) of anti-PD-(L)1 mAb nor undergoing alloHSCT ≤80 days (median) after last dose of PD-(L)1 mAb were associated with PFS or OS. However, pts with a shorter time to transplant (≤80 days) appeared to have a higher risk of severe (grade 3-4) aGVHD (6m CumInc 24% vs 9%, p=0.006). Recipients of PTCy in this cohort had lower 2y CumIncs of cGVHD (34% vs 58%, p=0.01) and relapse (12% vs 31%, p=0.02), superior 2y PFS (76% vs 54%, p=0.015), and similar rates of severe aGVHD (15% vs 18%, p=0.5), 2y NRM (12% vs 16%, p=0.5), and 2y OS (82% vs 78%, p=0.6). Conclusions: With extended follow-up of a large international cohort, our results argue that alloSCT performed after PD-(L)1 mAbs is a feasible strategy associated with an excellent PFS and a very low CIR for this disease. The use of PT-Cy appears to be associated with improved outcomes and may at present represent the optimal transplant strategy in this pt population. Figure Disclosures Corradini: kite: Honoraria; Abbvie: Honoraria; Servier: Honoraria; Sanofi: Honoraria; Takeda: Honoraria; Roche: Honoraria; Novartis: Honoraria; KiowaKirin: Honoraria; Janssen: Honoraria; Gilead: Honoraria; Daiichi Sankyo: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Ho:Jazz Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Consultancy; Omeros Corporation: Membership on an entity's Board of Directors or advisory committees. Jaglowski:Kite: Consultancy, Other: advisory board, Research Funding; Novartis: Consultancy, Other: advisory board, Research Funding; Juno: Consultancy, Other: advisory board; Unum Therapeutics Inc.: Research Funding. Herrera:Adaptive Biotechnologies: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; AstraZeneca: Research Funding; Merck: Consultancy, Research Funding; Genentech, Inc.: Consultancy, Research Funding; Pharmacyclics: Research Funding; Immune Design: Research Funding; Kite Pharma: Consultancy, Research Funding. Blaise:Jazz Pharmaceuticals: Honoraria; Sanofi: Honoraria; Pierre Fabre medicaments: Honoraria; Molmed: Consultancy, Honoraria. Hamadani:Pharmacyclics: Consultancy; Sanofi Genzyme: Research Funding, Speakers Bureau; Merck: Research Funding; Otsuka: Research Funding; Janssen: Consultancy; Medimmune: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy. Ansell:LAM Therapeutics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Affimed: Research Funding. Nieto:Astra-Zeneca: Research Funding; Affimed: Consultancy; Affimed: Research Funding; Novartis: Research Funding. Feldman:Celgene: Honoraria, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Other: Travel expenses, Speakers Bureau; Pfizer: Research Funding; AbbVie: Honoraria, Other: Travel expenses, Speakers Bureau; Portola Pharma: Research Funding; Kite Pharma: Honoraria, Other: Travel expenses, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Pharmacyclics: Honoraria, Other: Travel expenses, Speakers Bureau; Kyowa Hakko Kirin: Research Funding; Eisai: Research Funding; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Cell Medica: Research Funding; Roche: Research Funding; Corvus: Research Funding; Viracta: Research Funding; Trillium: Research Funding; Roche: Research Funding; Takeda: Honoraria, Speakers Bureau. McGuirk:ArticulateScience LLC: Other: Assistance with manuscript preparation; Bellicum Pharmaceuticals: Research Funding; Kite Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Gamida Cell: Research Funding; Pluristem Ltd: Research Funding; Juno Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Research Funding; Novartis: Research Funding; Fresenius Biotech: Research Funding. Mohty:Jazz Pharmaceuticals: Honoraria, Research Funding. Stamatoulas Bastard:Celgene: Honoraria; Takeda: Consultancy. Houot:Bristol Myers Squibb: Honoraria; Merck Sharp Dohme: Honoraria. Manson:Bristol Myers Squibb: Honoraria. Orvain:Incyte: Honoraria; Novartis: Honoraria; Jazz Pharmaceuticals: Other: Travel & accommodations; Pfizer: Other: Travel & accommodations. Bouabdallah:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Frigault:Novartis: Consultancy; Kite/Gilead: Honoraria; Nkarta: Consultancy; Incyte: Consultancy; Juno/Celgene: Consultancy; Foundation Medicine: Consultancy; Xenetic: Consultancy. Chen:Takeda: Consultancy; Kiadis: Consultancy; Magenta: Consultancy; Abbvie: Consultancy; Incyte: Consultancy. Lynch:T.G. Therapeutics: Research Funding; Rhizen Pharmaceuticals S.A: Research Funding; Takeda Pharmaceuticals: Research Funding; Juno Therapeutics: Research Funding; Incyte Corporation: Research Funding; Johnson Graffe Keay Moniz & Wick LLP: Consultancy. Smith:AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck Sharp & Dohme Corp: Consultancy, Research Funding; Acerta Pharma BV: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Bristol-Myers Squibb (spouse): Research Funding; Denovo Biopharma: Research Funding; Genentech: Research Funding; Ignyta (spouse): Research Funding; Incyte Corporation: Research Funding; Ayala (spouse): Research Funding; Seattle Genetics: Research Funding. Byrne:Karyopharm: Research Funding. Cohen:Hutchison: Research Funding; Astra Zeneca: Research Funding; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; Genentech, Inc.: Consultancy, Research Funding; UNUM: Research Funding; ASH: Research Funding; LAM Therapeutics: Research Funding; Lymphoma Research Foundation: Research Funding. Svoboda:AstraZeneca: Consultancy; Celgene: Research Funding; Incyte: Research Funding; Pharmacyclics: Consultancy, Research Funding; Kyowa: Consultancy; Merck: Research Funding; BMS: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding. Santoro:Bayer: Consultancy, Speakers Bureau; MSD: Speakers Bureau; Arqule: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; AstraZeneca: Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Servier: Consultancy, Speakers Bureau; Takeda: Speakers Bureau; BMS: Speakers Bureau; Roche: Speakers Bureau; Abb-Vie: Speakers Bureau; Amgen: Speakers Bureau; Celgene: Speakers Bureau; Novartis: Speakers Bureau; BMS: Consultancy; Lilly: Speakers Bureau; Sandoz: Speakers Bureau; Eisai: Consultancy, Speakers Bureau. Armand:Sigma Tau: Research Funding; Otsuka: Research Funding; Pfizer: Consultancy; ADC Therapeutics: Consultancy; Tensha: Research Funding; Affimed: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Adaptive: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Infinity: Consultancy; Genentech: Research Funding. Zinzani:Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Immune Design: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sandoz: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celltrion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Consultancy; Eusapharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Verastem: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kyowa Kirin: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; TG Therapeutics: Honoraria, Speakers Bureau. Carlo-Stella:Servier: Consultancy, Honoraria, Other: Travel, accommodations; Genenta Science srl: Consultancy; Boehringer Ingelheim: Consultancy; F. Hoffmann-La Roche Ltd: Honoraria, Other: Travel, accommodations, Research Funding; Novartis: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Other: Travel, accommodations, Research Funding; Sanofi: Consultancy, Research Funding; Rhizen Pharmaceuticals: Research Funding; Celgene: Research Funding; Amgen: Honoraria; AstraZeneca: Honoraria; Janssen Oncology: Honoraria; MSD: Honoraria; BMS: Honoraria; Janssen: Other: Travel, accommodations; Takeda: Other: Travel, accommodations.

Apoptosis has been proposed to mediate CD4+ T-cell depletion in human immunodeficiency virus (HIV)-infected individuals. Interaction of Fas ligand (FasL) with Fas (CD95) results in lymphocyte apoptosis, and increased susceptibility to Fas-mediated apoptosis has been demonstrated in lymphocytes from HIV-infected individuals. Cells undergoing apoptosis in lymph nodes from HIV-infected individuals do not harbor virus, and therefore a bystander effect has been postulated to mediate apoptosis of uninfected cells. These data raise the possibility that antigen-presenting cells are a source of FasL and that HIV infection of cells such as macrophages may induce or increase FasL expression. In this report, we demonstrate that HIV infection of monocytic cells not only increases the surface expression of Fas but also results in the de novo expression of FasL. Interference with the FasL-Fas interaction by anti-Fas blocking antibodies abrogates HIV-induced apoptosis of monocytic cells. Human monocyte-derived macrophages from healthy donors contain detectable FasL mRNA, which is further upregulated following HIV infection with monocytotropic strains. HIV-infected human macrophages result in the apoptotic death of Jurkat T cells and peripheral blood T lymphocytes. Interruption of the FasL-Fas interaction abrogates the HIV-infected macrophage-dependent death of T lymphocytes. These results provide evidence that human macrophages can provide a source of FasL, especially following HIV infection, and can thus participate in lymphocyte depletion in HIV-infected individuals.

Introduction Long-term hematopoietic stem cell transplant (HCT) survivors are burdened by a high prevalence and early onset of chronic diseases. Healthy dietary patterns have been associated with lower risks of chronic health conditions in the general population, yet no study to date has comprehensively documented the adherence of HCT survivors to the Dietary Guidelines for Americans (DGA), specifically designed to provide guidance for making healthy food choices. The aims of this study were to evaluate the extent to which HCT survivors adhere to the DGA and to determine nutrient intake adequacy. A secondary aim was to assess their willingness to take part in a future nutritional program or dietary intervention. Methods The study population included adults (≥18 y), who had undergone autologous or allogeneic HCT for a hematologic disease and were at least 1-year post-transplantation. Dietary intake was assessed using the Block 2014 food frequency questionnaire and diet quality (adherence to the DGA) was estimated using the Healthy Eating Index-2015 (HEI-2015). A HEI score of ≤50 indicates "poor diet quality", 51-80 suggests a "diet that needs improvement", and >81 indicates "good diet quality" out of maximum of 100. HEI-2015 scores by patient and transplant characteristics were analyzed by ANCOVA. Nutrient intake adequacies of the group were estimated by determining the percentage of the group falling below the Estimated Average Requirement (EAR) of the Dietary Reference Intakes. Receptivity to participate in a dietary intervention to stay healthy was measured by the question, "How willing would you be to take part in a healthy nutrition program or diet intervention?" Response categories included, "not at all," "somewhat," and "definitely". Results Between December 2017 and September 2018, 124 survivors were invited to participate, of whom 90 (51 autologous and 39 allogeneic HCT survivors) completed the dietary intake assessment and were included in the analysis. Majority were male (56%), White (72%), married (81%) and completed some college education (57%). Most participants were overweight (34%) or obese (37%). The median time from the HCT was 5.2 years. Mean ±SE HEI-2015 scores were 61.6 ± 1.3 and 60.7 ± 2.2 for the 18-64 y and ≥65 y age groups, respectively, slightly higher than the US general population. Adherence to a good quality diet was reported by only 10% of survivors. The majority of the survivors reported a diet in need of improvement (82%) or a poor-quality diet (8%). Intakes of vitamin A (720 ± 447 mcg/d), vitamin C (82 ± 73 mg/d), vitamin D (4.4 ± 3.4 mcg/d), magnesium (253 ± 133 mg/d), and calcium (781 ± 430 mg/d) suggested inadequacy, as more than 50% of the group fell below the specific EARs. Sodium intake at 2834 ± 1345 mg/d exceeded the DGA recommendation of 2300 mg/d. Fiber intake at 8.9 g per 1000 kcal/d was significantly below the Adequate Intake of 14 g per 1000 kcal/d. "Change in taste" was the only variable associated with lower quality of diet (p=0.02). Interestingly, 29% of HCT survivors reported persistent altered taste sensation. No significant relationships were seen for participant's demographics and diet quality which may be due to a sample population skewed toward older, causations and socioeconomically advantaged individuals. More than two thirds of participants (73%) indicated an interest in participating in dietary intervention. HCT survivors within 2 years of transplant were more likely to be receptive to participation in a diet intervention study compared to survivors beyond 2 years (52% vs 28%, p=0.0013). Conclusion Adult HCT survivors report poor adherence to the 2015 Dietary Guidelines for Americans and have numerous short-fall nutrient intakes. However, the willingness to participate in a nutritional program or dietary intervention in this survivorship population was relatively high. These findings reinforce the need to incorporate nutrition into HCT survivor care. Disclosures Wingard: Celgene: Consultancy; Merck: Consultancy; Shire: Consultancy; Ansun: Consultancy; Pluristem: Consultancy.