Citations

Abstract Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in Western countries. It has a strong genetic basis, showing a ~ 8-fold increased risk of CLL in first-degree relatives. Genome-wide association studies (GWAS) have identified 41 risk variants across 41 loci. However, for a majority of the loci, the functional variants and the mechanisms underlying their causal roles remain undefined. Here, we examined the genetic and epigenetic features associated with 12 index variants, along with any correlated (r2 ≥ 0.5) variants, at the CLL risk loci located outside of gene promoters. Based on publicly available ChIP-seq and chromatin accessibility data as well as our own ChIP-seq data from CLL patients, we identified six candidate functional variants at six loci and at least two candidate functional variants at each of the remaining six loci. The functional variants are predominantly located within enhancers or super-enhancers, including bi-directionally transcribed enhancers, which are often restricted to immune cell types. Furthermore, we found that, at 78% of the functional variants, the alternative alleles altered the transcription factor binding motifs or histone modifications, indicating the involvement of these variants in the change of local chromatin state. Finally, the enhancers carrying functional variants physically interacted with genes enriched in the type I interferon signaling pathway, apoptosis, or TP53 network that are known to play key roles in CLL. These results support the regulatory roles for inherited noncoding variants in the pathogenesis of CLL.

8052 Background: A significant proportion of patients with FL experience an early relapse and a subsequent poor outcome. While several prognostic indices have been developed, none were designed to predict early failure. Recently, we established that lack of intrafollicular CD4+ T-cell expression predicted risk of early failure, and integrating this microenvironment biomarker with the Follicular Lymphoma International Prognostic Index, termed BioFLIPI, further improved identification of FL patients at risk of early failure ( Blood 2019;134(suppl1):121). However, the microenvironment may be influenced by the genetic composition of tumor. We investigated whether the CD4 biomarker and BioFLIPI were impacted by genetic features of the tumor as assessed by a 23-gene expression prognostic score ( Lancet Oncol 2018;19:549-61). Methods: Of the 186 cases with FL grade 1-3A treated with immunochemotherapy (IC) in our prior study, 152 had digital expression quantification of 23 selected genes (23-GEP score), which used RNA from formalin-fixed, paraffin-embedded samples. Event-free survival (EFS) was defined as time from diagnosis to progression, relapse, retreatment, or death. Early failure was defined as failing to achieve EFS at 24 months. Risk of early failure was estimated using odds ratios (ORs) and 95% confidence intervals from logistic regression models. We also used Cox regression to assess associations with continuous EFS and overall survival (OS). Results: 28% of patients failed to achieve EFS24. Lack of CD4+ intrafollicular expression (38% of patients, OR = 2.33, p = 0.024) and high risk 23-GEP score (26% of patients, OR = 3.52, p = 0.001) each predicted early failure, and in a multivariable model that included FLIPI, both CD4+ (OR = 2.26, p = 0.046) and 23-GEP score (OR = 2.26, p = 0.0.057) remained predictors. Similarly, BioFLIPI modeled as a continuous score (1-4, OR per one point increase = 2.31, p < 0.001) predicted early failure, and the association remained (OR = 2.14, p < 0.001) when the high risk 23-GEP score (OR = 2.79, p = 0.013) was included in the model. When stratified on 23-GEP score, BioFLIPI was a stronger predictor of early failure in low risk (74%, OR = 2.51, p = 0.002) relative to high risk (26%, OR = 1.55, p = 0.27) patients. Similar patterns were observed for EFS and OS. Conclusions: CD4+ T-cell infiltrate and tumor gene expression appear to be independently predictive of early failure in newly diagnosed FL patients treated with IC. Future studies should integrate and validate these measures.

8026 Background: CLL progression and CLL-related complications (infections and second malignancies) were the leading cause of death (COD) in a prospective cohort of CLL patients (Strati, BJH 2017). The CLL-IPI integrates major clinical and molecular prognostic factors and stratifies patients into 4 risk groups with distinct prognosis. It is unknown if COD differs according to CLL-IPI risk group in patients with newly diagnosed CLL. Methods: Patients diagnosed with CLL between 1/2000-12/2019 and seen within 1 year of diagnosis were identified from the Mayo Clinic CLL database. Cumulative incidences of cause-specific death were analyzed using Gray’s test, with deaths from different causes treated as competing events and deaths from unknown causes excluded. Results: 1276 patients were included in this study. The median age at diagnosis was 63 years (range 24-92), and 880 (69%) were male. Based on CLL-IPI score, 449 (35%) had low risk disease, 443 (35%) had intermediate risk disease, and 384 (30%) had high/very high risk disease. Median follow-up time for the study was 6 years; 286 deaths occurred. The COD was CLL progression in 99 (35%), infection in 16 (6%), second malignancy in 47 (16%), CLL-unrelated in 59 (21%), and unknown in 65 (23%) patients. The rates of death due to CLL progression were higher (17.3% at 5 years; 30.3% at 10 years) than the rates due to CLL-related complications (5.7% at 5 years; 12.9% at 10 years) or due to CLL-unrelated causes (8.6% at 5 years; 16.9% at 10 years) in the CLL-IPI high/very high risk group, but not the CLL-IPI low or intermediate risk group (Table). A higher CLL-IPI risk group was associated with a higher rate of death due to CLL progression ( P < 0.001), as well as a higher rate of death due to CLL-related complications ( P = 0.013), and CLL-unrelated causes ( P < 0.001). Conclusions: Causes of death in newly diagnosed CLL patients differ according to their CLL-IPI risk group. In patients with high/very high risk CLL, improving CLL disease control with novel agents seems justified. In patients with low/intermediate risk CLL, there should be increased efforts to reverse immune dysfunction to reduce infections and second malignancies. [Table: see text]

e19112 Background: We sought to study the longitudinal QOL, financial burden and perception of care (PoC) in patients with multiple myeloma (MM) or lymphoma (LYM) enrolled on CTs vs. those receiving standard care (Non-CT). Methods: QOL was evaluated using the FACT-G questionnaire (baseline, 1, 2, 3, 6 & 12 months). Financial burden was evaluated using 10 questions adapted from the MEPS survey and PoC was evaluated using 6 questions adapted from the CAHPS survey (baseline, 3, 6 & 12 months). Results: 35 (28%) of 123 enrolled patients were treated on CTs. Demographics, QOL and financial burden are shown in the Table. Baseline QOL scores were similar in CT vs non-CT groups. Age, gender and self-reported performance status were significantly associated with baseline QOL, while lines of therapy & cancer type were not. There were no significant differences in change in QOL vs. baseline in patients treated on CTs vs. non-CTs at 1, 2, 3, 6 and 12 months from baseline, including the total FACT-G score and the subdomains of functional, physical, emotional and social well-being. Within each group, there was a decline in QOL over the first 3 months, specifically physical WB, which gradually returned to baseline. Baseline answers to financial burden questions were similar, except patients on CTs reported less need for taking extended time-off from work (22% vs. 46%, p = 0.02). The only statistically significant difference in individual Qs over 1 year was ‘worry about having to pay large medical bills’ at the 6-month timepoint (CT: 0%, non-CT: 52%, p = 0.01). Using a composite score from 4 MEPS questions, financial burden over time was lower in the CT group, though the differences were not statistically significant. There were no significant differences in PoC at baseline, 3, 6 and 12 months in the two groups based on answers to each of the six questions adapted from the CAHPS survey. Conclusions: Over 1 year, patients on CTs experienced a similar QOL and perceived their care to be similar as non-CT patients. Financial burden was lower in the CT group, though differences were not statistically significant. [Table: see text]

e14100 Background: Only 3-5% of adult cancer patients in the US enroll in clinical trials. Patients with organ dysfunction are often excluded from clinical trials, regardless of specific drug metabolism or relative function of the organ. The ASCO and the US FDA recommend modernizing criteria related to baseline organ function and comorbidities. In hematological malignancies, often the disease itself is the reason for organ function derangement. In order to better inform clinical trial eligibility and improve participation in the future, we evaluated the impact of baseline organ function on the potential eligibility for clinical trial enrollment for real world patients with newly diagnosed DLBCL. Methods: Consecutive, newly diagnosed lymphoma patients were offered enrollment from 2002-2015 into the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence. This analysis is based on 1270 DLBCL patients receiving immunochemotherapy. Baseline organ function parameters were identified from the exclusion criteria for hemoglobin, absolute neutrophil count (ANC), platelet count, creatinine, and bilirubin reported in recent frontline trials in DLBCL (Table). Abstracted clinical labs from the MER were used to determine the percent of patients that would be excluded based on the criteria. Results: We determined that 11-23% of MER DLBCL patients receiving standard of care frontline therapy would have been excluded in the various trials utilizing baseline organ function alone (Table). Hemoglobin and renal function had the greatest impact on exclusion. Conclusions: Current national and international (phase II and III) trials are excluding up to 23% of patients from clinical trial participation based on organ function alone in DLBCL. These data will be useful in future clinical trial development to meet ASCO recommendations to increase trial accrual, while balancing the drug toxicities and patient safety. An online tool was developed based on these results to aid future trial development. [Table: see text]

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 Subtle differences in immune response may play a role in non-Hodgkin lymphoma (NHL) etiology. Because adult immune response may be influenced by early childhood exposures, we examined the role of childhood crowding, history of atopic disease, and other childhood immune-related exposures on the risk of non-Hodgkin lymphoma in a multi-center case-control study. Interviews were completed with 1,321 cases ascertained from population-based cancer registries in Seattle, Detroit, Los Angeles and Iowa, and with 1,057 frequency-matched controls, selected by random-digit dialing and from the Health Care Financing Administration (HCFA) database. The association between NHL risk in relation to atopy and other exposures was assessed using multivariable logistic regression methods. Most types of allergy were associated with protection from NHL, with hay fever especially protective against all NHL combined (Odds Ratio [OR] = 0.71, 95% confidence interval [CI]= 0.54–0.94), diffuse large B-cell lymphoma [DLBCL] (OR=0.61, 95% CI=0.41–0.91), and follicular lymphoma (OR=0.70, 95% CI=0.45–1.09). A history of eczema increased risk of follicular lymphoma (OR=1.92, 95% CI= 1.08–3.41) but not DLBCL (OR=1.06, 95% CI= 0.55.2.04). Asthma in childhood was not associated with risk of NHL. Risk of DLBCL (OR =1.72, 95% CI=1.17–2.52), but not follicular lymphoma (OR=1.15, 95% CI=0.75–1.76) was elevated for the youngest compared to the oldest of siblings. Neither number of siblings nor years between births of siblings were significantly associated with risk. These results suggest that some immune-related exposures may affect NHL risk.

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 &gt;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 &gt; 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 &gt;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 &gt;10 years (p=0.061) and those with BMI &gt;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: Non-Hodgkin lymphoma (NHL) is a malignancy of lymphocytes, and may develop in the setting of inflammation and immune dysfunction. Small scale evaluations have suggested that common genetic variation in candidate genes related to immune function may predispose to the development of NHL. Here we report a comprehensive analysis of variants within genes associated with immunity and inflammation and risk of NHL. Methods: We used ParAllele’s Immune and Inflammation panel of 9,412 single nucleotide polymorphisms (SNPs) from 1,450 immune/inflammation genes as a discovery tool in a clinic-based study of 458 NHL cases and 484 frequency matched controls seen at the Mayo Clinic from 2002–2005. The panel included 537 coding non-synonymous SNPs (nsSNPs), with the remainder of the SNPs selected as tags from HapMap (tagSNPs) to provide coverage of the candidate genes (r2 = 0.8 and minor allele frequency &gt;0.05). To assess the association of individual SNPs with risk of NHL, we calculated Odds Ratios (ORs) and 95% confidence intervals, adjusted for age and gender. The most prevalent homozygous genotype was used as the reference group, and each polymorphism was modeled individually as having a log-additive effect in the regression model. Associations between haplotypes from each gene and the risk of NHL were calculated using a score test implemented in HAPLO.SCORE. We also modeled the main effects for all independent (r2 &lt;0.25) SNPs from a gene in a multivariate logistic regression model. Results: The mean age at diagnosis was 60 years for cases and 58% were male; in controls the mean age at enrollment was 61.6 years and 55% were male. In the gene analyses, the strongest findings (p≤0.001 from multiple SNP logistic regression or haplotype analysis) were for cAMP responsive element binding protein 1 (CREB1; p=0.0004), fibrinogen alpha chain (FGA; p=0.0006), TNF receptor-associated factor 1 (TRAF1; p=0.001), dual specificity phosphatase 2 (DUSP2; p=0.001), and fibrinogen gamma chain (FGG; p=0.001). In the nsSNP analyses, the strongest findings (p≤0.01) were for integrin β3 (ITGB3) L59P (OR=0.64, 0.50–0.83), Beta-1,3-N-acetylglucosaminyltransferase 3 (B3GNT3) H328R (OR=0.72, 0.57–0.91), transporter 2, ATP-binding cassette (TAP2) T665A (OR=1.32, 1.07–1.63), HLA-B associated transcript 2 (BAT2) V1895L (OR=0.60, 0.42–0.85), and complement component 7 (C7) T587P (OR=1.39, 1.07–1.80). Conclusions. Our results suggest that genetic variability in genes associated with antigen processing (CREB1 and TAP2), lymphocyte trafficking (B3GNT3), immune activation (TRAF1, BAT2), complement and coagulation pathways (FGA, FGG, ITGB3, C7), and MAPK signaling (DUSP2) may be important in the etiology of NHL, and should be pursued in replication studies.

Abstract Background: FL comprises one quarter of lymphoma in the United States, presents in a heterogeneous fashion, and generates substantial debate regarding optimal management strategies. The recently published clinical prognostic index (FLIPI, BLOOD104:1258) facilitates outcome evaluation and may guide therapeutic strategy. The National LymphoCare Study (NLCS) is an ongoing disease-based longitudinal observational study designed to assess patterns of initial disease presentation including prognosis, long term treatment choices, and clinical outcomes in FL patients. Methods: Beginning March, 2004, pts were recruited from U.S. community practices and academic centers. Pts with FL diagnosed within 6 months with no prior lymphoma history are eligible for enrollment. Collected data includes histology, staging and prognostic evaluation, serial management strategies including drug choices but not doses, response to treatment, and events including relapses and death. There is no study-specific prescribed treatment regimen or intervention. The treating physician determines management for FL according to clinical judgment. Results: 992 pts were enrolled from 207 sites through April, 2005. 182 community sites enrolled 86% of subjects. Pt characteristics include median age 62y, 52.5% female, 90.6% Caucasian, 40% Gr1, 26% Gr2, 19% Gr3, 13% NOS, with highest determined Ann Arbor stage = 17% I, 15%II, 26% III, 33%IV, 8% Unk. The demographic characteristics are similar to pts in the national SEER registry (median age 64, 51% F, 91.3% Caucasian) but clinical characteristics are notable for a higher fraction of advanced stage disease. 686/992 (69%) patients had calculable FLIPI scores based on initial investigator workup. Of factors contributing to FLIPI scores, LDH was collected by investigators in 78% of pts. When correlated with age, geography, and academic/community sites, LDH collection rates differ with 90% in academic sites vs 76% in community sites (p = .0002). Distribution of FLIPI among 686 pts with complete scores are shown in Table1, and show remarkable consistency across grades. Summary: The NLCS is an ongoing study with a large and rapidly growing database combining clinical and treatment data and is the first database investigating initial workup, prognosis, and outcomes of pts in a predominantly community based U.S. population. FL pts enrolled in NLCS are similar to those in the SEER database, and should be widely generalizable to the US population. FLIPI continues to define three distinct groups in the NLCS and is independent of histologic grade. Current evaluation patterns result in 31% incomplete FLIPI scores, suggesting this useful prognostic index is underutilized. FLIPI distribution (%) Low 36 37 37 38 34 81 14 Intermed 37 31 32 28 37 14 40 High 27 32 31 34 29 5 46 Solal Celigny n=1795 NLCS n=686 NLCS Gr1 n=276 NLCS Gr2 n=188 NLCS Gr3 n=136 Stage I/II n=234 Stage III/IV n=452