Citations

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

Background Management of delirium in intensive care units is challenging because effective therapies are lacking. Music is a promising nonpharmacological intervention. Objectives To determine the feasibility and acceptability of personalized music (PM), slow-tempo music (STM), and attention control (AC) in patients receiving mechanical ventilation in an intensive care unit, and to estimate the effect of music on delirium. Methods A randomized controlled trial was performed in an academic medical-surgical intensive care unit. After particular inclusion and exclusion criteria were applied, patients were randomized to groups listening to PM, relaxing STM, or an audiobook (AC group). Sessions lasted 1 hour and were given twice daily for up to 7 days. Patients wore noise-canceling headphones and used mp3 players to listen to their music/audiobook. Delirium and delirium severity were assessed twice daily by using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the CAM-ICU-7, respectively. Results Of the 1589 patients screened, 117 (7.4%) were eligible. Of those, 52 (44.4%) were randomized, with a recruitment rate of 5 patients per month. Adherence was higher in the groups listening to music (80% in the PM and STM groups vs 30% in the AC group; P = .01), and 80% of patients surveyed rated the music as enjoyable. The median number (interquartile range) of delirium/coma-free days by day 7 was 2 (1-6) for PM, 3 (1-6) for STM, and 2 (0-3) for AC (P = .32). Median delirium severity was 5.5 (1-7) for PM, 3.5 (0-7) for STM, and 4 (1-6.5) for AC (P = .78). Conclusions Music delivery is acceptable to patients and is feasible in intensive care units. Further research testing use of this promising intervention to reduce delirium is warranted.

Abstract Background: Lipid traits have been inconsistently linked to risk of non-Hodgkin lymphoma (NHL). We examined the association of genetically predicted lipid traits with risk of diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and marginal zone lymphoma (MZL) using Mendelian randomization (MR) analysis. Methods: Genome-wide association study data from the InterLymph Consortium were available for 2,661 DLBCLs, 2,179 CLLs, 2,142 FLs, 824 MZLs, and 6,221 controls. SNPs associated (P < 5 × 10−8) with high-density lipoprotein (HDL, n = 164), low-density lipoprotein (LDL, n = 137), total cholesterol (TC, n = 161), and triglycerides (TG, n = 123) were used as instrumental variables (IV), explaining 14.6%, 27.7%, 16.8%, and 12.8% of phenotypic variation, respectively. Associations between each lipid trait and NHL subtype were calculated using the MR inverse variance–weighted method, estimating odds ratios (OR) per standard deviation and 95% confidence intervals (CI). Results: HDL was positively associated with DLBCL (OR = 1.14; 95% CI, 1.00–1.30) and MZL (OR = 1.09; 95% CI, 1.01–1.18), while TG was inversely associated with MZL risk (OR = 0.90; 95% CI, 0.83–0.99), all at nominal significance (P < 0.05). A positive trend was observed for HDL with FL risk (OR = 1.08; 95% CI, 0.99–1.19; P = 0.087). No associations were noteworthy after adjusting for multiple testing. Conclusions: We did not find evidence of a clear or strong association of these lipid traits with the most common NHL subtypes. While these IVs have been previously linked to other cancers, our findings do not support any causal associations with these NHL subtypes. Impact: Our results suggest that prior reported inverse associations of lipid traits are not likely to be causal and could represent reverse causality or confounding.

Abstract Small lymphocytic lymphoma (SLL) is an incurable indolent lymphoma, and there are relatively few prognostic biomarkers for this important NHL subtype. We evaluated the hypothesis that inherited variability in cytokine and immune-related genes was associated with overall survival in SLL. We genotyped 73 SNPs in 44 candidate genes in 140 SLL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. DNA was extracted from a venous blood sample or mouthwash buccal cell sample. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform. 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. Cox proportional hazards analysis was used to estimate the hazard ratio (HR) and 95% confidence interval for the association between individual SNPs and overall survival, adjusted for age, demographic and clinical factors. Multiple simultaneous modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At last follow-up, there were 45 deaths in 140 patients (32%). The median follow-up of the 95 surviving patients was 58 months (range 24–75 months). In multivariate modeling, SNPs in IL13 (rs1800925; HRCC=2.36, 1.24–4.49), IL7R (rs1494555; HRGG =2.20, 0.84–5.76), and TNF-alpha (rs1800630; HRAC/AA=1.73, 0.95–3.17) were the strongest and most robust predictors of survival. Two or more deleterious genotypes from these three SNPs increased the risk of death (HR=2.2, 1.2–4.1) compared with one or fewer deleterious genotypes (p=0.009). Three groups (low, intermediate, and high risk) were defined by combining the SNP score and a clinical/demographic score. The 5-year Kaplan-Meier survival estimates for these groups were 85%, 65%, and 11%, respectively. Compared to patients with a low risk score, patients with intermediate (HR=2.5, 1.2–5.1) or high (HR=11, 4.3–27.7) risk scores had poorer overall survival (p=3.9 x 10−8). Our preliminary results suggest that SNPs in IL13, IL7R, and TNF-alpha alone and in combination predict overall survival in SLL, lending support to the hypothesis that host genetic background is a promising class of prognostic biomarkers in SLL.

Abstract DLBCL is a curable subtype of non-Hodgkin lymphoma, although a significant number of patients do not achieve a remission or they relapse with conventional chemotherapy. While clinical variables (e.g., IPI), tumor (somatic) genetic alterations, and gene expression profiling have all been shown to predict outcome, there remains a need for additional prognostic biomarkers. One understudied class of biomarkers is host genetic background. We evaluated the hypothesis that germline variability in 73 SNPs from 44 candidate immune genes was associated with overall survival in DLBCL. We addressed this hypothesis in 365 DLBCL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 (prior to the use of R-CHOP) through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. Germline DNA was extracted from a venous blood sample or mouthwash buccal cell sample, which was collected a median of 4.8 months after diagnosis in this population-based study. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform, and was successful in over 95% of the DNA samples for the SNPs evaluated. 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. Cox proportional hazards analysis was used to evaluate the association between individual SNPs, adjusted for age, demographic and clinical factors. Parallel modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At a median follow-up of 56 months (range, 27-78 months) for surviving patients, there were 96 deaths in 365 patients (26%). In multivariate modeling, SNPs in IL1A (rs1800587; HRCT/TT=1.90, 1.26–2.87), IL6 (rs1800795; HRGG=1.48, 0.99–2.23), IL-10 (rs1800896; HRAG/GG=1.48, 0.91–2.38), and IFNGR2 (rs2070385; HRAG/GG=1.35, 0.86–2.11) were the strongest and most robust predictors of overall survival. A summary score of the number of deleterious genotypes from these four genes in combination with clinical and demographic variables was strongly associated with survival (p=9.3 x 10−12); Kaplan-Meier 5-year survival estimates for low, intermediate, and high risk patients were 89%, 68%, and 47% respectively. In conclusion, host genetic background as measured by germline polymorphisms in immune genes including IL1A, IL6, IL10, and IFNGR2 were associated with overall survival in DLBCL after accounting for clinical and demographic factors. These promising results require confirmation and need further evaluation in patients treated with R-CHOP in conjunction with tumor and other prognostic biomarkers.

Abstract We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10−13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10−12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

AbstractEpidemiologic studies show an increased risk of non‐Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen‐stimulation in one disease leads to another. Here we assess shared genetic risk in genome‐wide‐association‐studies (GWAS).Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B‐cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta‐analysis.Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta‐analysis (combing AD with NHL) implicated genes of apoptosis and telomere length.This GWAS‐based analysis four NHL subtypes and three ADs revealed few weakly‐associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.