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Summary Evidence for an association between insulin‐like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF‐I concentrations and risk of MM by combining baseline serological data among UK Biobank participants ( n = 444 187; 732 incident MM) with a two‐sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF‐I and IGF‐binding protein 3 (IGFBP‐3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF‐I level was positively associated with MM risk Hazard ratio‐HR‐per one standard deviation‐SD‐increase (HR 1‐SD = 1.11, 95% confidence interval [CI]: 1.01–1.22; p ‐value = 0.03), especially closer to diagnosis. Genetically inferred IGF‐I levels were associated with increased MM risk (odds ratio [OR] = 1.27, 95% CI: 1.05–1.54) but not with any other LNs. Genetically inferred IGFBP‐3 levels showed no associations with any LN evaluated. Corroborating previous findings, in a secondary analysis, IGF‐I levels were associated with the risk of chronic lymphocytic leukaemia/small lymphocytic lymphoma (CLL/SLL) in males with higher body mass index (HR 1‐SD in obese male = 1.36, 95% CI: 1.14–1.61). Our serological and MR analyses suggest a contributing role of IGF‐I in the susceptibility of MM; the CLL/SLL findings warrant further investigation considering sex‐specific adiposity.

Abstract Background Standardizing beam modeling in the treatment planning system is challenging due to machine‐specific configuration variations. Because of the proton therapy system (PTS) complexity and continuous development, there is no vendor's representative (“golden”) beam data like in LINACs at this stage. Purpose The primary goal of this study is to create a PTS‐specific repository of source model parameters and beam commissioning data for scanning proton therapy treatment planning systems and establish a set of reference values with associated bands of variations for this data. Methods We conducted a survey of 31 PTSs at 27 proton therapy centers to gather beam commissioning source model parameters used in their treatment planning system, ensuring a diverse selection of PTSs from major vendors: Hitachi, IBA, Varian, and Mevion. For each proton therapy center, we collected (i) beam meterset calibration in protons per MU, (ii) in‐air spot size at isocenter in terms of standard deviation in x‐ (crossline, σ x ) and y‐ (inline, σ y ) directions, (iii) in‐air angular spread at isocenter in x‐direction (θ x ) and y‐direction (θ y ) and (iv) distal falloff. For each PTS, we plotted each parameter as a function of nominal energy and performed polynomial regression analysis with optimal model selection based on Akaike Information Criterion. We calculated intraclass correlation coefficients (ICC) to quantify inter‐PTS variability and generated uncertainty bands representing standard deviations across PTSs for each parameter. Additionally, we computed percentage deviations of each individual PTS from the overall multi‐vendor mean to identify systematic vendor‐specific patterns and outliers across the 31 total PTSs analyzed. Results Multi‐vendor beam parameter analysis across 31 PTSs revealed systematic vendor‐specific patterns in inter‐PTS consistency and energy dependencies. Beam meterset calibration demonstrated excellent inter‐PTS consistency across most vendors (ICC: Varian ProBeam ≈ 0, IBA Proteus ONE = 0.006, Mevion S250i with HYPERSCAN = 0.015), with IBA Proteus PLUS systems showing moderate variation (ICC = 0.156 for the dedicated nozzle, ICC = 0.248, for the universal nozzle). Spot size and angular spread variability were highly vendor‐dependent, ranging from excellent consistency in IBA Proteus ONE to substantial variation in IBA Proteus PLUS with the universal nozzle (angular spread ICC = 0.566). Distal falloff maintained excellent consistency across all vendors (ICC < 0.023), indicating reliable energy spread characteristics. Uncertainty band analysis revealed characteristic energy‐dependent patterns, with most systems showing larger uncertainties at lower energies for spot size and angular spread, while IBA Proteus PLUS with the universal nozzle exhibited the largest uncertainty bands overall. Percentage deviation analysis demonstrated vendor‐specific clustering patterns, with some systems showing systematic positive or negative deviations from the multi‐vendor mean. Conclusions The reference data provided in this work will help to cross‐check the beam model during treatment planning system commissioning. Furthermore, this information is useful for Monte Carlo applications and research, where beam characteristics are required to set up phase space parameters, thereby avoiding the need to model the entire PTS. Finally, the results of this study will have indispensable educational value by providing valuable insights into the characteristics and capabilities of different PTSs.

Purpose: To investigate the feasibility of using cone-beam computed tomography (CBCT)-derived synthetic CTs to monitor the daily dose and trigger a plan review for adaptive proton therapy (APT) in head and neck cancer (HNC) patients. Methods: For 84 HNC patients treated with proton pencil-beam scanning (PBS), same-day CBCT and verification CT (vfCT) pairs were retrospectively collected. The ground truth CT (gtCT) was created by deforming the vfCT to the same-day CBCT, and it was then used as a dosimetric baseline and for establishing plan review trigger recommendations. Two different synthetic CT algorithms were tested; the corrected CBCT (corrCBCT) was created using an iterative image correction method and the virtual CT (virtCT) was created by deforming the planning CT to the CBCT, followed by a low-density masking process. Clinical treatment plans were recalculated on the image sets for evaluation. Results: Plan review trigger criteria for adaptive therapy were established after closely reviewing the cohort data. Compared to the vfCT, the corrCBCT and virtCT reliably produced dosimetric data more similar to the gtCT. The average discrepancy in D99 for high-risk clinical target volumes (CTV) was 1.1%, 0.7%, and 0.4% and for standard-risk CTVs was 1.8%, 0.5%, and 0.5% for the vfCT, corrCBCT, and virtCT, respectively. Conclusion: Streamlined APT has been achieved with the proposed plan review criteria and CBCT-based synthetic CT workflow.

Abstract Background: A previous International Lymphoma Epidemiology (InterLymph) Consortium evaluation of joint associations between five immune gene variants and autoimmune conditions reported interactions between B-cell response-mediated autoimmune conditions and the rs1800629 genotype on risk of B-cell non–Hodgkin lymphoma (NHL) subtypes. Here, we extend that evaluation using NHL subtype-specific polygenic risk scores (PRS) constructed from loci identified in genome-wide association studies of three common B-cell NHL subtypes. Methods: In a pooled analysis of NHL cases and controls of Caucasian descent from 14 participating InterLymph studies, we evaluated joint associations between B-cell–mediated autoimmune conditions and tertile (T) of PRS for risk of diffuse large B-cell lymphoma (DLBCL; n = 1,914), follicular lymphoma (n = 1,733), and marginal zone lymphoma (MZL; n = 407), using unconditional logistic regression. Results: We demonstrated a positive association of DLBCL PRS with DLBCL risk [T2 vs. T1: OR = 1.24; 95% confidence interval (CI), 1.08–1.43; T3 vs. T1: OR = 1.81; 95% CI, 1.59–2.07; P-trend (Ptrend) &lt; 0.0001]. DLBCL risk also increased with increasing PRS tertile among those with an autoimmune condition, being highest for those with a B-cell–mediated autoimmune condition and a T3 PRS [OR = 6.46 vs. no autoimmune condition and a T1 PRS, Ptrend &lt; 0.0001, P-interaction (Pinteraction) = 0.49]. Follicular lymphoma and MZL risk demonstrated no evidence of joint associations or significant Pinteraction. Conclusions: Our results suggest that PRS constructed from currently known subtype-specific loci may not necessarily capture biological pathways shared with autoimmune conditions. Impact: Targeted genetic (PRS) screening among population subsets with autoimmune conditions may offer opportunities for identifying those at highest risk for (and early detection from) DLBCL.

AbstractEvidence for the human health effects of pesticides is needed to inform risk assessment. We studied the relationship between occupational insecticide use and risk of non‐Hodgkin lymphoma (NHL) by pooling data from nine case‐control studies participating in the InterLymph Consortium, including 7909 cases and 8644 controls from North America, the European Union and Australia. Insecticide use was coded using self‐report or expert assessment, for insecticide groups (eg, organophosphates, pyrethroids) and active ingredients (eg, malathion, permethrin). Associations with insecticides were estimated using logistic regression to produce odds ratios (ORs) and 95% confidence intervals (CI) for all NHL and NHL subtypes, with adjustment for study site, demographic factors and use of other pesticides. Occupational insecticide use, overall, was not associated with risk of NHL. Use of organophosphate insecticides was associated with increased risk of all NHL and the subtype follicular lymphoma, and an association was found with diazinon, in particular (ever use: OR = 2.05, 95%CI: 1.24‐3.37). The carbamate insecticide, carbaryl, was associated with risk of all NHL, and the strongest associations were found with T‐cell NHL for ever‐use (OR = 2.44, 95%CI: 1.13‐5.28) and longer duration (>8 years vs never: OR = 2.90, 95%CI: 1.02‐8.25). There was no association of NHL with other broad groups of insecticides, including organochlorines and pyrethroids, and some inverse associations were estimated in relation to historical DDT use. Our findings contribute to the totality of evidence available to help inform risk decisions by public health and regulatory agencies of importance given continued, widespread use of organophosphate and carbamate insecticides.

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 &lt; 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 &lt; 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.

Introduction. Acquired severe aplastic anemia (SAA) is a life-threatening disorder characterized by severe progressive pancytopenia and hypocellular bone marrow. The etiology of acquired SAA is not understood but believed to be related to abnormal immune responses to environmental exposures. We conducted a genome-wide association study (GWAS) to identify common germline variants associated with SAA. Methods. We identified 895 patients with SAA who underwent related or unrelated hematopoietic cell transplant (HCT) with clinical data and pre-HCT blood samples available in the Center for International Blood and Marrow Transplant Research (CIBMTR) database and biorepository. Pre-HCT DNA was extracted from blood of patients with SAA and genome-wide genotyping was conducted using the Illumina OmniExpress array. We excluded 93 inherited bone marrow failure cases. The SAA cases were grouped cases into discovery and validation sets based on time of batch sample receipt. Analyses were limited to patients of European ancestry based on principal component analyses to minimize the potential effect of population stratification. Controls were genomically matched and selected from previously scanned cancer-free subjects at the Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, NCI. The final analysis included 534 acquired SAA cases (359 in the discovery set and 175 in the validation set), and 2,455 controls (1,396 in the discovery set, and 1,059 in the validation set). Results. Patients with SAA in this study received HCT between 1989-2015 at a median age of 21 years, 56% were male, and the median time between SAA diagnosis and HCT was 11 months. Strong genome-wide association signals were identified across the human leukocyte antigen (HLA) genes encoded at the major histocompatibility complex (MHC) on chromosome 6p21 (Figure 1). The top SNP was located in the P4 binding pocket of the HLA class II gene HLA-DPB1(rs1042151A>G, p.Met105Val, pooled-odds ratio [OR]=1.75, 95% confidence interval [CI]=1.50-2.03, p=1.94x10-13). The expression of HLA-DP in CD19+ cells from 175 healthy donors was significantly different by rs1042151 A>G genotype (p=2.04x10-6) (Figure 2). A second SNP near HLA-B, rs28367832G>A, also reached genome-wide significance (pooled-OR=1.49, 95% CI=1.22-1.78, p=7.27x10-9). Copy-number variant analysis and next generation sequencing also identified somatic, clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes in 8.6% of the SAA cases and none of the controls. Conclusion. This SAA GWAS identified strong association signals between common germline genetic variants in HLA class I and II genes and SAA. The main SNP is associated with changes in HLA-DP expression suggesting a key role for this locus in SAA etiology. This study adds further evidence to the connection between SAA and immune dysregulation. Disclosures Cerhan: Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; Celgene: Research Funding. Lee:Incyte: Research Funding; Syndax: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Takeda: Research Funding; Kadmon: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; AstraZeneca: Research Funding.

Abstract Background. A recent meta-analysis of 9 case-control and 5 cohort studies reported a positive association of transfusion history with risk of NHL (RR=1.20; 95% CI 1.07-1.35), which was only evident in cohort (RR=1.25) and not case-control (RR=1.05) studies (Castillo et al., Blood 2010;116:2897-2907). Risk was similar in men and women, and for transfusions before or after 1992. In subset analyses, elevated risk was only apparent for chronic lymphocytic leukemia (CLL) and not diffuse large B-Cell lymphoma (DLBCL) or follicular lymphoma, but power was low. To further investigate these findings, particularly from studies conducted after 1990, better assess confounding, and address heterogeneity by NHL subtypes, we conducted an individual-level, pooled analysis of 13 case-control studies in the InterLymph Consortium (including 11 studies conducted after 1990; 8 studies were not included in the published meta-analysis). Methods. There were a total of 10,805 cases and 14,026 controls with transfusion data from 13 studies conducted in Europe, North America, and Australia. Transfusion history and other risk factors were self-reported in interviewer-administered or self-administered questionnaires. All risk factor data were harmonized centrally, and cases were grouped into NHL subtypes according to the WHO classification using guidelines from the InterLymph Pathology Working Group. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression, adjusted for age, sex, and study center. Results. The median age at diagnosis was 60 years for cases (range, 18-97) and 59 years for controls (range, 16-97). The overall prevalence of a history of any transfusion in controls was 15.5%, was higher in women (18.6%) than men (13.0%), and increased with age, but was not associated with race/ethnicity (Asian, Black, Hispanic, White, other) or geographic region after adjusting for age and sex. Among whites, history of any transfusion was inversely associated with NHL risk among men (OR=0.74; 95% CI 0.65-0.83) but not women (OR=0.92; 95% CI 0.83-1.03); there were no significant results for other race/ethnicity groups, and ORs were highly variable and imprecise due to small sample sizes. Thus analyses were restricted to white men, where there was no trend with the number of transfusions, time since first transfusion, age at first transfusion, or decade of first transfusion. Further adjustment for socioeconomic status, body mass index, smoking, alcohol use or hepatitis C virus (HCV) seropositivity did not alter these results. The associations were stronger in hospital-based (OR=0.56; 95% CI 0.45-0.70) than population-based (OR=0.84; 95% CI 0.72-0.98) studies, and were stronger in studies from Southern Europe (OR=0.53; 95% CI 0.36-0.79) than northern Europe (OR=0.67; 95% CI 0.53-0.83) or North America (OR=0.82; 95% CI 0.70-0.98). For NHL subtypes, statistically significant inverse associations were observed for follicular lymphoma (OR=0.70; 95% CI 0.56-0.88), DLBCL (OR=0.72; 95% CI 0.59-0.87), and CLL/SLL (OR=0.67; 95% CI 0.52-0.87), whereas weaker and non-statistically significant associations were observed for mantle cell (OR=0.81; 95% CI 0.54-1.23), marginal zone (OR=0.78; 95% CI 0.54-1.15), lymphoplasmacytic (OR=0.82; 95% CI 0.47-1.42) and peripheral T-cell (OR=0.83; 95% CI 0.49-1.40) lymphomas. Conclusion. Contrary to earlier results, transfusion history was inversely associated with risk of NHL and the common subtypes of follicular lymphoma, DLBCL and CLL/SLL among white men, whereas associations were null among white women and other racial/ethnic groups. These results were not explained by confounding by lifestyle factors or HCV seropositivity, era of first transfusion, hospital versus population-based study design, or geographic location. Despite dramatic changes in transfusion practice over the past 40 years, results were similar for decade of first transfusion, suggesting secular trends are a less likely explanation. Our results are unexpected and bias cannot be ruled out. Further studies, particularly cohort studies, are needed to clarify the role of transfusion history in NHL risk. Disclosures No relevant conflicts of interest to declare.

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.