Early complete response as a validated surrogate marker in extranodal marginal zone lymphoma systemic therapy.

ABSTRACT: Extranodal marginal zone lymphoma (EMZL) has a very indolent course, and the validation of surrogate markers could accelerate novel therapies. Although prognostic markers do exist, no surrogate markers have been validated in EMZL. We hypothesized that time to complete response within 24 months (TTCR24) and complete response (CR) at 24 months (CR24) could be valid surrogate markers of progression-free survival (PFS). The International Extranodal Lymphoma Study Group 19 phase 3 trial showed the advantage of double therapy (rituximab + chlorambucil) over single therapy (rituximab or chlorambucil) on PFS. We used 2 recently published single-trial approaches to assess whether TTCR24 and CR24 were good surrogate markers of 8-year PFS (8y-PFS). Among the 401 patients, 264 (66%) reached a CR in the first 24 months, of which 222 (84%) remained in CR at month 24. The cumulative incidence of CR over time was significantly higher in patients under double therapy (hazard ratio, 1.75; P < .001). The double therapy arm was associated with a higher CR24 rate, a shorter TTCR24, and a longer 8y-PFS. The estimated proportion of treatment effect on 8y-PFS explained by TTCR24 was 95% (95% confidence interval [CI], 0.27-1.87). CR24 was also a strong surrogate marker because it mediated 90% (95% CI, 0.51-2.22) of the treatment effect on PFS and its natural indirect effect was significant throughout the follow-up. We found that TTCR24 predicted 95% and that CR24 mediated 90% of the treatment effect on long-term PFS. Therefore, TTCR24 and CR24 could be used in clinical trials as informative and valid early indicators of treatment effect on PFS. This trial was registered at www.clinicaltrials.gov as #NCT00210353.

Prediction of outcomes for high-count monoclonal B lymphocytosis using an epigenetic and immunogenetic signature.

ABSTRACT: Monoclonal B-cell lymphocytosis (MBL) progresses to chronic lymphocytic leukemia (CLL) requiring therapy at 1% to 5% per year. Improved prediction of progression would greatly benefit individuals with MBL. Patients with CLL separate into 3 distinct epigenetic subtypes (epitypes) with high prognostic significance, and recently the intermediate epitype has been shown to be enriched for high-risk immunoglobulin lambda variable (IGLV) 3-21 rearrangements, impacting outcomes for these patients. Here, we employed this combined strategy to generate the epigenetic and light chain immunoglobulin (ELCLV3-21) signature to classify 219 individuals with MBL. The ELCLV3-21 high-risk signature distinguished MBL individuals with a high probability of progression (39.9% and 71.1% at 5 and 10 years, respectively). ELCLV3-21 improved the accuracy of predicting time to therapy for individuals with MBL compared with other established prognostic indicators, including the CLL international prognostic index (c-statistic, 0.767 vs 0.668, respectively). Comparing ELCLV3-21 risk groups in MBL vs a cohort of 226 patients with CLL revealed ELCLV3-21 high-risk individuals with MBL had significantly shorter time to therapy (P = .003) and reduced overall survival (P = .03) compared with ELCLV3-21 low-risk individuals with CLL. These results highlight the power of the ELCLV3-21 approach to identify individuals with a higher likelihood of adverse clinical outcome and may provide a more accurate approach to classify individuals with small B-cell clones.

Progression and survival of MBL: a screening study of 10 139 individuals.

Monoclonal B-cell lymphocytosis (MBL) is a common hematological premalignant condition that is understudied in screening cohorts. MBL can be classified into low-count (LC) and high-count (HC) types based on the size of the B-cell clone. Using the Mayo Clinic Biobank, we screened for MBL and evaluated its association with future hematologic malignancy and overall survival (OS). We had a two-stage study design including discovery and validation cohorts. We screened for MBL using an eight-color flow-cytometry assay. Medical records were abstracted for hematological cancers and death. We used Cox regression to evaluate associations and estimate hazard ratios and 95% confidence intervals (CIs), adjusting for age and sex. We identified 1712 (17%) individuals with MBL (95% LC-MBL), and the median follow-up time for OS was 34.4 months with 621 individuals who died. We did not observe an association with OS among individuals with LC-MBL (P = .78) but did among HC-MBL (hazard ratio, 1.8; 95% CI, 1.1-3.1; P = .03). Among the discovery cohort with a median of 10.0 years follow-up, 31 individuals developed hematological cancers with two-thirds being lymphoid malignancies. MBL was associated with 3.6-fold risk of hematological cancer compared to controls (95% CI, 1.7-7.7; P < .001) and 7.7-fold increased risk for lymphoid malignancies (95% CI:3.1-19.2; P < .001). LC-MBL was associated with 4.3-fold risk of lymphoid malignancies (95% CI, 1.4-12.7; P = .009); HC-MBL had a 74-fold increased risk (95% CI, 22-246; P < .001). In this large screening cohort, we observed similar survival among individuals with and without LC-MBL, yet individuals with LC-MBL have a fourfold increased risk of lymphoid malignancies. Accumulating evidence indicates that there are clinical consequences to LC-MBL, a condition that affects 8 to 10 million adults in the United States.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

The Lymphoma Epidemiology of Outcomes cohort study: Design, baseline characteristics, and early outcomes.

To address the current and long-term unmet health needs of the growing population of non-Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18-99). Participants came from 49 US states and included 538 Black/African-Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population-based SEER data (2015-2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population-based SEER rates for indolent B-cell (follicular and marginal zone) and T-cell lymphomas, but were 10%-15% higher than SEER rates for aggressive B-cell subtypes (diffuse large B-cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Physical activity and the risk of non-Hodgkin lymphoma subtypes: A pooled analysis.

Non-Hodgkin lymphoma (NHL) is composed of a heterogeneous collection of subtypes with considerable differences in genetics, biology and aetiology. Studies to date on physical activity and NHL risk have not had sufficient sample size to evaluate whether associations differ by subtype. We pooled data from nine case-control studies to examine the association between moderate-to-vigorous intensity physical activity (MVPA) and risk of NHL overall and by subtype (diffuse large B-cell lymphoma, follicular lymphoma, chronic lymphocytic leukaemia/small lymphocytic lymphoma, marginal zone lymphoma and mature T-cell lymphoma). A total of 5653 cases and 9115 controls were included in the pooled analysis. Physical activity was harmonised across nine studies and modelled as study-specific tertiles. Multinomial logistic regression was used to estimate the association between physical activity and NHL, adjusting for confounders. The overall odds of NHL was 13% lower among participants in the most active tertile of MVPA compared to the least active tertile (adjusted odds ratio = 0.87, 95% CI = 0.80, 0.95). Similar decreases were observed across NHL subtypes. In summary, in this pooled analysis of case-control studies, physical activity was associated with a modest risk reduction for each NHL subtype examined and with overall NHL.

Genome-wide Association Study Identifies HLA-DPB1 as a Significant Risk Factor for Severe Aplastic Anemia.

Severe aplastic anemia (SAA) is a rare disorder characterized by hypoplastic bone marrow and progressive pancytopenia. The etiology of acquired SAA is not understood but is likely related to abnormal immune responses and environmental exposures. We conducted a genome-wide association study of individuals with SAA genetically matched to healthy controls in discovery (359 cases, 1,396 controls) and validation sets (175 cases, 1,059 controls). Combined analyses identified linked SNPs in distinct blocks within the major histocompatibility complex on 6p21. The top SNP encodes p.Met76Val in the P4 binding pocket of the HLA class II gene HLA-DPB1 (rs1042151A>G, odds ratio [OR] 1.75, 95% confidence interval [CI] 1.50-2.03, p = 1.94 × 10-13) and was associated with HLA-DP cell surface expression in healthy individuals (p = 2.04 × 10-6). Phylogenetic analyses indicate that Val76 is not monophyletic and likely occurs in conjunction with different HLA-DP binding groove conformations. Imputation of HLA-DPB1 alleles revealed increased risk of SAA associated with Val76-encoding alleles DPB1∗03:01, (OR 1.66, p = 1.52 × 10-7), DPB1∗10:01 (OR 2.12, p = 0.0003), and DPB1∗01:01 (OR 1.60, p = 0.0008). A second SNP near HLA-B, rs28367832G>A, reached genome-wide significance (OR 1.49, 95% CI 1.22-1.78, p = 7.27 × 10-9) in combined analyses; the association remained significant after excluding cases with clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes (8.6% of cases and 0% of controls). SNPs in the HLA class II gene HLA-DPB1 and possibly class I (HLA-B) are associated with SAA. The replacement of Met76 to Val76 in certain HLA-DPB1 alleles might influence risk of SAA through mechanisms involving DP peptide binding specificity, expression, and/or other factors affecting DP function.

Natural history of monoclonal B-cell lymphocytosis among relatives in CLL families.

Chronic lymphocytic lymphoma (CLL) has one of the highest familial risks among cancers. Monoclonal B-cell lymphocytosis (MBL), the precursor to CLL, has a higher prevalence (13%-18%) in families with 2 or more members with CLL compared with the general population (5%-12%). Although, the rate of progression to CLL for high-count MBLs (clonal B-cell count ≥500/µL) is ∼1% to 5%/y, no low-count MBLs have been reported to progress to date. We report the incidence and natural history of MBL in relatives from CLL families. In 310 CLL families, we screened 1045 relatives for MBL using highly sensitive flow cytometry and prospectively followed 449 of them. MBL incidence was directly age- and sex-adjusted to the 2010 US population. CLL cumulative incidence was estimated using Kaplan-Meier survival curves. At baseline, the prevalence of MBL was 22% (235/1045 relatives). After a median follow-up of 8.1 years among 449 relatives, 12 individuals progressed to CLL with a 5-year cumulative incidence of 1.8%. When considering just the 139 relatives with low-count MBL, the 5-year cumulative incidence increased to 5.7%. Finally, 264 had no MBL at baseline, of whom 60 individuals subsequently developed MBL (2 high-count and 58 low-count MBLs) with an age- and sex-adjusted incidence of 3.5% after a median of 6 years of follow-up. In a screening cohort of relatives from CLL families, we reported progression from normal-count to low-count MBL to high-count MBL to CLL, demonstrating that low-count MBL precedes progression to CLL. We estimated a 1.1% annual rate of progression from low-count MBL, which is in excess of that in the general population.

Matching-adjusted indirect comparison from the Lymphoma Epidemiology of Outcomes Consortium for Real World Evidence (LEO CReWE) study to a clinical trial of mosunetuzumab in relapsed or refractory follicular lymphoma.

Mosunetuzumab is a novel bispecific antibody targeting epitopes on CD3 on T cells and CD20 on B cells with the goal of inducing T-cell mediated elimination of malignant B cells. A recent pivotal phase I/II clinical trial (GO29781) demonstrated that mosunetuzumab induced an overall response rate of 80%, complete response rate of 60%, and a median progression-free survival of 17.9 months in patients with relapsed/refractory (r/r) follicular lymphoma (FL) following at least two prior lines of systemic therapy, including alkylator and anti-CD20 antibody-based therapy. Historical data from cohorts receiving therapy for r/r FL can provide some context for interpretation of single-arm trials. We compared the results from the mosunetuzumab trial to outcomes from a cohort of patients with r/r FL from the LEO Consortium for Real World Evidence (LEO CReWE). We applied clinical trial eligibility criteria to the LEO CReWE cohort and utilized matching-adjusted indirect comparison weighting to balance the clinical characteristics of the LEO CReWE cohort with those from the mosunetuzumab trial. Overall response rates (73%, 95% CI:65-80%) and complete response rates (53%, 95% CI:45-61%) observed in the weighted LEO CReWE cohort were lower than those reported on the mosunetuzumab trial (ORR=80%, 95% CI:70-88%; CR=60%, 95% CI:49-70% respectively). Progression-free survival at 12 months was similar in the weighted LEO CReWE (60%, 95% CI:51-69%) and the mosunetuzumab trial (PFS 58%, 95% CI:47-68%). Sensitivity analyses examining the impact of matching variables, selection of line of therapy, and application of eligibility criteria, provide context for best practices in this setting.

Cell of origin is not associated with outcomes of relapsed or refractory diffuse large B cell lymphoma.

Activated B cell (ABC) type diffuse large B cell lymphoma (DLBCL), double hit lymphoma (DHL) and double expressor lymphoma (DEL) have poor outcomes to frontline R-CHOP but impact of these molecular features on outcomes of relapsed/refractory (R/R) disease is not well-characterized. We evaluated the association of diagnostic cell of origin (COO), double hit and double expressor status with overall survival after first relapse in DLBCL patients who were enrolled into the Molecular Epidemiology Resource (MER) cohort. COO was available from immunohistochemistry (IHC) using Hans criteria or gene expression profiling (GEP) (Nanostring) on the diagnostic FFPE biopsy. Of 373 pts with R/R DLBCL, 278 had COO by IHC: 152 were GCB, 107 were non-GCB. One hundred and fourty had COO by GEP: 44 were ABC, 65 were GCB and 13 were unclassifiable. Nineteen out of 163 (12%) were DHL; 30 out of 135 (22%) had DEL. COO, either by IHC (2 years OS GCB: 45% [CI95 : 38-54] vs. non-GCB: 44% [CI95 :36-55], p > 0.05) or GEP (2 years OS ABC: 42% [CI95 : 29-59] vs. GCB: 40% [CI95 : 30-54], p > 0.05), was not associated with difference in OS. DHL (2 years OS 16 [CI95 :6-45] vs. 45% [CI95 : 34-59], p < 0.01) and DEL (2 years OS 33% [CI95 : 20-56], vs. 50% [CI95 : 41-60], p < 0.05) had lower OS than non-DHL and non-DEL/non-DHL counterparts, respectively. COO by IHC or GEP was not associated with OS in R/R DLBCL while DHL and DEL were adverse prognostic markers in DLBCL at first relapse.

Molecular classification and identification of an aggressive signature in low-grade B-cell lymphomas.

Non-follicular low-grade B-cell lymphomas (LGBCL) are biologically diverse entities that share clinical and histologic features that make definitive pathologic categorization challenging. While most patients with LGBCL have an indolent course, some experience aggressive disease, highlighting additional heterogeneity across these subtypes. To investigate the potential for shared biology across subtypes, we performed RNA sequencing and applied machine learning approaches that identified five clusters of patients that grouped independently of subtype. One cluster was characterized by inferior outcome, upregulation of cell cycle genes, and increased tumor immune cell content. Integration of whole exome sequencing identified novel LGBCL mutations and enrichment of TNFAIP3 and BCL2 alterations in the poor survival cluster. Building on this, we further refined a transcriptomic signature associated with early clinical failure in two independent cohorts. Taken together, this study identifies unique clusters of LGBCL defined by novel gene expression signatures and immune profiles associated with outcome across diagnostic subtypes.

Utilization of real-world data in assessing treatment effectiveness for diffuse large B-cell lymphoma.

Direct comparisons of the effectiveness of the numerous novel therapies in the diffuse large B-cell lymphoma (DLBCL) treatment landscape in a range of head-to-head randomized phase 3 trials would be time-consuming and costly. Comparative effectiveness studies using real-world data (RWD) represent a complementary approach. Recently, several studies of relapsed/refractory (R/R) DLBCL have used RWD to create observational cohorts to compare patient outcomes with cohorts derived from single-arm phase 2 trials. Using propensity score methods to balance clinically and prognostically relevant baseline covariates, closely matched patient-level cohorts can be generated. By incorporating appropriate measures to assess covariate balance and address potential bias in comparative effectiveness study designs, robust comparative analyses can be performed. Results from such studies have been used to supplement regulatory approval of therapies assessed in single-arm trials. While RWD studies have a greater susceptibility to bias compared to randomized controlled trials, well-designed and appropriately analyzed studies can provide complementary real-world evidence on treatment effectiveness.

2016 US lymphoid malignancy statistics by World Health Organization subtypes.

Collectively, lymphoid neoplasms are the fourth most common cancer and the sixth leading cause of cancer death in the United States. The authors provide contemporary lymphoid neoplasm statistics by subtype based on the 2008 World Health Organization classifications, including the most current US incidence and survival data. Presented for the first time are estimates of the total numbers of US lymphoid neoplasm cases by subtype as well as a detailed evaluation of incidence and survival statistics. In 2016, 136,960 new lymphoid neoplasms are expected. Overall lymphoma incidence rates have declined in recent years, but trends vary by subtype. Precursor lymphoid neoplasm incidence rates increased from 2001 to 2012, particularly for B-cell neoplasms. Among the mature lymphoid neoplasms, the fastest increase was for plasma cell neoplasms. Rates also increased for mantle cell lymphoma (males), marginal zone lymphoma, hairy cell leukemia, and mycosis fungoides. Like incidence, survival for both mature T-cell lymphomas and mature B-cell lymphomas varied by subtype and by race. Patients with peripheral T-cell lymphomas had among the worst 5-year relative survival (36%-56%, depending on race/sex), while those with mycosis fungoides had among the best survival (79%-92%). For B-cell lymphomas, 5-year survival ranged from 83% to 91% for patients with marginal zone lymphoma and from 78% to 92% for those with hairy cell leukemia; but the rates were as low as 47% to 63% for patients with Burkitt lymphoma and 44% to 48% for those with plasma cell neoplasms. In general, black men had the lowest survival across lymphoid malignancy subtypes. These contemporary incidence and survival statistics are useful for developing management strategies for these cancers and can offer clues regarding their etiology. CA Cancer J Clin 2016;66:443-459. © 2016 American Cancer Society.

Modeling historic neighborhood deprivation and non-Hodgkin lymphoma risk.

Many studies have identified associations between neighborhood deprivation and disease, emphasizing the importance of social determinants of health. However, when studying diseases with long latency periods such as cancers, considering the timing of exposures for deprivation becomes more important. In this study, we estimated the associations between neighborhood deprivation indices at several time points and risk of non-Hodgkin lymphoma (NHL) in a population-based case-control study at four study centers - Detroit, Iowa, Los Angeles County, and Seattle (1998-2000). We used the Bayesian index regression model and residential histories to estimate neighborhood deprivation index effects in crude models and adjusted for four chemical mixtures measured in house dust and individual-level covariates. We found that neighborhood deprivation in 1980, approximately twenty years before study entry, provided better model fit than did neighborhood deprivation at 1990 and 2000. We identified several statistically significant associations between neighborhood deprivation in 1980 and NHL risk in Iowa and among long-term (20+ years) residents of Detroit. The most important variables in these indices were median gross rent as a percentage of household income in Iowa and percent of single-parent households with at least one child and median household income in Detroit. Associations remained statistically significant after adjustment for individual-level covariates and chemical mixtures, providing evidence for historic neighborhood deprivation as a risk factor for NHL and motivating future research to uncover the specific carcinogens driving these associations in deprived areas.

Modeling historic environmental pollutant exposures and non-Hodgkin lymphoma risk.

Environmental exposures to chemicals are suspected risk factors for non-Hodgkin lymphoma (NHL), but few studies have assessed historic environmental risk factors. In this study, we estimated the associations between NHL and 1) historic environmental pollutant emissions from the Risk Screening Environmental Indicators (RSEI) model, which uses a database from the Environmental Protection Agency of toxic release emissions to air, water, and land, and 2) chemical mixtures measured in house dust (groups of PCBs, PAHs, and two mixtures of pesticides) for study participants enrolled in the NCI-SEER population-based case-control study (1998-2000) at four SEER centers - Detroit, Iowa, Los Angeles County, and Seattle. We assigned 11 years of annual temporally-varying historic environmental exposure scores by intersecting residential locations from participants' residential histories with a fine grid from the RSEI model and by performing inverse distance weighting between facilities releasing specific carcinogenic chemicals and residential locations for spatially-precise exposure assignments. We used Bayesian index low-rank kriging multiple membership models to identify important lag times for RSEI scores, cumulative effects of RSEI scores, and specific carcinogenic chemical releases into the environment. We found a significant positive association between RSEI scores and NHL at the maximum time lag of 11 years (OR = 1.17, 95% CI (1.06, 1.32)) and a significant cumulative RSEI score effect (OR = 1.30, 95% CI (1.02, 1.84)) for long-term residents in Detroit, where benzene and trichloroethylene were the most important chemicals driving this association. Additionally, we identified significant inverse associations for two study centers and time lags that did not persist in cumulative exposure models. Large weights for dichloromethane and pentachlorophenol in models of cumulative exposure also support evidence for their association with NHL risk. These results underscore the importance of considering historic and cumulative environmental exposures and using residential histories for diseases with long latency periods such as NHL.

Do GWAS-Identified Risk Variants for Chronic Lymphocytic Leukemia Influence Overall Patient Survival and Disease Progression?

Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults worldwide. Although genome-wide association studies (GWAS) have uncovered the germline genetic component underlying CLL susceptibility, the potential use of GWAS-identified risk variants to predict disease progression and patient survival remains unexplored. Here, we evaluated whether 41 GWAS-identified risk variants for CLL could influence overall survival (OS) and disease progression, defined as time to first treatment (TTFT) in a cohort of 1039 CLL cases ascertained through the CRuCIAL consortium. Although this is the largest study assessing the effect of GWAS-identified susceptibility variants for CLL on OS, we only found a weak association of ten single nucleotide polymorphisms (SNPs) with OS (p < 0.05) that did not remain significant after correction for multiple testing. In line with these results, polygenic risk scores (PRSs) built with these SNPs in the CRuCIAL cohort showed a modest association with OS and a low capacity to predict patient survival, with an area under the receiver operating characteristic curve (AUROC) of 0.57. Similarly, seven SNPs were associated with TTFT (p < 0.05); however, these did not reach the multiple testing significance threshold, and the meta-analysis with previous published data did not confirm any of the associations. As expected, PRSs built with these SNPs showed reduced accuracy in prediction of disease progression (AUROC = 0.62). These results suggest that susceptibility variants for CLL do not impact overall survival and disease progression in CLL patients.

Chronic lymphocytic leukemia (CLL) risk is mediated by multiple enhancer variants within CLL risk loci.

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.

Inherited variants at 3q13.33 and 3p24.1 are associated with risk of diffuse large B-cell lymphoma and implicate immune pathways.

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.

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide.

Estimating mixture effects and cumulative spatial risk over time simultaneously using a Bayesian index low-rank kriging multiple membership model.

The exposome is an ideal in public health research that posits that individuals experience risk for adverse health outcomes from a wide variety of sources over their lifecourse. There have been increases in data collection in the various components of the exposome, but novel statistical methods are needed that capture multiple dimensions of risk at once. We introduce a Bayesian index low-rank kriging (LRK) multiple membership model (MMM) to simultaneously estimate the health effects of one or more groups of exposures, the relative importance of exposure components, and cumulative spatial risk over time using residential histories. The model employs an MMM to consider all residential locations for subjects weighted by duration and LRK to increase computational efficiency. We demonstrate the performance of the Bayesian index LRK-MMM through a simulation study, showing that the model accurately and consistently estimates the health effects of one or several group indices and has high power to identify a region of elevated spatial risk due to unmeasured environmental exposures. Finally, we apply our model to data from a multicenter case-control study of non-Hodgkin lymphoma (NHL), finding a significant positive association between one index of pesticides and risk for NHL in Iowa. Additionally, we find an area of significantly elevated spatial risk for NHL in Los Angeles. In conclusion, our Bayesian index LRK-MMM represents a step forward toward bringing the ideals of the exposome into practice for environmental risk analyzes.