Citations

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.

Background Genome-wide association studies (GWAS) conducted in populations of European ancestry (EA) have identified and confirmed 23 germline susceptibility loci for multiple myeloma (MM). The effect sizes of single nucleotide polymorphisms (SNPs) at these loci are small, therefore combining them into a single summary measure, known as a polygenic risk score (PRS), may provide a more meaningful risk factor. We have previously shown a PRS comprised of the 23 SNPs for MM contributes to increased risk of MM, with a 2.7-fold increase for highest vs. lowest PRS quintiles. Whether the MM-PRS is also associated with overall survival (OS) in MM cases has not been evaluated. We examined the association between MM-PRS and OS in two EA studies. Methods The first study consisted of 2,179 EA MM cases from ten studies included in the Multiple Myeloma Working Group within the International Lymphoma Consortium (InterLymph). Cases were diagnosed between 1970 and 2015 and genotyped using multiple platforms (Oncoarray, Affymetrix, Human660W-quad Beadchip, and Illumina arrays); 885 cases also had stage [based on International Staging System (ISS)] available. Each of the GWAS was subjected to rigorous standard quality control independently (prior to imputation via the Michigan imputation server based on the Haplotype Reference Consortium (HRC). The second study consisted of 515 newly diagnosed EA MM cases from CoMMpass (Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile), diagnosed from 2011-2013, who had whole genome sequencing (WGS) performed on germline DNA. The WGS data was used to call common germline genetic variants through the Mayo Clinic bioinformatics pipeline. Briefly, genetic variants were detected with GenomeGPS, aligned to the hg19 reference genome, called using the GATK (V3.6) Haplotype Caller, and merged for multiple-sample joint calling. To reduce the false positive variants, variant quality score recalibration (VQSR) was applied for both SNPs and INDELs. After quality control, 458 EA samples remained. Follow-up was available for both studies and consisted of time from MM diagnosis date until death or date of last known follow-up. The PRS was constructed from the 23 MM SNPs using the published per allele odds ratio associated with MM risk. The published log odds ratios for each SNP were multiplied by the number of risk alleles (0, 1, 2) for the corresponding SNP, and summed, resulting in a unique score per person. Kaplan-Meier curves and Cox proportional hazard models were used to assess the association between PRS with MM OS considering two models: 1) adjusted for age, sex, study and 2) additional adjustment by stage (ISS). Hazard ratios (OR) and 95% confidence intervals (CI) were estimated. The PRS was evaluated both as a continuous variable, per standard deviation (SD), and as a categorical variable (quintiles). Results MM cases (N=2,179) in the InterLymph study were 59% male and 41% female and the median age was 61.0 years (26-90 years). Median follow-up time was 57.2 months (1.0-509.0 months) with 868 reported deaths. MM cases with stage information available consisted of 20% stage I (n=178), 53% stage II (n=466), and 27% stage III (n=241). No association was observed between PRS and OS in MM patients regardless of adjustment for stage (continuous PRS (HR: 1.03, 95% CI: 0.83-1.28, P=0.80) or by quintile PRS (p>0.05)) (Table). The CoMMpass EA MM cases (n=458) had similar distributions for sex (61% male and 39% females) but were slightly older 65 years (27-93 years) and had shorter follow-up time (median=39.75 months (0.13-77.2)) with 117 deaths. Stage was available for 96% of CoMMpass cases including 36% stage I (n=159), 33% stage II (n=146), and 31% stage III (n=134). We also observed no association of PRS and OS in the CoMMpass study (HR=1.02, 95% CI: 0.72 -1.46, P= 0.89), adjusted for age, sex, and stage (Table). Discussion A PRS score for MM risk is not associated with OS for MM cases in two EA populations. Given that prior studies have shown association of genetic variation with MM survival, efforts to identify additional loci associated with OS or MM specific survival are warranted. Future studies should also consider germline variants impact on molecular subtypes, specific therapies, and outcomes. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Background: The 2018 iwCLL guidelines recommend close observation of early stage CLL pts who do not meet indications for therapy ("watch and wait" strategy). Prior attempts at early therapeutic intervention in unselected early-stage CLL pts using alkylating agents such as chlorambucil and chemoimmunotherapy failed to show a significant benefit; and these therapies were associated with substantial toxicities. The introduction of Bruton tyrosine kinase (BTK) inhibitors has revolutionized the treatment landscape of CLL. The German CLL Study group recently presented results of the CLL12 study which demonstrated a significant improvement in event-free survival (EFS) among untreated early stage high risk CLL pts who received ibrutinib compared to placebo (median EFS not reached vs. 47.8 months, respectively; Langerbeins, EHA, 2019). Acalabrutinib is a more selective second-generation BTK inhibitor that has fewer adverse events in pts with CLL, and has shown equally impressive clinical activity for CLL pts. We are conducting an investigator initiated randomized phase 2 study to compare acalabrutinib with or without obinutuzumab (a glycoengineered anti-CD20 monoclonal antibody approved in the treatment of CLL) among high risk early stage CLL pts. Study Design: All pts with newly diagnosed (<2 years from registration) previously untreated early stage CLL who do not meet the 2018 iwCLL guidelines for initiation of therapy are eligible for enrollment in this study. Pts undergo risk stratification according to the CLL-International prognostic index (CLL-IPI) which consists of the following 5 variables: age >65 years (1 point), Rai stage I-IV (1 point), del17p and/or TP53 mutation (4 points), unmutated immunoglobulin heavy chain (IGHV) genes (2 points), and serum β2-microglobulin >3.5 g/dL (2 points). Pts with high (4-6) and very high (7-10) risk CLL-IPI are randomly (1:1) assigned to acalabrutinib 100 mg orally twice daily (Arm A) or acalabrutinib with obinutuzumab at a standard approved schedule (Arm B). Treatment with acalabrutinib is continued for a minimum of 2 years unless the patient has unacceptable side effects or withdraws consent. Pts with low (0-1) and intermediate (2-3) risk CLL-IPI score are assigned to an observation arm with follow-up once every 6 months for 2 years, and then according to routine clinical practice (Arm C). Endpoints: The primary endpoint of the intervention arms (Arms A and B) is the achievement of minimal residual disease (MRD)-negative complete remission in the bone marrow after 2 years of therapy. MRD is assessed using an 8-color flow cytometry with a detection limit of 0.01%. The primary endpoint of the observation arm (Arm C) is time to first therapy. Secondary endpoints for all arms are: progression-free survival, overall survival, and safety. Statistical design: A randomized trial comparing the experimental arm (acalabrutinib plus obinutuzumab) against the control arm (acalabrutinib alone) will be conducted as described by Rubinstein. A sample size of 36 pts per arm provides 80% power to detect an improvement in MRD-negative complete response rate from 10% to 30%, using a one-sided test at a significance level of 0.10 (EAST 6.4). We anticipate accruing an additional 8 high/very high risk pts (4 in each arm) to account for ineligibility, cancellation, or major treatment violation. The total enrollment for Arms A and B will be 80 pts. We will enroll 40 pts to Arm C; for a total enrollment of 120 pts. Key correlatives: Comprehensive profiling to assess the innate and adaptive immune system in paired peripheral blood and bone marrow will be conducted in all pts registered to Arms A and B at baseline, 12 and 24 months after enrollment. In addition, bone marrow hematopoietic function will be assessed in all pts at these time points. We will employ a CLL focused custom 61-gene panel to estimate tumor mutational burden as well as mutational profiles for each patient at baseline, 12, and 24 month time points, as well at the time of disease progression. Preliminary results: The trial is registered at clinicaltrials.gov NCT03516617. The trial opened to accrual at all three Mayo Clinic sites (Rochester, MN; Jacksonville, FL; and Scottsdale, AZ) in September 2018. Twenty-eight pts have been registered; the baseline characteristics are shown in Table 1. The trial is expected to complete enrollment in September 2020; and the primary analysis will be available in September 2022. Disclosures Parikh: Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria. Ding:DTRM Biopharma: Research Funding; Merck: Research Funding. Ailawadhi:Pharmacyclics: Research Funding; Cellectar: Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Chanan-Khan:Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; Jansen: Research Funding; AbbVie: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding. Kay:Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board. OffLabel Disclosure: Drug: Acalabrutinib Purpose: treatment of CLL

INTRODUCTION Mutations in BTK and PLCG2 have been reported to occur in ~80% of CLL patients (pts) who have progression of disease on ibrutinib therapy (Woyach, JCO 2017; Ahn, Blood 2017). These mutations are described as appearing months before actual relapse and thus considered as a potential predictive biomarker for future relapse (Quinquenel, Blood 2019). However, the outcomes of these pts after disease progression are not well described. In this study, we seek to investigate time to next therapy and overall survival (OS) following progression among CLL pts on ibrutinib therapy with and without these resistance mutations. METHODS Between 10/2012 and 6/2019, we identified 34 pts in the Mayo Clinic clinical CLL resource who progressed while receiving ibrutinib therapy and also had testing for BTK and PLCG2 mutation performed as part of routine clinical practice at either NeoGenomics Laboratories or The Ohio State University. OS was calculated from time of ibrutinib progression to last known alive or death date; OS was plotted using Kaplan Meier methods and was compared using the log-rank test between various groups (e.g., mutation positive vs negative; CLL progression vs Richter's). Cumulative incidence of time to next treatment in those who had a treatment after progression was adjusted for the competing risk of death. RESULTS Of 34 pts who progressed while receiving ibrutinib, 26 pts experienced CLL progression and 8 pts had Richter's transformation; baseline characteristics in Table 1A. The presence of a BTK or PLCG2 mutation was found in 20/34 (59%) pts (specific mutations in Table 1B). BTK mutation alone was present in 9 pts, 7 pts had PLCG2 mutation alone, and 4 pts had both mutations. Median time between a positive test and start of next therapy was 4 months (range 1-19 months) and did not vary between BTK vs PLCG2 mutations. Among the 26 pts with CLL progression, 18 (69%) pts had a mutation present: BTK alone (n=8), PLCG2 alone (n=6), both (n=4). Therapy following progression on ibrutinib in these pts was as follows: venetoclax (n=16; 11 pts who continued ibrutinib in combination), idelalisib (n=4), investigational treatments (n=2), continued ibrutinib alone (n=2), dose-adjusted EPOCH-R (etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab; n=1), and unknown (n=1). Twelve of the 26 pts with CLL progression on ibrutinib, including 8 pts with a prior resistance mutation detected, had subsequent progression of disease on the aforementioned next line therapy. Treatment of these patients consisted of the following: restarted ibrutinib in addition to current treatment of venetoclax (n=5), venetoclax (n=2), pembrolizumab (n=2; 1 pt with continued ibrutinib), obinutuzumab with continued ibrutinib (n=1), gemcitabine and vinorelbine with continued ibrutinib (n=1), and no further treatment (n=1). Among the 8 pts with Richter's transformation as the initial progression event on ibrutinib after mutation testing, 1 pt had a BTK mutation and 1 pt had a PLCG2 mutation. Treatments following progression on ibrutinib included multi-agent chemoimmunotherapy (n=3; 2 pts received rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone [R-CHOP] with continued ibrutinib and 1 pt received doxorubicin, bleomycin, vinblastine, dacarbazine [ABVD] alone), pembrolizumab (n=3; 1 pt in combination with continued ibrutinib), venetoclax in combination with continued ibrutinib (n=1), and venetoclax and obinutuzumab (n=1). The median time to next treatment (second line of treatment beyond ibrutinib) for the 31 pts who started another therapy following progression on ibrutinib was 16.7 months (95% CI 9.6-NE; Figure 1A) and was not significantly different for pts with or without a resistance mutation (p=0.57). Median OS for all 26 pts with CLL progression was 28.7 month and there was no difference according to presence or absence of a resistance mutation (median 28.7 months vs 18.2 months, p=0.53; Figure 1B). The 8 pts with Richter's transformation had a median OS of 7.1 months (95% CI 2.0-NE). CONCLUSION Approximately 60% of pts tested in this progression cohort had a BTK or PLCG2 mutation at time of or preceding progression on ibrutinib therapy. OS and time to next therapy did not differ statistically between pts with mutated vs non-mutated clones; however, caution should be applied with the conclusions given the limited sample size. Disclosures Ding: DTRM Biopharma: Research Funding; Merck: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. Parikh:Ascentage Pharma: Research Funding; Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding.

Monoclonal B cell lymphocytosis (MBL) has been shown to be the precursor condition that precedes overt diagnosis of chronic lymphocytic leukemia (CLL). Whereas CLL is classified with greater than or equal to 5 × 109/L B lymphocytes in the peripheral blood, MBL is a clonal expansion of B-cells below this threshold. MBL can be further divided into high- or low-count based on whether the B-cell count is above or below 0.5 × 109/L. Approximately 10% of the population over 40 is estimated to have MBL, increasing to >50% over the age of 90. While low-count MBL is unlikely to progress, 1-2% of high-count (HC) MBL individuals progress to CLL requiring therapy per year. It is debatable if all patients with detectable MBL should be classified as an entity requiring monitoring by a hematologist, especially for low-count MBL. In addition, the diagnosis of leukemia is distressing to patients; therefore, it is important to identify HC MBL patients that are more likely to progress to disease requiring treatment and thus should be monitored more closely. As the majority of MBL cases phenotypically resemble CLL, established prognostic markers including recurrent chromosomal aberrations, beta-2 microglobulin levels, and the mutational status of the Immunoglobulin heavy-chain variable region locus (IGHV) have been shown to predict time to treatment (TTT) and overall survival (OS) in a large retrospective study of MBL1. CLL patients can also be divided into three distinct epigenetic subtypes that reflect progressive DNA methylation changes that occurs during B cell development. These 'epitypes' termed low-programmed (LP), intermediate-programmed (IP), and high-programmed (HP) independently predict clinical outcomes irrespective of disease stage and treatment2. LP-CLL patients follow a generally unfavorable clinical course compared to the more indolent HP-CLL patients, while IP CLL patients display an intermediate outcome. Here we sought to determine if epitype forecasts progression to CLL and eventual clinical outcome for individuals with MBL. We analyzed 66 individuals diagnosed with HC MBL at the Mayo Clinic with a median follow-up of 6.3 years. Developmental epitype was determined using our novel Methylation-iPLEX technique that interrogates 34 CpGs and assigns epitype using a random forest model2. Seventy-seven percent of the MBL cases were assigned to one of the three epitypes: 42.4% HP, 19.7% IP, and 15.2% LP. The residual 23% remained unclassified due to ambiguous (low confidence) epigenetic patterns or insufficient purity (Figure 1A). The overall proportion of HP and IP epitypes in MBL were significantly greater than proportions observed in CLL cohorts (P<0.01). Epitypes remained stable over time as 20/21 cases for which we obtained a high-confidence epitype classification at multiple time points remained unchanged. Epitype significantly predicted MBL individuals progressing to treatment (P=0.001) with LP individuals progressing in a median of 5.6 years (P=0.049 and P=0.0002 versus IP and HP, respectively); median was not reached in HP or IP (Figure 1B). Epitype also predicted overall survival (OS) in MBL (P=0.04), with LP individuals having a significantly shorter OS (median of 11 years versus not reached in IP and HP; P=0.056 and P=0.048 versus IP and HP, respectively). In this study we evaluated a cohort of 66 HC MBL cases and determined that classification using developmental DNA methylation epitypes can be employed in HC MBL to aid in risk stratification. HC MBL patients classified as LP are more likely to progress to requiring treatment and have a significantly reduced OS. The epigenetic classification may help clinicians decide how closely and frequently a HC MBL individual needs to be monitored. Figure 1: (A) Breakdown of the epigenetic subtype assigned to 66 HC MBL samples. (B) Kaplan-Meier analysis of time to treatment and (C) overall survival of MBL patients separated by epitype. 1. Parikh, S. A. et al. Outcomes of a large cohort of individuals with clinically ascertained high-count monoclonal B-cell lymphocytosis. Haematologica103, e237-e240 (2018). 2. Giacopelli, B. et al. Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia. Blood blood.2019000490 (2019). doi:10.1182/blood.2019000490 Disclosures Byrd: Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding. Shanafelt:Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Merck: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Glaxo-SmithKline: Research Funding; Abbvie: Research Funding; Cephalon: Research Funding; Celgene: Research Funding. Parikh:Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding. Kay:Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board.

Background: The 2008 International Working Group for CLL (IWCLL) criteria define MBL as a clonal B-cell disorder with a peripheral blood B-cell count of <5 x 109/L, in the absence of cytopenias(s), lymphadenopathy and/or organomegaly on physical examination, and no other concomitant lymphoproliferative disorder. In the presence of palpable lymphadenopathy and/or organomegaly, and a B-cell count of < 5 x 109/L, a diagnosis of small lymphocytic lymphoma (SLL) is established. A study by Gentile et al (Am J Hematol. 2013) reported that 29 out of 62 individuals with clinically identified MBL (42%) had lymphadenopathy identified on CT imaging. Notably, however, after a median follow-up of 35 months, the rate of progression among cases of MBL with lymphadenopathy identified on CT imaging was only 6.9% (2/29 patients), which was no different than in cases of MBL without lymphadenopathy on CT imaging (rate of progression, 9%; 3/33 patients). Our study sought to 1) determine if lymphadenopathy and/or organomegaly detected by imaging studies performed for unrelated reasons in individuals with MBL can identify a subset with shorter time to first CLL therapy (TFT) and overall survival (OS); and 2) compare outcomes of individuals with MBL who have incidentally detected lymphadenopathy/splenomegaly and SLL patients. Methods: We used the Mayo Clinic CLL Database to identify individuals with high-count MBL (absolute B-cell count: 0.5 - 4.9 x 109/L) and divided them into the following three cohorts: a) Cohort A: no imaging studies available at MBL diagnosis; b) Cohort B: imaging studies done within one year of MBL with no evidence of lymphadenopathy and/or organomegaly; and c) Cohort C: imaging studies done within one year of MBL with lymphadenopathy and/or organomegaly, attributable to MBL. All individuals with MBL were first seen at Mayo Clinic after 1/1/2002; those with a concomitant lymphoproliferative disorder within 3 months of diagnosis were excluded. Patients with SLL seen during the same time interval were identified as a comparison cohort. We compared the baseline characteristics (Kruskal Wallis for continuous and Chi-square for categorical variables) and TFT and OS across the three MBL cohorts, and patients with SLL. Cumulative incidence of TFT was adjusted for the competing risk of death. Age- and sex-adjusted OS was analyzed using inverse weights methods. Results: 657 individuals with high-count MBL with a median follow-up of 6.7 years were identified: 415 (63%) individuals were in Cohort A, 142 (22%) in Cohort B, and 100 in (15%) Cohort C. Compared to Cohort B, individuals in Cohort C were more likely to have unmutated IGHV, high expression of CD38, and higher beta-2 microglobulin level (Table 1). SLL patients were younger, had higher rate of unmutated IGHV, and had high expression of CD49d compared to MBL individuals in Cohort C (Table 1). There was suggestive evidence of a difference in TFT between Cohorts B and C (estimated 10-year treatment rate 28.3% vs. 41.6%; p=0.16; HR 1.62 95% CI 0.84-3.15). TFT was significantly shorter in SLL patients compared to those with Cohort C (estimated 10-year treatment rate 71% vs. 41.6%, respectively, P<0.001; Figure 1A). There was a trend toward shorter OS in Cohort C compared to Cohort B (estimated 10-year OS rate 53.7% vs. 64.2%, respectively, P=0.09; Figure 1B). In contrast, there was no difference in OS among MBL individuals in Cohort C compared to those with SLL (estimated 10-year OS rate 56.9% vs. 62.6%, P=0.72). Summary/Conclusion: Our findings demonstrate that individuals with MBL who have incidentally identified lymphadenopathy/splenomegaly at diagnosis are more likely to have an unfavorable risk profile, shorter TFT and OS compared to patients who did not have lymphadenopathy/splenomegaly at MBL diagnosis. Additionally, these individuals have a longer TFT but similar OS compared to SLL patients seen during the same time interval. If externally validated, these findings have significant implications for individuals with newly diagnosed MBL. Disclosures Ding: Merck: Research Funding; DTRM Biopharma: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. Parikh:AstraZeneca: Honoraria, Research Funding; Janssen: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding.

Background: While there is evidence in the literature of increased prevalence of hypogammaglobulinemia in chronic lymphocytic leukemia (CLL), there are no studies evaluating the prevalence of hypogammaglobulinemia in newly diagnosed diffuse large B cell lymphoma (DLBCL) or the relationship between hypogammaglobulinemia and presentation or outcomes. The objective of this study was to examine the prevalence of hypogammaglobulinemia in newly diagnosed DLBCL patients and to test the hypothesis that DLBCL patients with baseline hypogammaglobulinemia have a distinct clinical profile and outcome. Methods: We obtained banked frozen sera from 200 newly diagnosed, treatment-naïve, DLBCL patients from the Lymphoma SPORE Molecular Epidemiology Resource (MER), a prospective cohort study conducted at the Mayo Clinic and the University of Iowa. IgG/A/M levels were measured using immunoturbidimetric assay whereas IgE level was measured using electrochemiluminescence immunoassay; deficiency was defined using standard reference ranges. IgE levels were considered deficient if &lt;2 UI/ml. The associations between Ig deficiencies and clinical factors were evaluated with Wilcoxon rank sum and chi-squared (Fisher's exact, where appropriate) tests. Event-free survival (EFS) was defined as time from diagnosis to progression, relapse, retreatment, or death, and EFS24 was defined as EFS at 24 months after diagnosis (achieve or failure to achieve EFS24). The association of Ig levels with EFS24 was estimated using odds ratios (OR) and 95% confidence intervals (CI) from logistic regression, and with EFS, overall survival (OS), and lymphoma-specific survival (LSS) was estimated using Kaplan-Meier curves and hazard ratios (HR) and 95% CI from Cox regression. Results: The mean age (SD) of the cohort was 65.6 (13.4) years, 54% were males and 98% of the patients were white. Over a median follow-up of five years, there were 59 (29.5%) deaths. The prevalence of hypogammaglobulinemia, defined as any deficiency, in newly diagnosed, treatment-naïve DLBCL was 22.1% (44/199) in our cohort, and the most common Ig deficiency was for IgG (&lt;700 mg/dL, 13.5%), followed by IgM (&lt;40 mg/dL, 9.0%), IgE (&lt;2 UI/ml, 7.5%) and IgA (&lt;70 mg/dL, 4.0%) (Table1). There were no statistically significant differences between Ig deficient and non-deficient patients in terms of age at diagnosis, gender, stage, cell of origin, or MYC double hit status. However, median LDH levels were higher in Ig deficient patients (228 vs 194, p&lt;0.01). Any immunoglobulin deficiency was associated with inferior EFS (HR 1.94, 95% CI 1.16-3.24) (Figure 1) and OS (HR 2.02, 95% CI 1.17-3.49), and these associations were not attenuated after adjustment for the international prognostic index (IPI). Any Ig deficiency was also associated with failure to achieve EFS24 (OR=2.13, 95% CI 1.00-4.60) after adjusting for IPI. Conclusions: To the best of our knowledge, this is the first study to report the prevalence of hypogammaglobulinemia in treatment naïve DLBCL. We found that any Ig deficiency was not uncommon in our cohort and it was associated with an inferior EFS and OS in DLBCL patients. The prevalence of hypogammaglobulinemia in DLBCL patients seems to be lower than has been described in CLL patients. While the underlying relationship between these two immunologic disorders deserves further study, our findings highlight the interaction between global immune dysfunction and emergence of a clonal B cell process. Disclosures Nowakowski: Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding. Cerhan:NanoString: Research Funding; Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees.

Introduction: New Diffuse Large B-cell (DLBCL) treatments remain a clinical need despite the success of rituximab combined with CHOP chemotherapy (RCHOP), which results in durable responses in 60-70% of patients. Those refractory to, or who relapse following, first-line therapy have a very poor outcome, with only 20% surviving beyond 5 years. Rationally-targeted frontline strategies are needed, especially for those with high-risk disease. Significant advances have been made in the genomic classification of DLBCL, but none have impacted the design of phase III trials for untreated DLBCL patients. Building on new genetic profiling studies to personalize clinical treatment, an NCI initiative, could allow clinicians to add targeted therapies to the RCHOP backbone based on individual tumor signatures. The phase II ECOG-ACRIN1412 trial, which compared RCHOP combined with lenalidomide (R2CHOP) versus RCHOP showed significantly superior event free survival (EFS) and overall survival benefits for those treated with R2CHOP. Herein, we report the profile of a high-risk ABC/non-GCB subset of DLBCL driven by genomic alterations in inflammatory genes that are susceptible to front-line R2CHOP, but continue to experience poor outcome with RCHOP alone. Methods: We studied a total of 196 DLBCL patients. 47 were treated with R2CHOP from an investigator-initiated, open-label, single-arm phase II study (NCT00670358). 149 were newly diagnosed DLBCL cases treated with RCHOP, or R-immunochemotherapy (herein called RCHOP), and followed prospectively through the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic SPORE that served as a contemporary cohort. Patients from each treatment group were divided based on their event free survival at 24 months (EFS24). DNA alterations within these populations were identified through whole exome sequencing (WES). Variants were analyzed for their presence in EFS24 achievement or failure groups in both RCHOP and R2CHOP. Both tumor and germline sequencing was performed for 47/47 R2CHOP cases and 49/149 RCHOP cases. Gene expression data from the PanCan panel of 730 B-cell-related genes was analyzed to determine gene expression profiles characteristic of the high-risk/R2CHOP-profile on 59 available non-GCB DLBCL cases (45 RCHOP; 14 R2CHOP). A two-sided comparative marker analysis T statistic test was applied to assess what genes displayed differential expression based on achieving EFS24 in both R2CHOP and RCHOP populations. Positive values represented associations with achieving EFS24 and negative values were associated with cases of EFS24 failure. Results: Three genes were enriched in the RCHOP cases that failed EFS24 but achieved EFS24 with R2CHOP among non-GCB patients: PIM1, SPEN, and MYD88 (L265P), herein referred to as Responder Alterations. In R2CHOP cases, patients with a Responder Alteration had a better overall EFS (P = 0.051) compared to wild type patients. In contrast, RCHOP treated patients with a Responder Alteration in their tumor had a significantly worse overall EFS (P = 0.0004) compared to patients without a mutation. Together, PIM1, SPEN, or MYD88 (L265P) mutations were present in 38.0% (30/79) of all non-GCB cases. Collective R2CHOP and RCHOP EFS24 differential gene expression T values were significantly different for 18 previously-defined signatures. The R2CHOP cases that achieved EFS24 were enriched for genes involved in cell cycle, JAK-STAT, cytokine signaling, and NF-κB pathways based on these signatures and ontology analyses. Lastly, cases with WES and PanCan data were analyzed together to observe differential gene expression patterns between cases with and without signature mutations. These data suggest that R2CHOP disrupts tumors reliant on IRF4, NF-κB, and STAT transcription factors, leading to a loss of proliferative feedback systems. Conclusions: Our combined analysis of DNA and RNA across R2CHOP and RCHOP treatment cohorts identifies a high-risk non-GCB phenotype that encompasses approximately 38% of non-GCB patients, is capable of sustaining JAK-STAT and NF-κB signaling, and is sensitive to R2CHOP. Our study lays the groundwork for a precision therapy approach in DLBCL in which DNA or RNA profiles can be used to identify patients early in treatment who may not benefit from the current standard of care, RCHOP, and who would benefit from the addition of lenalidomide or other targeted agents. Disclosures Gandhi: Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Novak:Celgene Coorperation: Research Funding.

Background: Multiple myeloma (MM) treatment has advanced considerably with proteasome inhibitors, immunomodulatory drugs (IMiDs), and, most recently, monoclonal antibodies. However, treatment response is quite heterogeneous, and many patients still progress even with novel combination therapies. Thus, understanding the factors that underlie response to treatment is a priority. Several somatic genomic aberrations and mutations predict poor response to therapy. However, germline variation has not previously been investigated as a predictor of treatment response in MM. We used genome-wide association and transcriptome-wide association approaches to identify germline genetic predictors of treatment response in MM. Methods: We included 510 MM patients from Mayo Clinic and 324 MM patients from UCSF diagnosed from 1999-2015. Basic demographics, laboratory values and pathology at diagnosis, type of initial therapy, duration of therapy, and follow-up were ascertained by chart review. Patients were grouped into categories of treatment based on their first line therapy: proteasome inhibitor-based regimen, IMiD based regimen, combination proteasome and IMiD based regimen, or other. Response was assessed using International Myeloma Working Group (IMWG) response criteria after 4-6 cycles of induction. As such, response was categorized into progressive disease (PD), minimal response (MR), partial response (PR), very good partial response (VGPR), or complete response (CR). Germline samples were genotyped using Illumina or Affymetrix arrays and were imputed based on the Haplotype Reference Consortium (HRC). For the genome-wide association study (GWAS), we included all SNPs with minor allele frequency >0.01 and imputation r2 of >0.5. We tested each SNP for association with treatment response using a linear regression model that adjusted for age, gender, and genetic ancestry (from principal components analysis (PCA)). To perform the transcriptome-wide association study (TWAS), we calculated predicted gene expression data using PREDIXCAN software on a reference cohort of 922 individuals with genotype and RNA expression data from peripheral blood. We then tested the association between predicted gene expression and response to therapy using linear regression models. Both the GWAS and TWAS were performed on subgroups of patients who received either proteasome inhibitors or IMiD therapies. The analyses of patients on proteasome inhibitors were adjusted for IMiD use as a covariate and analyses of patients on IMiDs were adjusted for proteasome inhibitor use. The threshold for genome-wide significance loci was set at P = 5 x 10-8 and the threshold for suggestive loci was set at P = 10-6. The threshold for significance for TWAS was set at P = 4 x 10-6 by using a Bonferroni correction for the number of genes for which genetic models of expression could be developed by PREDIXCAN. Results: Overall, 42.7% (59 of 138) of patients on proteasome inhibitors alone, 32.5% (66 of 203) of patients on IMiDs alone, and 58.1% (50 of 86) of patients on combination achieved at least a VGPR. There were no significant differences in response across centers in analyses that adjusted for age, sex and types of therapy. There were no genome wide significant loci to predict for response. We identified 8 suggestive SNPs associated with proteasome inhibitor response and 4 suggestive SNPs associated with IMiD response. TWAS identified ZNF622 as a candidate genetic modifier of proteasome inhibitor effect that was significant after correction for multiple hypothesis testing (P = 1.6 x 10-6). Higher genetically predicted expression was associated with improved response to proteasome inhibitor therapy. Among patients above the median of predicted expression of ZNF622 on proteasome inhibitors, 62.6% achieved at least VGPR; among patients at or below the median of expression, only 37.6% achieved at least VGPR. Conclusions: We identified an association between predicted expression of ZNF622 and clinical response to proteasome inhibitor therapy among MM patients. ZNF622 is a zinc finger binding protein which is known to be co-activator of B Myb activity and to affect apoptosis in response to oxidative stress. Our work highlights the potential importance of pharmacogenetic modifiers of treatment response in MM. Disclosures Shah: Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Indapta Therapeutics: Equity Ownership; University of California, San Francisco: Employment; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wong:Celgene: Research Funding; Janssen: Research Funding; Roche: Research Funding; Fortis: Research Funding. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Purpose The development of cardiovascular disease (CVD) is a relatively rare but a clinically important adverse event in the treatment of lymphoma, particularly in individuals receiving anthracyclines. There are few studies assessing the role of germline genetic susceptibility as a predictor of CVD in this setting. We evaluated the association of 24 single nucleotide polymorphisms (SNPs) from candidate genes involved in anthracycline-induced cardiotoxicity, CVD, and venous thromboembolism with new-onset CVD in a prospective cohort of lymphoma patients treated in the modern era. Methods All patients were from the Mayo component of the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma SPORE. Enrollment from 2002-2015 was offered to patients with newly diagnosed lymphoma who were age ≥18 years. Clinical, pathology and treatment data were abstracted using a standard protocol, and participants provided a peripheral blood sample, from which DNA was extracted. All patients were prospectively contacted every 6 months for the first 3 years from diagnosis and then annually thereafter to assess disease status, re-treatment and development of new morbidities, including CVD. Reported CVD events included congestive heart failure (CHF), coronary heart disease (CHD), arrhythmia, valvular heart disease (VHD), and other CVD. These events were identified during follow-up and validated against medical records. Genotyping was conducted using a custom Illumina iSelect platform with rigorous quality controls. For each SNP, Cox regression was used to estimate Hazard Ratios (HRs) and 95% confidence intervals (CI) with time to first CVD, using death without CVD as a competing risk. HRs were also obtained for time to CHF, using death without CVD as a competing risk. We also modeled these events for all patients and for patients receiving frontline anthracyclines. Each SNP was modeled as having a log-additive (per minor allele) effect in the regression model. An ordinal test was used to assess the trend, with a nominal P<0.05 considered statistically significant. Results There were a total of 3,063 newly diagnosed lymphoma patients (excluding chronic lymphocytic leukemia) with no history of CVD at time of lymphoma diagnosis, of which 1280 had genotype data available for analysis. The median age at diagnosis was 59 years (range, 18-95) and 56% were male. The most common subtypes were follicular (26.3%), diffuse large B-cell (23.2%), Hodgkin (11.3%), marginal zone (11.2%), mantle cell (6.3%) and T-cell (5.4%) lymphoma. Anthracycline-based chemotherapy as initial therapy was used in 52% of individuals. At a median follow-up of 6.9 years (range, 0.1-17.1), 363 (30.7%) patients died, and 173 (13.5%) had new-onset CVD after lymphoma diagnosis. There were 234 incident CVD events in the 173 patients: 49 CHD, 50 CHF, 27 VHD, 103 arrhythmias, and 5 other CVD. Results are shown in the Table. When assessing all CVD, F5 (rs4524) (HR=1.28, 95% CI=1.03-1.58) and F11 (rs4253399) (HR=1.30, 95% CI=1.06-1.61) were associated with CVD at P<0.05; both associations attenuated slightly when restricted to anthracycline-treated patients (F5 HR=1.18, 95% CI=0.89-1.57; F11 HR=1.23, 95% CI=0.92-1.65). F11 was more strongly associated with CHF (HR=1.55, 95% CI=1.03-2.34) and CHF in anthracycline-treated patients (HR=1.64, 95% CI=0.98-2.76). NCF4 (rs1883112) was marginally associated with lower risk of CVD overall (HR=0.81, 95% CI=0.66-1.00), and this association strengthened when restricted to anthracycline-treated patients (HR=0.67, 95% CI=0.49-0.91) and showed similar trends in HRs for CHF (HR=0.77, 95% CI=0.51-1.16) and CHF in anthracycline-treated patients (HR=0.72, 95% CI=0.41-1.28), although neither estimate was statistically significant at P<0.05. Finally, while XDH (rs2236168) was not associated with all CVD (HR=1.00, 95% CI=0.81-1.23), it was associated with CHF (HR=0.66, 95% CI=0.47-0.93) overall, but attenuated in anthracycline-treated patients (HR=0.81, 95% CI=0.55-1.18). Conclusions In this exploratory study of candidate SNPs from the literature, we found limited evidence for a role of germline genetic variability in predicting risk of CVD or CHF in a cohort of lymphoma patients, especially after accounting for multiple testing. To fully address this hypothesis, future studies will need larger sample sizes and more comprehensive genetic assessment. Disclosures Maurer: Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Nowakowski:NanoString: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; Bayer: Consultancy, Research Funding; Curis: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees.