King, Rebecca L.

Background: Diffuse large B cell lymphoma (DLBCL) is the most common aggressive lymphoid malignancy in adults. Though standard immunochemotherapy regimens can result in clinical remission and cure in a majority of patients, approximately 30% of patients are primary refractory or eventually relapse, and their prognosis is very poor. Recent progress by large scale genomic and transcriptomic profiling of DLBCL patients has resulted in a deep understanding of disease drivers in newly diagnosed DLBCL (ndDLBCL). However, previous genomic studies of relapsed and/or refractory DLBCL (rrDLBCL) are limited by small sample sizes and much less is known about the genomic landscape or the changes in clonal populations that occur within a patient undergoing R-CHOP therapy. Analysis of a large cohort of rrDLBCL is needed to uncover the importance of known drivers, define clonal shifts that occur in relapsing patients, and discover novel mutations that impact resistance to therapy. Methods: DNA sequencing (whole exome or genome sequencing) was performed on tumor and matching germline samples from two rrDLBCL patient cohorts (N=143). The first rrDLBCL cohort consisted of 68 formalin fixed paraffin embedded (FFPE) tumor samples with matched germline obtained from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER); including 18 diagnostic/relapse paired samples. The second cohort consisted of 75 FFPE samples from 2 rrDLBCL clinical trials CC-122-ST-001 and CC-122-DLBCL-001 (NCT01421524 and NCT02031419). In addition, a ndDLBCL cohort (n=364) consisting of MER front line samples were also analyzed. CNV and SV calling was performed with Sclust and Manta, respectively. Mutational drivers were identified with cDriver. Cosmic mutational signatures were calculated for all samples. Results: For comparison of overall mutation rates between the ndDLBCL and rrDLBCL we analyzed the frequency of mutations in known driver genes [n=211, Chapuy et al, 2018; Schmitz et al, 2018; Reddy et al 2017]. Of these, the top 5 most mutated genes found in the relapse cohort were KMT2D (34.3%), IGLL5 (25.9%), CREBBP (22.4%), TP53 (21.0%), and HIST1H1E (19.6%) all of which were previously reported as mutated genes in rrDLBCL [Morin et al. 2016; Park et al. 2016;Greenawalt et al. 2017]. None of these frequencies changed significantly from the MER ndDLBCL cohort. However, frequencies of 2 genes NCOR1 and ACTB were increased significantly from 3.3% to 13.3% (p= 5.85 x 10-05) and 0.5% to 6.3% (p=2.56 x 10-04), respectively, in the rrDLBCL cohorts. Analysis of the previously reported driver mutations in 18 paired samples revealed a significant increase in the mean variant allele frequency (VAF) from diagnosis to relapse of mutations in BCL2 and BIRC6 from 18.5% to 28.8%(p=0.016) and 4.3% to 13.7%(p=0.011), respectively. In our analysis of novel drivers in rrDLBCL cohorts, 59 significant driver mutations (FDR 0.1) were identified, 23 were novel driver mutations while the remaining 36 have been previously reported as drivers of newly diagnosed DLBCL. These include novel mutations in genes such as IL4R (8.8%), CDK5R1 (6.7%), LAPTM5 (3.7%) and others whose function in lymphoma are unknown. In a secondary analysis, we performed mutational signature analysis for rrDLBCL and identified groups of patients with COSMIC mutational signatures that are associated with aging, defects in homologous end joining resulting in large insertions/deletions, and with defective mismatch repair often found in microsatellite unstable tumors. Together with the high prevalence of TP53 mutations, these results indicate genetic instability as a hallmark of relapse/refractory DLBCL. Analysis of CNV and SV will also be reported. Conclusion: Here we report to our knowledge the largest genomic dataset in relapsed and /or refractory DLBCL using tumor biopsies. Previously identified mutated genes in rrDLBCL were confirmed and novel drivers identified. Paired samples analysis reveals clonal shifts which occur during treatment and at time of relapse. Whether the novel driver mutations appeared as a function of selection of a rare clone over the course of therapy or a therapy induced mutation will be the focus of ongoing work. Novel variants including SNV, CNV and SV can potentially lead to new insights and deepen our understanding of the mechanisms of resistance in DLBCL. * Wenzl, Ortiz and Stong contributed equally **Novak and Gandhi contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Nikbakht:Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Bayer: Consultancy, Research Funding; Curis: Research Funding; Celgene: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Novak:Celgene Coorperation: Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties.

AbstractHistological transformation in Waldenström macroglobulinemia (WM) is an uncommon complication, with limited data, particularly regarding the impact of MYD88 L265P mutation on transformation. We examined risk factors and outcomes associated with transformation in WM, highlighting the role of MYD88 L265P mutation. Patients with WM seen at Mayo Clinic, Rochester, USA and University Hospital of Reims, France, between 01/01/1996 and December 31, 2017 were included; 50 (4.3%) of 1147 patients transformed to a high‐grade lymphoma, with median time‐to‐transformation of 4.5 (range 0‐21) years in the transformed cohort. The MYD88 L265P mutation status was known in 435/1147 (38%) patients (406 with non‐transformed WM and 29 patients in transformed cohort). On multivariate analysis, MYD88 WT status alone was an independent predictor of transformation (odds ratio, 7[95%CI: 2.1‐23]; P = .003). Additionally, the MYD88 WT status was independently associated with shorter time‐to‐transformation (HR 7.9 [95%CI: 2.3‐27; P = .001]), with a 5‐year transformation rate of 16% for MYD88 WT vs 2.8% with MYD88 L265P mutated patients. Patients with transformation demonstrated a significant increase in risk of death compared to patients who did not transform (HR 5.075; 95%CI: 3.8‐6.8; P < .001). In conclusion, the MYD88 WT status is an independent predictor of transformation and associated with a shorter time‐to‐transformation. Additionally, transformation conferred an inferior overall survival in patients with WM.

112 Background: CD47 delivers an anti-phagocytic (“do not eat”) signal by binding SIRPα on macrophages and is overexpressed on many cancers enabling immune surveillance evasion. TTI-621 is a decoy receptor that promotes phagocytosis of tumors by blocking CD47 and engaging activating FcR on macrophages. A first-in-human, phase 1a, open label, multicenter study (NCT02663518) evaluating safety and tolerability of weekly, intravenous infusions of TTI-621 was conducted. As of October 12, 2016, 18 subjects were treated with TTI-621 with doses of 0.05-0.3 mg/kg. Multiple pharmacodynamic and hematologic assessments were performed to characterize the effects of TTI-621 and better understand the mechanism of action. Methods: Serial blood draws were analyzed for CD47 receptor occupancy (RO), complete blood counts, cytokines, T cell repertoire changes and CD47, SIRPα and FcR sequences. CD47 expression, macrophage and T cell infiltration was assessed on biopsies by IHC. Results: Peripheral CD47 levels varied considerably between subjects and were inversely correlated with RO. A maximum of 80% RO was achieved on peripheral leukocytes. Circulating monocytes, neutrophils, and lymphocytes were transiently decreased at the end of the TTI-621 infusion and generally returned to baseline levels by 24 to 72 hours. Platelet counts decreased immediately after TTI-621 infusions, typically recovering to baseline levels prior to the subsequent treatment cycle. Hemoglobin levels did not meaningfully change during treatment. Cytokines associated with macrophage activation or phagocytosis, notably MIP-1α, MIP-1β, TNF-α and IP-10 were elevated in a dose dependent manner. Conclusions: Systemic administration of TTI-621 leads to CD47 blockade and dose dependent increases in cytokines associated with phagocytosis, temporally associated with reversible thrombocytopenia, suggesting enhanced macrophage mediated clearance of circulating platelets followed by a robust marrow regenerative response. Enrollment into multiple expansion cohorts addressing a wide range of hematopoietic cancers is ongoing. Clinical trial information: NCT02663518.

Introduction: The clinical presentation and frequency of organ involvement are quite distinct in patients with IgM amyloidosis compared to patients with non-IgM amyloidosis, with less heart involvement and more nerve, soft tissue and lung involvement in IgM patients. It has been observed that immunoglobulin light chain variable region (IGVL) gene and gene family of the plasma cell clone impact phenotypic manifestations in AL amyloidosis, particularly organ tropism. (Kourelis et al. Blood. 2017;129). Given the variability in clinical features amongst patients with IgM vs. non IgM AL amyloidosis, we hypothesized that IGVL gene usage would be different between these two groups. Methods: Patients with newly diagnosed IgM and non-IgM amyloidosis seen at our institution from 01/2006 to 12/2015 were identified. IGVL gene usage was assessed by liquid chromatography tandem mass spectrometry (LC/MS/MS) as previously described. (Vrana et al Blood 2009;Dasari et al J of Proteome Res; Kourelis et al. Blood. 2017). Mass spectrometry data for IGVL analysis was obtained from clinically available data. LC/MS/MS was performed on available archival specimens when such data was not available clinically. Results: Patients with newly diagnosed amyloidosis who had sufficient mass spectrometry data on fat aspirate or tissue biopsy for IGVL gene usage identification were included (IgM AL, N=44 and Non-IgM AL, N=391). Clinical Features: As expected, differences were noted in baseline characteristics of patients with IgM vs. non-IgM AL amyloidosis. Patients with IgM amyloidosis were older (68 vs. 64 years, p=0.04) and more likely to have kappa as the involved light chain (34% vs. 25%, p=0.2), though the difference did not reach statistical significance. IgM amyloidosis patients had lower difference in involved and uninvolved free light chains (dFLC) (15.5 vs. 25.8 mg/dL, p=0.01) and lower NTProBNP levels (median: 1987 vs. 2655 pg/mL, p=0.02) compared with non-IgM amyloid patients. Presence of t(11;14) was less common by FISH (30% vs. 48%, p=0.1), though the difference did not reach statistical significance. Patterns of organ involvement were different, with heart involvement being less frequent in IgM patients (64% vs. 76%), while peripheral nerve (30% vs. 18%, p=0.05), soft tissue (41% vs. 21%, p=0.005) and lung involvement (7% vs. 3%, p=0.1) were more common in patients with IgM vs. non-IgM AL amyloidosis. There was no difference in liver (9% vs. 15%), kidney (50% vs. 51%) GI (23% vs. 25%) or autonomic nervous system involvement (18% vs. 14%). IGVL Gene Usage: As shown in Figure 1, IGVL usage differed across the two groups. In the lambda group, LV2-08 (14% vs. 2%, p<0.001) and LV2-14 (36% vs. 10%, p<0.001) were more common in IgM amyloid patients, while LV1-44 (0% vs. 10%, p=0.02) and LV6-57 (2% vs. 18%, p=0.004) were less common in the IgM group. There was also a trend towards less frequent involvement of LV3-01 (2% vs. 12%, p=0.07) in IgM amyloid patients. In the kappa group, KV4-01 (11% vs. 4%, p=0.04) was more common in patients with IgM amyloidosis. Correlation Between IGVL Gene usage and Clinical Features: IGVL gene usage correlated with disease characteristics and differences in the clinical presentation of patients across the two groups. LV2-14 was more commonly seen in IgM amyloid patients (above). It has been previously associated with a higher frequency of peripheral nerve involvement (Kourelis et al. Blood 2017), which was more frequent in IgM group. LV2-14 is also associated with low dFLC levels, which were noted to be lower in the IgM AL cohort. LV1-44 has been associated with higher likelihood of cardiac involvement. LV1-44 was seen less frequently in the IgM amyloid patients, who also had lower rates of cardiac involvement. LV6-57 has been historically associated with higher rates of t(11;14). It was less common in IgM AL patients, who also had lower rates of t(11;14). Conclusions: IGVL gene usage differed significantly in patients with IgM vs. non-IgM amyloidosis, correlating with differences in disease characteristics and organ involvement. This is the first study to our knowledge to report IGVL gene usage differences in IgM vs. non-IgM AL amyloidosis. Differences in IGVL gene usage may explain the distinct clinical presentation seen in IgM amyloidosis, the biology of which has so far remained poorly understood. *SS and SD contributed equally Disclosures Dasari: The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Dispenzieri:Alnylam: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Akcea: Consultancy; Intellia: Consultancy. Murray:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding. Gertz:Prothena: Honoraria; Alnylam: Honoraria; Ionis: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding; Celgene: Honoraria.

Background: Neurolymphomatosis (NL) is a highly rare disorder defined as infiltration of peripheral nervous system by a lymphoproliferative neoplasm, both presented as the first manifestation of the malignancy (primary NL) or as a site of disease progression or relapse (secondary NL). Due to rarity of this disorder data on clinical features, best approach and outcome are limited. Furthermore diagnosis of this disease is often uncertain and based on radiological images only. Methods: We retrospectively reviewed clinical records of all histologically confirmed-NL, diagnosed and treated at the Division of Hematology of Mayo Clinic in Rochester, MN between January 2002 and December 2018. Clinical features and outcome were analyzed. Responses to therapy were assessed by post-treatment radiological changes and clinical symptoms improvement. Survival analysis such as progression free survival (PFS) and overall survival (OS) were estimated using Kaplan Meier curves with log-rank test. Comparison between subgroups was investigated using Fisher's exact test and Wilcoxon test for categorical and continuous variables, respectively. Results: Over a 16-year period 40 patients with biopsy-proven NL were included in study. Primary and secondary NL were 19 (48%) and 21 (52%) respectively, with a median age of 60.5 years (range 37-83) and male sex 24/40 (60%). The predominant histology was represented by B-cell lymphomas (39/40, 97%) with a vast majority large B-cell lymphoma (LBCL) 27/40 (67%) and only 1 case of T-cell lymphoma. The affected structures included brachial plexus (12/40, 35%), lumbosacral plexus (5/40, 12%), cauda equine and nerve roots (14/40, 35%), sciatic nerve (12/40, 30%), femoral nerve (4/40, 10%), cranial nerves (8/40, 20%), multiple nerves involved in 23/40 (57%). Four out of 40 cases had brain involvement and cerebrospinal fluid (CSF) was positive in 7/29 (24%). NL clinical manifestations included muscular weakness (33/4, 82%), sensory deficit (32/40, 80%), pain (28/40, 70%) and autonomic dysfunction (3/40, 7%). Magnetic resonance imaging (MRI) detected neural abnormalities in 35/36 cases (97%), CT imaging identified disease in 3/8 (37%) and FDG-PET scan was positive in 22/31 (71%); electromyography showed some grade of neuropathy in 28/29 (97%). Treatment included systemic chemotherapy in 38/40 (95%) cases, containing high dose methotrexate (HD-MTX) in 26/40 (65%) and rituximab in 20/40 (50%); 11/39 (28%) patients underwent consolidative autologous stem cell transplant (ASCT); 4/40 received consolidative radiotherapy (RT), 1/40 was treated with RT alone; intrathecal chemotherapy was infused in 1/40 cases; one patient with solely great auricular nerve NL involvement was cured with surgery only. Treatment efficacy evaluated by imaging and clinical improvement consisted with an overall response rate (ORR) of 73% (27/37) with a 24% (9/37) of complete remission (CR); No statistical difference in rate of response was observed by different systemic treatments. Of note, patients undergoing HDC-ASCT consolidation obtained 100% of ORR (n=10) versus 61.5% (n=16) achieved by others (P=0.03). With a median follow up of 45.1 months (range 0.5-186.7) a 36 months-OS of 77% (95% CI, 60-88) was observed for the whole cohort. A trend of longer survival rate for primary NL was observed, with a 36-month OS of 95% (95% CI, 72-99) vs. 55% (95% CI, 30-77) for secondary NL (p 0.134). A strong benefit in terms of outcome was observed for patients receiving rituximab-containing regimens with a 36 months-PFS of 72% (95% CI, 55-92) vs 28% (95% CI, 12-53) (P=0.001), and a 36 months-OS of 87% (CI 95%, 60-98) vs. 65% (95% CI , 41-84) (P=0.04) (figure 1); no survival difference was observed for patients treated with systemic therapy containing HD-MTX vs. others. ASCT consolidation was associated with a trend of improved survival with a 36 months-PFS of 69% (95% CI, 35-90) vs. 47% (95% CI, 29-66) for others (P=0.09). Conclusions: With the limit of a retrospective analysis, LBCL represent the predominant histologic subtype of NL; MRI and FGD-PET appeared to be the most accurate radiological tools to detect neural disease. Systemic treatments including rituximab should be preferred, HD-MTX seems to be not so effective while ASCT consolidation may be considered in selected patients. Due to the spare number of cases treated with RT its role cannot be clarified by our study. Disclosures Nowakowski: NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; 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.

Background: Standard first-line treatment for patients diagnosed with diffuse large B-cell lymphoma (DLBCL) is the R-CHOP regimen. Despite numerous efforts to improve on this regimen, in all comers and specifically in those with activated B-cell (ABC)-type DLBCL, results from large randomized studies have failed to show a significant clinical advantage above this standard. Recently, 2 large clinical trials in previously untreated DLBCL evaluated the combination of lenalidomide/R-CHOP (R2-CHOP) vs standard R-CHOP and demonstrated discordant results. We analyzed data from these trials to identify differences that may have impacted the disparate trial outcomes while identifying patient characteristics associated with benefit from the addition of lenalidomide across the trials. Methods: The 2 trials included in this evaluation are ROBUST, an international, randomized, double-blinded, placebo-controlled, phase III study of R2-CHOP vs placebo/R-CHOP, and the Intergroup ECOG-ACRIN 1412 (E1412) trial, a US-only, randomized, open-label, phase II study of R2-CHOP vs R-CHOP. Additional key study design differences included dosing, and subtype timing and inclusion (both studies used gene expression profiling [GEP] by NanoString). R-CHOP dosing differed only for prednisone, which was a flat 100 mg dose, d1-5 in ROBUST and 100 mg/m2, d1-5 in E1412. The lenalidomide dose and schedule varied between studies: 15 mg/d, d1-14/21 for ROBUST (210 mg/cycle) and 25 mg/d, d1-10/21 (250 mg/cycle) for E1412. ROBUST enrolled only patients prospectively identified with the ABC subtype, whereas E1412 enrolled all otherwise eligible patients and retrospectively evaluated for ABC-type with prespecified ABC-type accrual and power parameters. Both studies enrolled patients with IPI status ≥ 2, ECOG PS 0-2, and Ann Arbor stage II-IV (E1412 stage II with mass > 10 cm). The primary endpoint in both was progression-free survival (PFS; central review for ROBUST and investigator-assessed for E1412). Secondary endpoints included event-free survival (EFS; key for ROBUST), overall and complete response rates, overall survival (OS), and safety. Results: ROBUST enrolled 570 ABC patients and E1412 enrolled 280 GCB, ABC, and unclassified DLBCL patients. Patient profiles in both studies (ROBUST [ABC]/E1412 [all COO]) were similar in terms of median ages (65 y/66 y), male sex (58%/61%), and ECOG PS 1-2 (55%/63%). Patients in E1412 were more high risk: IPI 2 (42% ROBUST/34% E1412), IPI ≥ 3 (58%/66%), and Ann Arbor stage III/IV disease (87%/97%). Importantly, there was a notable difference in the time from patient diagnosis to treatment: median 31 days for ROBUST and 21 days (22% > 31 d) for E1412. Only 6% of patients in ROBUST were treated within 2 weeks of diagnosis vs 30% in E1412. At a median follow-up of ~2.5 y for both studies, E1412 met its primary endpoint of improvement in PFS with 34% reduction in the risk of PD/death (2-y PFS: 76% vs 70%) for all patients, but did not reach statistical significance in ABC-DLBCL patients for 2-y PFS (71% vs 61%) or 2-y OS (88% vs 76%). ROBUST showed no significant improvement in the primary PFS endpoint (2-y PFS: 67% vs 64%) or 2-y OS (79% vs 80%) in ABC patients. Subgroup analyses of PFS comparing R2-CHOP vs R-CHOP control within each study suggested that certain baseline factors favor the R2-CHOP arm, including: female sex, high IPI score (≥ 3), non-bulky disease (< 7 cm), and high Ann Arbor stage IV disease. Conclusion: While the ROBUST study design integrated state-of-the-art, real-time GEP to prospectively identify ABC-DLBCL patients with rapid lab turnaround time, cases of logistical delays in tissue submission for central analysis and staging procedures may have resulted in accrual of patients with lower-risk DLBCL and prolonged time from diagnosis to treatment. In contrast, E1412 retrospectively stratified patients by COO through GEP and was able to accrue higher-risk patients irrespective of COO within a shorter time from diagnosis to treatment, which among other differences (eg, smaller population size, study phase), could contribute to the improvement over R-CHOP control. Our comparative findings have significant implications for the design of future biomarker-driven trials and provide momentum for studies of novel combinations with R-CHOP in DLBCL. Further investigation into other factors, including dose intensity and their correlation with outcomes, will be presented. Disclosures Nowakowski: Celgene: Consultancy, Research Funding; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; Curis: Research Funding; Bayer: Consultancy, Research Funding. Chiappella:Servier: Other: advisory board, Speakers Bureau; Roche: Speakers Bureau; Teva: Speakers Bureau; Celgene: Other: advisory board, Speakers Bureau; Janssen: Other: advisory board, Speakers Bureau. Hong:Dana Farber Cancer Institute: Employment; Merck: Consultancy. Scott:Roche/Genentech: Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Amengual:Appia Pharmaceuticals: Research Funding; Epizyme: Speakers Bureau. Leonard:BeiGene: Consultancy; Miltenyi: Consultancy; Sandoz: Consultancy; Gilead: Consultancy; Celgene: Consultancy; ADC Therapeutics: Consultancy; MorphoSys: Consultancy; ADC Therapeutics: Consultancy; Epizyme, Inc: Consultancy; Miltenyi: Consultancy; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy; Karyopharm Therapeutics: Consultancy; Akcea Therapeutics: Consultancy; Merck: Consultancy; Nordic Nanovector: Consultancy; Akcea Therapeutics: Consultancy; Bayer Corporation: Consultancy; Sandoz: Consultancy; MorphoSys: Consultancy; Gilead: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy; Nordic Nanovector: Consultancy; Sutro Biopharma: Consultancy; Merck: Consultancy. Friedberg:Bayer: Honoraria, Other: Data & Safety Monitoring Committee; Acerta: Other: Data & Safety Monitoring Committee. Kostakoglu:F. Hoffman-La Roche: Consultancy; Genentech: Consultancy. Jurczak:Morphosys: Research Funding; Bayer: Research Funding; Roche: Research Funding; Incyte: Research Funding; Gilead: Research Funding; Celgene Corporation: Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novo Nordisk: Research Funding; Servier: Research Funding; Takeda: Research Funding; TG Therapeutics: Research Funding; Celtrion: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees, Research Funding. Yamamoto:Bristol-Myers Squibb: Consultancy, Honoraria; Bayer: Research Funding; Celgene Corporation: Consultancy, Honoraria, Research Funding; Mundipharma: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Meiji Seika Pharma: Consultancy, Honoraria; ARIAD: Research Funding; MSD: Consultancy, Honoraria; Gilead Sciences: Research Funding; Ono: Consultancy, Honoraria, Research Funding; SymBio: Research Funding; HUYA/IQVIA Services Japan: Consultancy, Honoraria; AbbVie: Consultancy, Research Funding; Chugai: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria; Sumitomo Dainippon: Honoraria; Incyte: Research Funding; Janssen: Honoraria; Kyowa Kirin: Honoraria; Novartis: Honoraria, Research Funding; Otsuka: Honoraria; Sanofi: Honoraria; Solasia Pharma: Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Czuczman:Celgene Corporation: Employment, Equity Ownership. Russo:Celgene Corporation: Employment, Equity Ownership. Hudak:Celgene Corporation: Employment, Equity Ownership; Novartis: Employment, Equity Ownership. Zhang:Celgene Corporation: Employment, Equity Ownership. Wade:Celgene: Employment, Equity Ownership. Kahl:ADC Therapeutics: Consultancy, Research Funding; BeiGene: Consultancy; TG Therapeutics: Consultancy; Seattle Genetics: Consultancy. Vitolo:Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. OffLabel Disclosure: Yes, these trials discuss off-label clinical trial investigation of lenalidomide plus R-CHOP in patients with newly diagnosed diffuse large B-cell lymphoma.

Background: Myelodysplastic syndrome (MDS)/myeloproliferative neoplasm (MPN) with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T) was formally included as a unique WHO-defined entity in the 2016, iteration of the classification of hematological neoplasms (under MDS/MPN overlap syndromes). Patients with MDS/MPN-RS-T have features of MDS-RS-single lineage dysplasia (SLD), persistent thrombocytosis (platelet count ≥450x109/L), with proliferation of large atypical megakaryocytes. Anemia, including red blood cell transfusion dependency (RBC-TD) is a major problem. While extensive studies have documented erythroid response rates (ERR) to erythropoiesis stimulating agents (ESA) in MDS and MDS-RS-SLD, the data in MDS/MPN-RS-T is less clear. We carried out this study to asses ERR in ESA treated patients with MDS/MPN-RS-T. Methods: After approval by the IRB, patients with 2016, WHO-defined MDS/MPN-RS-T were included in the study. The bone marrow (BM) morphology, cytogenetics and BM RS% were retrospectively reviewed. All study patients underwent next generation sequencing for 29 myeloid-relevant genes, obtained on BM mononuclear cells, at diagnosis, or at first referral, by previously described methods (Patnaik et al., BCJ 2016). Treatment details, including the type of ESA used, dose administered, side effects and reason for discontinuation were retrospectively abstracted. Erythroid responses were assessed using the 2006, international working group (IWG) MDS and the 2015, IWG MDS/MPN response criteria. Results: Forty seven patients with MDS/MPN-RS-T were identified, of which 37 (79%) patients received ESA treatment at any time point during their disease course; median age 73 years (range, 52-93), 46% male.The hemoglobin at diagnosis (HB) and baseline erythropoietin (EPO) levels were 9.1 gm/dL (range, 6.6-12.1) and 39 IU/L (range, 8-500), respectively. Ten (29%) patients were RBC-TD at baseline. None of the 37, ESA-treated patients were on concomitant cyto-reductive therapy for thrombocytosis. Twenty (54%) patients were treated with erythropoietin-a, 13 (35%) with darbepoetin, and 4 (11%) with both sequentially. Median doses were 40,000 IU weekly (range, 20,000-80,000) for erythropoietin-a and 200 mcg every 2 weeks (range, 100-500), for darbepoetin. Median treatment duration was 14 months (range, 1-173) and causes for discontinuation included; ESA failure/loss of response in 20 (54%), sustained HB rise in 1 (3%) and other causes, including adverse events in 4 (11%) patients. With regards to safety, the following events were considered potentially ESA related; treatment emergent hypertension in 2 (5%), venous thromboembolism, ischemic stroke and splenic infarction in 1 (3%) patient each, respectively. All patients with thrombotic/ischemic events had been on low dose aspirin prophylaxis. Erythroid responses by the IWG MDS and MDS/MPN response criteria were assessable in 35 (95%) patients: with 16 (46%) meeting criteria for an erythroid response, by both assessment systems. The median duration of ER was 20 months (range, 2-172). In comparison to ESA non-responders, those that responded were more likely to have baseline EPO levels ≤44 IU/L (ROC analysis; median, 28 vs 112 IU/L; p=0.0080), while there was a trend for inferior responses associated with RBC-TD (p=0.0857). Age, gender, baseline white blood cell and platelet counts, type of ESA used, BM RS %, JAK2V617F, SF3B1, DNMT3A, TET2 and ASXL1 mutational status did not impact ESA response (Table 1). On a univariate survival analysis (OS), survival was not significantly different between ESA responders vs non-responder (median OS, 76 vs 45 months; p=0.2929). After ESA failure, 7 (19%) patients received hypomethylating agents (HMA), while 5 (14%) received lenalidomide. There were no erythroid responses to HMA, while 1 of 3 (33%) assessable lenalidomide treated patients achieved a morphological complete response. Conclusion: Erythropoiesis stimulating agents are effective first line therapies for the management of anemia in patients with MDS/MPN-RS-T, with 46% achieving an erythroid response (median duration of response of 20 months). Low baseline endogenous EPO level (<44 IU/L) was the best predictor of response, with a trend towards an inferior response in the presence of RBC-TD. In the context of clonal thrombocytosis, potentially related thrombotic/ischemic events were documented in 8% of patients. Disclosures Al-Kali: Astex Pharmaceuticals, Inc.: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Introduction: Front-line immunochemotherapy (IC) with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is expected to cure 60-70% of newly diagnosed DLBCL. Up to one third of newly diagnosed DLBCL patients will have relapsed or refractory (r/r) disease.1 Current standard of care for these patients is salvage chemotherapy and, if chemosensitive, to be followed by high dose chemotherapy with hematopoietic cell rescue (autoHCT).2,3 Event-free survival at 24 months (EFS24) after frontline IC is associated with excellent long-term outcomes with overall survival (OS) similar to that of age- and sex-matched controls.4 In comparison, those achieving EFS24 following autoHCT for relapsed or refractory disease may have increased risk for late-mortality compared to the general population with advanced age and intensive salvage therapy contributing to the risk of late complications.5 We sought to better characterize EFS24 after autoHCT to determine the utility of this end-point for informed clinical decisions, patient management, and future clinical trials. Methods: Patients were prospectively enrolled onto the Molecular Epidemiology Resource (MER) of the University of Iowa/ Mayo Clinic Specialized Program of Research Excellence (SPORE). Patients were followed for relapse, retreatment, and death; all events were validated by medical record review. For this analysis patients were included if they were consented within 9 months of initial diagnosis of DLBCL between 2002-2012, had received anthracycline-based IC (R-CHOP, or similar), and eventually had undergone autoHCT for r/r DLBCL. Patients with primary central nervous system (CNS) lymphoma or post-transplant lymphoproliferative disorders (PTLD) were excluded. Overall survival (OS) was defined as time from autoHCT until death due to any cause. Event-free survival (EFS) was defined as time from autoHCT until progression, relapse, retreatment, or death due to any cause. OS from achieving EFS24 after autoHCT was compared to age- and sex-matched general US population. Results: 108 patients underwent autoHCT for relapsed DLBCL between 2002 and 2017. Median age at autoHCT of the patients was 60 years (range 20-78) and 72 (67%) were male. The most common transplant conditioning regimen was BEAM (82%). At a median follow-up after autoHCT of 85 months (range 1-171), 72 patients (67%) had an event and 64 patients (59%) had died. Kaplan-Meier estimates for EFS and OS at 24 months from the time of autoHCT were 49% (95% CI: 40-59) and 61% (95% CI: 52-71), respectively. 52 patients had a progression within 24 months of autoHCT; OS from progression was poor (median OS=2.8 months, 95% CI: 1.8-6.0; 5 year OS = 9%, 95% CI: 2-22). 48 patients achieved EFS24 after autoHCT; median OS from achieving EFS24 was 136 months (95% CI: 92-NE) and 5 year OS was 79% (95% CI: 68-93). This was inferior to the background population (Figure 1, SMR=3.64, 95% CI: 2.11-6.27, p<0.0001). Eight patients had a progression after achieving EFS24 from autoHCT. OS from progression in these 8 patients (median OS=27.3 months, 95% CI: 14.4-NE; 5 year OS = 16%, 95% CI: 3-93) was improved compared to progression within 24 months of autoHCT (p=0.072, figure B). Cause of death (COD) in EFS24 achievers was progression of lymphoma (n=6), infection (n=1), secondary malignancy related to therapy (n=3), heart disease (n=1), and unknown (n=1). Conclusions: Patients achieving EFS24 after salvage chemotherapy and autoHCT have a favorable long-term prognosis; however, overall survival remained inferior to the general population. Most common COD after achieving EFS24 was progression of lymphoma. In spite of this, EFS24 remains a valuable end-point for informed clinical decisions, patient management, and future clinical trials. Figure 1 Disclosures Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Nanostring: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding. Cerhan:Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding.

Introduction: Waldenström macroglobulinemia (WM) is characterized by circulating monoclonal IgM and bone marrow infiltration with lymphoplasmacytic lymphoma (LPL) cells. Presently, there is limited data to guide prognosis or treatment options of WM based on the proportion of lymphocytes or plasma cells in the LPL population on the pathology. In this study, we aim to look at differing clinical features and outcomes of patients with WM based on the plasma cell (PC) percentage in the diagnostic bone marrow biopsy. Methods Patients with WM seen at Mayo Clinic, Rochester, MN between January 2001 and December 2017, with a bone marrow biopsy and a corresponding serum free light chain (FLC) examination at diagnosis of WM were included. The percentage of lymphocytes and PCs in the marrow biopsy was determined based on morphology ± immunohistochemistry. On immunohistochemistry, CD138 and/or MUM-1 positivity was used to quantify PCs, whereas CD20 and/or PAX5 were used to quantify lymphocytes. Patients with ≥10% PC component in the lymphoplasmacytic (LPL) cells on bone marrow biopsy were considered to have WM with excess plasma cells (WMEPC), while those with &lt;10% PCs were considered to have lymphocytic WM (LWM). Continuous variables were compared using Wilcoxon test and categorical variables were compared using Chi square test or Fisher's exact test. Time-to-next therapy (TTNT) was defined as the period from initiation of first line therapy to start of second line therapy or death due to any cause before second line therapy. Time-to-event analyses were conducted using Kaplan Meier method. Results: Of 228 evaluable patients, 147 (64%) had ≥ 10% PCs in the initial marrow biopsy. The median follow-up was 3.4 years (95% CI: 2.3-4.3 years) for LWM and 4.3 years (95% CI: 3.4-4.8 years) for WMEPC (p=0.33). The baseline characteristics of WMEPC versus LWM are depicted in Table 1. Patients with WMEPC had lower bone marrow involvement by LPL (30%) compared to LWM (60%; p&lt;0.001) at diagnosis, but the rate of symptomatic hyperviscosity was higher in WMEPC during the disease course (Table 1). The TTNT was shorter for WMEPC [2.6 years (95% CI: 1.8-4.5 years)] compared to LWM [4.5 years (95% CI 3.2-8.2)], although it did not reach statistical significance (p=0.09, Figure 1). There was a trend towards shorter OS for WMEPC [Not reached (95% CI 7.2- NR)] compared to LWM [10.7 years (95% CI 7.3 -12.1 years); p=0.28], Figure 2. Of the 228 patients, 79% (n=182) had data available for systemic therapy. The rate of PR or better with frontline therapy was higher in rates in LWM compared to WMEPC (61 % vs 42% p=0.02, Table 1). Among WMEPC cohort, patients receiving either a proteasome inhibitor (PI)-based or an immunomodulatory (IMiD)-based combination as frontline therapy (n=16) had higher rates of partial response or better (68%) compared to non-PI/non-IMiD based therapy (n=114), p=0.04. Conclusion: WM with excess plasma cells at diagnosis is associated with a trend towards shorter TTNT and OS compared to WM with &lt;10% plasma cells in the lymphoplasmacytic population at diagnosis. Our preliminary data shows higher rates of partial response or better with the use of PI/IMiD based therapy, but the small cohort size limits the strength of this finding which needs to be validated externally. Disclosures Ansell: Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Affimed: Research Funding. Gertz:Spectrum: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Prothena: Honoraria; Alnylam: Honoraria; Ionis: Honoraria. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Nowakowski:Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Dispenzieri:Alnylam: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy. Lacy:Celgene: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Kapoor:Janssen: Research Funding; Cellectar: Consultancy; Glaxo Smith Kline: Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria.

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.