Tam, Wayne

Introduction: In recent years, increasing evidence suggests an important role of tumor-infiltrating B lymphocytes (TIL-Bs) in cancer immunity. In various types of solid tumors, high density of TIL-Bs and presence of mature tertiary lymphoid structures consistently correlate with better prognosis and response to immune checkpoint blockade therapies. Diffuse large B-cell lymphoma (DLBCL) is a type of aggressive lymphoma arising from mature B cells. TIL-Bs have been identified in DLBCL based on single-cell gene-expression data in several previous studies, but their prognostic significance in DLBCL is unknown. In this study, we determined the clinical significance of TIL-B abundance and investigated the potential underlying mechanisms. Patients and Methods: This abstract includes a discovery study in which we distinguished TIL-Bs from malignant B-cells by immunoglobulin gene (IG) clonotype analysis and a validation study using flow cytometry. In the discovery study, a molecularly well-characterized DLBCL cohort assembled by the International DLBCL R-CHOP Consortium Program was analyzed. DNA samples from DLBCL patients were sequenced by high-throughput ultra-deep sequencing assays using multiplexed forward and reverse primers. Based on the IG heavy chain (IGH) sequencing results, malignant B-cell and TIL-B VDJ clonotypes were identified for 138 patients, and the frequencies and numbers of TIL-B clonotypes in individual sequence repertoires were calculated. In 79 DLBCL cases, a DJ-only sequence was predominant and no productive VDJ sequences met the criteria for diagnostic sequences. Total frequencies of productive VDJ sequences in the sequence repertoires were then used to access high and low TIL-B frequencies. TIL-B frequencies were also evaluated by IG light chain clonotypes for these 217 patients and additional 52 patients. The TIL-B frequencies were correlated with patient survival, gene-expression profiling (GEP) data GSE31312, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex immunohistochemistry (mIHC). To validate the prognostic significance of TIL-B frequencies, we assembled a validation cohort of 94 DLBCL patients treated at Duke University Medical Center. TIL-Bs in tissues were quantified by flow cytometry immunophenotyping. Ratios of TIL-Bs to abnormal B cells were assessed for prognostic effects. Results: First, we found thathigh frequencies of TIL-Bs and clonotypic diversity were associated with significantly favorable prognostic effects in 138 DLBCL patients with their malignant B-cell IGH-VDJ clonotypes identified (Figure A). The prognostic effects of TIL-Bs outweighed those of the germinal center B-cell-like/activated B-cell-like classification (Figure B). Second, patients with high frequencies of TIL-Bs compared with those without had significant upregulation of immune response genes by GEP (Figure C), higher CD4 T cell infiltration quantified by fluorescent mIHC (Figure D), and enrichment of EcoTyper-defined specific cell states, including significantly increased frequencies of B cell state S2 (pre-memory), CD4 T cell state S3 (naïve), follicular helper T cell state S3, and endothelial cell state S3, whereas lower frequencies of B cell state S5 (plasmablast) and follicular helper T cell state S1. Third, high TIL-B abundance in 79 ‘DJ-only’ clonotype cases and additional 52 cases assessed by light chain clonotype analysis showed similar favorable prognostic effects and associations with upregulated immune gene expression and CD4 T cell infiltration. Fourth, the identified GEP signatures, prominent with genes involved in T-dependent B cell activation and T cell activation and differentiation, showed significant prognostic effects in two GEO datasets. Fifth, TIL-B abundance showed significant prognostic effects in DLBCL cases infiltrated with T-cells in both the discovery study (Figure E) and validation study (Figure F, flow cytometry cohort). Conclusions: TIL-B frequencies and clonotypic diversity have remarkable prognostic and biological effects in DLBCL, which has significant implications for developing novel therapeutic strategies. Our study identified a new prognostic biomarker in DLBCL and an important player in anti-lymphoma immune responses, providing a new point of view to analyze the tumor biology in aggressive B-cell lymphoma and precisely identify prognostic determinants.

Background: DNA mismatch repair (MMR) deficiency (dMMR), which leads to genomic and microsatellite instability, is a biomarker that predicts response to immunotherapies and has variable prognostic effects for chemotherapies in solid tumors. The dMMR can be detected using gene sequencing or immunohistochemistry for four essential MMR proteins: MSH6, MSH2, MLH1, and PMS2. Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma. Previous studies have suggested the role of MMR gene variants in DLBCL lymphomagenesis, yet the prognostic role of dMMR in DLBCL has not been well studied. Methods: We performed targeted next-generation sequencing and immunohistochemistry for MSH6, MSH2, MLH1, and PMS2 in a large cohort of DLBCL patients treated with standard chemoimmunotherapy. Gene expression profiling (GEP) was performed using the Affymetrix GeneChip Human Genome HG-U133 Plus 2.0 microarray (data in GSE31312). Fluorescent multiplex immunohistochemistry (mIHC) was performed using MultiOmyx multiplexing immunofluorescence staining protocols and antibodies against 13 immune markers. We investigated the frequencies of dMRR and MMR protein expression and correlated the mutation status and expression levels with patient survival and DLBCL biology, including the number of mutated genes, GEP data, previously analyzed DLBCL biomarkers, and immune cell immunophenotypes. Results: MMR gene mutations and loss of MMR protein expression were infrequent in DLBCL (Figure A) and did not show a significant prognostic impact. MMR proteins were commonly expressed in DLBCL samples and the germinal centers of reactive tonsil controls (Figure B), with higher mean and median percentages of tumor cells expressing MSH6 and MLH1 proteins than in the solid tumor samples used for comparison. High expression of MMR proteins was associated with Ki-67, MYC, and p53 overexpression as determined by immunohistochemistry. GEP analysis identified significantly upregulated genes involved in the mitotic cell cycle and DNA metabolism and prominent downregulated immune gene signatures in DLBCL with high MMR protein expression. Fluorescent mIHC confirmed the associations with decreased T cell abundance in MSH6/MSH2/MLH1/PMS2 highly expressing DLBCL (Figure C) independent of p53 and MYC expression status, whereas MSH6/ MLH1 mutations were associated with increased T cell frequencies. High versus low expression of MSH6, MLH1, and PMS2 showed significant unfavorable prognostic effects in DLBCL when the optimal cutoffs were used for high expression. However, when the median percentages were used as cutoffs, the prognostic effects were not significant; nonetheless, MSH6 and PMS2 high expression showed significant adverse prognostic effects in the MYC¯ DLBCL subset. Interestingly, when we used Ki-67, MYC + or BCL2 + percentages in DLBCL assessed by immunohistochemistry to subtract MMR protein percentages and then correlated the differences to survival, we found significant favorable prognostic impact by higher percentage expression differences between MMR proteins and BCL2, or by intermediately higher differences between MMR proteins and MYC. For MSH2/MLH1/PMS2, the higher percentages compared with MYC/BCL2 showed no significant correlations with T cell infiltration levels, whereas the higher differences between MSH6 and MYC/BCL2 were associated with significantly lower T cell frequencies (Figure D). Conclusions: This study revealed that high expression of MMR proteins is a common feature of DLBCL associated with lower tumor-infiltrating T cells, MYC and p53 overexpression, and context-dependent prognostic effects. In contrast, dMMR and loss of MMR proteins are infrequent and have no significant prognostic effects in DLBCL treated with standard chemoimmunotherapy. These results may have implications for understanding DLBCL biology and the low efficacy of PD-1 blockade immunotherapy in DLBCL.

Abstract Purpose: Tumor-infiltrating B lymphocytes (TIL-B) have demonstrated prognostic and predictive significance in solid cancers. In this study, we aimed to distinguish TIL-Bs from malignant B-cells in diffuse large B-cell lymphoma (DLBCL) and determine the clinical and biological significance. Experimental Design: A total of 269 patients with de novo DLBCL from the International DLBCL R-CHOP Consortium Program were studied. Ultra-deep sequencing of the immunoglobulin genes was performed to determine B-cell clonotypes. The frequencies and numbers of TIL-B clonotypes in individual repertoires were correlated with patient survival, gene expression profiling (GEP) data, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex IHC at single-cell resolution. Results: TIL-B abundance, evaluated by frequencies of normal B-cell clonotypes in the immunoglobulin repertoires, remarkably showed positive associations with significantly better survival of patients in our sequenced cohorts. DLBCLs with high versus low TIL-B abundance displayed distinct GEP signatures, increased pre-memory B-cell state and naïve CD4 T-cell state fractions, and higher CD4+ T-cell infiltration. TIL-B frequency, as a new biomarker in DLBCL, outperformed the germinal center (GC) B-cell–like/activated B-cell–like classification and TIL-T frequency. The identified TIL-B–high GEP signature, including genes upregulated during T-dependent B-cell activation and those highly expressed in normal GC B cells and T cells, showed significant favorable prognostic effects in several external validation cohorts. Conclusions: TIL-B frequency is a significant prognostic factor in DLBCL and plays a crucial role in antitumor immune responses. This study provides novel insights into the prognostic determinants in DLBCL and TIL-B functions with important therapeutic implications.

Abstract Introduction: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology. However, these biological subgroups overlap clinically. While R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard of care for treating patients with DLBCL, predicting which patients will not benefit from such therapy is important so that alternative therapy or clinical trials can be considered. Most of the studies stratifying patients select biomarkers first, then explore how these biomarkers can stratify patients based on outcome. We explored the potential of using machine learning to first group patients with DLBCL based on survival, then isolating the biomarkers necessary for predicting these survival subgroups. Methods: RNA was extracted from tissue paraffin blocks from 379 R-CHOP treated patients with de novo DLBCL, and from 247 patients with extranodal DLBCL. A targeted hybrid capture RNA panel of 1408 genes was used for next generation sequencing (NGS). Sequencing was performed using an Illumina NextSeq 550 System platform. Ten million reads per sample in a single run were required, and the read length was 2 × 150 bp. An expression profile was generated from the sequencing coverage profile of each individual sample using Cufflinks. A machine learning system was developed to classify patients into four groups based on their overall survival. This machine learning approach based on Naïve Bayesian algorithm was also used to discover the relevant subset of genes with which to classify patients into each of the four survival groups. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict the survival group for each patient. Results: Using machine learning, patients were first divided into two groups: short survival (S) and long survival (L). To refine this model, we used the same approach and divided the patients in each group into two subgroups, generating four groups: long survival in the long group (LL), short survival in the long group (LS), long survival in the short group (SL), and short survival in the short group (SS). The hazard ratio for this model was 0.174 (confidence interval: 0.120-0.251), and P-value <0.0001. After defining these four groups, a machine learning algorithm was used to discover the biomarkers from the expression data of the 1408 genes from NGS data. To reduce the effects of noise and avoid overfitting, we employed a 12-step cross validation to obtain a robust measure. For an individual gene, a generalized Naïve Bayesian classifier was constructed on the training of one of the 12 subsets and tested on the other 11 testing subsets. This allowed us to limit the prediction process to 60 genes for each separation step. Using the selected biomarkers, we classified the patients in the original set (379 patients) into LL, LS, SL, and SS groups and then evaluated the survival pattern of these groups. As shown in Fig. 1A, the selected biomarkers predicted survival as expected in the overall survival groups prior to biomarker selection. For additional validation of the system, we used the selected biomarkers to classify a completely new set of 247 samples of patients with extranodal DLBCL. As shown in Fig. 1B, these selected biomarkers successfully predicted the overall survival in this group of patients with an HR of 0.530 (confidence interval: 0.234-1.197, P=0.005). This classification correlated with cell of origin classification, TP53 mutation status, MYC expression, and IRF4 expression. However, in a multivariate analysis, only TP53 mutation was independent in predicting prognosis (P=0.005) and age (below or over 60) (P=0.01) along with the survival grouping (P<0.000001). Conclusions: Using a novel machine learning approach with the expression levels of 180 genes, we developed a model that can reliably stratify patients with DLBCL treated with R-CHOP into four survival subgroups. This model can be used to identify patients who may not respond well to R-CHOP to be considered for alternative therapy and clinical trials. Figure 1 Figure 1. Disclosures Hsi: AbbVie Inc, Eli Lilly: Research Funding. Ferreri: Ospedale San Raffaele srl: Patents & Royalties; BMS: Research Funding; Pfizer: Research Funding; Beigene: Research Funding; Hutchison Medipharma: Research Funding; Amgen: Research Funding; Genmab: Research Funding; ADC Therapeutics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; PletixaPharm: Membership on an entity's Board of Directors or advisory committees; x Incyte: Membership on an entity's Board of Directors or advisory committees; Adienne: Membership on an entity's Board of Directors or advisory committees. Piris: Millenium/Takeda, EUSA, Jansen, NanoString, Kyowa Kirin, Gilead and Celgene.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Winter: BMS: Other: Husband: Data and Safety Monitoring Board; Actinium Pharma: Consultancy; Janssen: Other: Husband: Consultancy; Agios: Other: Husband: Consultancy; Gilead: Other: Husband: Consultancy; Epizyme: Other: Husband: Data and Safety Monitoring Board; Ariad/Takeda: Other: Husband: Data and Safety Monitoring Board; Merck: Consultancy, Honoraria, Research Funding; Novartis: Other: Husband: Consultancy, Data and Safety Monitoring Board; Karyopharm (Curio Science): Honoraria.

Abstract Diffuse large B-cell lymphoma (DLBCL) is the major type of aggressive B-cell lymphoma. High-grade B-cell lymphoma (HGBCL) with MYC/BCL2 double-hit (DH) represents a distinct entity with dismal prognosis after standard immunochemotherapy in the current WHO lymphoma classification. However, whether TP53 mutation synergizes with MYC abnormalities (MYC rearrangement and/or Myc protein overexpression) contributing to HGBCL-like biology and prognosis is not well investigated. In this study, patients with DLBCL with MYC/TP53 abnormalities demonstrated poor clinical outcome, high-grade morphology, and distinct gene expression signatures. To identify more effective therapies for this distinctive DLBCL subset, novel MYC/TP53/BCL-2–targeted agents were investigated in DLBCL cells with MYC/TP53 dual alterations or HGBCL-MYC/BCL2-DH. A BET inhibitor INCB057643 effectively inhibited cell viability and induced apoptosis in DLBCL/HGBCL cells regardless of MYC/BCL2/TP53 status. Combining INCB057643 with a MDM2-p53 inhibitor DS3032b significantly enhanced the cytotoxic effects in HGBCL-DH without TP53 mutation, while combining with the BCL-2 inhibitor venetoclax displayed potent therapeutic synergy in DLBCL/HGBCL cells with and without concurrent TP53 mutation. Reverse-phase protein arrays revealed the synergistic molecular actions by INCB057643, DS3032b and venetoclax to induce cell-cycle arrest and apoptosis and to inhibit AKT/MEK/ERK/mTOR pathways, as well as potential drug resistance mechanisms mediated by upregulation of Mcl-1 and RAS/RAF/MEK/ERK pathways. In summary, these findings support subclassification of DLBCL/HGBCL with dual MYC/TP53 alterations, which demonstrates distinct pathobiologic features and dismal survival with standard therapy, therefore requiring additional targeted therapies. Implications: The clinical and pharmacologic studies suggest recognizing DLBCL with concomitant TP53 mutation and MYC abnormalities as a distinctive entity necessary for precision oncology practice. Visual Overview: http://mcr.aacrjournals.org/content/molcanres/19/2/249/F1.large.jpg.

Abstract Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routine practice by the World Health Organization classification for biological and therapeutic insights. Genetic subtypes uncovered recently are based on distinct genetic alterations in DLBCL, which are different from the COO subtypes defined by gene expression signatures of normal B cells retained in DLBCL. We hypothesize that classifiers incorporating both genome-wide gene-expression and pathogenetic variables can improve the therapeutic significance of DLBCL classification. To develop such refined classifiers, we performed targeted RNA sequencing (RNA-Seq) with a commercially available next-generation sequencing (NGS) platform in a large cohort of 418 DLBCLs. Genetic and transcriptional data obtained by RNA-Seq in a single run were explored by state-of-the-art artificial intelligence (AI) to develop a NGS-COO classifier for COO assignment and NGS survival models for clinical outcome prediction. The NGS-COO model built through applying AI in the training set was robust, showing high concordance with COO classification by either Affymetrix GeneChip microarray or the NanoString Lymph2Cx assay in 2 validation sets. Although the NGS-COO model was not trained for clinical outcome, the activated B-cell–like compared with the germinal-center B-cell–like subtype had significantly poorer survival. The NGS survival models stratified 30% high-risk patients in the validation set with poor survival as in the training set. These results demonstrate that targeted RNA-Seq coupled with AI deep learning techniques provides reproducible, efficient, and affordable assays for clinical application. The clinical grade assays and NGS models integrating both genetic and transcriptional factors developed in this study may eventually support precision medicine in DLBCL.

Abstract Background: Pev (TAK-924/MLN4924), a novel investigational NAE inhibitor, enhances the anti-leukemic effects of aza in AML cell lines and murine xenografts (Smith et al, Blood 2011). Single-agent pev activity was confirmed in relapsed/refractory AML pts (Swords et al, Br J Haematol 2015). This open-label, multi-center, dose-escalation study (NCT01814826) investigated pev + aza in treatment-naïve older AML pts. Dose-limiting toxicities (DLTs)includedG2 hyperbilirubinemia and G4 AST elevation (n=1 each) at pev 30 mg/m2. The maximum tolerated dose (MTD) for the combination was pev 20 mg/m2 + aza 75 mg/m2 (Swords et al, ASH 2014).We present updated safety/efficacy results for the MTD cohort (fully enrolled). Methods: Primary objectives included safety and tolerability assessments of pev + aza in addition to defining the MTD. Secondary objectives included pharmacokinetics (PK) and disease response assessments. Treatment-naïve pts ≥60 yrs unlikely to benefit from standard induction therapy (defined by ≥1 of: antecedent hematologic disease; known adverse cytogenetic risk; ECOG PS 2; ≥75 yrs), received pev 20 or 30 mg/m2 IV on d 1, 3 and 5, + fixed-dose aza (75 mg/m2 IV/SC) on d 1-5, 8 and 9, every 28 d until disease progression or unacceptable toxicity. Adverse events (AEs) were assessed per NCI-CTCAE v4.03; response per IWG criteria for AML. Bone marrow samples were collected at screening to assess cytogenetic risk (CALGB) and mutation profile; serial samples for PK analysis were drawn in cycle 1. Results: Demographics:As of May 17 2016, 61 pts (median age 75 yrs [range 61-89]; 54% male; 77% ECOG PS 0/1, 23% ECOG PS 2; 57% de novo, 43% secondary AML; median marrow blasts 36% [range 5-92]) had received pev 20 mg/m2, of whom 48% had intermediate-, 30% adverse-, and 3% favorable-risk cytogenetics. Safety/PK: Pts received a median of 4 cycles (range 1-33), and 23/61 pts (38%) received ≥6 cycles of pev + aza. The most common AEs were constipation (46%), nausea (44%), fatigue (43%), and anemia (39%). Fifty pts (82%) experienced ≥G3 AEs; the most frequent (≥15%) were anemia, febrile neutropenia (each 28%), thrombocytopenia (21%), neutropenia (18%), and pneumonia (15%). ≥G3 AST/ALT elevations were reported in 5% of pts. Forty-one pts (67%) experienced serious AEs; the most frequent (≥10%) were febrile neutropenia, neutropenia (each 25%), and pneumonia (11%). Two pts discontinued due to pev related toxicity (G3 febrile neutropenia). There were 11 on-study deaths unrelated to study therapy. In the MTD expansion phase (n=55), 2 pts experienced DLTs of transient G3/4 transaminase elevations, and were successfully re-challenged following dose reduction to remain on study. Pev PK was not altered by the addition of aza. Responses: Overall response rate (ORR) in 52 response-evaluable pts was 60% (18CR, 5CRi, 8PR; Figure 1), with a median duration of remission of 8.3 mos (95% CI: 5.75, 12.06); 19/31 (61%) responses occurred within the first 2 cycles.Of the 23 pts with CR/CRi, 14 had responses lasting ≥4 cycles, 2 went on to have allogeneic stem cell transplant, 9 had intermediate-, 7 adverse-, and 1 favorable-risk cytogenetics. ORR was: 64% (14/22; 7CR, 3CRi, 4PR) vs 57% (17/30; 11CR, 2CRi, 4PR) for pts with low- (<30%) vs high- (≥30%) marrow blasts; 58% (18/31; 11CR, 3CRi, 4PR) vs 62% (13/21; 7CR, 2CRi, 4PR) for de novo vs secondary AML pts; 61% (14/23; 8CR, 1CRi, 5PR) vs 50% (8/16; 5CR, 2CRi, 1PR) for intermediate- vs adverse-risk cytogenetic pts; 83% (19/23; 14CR, 2CRi, 3PR) vs 41% (12/29; 5CR, 3CRi, 4PR) for pts who received ≥6 cycles vs <6 cycles of aza, respectively. Responses were seen in pts with typically refractory disease; 7/11 pts with TP53 mutations achieved either a CR/CRi (n=3) or PR (n=4); 4 stayed on study for >10 cycles. After a median follow-up of 16.4 mos, 6-mo survival was 52%. Median overall survival was: 7.0 mos for the MTD cohort; 8.5 vs 5.2 mos for pts with low- (<30%) vs high- (≥30%) marrow blasts (Figure 2); 5.6 vs 11.2 mos for de novo vs secondary AML pts (Figure 3); and 16.1 vs 5.3 mos for pts aged 65-74 vs ≥75 yrs, respectively. Conclusion: Pev + aza was well tolerated. Response rates and durable remissions were observed with limited additional toxicity beyond what is expected for aza alone. The timing and frequency of responses suggests benefit from the addition of pev compared to aza alone (Dombret et al, Blood 2015). At the time of writing, a randomized phase 2 study in low-blast AML/high-risk myelodysplastic syndromes is ongoing. Disclosures Coutre: Janssen: Consultancy; Pharmacylics, LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding. Zeidner:Tolero: Research Funding; Merck: Research Funding; Takeda: Research Funding; Otsuka: Consultancy; Agios: Honoraria. Foran:medscape: Honoraria; Millennium Pharmaceuticals, Inc.: Research Funding; novartis: Honoraria; pfizer: Honoraria; karyopharm: Honoraria; boehringer ingelheim: Research Funding; agios: Research Funding; Cellerant: Research Funding. Cruz:Millennium Pharmaceuticals, Inc.: Honoraria; Millennium Pharmaceuticals, Inc.: Speakers Bureau. Erba:Novartis: Consultancy, Speakers Bureau; Celator: Research Funding; Daiichi Sankyo: Consultancy; Celgene: Consultancy, Speakers Bureau; Juno: Research Funding; Millennium Pharmaceuticals, Inc.: Research Funding; Pfizer: Consultancy; Seattle Genetics: Consultancy, Research Funding; Incyte: Consultancy, DSMB, Speakers Bureau; Amgen: Consultancy, Research Funding; Agios: Research Funding; Sunesis: Consultancy; Gylcomimetics: Other: DSMB; Astellas: Research Funding; Ariad: Consultancy; Jannsen: Consultancy, Research Funding. Berdeja:Abbvie, Acetylon, Amgen, Bluebird, BMS, Calithera, Celgene, Constellation, Curis, Epizyme, Janssen, Karyopharm, Kesios, Novartis, Onyx, Takeda, Tragara: Research Funding. Tam:Millennium Pharmaceuticals, Inc.: Consultancy. Vardhanabhuti:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dobler:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Faessel:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dash:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Sedarati:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dezube:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment, Equity Ownership. Savona:Takeda: Research Funding; Amgen Inc.: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; Sunesis: Research Funding; Ariad: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees.

Abstract Richter syndrome represents the evolution of chronic lymphocytic leukemia into an aggressive tumor, most commonly diffuse large B-cell lymphoma. The lack of in vitro and in vivo models has severely hampered drug testing in a disease that is poorly responsive to common chemoimmunotherapeutic combinations as well as to novel kinase inhibitors. Here we report for the first time the establishment and genomic characterization of two patient-derived tumor xenograft (PDX) models of Richter syndrome, RS9737 and RS1316. Richter syndrome xenografts were genetically, morphologically, and phenotypically stable and similar to the corresponding primary tumor. RS9737 was characterized by biallelic inactivation of CDKN2A and TP53, monoallelic deletion of 11q23 (ATM), and mutations of BTK, KRAS, EGR2, and NOTCH1. RS1316 carried trisomy 12 and showed mutations in BTK, KRAS, MED12, and NOTCH2. RNA sequencing confirmed that in both cases &gt;80% of the transcriptome was shared between primary tumor and PDX. In line with the mutational profile, pathway analyses revealed overactivation of the B-cell receptor, NFκB, and NOTCH pathways in both tumors, potentially providing novel tumor targets. In conclusion, these two novel models of Richter syndrome represent useful tools to study biology and response to therapies of this highly aggressive and still incurable tumor. Significance: Two patient-derived xenograft models of Richter syndrome represent the first ex vivo model to study biology of the disease and to test novel therapeutic strategies. Cancer Res; 78(13); 3413–20. ©2018 AACR.

Key Points RP2D of PEV 20 mg/m2 in PEV/AZA combo did not alter toxicity profile of AZA; dose-limiting toxicities were transiently elevated AST/ALT. In treatment-naive older AML patients, the intent-to-treat ORR was 50%.