Xu‐Monette, Zijun Y.

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 Purpose: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. Experimental Design: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. Results: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1–high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. Conclusions: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

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.

AimsIt is unknown whether Epstein–Barr virus (EBV) infection can occur in high‐grade B cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements, also known as double‐ or triple‐hit lymphoma (DHL/THL).Methods and resultsHere we report 16 cases of EBV+ DHL/THL from screening 846 cases of DHL/THL and obtaining additional EBV+ cases through multi‐institutional collaboration: eight MYC and BCL2 DHL, six MYC and BCL6 DHL and two THL. There were eight men and eight women, with a median age of 65 years (range = 32–86). Two patients had a history of follicular lymphoma and one had AIDS. Nine of 14 patients had an International Prognostic Index of ≥3. Half of the cases showed high‐grade/Burkitt‐like morphology and the other half diffuse large B cell lymphoma morphology. Using immunohistochemistry, the lymphoma cells were positive for MYC (n = 14 of 16), BCL2 (n = 12 of 16), BCL6 (n = 14 of 16), CD10 (n = 13 of 16) and MUM1 (n = six of 14). Using Hans’ algorithm, 13 cases were classified as germinal centre B cell (GCB) and three as non‐GCB. The lymphomas frequently showed an EBV latency Type I with a median EBV‐encoded small RNAs of 80% positive cells (range = 20–100%). After a median follow‐up of 36.3 months (range = 2.0–41.6), seven patients died, with a median survival of 15.4 months (range = 3.4–47.3) after diagnosis of EBV+ DHL/THL. Five of six patients with MYC and BCL6 DHL were alive, including four in complete remission. In contrast, only four of 10 patients with MYC and BCL2 DHL or THL were alive, including two in complete remission. The median survival in patients with MYC and BCL6 DHL was unreached and was 21.6 months in patients with MYC and BCL2 DHL or THL.ConclusionsEBV infection in DHL/THL is rare (~1.5%). Cases of EBV+ DHL/THL are largely similar to their EBV– counterparts clinicopathologically. Our findings expand the spectrum of EBV+ B cell lymphomas currently recognised in the World Health Organisation classification and suggest differences between EBV+ MYC and BCL2 DHL versus EBV+MYC and BCL6 DHL that may have therapeutic implications.

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 Context and objective Approximately 5-10% of diffuse large B-cell lymphoma (DLBCL) patients carry MYC gene translocations (MYC-translocation+) with a poor prognosis after standard chemotherapy. MYC-translocation+ DLBCL patients carrying BCL2 translocations (MYC+/BCL2+ double-hit lymphoma) have a worse survival. The efficacy of adjuvant radiotherapy in this setting is unknown. The purpose of this study is to evaluate the efficacy of radiotherapy as a part of the therapeutic regimen for patients with MYC-translocation+ DLBCL. Patients and methods From the International DLBCL R-CHOP consortium program, we selected 581 patients with de novo DLBCL treated with standard R-CHOP immunochemotherapy (diagnosed and treated from 2000 to 2010). We excluded patients with transformed DLBCL, primary mediastinal, cutaneous, testicular or central nervous system large B-cell lymphomas, patients with HIV infection, and patients not treated with R-CHOP. The median follow-up was 54.9 months. Fluorescence in situ hybridization assessing MYC was performed for all the patients (n=581) and results were correlated with available clinical data to identify clinicopathologic features associated with MYC translocation, and to evaluate the prognostic significance of MYC translocations regarding overall survival (OS, from the time of diagnosis to death from any cause) and progression-free survival (PFS, from the time of diagnosis to relapse or death from any cause). In the MYC-translocation+ DLBCL group, 38 patients received chemotherapy alone and 21 patients received chemotherapy with adjuvant radiation therapy. The clinicopathologic features and survival of MYC-translocation+ DLBCL patients treated with (n=21) and without radiotherapy (n=38) after immunochemotherapy were compared to in order to evaluate the radiotherapy efficacy and other confounding factors. Results MYC translocations were detected in 59 DLBCL patients (10.2%). Patients with MYC-translocation+ DLBCL more often had bulky tumors, involvement of multiple extranodal sites, and poorer OS (hazard ratio [HR]: 2.0, 95% confidence interval [CI]: 1.20 - 3.35, P= .0083) and PFS (HR: 1.96, 95% CI: 1.22 - 3.13, P= .0005) independent of the International Prognostic Index score. Poor survival was primarily attributable to patients with MYC+/BCL2+ double-hit DLBCL who were predominantly of germinal center B-cell subtype. Among MYC-translocation+ DLBCL patients, a better survival was achieved in patients who received radiotherapy (for OS, HR: .32, 95% CI: .15 - .71, P= .0049; for PFS, HR: .35, 95% CI: .17 - .73, P= .0043). Conversely, radiotherapy abolished the adverse impact of MYC translocations. In addition, radiotherapy was associated with better survival in the subset of patients with MYC+/BCL2+ double-hit lymphoma (P = .017 for OS, and P = .05 for PFS). However, owing to the common use of radiotherapy as consolidation therapy, the favorable prognoses in the group of patients who received radiotherapy could also be attributed to limited-stage disease and more frequent complete remission (CR) after first-line treatment and therefore these factors confound interpretation of the data. To address these issues, we evaluated radiotherapy efficacy in separate patient groups: patients who achieved CR, non-CR (PR/SD/PD) patients, and patient with stage I/II, or stage III/IV disease. The efficacy of radiotherapy appeared more apparent in patients with advanced disease who did not achieve CR after first-line chemotherapy. Multivariate analysis after adjustment for stage and IPI score validated that radiotherapy significantly improved OS (HR: .28, 95% CI: .10 - .81, P= .018) and PFS (HR: .32, 95% CI: .13 - .80, P= .015) of MYC-translocation+ DLBCL patients. Conclusions The presence of MYC translocations in DLBCL is an important biomarker that facilitates prognostic prediction and treatment stratification independent of the IPI score. For chemoresistant MYC-translocation+ DLBCL patients, radiotherapy seems to be an effective adjuvant regimen likely due to the higher frequency of extranodal involvement and bulky disease in MYC-translocation+ DLBCL patients. Our results provide a rationale for larger scale studies to assess the potential role of radiotherapy in the management of MYC-translocation+ DLBCL patients, particularly patients with MYC+/BCL2+double-hit DLBCL. Disclosures: Winter: Millenium: Research Funding; Novartis : Research Funding; Pfizer (Wyeth): Research Funding; Seattle Genetics: Research Funding; Spectrum: Research Funding; Janssen (Pharmacyclics): Research Funding; Spectrum (Allos): Consultancy; Sanofi Aventis: Consultancy; Tgen: Consultancy; AMBIT Biosciences (Spouse): Research Funding; Celgene (Spouse): DSMB, DSMB Other, Research Funding; Ariad Pharmaceuticals (Spouse): Research Funding; Novartis (Spouse): Consultancy, Research Funding; Amgen (Spouse): Consultancy, Research Funding; Astellas (Spouse): Research Funding; Caremark/CVS: Consultancy; Pfizer (Spouse): Consultancy; Sanofi Aventis (Spouse): DSMB, DSMB Other; Bristol Myers Squibb (Spouse): DSMB, DSMB Other; UptoDate, Inc.(Spouse): Patents & Royalties.