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Abstract Background The lymphoma proteome is the phenotypic representation of the underlying genetic and epigenetic makeup of each individual patient's tumor. The proteome is rich in druggable targets and offers a unique opportunity for the hematologist to personalize therapy. We developed a deep proteomic profiling method using ion exchange fractionation and tandem mass spectrometry. In this pilot study, we applied this method to detect differentially expressed proteins in anaplastic large cell lymphoma (ALCL) cell lines with previously known (ALK-positive) and unknown (ALK-negative) therapeutic targets. We then asked whether integrative informatic analysis of these data could be used to predict drug sensitivity in each of the cell lines. Methods To examine reproducibility of our method, proteins were extracted independently from 4 pellets each of FE-PD (ALK-negative) and Karpas 299 (ALK-positive) ALCL cells, reduced with dithiothreitol, alkylated with iodoacetamide, and digested with trypsin. Resulting peptides were separated into 6 fractions using strong anion exchange (SAX) chromatography. Peptides in each fraction were analyzed via shotgun proteomics on a QExactive mass spectrometer. Peptide mass spectra (MS/MS) were matched against a RefSeq human protein sequence database using MyriMatch software. Reversed sequences were added to the database to measure identification false discovery rates (FDRs). IDPicker filtered the peptide identifications at 2% FDR. Proteins with at least two unique peptide identifications and five MS/MS matches were considered to be present in the sample. Filtered protein identifications and corresponding spectral counts were used as input to QuasiTel software, which was configured to use proteins with at least one spectrum per biological replicate. Proteins that were significantly differentially expressed (quasi p-value < 0.05) with an absolute log2 fold-change of at least 0.5 fold were loaded into the Ingenuity Pathway Analysis (IPA) software, and a master list of drugs and corresponding gene targets was assembled using PharmGKB database and the Drug-Gene Interaction Database (DGID). The resulting drug-gene target list was merged with the differentially expressed protein identifications. Candidate targets were validated by Western blot and candidate drugs were assessed in viability assays. Results The SAX-LC-MS/MS method identified 10,111 proteins from all replicate analyses of FE-PD and Karpas 299 samples, and 93% of the identified proteome was detected in all 4 replicate analyses. The detected proteome was well represented by key transcription factors, phophatases, kinases, translation regulators and transmembrane regulators. There were 1369 proteins differentially expressed between the 2 cell lines, 709 up regulated in Karpas 299 cell line and 673 up regulated in FE-PD. Differentially expressed proteins also showed consistent expression across the biological replicates (Figure 1). Our integrated approach to identify candidate targets and drugs “rediscovered” ALK in Karpas299 and unexpectedly identified relative overexpression of the IL2-IL2RA-STAT5A-STAT5B network in ALK-negative FE-PD cells. Western blot confirmed these findings. As expected, 50-100 nM crizotinib (ALK inhibitor) decreased Karpas 299 viability (p =0.016) but had no effect on FE-PD (Figure 2). In contrast, 50-100 nM of the experimental STAT5 inhibitor 573108 (EMD Millipore) decreased FE-PD viability (p=0.002) but had no effect on Karpas 299 (Figure 2). Conclusion The lymphoma proteome is complex with 10,000 proteins and contains druggable targets that can be reproducibly identified using SAX-LC-MS/MS. These targets vary across samples and integrated informatic analysis can predict target-drug combinations that have efficacy in an experimental model. These data suggest that SAX-LC-MS/MS could be used to personalize treatment regimens in lymphoma patients. Figure 1: Spectral counts of 1369 differentially expressed proteins between Karpas299 and FE-PD cell lines were normalized and plotted in a heat map. Red color indicates down regulation and yellow color indicates up regulation. Disclosures: No relevant conflicts of interest to declare.

Abstract Background Next Generation sequencing (NGS) is a powerful tool to identify somatic mutations associated with tumor onset and drug response. While it is well suited for high quality fresh/frozen samples, NGS is not proven for FFPE tissue which is the most common type of clinical specimen. Since the nucleic acids can be readily extracted from FFPE samples for a variety of genomic analyses, a comparative mutational analysis of paired frozen and FFPE tissues is urgently needed. Our long term goal is to establish a lab protocol to detect mutations in FFPE tumors using a targeted capture and sequencing approach for genes of interest. This pilot study focuses on the comparison of FFPE and frozen samples to test the validity of using FFPE tissues in such application. Methods Gene Selection: 128 genes associated with known pathogenic mutations in lymphoma Sample Selection: 9 diffuse large B-cell lymphoma (DLBCL) cases with FFPE, frozen and germline samples, as well as 10 frozen normal lymphatic tissues as references for CNV detections Capture Probe Design: We targeted coding exons and UTR, as well as the evolutionarily conserved intronic regions. The capture probes were designed using the Agilent eArray tool. The titling density of the probes was set to 3 probes overlapping with every base in the target region to improve the capture efficiency in FFPE samples. The least stringent masking of the repeat regions was allowed to include regions with small repeats that are shorter than the length of the sequencing reads (100-bp). In addition, boosting parameters were picked to set various levels of probe replication in different regions in order to minimize the local coverage differences (e.g. between regions of different GC contents) Sequencing and Bioinformatics: The target capture and sequencing were performed by the Mayo Clinic Medical Genome Facility. The reads were mapped to Human Reference Genome Build 37 using Novalign, and SNVs were called using GATK. The CNVs were identified using an in-house developed algorithm, patternCNV. Results The designed probes covered 99.65937% of the target regions. We generated 2.2-6.7 Gbp of reads per sample, 57.4-71.5% of which were on target. This equalled an average coverage of 2100-6700 folds which is 10-30 times higher than the minimal coverage recommended by Agilent. Due to this high coverage, we observed duplicate reads that accounted for 7.7-73.5% of the total reads. When we analysed the data with and without the duplicated reads, the concordance of the called SNVs was between 84-93% out of 207-249 mutated positions per trio-sample. There were 7.8-8.9% and 1.1-2.2% unique SNVs per sample by excluding or including duplicate reads, respectively. The dis-concordances were mostly missed calls, where a SNV was observed in only 1 or 2 of the trio samples. The missed calls from frozen samples ranged from 0-10.4% compared to 1.4-10.4% from the FFPE tissues, with 0.88-2.4% more SNVs missed in FFPE. Further analyses showed that all of the missing calls came from the lack of or low coverage of the corresponding positions. There were also differences of the called SNVs between the trio samples. However, this was extremely rare. Only 2 out of the 9 trio samples at a total of 3 positions had disagreements in called SNVs between FFPE and frozen tissues, all due to the allelic imbalance where the percentage of reads supporting the alternative alleles were below 20%. Therefore, this dis-concordance can be removed by back-filling of the read-level information for each position. Unfortunately only 11.9-47.4% of the CNVs called in frozen tissues were identified in FFPE samples, due to the widely various coverage in FFPE samples. The consequent large noises of the log ratio values between the FFPEs and normal references significantly reduced the sensitivity for CNV calling. Conclusions This pilot study compared the performance of SNV and CNV detection in FFPE and paired frozen tissues using a target capture and sequencing approach. With a capture probe design strategized to benefit FFPE samples, we observed SNV detection rates in FFPE that were only slightly lower (0.88-2.4%) than those of frozen tissues due to poor coverage of some positions in FFPE samples. With a proper back-filling step, there was no dis-concordance of the called SNVs between FFPE and frozen samples. However, CNV detections in FFPE were more problematic due to the un-predictable regional coverage in FFPE samples. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1999 Recurrent chromosomal translocations involving the IGH locus are characteristic of B-cell non-Hodgkin lymphoma (NHL) and MALT lymphoma in particular has been pathologically characterized by specific IGH translocations. However, these translocations are present in only a subset of cases, suggesting that additional uncharacterized translocations might exist. In previous studies we characterized the novel t(X;14)(p11.4;q32) translocation in a patient with MALT lymphoma and found that GPR34, an orphan G-protein coupled receptor (GPCR), was highly expressed due to its juxtaposition to the IGHSA2 switch region. Although the t(X;14)(p11;q32) translocation was only identified in one patient, we wanted to determine its expression across a spectrum or normal and malignant lymphoma tissue, as other mechanisms may contribute to overexpression of genes. We measured GPR34 mRNA expression by quantitative PCR in tissue biopsies from a panel of lymphomas. As controls, we also measured GPR34 mRNA expression in normal resting or activated CD19+ B cells, resting and activated CD3+ T cells, and CD14+ monocytes. Expression of GPR34 was significantly increased in MALT (37-fold, n=35), LPL (23-fold, n=23), nodal marginal zone B cell lymphoma (18-fold, n=21), and splenic marginal zone B cell lymphoma (21 fold, n=33) compared to resting CD19+ B cells (n=11). In a gastric MALT lymphoma specimen we detected GPR34 expression at levels similar to the t(X;14)(p11;q32) patient and interphase FISH studies showed an extra intact GPR34 signal, but no translocation involving IGH or GPR34, suggesting that other mechanisms, including gene dosage effect, can upregulate GPR34. The receptor encoded by GPR34 is most similar to the PY2 receptor subfamily of GPCRs and signaling studies suggest that overexpression of GPR34 results in an accumulation of inositol phosphates and MAP-kinase activation. To further characterize the impact of GPR34 overexpression on cell signaling, HeLa cells were transduced with WT GPR34, a signaling deficient GPR34 (GPR34 DRY), or a vector control. To determine if MAPK activity was upregulated, the phosphorylation status of ERK1/2 in GPR34 WT, GPR34 DRY, and vector control cells was analyzed and we found that ERK1/2 was constitutively phosphorylated at higher levels (1.6-fold) in GRP34 WT cells compared to GRR34 DRY or vector control cells. To further explore which signaling pathways were affected by GPR34 overexpression, GPR34 WT or vector control cells were transfected with an AP-1, CRE, NF-kB, E2F, SRE, NFAT, or ISRE- luciferase reporter plasmid. GPR34 expressing cells had increased luciferase activity driven by AP-1 (5.35-fold), CRE (4.7-fold), NF-kB (2.6-fold), and E2F (2.1) when compared to vector control cells. GPR34 DRY was unable to activate these pathways. AP-1 and CRE have been implicated in a large variety of cellular processes, including transformation, and both AP-1 and CRE activity is induced upon activation of MAP kinases. In untreated cells, both AP-1 and CRE activity were significantly higher in GPR34 WT cells compared to GPR34 DRY cells and both AP-1 and CRE luciferase activity was inhibited by the MEK1 inhibitor PD98059, suggesting that activation of these pathways is MAP-kinase dependent. To determine the biologic impact of GRP34 overexpression, the proliferation rates of vector control, GPR34 WT, and GPR34 DRY cells were compared and we found that proliferation of GPR34 WT cells was significantly higher (5.6-fold) than that seen in GPR34 DRY cells. We next tested the effect of the MEK inhibitor on proliferation and saw a dose dependent decrease in proliferation of GPR34 WT expressing cells. These results suggest that GPR34-mediated proliferation is dependent on MAPK. The presence of elevated GPR34 expression in tumors and the increased proliferation mediated by GPR34 suggests that it may have oncogenic potential. We therefore tested the ability of GPR34 WT cells to generate tumors in a tumor colony-forming assay. Only the GRP34 WT cells had the ability to form tumors in soft agar suggesting that overexpression of GPR34 can result in tumor formation. Taken together, our results identify a novel translocation in MALT lymphoma, emphasize a novel role for GPR34 in tumor cell growth, and suggest that MEK inhibitors may be useful in a subset of translocation-harboring or GRP34 high-expressing tumors. Disclosures: Fonseca: Genzyme: Consultancy; Medtronic: Consultancy; BMS: Consultancy; AMGEN: Consultancy; Otsuka: Consultancy; Celgene: Consultancy, Research Funding; Intellikine: Consultancy; Cylene: Research Funding; Onyx: Research Funding; FISH probes prognostication in myeloma: Patents & Royalties.

Abstract Background: Peripheral T-cell non-Hodgkin’s lymphomas (PTCL) account for approximately 10% of all non-Hodgkin’s lymphomas in the U.S. and Europe. PTCL, unspecified (PTCL-U), as classified by the WHO, is the most common subtype. The ability of high-dose therapy (HDT) and stem cell transplantation (SCT) to improve patient outcome was evaluated in the current study. Methods: All patients with PTCL-U evaluated at our institution who had tissue specimens available for review from January, 1994 to December, 2005 were identified and both clinical characteristics and treatment course obtained from the medical record. Results: 89 patients with PTCL-U were identified, with a median follow up of 13 months (range 1 month–12 years). The median age at diagnosis was 56 years (range 24–90). The IPI was low, intermediate or high in 34%, 44% and 22% of patients, respectively. On univariate analysis, age >60 (p<.0001), ECOG performance status >1 (p<.0001), LDH greater than normal (p=.004), Ann Arbor Stage III/IV (p=.01) and the presence of B symptoms (p=.0004) were associated with a poorer overall survival, as was an intermediate or high IPI (p<.0001). In contrast, on multivariate analysis only age >60 (p=.0006) and ECOG performance status >1 (p=.007) were independently associated with poorer overall survival. Fifty-seven percent of patients were treated initially with an anthracycline-based regimen, most commonly CHOP (53%). Patients with a low (0–1), intermediate (2–3) or high (4–5) IPI experienced a 61%, 29% and 18% 5-year overall survival, respectively. Fourteen patients (16%) received HDT and autologous (n=12) or allogeneic (n=2) SCT, either at the time of a first partial or complete response (n=11) or at the time of first relapse (n=3). The median survival in those patients treated initially with an anthracycline-based regimen alone was 11 months (95% CI 0.6–1.6 years). Improvement in both 5-year overall (75% vs 24%, HR=5.6, 95% CI 2.0–23.4, p=.0004) and disease-free (60% vs 26%, HR=3.2, 95% CI 1.3–9.3, p=.008) survival was observed in patients who received HDT/SCT, as compared to patients treated with anthracycline-based therapy alone. Furthermore, improvement in both 5-year overall (80% vs 26%, HR=5.8, 95% CI 1.7–35.7, p=.002) and disease free (72% vs 26%, HR=3.8, 95% CI 1.3–15.8, p=.009) survival was observed in patients who received HDT/SCT at the time of a first partial or complete response when compared to patients who received anthracycline-based therapy. When patients who failed to achieve a first partial or complete response were excluded from the analysis, improved 5-year overall (80% vs 57%, HR=0.5, 95% CI 0.1–2.1, p=.4) and disease-free (72% vs 53%, HR=0.7, 95% CI 0.1–2.3, p=.5) survival were observed in patients who received upfront HDT/SCT, although this failed to reach statistical significance. The improved overall and disease free survival observed in patients receiving HDT/SCT, either at the time of a first response or at the time of relapse, remained significant when accounting for differences in the IPI. In conclusion, selected patients with PTCL-U may benefit from treatment with HDT/SCT following a first response to conventional anthracycline-based chemotherapy.

Abstract Splenic marginal zone lymphoma (SMZL) is an indolent B cell malignancy whose diagnosis is based on lymphocyte morphology, immunophenotype and marrow and/or splenic histology. Unlike other lymphomas, there is not a common chromosomal translocation specific for SMZL, and genetic prognostic factors are poorly defined. To investigate the pattern of genomic aberrations in SMZL, we applied comparative genomic hybridization to BAC microarrays (array CGH) to a well characterized series of 75 SMZL specimens. We applied two different 1 Mb-resolution BAC arrays: UCSF HumArray 3.2 and a novel array CGH platform developed at Univ. of Salamanca. These arrays allowed us to detect DNA copy number changes across the genome with high accuracy in 67 of 75 patient samples. Data were compared with our previous array CGH studies of 170 samples from different B-cell lymphoma subgroups. FISH studies for IGH, IGK and IGL translocations and 7q deletion were performed on tissue microarrays in 24 cases. Of the 67 samples, 19 (28%) showed a normal genomic profile. The median number of genomic aberrations per tumor was 2.2 (1.3 gains and 0.9 losses), which was lower than the rates detected in other lymphoma subgroups (diffuse large cell lymphoma, 6.4; mantle cell lymphoma, 6; follicular lymphoma, 4.5) and comparable to MALT lymphomas (2 abnormalities per tumor). SMZL cells showed a genomic pattern characterized by gain of chromosomes 3q24-q29 (18%), 6p (9%), 12q (9%), and 18q (4%) and loss of 7q32 (34%), 8p21-p23 (13%), 17p13 (10%) at P53 locus and 6q21-q27 (9%). Notably, no alterations of the P16/ARF (9p21) or MYC loci (8q24) were detected. Correlation of array CGH data with conventional cytogenetics, FISH and LOH studies revealed a high concordance. Detailed mapping of 7q deletions delineated a consensus region of loss of 3 Mb in 7q32. This 7q deletion was almost exclusive to SMZL, being observed in only 5 of 170 non-SMZL B-cell lymphomas (p=0.0000001). Four cases presented IG-translocation. Mutation of IGH was observed in 62% and correlated with a complex karyotype (61 vs. 13%; p=0,0008) whereas unmutated IGH correlated with the deletion of 7q (56 vs. 23%; p=0,01). Among the various genomic abnormalities, only the deletion of 8p or the presence of a complex karyotype correlated with inferior overall survival (OS) (median OS, 58 vs. 110 months, p=0,004; and 60 vs. 105 months, p=0,01; respectively). In summary, array CGH has defined a pattern of genomic aberrations in SMZL that differs from other B-cell lymphoma subgroups and that may predict overall survival. Because the deletion of 7q32 is the most distinctive genetic marker in SMZL, the identification of a putative tumor suppressor gene inactivated within the region of deletion seems mandatory.

Abstract Abstract 1604 Background EBV (+) DLBCL of the elderly is a lymphoproliferative disorder recently included as a provisional entity in the 2008 WHO classification of lymphoid tumors. Defined as EBV (+) DLBCL in patients over the age of 50 years without known immunosuppression, information is evolving in this entity. To date, the true incidence of EBV (+) DLBCL in adults remains imprecisely determined and may vary regionally. This study sought to determine the incidence, presenting clinical characteristics, and outcome of EBV (+) in an unselected cohort of DLBCL patients enrolled in a prospective observational study. Methods The University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) is a prospective, longitudinal observational study designed to collect information on patterns of care and outcomes for patients with newly diagnosed lymphoma. Patients seen at the Mayo Clinic, Rochester MN and the University of Iowa within 9 months of their initial diagnosis of lymphoma are offered enrollment. HIV (+) patients are excluded. Baseline patient reported data, clinical data and initial management are collected using a standard protocol and a central pathology review is performed. After enrollment, patients are actively followed for events (disease progression, retreatment, and death) and disease related comorbidities. Tissue Micro Arrays (TMA) are constructed on available primary biopsy specimens. Epstein Barr Encoded RNA (EBER) EBV testing was performed by in-situ hybridization, and scored by an expert hematopathologist. EBER reactivity in more than 30% of malignant cells were required for EBV(+) designation. All DLBCL patients from the MER with available TMA excluding primary mediastinal DLBCL and post transplant lymphoproliferative disorders (PTLD) are included in the current analysis. Event free survival (EFS) was defined as time from diagnosis until recurrence, retreatment, or death due to any cause. Results 184 newly diagnosed DLBCL patients with available TMAs were enrolled in the MER from 2002–2009. The median age at enrollment was 62 (range 18–89) and 57% were male. 89.7% were treated with immunochemotherapy. At a median follow-up of 66 months (range 1–116), 80 patients (43%) had an event which included 59(32%) deaths. TMA testing was positive for EBV in 13 (7 %) samples with an even distribution among age groups. There was a trend toward higher percentage of stage III/IV disease (85 vs 57%, p = 0.052), and BM involvement (46 vs 16%). EBV (+) was not associated with other extranodal disease or further identifiable differences in presenting clinical characteristics. Controlling for IPI, the hazard ratio for EFS among EBV+ in DLBCL pts over 50 was 0.41 (95% CI = 0.13–1.32) p = 0.14. EFS and OS curves for pts over 50 are shown below. There were no events or deaths in the 4 EBV+ pts under age 50. Conclusions EBV+ DLBCL represents a small proportion of DLBCL patients presenting for care to our academic medical centers, consistent with reports from other regions. Substantial unique clinical characteristics at presentation for those pts with EBV+ disease were not identified, and outcomes were no worse than EBV (−) counterparts. Given the apparent regional differences in reports of EBV(+) DLBCL of the elderly, future clinical series will need to establish a more precise definition or determine more distinctive features to justify adoption of EBV(+) DLBCL of the elderly as a full entity in the WHO classification. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1545 Introduction: The diagnosis of peripheral T-cell lymphoma (PTCL) is difficult and accurate diagnosis and subclassification relies on correlating histologic, immunophenotypic, molecular genetic, and clinical data. Evidence-based guidelines for the appropriate diagnostic work-up of PTCL are lacking. The objective of this study was to evaluate a large series of PTCLs by experienced hematopathologists with a tiered approach to immunohistochemistry (IHC) and molecular genetic characterization to document overall diagnostic accuracy and clinical relevance using this approach. Methods: 7 experienced hematopathologists from 5 institutions reviewed 374 cases of peripheral T and NK cell lymphomas (referred to collectively as PTCL). 6 cases of cutaneous T-cell lymphoma were excluded after final review in addition to 29 non-PTCL cases submitted as control cases to mimic diagnostic practice during the review. Cases received tier 0, 1 and 2 diagnoses by 3 independent pathologists, based on review of hematoxylin and eosin (HE) stain with basic demographic data, panel 1 IHC (CD3, CD5, CD10, CD20, CD21, CD30, CD45, PAX5), and panel 2 IHC (CD2, CD4, CD7, CD8, CD23, PD1, CD56, EBER, ALK, TIA1, TCRg, TCRbF1), respectively. A tier 2b diagnosis was then rendered after gene rearrangement data were available. A final consensus diagnosis was rendered after discussion of each case by the 3 reviewers with all available clinical data. Overall survival (OS) was assessed using Kaplan-Meier (KM) curves and Cox proportional hazards models. Results: 1122 individual diagnoses leading to 339 final consensus PTCL diagnoses were rendered. 341 (91%) cases had complete phenotypic data and 241 had gene rearrangement data. There was no bias of missing data according to final diagnosis subtype. Reviewer diagnoses using specific WHO subclassification were 16.3%, 36.9%, 82.7%, and 85.9% for tier 0, 1, 2, and 2b, demonstrating a significant increase in diagnostic certainty after a complete IHC panel. Gene rearrangement only contributed to a change in diagnosis in 51/650 (8%) individual reviews. Across all 374 cases, a small number of cases (n=28, 7.5%) showed no agreement among the 3 independent reviewers after tier 2b and required debate. These generally represented refinement of the subclassification of a PTCL. The most common disagreements were between PTCL, not otherwise specified (nos) vs. unclassifiable T-cell lymphoma, and PTCL, nos vs. angioimmunoblastic T-cell lymphoma (AITL). Currently, OS data was available in 198 cases and 52% have died (median age follow-up of 15 months for those still alive, range 0–160 mo). Figure 1 shows the KM survival curves for types with more than 10 cases. Of note, unclassifiable PTCL cases had poor OS, comparable to PTCL nos; a trend was seen for CD30+ ALK- ALCL to have a longer OS compared to PTCL nos (HR=0.5, 95% CI: 0.21–1.19, P=.09). EBER positivity in tumor cells was associated with poor OS in the cohort of all PTCL patients (HR=2.32, 95% CI: 1.28–4.23, p=0.006, Figure 2); the association was similar when nasal NK/T-cell lymphoma cases were excluded (HR=2.50, 95% CI: 1.00–6.26, p=0.05). Trends for poor prognosis were also seen for TIA-1 expression in PTCL, nos (HR=1.9, 95% CI 0.91–3.96, P=.09) and PD1 expression in AITL (HR=6.25, 95% CI 0.85–46.09, P=.07). Clinical data collection is still ongoing and will be updated. Conclusions: We demonstrate the diagnostic accuracy among experienced hematopathologists of a defined IHC panel, showing an overall ability to reach consensus diagnosis of 93% in PTCL cases. The resulting consensus diagnostic subtypes showed expected outcomes relative to other large series of PTCLs, and EBER positivity is a poor prognostic marker among T and NK cell lymphomas. A tiered approach to IHC is recommended when a PTCL is under differential diagnostic consideration since the first tier can often resolve the main question of whether a lesion is reactive or lymphoma. This can lead to more efficient use of the expanded tier 2 panel that will enable diagnosis and specific subclassification of PTCL. Gene rearrangement studies are not required in the great majority of cases. This evidence-based approach to the diagnosis of PTCL should inform practicing pathologists, clinical trial design, and policy makers regarding required ancillary studies in this group of diseases. Disclosures: Hsi: Allos: Research Funding. Said:Allos: Research Funding. Macon:Allos: Research Funding. Rodig:Allos: Research Funding. Gascoyne:Seattle Genetics: Research Funding. Ondrejka:Allos: Research Funding. Dorfman:Allos: Research Funding. Maurer:Allos: Research Funding. Dogan:Allos: Research Funding.

Abstract Abstract 1534 + equal contributions Diffuse large B-cell lymphoma (DLBCL) is a clinically and biologically heterogeneous disease with a high proliferation rate and infrequent somatic mutations of TP53 and genes encoding cell cycle pathway components. Despite recent advances in the molecular understanding of DLBCL pathogenesis, clinical models such as the International Prognostic Index (IPI) are still used to identify high-risk patients. By integrating high-resolution high-density SNP array data with transcriptional profiles and performing pathway analysis in 180 primary DLBCLs, we identified a comprehensive set of copy number alterations (CNAs) that decreased p53 activity and perturbed cell cycle regulation. Primary DLBCLs with single copy loss of 17p13.1 (TP53/RPL26/KDM6B) often had CNAs of an additional p53 modifier – 9p21.3 (CDKN2A/ARF), 19q13.42 (BCL2L12), 12q15 (MDM2) or 1q23.3 (MDM4/RFWD2). CNAs of the respective p53 modifiers, CDKN2A (ARF, 9p21.3), MDM2 (12q15) and MDM4/RFWD2 (1q23.3), occurred in largely separate groups of tumors. DLBCLs with CNAs of p53 pathway members frequently exhibited concurrent alterations of additional cell cycle components such as CCND3 (6p21.32), CDK6 (7q22.1), CDK2/CDK4 (12q15) and/or RB1 (13q14.2) or RBL2 (16q12.2). When the primary DLBCLs were clustered in the space of CNAs that perturb p53 pathway and cell cycle components, 66% of tumors had multiple alterations (“complex” pattern) whereas the remaining 34% of tumors lacked these lesions (“clean” signature). Tumors with “complex” alterations of p53 pathway and cell cycle components also had more total CNAs and more frequent TP53 mutations, highlighting the association between p53 deficiency, cell cycle deregulation and increased genomic instability in DLBCL. The patterns of “complex” vs. “clean” CNAs of p53 pathway and cell cycle components and the association between the “complex” signature and total CNAs were confirmed in an independent series of primary DLBCLs. To further characterize DLBCLs with “complex” vs. “clean” CNA patterns, we performed gene set enrichment analyses with publicly available series of p53 target genes and a RB-deficiency gene set which included multiple E2F targets. The p53 target transcripts were significantly less abundant in “complex” DLBCLs, directly linking their genetic signature of p53 deficiency with decreased p53 activity. Furthermore, the RB-deficiency gene set was significantly enriched in “complex” DLBCLs suggesting that these tumors had increased E2F-mediated cell cycle progression. Consistent with these observations, DLBCLs with “complex” CNA patterns also had significantly higher proliferation indices as determined by Ki67 immunostaining. We next assessed the prognostic significance of the “complex” CNA pattern in the subset of patients who were treated with R-CHOP (rituxan, cyclophosphamide, adriamycin, oncovin, prednisone) and had long-term follow-up. R-CHOP treated patients with “complex” CNA patterns had a 5-year overall survival of only 62%; in contrast, those with “clean” CNA signatures had an 100% overall survival (p =.001). The association between CN complexity and outcome was independent of transcriptionally defined categories and additive to the clinical IPI risk model. Taken together, these data provide a structural basis for deregulated cell cycle, increased cellular proliferation and unfavorable outcome in DLBCL and suggest targeted treatment strategies. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 149 Background. There are few established factors that predict risk of follicular lymphoma (FL) transformation, and only two studies have evaluated the role of germline genetic variation and risk of transformation. One study reported an association of a BCL6 SNP (397C>G) with risk of transformation, and a second study reported an association with rs6457327, which is in the HLA region of 6p21. This study evaluated the risk of FL transformation in the modern treatment era with germline SNPs that were previously reported to be associated with FL transformation (BCL6SNPs and rs6457327), along with SNPs (N=45) previously associated with either risk of FL or FL prognosis. Methods. Newly diagnosed FL patients were prospectively enrolled from 2002–2009 into the Molecular Epidemiology Resource of the University of Iowa/Mayo Clinic Lymphoma SPORE. Peripheral blood for genotyping was collected at enrollment, and clinical and treatment data were abstracted from medical records. All patients were actively followed for disease progression, retreatment, transformation and death. For this analysis, only FL patients with grade I-IIIa were included. Patients with composite DLBCL, FL grade IIIb, or other evidence of transformation at diagnosis were excluded. Transformation was based on either 1) biopsy confirmation of FL grade IIIb, DLBCL, or higher grade B-cell lymphoma; or 2) clinical indicators of transformation based on the published literature, including sudden rise in LDH, rapid discordant localized nodal growth, new involvement of unusual extranodal sites, new B-symptoms, or hypercalcemia. Genotyping was conducted using a custom Illumina iSelect panel. Cox regression was used to estimate Hazard Ratios (HRs) and 95% confidence intervals (CI) for individual SNPs with time to transformation, with death modeled as a competing risk. Each SNP was modeled with the most prevalent homozygous genotype used as the reference group, and each SNP was modeled as having a log-additive (per minor allele) effect in the regression model. An ordinal test was used to assess the trend, and p<0.05 was considered statistically significant. Results. There were 631 newly diagnosed grade I-IIIa FL patients, of whom 532 had DNA and were successfully genotyped. The median age at diagnosis was 60 years (range 23–93) and 53% were male. FLIPI distribution was 42% 0–1, 34% 2 and 24% 3–5. Initial therapies included observation (32%), rituximab (R) monotherapy (13%), alkylator-based chemotherapy +/− R (20%), and anthracycline-based chemotherapy +/− R (19%). At a median of 59 months of follow-up (range, 11–110), 58 patients died, 254 had an event (death, progression or retreatment) and 54 patients (10%) transformed. Transformation was biopsy proven in 43 of the 54 patients (80%). The SNP rs6457327 on chromosome 6p that was previously reported to be associated with transformation was positively associated with risk of transformation in our data (HR=1.40; 95%CI 0.97–2.04; p=0.07), although this association was weaker but still consistent with the prior report. Further, we evaluated additional typed SNPs from the HLA region of 6p, and found additional associations (p<0.05) with HLA-DRA (3 SNPs), HLA-DQA2 (2 SNPs), HLA-DOA (2 SNPs) and HLA-DPB1/HLA-DPA2 (2 SNPs), of which rs10484569 from HLA-DPB1/HLA-DPA2 was the most strongly associated with risk of transformation (HR=3.01; 95%CI 1.48–6.09; p=0.002). None of the BCL6 or other previously reported risk SNPs were associated with transformation. Of the SNPs previously associated with FL prognosis, only the FCGR2A rs1801274 (HR=1.41; 95%CI 0.94–2.10; p=0.09) and CD46 (CD46 molecule, complement regulatory protein) rs2466571 (HR=1.72; 95%CI 1.16–2.55; p=0.007) were associated with risk of transformation. For CD46, one additional SNP (rs2796269) was also associated with transformation (HR=0.61; 95%CI 0.40–0.95; p=0.03). Further adjustment for FLIPI score and treatment (observation versus all other) did not alter these associations. Conclusions. The previously reported association of rs6457327 with risk of transformation in the modern treatment era was replicated. In addition, several HLA loci and two FL prognosis SNPs were linked to transformation risk. The remaining published FL risk or prognosis SNPs were not associated with transformation. Our results support a role for germline genetic variation in the HLA region, FCRGR2A and CD46 in transformation of FL. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1575 We recently demonstrated in a phase II study that the anti-CD22 monoclonal antibody epratuzumab added to RCHOP improved DLBCL survival parameters. Despite these advances, 30–40% of DLBCL patients still relapse and die of disease. Recent advances have led to the identification of a variety of intracellular oncogenic pathways as potential targets for lymphoma therapy. Specifically, many studies have found that activation of the Signal transducer and activator of transcription 3 (STAT3) pathway promotes tumor cell survival in various types of cancers. STAT3 is a transcription factor and exerts its anti-apoptototic effect through several downstream targets such as MYC. MYC protein can be expressed in lymphoma cells with or without the presence of MYC translocation. The frequency of phosphorylated STAT3 (pSTAT3) and MYC expression and their prognostic relevance are unknown within diffuse large B-cell lymphoma (DLBCL), germinal center B-cell (GCB) and non-GCB subtypes. This study studied the tumor cell expression of pSTAT3 and MYC by IHC paired with serum cytokine levels in a DLBCL patient population uniformly treated on N0489. DLBCL tumor samples (n=38) were stained for detection of nuclear pSTAT3 expression. Using a threshold of ≥30% of tumor nuclei staining positive, 35 % (14/40) of tumors were pSTAT3+. An additional 17% (7/40) had between 10–30% pSTAT3+ cells. Non-malignant tonsil tissues (n=10) were positive for tSTAT3 in all cases but all but one case were pSTAT3 negative. Twenty-four of the same DLBCL tumors used for pSTAT3 expression were stained for MYC and 50% (12/24) were MYC positive (all nuclear) as defined by the criteria of ≥30% of cells staining positive. In cases (n=23) where both MYC and pSTAT3 IHC were performed, a positive pSTAT3 was more likely to have MYC expression whereas a positive MYC stain did not inform pSTAT3. By using a break apart probe for the MYC gene, MYC translocations in the major breakpoint regions were found in 10% (3/29) of cases. When MYC FISH was correlated with MYC IHC in the 24 DLBCL cases that had both techniques performed, all 3 MYC translocation cases were GCB by IHC, two were strongly positive for MYC by IHC, and 1 was negative. Among the 21 MYC FISH negative cases, 10 were MYC positive by IHC. These data suggest that MYC expression in lymphoma is not only controlled by genetic events such as translocations but also by other signaling pathways such as STAT3. pSTAT3 expression was correlated with an elevated serum LDH (p=0.0007). Neither MYC or pSTAT3 tumor expression correlated with other clinical or pathological features. Survival analysis revealed a trend toward shorter EFS for DLBCL patients whose tumors expressed MYC protein by IHC (p=0.2) or had a MYC translocation (p=0.09) by FISH; pSTAT3 expression status did not predict EFS (p=0.9). Within the GCB group 10 cases were MYC negative (10/17; 59%) and 7 cases were MYC positive (7/17; 41%). Among the non-GCB group 83% (5/6) were MYC positive. These data clearly suggest a trend of higher MYC positivity in the non-GCB DLBCL group (p=0.07). MYC positive cases had a clear trend of inferior EFS in both GCB (p=0.2) and in non-GCB (p=0.5) groups. The distribution of pSTAT3 (n=38) expression was also evaluated in the GCB (n=26) and non-GCB (n=12) DLBCL. In the GCB group 27% (7/26) were pSTAT3 positive compared to 58% (7/12) in the non-GCB group. Thus, there was a clear trend toward higher pSTAT3 positivity in non-GCB DLBCL tumors (p=0.06); however, pSTAT3 status did not correlate with EFS in either GCB or non-GCB DLBCL patients. In the present study we correlated pretreatment serum cytokines levels of these patients with pSTAT3 and MYC tumor cell expression. Out of the 30 cytokines tested, the only pre-treatment cytokines that were significantly correlated with pSTAT3 expression were IL-10 (p=0.05), G-CSF (p=0.03) and TNFa (p=0.04); none were correlated with MYC expression. Overall, our data provide evidence that over-expression of pSTAT3 and MYC is common in DLBCL. These biomarkers have potential as prognostic factors in the case of MYC and as a tool for selecting therapy for pSTAT3. MYC may be especially useful to further identify an adverse group of DLBCL patients within the otherwise favorable GCB tumor group. The availability of JAK/STAT and STAT-specific inhibitors provides the rationale to incorporate pSTAT3 staining in tumors from patients who are participating in these trials to learn if this biomarker can predict response Disclosures: No relevant conflicts of interest to declare.