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Abstract Background: EBV+ DLBCL not otherwise specified (EBV+ DLBCL NOS) is defined by the 2016 WHO Classification of Tumors of Hematopoietic and Lymphoid Tissues as EBV+ DLBCL in patients without a history of known immunosuppression. Among Asian patients, adverse outcomes have been associated with EBV+ vs EBV- DLBCL, and circulating EBV has been found in the majority of patients. Outcome studies of unselected North American patients are few and non-confirmatory. No formal assessment of immunosuppression status has been incorporated into these analyses, leading to the variable inclusion of patients with a history of immunocompromised states. We sought to determine the prevalence, presenting clinical and pathology characteristics, and outcomes of DLBCL by EBV and immunosuppression status in an unselected prospective cohort study of North American patients. Methods: From 2002-2012, we enrolled consecutive, newly diagnosed patients with lymphoma who were ≥ 18 years and HIV negative into the Molecular Epidemiology Resource (MER). Clinical, laboratory, and treatment data were abstracted from medical records. All DLBCL patients with available tissue microarrays (TMAs), excluding primary mediastinal DLBCL and post-transplant lymphoproliferative disorders, were included. Medical records were reviewed using a standard protocol to classify patients as immunocompromised based on a documented history of primary immunodeficiency or iatrogenic immunosuppression. DLBCL cell of origin was classified as germinal center (GCB) vs non-GCB using the Hans algorithm. CD30 was determined using immunohistochemistry; positivity cutoff was 20% of neoplastic cells. EBV testing was performed by in-situ hybridization for EBV encoded small RNAs (EBERs), and scored by an expert hematopathologist. Event free survival (EFS) was defined as time from diagnosis until recurrence, retreatment, or death due to any cause. Associations with EFS and Overall Survival (OS) were obtained using the methods of Kaplan-Meier (KM). Hazard Ratios (HRs) and 95% confidence intervals (CIs) were estimated from Cox regression models. Results: 1,100 patients with DLBCL were enrolled into the MER; 362 had TMAs available for this analysis. Median age was 63 years (range 20-89) and 59% were male. 89.5% of patients were treated with immunochemotherapy. 16 cases (4.4%) were EBV+, and 39 cases (10.8%) were considered immunocompromised. EBV positivity was more common in immunocompromised vs immunocompetent patients, with a trend towards significance (10.3% vs 3.7%; P = 0.08). The non-GCB subtype was more frequent in EBV+ vs EBV- DLBCL (62.5% vs 34.1%; P < 0.01), but similar between immunocompromised vs immunocompetent patients (48.7% vs 33.7%; P = 0.10). CD30 positivity was also more frequent in EBV+ vs. EBV- DLBCL (25.0% vs 8.1%; P < 0.01), but similar between immunocompromised vs immunocompetent patients (12.8% vs 8.4%, respectively; P = 0.45). With a median follow-up of 59 months (range 0.7-155.2) there were 151 events and 119 deaths. KM curves by EBV and immunosuppression status are shown in the figure. There was no association of EBV positivity with EFS (HR = 0.76; 95% CI 0.34-1.72) or OS (HR = 0.99; 95% CI 0.43-2.25). A history of immunosuppression was not associated with EFS (HR = 1.17; 95% CI 0.72-1.89) or OS (HR = 1.02; 95% CI 0.58-1.78). In the subset of immunocompetent patients, there was no association of EBV positivity with EFS (HR = 0.54; 95% CI 0.17-1.70) or OS (HR = 0.71; 95% CI 0.23-2.25). Similar results were obtained after adjustment for the International Prognostic Index. Circulating viral DNA was detected in 2/5 EBV+ and 4/49 EBV- DLBCL patients. Conclusions: The prevalence of EBV+ DLBCL NOS is <5% among patients in a large North American cohort, similar to other western populations. There was no evidence of an association of EBV or immunosuppression status with EFS or OS, with low power for detecting associations with EBV. Circulating viral DNA was infrequent among either EBV+ or EBV- DLBCL patients. While immunosuppression has been previously shown to be a risk factor for DLBCL, it was not found to be associated with EFS or OS. Overall, these results suggest divergent outcomes among EBV+ DLBCL patients between western and non-western populations, underscoring differences in host factors or circulating viral strains. Disclosures Ansell: BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding.

Abstract Background: B-cell non-Hodgkin lymphomas (NHL) are common lymphoid malignancies in which malignant B-cells arrested at various stages of differentiation proliferate within lymph nodes and occasionally other tissues. The microenvironment that supports the growth and survival of NHL B cells consists of a complex network of immune cells and cytokines and its specific composition has been shown to have significant clinical implications. The intratumoral immune cells include effector and regulatory T (Treg) lymphocytes that are more than simple residual elements from the normal lymph node structure. We previously explored whether the extent of T cell infiltration played a role in the clinical outcome of patients with B-cell NHL and found that an increased percentage of CD4+ T cells in the diagnostic biopsy of lymphoma patients significantly correlated with an improved 5-year overall survival. We have also shown that intratumoral Treg cells significantly suppress the anti-tumor response. Based on the fact that intratumoral T-cells are important in B-cell NHL, we evaluated whether genetic variation in genes that regulate the T-cell response may be associated with lymphoma risk. Methods: We genotyped 257 single nucleotide polymorphisms (SNPs) from 50 candidate genes related to T-cell differentiation and function in a clinic-based study of 441 Caucasian NHL cases and 475 frequency matched Caucasian controls seen at the Mayo Clinic from 2002–2005. Tagging and nsSNPs were selected from HapMap. The most prevalent homozygous genotype was used as the reference group and each SNP was modeled individually as having a log-additive effect, expressed as ordinal odds ratios (OR) per variant allele and 95% confidence intervals, in an age- and sex-adjusted logistic regression analysis. We also evaluated the consistency of the findings for the most common types of B-cell NHL - diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and CLL/SLL. For gene-level analyses, we used principal components (PC) analysis using all SNPs from a gene; those PCs that explained > 90% of the variability were then modeled in a logistic regression analysis and significance was determined using a likelihood ratio test. We also evaluated the association of haplotypes from each gene with risk of NHL using the score test implemented from HAPLO.SCORE. Results. The mean age at diagnosis was 60.1 years for cases and 58% were male; among controls, the mean age at enrollment was 61.7 years and 55% were men. In the PC gene analyses, PRF1 (perforin gene - involved in cytotoxicity; p=0.004), CD276 (B7-H3 gene - involved in co-stimulation; p=0.01), TBX21 (T-bet gene – regulates Th1 cell development; p=0.02), and IL6 (p=0.02) were significant at p<0.05; haplotype analysis showed similar results, with the addition of CARD15 (NOD2 gene – regulates Th1 responses; p=0.02). There were 2 SNPs in PRF1, and both the intronic SNP rs3758562 (OR=1.38; 1.13–1.69) and the synonymous coding SNP rs885821 (OR=0.80; 0.63–1.02) were associated with NHL risk overall and for each subtype. There were 2 SNPs in CD276, and both the intronic SNP rs7176654 (OR=1.29; 1.07–1.56) and the mrna-utr SNP rs3816661 (OR=0.82; 0.68–0.99) were associated with NHL risk overall and with the CLL/SLL and follicular NHL subtypes specifically. There were 2 SNPs in TBX21, and only the mrna-utr SNP rs7502875 (OR=0.73; 0.59–0.92) was associated with NHL risk overall and for each subtype. There were 11 SNPs in IL6, and the intronic SNP rs2069835 (OR=1.88; 1.24–2.84) and the locus-region SNP rs2069824 (OR=1.73; 1.20–2.50) were each associated with NHL risk overall and each subtype. Finally, there were 9 SNPs in CARD15, with only the nonsynonymous coding SNP rs5743291 (OR=1.43; 1.02–1.98) being associated with overall NHL risk, and risk was specific to FL. Conclusions. Genetic variation in several genes that play critical roles in T-cell maturation and function was associated with lymphoma risk. These genes appeared to be associated with the differentiation and function of effector T-cells particularly Th1 and Th17 cells. These results provide potentially important insights into the role of T-cells in lymphomagenesis.

Abstract Abstract 88 Introduction: The biology and genetics of anaplastic large T-cell lymphomas (ALCLs) lacking ALK translocations remain poorly defined. We recently identified recurrent translocations involving the DUSP22-IRF4 locus on 6p25.3 in ALK-negative ALCL (Blood 2011;117:915–9). This translocation is present in about 20% of ALK-negative ALCLs and is absent in other T-cell lymphomas; however, the biologic consequences are unknown. In this study, we utilized gene expression profiling (GEP) to compare T-cell lymphomas with and without this translocation. Methods: cDNA was prepared from total RNA extracted from frozen tissue from 25 T-cell lymphoma patients under a Mayo Clinic IRB-approved protocol as follows: 5 ALK-negative ALCLs with 6p25.3 translocations (2 systemic, 3 cutaneous), 12 ALK-negative ALCLs without 6p25.3 translocations (11 systemic, 3 cutaneous), 5 ALK-positive ALCLs, and 3 CD30-positive peripheral T-cell lymphomas (1 transformed mycosis fungoides and 2 not otherwise specified). Partner loci in cases with 6p25.3 translocations were 7p32.3 in 2, 9p24.3 in 1, and unknown in 2. GEP data (Affymetrix U133 plus 2.0) were analyzed by unsupervised clustering; in addition, a GEP signature was developed using genes with raw values >200 in at least 2 cases with at least 2-fold, statistically significantly different expression between 6p25.3-translocated and non-translocated cases (p<0.05 after Benjamini-Hochberg multiple testing correction). Representative overexpressed genes were confirmed by quantitative real-time (qRT-) PCR. Supervised pathway analysis was performed using signatures derived from other studies or curated from public pathway databases. Results: By unsupervised clustering, the 5 cases with 6p25.3 translocations clustered together (281 probe sets). A GEP signature segregating translocated from non-translocated cases included 283 genes (195 up- and 88 down-regulated). Key features of this signature included altered expression of histone-modifying genes (e.g. EZH2, SUZ12, MLLT3, MLL; HDAC4) and up-regulation of cancer-testis antigen (CTA) genes (e.g. SSX4, TEX14, MAGEA12, SSX1, CTAG2). The signature included down-regulation of DUSP22 but not of other genes on 6p25 in the signature. Additional overexpressed genes were validated by qRT-PCR (relative expression: TEX14, 2.9, p=0.01, t test; MAL, 6.5, p=0.003; CCR8, 7.6, p=0.0004). Supervised pathway analysis demonstrated a high proliferation signature in cases with 6p25.3 translocations (p=0.006 vs. untranslocated cases). Conclusions: ALK-negative ALCLs with translocations involving the DUSP22-IRF4 locus on 6p25.3 have a distinct gene expression signature characterized by alterations of histone-modifying genes and CTA genes (which typically are regulated epigenetically, either through histone modifications or changes in methylation). This signature appears independent of anatomic site (systemic vs. cutaneous) and partner locus (7p32.3 vs. other). DUSP22, encoding a dual-specificity phosphatase involved in modulating mitogen-activated protein kinase (MAPK) signaling, is significantly down-regulated in translocated cases; however, pathway analysis did not show significant alterations in MAPK-associated genes. Other known genes in the region of the breakpoint on 6p25 were not affected substantially. These findings suggest the possibility of an unrecognized function of DUSP22. Contributions of the varying partner loci remain unclear. The distinct GEP signature associated with 6p25.3 translocations provides strong support for their biologic relevance. Finally, the genes involved in the histone-modifying signature show overlap with histone-modifying genes mutated in B-cell lymphomas, suggesting potential commonalities in the biology and possibly targeted treatment of B- and T-cell lymphomas. Disclosures: No relevant conflicts of interest to declare.

Abstract Massively parallel sequencing analyses have revealed a common mutation within the MYD88 gene (MYD88L265P) occurring at high frequencies in many non-Hodgkin lymphomas (NHL) including the rare lymphoplasmacytic lymphoma, Waldenström’s macroglobulinemia (WM). Using whole exome sequencing, Sanger sequencing and allele-specific PCR, we validate the initial studies and detect the MYD88L265P mutation in the tumor genome of 97% of WM patients analyzed (n=39). MYD88L265P was detected at lower frequencies in other indolent lymphomas including LPL (0%), MALT (4%), nodal MZL (5%) and splenic MZL (8%); all but one MYD88L265P was heterozygous. Due to the high frequency of MYD88 mutation in WM and other NHL, and its known effects on malignant B cell survival, therapeutic targeting of MYD88 signaling pathways may be useful clinically. However, while the effects of MYD88L265P on the activity of IRAK1/4 and NF-κB are have been studied previously, we are lacking a thorough characterization of the role of intermediary signaling proteins such as TRAF6 and TAK1 on the biology of MYD88L265P-expressing B cells. A better understanding of the proteins involved in MYD88L265P signaling may lead to the development of more targeted and effective therapeutic approaches. In an attempt to identify MYD88L265P –specific therapeutic targets we first wanted to characterize the role of intermediary signaling proteins that facilitate the downstream activation of NF-κB. Upon activation of TLRs or IL-1b receptors, MYD88 forms a homodimer and recruits IRAK1/4 and TRAF6 into a complex resulting in association and phosphorylation of TAK1 followed by activation of NF-κB. We monitored the formation of a complex comprised of MYD88, IRAK1, IRAK4 and TRAF6 and immunoprecipitation of either endogenous IRAK4 or IRAK1 revealed constitutive association of IRAK with TRAF6 and MYD88L265P. To assess if the formation of a MYD88L265P/IRAK/TRAF6 complex results in downstream activation of TAK1, constitutive TAK1 phosphorylation was measured and detected in all three cell lines that express MYD88L265P. An association between TAK1 and TRAF6, another measure of TAK1 activation, was also detectable. When a similar analysis of TAK1 was performed in DLBCL cells expressing wild-type MYD88, no phosphorylation of TAK1 was detected, nor was TAK1 associated with TRAF6. IRAK1, IRAK4, TAK1, TRAF6, and MYD88 were expressed at similar levels in all cell lines studied and therefore did not contribute the differences in MYD88 complex formation observed between cell lines. These studies were further confirmed using HEK 293T cells that were transduced with either a vector control plasmid or HA-tagged MYD88WT or MYD88L265P expression plasmids. Together, these studies suggest that MYD88L265P forms a complex with IRAK and TRAF6 resulting in constitutive activation of TAK1 and NF-κB. To confirm the significance of TAK1-mediated MYD88L265P signaling on lymphoma cell growth, the effect of the selective TAK1 inhibitor, (5Z)-7-Oxozeaenol, on cell proliferation was tested. All MYD88L265P-expressing cell lines were sensitive to TAK1 inhibition in a dose-dependent manner (0-10 μM). In contrast, NHL cells expressing MYD88WT were found to be insensitive to TAK1 inhibition. We next tested the impact of the TAK1 inhibitor on a MYD88L265P positive WM patient sample. Similar to what was seen in the WM cell lines, the TAK1 inhibitor inhibited WM cell growth and survival in a dose dependent manner. Additionally, the TAK1 inhibitor significantly reduced the level of IL-10 secreted by each of the cell lines. Together, these data suggest that MYD88L265P drives cell proliferation and cytokine secretion through a TAK1-dependent mechanism. In conclusion, we are the first to validate by NGS in a large patient cohort the high prevalence and specificity of MYD88L265P in WM. Cells harboring the L265P mutation but not wild-type MYD88 exhibit constitutive signaling leading to the hyperactivation of NF-κB. We have established the role of TAK1 as an integral component of MYD88L265P signaling in both WM and DLBCL cell. Our data suggest that targeting TAK1 clinically may be an effective strategy for the treatment of WM and other lymphomas driven by MYD88L265P signaling. Disclosures: Fonseca: millennium: Consultancy; amgen: Consultancy; Binding site: Consultancy; onyx: Consultancy; medtronic: Consultancy; Genzyme: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; lilly: Consultancy; Onyx: Research Funding; cylene: Research Funding.

Abstract Abstract 960 Diffuse large B cell lymphoma (DLBCL) is an aggressive lymphoma whose survival depends on various signaling pathways one of which is Signal transducer and activator of transcription 3 (STAT3)/Janus kinase 2 (JAK2). We have demonstrated that JAK2 is constitutively activated at the auto-phosphorylation site in many cases of DLBCL. The most common mechanism causing abnormal JAK2 activation is through dysregulated cytokine signaling. Cytokines are deregulated in several hematological malignancies and may play a role in tumor cell growth through receptor-mediated and ligand dependent activation of the JAK2 kinase. In this study we investigated the role of cytokine signaling in JAK2 activation in DLBCL and use of a novel JAK2 inhibitor (JAK2i) to inhibit IL-10 induced JAK/STAT signaling. We studied serum cytokines from 70 patients with new untreated DLBCL who participated in a clinical trial in the North Central Cancer Treatment Group (Micallef, IN et al Blood 2011). Compared to control sera, patients with DLBCL had higher levels of several JAK2 kinase related cytokines (IL-2, IL-6, IL-10, and EGF). IL-10 and IL-6 were significantly higher in DLBCL patients vs controls with p values >0.03 and >0.001, respectively. We next examined whether DLBCL cell lines produced IL-10. The phospho-JAK2 (pJAK2) positive DLBCL cell lines Ly10, DHL2 and HBL1 produced more IL-10 (40–80 pg/ml) than the pJAK2 negative cell lines Ly1, Ly19 and DHL6 (0–5 pg/ml). Analysis of the surface expression of IL-10 receptors (IL-10R) determined that most p-JAK2 positive DLBCL cells express either IL-10Ra or IL-10Rb or both. IL-10 had no effect on DLBCL cell survival in vitro; however, it did promote their proliferation. Only IL-10 (but not the other elevated cytokines) was specifically able to activate JAK2 and STAT3 phosphorylation in a subgroup of DLBCL cell lines. IL-10 was not able to activate JAK1, STAT1 and STAT5, which suggests a specific role of IL-10 in the JAK2 pathway. Moreover, neutralizing antibody to IL-10 inhibited IL-10-induced JAK2 and STAT3 tyrosine phosphorylation. We studied the effect of SAR302503 (SAR503, Sanofi, Cambridge, MA), a selective JAK2i currently in clinical trial for myelofibrosis on constitutive JAK2 signaling in DLBCL cells. SAR503 was able to inhibit JAK2 and STAT3 phosphorylation in a dose and time dependent manner in a variety of DLBCL cell lines and patient samples. JAK2 inhibition with SAR2503 caused a dose-dependent inhibitory effect on survival of pJAK2 positive DLBCL cells not observed in pJAK2 negative cells. Activation of STAT3 signaling up-regulates the expression of various genes involved in cell survival and proliferation such as bcl-xl, bcl-2, mcl-1 and c-myc. We observed a dose-dependent decrease in c-myc protein and mRNA levels in Ly3 and DHL2 cells with SAR503 treatment; however, SAR503 did not effect expression of bcl2, mcl-1 and bcl-xl proteins in DLBCL cells. Interestingly, JAK2 inhibition with SAR503 inhibited the autocrine secretion of IL-10 in a dose-dependent manner. Next, we determined if higher pre-treatment serum IL-10 correlates with the overall survival of 81 DLBCL patients. IL-10 by ELISA demonstrated that IL-10 levels were high in 51% (41/81) of patients (median, 57.7pg/ml; range, 26.1–503.7), and low in 49% (40/81) (median, 15.9 pg/ml; range, 0–25.9). Using a cut-off value of 26.1pg/ml, patients with a high serum IL-10 level had a significantly worse event-free survival (p=0.01). Clinical correlation of serum IL-10 with disease parameters showed that the IL-10 level was correlated with elevated serum LDH (p= 0.0085) and IPI score (p=0.01); there was no correlation with the number of extranodal sites, age, or B symptoms. DLBCL tumors from 40 patients were classified into germinal center B-cell type (GCB) and non-GCB type using the Hans algorithm. There was a clear trend towards a higher serum IL-10 in non-GCB DLBCL patients (p <0.06). In summary, our data identifies mechanisms of JAK2 kinase activation in DLBCL and supports the hypothesis that the IL-10-JAK2-cmyc pathway is activated in patients with DLBCL. Finally our data provide a mechanistic basis of selecting and targeting DLBCL tumor cells with high IL-10 levels and/or constitutive JAK2 activity with potent and novel JAK2 inhibitors such as SAR503. Disclosures: No relevant conflicts of interest to declare.

Abstract The amyloidoses are heterogeneous diseases associated with the deposition of insoluble proteins or peptides with a characteristic beta-diffraction pattern extracellularly. At the current time, over 27 different extracellular fibril proteins are known to cause disease in humans. Iatrogenic amyloidosis is a rare, often not sought diagnosis. On occasion, patients with drug induced amyloidosis can present with other systemic features reminiscent of systemic immunoglobulin-derived (AL) amyloidosis, and may present a diagnostic challenge. Treatment of the latter often involves chemotherapy and/or stem cell transplantation, while the former tends to remain localized and needs local therapy; thus accurate diagnosis is critical. To this end, proteomic analysis of amyloid tissue has proven to be an invaluable tool in amyloid typing. We have analyzed the biochemical composition of iatrogenic amyloid using laser capture/tandem mass spectrometry (LC-MS/MS)-based proteomic analysis in 52 cases of insulin and enfuvirtide (Fuzeon¨) associated amyloidosis. In brief, 10-μm-thick sections of formalin-fixed paraffin-embedded tissues were stained with Congo red. Congo red positively staining tissue as viewed with a fluorescent light source appeared bright red. Positive areas were dissected using laser microdissection to a volume of at least 60,000 μm2; three microdissections were analyzed for each case. The microdissected material was collected into 0.5-ml microcentrifuge tube caps containing 35 μL Tris/EDTA/0.002% Zwittergent buffer. Microdissected fragments were subjected to a heat-mediated antigen retrieval method (98C for 90minutes) before being denatured via sonication and subsequently digested into tryptic peptides overnight using 0.5ug of trypsin. The resulting digests were then analyzed with nanoflow LC-MS/MS. The MS/MS spectra of each case were matched against a composite protein sequence database using three different search algorithms (Sequest, X!Tandem, and Mascot). The composite database contained the human SwissProt entries but was also augmented with known immunoglobulin variant domains, known amyloidogenic mutations from literature, the enfuvirtide amino acid sequence, and common contaminants. Reversed protein sequences were appended to the database for estimating the false discovery rates of the identifications. The peptide identification results were filtered using Scaffold software (Proteome Software, Portland, OR) and then filtered peptides were assembled into protein identifications. Candidate proteins with at least one high-confident (probability of identification &gt;90%) unique peptide identification and at least four MS/MS spectral matches were considered for clinical interpretation. For each case, we created a personalized proteomic profile that lists all the confident protein identifications in each of the microdissection along with their respective MS/MS spectral counts. The number of MS/MS spectra matching to a protein is considered as a semi-quantitative measure of its abundance. The most abundant amyloidogenic protein detected across all microdissections and as interpreted in the context of the clinical history is considered to be the amyloid subtype. Figure 1 shows the results of insulin amyloidosis. Figure 2 shows the results of enfuvirtide amyloidosis. Amyloid deposits are shown to be composed of the recombinant drug in addition to amyloid precursor proteins such as apolipoprotein A-I, A-IV, E and serum amyloid P (SAP).Figure 1. Insulin-associated amyloidosisFigure 1. Insulin-associated amyloidosisFigure 2Enfuvirtide (Fuzeon¨)-associated amyloidosisFigure 2. Enfuvirtide (Fuzeon¨)-associated amyloidosis In conclusion, we show the biochemical composition of all known drug-induced iatrogenic amyloidosis and provide the utility of proteomic analysis in elucidating amyloid subtyping for accurate diagnosis and management. Legend: A spectral count number of greater than 4 is significant. The green boxes denote protein identification at a probability of over 95%, and yellow 80-94%. In figure 1, insulin (# 2) and in figure 2, enfuvirtide (#5) are shown in abundance, additionally other amyloid precursors such as apolipoproteins A-IV, E, A-I and SAP are also seen. Disclosures: No relevant conflicts of interest to declare.

Abstract To further understand the molecular biology of mucosa-associated lymphoid tissue (MALT) lymphoma, we conducted a comprehensive gene expression study on the Affymetrix platform using total RNA extracted from biopsy specimen of 35 well-characterized pulmonary MALT lymphoma samples and compared them to gene expression profiles of a range of B and T cell lymphoma, such as Burkitt’s lymphoma, diffuse large B-cell lymphoma, Waldenstrom macroglobulinemia, chronic lymphocytic leukemia, multiple myeloma, and peripheral T-cell lymphoma, and normal cellular counterparts, such as different B-cell and T-cell populations, normal plasma cells and lung tussue. Analytical strategies were adopted to negate tissue specific effect such that our results can be generalized to MALT lymphoma from other anatomical sites. We further analyzed the data using functional tools such as gene-set enrichment analysis and gene ontology. Network/pathway analysis was performed using Metacore. Unsupervised clustering of whole dataset (including other lymphoid malignancies and normal cellular counterpart) using genes with variable expression, showed that compared to other B-cell lymphoid malignancies, MALT lymphoma have a prominent T-cell signature. Using established gene expression of different B-cell compartment, we confirmed that MALT has a marginal zone B-cell and memory B-cell cell-of-origin signature. Using ANOVA with post-hoc pair-wise comparison, we identified 4 novel transcripts over-expressed in MALT but not other B-cell tumors, and validated one of these using immunohistochemistry. MALT lymphoma with t(11;18) or t(14;18) over-expressed genes enriched for pathways other than the NFKB pathway such as JAK-STAT and SRC signaling pathways, which may represent novel therapeutic targets. We identified a number of genes with ‘outlier’ expression including RARA and RGS13. However, translocation involving RARA and the immunoglobulin heavy chain locus was not detected by FISH, suggesting other mechanisms of deregulating gene expression were involved. Using unsupervised clustering of only the MALT samples, we found that the molecular heterogeneity within MALT is composed of a group characterized by MALT1 translocations and another group with plasmacytic differentiation. Interestingly, further refinement of this grouping can be achieved by clustering the samples based on ‘outlier’ gene expression. Samples with MALT1 translocations have high expression of RARA, samples with plasmacytic differentiation have high FKBP11 expression and samples with high RGS13 expression tend to have trisomy 3 and reactive follicles. Our study therefore identified novel molecular markers, deregulated pathways and genetic defects in MALT. Furthermore, subgroups with distinct pathological features and anchored by unique pattern of ‘outlier’ gene expression were identified.

Abstract Background Immunoglobulin light chain-associated amyloidosis (AL) is caused by deposition of immunoglobulin light chain molecules with unique, clonotypic variable (V) regions. Detection and identification of the V region, however, has been challenging due heterogeneity inherent in V regions. We developed a new method for detecting IGKV and IGLV region fragments in AL deposits using protein mass spectrometry and novel bioinformatics approach. We report distinct IGKV and IGLV usage in localized versus systemic AL. Methods Shotgun protein mass spectrometry on amyloid plaques was performed as previously described (Blood. 2009; 114: 4957-9). Peptide tandem mass spectra (MS/MS) were searched against a composite sequence database containing SwissProt's human complete proteome augmented with 1764 IG V region sequences obtained from ImMunoGeneTics database and a Mayo Clinic internal database. Reversed sequences were appended to the database for estimating identification false discovery rates (FDRs). Peptide identifications were processed with Scaffold software. Confident protein identifications (probability > 0.9) with at least one unique peptide identifications and five MS/MS matches were considered. Detected variable gene family (if any) with most number of peptide and spectral matches is considered to be present in the deposit. The method was first validated in 8 cases of AL amyloidosis with known IGKV and IGLV region sequences and then applied on 1238 systemic and 393 localized AL cases. Differences between groups were measured by generating hypergeometric p-values. Results In all 8 AL cases with known IGKV and IGLV region usage, gene family identified in the AL deposit via proteomics matched the gene family inferred from bone marrow plasma cells by Sanger sequencing of IGLC genes. Armed with this method, we analyzed the amyloid proteomics data from 1238 patients with systemic AL amyloidosis and 393 patients with localized AL amyloidosis. The anatomical site distribution in systemic cohort was 296 GI tract, 364 heart, 225 kidney, 81 liver and 272 fat aspirate; Localized cohort has 78 bladder, 158 lung and 157 skin cases. Figure 1 shows the normalized frequency of the variable gene families detected between the systemic and localized AL amyloidosis. For AL-kappa, KV1 was more prevalent in systemic cases when compared to localized cases (p=7.2E-12) suggesting KV1 clones as a hallmark for systemic AL-kappa amyloidosis. KV3 was more frequently seen in localized AL-kappa cases when compared to systemic AL-kappa cases (p =2.8E-11). For AL-lambda, LV1 and LV2 gene families were more prevalent in localized cases when compared to systemic cases (p= 0.039 and 2.7E-05). LV6 was more prevalent in systemic AL-lambda cases (p=1.4E-07). We also detected a higher incidence of mixed AL/AH type in localized AL (18%) when compared to systemic AL (5%; Odds Ratio=4.2673, p<0.0001). We next turned to the organ specific IGKV and IGLV gene family usage patterns in patients with localized amyloidosis. For 147 localized AL-kappa cases, KV3 was most dominant in lung (64%) and KV1 was dominant in skin (38%). For 246 localized AL-lambda cases, LV2 was most prevalent in lung (34%) and LV3 was most prevalent in skin (36%). For bladder, both LV1 and LV2 had comparable prevalence (42% and 32%). For 361 systemic AL-kappa cases, KV1 consistently ranked at the top of gene families used in GI tract (55%), heart (71%), kidney (59%), liver (75%) and fat aspirate (50%). For 877 systemic AL-lambda cases, LV2 was predominant in GI tract (30%), LV3 in heart (35%) and LV6 in kidney (33%). The prevalence of LV1, LV2 and LV3 in liver is comparable (36%, 22% and 31%). LV6 and LV3 had comparable prevalence (22% and 24%) in AL-lambda fat aspirates. Conclusion The novel proteomics method detects IGLC V family usage in large cohorts of AL patients. It identifies unique profiles in systemic and localized cases, and in different organ sites. This information will be helpful in determining systemic versus localized nature of AL amyloidosis at diagnosis and to assess risk of specific end organ involvement. We found also a strong association between IGKV and IGLV gene usage and organ involvement. Disclosures: No relevant conflicts of interest to declare.

Abstract Amyloidosis is a group of hereditary and acquired disorders of diverse pathogenesis united by end organ damage due to tissue deposition of misfolded proteins. The diagnosis is typically based on demonstrating Congo red positive amyloid deposits in tissue biopsies of clinically involved sites. Because treatment options for amyloidosis patients are highly varied and intricately tied to the identity of the protein that constitutes the amyloid deposits, adequate diagnostic evaluation now requires identification of the amyloidogenic protein. Traditionally, immunohistochemistry with antibodies to amyloid-associated proteins was the clinical technique of choice for subtyping amyloid deposits in tissue sections. This technique suffers from poor analytical sensitivity and specificity and is a suboptimal technique on which to base treatment decisions for amyloidosis patients. We developed a highly accurate and reproducible liquid chromatography electrospray tandem mass spectrometery (LC-MS/MS)-based shotgun proteomics assay for subtyping amyloid deposits (Blood. 2009; 114: 4957-9) from microdissected paraffin embedded tissue samples. Implementation of this assay in a CAP/CLIA clinical laboratory has subsequently transformed the standard of amyloidosis care at Mayo Clinic. Since 2008, we utilized the assay in routine practice to identify 20 different amyloid types in tissue samples from diverse anatomic sites from 4139 patients (Table 1). Although AL and ATTR were most common, the cases include a large variety of unusual, and in many cases clinically unsuspected amyloid types. In addition, the amyloid protein subtypes had different frequencies in different anatomic sites (A partial list of tissue sites and their amyloid types analyzed in this study includes: bone marrow: AL 82%, ATTR 15%, AA 2%, other 1%; kidney: AL 51%, ALect2 18%, AA 17%, AH 5%, AFib 4%, other 5%; liver: AL 64%, ALect2 23%, AApoA1 6%, AA 3%, ATTR 2%, other 2%; heart: ATTR 60%, AL 37%, AANF1%, other 2%; GI tract: AL 78%, ATTR 13%, AA 6% AApoA4 1%, other 2%; eye [primarily adnexae] AL 63%; eye [primarily cornea] TGFB induced protein ig-h3 34%, other 3%). One caveat is that these distributions of amyloid types may not accurately reflect population prevalence. More likely, the findings reflected a composite prevalence that included challenging amyloidosis cases.Table 1Frequency of amyloid subtypes observed in the Mayo Amyloid Cohort (n=4139). Asterisk denotes non-canonical subtypesAmyloid SubtypeNumber (%) of casesAL2553 (61.68)ATTR1015 (24.52)AA151 (3.65)ALect2148 (3.58)AIns48 (1.09)Keratin*36 (0.87)AApoA130 (0.72)AH27 (0.65)AFib26 (0.63)TGFB1-IP*22 (0.53)AApoA420 (0.48)AANF14 (0.34)Ab2M12 (0.29)AGel12 (0.29)ASem112 (0.29)APro7 (0.17)ALys3 (0.07)ACal2 (0.05)Enfuvirtide*2 (0.05)AIAPP2 (0.05) The prevalence of diverse and unexpected amyloid types in many tissues suggest that shotgun proteomic-based analysis may be the only way to accurately assign amyloid subtype in tissue samples. The technique avoids the analytical problems of immunohistochemistry and the bias introduced by assigning probable amyloid type based on clinical presentation and disease distribution. It provides the clinician with an amyloid subtype that allows for confident individualized patient management. Accurate amyloid subtyping by LC-MS/MS is not only possible, but has proven to be a robust routine clinical tool for the evaluation of numerous amyloidosis patients in our practice. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 3927 Poster Board III-863 In previous studies we characterized the 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. As part of a larger MALT gene expression-profiling project, we have now acquired gene expression analysis on the patient carrying the t(X;14)(p11;q32) translocation and have confirmed overexpression of GPR34. We then measured GPR34 mRNA expression in a panel of MALT lymphomas (n=17) and found that GPR34 was expressed at levels higher than that seen in normal B cells (mean, 11.3 fold; median, 5.5; range, 1.4-64 fold). When analyzed separately, 70% (12/17) had an expression level greater than 3-fold over normal B cells. Of note, in a gastric MALT lymphoma specimen, we found a 64 fold increase in GPR34 mRNA expression. FISH studies performed on this specimen showed an extra intact GPR34 signal but no translocation involving IGH or GPR34, suggesting that other mechanisms, including gene dosage effect, can upregulate GPR34. Elevated expression of GPR34 mRNA was also detected in other histologic types of NHL, but not to the extent seen in MALT lymphoma. Taken together, these data suggest that GPR34 is commonly overexpressed in MALT lymphoma and that deregulation of GPR34 expression can occur independent of a t(X;14)(p11.4;q32) translocation. The receptor encoded by GPR34 is most similar to the PY2 receptor subfamily of GPCR and GPR34 mRNA transcripts are abundant in mast cells while lower levels were detected in other immune cells including B cells. Signals from GPR34 have been briefly described and the results to date suggest that overexpression of GPR34 results in an accumulation of inositol phosphates. To further characterize the impact of GPR34 overexpression on cell signaling, HeLa cells were transduced with a retroviral expression plasmid (pBMN-GFP) that expresses GPR34 and GFP. GFP expressing cells were isolated and overexpression of GPR34 mRNA was confirmed by PCR and GPR34 protein expression was detected by flow cytometry. When normalized to the isotype control, pBMN-GPR34 cells expressed 17-fold more GPR34 on their cell surface compared to the pBMN-vector control cells. To determine which signaling pathways were affected by GPR34 overexpression, pBMN-GPR34 or pBMN-vector control cells were transfected with an AP-1, CRE, NF-κB, E2F, SRE, NFAT, or ISRE- luciferase reporter plasmid. Upon normalization with renilla, pBMN-GPR34 expressing cells had increased luciferase activity (n=3) driven by AP-1 (5.35-fold), CRE (4.7), NF-κB (2.8-fold), and E2F (2.13) when compared to pBMN-vector control cells. ISRE, NFAT, and SRE mediated luciferase expression was similar in the GPR34 and control cells. 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. To determine if MAPK activity was also upregulated in GPR34 expressing cells, we analyzed the phosphorylation status of Erk1/2 in pBMN-GPR34 cells by western blot and found that Erk1/2 was constitutively phosphorylated in GRP34 expressing cells (1.8 fold increase) compared to vector control cells. Increased phosphorylation of PKC-α/β was also detected in pBMN-GPR34 cells (3.5 fold increase compared to control cells). To determine the biologic impact of GRP34 overexpression on cell growth, the proliferation rates of pBMN-control and pBMN-GPR34 cells were compared and it was found that proliferation of GPR34 expressing cells was 2.2 times higher than that seen in control cells. Because the MAPK kinase pathway was found to be active in the pBMN-GPR34 cells, we tested the effect of the MEK inhibitor PD98059 on proliferation and saw a dose dependent decrease in proliferation of GPR34 expressing cells. These results suggest that GPR34-mediated proliferation is Erk-dependent. In summary, these data suggest that deregulation of GPR34 is commonly found in MALT lymphoma and that overexpression of GPR34 results in activation of Erk1/2, phosphorylation of PKC, and results is AP-1 and CRE mediated transcription. Additionally, our data suggest that overexpression of GPR34 results in increased cell growth that is MAPK-dependent. Taken together, this studies indicate that overexpression of a GPCR, GPR34, may be a novel mechanism by which MALT, lymphoma, and potentially other subtypes of NHL, develop. Disclosures: No relevant conflicts of interest to declare.