Braggio, Esteban

Abstract Despite recent advances and improvement in treatment options, chronic lymphocytic leukemia (CLL) is still an incurable disease. Recent advancement in parallel sequencing technology has provided better understanding of genetic landscape and clonal architecture underlying disease course. Furthermore, mutation status of TP53, SF3B1, NOTCH1, and BIRC3 has improved current CLL risk stratification. In order to better understand the genetic basis and clonal evolution underlying disease progression we analyzed a homogeneously treated cohort of CLL cases at multiple time points before and after therapy. We performed WES in 30 sequential samples from 12 CLL cases. All 12 cases received PCR (pentostatin, cyclophosphamide and rituximab) based chemoimmunotherapy as initial treatment. Of these 12 cases, two had samples available both >6 months prior to enrollment and at treatment initiation, seven patients who experienced relapse had samples available at both treatment initiation and at and the time of relapse, and three patients had samples >6 months prior to enrollment, at treatment initiation, and at relapse. These cases were previously characterized by aCGH/FISH. R function Mclust and kernel density estimate (KDE) plots were used to identify subclonal heterogeneity. An average of 102-fold depth coverage was obtained with an average of 80% of the targeted regions being covered by at least 30X. Overall, we detected a total of 219 nonsynonymous Single Nucleotide Variants (SNV) and indels (average 19, range 11-33). Del13q (42%) was identified as most prevalent copy number abnormality followed by trisomy 12 (33%), del11q and del17p (17% each). Recurrent mutations were identified in NOTCH1 (33%), DDX3X (25%), TP53, SF3B1 XPO1 and MED12 (17% each). Other tumor implicated genes such as CARD11, NOTCH2, NOTCH4, DIS3, TRAF2, NFKBID, CHK2 and RB1 were found mutated in individual cases. In all 12 cases we identified at least one relevant cytogenetic abnormalities (del11q32, del13q14, del17p13, trisomy 12) and/or a mutated driver gene. Interestingly we found NOTCH1, DDX3X and XPO1 mutated at a significantly higher prevalence than previous studies (10%, 2% and 4%, respectively). Since all cases in our cohort correspond to individuals with progressive disease, a plausible explanation for the higher prevalence of mutations in our cohort is that these mutations are associated with disease progression. By WES we identified multiple subclones in 58% of cases (7 of 12 cases), as compared to previously identified 33% (4 of 12 cases) by CGH/FISH. In 5 chemotherapy naïve cases, no significant increase in genomic complexity was detected with disease progression. In contrast, 5 out of 10 cases with samples analyzed before CIT and at the time of relapse had changes in clonal dynamics, with initially dominant subclones diminishing in response to therapy and the available empty niche being occupied by expansion of another “fitter” subclone at the time of relapse. No acquisition of tumor associated gene mutations was seen post therapy or associated with relapse in 9 of 10 cases. In the remaining case we identified an interesting example of convergent evolution. The pre-therapy sample was comprised of a unique clone characterized with del11q13, mutations in SF3B1 (G742D) and DDX3X (pE196fs). After therapy that clone was either eradicated or reduced to below detection level. Interestingly another clone emerged after relapse that harbored an independent del11q22 and mutations affecting different aminoacids of SF3B1 (K700E) and DDX3X (pL21fs). The strong selection of impairment in these genes during disease progression suggests a key role of these pathways/genes in the pathogenesis of this patient. In conclusion, these studies provide additional insight into the genomic landscape and clonal architecture in a cohort of homogeneously treated CLL cases before and after therapy. Stable clonal architecture was seen in prior to treatment, whereas clonal evolution leading to increased tumor heterogeneity occurred after the under selection selective pressure of therapy in relapsed cases. Early identification of tumoral heterogeneity and underlying genetic abnormalities might provide better targets for therapy to decrease the likelihood of relapse. Disclosures: Fonseca: Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties. Shanafelt:Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is defined as somatic mutations in clonal blood cells of individuals without any other hematological abnormalities and have been identified using whole exome sequencing (WES) from pre-specified genes. CHIP is reportedly associated with aging, reduced overall survival, cardiovascular disease, and hematologic disease, mainly myeloid cancers. Additionally, whole genome sequencing and WES studies in CLL cases have identified putative CLL driver genes with recurrent somatic variants or copy number alterations. Here, we investigate the associations of CHIP and mutations in CLL somatic driver genes with risk of CLL and MBL, a precursor to CLL. Using WES, 571 individuals from 132 CLL families were sequenced from two different sites, Mayo Clinic (92 families) and National Cancer Institute (NCI, 40 families), including 251 CLLs, 74 MBLs, and 246 unaffected relatives. DNA was extracted from buccal cells (Mayo Clinic) and peripheral blood (NCI). Allele counts from gVCF files were extracted for specific genes and analyzed. Variants were annotated using the Variant Effect Predictor in Ensembl, genome build GRCh37 (http://useast.ensembl.org/index.html). Highly-sensitive flow cytometry of the blood was used to screen for MBL. CHIP was defined as in Genovese et al., 2014 as the presence of any of the following: A) disruptive mutations in ASXL1, TET2, or PPM1D; B) missense mutation p.617F in JAK2; C) disruptive or missense mutations in DNMT3Alocalized to exons 7 to 23D) any mutations reported at least 7 times in hematological malignancies in the Catalogue of Somatic Mutations in Cancer (COSMIC); and (E) No variant allelic fraction (VAF) threshold. CLL driver genes included disruptive or missense mutations in ATM, BIRC3, MYD88, NOTCH1, SF3B1, TP53, EGR2, POT1, NFKBIE, XPO1, or FBXW7with VAF greater than 0.1. Mutations from COSMIC and CLL driver genes were excluded if the minor allele frequency in 1000 Genomes was greater than 0.5%. Data was analyzed using logistic regression adjusting for age, sex, and site. Odds ratios (OR) and 95% confidence intervals (CI) were estimated. Median age for CLL, MBL, and unaffected was 63, 61.5, and 54, respectively. The unaffected relatives were significantly younger than both the CLL and MBL groups (p<0.0001), with no difference between CLL and MBL (p=0.46). A total of 70 (12%) individuals from 54 different families had CHIP. CHIP was characterized in the majority of samples as mutations in DNMT3A, ASXL1, and TET2with 43, 9 and 8 individuals, respectively. As expected, CHIP was associated with age (p<0.001) but not sex (p=0.87). CHIP was present in 42 (17%) CLLs, 9 (12%) MBLs, and 19 (8%) unaffected relatives. There was a significant association between the presence of CHIP and CLL risk compared to unaffected relatives (OR= 2.19, 95% CI: 1.20 - 4.13, p=0.013) but not with MBL risk (OR=1.34, 95% CI: 0.54 - 3.11, p=0.51). Using the CLL driver genes, we found mutations in 119 (47%) CLL, 20 (27%) MBL, and 70 (29%) unaffected relatives. Mutations in CLL driver genes were associated with CLL risk compared to unaffected relatives (OR = 2.51, 95% CI: 1.64 - 3.87, p<0.0001), but there was no evidence for increased MBL risk (OR = 1.00). These results held when we subset the analysis to the Mayo only data where the DNA was extracted from buccal cells. This study further supports the association between mutations in CHIP related genes and risk of hematologic malignancies, in particular CLL. This is the first report of the prevalence of CHIP in MBLs. Although MBL and CHIP represent clonal population of blood cells, our data suggest the clones are different. Mutations in CLL driver genes are also associated with CLL risk but show little to no evidence with increased MBL risk. Interestingly, our unaffected relatives of CLL cases also had a high frequency of CLL driver mutations. Future studies are needed to understand these acquired mutations (both in CHIP- and CLL driver- related genes) in the unaffected to MBL to CLL continuum. Disclosures Parikh: Abbvie: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Research Funding. Ding:Merck: Research Funding. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Shanafelt:Jansen: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding. Kay:Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Background The precise molecular mechanism and targets of lenalidomide specific anti-Multiple Myeloma (MM) activity remain largely unknown, although, cereblon (CRBN) has been identified as a central mediator of activity with IRF-4 acting as a downstream molecule. Lenalidomide resistance in MM cells which, despite CRBN depletion, are able to restore their IRF-4 levels suggests the existence of alternative pathways. Methods To measure apoptosis and gene expression analysis 1x 106cells were incubated with 10μm to 50μm of lenalidomide for 24 to 96 hours before they were examined by annexin-PI and FACS analysis. Gene and protein expression were measured by RT-PCR, western blot, and immunohistochemistry. For lenalidomide followed bortezomib serial studies, cells were incubated with 10μm of lenalidomide for 48 hours and later treated with bortezomib for 24 to 48 hrs. CRBN and immunoglobulin light chain knock-down were performed by lentiviral mediated shRNA. Results We found lenalidomide induces Endoplasmic reticulum stress (ERS) via accumulation of intracellular immunoglobulin proteins, but only in the presence of CRBN in a panel of MM cell lines. This accumulation of intracellular proteins resulted in ERS as documented by western blot and RT-PCR in OPM2 and MMIS cell lines. We next utilized OPM2 cells knocked down for CRBN and control, non-target (NT), and treated with different doses of lenalidomide. After three days of treatment an ERS response was occurring in OPM2-NT cells but not in CRBN knockdown cells. Using Western blot we found decreased XBP-1u and increased XBP-1s, ERS marker proteins, in CRBN positive (NT) cells after 72 hours of lenalidomide treatment, but not in CRBN knock-down cells. Another ERS marker GRP78/BiP was also clearly accumulated after lenalidomide treatment in CRBN positive cells. Inactivation of the tumor suppressor p53 by degradation is a mechanism utilized by cells to adapt to ERS has been reported. We also found that p53 protein down regulated after lenalidomide treatment in CRBN positive OPM2 and MMIS cells. We have analyzed other isogenic cell lines MM1.S (lenalidomide-sensitive) and isogenic MM1.Sres (lenalidomide-resistant) HMCLs and found that lenalidomide induces ERS in MM1.S but not MM1.Sres cells. CRBN is important for lenalidomide to induce immunoglobulin protein accumulation and ERS was further proved by over-expressing CRBN in OCI-My5 MM cell line and subsequent lenalidomide treatment. To test the effect of light chain accumulation as ER stressors, we knocked down immunoglobulin light chain lambda in human MM cell line OPM2. Knock-down of lambda light chain in OPM2 cells resulted in lenalidomide resistance and it induced endoplasmic reticulum stress mediated anti-myeloma activity. Our preliminary data reveals that lenalidomide mediated progressive ERS can positively enhance bortezomib induced apoptosis in an in-vitro MM model. We pre-treated myeloma cell lines with lenalidomide and subsequently treated with bortezomib. MM cells pre-treated with lenalidomide for two days and there after treated with bortezomib clearly shown increased sensitivity to bortezomib induced apoptosis than non-pre-lenalidomide treated cells. Conclusion Here we show that lenalidomide causes accumulation of immunoglobulin light chains, inducing progressive ER stress, resulting in anti-myeloma activity and that effect depends on the presence of CRBN. Proteasome inhibitors such as bortezomib also sensitize MM cells to endoplasmic reticulum stress-mediated apoptosis. Our data demonstrated the synergistic effect of lenalidomide and proteasome inhibitors, likely due to the augmented protein stress. This data support the use of serial therapy utilizing pre-lenalidomide treatment followed by bortezomib or carfilzomib treatment. Disclosures: Fonseca: Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties.

Abstract Abstract 5093 A relative increase in proliferation is now accepted as the most important measure in risk stratification of myeloma. Attempts to include measures of proliferation in different stratification strategies have been met with obstacles largely influenced by their practicality and economic viability in the clinical setting. The plasma cell labelling index (PCLI) is the gold standard used in myeloma; however it is still only used in a minority of centers across the globe. New surrogate markers of proliferation, such as serum biomarkers and transcription-based methods, are under investigation but few have evolved to become part of a uniform strategy in the stratification of myeloma. The gene-expression based proliferation indices (gPI) described by Bergsagel et al, Shaughnessy et al and Hose et al all show similar correlation with PCLI. Studies comparing all currently available methods are lacking. In a cohort of 70 patients, PCLI and gPI were compared with two immunohistochemistry-based methods of measuring proliferation, Ki67 and a more specific measure of S-phase entry – phosphorylation of minichromosome maintenance protein 2 (pMcm2) at serine 40/41, combined with dual staining of CD138. We observed a similar correlation of gPI wth PCLI to that previously reported (r value; CI – 0.43;0.21–0.61). Both Ki67 and pMcm2 staining showed a stronger correlation with PCLI than with gPI and PCLI (r value; CI – 0.81;0.71–0.88 and 0.86; 0.78 – 0.91 respectively). PCLI and gPI have already been shown to be an independent predictor of time to progression and overall survival. Although this sample size was too small to test for time to progression or overall survival and thus independence, a logical extrapolation would indicate similar independence and predictions on survival and time to progression. As Ki67 is routinely used for more proliferative cancers in the clinic, the extension of its use as part of a new stratification system in myeloma provides interesting possibilities for further exploration. Disclosures: O'Dwyer: Novartis: Honoraria, Research Funding.

Abstract Abstract 2838 The combination of novel agents and chemo-immunotherapy (CIT) has led to a significant increase in both overall and complete response rates for chronic lymphocytic leukemia (CLL). There is, however, significant clinical heterogeneity in the overall effectiveness of CIT. Specifically, some patients are long-term responders who experience durable clinical remission while others, even though responding well initially, have less durable remissions. It is unclear if this heterogeneity is a reflection of an incomplete cytotoxic effect or whether certain leukemia sub-populations (i.e. subclones) are resistant to the effects of CIT. Comprehensive analysis of tumor cells has provided, in some malignancies, evidence of extraordinary genomic complexity and intraclonal genetic diversity. Conversely, little is known of the genetic architecture of the leukemic clone in CLL patients and the extent to which CLL tumor cells differentiate genetically at the subclonal level. In order to gain insight into the genetic architecture and clonal evolution underlying disease progression/relapse, we performed a sequential, longitudinal whole genome analysis by array-based comparative genomic hybridization (aCGH) in 22 CLL cases with evidence of clinical progression and/or clinical relapse post therapy. These patients received standard purine analogue, cyclophosphamide and rituximab (PCR) for progressive disease. For the purposes of this study, we classified samples as; time point 1 (TP1) collected >6 months before starting first-line CIT for disease progression; time point 2 (TP2) consisting of tumor samples at the time of initial progression requiring treatment; and time point 3 (TP3) consisting of tumor samples collected >6 months after initial treatment but prior to subsequent treatments. Overall, aCGH assay was performed in 54 samples from 22 cases (2 to 4 time points analyzed per patient): 6 cases were analyzed at TP1 and TP2, 8 at TP2 and TP3, 2 at TP1 and TP3, and the remaining 6 cases were analyzed at TP1, TP2 and TP3. In cases showing genetic changes between time points, FISH analyses were performed in 32 additional samples to assess intra-clonal diversity and provide a quantification of the clone size. There was a small increase in genomic complexity in later time points with a mean of 4 (median 4, range 0–12) CNAs detected at the first time point for each patient, increasing to a mean of 5.3 (median 4.5, range 0–21) CNAs at the last time point analyzed. Diverse patterns of changes in genetic architecture were observed. The simplest change in genetic architectures was the linear sequence, found in 2 cases (9%) and characterized by the maintenance of the initial abnormalities and the subsequent acquisition of additional CNAs in the same subclone. The pattern of changes in genetic architecture in another 4 patients (18%) demonstrated marked heterogeneity including multiple genetic subclones evolving either in succession or in parallel. In all 4 cases with multiple subclones, a marked shift in the dominant subclone was observed at the time of disease relapse, with the minor subclones at TP1 and TP2 becoming the dominant subclones at TP3. In addition, the subclonal evolution continued following secondary therapies, and in all 4 cases the emerging subclone showed resistance to multiple treatments. This argues strongly in favor of subclones with specific genetic structures becoming dominant with the selective evolutionary pressure imposed by therapy. In summary, this sequential genetic study reveals that CLL leukemic B cells exhibit an unanticipated level of heterogeneity including a variable number of genetically distinct subclones, which display dynamic behavior in disease progression. The characterization of this intraclonal architecture is of critical importance to better understand the mechanisms of disease progression and relapse as well as to ultimately inform us of individualized treatment strategies. Disclosures: Fonseca: Consulting :Genzyme, Medtronic, BMS, Amgen, Otsuka, Celgene, Intellikine, Lilly Research Support: Cylene, Onyz, Celgene: Consultancy, Research Funding.

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 2881 Multiple myeloma (MM) is characterized by a remarkable heterogeneity in outcome following standard and high-dose therapies. Significant efforts have been made to identify genetic changes and signatures that can predict clinical outcome and include them in the routine clinical care. Gene expression profiling (GEP) studies have achieved a central role in the study of multiple myeloma (MM), as they become a critical component in the risk-based stratification of the disease. To molecularly stratify disease-risk groups, we performed GEP on purified plasma cells (obtained from the immunobead selection of CD138+ cells) from 489 MM samples in different stages of the disease using the Affymetrix U133Plus2.0 array. A total of 162 probes were analyzed using an in house automated script to generate a GEP report with the most used risk stratification indices and signatures, including the UAMS 70-gene, UAMS class, TC classification, proliferation and centrosome signature, and NFKB activation indices. In a subset of 57 samples, IgH translocations were analyzed using FISH and results were correlated with GEP data. A macrophage index was calculated and used as a surrogate measurement of non-plasma cell contamination. A total of 49 samples (10%) were excluded from subsequent analysis as the macrophage index indicated a significant contamination with no plasma cells, hence potentially compromising the results. The percent of high-risk disease patients identified from different signatures ranged from 26.4% by using high proliferation index to 28.8% with high centrosome signature and 31.3% with high 70-gene index. This percent of high-risk cases based on the 70-gene index is similar to what was found in Total therapy 2 (TT2) and TT3 cohorts. A third of patients (33.2%) were classified as D1 in the TC class, followed by 11q13 (19.3%), D2 (16.4%), 4p16 (13.8%), MAF (6.1%), None (4.7%), D1+D2 (4.5%) and 6p21 (1.8%). The NF-kB pathway was likely activated in 45.5% to 59.5% of cases, depending on the index used for its calculation. High proliferation index and high centrosome signature significantly correlates with 70-gene high-risk group (p<0.0001). Conversely, the activation of NF-kB pathway was not significantly different between high- and low- risk subgroups. TC subgroups D1 (p<0.0001) and 11q13 (p=0.01) were significantly more common in the 70-gene low-risk group. Similarly, TC subgroups 4p16 (p=0.0004), Maf (p=0.02) and D2 (p=0.05) were enriched in the high-risk group. Translocations t(4;14)(p16;q32), t(11;14)(q13;q32) and t(14;16)(q32;q23) were precisely predicted by the TC classification (100% correspondence). Cases with IgH translocations with unknown partner were classified in subgroups D1 (33%), D2 (25%), 6p21 (25%) and Maf (16%). Here we summarized the associations between the most significant gene expression indices and signatures relevant to MM risk-stratification. The multiple variables simultaneously analyzed in an automated way, provide a powerful and fast tool for risk-stratification, helping in the therapeutic decision-making. Disclosures: Stewart: Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding. Fonseca:Consulting :Genzyme, Medtronic, BMS, Amgen, Otsuka, Celgene, Intellikine, Lilly Research Support: Cylene, Onyz, Celgene: Consultancy, Research Funding.

Abstract Abstract 2869 Background: Chromosome abnormalities are universal in multiple myeloma (MM) and will ultimately categorize patients into hyperdiploid and non-hyperdiploid MM. Among non-hyperdiploid patients those that exhibit hypodiploidy have the most aggressive clinical phenotype. What genetic features are unique to hypodiploidy are not fully described. Therefore, we performed a comprehensive high-resolution analysis to differentiate and characterize hypodiploid MM. Materials and methods: MM patients were analyzed using a combination of array-based comparative genomic hybridization (aCGH) (n=275) and gene expression profiling (GEP) (n=239). Agilent 244K and Affymetrix U133A Plus 2.0 arrays were used in the aCGH and GEP experiments, respectively. Hypodiploid MM was differentiated using pseudokaryotyping based on aCGH findings. Samples estimated to have less than or equal to 44 chromosomes were designated hypodiploid, 45–47 chromosomes were nonhyperdiploid and greater than or equal to 48 and less than 74 chromosomes were considered hyperdiploid. Using GEP the main gene indices and signatures associated with outcome were determined including the translocation and cyclin D (TC) classification, UAMS 70-gene index, proliferation index, centrosome signature and NF-kB index. Differentially expressed genes were also investigated. Results: A total of 53 (19%) MM patients were classified into the hypodiploid group, mainly characterized by monosomies of chromosomes 13 (83%), 14 (42%), 22 (23%) and × (50%) (females) with p and/or q-arm aberrations including gains of 1q (51%) and 8q (25%) and losses of 1p (49%), 4p (21%), 4q (23%), 6q (38%), 8p (34%), 12p (25%), 12q (26%), 14q (32%), 16p (25%), 16q (51%) and 17p (25%). Patients with loss of 1p were associated with 4p- (p <0.029), 4q- (p<0.0001), 12p- (p<0.007), 12q- (p<0.0002), any 14 (p<0.022), 16p- (p<0.005), 16q- (p<0.001), and monosomy 22 (p<0.024). Patients with loss of 17p were associated with 12p- (p<0.025), 12q- (p<0.039) and 16q- (p<0.031). The main gene indices and signatures in MM showed that nearly one half of the hypodiploid patients having high-risk disease, ranging from 45% with a high 70-gene index, 47% with high centrosome signature and 51% with a high proliferation index. In addition, hypodiploid patients also displayed a translocation type signature in the TC classification defined by 11q13 (24%), 4p16 (24%) and maf (12%). Overall, 253 genes have >2 fold expression change comparing hypodiploid vs. hyperdiploid including a five fold decrease in the heparin-degrading endosulfatase gene SULF2, a decrease of genes in the TGF-b signaling pathway (MYC, ID3, SMAD1, LTBP1) and those involved in Wnt signaling (DKK1, FRZB). Up regulated genes included those from the p53 signaling pathway and cell cycle (CCND2, CDKN1C, RPRM), cell adhesion molecules (ITGB8, CD28) and tight junction pathway (RRAS2, RRAS, CSDA). Conclusion: This represents the most comprehensive genomic characterization of hypodiploid MM to date. These cases exhibit a high propensity for high-risk gene expression profiles and have a high prevalence of −13, −14, 1q gain and 1p loss as predicted. Given our findings it is likely that hypodiploid is not a separate category but rather the genetic “phenotype” of a more advanced clone. Today, using these two platforms together in a routine setting would provide the most comprehensive genetic analysis, important for individualized therapeutics. Disclosures: Fonseca: Consulting :Genzyme, Medtronic, BMS, Amgen, Otsuka, Celgene, Intellikine, Lilly Research Support: Cylene, Onyz, Celgene: Consultancy, Research Funding.

Abstract Abstract 127 The precise molecular mechanism of action and targets through which thalidomide and related immunomodulatory drugs (IMiDs) exert their anti-tumor effects remains unclear. A landmark paper has recently identified cereblon (CRBN) as a primary target of thalidomide teratogenicity. We hypothesized that this protein would also be required for myeloma (MM) cytotoxicity. To examine this issue we first tested 12 MM cell lines: 4 of which (OCIMY5, OPM1, SKMM2 and KMS12 PE) were very resistant to treatment with both lenalidomide and pomalidomide. Of these, OCIMY5 and OPM1 showed CRBN gene expression levels at the bottom 10% across the human MM cell lines. We next used CRBN shRNA lentiviral expression constructs to knock down CRBN in 5 human-derived myeloma cell lines (HMCLs) (KMS18, MM1.S, H929, OPM2 and JJN3). HMCLs infected with CRBN shRNAs have a significant reduction of CRBN expression and subsequent diminished cell viability (reduced 65–78%). Surviving MM cells with CRBN knock down demonstrate an acquired (essentially complete) resistance to lenalidomide when compared with controls but retained sensitivity to melphalan, dexamethasone and bortezomib. Gene expression changes induced by lenalidomide were dramatically suppressed in those CRBN depleted cells, e.g., OPM2 cells only showed 30 down regulated (3% of control) and 150 up-regulated genes (24% of control) after lenalidomide treatment, further emphasizing that CRBN is required for lenalidomide activity. We next compared by array comparative genomic hybridization the differences between MM1.S (lenalidomide sensitive) and its isogenic lenalidomide resistant line (MM1.S res), generated by culturing MM1.S in gradually increasing concentrations of lenalidomide. Only three structural abnormalities were noted differentiating the two lines one of which was deletion of CRBN. In fact the baseline MM1.S cell line has a minor population of 9% of cells with CRBN depletion which becomes dominant after lenalidomide treatment. However, further scrutiny of CRBN status in additional HMCLs and MM patients (irrespective of therapy and stage) suggested that copy-number abnormalities affecting this gene are uncommon events in MM, with 12% of HMCLs (7 out of 60) and only 1.2% of MM patients (3 out of 238) showing CRBN monoallelic deletion. Next, we examined by quantitative polymerase chain reaction (Q-PCR) ten MM patients who had become resistant to lenalidomide therapy. CRBN expression level by Q-PCR in 8 of 10 patient samples had a significant reduction (20% to 90% reduction compared to baseline) at time of drug resistance, suggesting CRBN expression as a potential biomarker to predict IMiD response. Notably however some clearly resistant patients have normal CRBN, demonstrating that while CRBN is absolutely required for response, multiple resistance mechanisms are likely present. By gene and protein expression downstream targets of CRBN were examined and included interferon regulatory factor 4 (IRF4) previously reported to also be a target of lenalidomide. In summary, we demonstrate here that CRBN is essential for IMiD activity and preliminary data support that low levels of CRBN predict for poor drug response. In addition, our data suggest that CRBN is a critical molecule but not the unique source of IMiD resistance. We suggest that the “IMiDs” be renamed Cereblon binding small molecules to more accurately reflect their mechanism of action. Disclosures: Orlowski: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Abstract 606 Multiple myeloma is a complex malignancy with multiple underlying genetic events. Our group has spent considerable effort over the last 15 years to elucidate the genetic underpinnings of myeloma. Most recently, we used array-based comparative genomic hybridization (aCGH) as a discovery tool in 62 myeloma patients and 46 myeloma cell lines. In that preliminary screen using the Agilent 44B aCGH platform (∼70kb resolution) we identified a diverse array of abnormalities, which resulted in constitutive activation of the NF-kB pathways. That initial analysis concentrated on the 43 genes we identified as potential targets of the 13 homozygous deletion events detected in the patient samples. A pathway analysis of these genes revealed a single pathway involving TRAF3, TRAF2, BIRC2, BIRC3, and CYLD. This first analysis focused exclusively on abnormalities present in the patient samples as we worried some abnormalities identified exclusively in the cell lines might not be relevant to the pathogenesis of myeloma in patients. However, several abnormalities were equally or more frequent overall but occurred exclusively in cell lines including CDKN2C (14 samples), CDKN1B (4 samples), KDM6A/UTX (4 samples), RB1 (3 samples), TP53 (3 samples). Given the fact that KDM6A/UTX deletions were as frequent as many of the best-described tumor suppressors it seemed like a good candidate but in the absence of patient events or a known function at the time it was not prioritized for further study. Recently, as part of the Multiple Myeloma Research Consortium (MMRC) Genomics Initiative, we have completed the analysis of a cohort of 250 myeloma patient samples by aCGH using the Agilent 244A aCGH platform (∼15kb resolution) and gene expression profiling using the Affymetrix U133Plus2.0 genechip. In this cohort with a significantly improved aCGH platform we identified 17 genes that are recurrently inactivated by homozygous deletions including DIAPH2 (15 samples), CDKN2C (14 samples), TRAF3 (11 samples), CYLD (8 samples), BIRC2/3 (7 samples), KDM6A/UTX (6 samples), and RB1 (5 samples). Based on the significant improvement in resolution and data quality achieved with the Agilent 244A aCGH platform we rescreen all of the cell lines on this improved platform. This significantly changed the frequency of several homozygous deletions in this population with the most frequently targeted genes now being CDKN2C (20 samples), KDM6A/UTX (13 samples), DIAPH2 (7 samples), RB1 (4 samples), TP53 (4 samples), CDKN1B (4 samples), and TRAF3 (4 samples). Moreover, as part of the genomic characterization of a spontaneous myeloma mouse model that we have developed, Vk*-Myc, we have identified recurrent (∼50%) homozygous deletions of Kdm6a/Utx. Therefore, one of the genes most commonly targeted by a homozygous deletion in human and mouse myeloma is KDM6A/UTX. In late 2007 after we had identified the first patients with KDM6A/UTX deletions it was shown that UTX is a functional histone demethylase that removes methyl groups from histone H3 lysine 27 (H3K27me). Given the high incidence of deletions and the fact that MMSET, the overexpressed target gene of t(4;14) in myeloma, is predicted to methylate H3K27, H3K36, and/or H4K20 by evolutionary conservation we developed the hypothesis that myeloma is characterized by abnormalities that result in excessive H3K27me (typically a repressive chromatin mark). Given the extensive whole genome sequencing occurring in the MMRC genomics initiative we elected to focus our resequencing efforts on the cell lines exclusively. These studies identified an additional 4 samples with LOH and an inactivating mutation bringing the total percentage of inactivated cell lines to 33%. Clearly, in the expanded patient and cell line cohorts the inactivation of KDM6A/UTX is not independent of MMSET overexpression suggesting they may act independently or synergistically. We are currently attempting to identify the genes controlled by KDM6A/UTX inactivation to better understand the functional consequences of this highly recurrent event. However, in the mouse model unlike the patient or cell lines, the gene expression profiling has identified a gene expression signature that differentiates UTX inactivated and functional samples suggesting an oncogenic function of inactivation. Disclosures: No relevant conflicts of interest to declare.