ALBERT

Description: INTRODUCTION: Multiple myeloma (MM) is a biologically and clinically heterogeneous disease. Different recurrent driver genomic events have been reported, but to date no unifying feature has been identified in MM evolution. The recent interest in signatures of mutational processes through analysis of whole-exome sequencing data has led to initial insights into what generates MM mutational repertoire (Bolli et al, Nat Com 2014). Here, taking advantage of the increased power provided by whole genome sequencing (WGS), we analyzed 22 paired samples from 11 patients first at the smoldering (SMM)/MGUS stage and subsequently at the time of progression to symptomatic MM to gain a deeper understanding of the full landscape of mutational processes operative in MM, especially during their evolution over time. MATERIAL AND METHODS: DNA from bone marrow CD138+ cells underwent WGS along with a matched normal sample using HiSeq X Ten machines (Illumina, Inc.). Mutational signature extraction was performed running non-negative matrix factorization (NMF) as previously described (Alexandrov et al, Nature 2013). RESULTS: We have observed and utilized a median number of 5780 (range 2599-7760) substitutions per patient at the asymptomatic stage and 5954 (ranges 2824-8227) at progression to MM stage to extract mutational signatures. NMF extracted 5 main signatures (http://cancer.sanger.ac.uk/cosmic/signatures). Specifically, APOBEC- (signature #2) and age-related signatures (signatures #1 and #5) accounted for 13% (1-21%) and 23% (3.2-40%) of all substitutions, respectively. In addition, we found two known signatures that were not implicated in MM so far: non-canonical AID (Signature #9), contributing to 28% of all substitutions (17-55%); and signature #8, accounting for 28% of all substitutions (13-45%) and pertaining to a yet unknown mutational process. Finally, the fifth signature did not match any of the previously described ones, representing a potential novel process which we defined as MM-1 (7%, range (1-16%). Interestingly, we found a differential contribution of processes in non-coding and intronic regions where AID was more prevalent, while exonic regions where APOBEC and age signatures were more prevalent. In intronic regions we found widespread regions of kataegis (9/11 patients), reflective of localized hypermutation. In our patients, kataegis was associated with rearrangements in 60% of cases, and was present in both the SMM and MM sample in 84% of cases, suggestive of an early event during tumor development. Contrary to what is observed in solid cancers, APOBEC signature was only responsible for 25% of kataegis variants, vs 70% for AID, suggesting a causative role of aberrant AID activity in shaping the early mutational repertoire of neoplastic plasma cells. To confirm this, we looked at serial samples in our cohort. While the percent contribution of each signature varied in each patient, confirming genomic heterogeneity of MM, it did not change when paired SMM and MM samples from the same patient were compared. This shows that mutational processes required for the development of symptomatic MM act early, and have been already operative at the SMM stage. However, by clustering substitutions as clonal (early variants present at the time of tumor initiation) or subclonal (late variants arisen closer to the time of sampling) using a Bayesian hierarchical Dirichlet process (Bolli et al, Nature Comms 2014), we could analyze processes operative before SMM was diagnosed. NMF analysis of these clusters reported striking differences. Specifically, AID and age were the predominant mutational processes in early substitutions in all patients, contributing to a median of 35% (25-54%) and 30% (15-43%) of variants respectively. Conversely the contribution of AID was minimal among late substitutions (5%, 1-22%), where instead APOBEC, Signature #8 and MM-1 activity was prominent [19% (1-43), 38% (8-73%), 16% (2-50%) respectively]. CONCLUSION: WGS data allowed the identification of mutational processes operative well before MM becomes clinically evident. Our observation that all samples have signs of aberrant AID at the time of tumor initiation supports a unifying model where MM precursors are initially transformed with the contribution of AID, providing a fertile ground for other later processes (i.e APOBEC and signature #8) to act and shape the final genomic landscape of overt multiple myeloma. Disclosures No relevant conflicts of interest to declare.

Description: Abstract 1817 Poster Board I-843 Deletion of the short arm of chromosome 17 [del(17p)] is known to confer a poor prognosis in multiple myeloma (MM). However, no large study has been specifically dedicated to this purpose, especially in the novel drug era. We analyzed a series of 1324 patients with MM at diagnosis, treated within or according to IFM trials, and analyzed for del(17p). Most of the patients were under 65 years of age (1122 of the 1324 patients), and were treates either with a VAD-based induction or a Velcade®/Dexamethasone-based induction, followed by one or two courses of high-dose melphalan. Del(17p) was correlated to the major other prognostic parameters, both for event free survival and overall survival. Del(13) was observed in 71% of the patients with del(17p). A significant association was observed with anemia 〈 10g/dl (p=.05), with thrombocytopenia 〈 130 G/l (p3.5 mg/l (p=.006). No specific association was observed with t(4;14) (17% of the del(17p)-positive patients displayed t(4;14)). Del(17p) was observed in 10% of the patients. Del(17p) was associated with a very poor outcome, both in young and elderly patients. Actually, the prognostic value was observed only in patients displaying del(17p) in at least 70% of their plasma cells. The median EFS and OS were 18 and 28 months respectively, versus 30 and 69 months for patients lacking the del(17p). A particularly poor outcome was observed in patients presenting both del17p and t(4;14), with a median EFS of 4.5 months and a median OS of 12 months. Of particular importance, none of the treatment modality (high-dose melphalan, thalidomide, bortezomib) overcame the poor prognosis associated with del(17p), although patients lacking del(17p) displayed a better outcome when treated with Vel/Dex or MP-Thalidomide. In conclusion, del(17p) is associated with an especially poor outcome, independently of the type of treatment, including novel drugs. Disclosures No relevant conflicts of interest to declare.

Description: Rearrangements of the c-myc oncogene have been found in most plasmacytomas induced in mice and human myeloma cell lines (HMCLs) analyzed so far. However, neither induced mouse plasmacytomas nor HMCLs represent relevant models for human multiple myeloma (MM). To evaluate the incidence of c-mycrearrangements in human plasma cell dyscrasias, sets of probes were generated to allow direct assessment of c-myctranslocations on interphase plasma cells by using fluorescence in situ hybridization. After validation of these probes, a large cohort of patients with either newly diagnosed MM (n = 529), relapsed MM (n = 58), primary plasma cell leukemia (PCL; n = 23), monoclonal gammopathy of undetermined significance (n = 65), or smoldering MM (n = 24) were analyzed. C-myc rearrangements were identified in 15% of patients with MM or primary PCL, independently of the stage of the disease (ie, diagnosis or relapse and MM or primary PCL). Analysis of the 2 main translocations observed on karyotyping, ie, t(8;14) and t(8;22), revealed that these specific translocations represented only 25% (23 of 91) of c-mycrearrangements. c-myc rearrangements were then correlated with several other patients' characteristics: illegitimateIgH recombinations, chromosome 13 deletions, and serum β2-microglobulin levels. The only significant correlation was with a high β2-microglobulin level (P = .002), although a trend for association with t(4;14) was observed (P = .08). Thus, c-myc rearrangement analysis in patients with MM revealed a strikingly lower incidence than that in HMCLs and plasmacytomas induced in mice, indicating that data obtained with these models cannot be directly extrapolated to human MM.

Description: Epigenomic changes have become an important component of cellular regulation and ultimately, of our understanding of oncogenomics in Multiple Myeloma (MM) as well as in other cancers. In recent years, both clinical and preclinical studies have confirmed that MM is vulnerable to epigenetic intervention, with histone deacetylases (HDACs) emerging as the most promising epigenetic targets. Although Pan-HDAC inhibitors are effective as therapeutic agents, there is increasing emphasis on understanding the biological and molecular roles of individual HDACs. Here we have evaluated the role of HDAC8, a member of Class I HDAC isoenzymes in MM. First, we evaluated the expression of HDAC8 in 172 newly-diagnosed MM patients from the IFM myeloma dataset and observed HDAC8 overexpression as well as its significant correlation with poor survival outcome (p

Description: Although most multiple myeloma (MM) cases are characterized by the detection of a monoclonal immunoglobulin in the serum, about 15% of the patients present only immunoglobulin light chains, detected either in the urine or serum or both. These patients are designated as having light-chain (LC) MM. Using fiber-fluorescent in situ hybridization, and in contrast to patients and myeloma cell lines secreting heavy chains (who presented a legitimate functional IgH rearrangement in every case), LC MM never displayed a functional IgH recombination. Interestingly, most LC MM cases presented one IgH allele with a germline configuration (including the DJ region), the second allele being usually involved in an illegitimate recombination. Of note, most of these translocations occurred close to (or at) switch regions, even though in some cases, breakpoints involving nonswitch regions were observed. Thus, this study clearly showed that LC MM is due to the absence of legitimate IgH rearrangement at the DNA level, reflecting possible abnormalities in the IgH gene recombinations during B-cell maturation. Furthermore, it showed that this defect did not prevent the activation of the switch process because most of 14q32 translocations observed in LC MM occurred at switch regions.

Description: Abstract 807FN2 Gene expression profiling (GEP) of newly-diagnosed cancer patients is now a routine task in the oncogenomic research using functional genomics platforms like microarray and next generation sequencing. These profiles are then utilized to derive gene expression signatures (GES) that can stratify patients according to survival groups using various statistical methodologies. This is an active area of research with important implications on clinical decision making and patient care. It is important to note that the treatment itself probably plays a major role in influencing outcome in cancer. Therefore, the GES may be specific to a particular treatment and may not be universally applicable in predicting survival of patients treated with different therapeutic regimen. We evaluated the impact of therapy on GES utilizing two large publicly available gene expression datasets from newly-diagnosed multiple myeloma (MM) patients generated using Affymetrix U133+2 microarrays. The dataset from University of Arkansas Medical Sciences (UAMS; Shaughnessy et al Blood 2007) has gene expression profile (GEP) from 569 patients treated on total therapy (TT)2 and TT3 protocols while the dataset from HOVON-65 trial contains GEO data from 320 patients treated with either the VAD or PAD regimen in equal numbers. The UAMS dataset was partitioned into training and validation sets. Using a combination of a network inspired univariate ranking procedure and ultra refined methods for variable selection we derived a sparse multivariate survival signature consisting of 40 genes that worked extremely well on the training set (p-value 〈 e-16) as well as the validation set (p-value 〈 e-5). Interestingly we saw the difference of performance between TT2 and TT3 induction arms. The p values were 0.002 for the TT2 induction arm while for the TT3 the p value was 0.02. On applying the signature to the whole HOVON-65 test set our signature worked only moderately well (p-value = 0.003). When the HOVON-65 dataset was split according to the induction treatment arms, the GES worked extremely well (p-value 〈 e-5) in predicting the outcome in patients receiving VAD regimen but had no power to distinguish survival in patients receiving PAD regimen. We have evaluated the results on additional data sets that confirmed our observation from the HOVON study. To our knowledge this is the first clear demonstration of treatment specificity of GES. This data suggest that we may need to derive multiple therapy-specific GES to be applied to the patients to treat the new patient with therapy for which he/she is predicted to have best outcome. Disclosures: No relevant conflicts of interest to declare.

Description: Pharmacogenomic profiles of genes involved in bortezomib - dexamethasone response may help to understand resistance and could provide new therapeutic targets as well as contributing to novel prognostic markers in multiple myeloma. We have used gene expression profiling to analyze the complex signaling pathways regulating the response to bortezomib - dexamethasone. Gene expression profiles were established in 9 cell lines, derived from 9 myeloma patients, incubated or not with a combination of bortezomib 10 nM and dexamethasone 1 μM. These concentrations correspond to the ones used for patients in the IFM 2005-01. Cells were collected after 6 hours of treatment. We focused our interest in early response genes, making the hypothesis that the comprehension of early effects would help to better understand the mechanisms of resistance that take place in at least two third of myeloma patients. Supervised analysis with permutations identified significantly up regulated genes involved in stress responses (heat shocks proteins, RTP801/dig2/REDD1/DDIT4), endoplasmic reticulum stress (HERP/HERPUD1, gadd145/CHOP/DDIT3), ubiquitin/proteasome pathway (proteasome 26S subunits PSMB7, PSMC4, PSMD3 and PSMD13), unfolded protein response (such as SQSTM1, ATF4) or redox equilibrium (PLRX, PRDX1). We assumed that these genes might represent a molecular signature of response to bortezomib and provide important insight into the complex mechanisms of action of these drugs. We focused on REDD1 a gene cloned in 2002 that is known to be rapidly induced by a wide variety of stress conditions (arsenic, hypoxia, dexamethasone, thapsigargin, tunimycin and heat shock) and DNA damages (ionizing radiation, ultraviolet radiation, DNA alkylant). We found that both REDD1 gene and protein expression were early and highly induced after bortezomib exposure alone or in combinaison with dexamethasone. This effect was dependent upon cell line: REDD1 was overexpressed within two hours in resistant cell lines in association with a cell size decrease while in sensitive cell lines, neither REDD1 induction nor morphological changes occured. REDD1 induction was associated with the dephosphorylation of S6K1, a key substrat of mTOR, a protein kinase which controls cell growth and cell size in response to various signals. SiRNA studies confirmed that bortezomib lead to a negative regulation of mRTor activity mediated by REDD1: disruption of REDD1 abrogates both S6K1 phosphorylation and early transitory cell size reduction. Our results are in accordance with data obtained in mouse showing an early regulation of mTOR pathway and cellular proliferation induced by REDD1 expression in response to stress. Our study suggests that mTOR regulation could be a resistance mechanism mediated by REDD1 expression. As we found that REDD1 was differentially induced in primary plasma cells from patients, this gene expression could help to predict response to bortezomib. Our objective is now to clarify the pathway that links bortezomib to REDD1 in multiple myeloma and to investigate REDD1 expression in patients enrolled in IFM 2005-01 clinical trial.

Description: Key Points The majority of mutations are found in genes that have low or no detectable biological expression. Mutated genes often show differential allelic expression in multiple myeloma patient samples.