Multiple myeloma (MM) is a genetically heterogeneous disease and the management of relapses is one of the biggest clinical challenges. TP53 alterations are established high-risk markers and are included in the current disease staging criteria. KRAS is the most frequently mutated gene affecting around 20% of MM patients. Applying Clonal Competition Assays (CCA) by co-culturing color-labeled genetically modified cell models, we recently showed that mono- and biallelic alterations in TP53 transmit a fitness advantage to the cells. Here, we report a similar dynamic for two mutations in KRAS (G12A and A146T), providing a biological rationale for the high frequency of KRAS and TP53 alterations at MM relapse. Resistance mutations, on the other hand, did not endow MM cells with a general fitness advantage but rather presented a disadvantage compared to the wild-type. CUL4B KO and IKZF1 A152T transmit resistance against immunomodulatory agents, PSMB5 A20T to proteasome inhibition. However, MM cells harboring such lesions only outcompete the culture in the presence of the respective drug. To better prevent the selection of clones with the potential of inducing relapse, these results argue in favor of treatment-free breaks or a switch of the drug class given as maintenance therapy. In summary, the fitness benefit of TP53 and KRAS mutations was not treatment-related, unlike patient-derived drug resistance alterations that may only induce an advantage under treatment. CCAs are suitable models for the study of clonal evolution and competitive (dis)advantages conveyed by a specific genetic lesion of interest, and their dependence on external factors such as the treatment.

Smoldering multiple myeloma (SMM) precedes multiple myeloma (MM). The risk of progression of SMM patients is not uniform, thus different progression-risk models have been developed, although they are mainly based on clinical parameters. Recently, genomic predictors of progression have been defined for untreated SMM. However, the usefulness of such markers in the context of clinical trials evaluating upfront treatment in high-risk SMM (HR SMM) has not been explored yet, precluding the identification of baseline genomic alterations leading to drug resistance. For this reason, we carried out next-generation sequencing and fluorescent in-situ hybridization studies on 57 HR and ultra-high risk (UHR) SMM patients treated in the phase II GEM-CESAR clinical trial (NCT02415413). DIS3, FAM46C, and FGFR3 mutations, as well as t(4;14) and 1q alterations, were enriched in HR SMM. TRAF3 mutations were specifically associated with UHR SMM but identified cases with improved outcomes. Importantly, novel potential predictors of treatment resistance were identified: NRAS mutations and the co-occurrence of t(4;14) plus FGFR3 mutations were associated with an increased risk of biological progression. In conclusion, we have carried out for the first time a molecular characterization of HR SMM patients treated with an intensive regimen, identifying genomic predictors of poor outcomes in this setting.

Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of pathogenic CD138+ plasma cells (PPCs) in bone marrow (BM). Recent years have seen a significant increase in the treatment options for MM; however, most patients who achieve complete the response ultimately relapse. The earlier detection of tumor-related clonal DNA would thus be very beneficial for patients with MM and would enable timely therapeutic interventions to improve outcomes. Liquid biopsy of "cell-free DNA" (cfDNA) as a minimally invasive approach might be more effective than BM aspiration not only for the diagnosis but also for the detection of early recurrence. Most studies thus far have addressed the comparative quantification of patient-specific biomarkers in cfDNA with PPCs and BM samples, which have shown good correlations. However, there are limitations to this approach, such as the difficulty in obtaining enough circulating free tumor DNA to achieve sufficient sensitivity for the assessment of minimal residual disease. Herein, we summarize current data on methodologies to characterize MM, and we present evidence that targeted capture hybridization DNA sequencing (tchDNA-Seq) can provide robust biomarkers in cfDNA, including immunoglobulin (IG) rearrangements. We also show that detection can be improved by prior purification of the cfDNA. Overall, liquid biopsies of cfDNA to monitor IG rearrangements have the potential to provide important diagnostic, prognostic, and predictive information in patients with MM.

S12patients with a resistant clone that did not respond or only very partly responded to treatment, > 50% of the malignant PCs were found in the BM post-treatment (5/12 patients, 42%); and patients with clonal selection, indicating that the significant clone has been replaced by a small or undetectable clone at baseline (4/12 patients, 33%).For these four patients identified with clonal selection, one was observed with branching evolution, and the other three were observed with differential evolution.Transcriptional differences among sensitive clones, resistant clones, and selective clones were detected based on a pairwise comparison of the gene expressions.A large number of differentially expressed genes with reported MM resistant-related functions were observed in the resistant clones, including previously reported 1q-related genes such as CKS1B, HNRNPU, and H3F3A; cell cycle-and cell proliferation-related genes such as TUBA1B, STMN1, and HMGB2.For selective clones, an evident activation of the NF-kB signaling pathway was observed.Conclusions: Together, our study confirms that clonal dynamics of the evolving PC clones may occur early after upfront therapy, and reveals that the acquisition of therapeutic resistant pathways is associated with early adaptation to treatment.

Chronic neutrophilic leukemia (CNL) and atypical chronic myeloid leukemia (aCML) are rare myeloid disorders that are challenging with regard to diagnosis and clinical management. To study the similarities and differences between these disorders, we undertook a multicenter international study of one of the largest case series (CNL, n = 24; aCML, n = 37 cases, respectively), focusing on the clinical and mutational profiles (n = 53 with molecular data) of these diseases. We found no differences in clinical presentations or outcomes of both entities. As previously described, both CNL and aCML share a complex mutational profile with mutations in genes involved in epigenetic regulation, splicing, and signaling pathways. Apart from CSF3R, only EZH2 and TET2 were differentially mutated between them. The molecular profiles support the notion of CNL and aCML being a continuum of the same disease that may fit best within the myelodysplastic/ myeloproliferative neoplasms. We identified 4 high-risk mutated genes, specifically CEBPA (beta = 2.26, hazard ratio [HR] = 9.54, P = .003), EZH2 (beta = 1.12, HR = 3.062, P = .009), NRAS (beta = 1.29, HR = 3.63, P = .048), and U2AF1 (beta = 1.75, HR = 5.74, P = .013) using multivariate analysis. Our findings underscore the relevance of molecular-risk classification in CNL/ aCML as well as the importance of CSF3R mutations in these diseases.

Next-generation sequencing (NGS) has greatly improved our ability to detect the genomic aberrations occurring in multiple myeloma (MM); however, its transfer to routine clinical labs and its validation in clinical trials remains to be established. We designed a capture-based NGS targeted panel to identify, in a single assay, known genetic alterations for the prognostic stratification of MM. The NGS panel was designed for the simultaneous study of single nucleotide and copy number variations, insertions and deletions, chromosomal translocations and V(D)J rearrangements. The panel was validated using a cohort of 149 MM patients enrolled in the GEM2012MENOS65 clinical trial. The results showed great global accuracy, with positive and negative predictive values close to 90% when compared with available data from fluorescence in situ hybridization and whole-exome sequencing. While the treatments used in the clinical trial showed high efficacy, patients defined as high-risk by the panel had shorter progression-free survival (p = 0.0015). As expected, the mutational status of TP53 was significant in predicting patient outcomes (p = 0.021). The NGS panel also efficiently detected clonal IGH rearrangements in 81% of patients. In conclusion, molecular karyotyping using a targeted NGS panel can identify relevant prognostic chromosomal abnormalities and translocations for the clinical management of MM patients.

Introduction Multiple Myeloma (MM) is a heterogeneous disease with a complex clonal and subclonal architecture with few recurrent mutations. The arrival of next-generation sequencing (NGS) has allowed us to have a deeper understanding of the disease. Due to that complexity and the low recurrence of "driver" mutations, the study of general mutational profile, copy number variation (CNV) and translocations is crucial to make an accurate diagnosis and prognosis. For that reason, a clinically validated NGS capture panel has been designed to analyze in a single assay all interesting genetic aberrations simultaneously including SNVs, indels, CNVs and chromosomal translocations. Methods In addition to genomic DNA (gDNA) from 33 healthy donors to create a robust baseline forCNV detection,we studied 161 DNA samples from 149 newly diagnosed MM patients enrolled in the GEM2012MENOS65clinical trial and treated homogeneously: gDNA from 149 BM CD138+ plasma cells and 12 paired cfDNA from peripheral blood samples obtained at diagnosis. First, starting with 100 ng of gDNA and 200ng for cfDNA samples, a custom targeted NGS panel using SureSelect capture technology (Agilent) followed by NextSeq500 (Illumina) sequencing identified SNVs, indels, CNVs and the most relevant IGH translocations within 26genes involved with MM. The average sequencing depth was 609x across samples; and 98% of the targeted regions were sequenced with >200x. Second, NGS custom panel results were compared with FISH (n=88) and whole exome sequencing (SureSelect XT V6) (n=48) results. Both NGS panel and exome raw data were analyzed by DREAMgenics applying a custom bioinformatic pipeline. Finally, 5 discordant cases were followed-up by SNP-arrays. Results We have identified 408 exonic and non-synonymous variants. At least 1 oncogenic mutation was detected in 86% (128/149) of patients. NRAS was mutated in25% of patients, followed by KRAS(23%), BRAF(12%) DIS3(11%) and TP53(9%). Other interesting pathogenic mutations were identified in FGFR3 andHIST1H1E genes in 9% and 5% of patients, respectively. In 92% (11/12) of cfDNA samples at least 1 oncogenic mutation was detected. For this 12 cases, paired samples (BM CD138+vscfDNA) were available. A total of 39 somatic mutations were identified in those cases. In cfDNA, 10 mutations were detected, and 5 were present in both samples. Furthermore, a mean decrease of 0.19VAF was observed in cfDNA (0.12; 0.01-0.48) vs plasma cells (0.31; 0.01-0.51). Regarding to CNV, 1q gain was detected in 32% of patients (28/88), and 1p and 17p deletions in 17% (15/88) and 13% (11/88), respectively. Additionally, ATR and CRBN gene amplifications were detected in 22% and 16%, respectively. When these data were compared to FISH, a 75% of sensitivity and 91% of specificity was achieved by our method, with a PPV of 68% and a NPG of 93%. Translocations were identified in 28% (25/88) of patients, including 7% (6/88)) t(11;14), 14% (12/88), t(4;14), and 1 patient t(14;16). We also detected t(6;14)(p21;q32) IGH/CCND3 in 3 patients that had also been described in MM.Translocations were detected with a 94% of sensitivity, 99% of specificity, with a predictive positive value of 94% and a predictive negative value of 99%. Importantly, NGS-based method revealed a t(10;14) in 3 patients that had not been identified by FISH, a new translocation implying the miRNA hsa-mir-4537. Finally, the impact on PFS from FISH and NGS results was analyzed separately. PFS was similar for translocations and 17p deletions. However, 1p-detected by NGS showed a higher negative prognostic impact (p=0,006 vs p=0,127 by FISH)(Fig.1). Furthermore, our panel showed that 7% of patients (6/88) had a bi-allelic TP53 inactivation. Survival analysis showed that these patients relapsed significantly earlier than the others (p=0.028). Amplifications (≥4 copies) in 1q+could not identified with this panel. Conclusions Our custom NGS-based test allows in a single assay a more comprehensive study of the genomic landscape of MM patients by (a) detecting with a high sensitivity the most important and recurrent mutations and cytogenetic alterations, (b) identifying translocations and CNVs not previously detected by FISH and (c) identifying a double-hit MM patient. Additionally, cfDNA could be analyzed with this NGS strategy identifying molecular alterations in most of the patients. Disclosures Oriol: Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy. Sureda Balari:Takeda: Consultancy, Honoraria, Speakers Bureau; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Honoraria; Sanofi: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Gilead/Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Incyte: Consultancy; Celgene: Consultancy, Honoraria; BMS: Speakers Bureau; Merck Sharpe and Dohme: Consultancy, Honoraria, Speakers Bureau. de la Rubia:Janssen: Consultancy, Other: Expert Testimony; Celgene: Consultancy, Other: Expert Testimony; Amgen: Consultancy, Other: Expert Testimony; Ablynx/Sanofi: Consultancy, Other: Expert Testimony. Mateos:Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; PharmaMar-Zeltia: Consultancy; Abbvie/Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Consultancy, Honoraria; Regeneron: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Blade Creixenti:Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. San-Miguel:Amgen, BMS, Celgene, Janssen, MSD, Novartis, Takeda, Sanofi, Roche, Abbvie, GlaxoSmithKline and Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees. Garcia-Sanz:Novartis: Honoraria; Janssen: Honoraria, Research Funding; Incyte: Research Funding; Gilead: Honoraria, Research Funding; BMS: Honoraria; Amgen: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria; Takeda: Consultancy, Research Funding. Martinez-Lopez:Novartis: Research Funding; BMS: Research Funding, Speakers Bureau; Incyte: Research Funding, Speakers Bureau; Janssen: Speakers Bureau; Roche: Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau; Vivia Biotech: Honoraria; Altum: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Hosea: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties.

Multiple myeloma is a heterogeneous disease whose pathogenesis has not been completely elucidated. Although B-cell receptors play a crucial role in myeloma pathogenesis, the impact of clonal immunoglobulin heavy-chain features in the outcome has not been extensively explored. Here we present the characterization of complete heavy-chain gene rearrangements in 413 myeloma patients treated in Spanish trials, including 113 patients characterized by next-generation sequencing. Compared to the normal B-cell repertoire, gene selection was biased in myeloma, with significant overrepresentation of IGHV3, IGHD2 and IGHD3, as well as IGHJ4 gene groups. Hypermutation was high in our patients (median: 8.8%). Interestingly, regarding patients who are not candidates for transplantation, a high hypermutation rate (≥7%) and the use of IGHD2 and IGHD3 groups were associated with improved prognostic features and longer survival rates in the univariate analyses. Multivariate analysis revealed prolonged progression-free survival rates for patients using IGHD2/IGHD3 groups (HR: 0.552, 95% CI: 0.361−0.845, p = 0.006), as well as prolonged overall survival rates for patients with hypermutation ≥7% (HR: 0.291, 95% CI: 0.137−0.618, p = 0.001). Our results provide new insights into the molecular characterization of multiple myeloma, highlighting the need to evaluate some of these clonal rearrangement characteristics as new potential prognostic markers.

This study was supported by the Centro de Investigacion Biomedica en Red—Area de Oncologia—del Instituto de Salud Carlos III (CIBERONC; CB16/12/00369; and CB16/12/00489), Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria (FIS No. PI13/02196), Asociacion Espanola Contra el Cancer (GCB120981SAN and the Accelerator Award), CRIS against Cancer foundation grant 2014/0120, and the Black Swan Research Initiative of the International Myeloma Foundation.

The work was supported by the Deutsche Forschungsgemeinschaft (KFO216), the IZKF, the BTHA and the CDW Stiftung (KMK). UM was supported by a grant of the German Excellence Initiative to the Graduate School of Life Sciences, University of Wurzburg.

Background: Progression and relapse in Multiple Myeloma (MM) is induced by changes in the clonal tumor composition. In order to better understand the mechanisms underlying these dynamics, we developed clonal competition models based on the co-culture of fluorescent labelled isogenic MM cells, with or without the alteration under study. Methods: To understand the effect of mono- and bi-allelic TP53 lesions, we use the AMO1 cell line, one of few myeloma cell lines harbouring wild type TP53 (WT). After modification with CRISPR / CAS9, we selected subclones with mono- and/or bi-allelic deletion of TP53. For the characterization of alterations in RAS, we selected OPM2 cells, one of the few lines with the RAS pathway intact. Furthermore, we generated the KRAS WT, G12A and A146T sublines by stable transfection with Sleeping Beauty vectors. To study mutations related to resistance to IMIDs and PIs, we introduced mutations in the target genes IKZF1 (WT, A152T, Q170D or R439H), CUL4B (KO), and PSMB5 (WT or A20T ) in AMO1 and L363, cell lines sensitive to IMiD or PI treatment. In addition, all WT and mutant sublines were also stably transformed with E-GFP or LSS-mkate2-RFP for flow cytometry analysis. Results: We recently demonstrated that lesions in TP53, both mono- and bi-allelic, induce a growth advantage to the affected cells. In the current study, we also observed an increased fitness in KRAS mutated cells (G12A or A146T vs WT) independent of treatment. We co-cultivated KRAS mutant with WT cells at a ratio 1:3 in two independent experiments, with the color labelling switched (red/green wt/mutant and vice-versa). KRAS G12A clone significantly expanded and reached 50% of the cells at day 40. Likewise, A146T clone outcompeted WT cells, but the time required to represent the majority of cells in the coculture was longer. We next explored the effects of resistance mutations and drug exposure. Both the IKZF1 A152T and CUL4B KO mutants outcompete WT cells in the presence of Lenalidomide (LEN). The same effect was observed for the PSMB5 A20T mutant exposed to Bortezomib (BOR). This selection ("Survival Fitness") did not occur without the presence of the drug. Thus, resistance related mutations seem only to provide a fitness advantage under drug exposition. In addition, both the CUL4B KO and PSMB5 A20T mutants were overcome by WT cells when the drug was removed from co-culture, suggesting that these lesions provide a survival disadvantage without the selective pressure of IMiD or PI. This may provide an explanation for the low mutation rate in this gene in recent sequencing publications, as usually samples are not obtained under selective pressure but in treatment free intervals. IKZF1 mutations outside the IMiDs / CRBN binding area (Q170D and R439H) provided no advantage to the cells. Conclusions: Our clonal competition assays provide novel insights on the impact of point mutations on the fitness of affected myeloma subclones, either with or without the selective pressure of therapy. Figure Disclosures Martinez-Lopez: Celgene: Honoraria, Other: Advisory boards and Non-Financial Support ; Amgen: Honoraria, Other: Non-Financial Support ; F. Hoffmann-La Roche Ltd: Honoraria; Janssen: Honoraria, Other: Advisory boards and Non-Financial Support ; BMS: Honoraria, Other: Advisory boards; Incyte: Honoraria, Other: Advisory boards; Novartis: Honoraria, Other: Advisory boards; VIVIA Biotech: Honoraria.

Background:The amount of descriptive genetic data in multiple myeloma (MM) is growing exponentially. Clonal dynamics leading to disease progression and resistance development are evident and have been described in a number of exemplary MM patients. Still, for most identified genetic lesions, the specific impact on clinic and biology remains unclear.Aims:Aiming for a better understanding of the underlying mechanisms of clonal progression, we developed clonal competition models, based on co‐culture of fluorescence‐marked isogenic MM cells with or without the alteration under study. This experimental setting allows us to study the implications of a specific lesion and its interactions with different environmental conditions such as drug exposition.Methods:To study the effect of mono‐ and bi‐allelic TP53 lesions and the impact of proteasome subunit mutations we selected the TP53 wild‐type (WT) cell line AMO1. As this cell line has a weak response to IMiDs, we generated L363 sublines with IKZF1 or PSMB5 alterations and MM1S cells with IKZF1 or TP53 lesions. All these sublines and their parental (WT) controls were then stably marked with EGFP or LSS mKate RFP. Then, the co‐cultures with mutant and WT cells were monitored by flow cytometry under different therapeutic conditions.Results:Exploring the CoMMpass dataset, we detected one patient (MMRF_1152) who acquired two sub‐clonal nonsense CUL4B mutations after IMiD exposition. In our clonal competition assays, CUL4B KO cells were selected in the presence of LEN but they induced a survival disadvantage when the drug was not present (Figure, top). We previously described a similar observation regarding PSMB5 mutations affecting the chymotrypsin‐like catalytic core (PI binding). In vitro these alterations generated an impasse on the proteasome activity that potentially affects cell growth (Barrio S, et al. Leukemia 2019). Our results suggest that some of the acquired mutations may induce survival fitness under drug exposition but represent a disadvantage when the therapy is removed. This could explain why such alterations are not being detected more frequently in relapsed MM patients. Of note, however, a hotspot mutation identified in the LEN binding area of IKZF1 (A152T) did not have any negative impact on cell growth without treatment but was selected in the presence of LEN. IKZF1 mutations outside the LEN binding area (Q170D and R439H) did not provide any advantage to the cells. Besides survival fitness, we have also observed growth fitness, a selection that occurs independently of therapy. When cells with mono‐ or bi‐allelic TP53 lesions were co‐cultured with WT cells, a strong growth dynamic was observed. This advantage remained under exposure to Melphalan (MEL) or Bortezomib. Of interest, MEL seems to increase the fitness of cells with mono‐allelic TP53 alterations.Summary/Conclusion:In summary, we observed three different types of fitness advantages (Figure, bottom): Negative survival fitness, induced by drug exposition but with negative impact on basal cell growth as described for CUL4B or PSMB5. Neutral survival fitness (IKZF1), without this negative effect when the drug is absent. Growth fitness, independent of treatment exposition (TP53 mono‐ and bi‐allelic lesions). Altogether, our data suggest that it is possible to apply clonal competition assays to perform analytical or even quantitative genetics. This approach might help in the future to select the best regimen to control the fitness advantages induced in MM cells by patient‐specific lesions.image

Cereblon (CRBN), a target of immunomodulatory drugs (IMiD), forms the CRL4 E3 ubiquitin ligase (CRL4) complex with DDB1, CUL4B and ROC1. Under the influence of IMiD, CRL4 polyubiquitinates and thus depletes the transcription factors IKZF1 and IKZF3, resulting in cytotoxicity to multiple myeloma (MM) cells. In vitro, CRBN and IKZF1/3 mutations affecting the CRBN-lenalidomide binding site (degron) cause drug resistance to IMiD. We hypothesized that mutations in the other components of the CRL4 complex and its targets, Ikaros and Aiolos, likewise interfere with ubiquitin ligase activity, thus contributing to resistance to IMiD. In order to select the most promising patient-derived candidate mutations for functional validation, we first generated a comprehensive overview of point mutations affecting IKZF1, IKZF3 or CRL4 genes in patients with advanced MM. Next, we contextualized all described mutations at the protein level, to investigate their structural impact on complex formation and stability. Based on these analyses, we then selected a subset for functional validation by expressing mutant IKZF1, CRBN or CUL4B in MM cell lines and analyzed their effects on resistance to IMiD, thus probing the relevance of such alterations for complex integrity and the transmission of IMiD activity. To select relevant candidate mutations, we analyzed data from different Multiple Myeloma Mutation panel (M3P) cohorts and from other published and unpublished datasets for a total of 1,838 MM cases (Online Supplementary Methods). In this meta-analysis we observed that the mutation frequency increased significantly after treatment (Z-score: 4.5; P<0.00001), from 2.0% (28/1373) in untreated cases to 6.2% (29/465) in pretreated cases. Notably, this increase occurred predominantly in three genes, IKZF1 (0.15% to 1.3%, Z-

Abstract Introduction High-throughput sequencing studies have rendered seminal knowledge in monoclonal gammopathies such as multiple myeloma (MM) and Waldenström's macroglobulinemia (WM). Unfortunately, the low incidence of AL amyloidosis and its typically low tumor burden, often masked by a polyclonal plasma cell (PC) background, account for the limited information on its tumor cell biology. Thus, it remains unknown if AL amyloidosis harbors a unifying mutation as occurs in WM or if, in its absence, there are recurrent mutations and if these overlap with those observed in MM. With this background , the aim of this study is to perform a whole exome sequencing (WES) in a series of patients with AL amyloidosis and to compare mutational profiles in AL amyloidosis vs MM and analyze the copy number variation in this series of patients. Methods A total of 27 patients with confirmed diagnosis of AL were included. WES was performed in 56 paired samples of FACSorted bone marrow tumor plasma cells and peripheral blood mononucleated cells. Each tumor sample was captured in triplicate using Agilent's SureSelect Human All Exon V6 + UTR kit and sequenced on the Illumina NextSeq 500 platform. Data was analyzed with Strelka software to discard germinal mutations, ANNOVAR for functional annotation, and a data reduction strategy to identify candidate variants. The mutational signature was analyzed with Mutational Signatures in Cancer (MuSiCa) software. We used the MMRF CoMMpass dataset (895 patients) to compare the mutational landscape of MM vs AL. We also determined immunoglobulin gene rearrangements in AL by next generation sequencing. Besides, we analyzed the copy number variation (CNV) with CNVkit program. Results The mean depth coverage for control and tumor samples was 64x and 186x, respectively. A total of 1983 somatic SNV and 133 INDEL were identified, with an average of 71 (20-281) SNV and 5 (0-25) INDEL per patient. Overall, the most frequently mutated genes in this series were IGLL5 and MUC16 (recurrence of 17% each). When compared to MM (average of 66 SNV and 2,5 INDEL), we observed a similar mutational load. However, none of the most frequently mutated genes in MM (i.e. KRAS, NRAS, FAM46C, BRAF, TP53, DIS3, PRDM1, SP140, RGR1, TRAF3, ATM,CCND1, HISTH1E, LTB, IRF4, FGFR3,RB1, ACTG1, CYLD, MAX, ATR) were recurrently mutated in patients with AL. The only genes commonly mutated in AL amyloidosis and MM were MUC16 (recurrence of 17% and 8%, respectively) and IGLL5 (recurrence of 17% each).Most patients with AL harbored between 1 and 8 mutational signatures, implying that multiple mutational processes are operative. The most frequent mutational signature were (signatures 6, 15 and 20) associated with mismatch repair protein deficiency (MMR) and high microsatellite instability (93%), mutational signature 2 (89%), related with the aberrant activity of APOBECs, a family of proteins that enzymatically modify single-stranded DNA and mutational signature 1 (81%), profile that appear in all types of cancers and has been correlated with the age of cancer diagnosis. The signature 2 is also representative of MM. Regarding the immunoglobulin gene repertoire, we noted that 26% of patients with AL harbored more than one clone; this extent in clonal heterogeneity being similar to that found in MM (23%).The most frequent IGH gene involved was IGHV3-30 in both AL (recurrence of 10%) and MM (recurrence of 12%).Regarding CNV, recurrent gains included chromosomes 1q (29%), 5 (38%), 6p (14%), 7 (43%), 9 (43%), 15 (24%), 18 (14%) and 19 (43%). Recurrent losses affected chromosome 13 (33%), 6q (14%) and 16q (19%). Conclusions This is the first WES study performed in a series of patients with AL. We demonstrated the lack of a common driver mutation in this disease and unveiled that recurrently mutated genes in AL amyloidosis do not overlap with those observed in MM. We also confirm the existence of numerous chromosomal alterations in patients with AL. The frequencies of aberrations and alterations detected by NGS are comparable with those describe in previous studies by copy number array analysis, but here we show some novel recurrent chromosomal aberrations as gain of chromosome 7 (43%) and losses of chromosome 18 (14%). Overall, these results may have significant impact in our understanding of the pathogenesis of AL amyloidosis and its differential diagnosis vs other monoclonal gammopathies. Disclosures Ocio: BMS: Consultancy; Novartis: Consultancy, Honoraria; Sanofi: Research Funding; Takeda: Consultancy, Honoraria; Seattle Genetics: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Honoraria; Pharmamar: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Mundipharma: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Array Pharmaceuticals: Research Funding. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. Oriol:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Puig:Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Celgene: Honoraria, Research Funding. Lahuerta:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Mateos:Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; BMS: Honoraria; Novartis: Honoraria; Sanofi: Honoraria; Roche: Honoraria. Martinez Lopez:Novartis: Research Funding, Speakers Bureau; Jansen: Research Funding, Speakers Bureau; BMS: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau.

Next-generation sequencing has substantially improved our understanding of the genomic landscape of multiple myeloma; however, the application of this technology has been confined mostly to research studies. Here, we report on a customized panel to characterize the mutational profile of 79 newly diagnosed patients with multiple myeloma, older than 65 years and who were not transplant candidates, applying the highest read depth to date that has been used for equivalent studies in multiple myeloma. Overall, we identified 53 genes mutated in 85% of patients, including KRAS, NRAS, BRAF, DIS3 and TP53, and found a complex subclonal structure. In addition, the total number of mutations, as well as mutations in TP53 and the Cereblon pathway, were negatively associated with survival. The latter result is particularly noteworthy as patients enrolled in this phase II clinical trial were treated with lenalidomide, which targets this pathway. Our next-generation sequencing strategy not only identified a group of patients with poor outcome, but also provided an extensive genetic profile that should prove useful in the search for new biomarkers and therapeutic targets in multiple myeloma, at an affordable price and with a small amount of sample, which are indispensable features for translating personalized medicine protocols to clinical practice.

Despite an increasing number of approved therapies, multiple myeloma (MM) remains an incurable disease and only a small number of patients achieve prolonged disease control. Some genes have been linked with response to commonly used anti-MM compounds, including immunomodulators (IMiDs) and proteasome inhibitors (PIs). In this manuscript, we demonstrate an increased incidence of acquired proteasomal subunit mutations in relapsed MM compared to newly diagnosed disease, underpinning a potential role of point mutations in the clonal evolution of MM. Furthermore, we are first to present and functionally characterize four somatic PSMB5 mutations from primary MM cells identified in a patient under prolonged proteasome inhibition, with three of them affecting the PI-binding pocket S1. We confirm resistance induction through missense mutations not only to Bortezomib, but also, in variable extent, to the next-generation PIs Carfilzomib and Ixazomib. In addition, a negative impact on the proteasome activity is assessed, providing a potential explanation for later therapy-induced eradication of the affected tumor subclones in this patient.