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AimsAmyloidosis is caused by deposition of abnormal protein fibrils, leading to damage of organ function. Hereditary amyloidosis represents a monogenic disease caused by germline mutations in 11 amyloidogenic precursor protein genes. One of the important but non-specific symptoms of amyloidosis is hypertrophic cardiomyopathy. Diagnostics of hereditary amyloidosis is complicated and the real cause can remain overlooked. We aimed to design hereditary amyloidosis gene panel and to introduce new next-generation sequencing (NGS) approach to investigate hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance.MethodsDesign of target enrichment DNA library preparation using Haloplex Custom Kit containing 11 amyloidogenic genes was followed by MiSeq Illumina sequencing and bioinformatics identification of germline variants using tool VarScan in a cohort of 40 patients.ResultsWe present design of NGS panel for 11 genes (TTR, FGA, APOA1, APOA2, LYZ, GSN, CST3, PRNP, APP, B2M, ITM2B) connected to various forms of amyloidosis. We detected one mutation, which is responsible for hereditary amyloidosis. Some other single nucleotide variants are so far undescribed or rare variants or represent common polymorphisms in European population.ConclusionsWe report one positive case of hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance and set up first panel for NGS in hereditary amyloidosis. This work may facilitate successful implementation of the NGS method by other researchers or clinicians and may improve the diagnostic process after validation.

Monoclonal gammopathy of undetermined significance (MGUS) is a benign condition with an approximate 1% annual risk of symptomatic plasma cell disorder development, mostly to multiple myeloma (MM). We performed genomewide screening of copy-number alterations (CNAs) in 90 MGUS and 33 MM patients using high-density DNA microarrays. We identified CNAs in a smaller proportion of MGUS (65.6%) than in MM (100.0%, P = 1.31 × 10-5 ) and showed median number of CNAs is lower in MGUS (3, range 0-22) than in MM (13, range 4-38, P = 1.82 × 10-10 ). In the MGUS cohort, the most frequent losses were located at 1p (5.6%), 6q (6.7%), 13q (30.0%), 14q (14.4%), 16q (8.9%), 21q (5.6%), and gains at 1q (23.3%), 2p (6.7%), 6p (13.3%), and Xq (7.8%). Hyperdiploidy was detected in 38.9% of MGUS cases, and the most frequent whole chromosome gains were 3 (25.6%), 5 (23.3%), 9 (37.8%), 15 (23.3%), and 19 (32.2%). We also identified CNAs such as 1p, 6q, 8p, 12p, 13q, 16q losses, 1q gain and hypodiploidy, which are potentially associated with an adverse prognosis in MGUS. In summary, we showed that MGUS is similar to MM in that it is a genetically heterogeneous disorder, but overall cytogenetic instability is lower than in MM, which confirms that genetic abnormalities play important role in monoclonal gammopathies.

Flow cytometry (FCM) has found its application in clinical diagnosis and evaluation of monoclonal gammopathies (MG). Although, research has been mainly focused on multiple myeloma (MM), nowadays FCM becomes to be potential tool in the field of AL amyloidosis. Clonal plasma cells identification and specific phenotype profile detection is important for diagnosis, monitoring and prognosis of AL amyloidosis. Therefore, FCM could be a perspective method for study not only MM but also AL amyloidosis. This review provides an overview and possibilities of FCM application in AL amyloidosis.

Immunoglobulin light chain amyloidosis (AL amyloidosis - ALA) is a monoclonal gammopathy characterized by presence of aberrant plasma cells producing amyloidogenic immunoglobulin light chains. This leads to formation of amyloid fibrils in various organs and tissues, mainly in heart and kidney, and causes their dysfunction. As amyloid depositing in target organs is irreversible, there is a big effort to identify biomarker that could help to distinguish ALA from other monoclonal gammopathies in the early stages of disease, when amyloid deposits are not fatal yet. High throughput technologies bring new opportunities to modern cancer research as they enable to study disease within its complexity. Sophisticated methods such as next generation sequencing, gene expression profiling and circulating microRNA profiling are new approaches to study aberrant plasma cells from patients with light chain amyloidosis and related diseases. While generally known mutation in multiple myeloma patients (KRAS, NRAS, MYC, TP53) were not found in ALA, number of mutated genes is comparable. Transcriptome of ALA patients proves to be more similar to monoclonal gammopathy of undetermined significance patients, moreover level of circulating microRNA, that are known to correlate with heart damage, is increased in ALA patients, where heart damage in ALA typical symptom.Key words: amyloidosis - plasma cell - genome - transcriptome - microRNA.

Introduction: Multiple myeloma (MM) is a plasma cell dyscrasia causing damage of multiple organs with fatal consequences for patients. Despite the success of modern therapies eliminating a vast bulk of the aberrant cells, surviving residual clones eventually lead to the relapse of the disease. Accumulation of genomic alterations during the stage of minimal residual disease (MRD) likely contributes to a selective grow advantage and survival under the drug pressure. Identification of specific mutations in MM patients with MRD can provide unique opportunities to target the residual plasma cell clones. Here we present the first whole exome sequencing (WES) analysis of 22 MM samples of patients with MRD that identified 814 mutated genes with 4% of genes previously implicated in the pathogenesis of MM. Methods: Aberrant plasma cells (A-PCs) and peripheral blood (PB) were collected from patients after signing informed consent form. Presence of MRD was assessed with EuroFlow protocol and A-PCs were sorted out from bone marrow according to their pathological immunophenotype based on the expression of antigens CD38, CD45, CD19 and CD56. DNA from A-PCs was isolated and amplified by Repli-g Single cell kit (QIAGEN). Sequencing libraries were prepared using SureSelect Human All Exon V6 Kit (Agilent Technologies) and sequenced by Macrogen Inc. on Illumina HiSeq 4000 platform with average coverage 50x and 2x 100bp read length. Sequencing data were processed using the Bcbio framework following the standard workflow for tumor-matched-normal studies. Specifically, reads were mapped to the human reference genome GRCh37, successively marking duplicates using Picard. Germline mutations were identified using GATK HaplotypeCaller, whereas somatic mutations were identified using MuTect2 reporting as significant variants observed in at least 5 reads and minimum allele frequency of 10%. Variants in homopolymer regions longer than 5 nucleotides were filtered out. The final set of calls were further characterised by assessing their functional impact using snpEff and by annotating each variant using data from 1000 Genomes Phase 3, ExAC, and ClinVar. We then used OncodriveCLUST to identify putative oncogenic genes, and later compared these results with a literature curated list of MM driver genes (Weaver & Tariman, 2017). Results: Our dataset comprises 22 samples from 21 patients (one patient was sampled in two time points) with MM MRD, who received bortezomib-based regimen (age 41-71, average 59 years, 11/22 males, 10/22 females). 8 patients reached complete response, 9 patients had very good partial response and 4 patients had partial response. In our analysis, we detected 1,014 tumour somatic variants (8-287 per sample, median 36), most of them being missense mutations (676/1014), splice site mutations (145/1014) and frameshift insertions (134/1014). The variants affected a total of 814 genes, 97 genes were shared in at least two samples. The most frequently mutated genes were KIAA1211 (11/22), the immunoglobulin gene IGLV3-1 (8/22), apoptotic chromatin condensation inducer ACIN1 (7/22) and CCR4-associated factor 3 CNOT3 (7/22). We also identified 32 genes known to be mutated in MM in 64% of our samples (14/22). We found mutations shared by at least 2 samples in KRAS (4/22), DIS3 (3/22), TRAF3 (3/22), NRAS (2/22), ANK2 (2/22), BRAF (2/22) and RBM15 (2/22). Further analysis with OncodriveCLUST identified 18 putative oncogenic genes (FDR < 0.1), including KRAS, DIS3, ACIN1. Conclusion: We presented the first whole exome study of MM MRD, providing a characterisation of the mutations observed in A-PCs. We overcame problem with low amount of A-PCs in this disease stage by using whole genome amplification and a highly customised bioinformatic analysis pipeline. Our study suggests that A-PCs are characterised by new MM MRD specific set of mutated genes, along with the presence of mutations in well-known multiple myeloma cancer driver genes. This offers a great potential for design of novel precise treatments targeting MRD after standard MM therapies. Supported by Ministry of Health of the Czech Republic (17-30089A, CZ-DRO-FNOs/2016) and Ministry of Education of the Czech Republic (SGS18/PřF/2017-2018) Disclosures Kryukov: JSC BIOCAD: Employment. Maisnar:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Hajek:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Novartis: Research Funding.

Waldenströms macroglobulinemia (WM) is a B-cell malignancy characterized by high level of monoclonal immunoglobulin M (IgM) paraprotein in blood serum and associated with the bone marrow infiltration by malignant cells with lymphoplasmacytic differentiation. WM remains incurable advances in therapy. Most of WM cases are associated with a somatic point mutation L265P in MYD88. Significantly higher risk of progression from the IgM monoclonal gammopathy of undetermined significance (IgM MGUS) to WM for patients with mutated MYD88 gene suggests that this mutation is an early oncogenic event and plays a central role in development of malignant clones. The second, most prevalent mutation in WM is found in the CXCR4 gene and is often associated with drug resistance and aggressive disease presentation. Therefore, detection of these mutations (MYD88L265P and CXCR4S338X) could be useful diagnostic and prognostic tool for the patients with WM. While detection of these mutations in bone marrow sample is common, the aim of our study was to compare sensitivity of detection of mutation from different cell fraction from peripheral blood and bone marrow. The results show possibility to describe MYD88 and CXCR4 mutation status even from peripheral blood sample (sensitivity for MYD88L265P was 100%, for CXCR4S338X 91%), which significantly facilitate material collection. Moreover, comparable detection sensitivity of these mutations in bone marrow and peripheral blood samples examined before and during the therapy offers a promising tool for more routine diagnostic and monitoring of disease progression.Key words: Waldenström macroglobulinemia - hematology - neoplasms - lymphoma - mutation - MYD88 - CXCR4.

Immunoglobulin light chain amyloidosis (AL amyloidosis) is indeed a rare plasma cell disorder, yet the most common of the systemic amyloidoses. The choice of adequate treatment modality is complicated and depends dominantly on the risk stratification of these fragile patients. Immunomodulatory drugs (IMiDs) are currently used in newly diagnosed patients as well as in salvage therapy in relapsed/refractory patients. IMiDs have a pleiotropic effect on malignant cells and the exact mechanism of their action has been described recently. Thalidomide is the most ancient representative, effective but toxic. Lenalidomide seems to be more effective, nevertheless the toxicity remains high, especially in patients with renal insufficiency. Pomalidomide is the newest IMiD used in this indication with a good balance between efficacy and tolerable toxicity and represents the most promising compound. This review is focused on the evaluation of all three representatives of IMiDs and their roles in the treatment of this malignant disorder.

Introduction: Release of the aberrant plasma cells (PC) from the bone marrow (BM) and their presence in the peripheral blood (PB) is a maker of disease progression and worse survival in multiple myeloma (MM) (Nowakowski et al., 2005). Circulating plasma cells (cPCs) are able to survive without homing microenvironment, evade the original tumor and colonize other bone marrow niche. Detailed analysis of various surface proteins showed that cPCs display decreased levels of integrins, adhesion molecules N-CAM (CD56) and the stem cell factor receptor (Paiva et al., 2013). Comprehensive analysis of the genome-wide gene expression profiling that could provide deeper insight into the expression patterns of cPCs of MM is still lacking. Aims: To identify differentially expressed genes in paired samples of aberrant plasma cells from BM and PB and to describe potential biomarkers of cPCs in MM. Material and methods: Ten patients with multiple myeloma (seven new diagnoses and three relapses) have been included in the study after signing the informed consent form. Paired samples of aberrant plasma cells from bone marrow and peripheral blood were obtained from each patient. Aberrant plasma cells (aPCs) were sorted according to the immunophenotype as CD45dim/CD38+/CD19-/CD56-/+ cells. Gene expression profiling (GEP) was performed on paired samples using Affymetrix GeneChip Human Gene ST 1.0 array. RMA normalized data at gene level were analyzed using Wilcoxon paired test with Benjamini-Hochberg multiple testing correction. Results: The median infiltration of aberrant PC in the BM was 27.5% (range 1.1 - 93%) and 1.2% (range 0.19 - 2.8%) for cPCs in the PB. The median level of M-protein was 32.35 g/l (range 18.6 - 62.2 g/l). GEP analysis of paired BM and PB samples revealed 1001 significantly changed genes in cPCs (adjusted p-value Conclusion: The infiltration of aPCs in the bone marrow does not correlate with the amount of cPCs (p=0.16). Among differentially expressed genes, two surface markers upregulated in cPCs are of particular interest: CD44 and ADGRE5 (CD97). The CD44 antigen is a cell-surface glycoprotein involved in cell-cell interactions, cell adhesion and migration. Moreover, CD44 contribute to lenalidomide resistance in multiple myeloma (Bjorklund et al., 2014). CD97 is encoded by ADGRE5 gene and belongs to the EGF-TM7 subgroup of adhesion G-protein-coupled receptors. The expression of CD97 has been linked to invasive behavior in thyroid and colorectal cancer. Moreover, higher CD97 expression levels have been detected in 54% (208/385) of primary AML samples based on flow cytometric analysis (Wobus et al., 2015). Nevertheless, neither ADGRE5 nor CD97 expression were described in plasma cell dyscrasia previously. Thus, despite non-systemic changes of gene expression at the whole transcriptome level, cPCs in MM likely represent distinct biological entity with specific expression profile underlying advanced PC malignant transformation. To confirm the results, flow cytometric analysis on the bigger cohort will be performed. Acknowledgment: This study was supported by Institutional Development Plan of University of Ostrava (IRP201550) and The Ministry of Education, Youth and Sports (Specific university research of the Faculty of Medicine, University of Ostrava) project no. SGS03/LF/2015-2016, Ministry of Health Czech Republic RVO-FNOs/2014/17P and RVO-FNOs/2016/21. Figure 1 Genes of interest differentially expressed in the bone marrow (BM) versus peripheral blood (PB) aberrant plasma cells. Figure 1. Genes of interest differentially expressed in the bone marrow (BM) versus peripheral blood (PB) aberrant plasma cells. Disclosures Hajek: BMS: Honoraria; Onyx: Consultancy; Novartis: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding.

Introduction: Malignant transformation of normal to tumour cells is a multistep process followed by sequential aggregation of hits at different molecular levels. Genetic events including single nucleotide variants (SNVs), insertion-deletion changes (indels) as well as copy number variants (CNVs) affect the phenotype of the tumour population and consequently patient prognosis. Transformation from a symptomless state, monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) can be used as a unique model for cancer development studies. To date, there is very little data regarding the mechanisms leading to disease progression at molecular level. In our study, we performed exome sequencing together with SNP array analysis on 33 MGUS patients to describe the premalignant phenotype and compared these to advanced tumour cells at the DNA level. We hypothesised that increased genetic instability indicated MGUS patients with a high risk of progression to MM. Methods: 33 MGUS patients (M:F 1.5:3; median age 61, range: 35-86) were included in this study. Plasma cells were isolated from bone marrow by FACSAria (BD Biosciences) system using CD138, CD19 and CD56 markers to obtain a pure abnormal plasma cell population with a purity >90%. Tumour DNA was isolated using Gentra Puregene Kit and amplified using REPLI-g Midi Kit (both Qiagen); control DNA was gained from peripheral white blood cells by MagNA Pure System (Roche Diagnostics). For exome sequencing, NEBNext kit (NEB) and SureSelect Human All Exon V5 (Agilent Technologies) were used and samples were sequenced by HiSeq2000 (Illumina) using 76-bp paired end reads. Unbalanced CNVs were tested by SurePrint G3 CGH+SNP, 4x180K (Agilent Technologies). Results were compared to 463 MM patients. Results: In our analysis, we found acquired SNVs in 100% (33/33) MGUS patients with a median of 89 (range 9-315) SNVs per patient. Non-synonymous SNVs (NS-SNVs) were present in 97% (32/33) cases with a median 19 (range 0–70) NS-SNVs per patient. Overall, 42 genes were recurrently mutated in at least 2 patients and 6 genes were mutated in at least 3 cases including MUC16, IGK, TTN, KLHL6, AKAP9 and NPIPL2. We identified 7 genes which were significantly mutated in MM in our previous study including KRAS (n=2), HIST1H1E (n=2) and NRAS, DIS3, EGR1, LTB, PRKD2 (all n=1). IGH translocations were identified in 27% (9/33) of patients: t(11;14) in 12% (4/33), t(4;14) in 9% (3/33), t(14;16) in 3% (1/33) and t(14;20) in 3% (1/33). We did not find any translocations involving MYC (8q24.21) or the light chain loci IGK (2p12) and IGL (22q11.2). Using SNP arrays, unbalanced CNVs were presented in 67% (22/33) of MGUS patients and detected CNVs showed similarity to MM across the cohort. As previously described in MM, only one type of IGH translocation was found per patient and all 9 cases with IGH translocation did not have additional hyperdiploidy. Furthermore, we identified a patient with two CCND1 (p.K50T, p.E51D) mutations and a t(11;14), a case with a DIS3 (p.D488N) mutation and a 13q loss. Moreover, we noticed a co-segregation of cases t(4;14) and t(14;16) who all had a 13q loss (100%, 4/4). In contrast none of the patients (0/5) with a t(11;14) or a t(14;20) had a 13q loss. Of note 29% (7/24) patients without any IGH translocation had a 13q loss. Sixty seven percent (2/3) of patients with a t(4;14) and the one case with a t(14;16) also had a 1q gain. In comparison, none of patients with a t(11;14) (0%; 0/4) had a 1q gain. Unlike what has previously been described in MM, neither of the 2 MGUS patients with a KRAS (p.Q61L and p.A146T) mutations had a t(11;14). We also identified a patient with both a KRAS (p.Q61L) and an NRAS (p.G13R) mutation which are although not mutually exclusive, negatively correlated in MM. Importantly, we did not find any mutations in TP53, ATM, ATR and ZFHX4 genes involved in DNA repair pathway alterations which were identified as unfavourable factors in survival of MM patients. Summary: We have performed the first comprehensive analysis of 33 MGUS patients using exome sequencing together with SNP arrays and described the main genetic events that are already present in this premalignant state. We found similarities to MM in terms of SNVs, CNVs and their correlations. We identified 6 MGUS cases with NS-SNVs in potential key genes that could indicate a potential high risk to progression. Support: IGA MH CZ NT13492, OPVK CZ.1.07/2.3.00/20.0183. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

Background Immunoglobulin light chain amyloidosis (AL amyloidosis) is a plasma cell dyscrasia characterized by deposition of amyloid fibrils in various organs and tissues, derived from monoclonal immunoglobulin light chains (LC), leading to organ dysfunction. Until now there is no systematic study of genomic expression of patients with AL amyloidosis compared to other monoclonal gammopathies. Aim of this study was to reveal genomic expression differences between AL amyloidosis patients versus healthy donors (ND), monoclonal gammopathy of undetermined significance (MGUS), smouldering myeloma (SMM) and multiple myeloma (MM) patients. Methods Gene expression profiling data from GEO database (GSE6477, GSE24128) comprised of ND (n=15), MGUS (n=21), SMM (n=24), MM (n=69) and AL (n=16) patients were used. To ensure the comparability between arrays and eliminate the batch effect, quantile normalization was performed. To identify the AL patients´ gene expression profile which significantly differs in comparison with ND, MGUS, SMM or MM patients, we applied SAM algorithm for 6588 selected genes that fulfilled the condition having standard deviation above the median. Genes with fold change ≥1.5 or ≤0.5 and false discovery rate >0.001 were considered as significant. Prediction analysis of microarrays (PAM) using nearest shrunken centroids and cross validation assay was carried out to identify the smallest subsets of genes that were able to accurately predict classes. Results Comparison of AL patients vs. ND revealed 229 changed genes, AL vs. MGUS 126 genes, AL vs. SMM 338 genes and AL vs. MM 110 genes, respectively. Out of them, the most significantly changed 100 genes from each comparison were further analysed. Some of the genes occurred repeatedly, thus only 256 of genes from all comparisons were unique. Using PAM algorithm we found the genes that have the best predictive power for differentiation AL patients from ND, MGUS, SMM and from MM patients was as followed: RPS6, RPS14, RPS17, RPLA18A, TMEM66, EIF3L, CCDC72, GLTSCR2, NDUFS6, DUSP1, IGLJ3, IGHM, IGKV1-5IGKC///IGKV1-5///IGKV1D-8 and IGHA1///IGHA2///IGHD///IGHG1///IGHG3///IGHG4///IGHM/// IGHV3-23///IGHV4-31///IGHV4-59. Gene expression changes are presented on Figure 1. Conclusion Based on offered meta-analysis, 16 genes representing mostly ribosomal proteins and immunoglobulin regions allow us to detect specific aberrant clone responsible for pre-amyloid production and can serve as candidates for further detailed study. Work was supported by grants IGA NT 12130, NT 14575 and NT 13190. Figure 1. Gene expression for the genes which best discriminate AL patients from ND, MGUS, SMM and MM patients Figure 1. Gene expression for the genes which best discriminate AL patients from ND, MGUS, SMM and MM patients Disclosures Hajek: Merck: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Honoraria.