Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

1 Vol.:(0123456789) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports Whole‑genome optical mapping of bone‑marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities Eva Kriegova1*, Regina Fillerova1, Jiri Minarik2, Jakub Savara1,3, Jirina Manakova1, Anna Petrackova1, Martin Dihel1, Jana Balcarkova2, Petra Krhovska2, Tomas Pika2, Petr Gajdos3, Marek Behalek3, Michal Vasinek3 & Tomas Papajik2 Extramedullary disease (EMM) represents a rare, aggressive and mostly resistant phenotype of multiple myeloma (MM). EMM is frequently associated with high‑risk cytogenetics, but their complex genomic architecture is largely unexplored. We used whole‑genome optical mapping (Saphyr, Bionano Genomics) to analyse the genomic architecture of CD138+ cells isolated from bone‑marrow aspirates from an unselected cohort of newly diagnosed patients with EMM (n = 4) and intramedullary MM (n = 7). Large intrachromosomal rearrangements (> 5 Mbp) within chromosome 1 were detected in all EMM samples. These rearrangements, predominantly deletions with/without inversions, encompassed hundreds of genes and led to changes in the gene copy number on large regions of chromosome 1. Compared with intramedullary MM, EMM was characterised by more deletions (size range of 500 bp–50 kbp) and fewer interchromosomal translocations, and two EMM samples had copy number loss in the 17p13 region. Widespread genomic heterogeneity and novel aberrations in the high‑risk IGH/IGK/IGL, 8q24 and 13q14 regions were detected in individual patients but were not specific to EMM/MM. Our pilot study revealed an association of chromosome 1 abnormalities in bone marrow myeloma cells with extramedullary progression. Optical mapping showed the potential for refining the complex genomic architecture in MM and its phenotypes. Abbreviations EMM Extramedullary multiple myeloma MM Multiple myeloma BM Bone marrow HMW DNA High molecular weight DNA FISH Fluorescence insitu hybridization NGS Next-generation sequencing BMMC Bone marrow mononuclear cell SV Structural variant VAF Variant allele frequency CNV Copy number variation OPEN 1Department of Immunology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Hnevotinska 3, 779 00 Olomouc, Czech Republic. 2Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Czech Republic. 3Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava, Czech Republic. *email: [email protected] 2 Vol:.(1234567890) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ FICTION Fluorescence immunophenotyping and interphase cytogenetics as a tool for investigation of neoplasms CT Chromosome territory Multiple myeloma (MM) is a clonal plasma cell proliferative disorder usually limited to a bonemarrow (BM) microenvironment. Rarely, patients present with extramedullary disease (EMM), in which myeloma cells spread to other organ systems1–3. This aggressive and mostly treatment-resistant sub-entity of MM can either accompany a newly diagnosed disease, occurring at a frequency of 3–18%4,5, or develop with disease progression or relapse, with a frequency of 6–20%4,6. Currently, little is known about the mechanisms leading to the development of EMM, stroma-independent growth and the survival of myeloma cells at extramedullary sites or the reasons for poor treatment responses. There is growing evidence that genetic factors may contribute to EMM pathogenesis and evolution1,4,5. Genetic studies have shown that high-risk abnormalities, such as 1q21 gain and del(1p32) (detected in > 55% of EMM patients), t(4;14) (~ 52%), MYC overexpression (~ 38%), del(17p13) (~ 35%) and del(13q14) (~ 31%), are commonly associated with EMM1,4,5. The disruption of the TP53 gene by del(17p) and/or mutations seems to be a crucial driver of EMM (EMM vs MM: 34.5% vs 11.9%)7,8. Mutations in the RAS9, KRAS, PIK3CA, ATM and NFKB21 genes have also been associated with the presence of EMM, including CRBN mutations leading to treatment resistance10. Other important aberrations in EMM include the activating mutations in the NF-κB pathway genes and the homozygous deletion of the genes encoding inhibitors of this pathway11. The resulting constitutive activation of NF-κB enhances the expression of adhesion molecules, such as integrinVLA-4, CD-44, P-selectin and numerous chemokines/receptors6,12, leading to the migration and stroma-independent growth of myeloma cells11. Additional genetic aberrations may occur in patients with extramedullary mass due to clonal evolution7,13. However, the complex genetic architecture in MM and EMM is still poorly understood, likely due to its complexity and heterogeneity. Therefore, we applied novel whole-genome optical mapping to investigate the complex genomic architecture of BM myeloma cells in newly diagnosed MM and EMM patients. This method has an advantage in detecting small and large structural rearrangements as well as complex rearrangements across the whole genome that are undetectable by traditional methods, such as sequencing and cytogenetics14. The characterisation of genetic architecture in EMM could significantly contribute to the understanding of EMM pathogenesis with the potential to discover new prognostic and diagnostic biomarkers and improve the outcome of this MM entity. Moreover, a comparison of MM and EMM may help to elucidate genetic events, allowing the dissemination of myeloma cells from BM to blood and distant tissues. Materials and methods Subject enrolment. BM aspirates were obtained from an unselected cohort of 11 newly diagnosed MM patients with EMM presentation (n = 4; median age: 77years, min–max: 51–79; M/F: 3/1) and without EMM (MM, n = 7; 75years, 62–82; 5/2). Patients were diagnosed according to the International Myeloma Working Group criteria15. The only criteria for patient enrolment were sampling at diagnosis and a sufficient number of sorted cells to perform all genetic analyses (≥ 2 million myeloma cells). In our patients,all EMM sites were bone related, with two in the thoracic spine and two in the pelvis (one in the iliac bone and one in the acetabulum). Patient’s clinical and demographic data are summarised in Table1 and TableS1. For all patients, karyotype, FISH (fluorescence insitu hybridization, TableS2), arrayCGH (TableS3) and next-generation sequencing (NGS) for mutations in the TP53, KRAS, NRAS and BRAF genes (TableS2) were available. All patients provided written informed consent about the usage of BM for this study, which was performed in accordance with the Helsinki Declaration and approved by the ethics committee of the University Hospital and Palacký University Olomouc. Collection of BM aspirates. BM aspirates (2.5–10ml) were collected in a 5ml RPMI-1640 medium (Sigma-Aldrich, MO, USA) containing 5000IU/ml heparin (Zentiva, Prague, Czech Republic). BM mononuclear cells (BMMCs) were collected after red blood cell lysis (155mM NH4Cl, 10mM KHCO3, 0.1mM Na2EDTA, pH 7.3) by centrifugation (1000g, 5min). After washing with phosphate-buffered saline containing 0.5M EDTA (Sigma-Aldrich) and 2% FBS (Thermo Fisher Scientific, MA, USA), the total count of BMMCs and the infiltration of CD138+ cells were determined by BD FACSCanto II (BD Biosciences, CA, USA). CD138+ plasma cells were enriched using an EasySep Human CD138 positive Selection Kit II (STEMCELL Technologies, Vancouver, Canada), according to the manufacturer’s instructions. The enriched myeloma cells were quantified by BD FACSCanto II (BD Biosciences, CA, USA) using a combination of CD19/CD38/CD45/CD56/CD138 antibodies (BioLegend, CA, USA). After centrifugation (2000g, 2min), dry pellets of 0.6–2.5 million myeloma cells were stored at − 80°C for further analysis. Isolation of high molecular weight DNA, labelling and analysis. Frozen myeloma cell pellets were processed following the Bionano Prep SP Frozen Cell Pellet DNA Isolation Protocol16. High molecular weight (HMW) genomic DNA was isolated using the SP Blood and Cell Culture DNA Isolation Kit (Bionano Genomics, CA, USA, #80030), according to the manufacturer’s recommendations. DNA quantification was performed using the Qubit dsDNA BR assay kit (Thermo Fisher Scientific) with a Qubit 2.0 Fluorometer (Thermo Fisher Scientific). A total of 750–1000ng of HMW DNA was then labelled using the Bionano Prep Direct Label and Stain DLS DNA Kit (Bionano Genomics, #80005), according to the manufacturer’s protocol17. The HMW-labelled DNA (within the recommended range of 8–25 labels/100kbp) was loaded into the Saphyr Chip (Bionano Genomics, 3 Vol.:(0123456789) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ #20319) flow cell at a concentration of 4–12ng/μl and analysed using a Bionano Saphyr instrument, according to the manufacturer’s instructions18, targeting 100–300× human genome coverage by collecting 500–1300GB of data per sample. Data assembly, structural variant calling and the identification of breakpoint regions. All data were analysed using Bionano Access software (v1.5) containing the Bionano Solve tool (v3.5) and featuring both de novo and rare variant bioinformatics pipelines (Fig.1), according to the manufacturer’s recommendations1–21. Only DNA molecules with a minimum length of 150kbp were used for bioinformatics analysis along with a minimum of nine labels per molecule. Briefly, the de novo pipeline’s first assembly of all single molecules was based on the distinct distribution of sequence labels by pairwise alignment. The aligned molecules created consensus maps (contigs) in de novo genome maps, which were compared with the in silico DLE1 labelled human hg38 reference map. This pipeline revealed structural variants (SVs) from 500bp to tens of Mbp long. In the rare-variant pipeline, all single molecules were pairwise aligned against the hg38 reference assembly; molecules with SVs were clustered, and the obtained maps were locally aligned to the hg38 reference sequence. This pipeline was sensitive enough to detect SVs from 5kbp to tens of Mbp long at a variant allele frequency (VAF) as low as 5%. SVs were considered subclonal (i.e. low-allele frequency) when VAF was ≤ 25% and clonal (i.e. high-allele frequency) when VAF was > 25%, based on a cut-off value for neutral evolution in MM11. Additionally, both pipelines included copynumber variation (CNV) analysis to detect the fractional copynumber changes and chromosomal aneuploidy events. Specific hg38 masks concealing common structural variation in a human genome, N-base reference gaps and problematic sub-centromeric and sub-telomeric regions were used in both pipelines. To annotate the SV calls Table 1. Basic demographic and clinical characteristics of enrolled MM and EMM patients. ISS International Staging System, LC monoclonal protein’s light chain, FLC free light chain. a 10% positive cut-off level used. b The full coding sequence of the TP53 gene (exons 2–11, plus 5′ and 3′UTR; NM_000546) and the hotspot regions in NRAS (exons 2–4; NM_002524), KRAS (exons 2–4; NM_004985) and BRAF (exons 11 and 15; NM_004333) were sequenced. Clinical features All patients (n = 11) EMM (n = 4) MM (n = 7) Male/female 8/3 3/1 5/2 Age (years), median (min–max) 77 (51–82) 77 (51–79) 75 (62–82) ISS staging, n (%) ISS I 5 (45.5) 2 (50.0) 3 (42.9) ISS II 1 (9.1) 0 (0.0) 1 (14.3) ISS III 5 (45.5) 2 (50.0) 3 (42.9) Durie-Salmon stage, n (%) IA 1 (9.1) 0 (0.0) 1 (14.3) IIA 4 (36.4) 1 (25.0) 3 (42.9) IIIA 4 (36.4) 2 (50.0) 2 (28.6) IB 1 (9.1) 0 (0.0) 1 (14.3) IIIB 1 (9.1) 1 (25.0) 0 (0.0) LC + FLC, n (%) IgG kappa 5 (45.5) 3 (75.0) 2 (28.6) IgA kappa 4 (36.4) 0 (0.0) 4 (57.1) IgA lambda 2 (18.2) 1 (25.0) 1 (14.3) Cytogenetic analysisa, n (%) t(4;14) 1 (9.1) 0 (0.0) 1 (14.3) t(11;14) 1 (9.1) 0 (0.0) 1 (14.3) Gain (1q21) 6 (54.5) 2 (50.0) 4 (57.1) del(13q14) 4 (36.4) 1 (25.0) 3 (42.8) del(1p32) 1(9.1) 1 (25.0) 0 (0.0) del(17p) 0 (0.0) 0 (0.0) 0 (0.0) Monosomy 5 (45.5) 2 (50.0) 3 (42.8) Trisomy 9 (81.8) 4 (100.0) 5 (71.4) Tetrasomy 5 (45.5) 3 (75.0) 2 (28.6) NGS analysisb, n (%) TP53 0 (0.0) 0 (0.0) 0 (0.0) KRAS 2 (18.2) 1 (25.0) 1 (14.3) NRAS 0 (0.0) 0 (0.0) 0 (0.0) BRAF 3 (27.3) 1 (25.0) 2 (28.6) 4 Vol:.(1234567890) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ Figure1. Workflow of optical mapping and bioinformatics pipelines used. HMW DNA is isolated from CD138+ plasma cells of BM aspirates and labelled by DLS chemistry in specific sequences across entire genomes. Labelled DNA is loaded on the chip and linearised and visualised in a Saphyr instrument. Images are converted to BNX molecules. The architecture of the bioinformatics pipeline includes two pipelines (de novo and rare variant), constructing optical genome maps and comparing them with a human reference map (hg38), filtering detected variants for somatic SVs and merging data from both pipelines. The last step enables a comparison of the data with the gene panels created from NCBI gene datasets. 5 Vol.:(0123456789) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ that were likely somatic variants, a variant annotation pipeline was applied to filter SVs out of the database of ethnically diverse, mapped control human genomes with no reported disease phenotypes. In the next step, annotated SVs and CNVs from both pipelines were merged (Fig.1), including aberrations sized 500bp–5Mbp (deletions, insertions, duplications and inversions) as well as interand intrachromosomal aberrations larger than 5Mbp. The intrachromosomal rearrangements with breakpoints at least 5Mbp apart, e.g. large deletions (supported by copynumber loss), insertions (copynumber gains) or inversions (no change in CNVs) were called intrachromosomal translocations by the Bionano software (Fig.S1). Only SVs with VAF > 5% and a minimum of ten self-molecules were further analysed in this study. Identified candidate SVs were confirmed by arrayCGH, FISH, breakpoint-specific PCR amplification and/or long-read whole-genome sequencing (TELL-Seq, Universal Sequencing Technology, CA, USA). For a comparison of optical mapping and long-read sequencing data, we developed our own tool, which is available at http:// olgen. cz/ en/ resou rces22. Finally, the sample-specific SVs were compared with BED masks generated from the NCBI gene database (h ttps:// www. ncbi. nlm. nih. g ov/ gene) for gene panels associated with cancer (created using the keywords cancer, tumour suppressor and oncogene; panel of 10,812 genes), MM (696 genes), bone metabolism (osteolysis, cellular calcium signalling, bone metabolism; 1810 genes), cell cycle (cell signalling, cell division, apoptosis, cell cycle, DNA repair; 9750 genes) and inflammation (inflammation, cell migration, adhesion molecules, cytokine/ receptor, chemokine/receptor; 4741 genes). NGS mutation assessment. The full coding sequence of the TP53 gene (exons 2–11, plus 5′ and 3′UTR; NM_000546) and the hotspot regions in NRAS (exons 2–4; NM_002524), KRAS (exons 2–4; NM_004985) and BRAF (exons 11 and 15; NM_004333) were analysed by targeted, ultra-deep NGS, as reported previously23,24. Amplicon-based libraries were sequenced as paired ends on MiSeq (2 × 151bp, Illumina, CA, USA), with a minimum target read depth of 5000×. The detection limit was set up to 1%, and the variants within 1–3% were confirmed by replication. Cytogenetic and molecular cytogenetic analysis. After culturing the heparinised BM aspirates in the BM medium (Biological Industries, CN, USA) overnight with colcemid (Gibco, Thermo Fisher Scientific), the samples were processed as reported previously25, and at least ten metaphases were karyotyped. A combination of FISH with immunophenotyping, called fluorescence-immunophenotyping and interphase cytogenetics as a tool for investigation of neoplasms (FICTION), was used to assess the cytogenetic abnormalities using the following probes: LSI RB1 (Abbott Molecular, IL, USA), SPEC IGH, SPEC CKS1B/CDKN2C, TP53/c17, CCND1/IGH, FGFR3/IGH (Zytovision, Bremerhaven, Germany), XL MAF/IGH, CCND3/IGH, MAFB/IGH (MetaSystems, Altlussheim, Germany) and centromeric probes for chromosomes 7, 9, 11 and 15 (Cytocell, Cambridge, United Kingdom), as reported previously25. ArrayCGH was performed using SurePrint G3 CGH/CGH + SNP 4 × 180K microarray (Agilent Technologies, CA, USA)26. Ethics declarations. All patients provided written informed consent about the usage of bone marrow samples for this study, which was performed in accordance with the Helsinki Declaration and approved by the ethics committee of the University Hospital Olomouc and Palacký University Olomouc. Consent for publication. This manuscript has been viewed and approved by all authors for publication. Results Sample analysis by optical mapping. The infiltration of myeloma cells in BM aspirates based on immunophenotyping was highly variable in enrolled patients (3–36%); more than 10% infiltration of plasma cells was found in the BM smears of all enrolled patients. The inter-individual variability in the myeloma cell infiltration may be linked to patchy or site-varied myeloma cell distribution, haemodilution, aspirate pull order, the aggregation of myeloma cells in aspirated BM, myeloma cell immunophenotypes and time-dependent losses of surface markers23, as well as disease heterogeneity itself27. The infiltration of myeloma cells in all samples after enrichment was > 80% (81–96%). Optical mapping was performed in all enriched samples with the following run parameters: average effective coverage, 154× (min–max: 78–324×); collected data per sample, 699GB (427– 1710GB); DNA molecule size (N50), 316kbp (219–446kbp); label density 17.3 labels per 100kbp (14.1–22.6); and map rate, 74.4% (41.5–93.3%). The quality control parameters for each sample are summarised in TableS4. Detection of SVs and CNVs in myeloma samples. The median number of SVs per patient was as follows: deletions, 1700 (min–max: 1583–1755); insertions, 4433 (4268–4550); inversions, 62 (44–75); duplications, 54 (48–79); chromosome translocations, 2 (0–8); and intrachromosomal rearrangements, 6 (0–24) (TableS5). After filtering only for likely somatic variants, the number of deletions per patient (41, 24–62) dominated over insertions (18, 10–30), inversions (3, 1–9) and duplications (3, 0–13) (TableS5, Fig.2A), reaching high interindividual variability. All detected chromosome translocations and intrachromosomal rearrangements were identified as somatic-like in all samples. The EMM genome contained more deletions than the MM (median number of 45 vs 34, P = 0.05), particularly small deletions of 500bp–50kbp (37 vs 24, P = 0.01) (Fig.2). The number of inversions and duplications did not differ between EMM and MM (P > 0.05). The spectrum of SVs and affected genes and chromosomes displayed high inter-individual variability. In addition to the deletion of the CCSER1 gene on chromosome 4 found in ~ 45% of our patients, the SVs in two patients covered NKAIN2, and two others covered the EYS gene, both within a commonly affected region, 6q. 6 Vol:.(1234567890) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ Regarding CNVs, losses in copy numbers (CN = 1) (median per patient 13, min–max 5–38), as well as gains (CN = 3–25) (37, 4–56), were common in all patients. Except for two MM patients, the majority of patients had a mean of five regions of CN > 3 (range 1–16 per patient) in their genomes. The distribution of CNVs across the genome was highly variable in enrolled EMM and MM patients. Optical mapping confirmed 98% of SV and CNV changes detected by diagnostic cytogenetic and arrayCGH assessments (TablesS2, TablesS3) and revealed numerous novel rearrangements in all enrolled patients. Interchromosomal translocations in MM and EMM. In three MM patients, optical mapping detected translocations within IGH/IGK/IGL immunoglobulin loci, t(4;14) and t(11;14) (confirmed by diagnostic FISH), and one t(8;22)(q24;q11) translocation that was detected by mapping only (this region is not routinely assessed by FISH). In EMM patients, no translocations within IGH/IGK/IGL immunoglobulin loci were detected. Additionally, numerous other translocations were detected across all MM patients, frequently affecting chromosomes 2, 3, 6 and 8 (TableS6). All MM patients carried at least two translocations, except for one MM patient with only t(4;14) (TableS6, Fig.3). Complex chromosomal rearrangements involving three chromosomes were detected in four (57%) MM patients but not in any EMM patients (TableS6, Fig.3). The translocations were present at clonal and subclonal levels (VAF 5–43%). The affected genes and putative fusion genes are shown in TableS6. EMM genomes were associated with fewer translocations than MM; two EMM patients had no translocations, one EMM patient had one translocation and the only EMM patient that reached complete response after first-line therapy had four translocations. The translocations were present at clonal and subclonal levels (VAF 5–49%) (Fig.3). Intrachromosomal rearrangements in MM and EMM. Large chromosomal rearrangements encompassing regions longer than 5Mbp on chromosome 1 were detected in all EMM genomes but not in any MM genomes (Fig.4, Table2). The large rearrangements, together with the small SVs (predominantly deletions), affected various regions across chromosome 1, often involving deletions and inversions accompanying the CNV changes. EMM1 had one large intrachromosomal rearrangement of 14.5Mbp, encompassing 230 genes in the 1p36 region, and five deletions; EMM2 had three large intrachromosomal rearrangements of 47.5Mbp, 57.9Mbp and 21.5Mbp, encompassing 1093 genes in the 1p35-p31, 1p32-p12 and 1p22-p13 regions, and an additional six deletions and one insertion. EMM3 had four rearrangements on chromosome 1 of 7.6Mbp, 7.5Mbp, 12.6Mbp and 12.8Mbp, encompassing 794 genes in the 1p35-p34, 1p22-p21 and 1p21-p13 regions, and two deletions. EMM4 had two large rearrangements of 36.1Mbp and 12.0Mbp, encompassing 564 genes in the 1p34-p31 and 1p34-1q23 regions, three deletions and five insertions (Fig.S1). The majority of the affected genes by intrachromosomal rearrangement across chromosome 1 in EMM were associated with cancer (~ 35%), cell cycle (~ 30%) and inflammation (~ 10%); very few affected genes were associated with MM (~ 10%) (TableS7). In contrast, no intrachromosomal rearrangements, fewer deletions (2, 0–4) and more insertions and duplications (4, 0–6) on chromosome 1 were detected in MM compared with EMM. The number of affected genes was also low (2, 0–40). Additionally, intrachromosomal rearrangements were distributed across other chromosomes in both MM and EMM (TableS8, Fig.S2). The typical patterns of intrachromosomal translocation were large deletions with partial inversion, accompanied by copynumber loss. Multiple rearrangements within the same chromosome Figure2. (A) Distribution of SVs (deletions, insertions, inversions and duplications) and (B) deletions subdivided according to their size in EMM (red columns) and MM (grey columns) patients. Each column represents an individual patient and the column height the number of SVs detected. 7 Vol.:(0123456789) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ often occurred in some patients. In four patients, these rearrangements were part of the interchromosomal translocations (highlighted in blue in Fig.4). SVs and CNVs in high‑risk loci associated with MM/EMM. In addition, we focused on SVs in highrisk regionssuch as IGH/IGK/IGL immunoglobulin loci, del(17p13), del(13q14), the 8q24 region, 1q21 gain and del(1p32). Figure3. Distribution of chromosome translocations in EMM (red lines) and MM (black lines) patients. Large circos plots (A) show the sum of translocation in EMM and MM groups; (B) small circos show detected translocations in a particular patient. The VAF of each translocation is denoted by the thickness and colour of the line (key bottom right). SVs were visualised using circos plots28. 8 Vol:.(1234567890) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ Regarding the IGH locus, optical mapping revealed t(4;14) and t(11;14) in three MM, which were confirmed by cytogenetics. In the majority (6/7) of MM samples, but not in any EMM sample, translocations involving immunoglobulin-associated chromosomes 2, 14 and 22 were detected. Additionally, a 0.4 Mbp inversion was detected in one EMM patient, and 1.2 Mbp and 0.8 Mbp duplications on chromosome 14 in two MM patients (TableS9). Also, somatic-like SVs within the IGK and IGL loci were detected: deletions in five patients (three EMM and two MM), insertions in two (two EMM) and duplication in one (MM) were identified (TableS9, Fig.S3). Regarding TP53 disruption, diagnostic analysis by FISH and NGS did not detect any abnormalities in enrolled patients. Nevertheless, optical mapping revealed copynumber loss (CN = 1) in the region overlapping the TP53 gene in two EMM patients (Fig.5). Optical mapping confirmed del(13q14) identified by FISH in one EMM and three MM patients. Additionally, optical mapping detected a 1.1 Mbp deletion affecting the RB1 gene, supported by copy number loss in the 13q14.2 region in one MM patient, which was not detected by FISH (Fig.5). Regarding the 8q24 locus, one EMM patient carried a deletion and one MM a duplication, detected by both mapping and cytogenetics. Optical mapping revealed additional changes within this locus associated with MYC gene amplification in three patients: one MM patient had a 0.6 Mbp insertion and three translocations, t(6;8), t(8;17) and t(8;22); one MM hadan inversion; and one EMM patient had a novel 0.2 Mbp insertion (TableS10). Regarding high-risk regions on chromosome 1 commonly affected in MM, we confirmed 1q21 gain in six patients (two EMM and four MM) and del(1p32) in one EMM patient (TableS11). On chromosome 1, 1.4 times more SVs within/outside the high-risk 1q21/1p32 regions were found in EMM than in MM. In EMM, deletions (50%) and intrachromosomal rearrangements (31%) were the most frequent, not duplications and translocations. Discussion This study characterised genomes of BM myeloma cells in newly diagnosed EMM and MM patients using nextgeneration optical mapping. When comparing the EMM and MM genomes, EMM was associated with large intrachromosomal rearrangements across chromosome 1, fewer interchromosomal translocations and more deletions across the entire genome compared with MM. For high-risk loci, optical mapping revealed copynumber Figure4. Intrachromosomal rearrangements identified in EMM (red lines) and MM (black lines) patients. Blue lines represent complex rearrangements including translocations. 9 Vol.:(0123456789) Scientific Reports | (2021) 11:14671 | https://doi.org/10.1038/s41598-021-93835-z www.nature.com/scientificreports/ ID SV type SV size (kbp) Cytobands Chromosome A Chromosome B VAF (%) Number of affected genesNr RefStart Nr RefEnd EMM1 Intra-chrom 14,502 1p36.33-p36.13 1 1451742 1 16010418 8 230 Deletion 12.3 1p32.3 1 54437326 1 54468426 13 0 Deletion 0.7 1p31.1 1 73986848 1 73989906 49 0 Deletion 0.7 1q21.2 1 149255041 1 149297922 12 0 Deletion 83.9 1q31.1 1 188862967 1 188948998 13 0 Deletion 0.9 1q41 1 219227885 1 219230864 69 0 EMM2 Intra-chrom 46,876 1p35.1-p31.1 1 33649122 1 80528558 13 475 Deletion 1,611 1p32.3 1 52146402 1 53764220 6 22 Deletion 20.0 1p32.2 1 56859220 1 56897293 5 1 Deletion 311 1p32.2 1 57042204 1 57356850 6 1 Insertion 0.6 1p32.2 1 57981404 1 57987615 27 1 Intra-chrom 57,947 1p32.1-p12 1 60494258 1 118466419 9 443 Deletion 14.5 1p31.1 1 70404062 1 70438713 20 1 Deletion 5.5 1p31.1 1 70766057 1 70784216 25 0 Intra-chrom 21,501 1p22.2-p13.3 1 89446367 1 110953619 6 175 Deletion 7.3 1q25.3 1 182529994 1 182549190 61 1 EMM3 Intra-chrom 7,575 1p35.2-p34.3 1 30221701 1 37801246 15 120 Intra-chrom 7,465 1p35.2-p34.3 1 30860870 1 38353947 8 126 Intra-chrom 12,639 1p22.1-p21.1 1 93051297 1 105699124 9 81 Deletion 1.3 1p22.1 1 93329493 1 93335818 10 1 Intra-chrom 12,839 1p21.1-p13.2 1 102272272 1 115119846 21 140 Deletion 5.8 1q42.3 1 235342739 1 235355292 18 1 EMM4 Deletion 53.1 1p36.33 1 1679533 1 1743791 7 3 Insertion 2.5 1p36.12 1 21983384 1 22006562 13 2 Intra-chrom 36,076 1p34.2-p31.1 1 39891936 1 75973164 7 363 Deletion 3,687 1p34.2-p34.1 1 42633541 1 46350766 8 102 Intra-chrom 119,844 1p34.1-1q23.3 1 44054030 1 163946030 8 1175 Insertion 2.5 1p13.2 1 111794239 1 111807945 11 1 Insertion 6.1 1p13.1 1 115530277 1 115543191 14 0 Deletion 0.8 1q31.3 1 195460336 1 195473816 16 0 Insertion 18.6 1q32.2 1 207515921 1 207534396 12 2 Insertion 6.0 1q32.3 1 213171761 1 213205644 12 1 MM1 Insertion 5.9 1p36.33 1 1590522 1 1654114 17 7 Insertion 59.9 1q21.2 1 149365317 1 149390055 51 0 Insertion 10.9 1q21.3 1 152289954 1 152296885 13 0 Deletion 231.9 1q25.1 1 175947709 1 176185749 28 2 Deletion 3176 1q32.3-q41 1 214386812 1 217572960 21 8 Insertion 19.9 1q42.12 1 226337005 1 226338164 32 0 Deletion 315.8 1q43 1 238186340 1 238513554 23 1 Deletion 31.4 1q43 1 239651938 1 239694630 23 1 MM2 Insertion 5.4 1p36.12 1 20372589 1 20396493 12 1 Deletion 14.6 1p31.1 1 83171695 1 83186312 19 0 Duplication 95.5 1q21.2 1 148669395 1 148764931 46 1 Insertion 2.4 1q23.2 1 161184787 1 161193876 13 1 Deletion 4.4 1q25.2 1 179360227 1 179368480 28 1 MM3 t(1;19) 1p34.3-19p13.11 1 38291095 19 16838518 15 t(1;19) 1p34.3-19p13.12 1 39900616 19 15299192 18 Deletion 0.6 1q32.1 1 200212204 1 200225458 24 0 MM4 Insertion 14.6 1p36.31 1 5999446 1 6006996 20 0 Insertion 1.8 1p12 1 119153160 1 119157652 27 0 Duplication 95.5 1q21.2 1 148669395 1 148764931 49 1 Insertion 2.4 1q23.3 1 161184787 1 161193876 28 1 Continued