Abstract: Introduction: Treatment strategies incorporating proteasome inhibitors, immunomodulators, and autologous transplantation induce durable remissions in most newly diagnosed multiple myeloma (NDMM) patients. However, for 20% of patients even the most intensive therapies have not resulted in satisfactory outcomes. Currently available risk scores do not fully appreciate the complex biology of MM and have limited sensitivity and/or specificity for identification of high risk (HR) disease. We therefore aimed to characterize the mutational landscape of transplant-eligible NDMM patients who relapsed within 2 years after treatment initiation, thereby defining true clinical HRMM. To elucidate the clonal structure and evolution in these patients, we performed deep whole genome sequencing (WGS, ~80x) and RNAseq of samples collected at baseline and first relapse. Methods: We included 34 transplanted NDMM patients who experienced early relapse during maintenance within 2 years after treatment initiation. Tumor samples were collected from 20 and 31 patients at baseline and first relapse, respectively. Paired samples taken at both time points were available from 17 patients. WGS and RNAseq data were pre-processed using in-house pipelines. Single nucleotide variants (SNVs), indels, translocations, and copy number variants (CNVs) were called using Platypus, SOPHIA and ACESeq. Subclones were identified using SciClone. RNAseq data was aligned using STAR. Fusion genes were called by Arriba. Differential gene expression was assessed using DESeq2. Results: At baseline, only 12/20 patients would have been classified as HR according to conventional markers, including presence of t(4;14), t(14;16), amp(1q), clonal del(17p) or ISS3. In 5 patients del(17p) was solely observed in a minor sublone, which was selected during treatment and became dominant at relapse in 3 of them. Selection of amp(1q)-positive subclones was seen in 2 patients, illustrating that subclonal amp(1q) or del(17p) are frequent events in HR patients, and - in contrast to recent results - could contribute to early relapse. Translocations involving MYC have also been reported to be of prognostic impact. At baseline 9 of 20 patients were positive for this event, with BMP6 and the lambda locus being the translocation partner in 2 patients each. At relapse we found an additional MYC-lambda, and two MYC-kappa translocations, supporting recent observations that MYC-light chain translocations are associated with aggressive disease. We identified a median of 40 (range: 17-233) nonsilent somatic SNVs per patient at baseline and 61 (range: 14-322) at relapse. Yet, comparing paired samples there was no significant increase in SNVs. In our HRMM set, 21 of 64 recently identified driver genes were mutated at baseline with KRAS (n = 6), TP53 (n = 6), NRAS (n = 2), and DIS3 (n = 2) being the most frequently affected genes. 6 of them - ACTG1, DIS3, FAM46C, NFKB2, RB1, and TRAF3 - were involved in fusion genes. At relapse the number of mutated driver genes increased to 29, and 10 of 31 patients presented with a clonal TP53 mutation. All patients with a TP53 mutation also showed deletion of the second allele or LOH. Including other tumor suppressor genes, such as RB1, CDKN2C, or TRAF3, 12/20 NDMM and 20/31 relapsed patients had at least one bi-allelic aberration, doubling the number of HR patients with such events compared to considering TP53 alone. Longitudinally, we observed all patterns of clonal evolution that were recently described for unselected patients. Stable evolution was primarily seen in patients achieving partial remission, supporting a model where some tumor cells survive in a protective microenvironment (ME). In deep responders, however, branching evolution was the dominant patterns. This observation rather supports strong cell-intrinsic mechanisms and rapid selection of aggressive minor subclones in clinically defined HRMM. Conclusions: Understanding the mutational landscape in HRMM and drivers of early relapse is crucial in order to improve treatment options. Our study highlights the importance of bi-allelic events in HR and suggests that focusing on TP53 is not sufficient, if all HR cases are to be identified. Of note, 3 patients in the entire cohort would have been classified as low risk by conventional risk scores and even at relapse did not carry any bi-allelic event, indicating the existence of unknown somatic HR aberrations or a protective ME. Disclosures Müller-Tidow: MSD: Membership on an entity's Board of Directors or advisory committees. Goldschmidt:MSD: Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Molecular Partners: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; John-Hopkins University: Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding.

Abstract: Introduction: Treatments incorporating autologous transplantation (ASCT), proteasome inhibitors (PIs), and immunomodulatory drugs (IMIDs) induce deep and durable remissions in most multiple myeloma (MM) patients, resulting in prolonged survival. Yet, patients who suffer from early relapse within 2 years of treatment initiation or become refractory to PIs and IMIDs still have a dismal outcome. The mutational landscape in early relapsed MM (ERMM) and relapsed/refractory MM (RRMM) has been comprehensively described. Several aberrations are associated with these two types of high-risk disease but little is known about the biological difference between them. To this end, we have comparatively and sequentially analyzed whole genome and RNA sequencing data from ERMM and RRMM patients. Methods: We included 32 patients who had relapsed within 2 years of first-line therapy (ERMM group, 30 after ASCT). Samples were collected at first relapse. Paired baseline samples were available from 17 patients. For the RRMM group, we included 43 patients with a median of 5 prior lines of therapy (range 2 - 13; 88% with ASCT), who had relapsed after PIs and IMiDs. For 22 of them consecutive tumor samples were available. Sequencing data were pre-processed using in-house pipelines. Mutations, indels, translocations, and copy number variants were called using Platypus, SOPHIA and ACESeq. Mutational signatures were identified with MMSig and subclonal structures with SciClone. Differential gene expression was assessed using DESeq, gene set enrichment analysis was performed with hypeR, and gene fusions were detected with Arriba. Results: Nonsynonymous mutations occurred more frequently in RRMM (median=180) compared to ERMM at first relapse (median=62, p & lt;0.001). While TP53 mutations were more often seen in ERMM (31% of cases vs. 21% in RRMM), NRAS mutations were enriched in RRMM (37% vs. 22%). Bi-allelic inactivation of TP53, RB1, or CDKN2C was more frequent in ERMM (44% vs. 30% in RRMM). In 11/14 ERMM patients these events were already present at baseline. Genes associated with sensitivity to PARP inhibition, homologous recombination deficiency, HECT, Pi3K and NOTCH signaling were more often mutated in RRMM (p & lt;0.05). While mutations associated with PI-resistance were equally common in both groups (~20%), IMID-resistance mutations were more common in RRMM (23% vs 9%). We observed a median number of 60 and 48 fusion genes in ERMM and RRMM, respectively. Fusions involving B2M, TXNDC5, PVT1 and MYC were more frequent in ERMM, while SPINK family and MAGEC1 fusions were more common in RRMM. Analysis of mutational signatures revealed a major impact of signature MM1 (associated with melphalan-exposure), in 66% of RRMM patients. In contrast, only 22% of ERMM samples showed this signature (p & lt;0.001). Signature 3 (defective homologous recombination-based DNA damage repair) was rarely detectable in ERMM (4/32) but one of the major signatures in RRMM (16/43). Analyzing expression profiles, we found upregulated genes in ERMM that were enriched for epithelial-mesenchymal transition, hypoxia, glycolysis and KRAS/IL6-JAK-STAT3 signaling. For RRMM we found no significantly enriched gene set. Yet, 50 upregulated genes were ribosomal protein pseudogenes. Longitudinally, we mainly observed branching evolution in ERMM and RRMM. Major changes in the clonal substructure with new dominant clones were seen in 65% and 55% of ERMM and RRMM, respectively. No changes ("stable" evolution) were rare in both ERMM (3/17), and RRMM (4/22). Conclusions: According to our results ERMM and RRMM are biologically distinct entities of MM. While ERMM is characterized by inactivation of tumor suppressors and upregulation of gene sets associated with hypoxia and glycolysis, RRMM shows mutations in multiple gene networks, upregulation of ribosomal protein pseudogenes with unknown function and a signature linked to defective DNA repair, suggesting multifactorial mechanisms that lead from first relapse to end-stage relapsed refractory disease. Comparing paired samples, we did not observe major difference in evolution patterns between ERMM and RRMM. Yet, the low prevalence of the melphalan MM1 signature in ERMM suggests selection of pre-existing clones in this entity. In contrast, single tumor cells exposed to melphalan are often the precursors of clones dominating at the RRMM stage, indicating that first-line ASCT has a long-term effect on MM evolution. Disclosures John: Proteona: Research Funding. Mueller-Tidow:Janssen-Cilag Gmbh: Membership on an entity's Board of Directors or advisory committees; Deutsche Forschungsgemeinschaft: Research Funding; Deutsche Krebshilfe: Research Funding; Daiichi Sankyo: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; BiolineRx: Research Funding; Bayer AG: Research Funding; Jose-Carreras-Siftung: Research Funding; Wilhelm-Sander-Stiftung: Research Funding; BMBF: Research Funding. Goldschmidt:Johns Hopkins University: Other: Grants and/or provision of Investigational Medicinal Product; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Incyte: Research Funding; Molecular Partners: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Novartis: Honoraria, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma GmbH: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; University Hospital Heidelberg, Internal Medicine V and National Center for Tumor Diseases (NCT), Heidelberg, Germany: Current Employment; GlaxoSmithKline (GSK): Honoraria; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Chugai: Honoraria, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Dietmar-Hopp-Foundation: Other: Grants and/or provision of Investigational Medicinal Product:; Merck Sharp and Dohme (MSD): Research Funding. Raab:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Heidelberg Pharma: Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees.

Abstract: In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.

Abstract: Tumor heterogeneity plays a significant role in the development of therapy resistance in multiple myeloma (MM). Focal lesions (FLs), which are nodular accumulations of MM cells, have been shown to be hotspots of genetic spatial tumor heterogeneity, which is characterized by unique tumor sub-clones at different sites in the bone marrow (BM). However, little is known about the mechanisms leading to mutations in FLs, the architecture of the tumor microenvironment (ME) at these sites, and the link between FL sub-clones and relapse. We applied whole genome sequencing (WGS) to CD138 + MM cells from paired FL and iliac crest random BM aspirates (RBMA) of 15 newly diagnosed MM (NDMM) patients. For 7 of these patients, single cell (sc) analyses were performed, including sc gene expression (scRNA) and T-cell receptor (TCR)-sequencing and sc assay for transposase-accessible chromatin (ATAC)-sequencing for paired BM CD138 + MM and CD138 - ME, as well as peripheral blood mononuclear cells (PBMC). WGS data was analyzed using inhouse pipelines. Mutations, copy-number-variations and mutational signatures were called using mpileup, ACESeq and mmsig. Neoantigen epitopes were predicted using NeoPredPipe. Sc data was generated using the 10X Genomics platform. Pre-processing and analysis of the sc data was performed with CellRanger and the R-packages Seurat, ArchR and inferCNV. In 13/15 patients we found significant differences in chromosomal and mutational profiles between FLs and paired RBMAs, with major unshared mutations (mutation seen in & gt; 60% cells) being enriched at the FL site (mean 310 vs. 123, p & lt;0.05). Mutations in driver genes, such as KRAS, CYLD, CDKN2C and TP53, were site-unique or strongly enriched in FLs in 6/15 patients. To identify the mechanisms underlying heterogeneous mutations, we analyzed mutational signatures and found COSMIC signature SBS18 in these mutations, suggesting a role of reactive oxygen species. Combining WGS and sc sequencing, we observed between 3 and 6 sub-clones per patient. Sub-clones, which dominated in FLs, showed increased regulatory accessibility and expression of genes associated with disease aggressiveness and drug resistance such as CXCR4 and members of the NFKB- and interferon pathways, implying that FLs could play a significant role in the development of treatment resistance. Indeed, comparing sub-clones at baseline and at relapse after high-dose melphalan and autologous stem cell transplantation in one patient, we observed expansions of tumor cells at relapse, which were closely related to the main FL sub-clone at baseline. On average, 23 (range 0-83) site-unique baseline mutations were predicted to be neoantigens. Thus, we hypothesized that spatial tumor heterogeneity could be associated with heterogeneity in the tumor ME. We did not observe expansion of site-unique T cell clones, but some of the clones were enriched up to 10-fold at one of the two sites. These clones were typically seen in the PB at low frequency. Expanded T-cells clones were almost exclusively found in the CD8 +-compartment, with 65% and 27% of expanded T-cell clones being CD45RO +/CD57 +-memory- and CD69 +-effector-T-cells, respectively. Besides differences in the T-cell clonality, we observed changes in proportions of other cell types, including a depletion of CD14+- and CD16+-macrophages in FLs (p & lt;0.05). Furthermore, we observed gene expression differences between FL and RBMA macrophages, especially for genes involved in TNFα, IL-6 and JAK/STAT3 signaling. While CCL2, CD44, CXCL2/3, KLF2/4 and CCR1 were significantly higher expressed in FLs compared to RBMAs, BTG2, DUSP1 and HIF1A were down-regulated. In conclusion, our results strengthen the concept of MM as a spatially heterogeneous disease, suggest that reactive oxygen species result in site-specific mutagenesis, and support the hypothesis that FLs are the origin of aggressive disease. We demonstrate spatial heterogeneity at single-cell level in the BM immune ME for the first time, which implies that understanding the complex biology of FLs could be important in the context of novel immune therapies such as bispecific antibodies and CAR-T-cells. Disclosures John: Janssen: Consultancy. Müller-Tidow: Janssen Cilag: Consultancy, Research Funding; Bioline: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Goldschmidt: Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Novartis: Honoraria, Research Funding; Mundipharma: Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Johns Hopkins University: Other: Grant; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Incyte: Research Funding; GSK: Honoraria; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Adaptive Biotechnology: Consultancy; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding. Raab: Janssen: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees. Weinhold: Sanofi: Honoraria.