Multiple Myeloma Patient Samples Research Articles

Abstract 4670: KS18, an Mcl-1 inhibitor, triggers cell death and enhances the therapeutic efficacy of venetoclax in bortezomib-resistant multiple myeloma cells

Abstract A critical clinical challenge in the management of multiple myeloma (MM) is the development of both innate and acquired resistance to the treatment with bortezomib. Our prior research showed that the overexpression of the anti-apoptotic Bcl-2 family protein Mcl-1 can result in resistance to the chemotherapy drugs bortezomib and venetoclax. In order to overcome the issues posed by resistance, this study investigates the possibility of a small chemical called KS18, a novel Mcl-1 inhibitor. KS18 outperforms other Mcl-1 inhibitors such as S63845, VU661013, and AZD5991, according to the findings of our research, which shows that it is extraordinarily effective against MM cells that have become resistant to bortezomib. We establish the selectivity of KS18 through tests employing Mcl-1 knock-down (KD), and we find that it is both effective and efficient. In addition, we used immunoprecipitation (IP) and protein-protein interaction analysis (PPIs) to investigate the dynamic connections that exist between Mcl-1 and pro-apoptotic proteins. The KS18 therapy exhibits an outstanding ability to cause complete apoptosis, as seen by the remarkable 88.8% apoptosis rate recorded in MM patient samples. Not only does KS18 restore apoptosis in bortezomib-resistant MM cells, but it also synergizes with venetoclax to enhance the apoptotic response. This is an important finding. It has been demonstrated through both in vitro and in vivo research that KS18 can re-sensitize MM cells to the effects of bortezomib, which represents a potential step forward in the treatment of the disease. In bortezomib-resistant MM cells, treatment with KS18 led to a remarkable 92% reduction in colony formation compared to untreated controls. In vivo experiments that were performed on mice models that were resistant to bortezomib provide additional evidence that KS18 is effective. The extraordinary reduction in tumor weight of 55% that occurred as a direct result of treatment with KS18 at a dose of 1 mg/kg for a period of 15 days exemplifies the powerful anti-resistance characteristics of this compound. These intriguing findings highlight the potential value of KS18 as an adjunct to therapies aimed at overcoming bortezomib resistance in MM and other associated cancers. Bortezomib-resistant malignancies provide a challenge for patients, but additional research into the clinical value of KS18 holds the potential to improve treatment outcomes and broaden the range of therapeutic alternatives available to these patients. Citation Format: Omar S. Al Odat, Osama Aloudat, Emily Nelson, Tulin Budak-Alpogan, Subash Jonnalagadda, Yong Chen, Manoj Pandey. KS18, an Mcl-1 inhibitor, triggers cell death and enhances the therapeutic efficacy of venetoclax in bortezomib-resistant multiple myeloma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4670.

Abstract 4587: Development of highly selective, potent, orally available PIM1 inhibitor BLX0631 shows a therapeutics potential in multiple myeloma models

Abstract Background: The Proto-oncogenic PIMs family are nuclear and cytoplasmic Ser/Thr kinases (PIM1, PIM2, and PIM3) that are constitutively active and play a vital role in proliferation and survival in Multiple Myeloma (MM). Activated PIM1 kinase can induce progression of the cell cycle, inhibition of apoptosis, and modulation of other signal transduction pathways. Methods: BLX-0631 and a few analogs evaluated against a panel of MM cell lines (EJM, IM-9, L-363, LP-1, MM-1R, MM.1S, MOLP-2, NCI-H929, OPM-2, RPMI8226 and U-266) and primary MM patient samples by CellTiter-Glo® (CTG) assays. Cellular apoptosis, Cell cycle analysis, Flow Cytometry, and bone marrow microenvironment experiments on the most sensitive cells were performed. PIM1 and downstream targets by western blot, cell migration, and invasion on our lead PIM1 inhibitor BLX-0631 along with, kinome selectivity, ADME-Tox, PK, and in vivo MM.1S efficacy experiments were conducted. Results: The application of our empirical MolecuLernTM fragment library, PIM1 crystal structure, scaffold hopping, and the enumeration features of MolecuLernTM in combination with 3, 6, and 7-group analysis on pyridazine, lead to a synthesizable potential new lead series, representing Med Chem tractability and developable characteristics. Further, the consensus scoring, binding energies, and MolecuLern tractability filters were applied and led to the discovery of the BLX-0631 series that inhibits the PIM1 kinase. The active compounds, with their binding modes and lead optimization strategies, lead to the synthesis and testing of over 60 novel entities as PIM1 kinase inhibitors. Thus, based on our previous chemotype series and scaffold hopping method, the impact of changing the 3, 6, and 7 positions, while retaining the pyridazine core led to the discovery of BLX-0631 and its series of compounds exhibiting <5 nM potency. BLX-0631 in CTG assay demonstrated 100% cell growth inhibition across all MM cell lines tested. The lead compound BLX-0631 is a very potent inhibitor with an IC50 of 5.0/17/5.0 nM when tested against PIM1, PIM2, and PIM3 kinases respectively, and selective against a panel of 468 kinase panels. Dosing through IV and PO delivery routes, formulations, salt forms of BLX-0631 in mice, PK properties along with ADME-Tox, P450, and hERG results will be presented. In vivo MM.1S mouse xenograft models of BLX-0631 at 15, 30 and 45 mg/Kg, p.o, QD demonstrated TGI of 16.28%, 31.81% & 35.16% dose-dependently. Conclusions: The present study demonstrates that PIM1 plays a vital role in the proliferation and survival of Multiple Myeloma. BLX-0631 induces full inhibition of all MM cell lines, suppresses cancer cell proliferation in vitro, and exhibits promising efficacy in MM tumor models. BLX-0631, a nominated IND candidate can serve as a novel targeted agent for treating Multiple Myeloma patients. Citation Format: Zhaoang li, Chenyu Lin, David J. Bearss, Hariprasad Vankayalapati. Development of highly selective, potent, orally available PIM1 inhibitor BLX0631 shows a therapeutics potential in multiple myeloma models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4587.

Steroid-free combination of 5-azacytidine and venetoclax for the treatment of multiple myeloma.

Multiple Myeloma (MM) is an incurable plasma cell malignancy, that despite an unprecedented increase in overall survival, lacks truly risk-adapted or targeted treatments. A proportion of patients with MM depend on BCL-2 for survival and recently the BCL-2 antagonist venetoclax has shown clinical efficacy and safety in t(11;14) and BCL-2 overexpressing MM. However, only a small proportion of MM patients rely on BCL-2 (~20%), there is a need to broaden the patient population outside of t(11;14) that can be treated with venetoclax. Therefore, we took an unbiased screening approach and screened epigenetic modifiers to enhance venetoclax sensitivity in two non-BCL-2 dependent MM cell lines. The demethylase inhibitor 5-azacytidine was one of the lead hits from the screen, and the enhanced cell killing of the combination was confirmed in additional MM cell lines. Using dynamic BH3 profiling and immunoprecipitations we identified the potential mechanism of synergy is due to increased NOXA expression, through the integrated stress response. Knockdown of PMAIP1 or PKR partially rescues cell death of the venetoclax and 5-azacytidine combination treatment. The addition of a steroid to the combination treatment did not enhance the cell death and interestingly we found enhanced death of the immune cells with steroid addition, suggesting that a steroid-sparing regimen may be more beneficial in MM. Lastly, we show for the first time in primary MM patient samples, that 5-azacytidine enhances the response to venetoclax ex-vivo, across diverse anti-apoptotic dependencies (BCL-2 or MCL-1) and diverse cytogenetic backgrounds. Overall, our data identifies 5-azacytidine and venetoclax as an effective treatment combination and this could be a tolerable steroid-sparing regimen, particularly for elderly MM patients.

Deciphering the Exact Sequence of Endogenous Soluble B Cell Maturation Antigen and Unbiased Quantitation in Multiple Myeloma Patient Samples by LC-MS.

B-cell maturation antigen is a pivotal therapeutic target for multiple myeloma (MM). Membrane-bound BCMA can be cleaved by γ-secretase and shed as soluble BCMA (sBCMA). sBCMA can act as a neutralizing sink to compete with drug, as well as serve as a diagnostic/prognostic biomarker for MM. Antibody-capture based methods, such as enzyme-linked immunosorbent assay (ELISA) and immunoaffinity-liquid chromatography-multiple reaction monitoring (IA-LC-MRM), have been reported and well adopted to measure sBCMA in clinical samples. However, both methods are biased by capturing antibodies. We have used various LC-MS workflows to characterize and quantify endogenous sBCMA in MM patient samples, including bottom-up peptide mapping, intact analysis, IA-based, and reagent-free (RF)-LC-MRM quantitation. We have confirmed that sBCMA contains a variable N-terminus and a C-terminus that extends to the transmembrane domain, ending at amino acid 61. Leveraging an in-house synthesized G-1-61 sBCMA recombinant standard, we developed a RF-LC-MRM method for unbiased sBCMA quantitation in MM patient samples. By comparing the results from RF-LC-MRM with ELISA and IA-LC-MRM, we demonstrated that RF-LC-MRM measures a more complete pool of endogenous sBCMA compared to the antibody-based methods. This work fills the knowledge gap of the exact sequence of endogenous sBCMA for the first time, which differs from the current commercially available standard. Additionally, this work highlights the necessity of identifying the actual sequence of an endogenous soluble target such as sBCMA, both for bioanalytical purposes and to underpin pharmacodynamic measurements.

Abstract A125: Clinical evaluation of a functional combinatorial precision medicine platform to predict combination immunotherapy responses in hematological malignancies

Abstract Purpose: Proliferation of immune checkpoint inhibitors and lineage-specific antigen-based therapy have made identifying the most appropriate immunotherapy for specific patients or subgroups of patients increasingly difficult. Furthermore, combination of these therapeutic antibodies with other targeted agents or chemotherapy is often required to achieve durable response. To address the large search space of possible combinations of these immunotherapies with available targeted and cytotoxic drug partners, we applied a hybrid experimental-analytical platform, Flow Cytometry Immunophenotyping–Quadratic Phenotypic Optimization Platform (FCI-QPOP), on primary patient samples from acute myeloid leukemia (AML) and multiple myeloma (MM) cases to predict patient and subtype-specific combination immunotherapy responses. Successful development of this functional combinatorial precision medicine platform could help guide combination therapy treatment while also providing a tool for improving combination therapy design for emerging immunotherapies. Experimental Detail: Single drug dosage response analysis of a set of immunotherapies, targeted small molecules and cytotoxic agents were performed from initial patient samples and used to inform subsequent dosing levels for 8-drug, 3-level FCI-QPOP. In FCI-QPOP, primary AML or MM patient samples composed of both cancer cells and normal cells were treated with an array of test combinations and analyzed by flow cytometry to provide a quantitative phenotypic output for each test combination. This OACD dataset was then analyzed by QPOP to rank all possible drug combinations towards a predicted treatment outcome. Concordance analysis was then performed comparing patient sample results with parallel treatment initiated at time of sample collection. Results: Drug-dose response analysis by flow cytometry could accurately identify samples-specific response, including IC50 determination, to both therapeutic antibodies and small molecule drugs. Following this, 8-drug, 3-level FCI-QPOP was successfully performed on 14 of 17 primary patient samples. Concordance analysis could be performed on 9 cases, with 5 cases still pending clinical follow-up. Concordance to both antibody therapies as well as small molecule treatments were analyzed following FCI-QPOP. FCI-QPOP had a sensitivity of 80% and specificity of 75% and a total predictive value (TPV) of 77.78%. Additionally, FCI-QPOP provided potentially effective combination rankings for a diverse range of therapeutic antibodies, including gemtuzumab-based combination therapies. Conclusion: The results show the potential for FCI-QPOP to predict clinical response to immunotherapy-based treatments. Furthermore, FCI-QPOP can improve drug development pipelines through patient samples-based design of effective immunotherapy-based combinations that may benefit larger populations of patients or specific subgroups of patients. Citation Format: Noor Rashidha Bte Meera Sahib, Masturah Rashid, Sanjay de Mel, Wei Ying Jen, Melissa Ooi, Edward K Chow. Clinical evaluation of a functional combinatorial precision medicine platform to predict combination immunotherapy responses in hematological malignancies [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A125.

Multi-Level Control of Myeloma Cell Proliferation and Genomic Instability By the PDZ Binding Kinase (PBK)

Genomic instability and cell proliferation play important roles in the development and progression of cancer. We identified a six-gene kinase signature that correlated with overall genomic instability in multiple human cancers including multiple myeloma (MM). PDZ Binding Kinase (PBK) was one of the top kinases in this signature. Inhibiting PBK downregulated E2F and FOXM1-related pathways and impacted several members of the DREAM complex, which represses cell cycle genes during quiescence. We further evaluated whether PBK affects entry into mitosis by controlling FOXM1 phosphorylation and affects genome stability. Using co-immunoprecipitation and chromatin immunoprecipitation assays, we observed that PBK binds to and phosphorylates FOXM1, leading to upregulation of FOXM1 target genes. Overexpression of PBK increased the association of LIN54 (a major component of the MuvB complex) with phosphorylated-FOXM1 and inhibited LIN54 interaction with E2F4 in the DREAM complex. Consistently, PBK knockdown or inhibitor increased the LIN54-E2F4 interaction and inhibited the LIN54 and phosphorylated-FOXM1 interaction. The inhibitor also impaired tumor growth in vitro and significantly increased the efficacy of a chemotherapeutic agent ( P = 0.0011) in a subcutaneous mouse model of MM. Overall, these data indicate that PBK phosphorylates FOXM1, then FOXM1 interacts with MuvB which is associated with the start of mitosis, dissociating it from E2F4 in the DREAM complex, thus allowing entry into mitosis and subsequent tumor growth. Given that phosphorylation of FOXM1 also activates the expression of major DNA repair genes (including RAD51, EXO1), we investigated whether PBK affects genome stability. Surprisingly, we observed that PBK also directly phosphorylates DNA repair/HR genes, such as flap structure-specific nuclease 1 (FEN1), and that PBK inhibition reduces spontaneous and chemotherapy (melphalan)-induced genomic instability ( P < 0.05). A significant upregulation of PBK has also been observed in MM patient samples at relapse (after melphalan treatment) relative to paired samples collected at diagnosis (GSE19554). To further investigate the consequences of elevated PBK in vivo, we transformed the normalized PBK expression into a Z-score and used this to divide patients (in MMRF-COMPASS) into three groups based on PBK expression (i.e., high, medium and low PBK expression groups). Patients with high PBK expression had poor overall survival as compared to those with medium and low PBK expression ( P=1.127e−13). DNA replication, mismatch repair, homologous recombination, cell cycle and Fanconi anemia were the top upregulated pathways in patients with high PBK expression. Known drivers of DNA replication, including those involved in the initiation of once-per-cell cycle replication and several DNA repair and HR genes, which are part of different genomic instability signatures (such as RAD51, RAD51C, RAD54B, RAD54L, EXO1, BRCA1, FEN1, ATAD2, CENPA, MAD2L1, TTK), were significantly overexpressed in patients with high PBK expression. Interestingly, FOXM1, which can impact both replication and genome stability was also overexpressed (Log2 Fold change of 1.8; P adj = 1.27E-86). In summary, we demonstrate that PBK drives DNA replication and genomic instability in MM cells by acting at multiple levels. Therefore, PBK inhibitors investigated here have the potential to impair growth and increase the efficacy of chemotherapeutic agents while reducing spontaneous as well as chemotherapeutic agent-induced genomic instability in MM.

Drug Resistance Can be Overcome in Multiple Myeloma and Acute Myeloid Leukemia By Targeting Mcl-1 with the Small Chemical KS18

Drug resistance and patient recurrence are still key clinical difficulties in multiple myeloma (MM) treatment, despite the tremendous improvements provided by bortezomib therapy. In many cancers, Mcl-1, a member of the Bcl-2 protein family, helps keep cells alive by preventing their natural death process, apoptosis. The anti-cancer therapeutic promise of Mcl-1 inhibitors is highlighted by the fact that Mcl-1 overexpression increases carcinogenesis and medication resistance. Here, we provide KS18, a powerful pyoluteorin derivative with excellent effectiveness towards Mcl-1-dependent cancer cells, to address this unmet therapeutic need. Based on our results, we conclude that KS18 causes apoptosis in cancer cells through activating the mitochondrial outer membrane permeabilization (MOMP) pathway, with the participation of Bak and Bax, in particular in MM and acute myeloid leukemia (AML). With IC 50 values below 1.5µM, KS18 demonstrated efficacy against bortezomib-resistant MM cells, outperforming other Mcl-1 inhibitors in clinical trials such as S63845, VU661013, and AZD5991. Total apoptosis in MM patient samples treated with KS18 was an impressive 88.8 percent. After four weeks of treatment with a single tolerable dose each week, a model of bortezomib-resistant MM showed considerable tumor shrinkage, demonstrating the powerful anti-tumor efficacy of KS18. According to these results, KS18 may be able to overcome resistance by concentrating on Mcl-1. These encouraging findings have prompted the development of many models of drug-resistant MM and AML for in vivo evaluation of this potential chemical.

Ex-Vivo Testing Platform to Predict Clinical Response and Resistance to Proteosome Inhibitors, IMiDs and Daratumumab in Multiple Myeloma

Treatment of Multiple Myeloma (MM) relies on Standard of Care (SoC) schemes that include immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) in combination with dexamethasone (Dexa). More recently, monoclonal antibodies such as Daratumumab (Dara) have become complementary therapeutic strategies to treat newly diagnosed and relapsed MM patients. Despite the multiple therapeutic schemes available, MM remains an incurable disease in which patients transit intermittent cycles of relapse and remission that ultimately lead to multi-drug resistance. It has therefore become clear that novel tools for personalized therapy selection are necessary to improve outcomes and reduce trial and error, particularly when selecting later lines of treatment. At OncoPrecision, we have developed a personalized ex-vivo platform that mimics the tumor microenvironment and promotes the survival of Patient-Derived Cells (PDCs), with the goal to predict the performance of the complete array of FDA-approved drugs, as well as experimental treatments, within 7 days. This technology, which we have named Patient Micro Avatars (PMAs), consists of the co-culture of PDCs with engineered neoplastic (System Control) and stromal (Tox Control) heterologous cells in combination with a multi-tagging approach coupled to high-throughput flow cytometry (Figure: Upper Panel). Our PMAs not only enable us to rank the activity of all approved treatments, but also unveil potential unspecific toxicities of novel treatments on non-tumoral cells, thus unlocking unique insights for early drug development programs. In this work, we introduce our PMA technology for MM by presenting differential response between patients in a Clinical Study performed in collaboration with two healthcare centers which, through approved IRBs, have provided MM patient samples from bone marrow aspiration. We present ex-vivo profiling results with a comprehensive MM drug matrix which includes SoC treatments used in several lines of therapy. We illustrate the potential of PMAs to identify differential activity from individual agents and synergistic drugs combinations in 13 patients (Figure: Lower Panel). By anticipating vulnerability/resistance to SoC treatments, our platform has the potential to become a first-in-class phenotypic biomarker to serve as a decision-support tool for Physicians to select optimal therapeutic regimes, as well as to elucidate valuable pre-clinical patient-derived insights for the development of innovative therapies for MM.

Selinexor Disrupts Epigenetic Programing and Modulates Immunogenicity in Multiple Myeloma

Introduction: Multiple myeloma (MM), remains an incurable, but treatable, malignancy that has benefitted from the integration of novel immunologic agents in clinical use, such as monoclonal antibody, bispecific T cell engager (TCE) and chimeric antigen receptor T (CAR-T) cell and antibody-drug conjugate based therapies. While these agents have shown great promise in treating relapsed/refractory MM patients, there is heterogeneity in response to therapy due to differences in patients' immune tumor microenvironments (iTME) and immunogenicity of the tumor cells. Previously (Sudalagunta et. al., ASH 2021), we used functional genomic screening of 53 MM samples to characterize the transcriptomic profile associated with sensitivity to the selective nuclear export inhibitor, selinexor (SELI), which was shown to be inversely correlated with the transcriptomic profile associated with sensitivity to an anti-CD38 monoclonal antibody in 106 MM samples. In this study, we investigate the cellular mechanisms of SELI resistance leading to an immunogenic cell state. Methods: Primary cells from an additional set of MM patients (n=65) were used for paired bulk RNAseq and an organotypic ex vivo drug sensitivity assay. Cellular viability was assessed using digital analysis of brightfield longitudinal images, and drug sensitivity was assessed as area under the dose-time-response curve (AUC) for each sample. We conducted gene set enrichment analysis (GSEA) on paired RNAseq data and ex vivo AUC of SELI. Individual genes and their respective correlations with ex vivo AUC of SELI were ranked from highest to lowest. We used RNAseq to examine the role of acute exposure to SELI on CD138-selected cells from paired pre/post treatment bone marrow specimens of five MM patients enrolled in the NCT02186834 clinical trial, taken prior to treatment with SELI and dexamethasone (DEX) and one/two weeks post-induction. Paired t-tests were carried out to quantify the changes. Results: In our previous analysis of 844 MM samples, a subset of the genes whose expression is positively correlated with SELI AUC are controlled by H3K27me3, which is catalyzed by nuclear accumulation of EZH2. Tripathi et. al. (AACR Annual Meeting 2022 & 2023) have demonstrated that XPO1 and EZH2 form a complex, and inhibition of XPO1 activity blocks export of EZH2. GSEA of a new cohort of 65 MM patient samples demonstrated increased ex vivo SELI sensitivity (lower AUC, hence negative correlation) in samples with higher expression of known epigenetic regulators of the polycomb repressive complex 2 (PRC2), such as EZH2, SUZ12, and EED; as shown in Figure a, which led to lowering of expression of genes bound by these proteins due to gene silencing via H3K27me3, shown in red in Figure a, according to GSEA of ChIPseq databases. Furthermore, gene expression profiles of paired pre/post SELI/DEX treatment samples showed reduced expression of genes associated with H3K27me3 histone modification (paired t-test p=2.06e-83, 1.1061e-81, 2.56e-80, 5.15e-12, 6.22e-4) in all five patients. These observations suggest that XPO1 inhibition leads to nuclear accumulation of epigenetic modulators like EZH2, SUZ12, and EED, which catalyze H3K27me3 activity leading to silencing of H3K27me3-regulated genes. GSEA of paired ex vivo AUC and RNAseq data for an EZH2 inhibitor (EPZ-6438) resulted in negative correlation between expression of genes in PRC2 and ex vivo sensitivity, similar to SELI. Interestingly, we observed that this epigenetic mechanism of resistance to SELI is inversely associated with key immunological targets in MM such as CD74, SLAMF7, CD38, CD46, TNFRSF13B, and LY9 as shown in Figure a. In Figure b, we present a graphical visualization of intracellular changes due to exposure to SELI in a naïve and a SELI-resistant MM cell. Conclusions: Here we propose that SELI disrupts EZH2 subcellular localization, dysregulating H3K27me3-gene suppression. Sequential BM biopsies from SELI treated patients demonstrate decreased expression of H3K27me3-regulated genes, suggesting increased EZH2 activity by nuclear accumulation. Finally, SELI-resistant primary cells have increased expression of EZH2 regulated immunotherapy target genes (e.g. CD38, SLAMF7), suggesting a possible therapeutic strategy of sequential treatment of SELI followed by immunotherapy. Using multiparameter flow cytometry of samples pre/post SELI/DEX induction, we will study SELI's effect on iTME.

The Impact of the Peptide Drug Conjugate Melflufen on the Myeloma Tumour Microenvironment

Introduction Melphalan flufenamide (melflufen), is a peptide-drug conjugate that delivers alkylating agents in tumors upon cleavage by aminopeptidases, and recently approved by the EMA for the treatment of relapsed/refractory multiple myeloma (MM). Although melflufen's MoA on tumor cells had been extensively studied, little is known about the drug impact on the tumor microenvironment. By applying single cell, multi-parametric, flow cytometry-based analysis to bone marrow mononuclear cells (BM-MNC) from MM patient samples treated ex vivo, we investigated the effect of melflufen on immune cell populations to assess for potential immune modulatory effects and to identify potential immune-based biomarkers of response. Methods Viably frozen BM-MNC from 26 samples of patients diagnosed with MM were used for multi-parametric flow cytometry-based drug sensitivity and resistance testing evaluation to melflufen after written informed consent following approved protocols in compliance with the Declaration of Helsinki. Drug sensitivity was assessed using five different concentrations of melflufen ranging between 0.5-5000 nM and cells incubated with drug or DMSO control for 72 hrs incubation. For analysis, we used antibody panels allowing us to identify and phenotype T and B lymphocytes, NK, progenitor, and malignant plasma cells (PC). Based on drug sensitivity scores (DSS) of gated PCs from drug treated and controls samples, we divided the samples into two groups - high sensitivity (HS, Q3 of PC-DSS) and low sensitivity (LS, Q1 of PC-DSS). Samples with no PCs detected (n=11) were excluded from PC subset analysis. Results The MM samples were divided based on the sensitivity of the PC population to melflufen with DSS > 21.25 defining a highly sensitive group and DSS < 15.9 defining a less sensitive group. We found that HS samples have higher abundance of mature NK and iNKT cells, although significance was low, likely due to the small cohort size. In addition, we discovered that effector memory (EM) and terminal effector (TE) T cells have higher sensitivity to melflufen, compared to naïve and central memory (CM) phenotypes (Fig. 1). More mature NK cells (Stage 5 and 6) also showed higher sensitivity than NK cells of earlier stages of maturation. Importantly, we observed that in many of the tested samples, progenitor-like CD34+CD38- cells either were not sensitive to the cytotoxic effect of the drug, or even proliferated in higher drug concentrations (Fig. 2). Interestingly, HS samples had significantly higher baseline abundance of this cell population (p<0.05). At the same time, response profiles of healthy B and malignant PCs were similar. Finally, in our tests, PCs in samples with trisomy 11 abnormality showed lower sensitivity to melflufen (p<0.05). Conclusion In a previous study, we found that effector-like cells could be associated with better response to melflufen. In this study, we observed the same trends and confirm our earlier findings demonstrating an association of NK and NKT cells with higher sensitivity to melflufen. Moreover, we identified differential response of CD4, CD8 and NK cell populations comprising the tumor microenvironment to melflufen suggesting that in addition to direct tumor cell killing, melflufen may have modulating effects on different tumor associated immune cell populations. Finally, we observed proliferation of CD34+CD38- progenitor cells, which might be relevant for lymphocyte proliferation and function, and additionally supporting potential modulating effect. Further analyses are being done to validate these findings.

Whole-Genome Sequencing Identifies Structural Variation As a Key Driver of Disease Relapse and Aggressive Clinical Behavior in Multiple Myeloma

INTRODUCTION: Many key genomic events leading to relapse in multiple myeloma (MM) occur outside of coding regions and can only be identified using whole-genome sequencing (WGS). Studies of MM progression examining single nucleotide variants (SNVs) and insertions/deletions (InDels) have identified a distinct pattern of mutations associated with resistance, however these do not fully account for drivers of progression. Studies of relapsed patients provide hints about the molecular mechanisms driving progression based on identification of homozygous loss of tumor suppressor genes, aberrant copy-number variants (CNVs), and rare examples of complex structural variants (SV). We have analyzed a set of presentation and relapsed MM samples, including paired data, derived from WGS of plasma cells and focused on SVs as key drivers of progression. METHODS: WGS was performed on 338 MM patient samples using CD138-sorted plasma cells, among which 237 samples were paired including 101 patients (30%) at presentation and at relapse, 35 of whom had more than one sample at relapse. A bioinformatics pipeline employing a consensus mechanism for determining the final set of somatic events was used based on Mutect2, Strelka2, and VarScan2 for SNVs; Mutect2, Strelka2, VarScan2, and SvABA for InDels; Battenberg and FACETS for CNVs; Manta, SvABA, DELLY2, and IgCaller for SVs. Additionally, an admixture workflow was used to estimate each individual's ancestral lineage using continentally-distinct references, comprising 23 regional populations within 5 super-populations from the 1000 Genomes Project (https://github.com/pblaney/mgp1000). Complex rearranged genomes were reconstructed using the graph-based R package JaBbA (https://github.com/mskilab-org/JaBbA). Additionally, the python package Pairtree (https://github.com/morrislab/pairtree) was used to describe the evolutionary history of acquired mutations in these patients. RESULTS: Themedian age of the cases studied was 67, and 42% were female. Racial admixture correlated with self-identification, including 74% of European ancestry with the remainder being predominantly of African ancestry. High-risk cytogenetic features were found in 10% and 13% at diagnosis and relapse, respectively. As expected, the tumor mutational burden of the relapse cases was higher than that at presentation. The patterns of SNV mutational drivers were similar at relapse in comparison to presentation with again evidence for a role of biallelic tumor suppressor gene inactivation as being a key mechanism. We also found that the number of SVs increased at relapse. Complex SVs including templated insertions, chromoplexy, and chromothripsis were detected and occurred exclusively at relapse in some cases as well as earlier in the natural history in others, suggesting they can occur as both early and late driver events. Characterizing complex SVs, further we identified them at lower levels in cases at presentation compared to relapse, consistent with these being at a higher clonal fraction and providing further evidence for their role as driver events. We did not see the emergence of additional rearrangements at relapse in either the templated insertions or chromoplexy events, suggesting that these occur at a single timepoint and remain structurally stable overtime. CONCLUSIONS: Complex SVs provide a novel mechanism driving relapse in MM which can deregulate multiple genes simultaneously providing new potential markers of aggressive disease behavior and disease evolution.

Bivalent BCMA Binding and Low Affinity CD3 T-Cell Engagement By Abbv-383 Drives Sustained Activation with Reduced T-Cell Exhaustion in Preclinical Models of Multiple Myeloma

Introduction: ABBV-383 is an IgG4-based CD3-bispecific T-cell engager (TCE) that has shown promising efficacy and a favorable safety profile in heavily pre-treated patients with relapsed/refractory multiple myeloma (MM). ABBV-383 possesses a unique combination of a low-affinity CD3δε antibody coupled to a bivalent, high-affinity BCMA engager arm in a 2+1 format. Prior pre-clinical studies demonstrated that ABBV-383 induces potent redirected T-cell killing of MM tumors with reduced cytokine release. Here, we provide additional evidence that bivalent BCMA binding by ABBV-383 reduces the negative impact of soluble BCMA and low affinity CD3 T-cell engagement drives sustained T-cell activation with reduced immune exhaustion. Methods: Structural variants of ABBV-383 were created, including 1) the bivalent BCMA targeting antibody of ABBV-383 replaced by proximal and distal monovalent VH targeting molecules, and 2) BCMA antibody structures coupled to high-and low affinity CD3 variants ( Figure). For functional testing, ABBV-383 and the structural variants were added to PBMCs or T-cells from healthy donors to serve as effector cells in co-culture with BCMA-positive MM tumor cell lines. Tumor cell killing and T-cell activation were determined by flow cytometry, and cytokine production was assessed using Luminex instrumentation. Recombinant soluble BCMA (sBCMA) was utilized in the experimental models to evaluate the extent of BCMA TCE suppression. To define the relationship between CD3-affinity and T-cell exhaustion, multi-dimensional flow cytometry was performed in long-term, 28-day co-cultures with irradiated tumor cells replated every 7 days. Results: T-cell binding was shifted by >100x with substitution of the high affinity CD3 antibody compared to ABBV-383. While all antibody variants tested induced T-cell specific MM cell killing in a BCMA-dependent manner, the negative impact of soluble BCMA on tumor killing was reduced with ABBV-383 due to its bivalent interaction with tumor cells compared to the monovalent TCE formats. In addition, the low CD3 binding affinity of ABBV-383 lowered T-cell activation antigen expression and reduced inflammatory cytokine production but resulted in similar maximal cytotoxicity of tumor cells in co-cultures of healthy and MM patient samples compared to high-affinity CD3 targeting. While maximal tumor cytotoxicity was similar, ABBV-383 was found to significantly delay the induction of a critical exhaustion-inducing transcription factor, TOX, in long-term assays. T-cell population changes were observed as early as 3 days with decreased effector memory cells (CD45RA-CD62L-) and increased naïve T-cell populations (CD62L+CD45RA+) compared to high-affinity CD3 targeting. On day 21, the high-affinity CD3 x bivalent BCMA molecule resulted in 85% of the CD8+ T-cell population expressing the transcription factor TOX compared to only 15% for ABBV-383 co-cultures. TOX induces several gene families with chromatin-modulating capacity that drive the distinct transcriptional trajectory leading to T-cell dysfunction during chronic stimulation. Simultaneous expression of multiple checkpoint inhibitory proteins is indicative of T-cell exhaustion. Triple positive CD8+ T-cells expressing LAG3, PD-1 and CTLA4 were significantly reduced by ABBV-383 versus the high-affinity CD3 variant ( Figure). Conclusions: High avidity BCMA binding coupled to low affinity T-cell engagement distinguishes the resulting mechanism of action for ABBV-383 in MM. Here, we show that the presence of bivalent-BCMA reduced the negative impact of soluble BCMA, reduced inflammatory cytokine production, and dampened the emergence of TOX+ CD8+ T-cells indicating that ABBV-383 structure maximizes its clinical potential as a safe and effective MM therapy.

Prospective Molecular Characterization of Multiple Myeloma Patient Samples Identifies High-Risk Patients and Informs Treatment Sequences through Resistance Mechanisms to Immunotherapies

Introduction. Multiple myeloma (MM) genetic diagnostics has traditionally been performed using fluorescence in situ hybridization (FISH), giving prognostic information based on immunoglobulin (Ig) translocations and key copy number abnormalities such as 1p, 1q, and 17p. However, in recent years it has become clear that more mutations, biallelic events, and focal deletions are also prognostically important and can be captured better through molecular techniques such as DNA sequencing. In addition, as targeted and immunotherapies become standard, monitoring the molecular targets will be important in determining the optimal sequence of therapies. Methods. Bone marrow aspirates from patients with MGUS/amyloid (n=3), smoldering MM (n=3), newly diagnosed MM (n=15), or progression/relapse MM (n=33) were collected. All patients were enrolled in the Indiana Myeloma Registry and consented for use of data for research purposes. CD138+ MACS cell separation was performed in a clinical pathology laboratory and DNA was extracted from CD138+ cells and patient-matched buccal swabs. 100 ng DNA from both the tumor and control sample were processed using the HyperPlus kit (KAPA Biosystems) and hybridized to the Myeloma Genome Project (MGP) sequencing panel in a CLIA-certified laboratory. The panel consisted of 228 genes for mutation and copy number analysis, as well as the immunoglobulin and MYC loci for translocation analysis. Samples were sequenced using paired-end reads to a median depth of 1063x. Data were analyzed using a clinical workflow and genomic abnormalities reported by a pathologist. Results. Of the 54 patients, Ig translocations were detected in 30 and included the known t(4;14), t(6;14), t(11;14), t(14;16) and t(12;14) as well as rare Ig translocations to partners such as GADD45B, LYN, PPCDC, and RCBTB2, of which over-expression of GADD45B and LYN are potentially targetable. A complex t(1;8;11;14) was also detected involving CCND1, MYC and the IGH loci which would not have been detectable by FISH. High-risk markers, such as gain/amp1q (22.2%) and deletion/mutation TP53 (16.6%) were detected including biallelic TP53 alterations in 5 patients (9.3%), which were mostly deletion plus mutation (4/5) and would not have been detected by traditional techniques. Of the MM patients who had been previously treated (n=33), 27 had received an IMiD and 30 had received a proteasome inhibitor. One patient showed mutation of CRBN (p.N236D) in conjunction with del3p and another patient with mutation of CUL4B (p.E277Ter) with delX indicating complete inactivation of the genes as a resistance mechanism to IMiDs. In addition, 17 patients had received an immunotherapeutic regimen including anti-CD38 or anti-BCMA. Of those that had received an anti-CD38 treatment (n=17), three had deletion of 4p (the location of CD38) including one patient, who had received three previous anti-CD38 regimens, with focal deletion of CD38. Six patients had also received anti-BCMA therapy, of which one had a mutation in the gene encoding BCMA, TNFRSF17, resulting in premature termination within the extracellular domain (p.S48Ter) in 42% of cells. This sample came from a patient who relapsed after an initial response to a BCMA CAR-T, followed by a progression occurring quickly while on a BCMA bispecific antibody Teclistamab, suggesting the loss of BCMA expression as a mechanism of resistance in both treatments. Interestingly, two patients harbored somatic mutations in the transmembrane domains of either CD38 (p.S29I) or TNFRSF17 (p.L60S) prior to the start of the respective treatments indicating that not all mutations seen in these genes are a result of treatment resistance. Conclusions. DNA sequencing approaches are cost-effective alternatives to FISH, the current standard diagnostic technology, to detect genomic abnormalities in multiple myeloma and they can identify clinically meaningful markers related to prognosis and treatment, particularly in the emerging era of immunotherapeutics where antigen evasion is a key mechanism of molecular resistance.

Metastatic Infiltration of Nervous Tissue and Periosteal Nerve Sprouting in Multiple Myeloma-Induced Bone Pain in Mice and Human.

Multiple myeloma (MM) is a neoplasia of B plasma cells that often induces bone pain. However, the mechanisms underlying myeloma-induced bone pain (MIBP) are mostly unknown. Using a syngeneic MM mouse model, we show that periosteal nerve sprouting of calcitonin gene-related peptide (CGRP+) and growth associated protein 43 (GAP43+) fibers occurs concurrent to the onset of nociception and its blockade provides transient pain relief. MM patient samples also showed increased periosteal innervation. Mechanistically, we investigated MM induced gene expression changes in the dorsal root ganglia (DRG) innervating the MM-bearing bone of male mice and found alterations in pathways associated with cell cycle, immune response and neuronal signaling. The MM transcriptional signature was consistent with metastatic MM infiltration to the DRG, a never-before described feature of the disease that we further demonstrated histologically. In the DRG, MM cells caused loss of vascularization and neuronal injury, which may contribute to late-stage MIBP. Interestingly, the transcriptional signature of a MM patient was consistent with MM cell infiltration to the DRG. Overall, our results suggest that MM induces a plethora of peripheral nervous system alterations that may contribute to the failure of current analgesics and suggest neuroprotective drugs as appropriate strategies to treat early onset MIBP.SIGNIFICANCE STATEMENT Multiple myeloma (MM) is a painful bone marrow cancer that significantly impairs the quality of life of the patients. Analgesic therapies for myeloma-induced bone pain (MIBP) are limited and often ineffective, and the mechanisms of MIBP remain unknown. In this manuscript, we describe cancer-induced periosteal nerve sprouting in a mouse model of MIBP, where we also encounter metastasis to the dorsal root ganglia (DRG), a never-before described feature of the disease. Concomitant to myeloma infiltration, the lumbar DRGs presented blood vessel damage and transcriptional alterations, which may mediate MIBP. Explorative studies on human tissue support our preclinical findings. Understanding the mechanisms of MIBP is crucial to develop targeted analgesic with better efficacy and fewer side effects for this patient population.

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma.

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MMcell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro. Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.

Phenotypic deconvolution in heterogeneous cancer cell populations using drug-screening data

Tumor heterogeneity is an important driver of treatment failure in cancer since therapies often select for drug-tolerant or drug-resistant cellular subpopulations that drive tumor growth and recurrence. Profiling the drug-response heterogeneity of tumor samples using traditional genomic deconvolution methods has yielded limited results, due in part to the imperfect mapping between genomic variation and functional characteristics. Here, we leverage mechanistic population modeling to develop a statistical framework for profiling phenotypic heterogeneity from standard drug-screen data on bulk tumor samples. This method, called PhenoPop, reliably identifies tumor subpopulations exhibiting differential drug responses and estimates their drug sensitivities and frequencies within the bulk population. We apply PhenoPop to synthetically generated cell populations, mixed cell-line experiments, and multiple myeloma patient samples and demonstrate how it can provide individualized predictions of tumor growth under candidate therapies. This methodology can also be applied to deconvolution problems in a variety of biological settings beyond cancer drug response.

Dysregulation of alternative splicing contributes to multiple myeloma pathogenesis.

Dysregulation of alternative splicing (AS) triggers many tumours, understanding the roles of splicing events during tumorigenesis would open new avenues for therapies and prognosis in multiple myeloma (MM). Molecular, genetic, bioinformatic and statistic approaches are used to determine the mechanism of the candidate splicing factor (SF) in myeloma cell lines, myeloma xenograft models and MM patient samples. GSEA reveals a significant difference in the expression pattern of the alternative splicing pathway genes, notably enriched in MM patients. Upregulation of the splicing factor SRSF1 is observed in the progression of plasma cell dyscrasias and predicts MM patients' poor prognosis. The c-indices of the Cox model indicated that SRSF1 improved the prognostic stratification of MM patients. Moreover, SRSF1 knockdown exerts a broad anti-myeloma activity in vitro and in vivo. The upregulation of SRSF1 is caused by the transcription factor YY1, which also functions as an oncogene in myeloma cells. Through RNA-Seq, we systematically verify that SRSF1 promotes the tumorigenesis of myeloma cells by switching AS events. Our results emphasise the importance of AS for promoting tumorigenesis of MM. The candidate SF might be considered as a valuable therapeutic target and a potential prognostic biomarker for MM.

A Multiomic Approach to Reversing Therapy Resistance in Multiple Myeloma Using Paired Ex Vivo Drug Sensitivity Measures and RNA Sequencing Data

A key challenge in multiple myeloma (MM) is evolution of resistance to standard-of-care (SOC) therapies such as proteasome inhibitors (PI), monoclonal antibodies, and novel targeted therapies. We developed a computational framework that identifies gene programs associated with SOC therapy resistance by pairing patient RNAseq data with clinical response and ex vivo drug response to find patient-specific targets to overcome therapy resistance. We hypothesize that there are two types of mechanisms of resistance in MM; dynamic (involving cell cycle) and cytostatic (cell-intrinsic, EMDR, complement, etc.). We inferred the dynamic mechanism of resistance by comparing transcriptomic profiles of therapy-naïve vs refractory MM patients, therapy-resistant vs wildtype cell lines, drug perturbation transcriptomics from LINCS-L1000 and activity-based proteomic profiling of MM cell lines. The cytostatic mechanism of resistance was inferred by associating RNAseq data with ex vivo drug response, where CD138+ cells from MM patient samples were co-cultured with human bone marrow stromal cells and patient plasma in an ex vivo reconstruction of the tumor microenvironment and tested with SOC drugs in 399 MM patient samples. The computational framework begins with the construction of a topological map of MM transcriptome using t-SNE and fuzzy c-means clustering on z-normalized expression of 16,738 genes across 844 MM patient samples, which yielded MM-specific gene programs (clusters of co-expressing genes). Using publicly available ChIP-seq databases like ENCODE and ChEA, we identified regulatory proteins (RPs) upstream of these gene programs. Kinases phosphorylating these RPs were identified from proteomic databases like PhosphoSitePlus and PhosphoPoint; generating a cascading GRN of MM gene programs, their RPs, and kinases, described by a biophysical model representing transcription, translation, and post-translational effects. The model estimates expression of each gene as a function of gene expression of its upstream RPs and kinases. The model for transcriptional regulation for each gene is trained using RNAseq data of 422 patients and validated against the rest of the cohort (422). Figure 1 is a graphical representation of gene-wise Pearson's correlation of model-predicted and actual gene expression represented by the color of each point (gene) on the tSNE. The set of genes that have poor correlation in Figure 1 (blue) statistically significantly (hypergeometric test; p-value <1e-48 and representation factor = 7.27) coincide with genes that are epigenetically regulated (identified by their high variability of chromatin accessibility across MM patients). We implement this computational framework to identify gene programs associated with a dynamic mechanism of PI (frontline therapy in MM) resistance, which yielded a GRN comprising of 218 co-expressing genes, 13 upstream RPs, and 45 kinases (17 druggable by kinase inhibitors). Network analysis of this GRN revealed that FOXM1 as a key therapeutic vulnerability (characterized by the highest betweenness centrality - a hub for flow of information) that can be targeted by inhibiting PLK1; a key regulator of cell cycle that phosphorylates FOXM1 that, in turn regulates PLK1 expression. A statistically significant (unpaired t-test) increase in z-normalized expression of PLK1 was observed in MM patients (n = 233) clinically refractory to CFZ (p-value < 0.0001) and BTZ (p-value = 0.0004) compared to PI-naïve. Ex vivo functional validation in a cohort of 61 MM patient samples shows a statistically significant (unpaired t-test) lowering of Volasertib (PLK1 inhibitor) AUC in MM patients that were clinically refractory to CFZ (p-value = 0.03) and BTZ (p-value = 0.02) compared to PI-naïve (Figure 2). Similarly, we infer cytostatic mechanism of resistance to PIs by pairing ex vivo drug response from 399 MM patients with RNAseq data to identify gene programs that are enriched for PI-resistance and PI-sensitivity using gene set enrichment analysis; which identified PRCK, ROCK, and PLK1 inhibitors as therapeutic targets that can either synergize with PIs or exhibit synthetic lethality. Ongoing studies are focused on identifying novel targets to overcome resistance to DARA. The proposed computational approach can identify novel therapeutic strategies to overcome SOC therapy resistance using patient-specific targeted therapies. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

A Single Next Generation Sequencing Assay for Detection of Driver Mutations, Translocations and Copy Number Alterations in Patients with Multiple Myeloma

Multiple myeloma (MM) is a plasma cell malignancy characterized by several genetic abnormalities that impact risk stratification, outcome, and response to therapy; with fluorescence in situ hybridization (FISH) considered the gold-standard assay to detect the presence of chromosomal translocations and copy-number variations (CNV). Here, we evaluate the performance of a single clinically actionable targeted sequencing (NGS) assay for detecting cytogenetic abnormalities in addition to recurrent driver mutations in MM. Patient-derived bone marrow aspirates were obtained and enriched for CD138+ plasma cells. Targeted sequencing was performed using a 2.3 Mb custom capture panel covering 139 genes and regions surrounding MYC, immunoglobulin heavy chain (IgH), and immunoglobulin light chain kappa (IgK) and lambda (IgL) loci. Chromosomal translocations were identified using an in-house algorithm designed specifically for targeted capture DNA sequencing data analyses. Structural variants were called based on discordant read pairs as well as junction split reads, solving the challenges from both the overlapping paired-end reads due to the longer read lengths (150 bp) and the mapping ambiguities in the Ig regions. CNV were assessed using both on and off target reads, using a 200 kb bin size for segmentation covering the entire genome. Clinical annotations and FISH panel reports were abstracted. We sequenced 264 MM patient samples, 94% of which had available FISH information. A median of two somatic mutated genes per sample (range 0-13) was found. The most commonly mutated genes per sample were: KRAS (35%), NRAS (25%), FAM46C (15%), DIS3 (13%), BRAF (13%), ATM (11%), and TP53 (11%). Comparing NGS with FISH, we found a perfect concordance for the identification of t(4;14), t(6;14), t(14;16), and t(14;20); a 100% specificity and 97% sensitivity for t(11;14); and sensitivity >90% and an average specificity of 85% for trisomies of chromosomes 3, 7, 9, 11, and 15. The NGS approach was also able to detect gain(1q) and mono(13) with a sensitivity and specificity >90%, and del(17p) with a 60% sensitivity and 100% specificity. The reduced sensitivity for del(17p) detection was mostly due to focal deletions and low tumor purity. Because the TP53 gene is included in the custom capture panel, we increased the sensitivity by determining six separate regions of coverage using on-target probes, which enabled the detection of focal del(17p), increasing the sensitivity to 78%. The NGS approach also allowed the characterization of 16 (6%) samples with unavailable FISH. Of the 27 samples with del(17p) detected by FISH, NGS was able to identify TP53 mutations (i.e., biallelic inactivation) in 14 samples (52%). Due to the existence of multiple and promiscuous chromosomal partners involved in IgH translocation, the identification of the chromosomal partners is limited to the clinical FISH probe sets; in fact, 19 study samples presented abnormal IgH without a known partner by FISH. Our NGS assay was able to identify these partners, confirming MYC-IGH translocations in seven (37%) of these cases. Additionally, we detected MYC translocations with immunoglobulin light chains: 14 (5%) cases with IGK, and eight (3%) with IGL. Although IgL translocations, particularly IgL-MYC translocations, have been recently associated to poor prognosis, they are not routinely evaluated in FISH assays. The risk stratification and clinical utility of the NGS assay was demonstrated by the shorter overall survival observed in samples classified as high risk (mSMART 3.0; hazard ratio [HR]= 2.81; CI:1.89-4.17; p<0.0001), which was also observed with risk assessment by FISH (HR = 2.48; CI:1.72-3.58; p<0.0001). Therefore, in addition to the detection of clinically relevant somatic mutations, the targeted NGS approach showed robust detection of recurrent MM specific IgH translocations and CNV. Furthermore, the detection of relevant abnormalities not routinely assessed in most clinical labs, such as TP53 bi-allelic inactivation, IgL and MYC rearrangements, supports the use of this small, targeted panel as a clinically relevant, single molecular assay, for the comprehensive profiling of MM.

A Potential Role of NK Cells and ABCB9 in Modulating the Response to Melflufen in Multiple Myeloma

Introduction Melphalan flufenamide (melflufen), is a novel peptide-drug conjugate that delivers alkylating agents in tumours upon hydrolysis by aminopeptidases. Melflufen was recently approved by the EMA for the treatment of relapsed/refractory multiple myeloma (MM). Considering the challenges in treating this group of patients and their low overall survival, information that can support treatment selection and success is urgently needed. To discover possible biomarkers of melflufen sensitivity, we applied a multiparametric drug sensitivity assay to MM patient samples ex vivo and analysed the samples by single cell RNA sequencing (scRNAseq) and flow cytometry. Drug testing identified groups of MM samples with high and low sensitivity to melflufen, while differential gene expression and flow cytometry analysis revealed markers associated with response and cytotoxicity. Methods Bone marrow mononuclear cells from 12 newly diagnosed (ND) and 12 relapsed/refractory (RR) patients were used for multi-parametric flow cytometry-based drug sensitivity and resistance testing (DSRT) evaluation to melflufen and melphalan, and for scRNAseq after written informed consent following approved protocols in compliance with the Declaration of Helsinki. Based on the results from the DSRT assay and drug sensitivity scores (DSS), we divided the samples into three groups - high sensitivity (HS, DSS > 40 (melflufen) or DSS > 16 (melphalan)), intermediate sensitivity (IS, 31 ≤ DSS ≤ 40 (melflufen) or 10 ≤ DSS ≤ 16 (melphalan)), and low sensitivity (LS, DSS < 31 (melflufen) or DSS < 10 (melphalan)). To identify genes, responsible for the general sensitivity to we conducted differential gene expression (DGE) analyses between HS and LS samples for both drugs ("HS vs. LS melphalan” and "HS vs. LS for melflufen", respectively). In addition, we conducted flow cytometry analysis to evaluate the levels of HLA-B protein, associated with increased cytotoxicity of NK cells. Results We analyzed the DSRT and scRNAseq data for the MM samples of different melflufen sensitivity groups (HS, IS, LS). DGE analysis showed significantly lower levels of the ABCB9 gene in plasma cells populations of the HS compared to LS group (2.2-fold, HS vs. LS groups for melflufen, p < 0.01). ABCB9 belongs to a family of proteins known for drug efflux and multidrug resistance. A similar pattern was detected for the melphalan HS vs. LS (3.2-fold, p < 0.01) comparison suggesting that this alteration might be a common indicator of sensitivity to melflufen and melphalan. As a confirmation, we found that MM cell lines treated with melphalan (Fig. 1) also tend to express higher levels of ABCB9, as compared to control cells (1.2-fold, p<0.001), indicating its potential role in drug resistance. Based on scRNAseq and flow cytometry analysis, we also discovered that NK cells may be associated with melflufen cytotoxic effect. Our results demonstrated higher levels of NK and NKT subpopulations, as well as lower surface HLA-B protein level (p<0.01) and activation of NFKB signalling in the melflufen HS group in comparison to the LS group (Fig. 2). The latter two features are associated with increased NK cells cytotoxicity, thus, suggesting synergistic effect of innate immunity with melflufen. Conclusion In summary, we demonstrate the association of ABCB9 expression with resistance both to melphalan or melflufen. Furthermore, we observed that MM samples that were highly sensitive to melflufen exhibited markers associated with NK-mediated cytotoxicity, suggesting a potential role of NK cells for enhancing the efficacy of melflufen. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal