Tumor Specific cfDNA Predicts Treatment Response of Multiple Myeloma Patients

Abstract Introduction: Great progress achieved in treatment of multiple myeloma (MM) over the past decade changed overall perception of importance of minimal residual disease (MRD) assessment. Since new drugs induce deep responses, MRD must be evaluated using sensitive techniques, such as allele specific PCR (ASO-PCR), next-generation sequencing (NGS) or flow cytometry. MM is a genetically heterogeneous cancer of plasma cells characterized by multiple focal lesions in the bone marrow (BM). Hence, a single-site biopsy can create a sampling bias. In spite of this, BM samples are typically used for MRD analysis, but currently an alternative approach called liquid biopsies, which utilizes body fluids for analysis of various molecules and cells, is intensively studied. Cell-free DNA (cfDNA) as one type of the molecule which can be analyzed using liquid biopsy approach showed promising results previously. In our study, patient-specific, clonotypic rearrangement of immunoglobulin heavy chain (IgH) gene, identified in bone marrow samples, was used for qPCR analysis of cfDNA samples from peripheral blood. We demonstrate that dynamics and quantity of patient-specific, clonotypic IgH rearrangement found in cfDNA can predict the outcomes and response of MM patients. Methods: Total of 45 patients enrolled in the study. Samples of BM were collected at diagnosis, and CD138+ cell fraction was sorted using magnetic activated cell sorting. At diagnosis and at three-month intervals, samples of peripheral blood (PB) were collected for cfDNA extraction and analysis until a patient reached complete remission (CR). If CR was not reached, samples were collected for 24 months after diagnosis. Two more samples of PB were collected (CR+3, CR+6) if patients reached CR. Patient-specific VDJ rearrangement was identified using previously described PCR method from genomic DNA extracted from CD138+ cell fraction; based on the results, patient-specific primers and probes were designed for use in ASO-qPCR. Obtained data were evaluated by absolute and relative frequencies of categorical variables and median (minimum-maximum) of quantitative variables. Results: First, we assessed time to CR. Patients were classified according to the quantity of cfDNA measured at time of diagnosis into three groups: negative, PNQ (= positive non-quantifiable) and positive. As PNQ had a similar profile to negative-classified samples (in K-M plot), PNQ were grouped together with negative results except extremely high values (> 5, n = 2) which were reclassified from PNQ to positive group. The Kaplan-Meier estimates at 12 months were reported and supplemented by the 95% confidence interval derived using Greenwood formula. The results show that significantly higher number of patients classified as negative or PNQ with quantity < 5 have reached CR in contrast to patients classified as positive or PNQ with quantity > 5. The same trend applies to association of quantity of tumor-specific cfDNA with time to CR where Cox proportional-hazards model was adopted. Patients classified as negative or PNQ with quantity < 5 have significantly increased chance of achieving CR (2.7 times) in comparison to patients classified as positive or PNQ with quantity > 5. Conclusion: Our results demonstrate that MM patient-specific cfDNA fragments are released into the bloodstream and that patients either with no or very few DNA fragments have a higher chance of achieving better treatment response eventually. Work was supported by grant AZV 17-29343A Disclosures Hajek: Amgen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

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Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modelling Multiple Myeloma Algorithm

Blood ◽

10.1182/blood-2018-99-118686 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1893-1893

Author(s):

Ravi Vij ◽

Justin King ◽

Mark A. Fiala ◽

Neeraj Kumar Singh ◽

Mohammed Sauban ◽

...

Keyword(s):

Multiple Myeloma ◽

Computational Biology ◽

Clinical Response ◽

Treatment Response ◽

Board Of Directors ◽

Research Funding ◽

Patient Specific ◽

Similar Response ◽

Advisory Committees ◽

Combination Regimens

Abstract Background: Multiple myeloma (MM) is an incurable and heterogeneous haematological malignancy in which immune suppression and complex biology affect the disease and its response to treatment. Several new treatments have been approved for MM in recent years providing numerous options for patients with relapsed/refractory disease. However, there is no validated method for selecting the best treatment combination for each patient, making patient management difficult. The ability to predict treatment response based on disease characteristics could improve clinically outcomes. Aim: This was a validation of a genomics-informed response prediction using computational biology modelling (CBM) in patients with relapsed/refractory MM. Methods: Input data from fluorescence in-situ hybridization (FISH), karyotype, and a MM specific next generation sequencing capture array were analysed using CBM. This was a retrospective review of patients which were treated with different combinations based on patient/physician choice. The CBM uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated pathways. The specific drug combination for each patient was simulated and the quantitative drug effect was measured on a composite MM disease inhibition score (i.e., cell proliferation, viability, apoptosis and paraproteins). The predicted outcomes were then compared to the clinical response (≥PR or < PR per IMWG) to assess the accuracy of this CBM predictive approach. Results: 27 patients were selected for the study; 3 failed CBM due to missing inputs and in 3 clinical response was not able to be assessed, leaving 21 eligible for the analysis. The median age at presentation was 57 years (range 37-76) and 52% were male. The median prior lines of MM therapy was 5 (range 1-15). 38% were refractory to bortezomib, 62% to lenalidomide, 52% to carfilzomib, 57% to pomalidomide, and 43% to daratumumab. 81% had a prior autologous stem cell transplant. The treatments modelled included IMiD-based regimens (n = 9), PI-based regimens (n = 6), chemo-based regimens (n = 3), selinexor (n = 2), PI/IMiD combination regimens (n = 1). Sixteen were clinical responders and 5 were non-responders. CBM predictions matched for 17 of 21 treatments overall, 15 of 16 clinical responders and 2 of 5 non-responders. The statistics of prediction accuracy against clinical outcome are presented in Table 1. Interestingly, the CBM identified drugs within the combination regimens which may not have impacted efficacy. For example, the CBM predicted that one patient treated with bortezomib, venetoclax, and dexamethasone would have had similar response if venetoclax had been omitted from the regimen. Conclusion: We have demonstrated that a CBM approach, which incorporates genomics, can help predict response in patients with relapsed or refractory MM. Prospective studies using the CBM as part of treatment decision-making will help determine its application into clinical settings. Disclosures Vij: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Honoraria, 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; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees. Singh:Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Lakshminarayana:Cellworks Research India Private Limited: Employment. Talawdekar:Cellworks Research India Private Limited: Employment. Mitra:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment.

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Reactive Polyclonal Gammopathy Associated with Polyclonal Plasmacytosis Is Common in Patients with Multiple Myeloma Receiving Prolonged Lenalidomide Therapy: A Retrospective Study of 104 Patients

Blood ◽

10.1182/blood.v120.21.4033.4033 ◽

2012 ◽

Vol 120 (21) ◽

pp. 4033-4033

Author(s):

Dmitriy Zamarin ◽

Sean Devlin ◽

Maria Arcila ◽

Sergio A. Giralt ◽

Heather Landau ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Board Of Directors ◽

Median Time ◽

Research Funding ◽

Moderate Increase ◽

Advisory Committees ◽

Number Of Patients ◽

Polyclonal Gammopathy ◽

The Absolute

Abstract Abstract 4033 BACKGROUND: Prolonged lenalidomide treatment is frequently used in patients with multiple myeloma (MM), both in the upfront and relapsed settings. We have previously reported a small series of 6 patients receiving prolonged lenalidomide treatment who presented with a polyclonal IgA gammopathy characterized by a marked elevation in the serum IgA level, polyclonal plasmacytosis in the bone marrow, and without any evidence of clinical disease progression. Although the immunologic mechanism underlying this observation is currently under investigation, it is important to recognize and characterize its incidence, clinical features, and prognostic significance. For these purposes, we have undertaken a retrospective analysis of all patients treated at MSKCC with prolonged course of lenalidomide. METHODS AND RESULTS: We retrospectively identified 104 patients with MM who received a prolonged course of lenalidomide (>6 months). Among these patients, 21 (20%) were noted to have polyclonal immunoglobulin (Ig) elevation above the upper limit of normal during lenalidomide therapy, affecting IgA in 13, IgG in 6, and both IgA and IgG in 2 patients. All 21 patients were without evidence of relapse or progression (R/POD) by serologic or clinical criteria at the time of polyclonal Ig elevation. In 15 patients the polyclonal Ig did not involve the initial monoclonal isotype. The median time from lenalidomide initiation to polyclonal elevation of Ig level was 10.9 months (range 2 to 38.6 months), with the median peak IgA level of 587 mg/dl (range 374 to 1190 mg/dl), and the median peak IgG level of 1800 mg/dl (range 1575 to 2650 mg/dl). Bone marrow aspirates and biopsies were available in 12 patients during the period of Ig elevation and the median plasmacytosis was 12% (range 5 to 20%) on the aspirate. Immunohistochemical (IHC) studies of the bone marrow biopsy showed moderate increase in CD138+ cells without light chain restriction. IHC using IgA and IgG antibody staining in the patients with IgA elevation confirmed that most plasma cells were IgA-producing and were not consistent with the original myeloma clone. To evaluate for the association of polyclonal gammopathy with progression free survival, we performed a landmark analysis on all 104 patients based on the magnitude of the absolute Ig elevation measured at 6 months after initiation of lenalidomide. The patients were divided into 2 groups on the basis of the median absolute elevation in the levels of IgA (40 mg/dl) or IgG (150 mg/dl) from the baseline prior to therapy initiation to 6 months after starting the treatment. Statistical comparison was limited by the small number of patients who had R/POD in the sample (n=16), but there was a trend toward improved PFS in the patients who achieved absolute IgA elevation >40mg/dl, though any difference was attenuated by 36 months following the 6-month landmark (logrank p-value: 0.54). Interestingly, when focusing exclusively on the 16 patients with R/POD during the followup, the median time to progression was 27.5 months and 13.1 months in patients with absolute IgA elevation >40mg/dl (n=10), and those with absolute IgA elevation <40mg/dl (n=6) at the 6 month landmark, respectively. CONCLUSIONS: Polyclonal gammopathy with Ig levels exceeding the normal range associated with polyclonal plasmacytosis occurs with a relatively high frequency (20%) in patients treated with prolonged courses of lenalidomide. Awareness of this effect is important especially in view of the associated significant bone marrow plasmacytosis, which may mistakenly be construed as R/POD in patients who are actually responding to treatment. In addition, the absolute elevation in the IgA level measured at 6 months post initiation of treatment may be a prognostic indicator of progression, with high elevations potentially indicating an extended benefit from lenalidomide treatment. Further studies are needed to validate these observations and to elucidate their mechanism. Disclosures: Giralt: Celgene: Honoraria, Research Funding. Landau:Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Research Funding. Hassoun:Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding.

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Engineering a Humanised Niche to Support Human Haematopoiesis in Mice: Novel Opportunities in Modelling Cancer

Cancers ◽

10.3390/cancers12082205 ◽

2020 ◽

Vol 12 (8) ◽

pp. 2205 ◽

Cited By ~ 1

Author(s):

Alvaro Sanchez-Herrero ◽

Isabel A. Calvo ◽

Maria Flandes-Iparraguirre ◽

Marietta Landgraf ◽

Christoph A. Lahr ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Peripheral Blood ◽

Drug Testing ◽

Tumour Microenvironment ◽

Patient Specific ◽

Human Cd34 ◽

Haematopoietic Cells ◽

Cd34 Cells ◽

Haematopoietic System

Despite the bone marrow microenvironment being widely recognised as a key player in cancer research, the current animal models that represent a human haematopoietic system lack the contribution of the humanised marrow microenvironment. Here we describe a murine model that relies on the combination of an orthotopic humanised tissue-engineered bone construct (ohTEBC) with patient-specific bone marrow (BM) cells to create a humanised bone marrow (hBM) niche capable of supporting the engraftment of human haematopoietic cells. Results showed that this model supports the engraftment of human CD34+ cells from a healthy BM with human haematopoietic cells migrating into the mouse BM, human BM compartment, spleen and peripheral blood. We compared these results with the engraftment capacity of human CD34+ cells obtained from patients with multiple myeloma (MM). We demonstrated that CD34+ cells derived from a diseased BM had a reduced engraftment potential compared to healthy patients and that a higher cell dose is required to achieve engraftment of human haematopoietic cells in peripheral blood. Finally, we observed that hematopoietic cells obtained from the mobilised peripheral blood of patients yields a higher number of CD34+, overcoming this problem. In conclusion, this humanised mouse model has potential as a unique and patient-specific pre-clinical platform for the study of tumour–microenvironment interactions, including human bone and haematopoietic cells, and could, in the future, serve as a drug testing platform.

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Molecular Characterization of Bone Marrow and Peripheral Blood Compartments from Patients with Plasma Cell Leukemia in the Mmrf Commpass Study

Blood ◽

10.1182/blood-2019-130697 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1782-1782

Author(s):

Sheri Skerget ◽

Austin Christofferson ◽

Sara Nasser ◽

Christophe Legendre ◽

The MMRF CoMMpass Network ◽

...

Keyword(s):

Cell Cycle ◽

Multiple Myeloma ◽

Bone Marrow ◽

Flow Cytometry ◽

Plasma Cell ◽

Peripheral Blood ◽

Research Funding ◽

Plasma Cells ◽

Cell Cycle Control ◽

Cell Leukemia

Plasma cell leukemia (PCL) is rare but represents an aggressive, advanced form of multiple myeloma (MM) where neoplastic plasma cells (PCs) escape the bone marrow (BM) and circulate in the peripheral blood (PB). Traditionally, PCL is defined by the presence of >20% circulating plasma cells (CPCs), however, recent studies have suggested that PCL be redefined as the presence of >5% CPCs. The Multiple Myeloma Research Foundation CoMMpass study (NCT01454297) is a longitudinal, observational clinical study with 1143 newly diagnosed MM patients. BM-derived MM samples were characterized using whole genome (WGS), exome (WES), and RNA (RNAseq) sequencing at diagnosis and each progression event. When >5% CPCs were detected by flow cytometry, PCs were enriched independently from both compartments, and T-cells were selected from the PB as a control for WGS and WES. This substudy within CoMMpass provides the largest, most comprehensively characterized dataset of matched MM and PCL samples to date, which can be leveraged to better understand the molecular drivers of PCL. At diagnosis, 813/1143 CoMMpass patients had flow cytometry data reporting the percent PCs in PB, of which 790 had <5%, 17 had 5-20%, and 6 had >20% CPCs. Survival analyses revealed that patients with 5-20% CPCs (median = 20 months) had poor overall survival (OS) outcomes compared to patients with <5% CPCs (median = 74 months, p < 0.001), and no significant difference in outcome was observed between patients with 5-20% and >20% (median = 38 months) CPCs. Patients with 1-5% CPCs (median = 50 months, HR = 2.45, 95% CI = 1.64 - 3.69, p < 0.001) also exhibited poor OS outcomes compared to patients with <1% CPCs (median = 74 months), suggesting that patients with >1% CPCs are a higher risk population, even if they do not meet the PCL threshold. Using a cutoff of >5% CPCs, 23/813 (2.8%) patients presented with primary PCL (pPCL) at diagnosis. Of these patients, 7 (30%) were hyperdiploid (HRD), of whom 1 had a CCND1 and 1 had a MYC translocation; while 16 (70%) were nonhyperdiploid (NHRD), all of whom had a canonical immunoglobulin translocation (6 CCND1, 5 WHSC1, 3 MAF, 1 MAFA, and 1 MAFB). Of 124 patients with serial sample collections, 5 (4%) patients without pPCL had >5% CPCs at progression, and thus relapsed with secondary PCL (sPCL). Of the 5 sPCL patients, 2 (40%) were NHRD with a CCND1 or MAF translocation; while 3 (60%) were HRD, 1 with a WHSC1 translocation. Median time to diagnosis of sPCL was 22 months (range = 2 - 31 months), and patients with sPCL (median = 22 months) and pPCL (median = 30 months) exhibited poor OS outcomes as compared to MM patients (74 months, p < 0.001). Sequencing data was available for 15 pPCL and 5 sPCL samples. For 12 patients with WES, WGS, and RNAseq performed on their PCL tumor sample, an integrated analysis identified recurrent, complete loss-of-function (LOF) events in only CDKN2C/FAF1, SETD2, and TRAF3. Five pPCL patients had complete LOF of a gene involved in G1/S cell cycle control, including CDKN2C, CDKN2A, CDKN1C, and ATM. These LOF events were not observed in NHRD t(11;14) PCL patients, suggesting that CCND1 overexpression and LOF of genes involved in G1/S cell cycle control may represent independent drivers of PCL. Comparing WES and WGS data between matched MM and PCL tumor samples revealed a high degree of similarity in mutation and copy number profile. However, differential expression analysis performed for 13 patients with RNAseq data comparing their MM and PCL tumors revealed 27 up- and 39 downregulated genes (padj < 0.01, FDR = 0.1) in PCL versus MM. Pathway analysis revealed an enrichment (p < 0.001) for genes involved in adhesion and diapedesis, including upregulation of ITGB2, PF4, and PPBP, and downregulation of CCL8, CXCL12, MMP19, and VCAM1. The most significantly downregulated gene in PCL (log2FC = -6.98) was VCAM1, which plays a role in cell adhesion, and where loss of expression (TPM < 0.01) was observed across all PCL samples. Upregulation of four S100 genes including S100A8, S100A9, S100A12, and S100P, which have been implicated in tumor growth, metastasis, and immune evasion, was also observed in PCL. Interestingly, a S100A9 inhibitor has been developed and may represent a novel treatment option for PCL patients. In summary, PCL was found to be associated with molecular events dysregulating G1/S cell cycle control coupled with subtle changes in transcription that likely occur in a subclonal population of the MM tumor. Disclosures Lonial: Genentech: Consultancy; GSK: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding; Amgen: Consultancy.

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Carfilzomib Thalidomide and Dexamethasone Is Safe and Effective in the Treatment of Relapsed/Refractory Multiple Myeloma: Preliminary Outcome from the Open Label Phase II ALLGMM018/AMN003 Study

Blood ◽

10.1182/blood-2018-99-111434 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1955-1955

Author(s):

Hang Quach ◽

Simon J. Harrison ◽

Slavisa Ninkovic ◽

Jane Estell ◽

Noemi Horvath ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

T Cells ◽

Board Of Directors ◽

Peripheral Blood ◽

Research Funding ◽

Open Label ◽

Advisory Committees ◽

Open Label Phase ◽

Grade 3

Abstract Background: Carfilzomib lenalidomide and dexamethasone (KRd) is FDA-approved for the treatment relapsed/refractory multiple myeloma (RRMM) based on data from the ASPIRE study (Stewart K et al. NEJM 2015). Thalidomide, a first generation immunomodulatory drug (IMiD) is less costly than lenalidomide and is synergistic in combination with proteasome inhibitors in the treatment of MM. ALLG MM018/ AMN003 is an open label phase II study of carfilzomib thalidomide and dexamethasone (KTd) for patients with RRMM. The primary end point is progression free survival (PFS). Secondary endpoints include overall response rate (ORR), duration of response (DOR), safety and health related quality of life. Method: Eligible patients were those with RRMM who have had 1-3 prior lines of treatment. The KTd regimen consisted of carfilzomib [20mg/m2 IV C1D1 and 2, 56mg/m2 (36mg/m2 for patients age ≥75 years) from C1D8 onwards], thalidomide (100mg po nocte) and dexamethasone [40mg (20mg for patients age ≥75 years) po weekly], in a 28-day cycle. After 12 cycles, thalidomide was omitted and Kd [carfilzomib 56mg/m2 (36/m2 for patients age ≥75 years) on days 1,2,15,16 and dexamethasone 40mg (20mg for patients age ≥75 years) on days 1,15 every 28 days]was continued for a further 6 cycles. Peripheral blood and bone marrow aspirate and trephine for correlative studies were collected from the first 30 patients, at baseline, after cycle 6 and at confirmed disease progression. The aim of the correlative study was to assess for immunological correlates to clinical outcome. Immunological parameters that will be assessed include NK and T cells subsets on peripheral blood via mass cytometry (CyTOF). On the bone marrow trephine, NK cells, T cells, GRP78 expression within CD38 positive plasma cells, PD1 and PDL1 expression will be assessed at the myeloma site and the surrounding microenvironment using OPAL multiplex immunohistochemistry technology. Results: Between March 2017 to June 2018, 56 patients (median age 66 years, range 56-79; 77% Caucasian and 23% Asian) out of the planned 100 were enrolled, with a median follow up of 4.9 (range, 1.0-13.7) months. Response rates in 39 evaluable patients were ≥MR (97%), ≥PR (89%) and ≥VGPR (66%). Median PFS is not reached, and no patients with ≥MR have relapsed. Grade ≥3/4 AEs occurred in 56% of patients, the most common of which were peripheral sensory neuropathy (13%), dyspnoea (13%) and infections (7%). All grade cardiovascular AEs included dyspnoea (27%), cardiac complications (5%), systemic-hypertension (9%) and pulmonary-hypertension (1.9%), however very few were grade ≥3. Three patients have died on study from disease complications, haemorrhage, and primary cardiac ischaemic event. Thus far, we have not found a significant difference in rates or profile of adverse events between the Caucasian versus Asian subgroups of patients. Conclusion: This preliminary analysis demonstrates that the KTd combination is a tolerable regimen for patients with RRMM with a safety profile in line with previous reports for each of carfilzomib and thalidomide. Initial response rates appear very promising and durable with responses up to 13.7 months thus far in some patients. Patient accrual is ongoing. Disclosures Quach: Janssen Cilag: Consultancy; Sanofi Genzyme: Research Funding; Celgene: Consultancy, Research Funding; Amgen: Consultancy, Research Funding. Harrison:Janssen-Cilag: Other: Scientific advisory board. Mollee:Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Durie:Takeda: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Chng:ASLAN Pharmaceuticals: Research Funding.

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Use of Genomic Information to Predict Treatment Response in Multiple Myeloma Patients By Computational Mapping of Protein Network Disturbances

Blood ◽

10.1182/blood.v128.22.2099.2099 ◽

2016 ◽

Vol 128 (22) ◽

pp. 2099-2099

Author(s):

Leylah Drusbosky ◽

Mark A Fiala ◽

Justin A King ◽

Ravi Vij ◽

Shireen Vali ◽

...

Keyword(s):

Multiple Myeloma ◽

Computational Biology ◽

Treatment Response ◽

Research Funding ◽

Treatment Effectiveness ◽

Protein Network ◽

Response To Treatment ◽

Patient Specific ◽

Newly Diagnosed ◽

Predictive Values

Abstract Background: Multiple myeloma (MM) is an incurable heterogeneous hematological malignancy in which immune suppression and complex biology affect the disease and its response to treatment. Bortezomib (btz) and lenalidomide (len) alone or in combination with dexamethasone (dex) or other agents, are the predominant treatments for newly diagnosed and relapsed MM. Unfortunately, no precise method exists to predict disease response, making MM patient management difficult. Predicting treatment response would improve treatment effectiveness, and potentially reduce unnecessary treatment-related adverse events and health care costs. Aim: To determine the application of a genomics-informed predictive simulation model in MM patients treated with btz or len in combination with dex. Methods: Fourteen patients were selected from two datasets. Nine relapsed MM patients were identified from Washington University and 5 newly diagnosed MM patients were identified from the publicly accessible MMRF CoMMpass dataset. In all cases, whole exome sequencing and array CGH were performed. For each patient, every available genomic abnormality was entered into a computational biology program (Cellworks Group) that uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated protein pathways (Doudican, et al, J Transl Med, 2015). Digital drug simulations with HMAs were conducted by quantitatively measuring drug effect on a composite MDS disease inhibition score (i.e., cell proliferation, viability, and apoptosis). Clinically, patients received standard of care treatment and clinical responses were recorded. Predictive values were calculated based on comparisons of the computer predictions and actual clinical outcomes. Results: The models predicted that 9 patients would respond to combination treatment and 5 would not. All response predictions were properly matched to their clinical response, resulting in 100% PPV, NPV, sensitivity, specificity, and accuracy. Interestingly, the model predicted that 6 of the 9 responders would not have responded to btz or len alone; instead, response was predicted to combination therapy with dex. Conclusions: Computational biology for MM demonstrated high predictive value for response to btz and len with dex. The model may be useful in uncovering the mechanisms for treatment failure and highlight additional pathways that could be targeted to increase chemosensitivity. Disclosures Vij: Jazz: Consultancy; Shire: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Karyopharma: Consultancy. Vali:Cellworks Group: Employment. Abbasi:Cellworks: Employment. Kumar Singh:Cellworks: Employment. Kumar:Cellworks group: Employment. Gera:Cellworks: Employment.

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Monocytosis at Diagnosis Is Associated with Decreased Overall Survival in Patients with Newly Diagnosed Multiple Myeloma

Blood ◽

10.1182/blood-2020-141584 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 8-9

Author(s):

Camille V Edwards ◽

Cenk Yildirim ◽

Nathanael Fillmore ◽

Nikhil C. Munshi

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Overall Survival ◽

Prognostic Factors ◽

Peripheral Blood ◽

Categorical Variables ◽

Monocyte Count ◽

Private Company ◽

Absolute Increase ◽

Β2 Microglobulin

Introduction : Multiple myeloma (MM) is an incurable hematologic malignancy caused by the neoplastic proliferation of plasma cells within the bone marrow. The tumor microenvironment within the bone marrow consists of a diverse array of immune cells which regulate MM cell proliferation and survival. Specifically, tumor-associated macrophages (TAMs) derived from peripheral blood monocytes migrate to the bone marrow where they support MM cell growth and promote resistance to apoptosis. Several studies suggest that the amount of bone marrow TAMs directly correlates with disease activity and worse clinical outcomes in MM. Considering that peripheral blood absolute monocyte count (AMC) could reflect the burden of bone marrow TAMs, we sought to determine the prognostic significance of AMCs at diagnosis of MM. Methods: Using the integrated nationwide VA electronic health records and VA Corporate Data Warehouse, patients were identified by International Classification of Diseases (ICD) codes for MM. Patients were required to have at least 3 visits with an MM ICD code on separate days, have received at least one MM drug with the exception of corticosteroids after the date of diagnosis and have 2 or more absolute monocyte counts measured by automated or manual differential at separate visits within 18 months before and 7 days after MM diagnosis. We further confirmed the date of diagnosis using the VA Cancer Registry. We excluded patients with aplastic anemia, myelodysplastic syndrome, chronic myelomonocytic leukemia and other myeloproliferative neoplasms. In this cohort, monocytosis was defined based on the institution's cut-off as a sustained absolute increase in monocyte count of 0.8 (800/mm3) or greater with extreme monocytosis being greater than 1.25 (1250/mm3). Patients were stratified into three groups according to AMC at diagnosis, namely AMC <0.8, AMC 0.8 - 1.25 and AMC >1.25. To avoid extreme values significantly affecting the analysis, the Kruskal-Wallis test was used to compare continuous variables between the groups. Chi-squared tests were used to compare categorical variables. Hazard estimates for the prognostic analysis were obtained via adjusted Cox proportional hazard models. Overall survival was estimated using the Kaplan-Meier method and log-rank tests were used to compare the survival of each group. Results: A total of 5,265 patients with MM were included in the final analysis with a median follow up of 2.9 years (range 1.3 - 5.2). At diagnosis of MM, 39.3% of patients presented with monocytosis. Patients with monocytosis were younger and more likely to have abnormal levels of prognostic markers known to be associated with increased tumor burden and worse outcomes in MM. Notably, patients with monocytosis had higher median levels of β2-microglobulin and lactate dehydrogenase (p <0.001) and lower median albumin levels (p <0.001) than those without monocytosis. Patients with extreme monocytosis had the highest median β2-microglobulin (5.01, range 3.30 - 6.98, p <0.001) and the lowest median albumin levels (2.9, range 2.4 - 3.4, p <0.001) in the entire cohort. Patient characteristics according to AMC at diagnosis are shown in Table 1. On univariate analysis, the AMC predicted overall survival when analyzed as a trichotomized variable. The median overall survival was 4.6, 3.5 and 3.1 years in the AMC <0.8, AMC 0.8-1.25 and AMC >1.25 groups respectively (p <0.0001) [Figure 1]. When adjusting for known prognostic factors associated with outcomes in MM, the AMC was significantly associated with inferior overall survival (AMC 0.8 - 1.25 HR 1.230, p <0.008; AMC >1.25 HR of 1.312, p <0.003). Conclusion : The results of our study suggest that an elevated absolute monocyte count at MM diagnosis is associated with worse overall survival independent of known poor prognostic factors. The role of peripheral blood monocyte count as a surrogate biomarker for the state of the bone marrow microenvironment in MM warrants further in vitro, prospective studies. Disclosures Munshi: AbbVie: Consultancy; Amgen: Consultancy; Legend: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Karyopharm: Consultancy; Takeda: Consultancy; BMS: Consultancy.

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Bone Marrow Mobilization Of Endothelial Progenitor Cells Represents An Early Pathogenic Event During Multiple Myeloma Progression

Blood ◽

10.1182/blood.v122.21.680.680 ◽

2013 ◽

Vol 122 (21) ◽

pp. 680-680 ◽

Cited By ~ 3

Author(s):

Michele Moschetta ◽

Yuji Mishima ◽

Yosra Aljawai ◽

Ilyas Sahin ◽

Arianna Calcinotto ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Flow Cytometry ◽

Progenitor Cells ◽

Peripheral Blood ◽

Research Funding ◽

Advisory Board ◽

Scid Mice ◽

Healthy Controls ◽

M Spike

Abstract Background Increased bone marrow (BM) microvessel density (MVD) has been associated with progression of multiple myeloma (MM). Endothelial progenitor cells (EPCs) are circulating precursors with the capacity to differentiate into endothelial lineage cells through a process known as “vasculogenesis” thus contributing to vessel formation. The role of these cells in MM pathogenesis remains largely unexplored. We studied EPC BM mobilization in several MM mouse models (5TGM1, MM1S and Vk*MYC) during disease progression and quantified these cells in peripheral blood (PB) from patients at different stages of MM disease. Methods EPCs were quantified using flow cytometry (circulating CD34+ VEGFR2+ cells) in PB from mice injected intravenously (i.v.) with either murine MM 5TGM1-turboRFP+ cells or human MM1S-GFP+/luc+ cells. Circulating EPCs were also enumerated in PB from mice previously transplanted with BM from SCID/GFP mice (GFP-BM SCID mice) after the i.v. injection of 5TGM1-turboRFP+ cells as circulating GFP+ CD34+ VEGFR2+ cells. Peripheral blood samples were obtained from transgenic Vk*MYC mice affected by smoldering (s) MM (M-spike less than 6% of total protein on SPEP); active (a) MM (M-spike higher than 6% of total protein on SPEP); or healthy syngeneic mice, and examined for EPC levels through flow-cytometry (circulating CD34+ VEGFR2+ cells). Finally, the level of EPCs was evaluated in PB from healthy controls, smoldering (s) MM patients, in remission (r) and active (a) MM patients by using flow-cytometry (CD34+VEGFR2+ cells) and in vitro by performing endothelial colony forming assays [endothelial cells colony forming units (EC-CFUs) and endothelial colony forming cells (ECFCs)]. Results An increase in EPCs was evident starting one week after i.v. injection of tumor cells in both murine 5TGM1 and human MM1S orthotopic models. Compared to control mice, this EPC increase became significant (P<.05) two week after injection of 5TGM1 cells (8.2 times increased, p=0.04) and three weeks after MM1S cell injection (4.1 times increased, p=0.04). The baseline percentage of CD34+VEGFR2+ cells in normal SCID mice, and of GFP+CD34+VEGFR2+ cells in GFP-BM SCID mice was comparable (0.0176% and 0.0156% of PBMCs respectively). A significant increase of EPCs to 0.059% (p=0.04) and 0.049% (p=0.02) was observed in SCID or SCID-GFP-BM mice after 2 week of tumor engraftment of 5TGM1-turboRFP+ murine myeloma cells. This, suggest that the origin of EPCs is from the bone marrow and that the number of EPC increases with MM progression. In transgenic Vk*MYC mice, a significant increase (P<.05) of circulating CD34+VEGFR2+ cells was observed in both sMM (2.88%) and aMM (1.706%) compared to healthy syngenic mice (0.38%). This further suggests that an increase of vasculogenic activity takes place at the early stage of MM development and persists during MM progression. We next corroborated our findings in MM patients. Smoldering MM patients as well as in remission and active MM patients presented in PB a significant increase in circulating CD34+VEGFR2+ cells compared to healthy donors (0.039% and 0.042% and 0.078% respectively vs 0.005%, P<.05) Peripheral blood mononuclear cells (PBMCs) from sMM, rMM and aMM showed an increase ability to form both EC-CFUs (10.05 and 12.85 and 16.05 respectively vs 6.4 colonies per 20x106 total PBMCs) and ECFCs compared to healthy controls (0.75 and 0.51 and 0.75 respectively compared to 0.33 colonies per 15 ml blood). Conclusion Together, these results demonstrate that vasculogenesis may represent an early pathogenic event driving MM progression. Vasculogenesis mediated by BM-derived EPC could contribute to the “angiogenic switch” described during the transition MGUS/sMM to overt MM. Therefore, EPCs represent a new cell target in MM that could potentially halt MM progression. Disclosures: Ghobrial: Onyx: Advisoryboard Other; BMS: Advisory board, Advisory board Other, Research Funding; Noxxon: Research Funding; Sanofi: Research Funding.

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The Senescence-Associated Secretory Phenotype In Multiple Myeloma

Blood ◽

10.1182/blood.v122.21.5357.5357 ◽

2013 ◽

Vol 122 (21) ◽

pp. 5357-5357

Author(s):

Tanya M Wildes ◽

Jacob Paasch ◽

Mark A. Fiala ◽

Ling Chen ◽

Ravi Vij ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Growth Factor ◽

Blood Serum ◽

Peripheral Blood ◽

Research Funding ◽

Bone Marrow Aspirate ◽

Intercellular Adhesion Molecule ◽

Future Research ◽

Secretory Phenotype

Abstract Introduction The incidence of multiple myeloma (MM) increases with age, yet some cytogenetic changes are actually more common in younger patients with MM (Avet-Loiseau J Clin Oncol 2013). This suggests that a mechanism other than chromosomal changes underlies the increased incidence with age. Senescent cells secrete a number of proinflammatory cytokines, chemokines, growth factors and proteases resulting in the senescence-associated secretory phenotype (SASP), which can promote tumor growth. Preclinical data suggests that myeloma bone marrow stromal cells express the SASP (Andre PLOS ONE 2013). We hypothesized that SASP factors correlate with age in patients with MM. Methods Peripheral blood serum and matched bone marrow aspirate plasma from patients with multiple myeloma were evaluated for selected factors associated with the SASP using quantitative multiplex immunoassay (Rules Based Medicine, Austin TX USA). SASP factors with a known role in MM [interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-15 (IL-15), granulocyte-macrophage colony-stimulating factor (GMCSF), intercellular adhesion molecule 1(ICAM1), osteoprotegerin (OPG), hepatocyte growth factor (HGF), insulin-like growth factor-binding protein(IGFBP-1), interleukin-1 beta (IL1b), monocyte chemotactic protein 1(MCP-1), macrophage inflammatory protein-1 alpha(MIP-1a), angiogenin, leptin, vascular endothelial growth factor receptor 1(VEGFR1) and stem cell factor(SCF)] were selected. The relationship between age and SASP factors were analyzed using Kendall tau rank correlation coefficient. Results Samples from 25 patients (each with peripheral blood serum and matched bone marrow aspirate plasma) were analyzed. The median age was 62 (range 47 - 74). Disease states were as follows: 36% newly diagnosed/untreated, 24% pretransplant and 40% relapsed. ISS stage included 40% stage I, 28% stage II and 32% stage III. Three of the selected SASP factors in the peripheral blood correlated with age: IL-8 (Kendall Tau 0.334, p=0.027), OPG (Kendall Tau 0.289, p=0.046) and MCP-1 (Kendall Tau 0.332, p=0.022). No SASP factors tested in the bone marrow plasma were significantly correlated with age. Conclusions We demonstrated age-associated differences in the SASP factors IL-8, OPG and MCP-1 in the peripheral blood of myeloma patients. Future research will examine differences between patients with myeloma and age-matched controls without cancer. Disclosures: Vij: Celgene : Honoraria, Research Funding, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria, Research Funding, Speakers Bureau. Stockerl-Goldstein:Celgene : Speakers Bureau; Celgene : Speakers Bureau; Millennium: Speakers Bureau; Millennium: Speakers Bureau.

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Molecular Predictors of Outcome and Drug Response in Multiple Myeloma: An Interim Analysis of the Mmrf CoMMpass Study

Blood ◽

10.1182/blood.v128.22.194.194 ◽

2016 ◽

Vol 128 (22) ◽

pp. 194-194 ◽

Cited By ~ 6

Author(s):

Jonathan J Keats ◽

Gil Speyer ◽

Austin Christofferson ◽

Christophe Legendre ◽

Jessica Aldrich ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Dna Repair ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Peripheral Blood ◽

Interim Analysis ◽

Research Funding ◽

Whole Genome ◽

Sequencing Data

Abstract The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) is a longitudinal study of 1147 patients with newly-diagnosed multiple myeloma from clinical sites in the United States, Canada, Spain, and Italy. Each patient receives a treatment regimen containing a proteasome inhibitor, immunomodulatory agent, or both. Clinical parameters are collected at study enrollment and every three months through the eight-year observation period. To identify molecular determinants of clinical outcome each baseline and progression tumor specimen is characterized using Whole Genome Sequencing, Exome Sequencing, and RNA sequencing. Data available as of January 1, 2016 is included in this first formal interim analysis, which includes 995 enrolled patients of whom 851 are molecularly characterized. This cohort of patients includes 74 patients with at least two sequential samples, plus 15 patients with characterized tumor samples from the bone marrow and peripheral blood. The median follow-up of the cohort is 66 weeks, which identified a median PFS of 36 months for the cohort. The median OS was not reached but 76% are still alive at 3 years. Although the age at enrollment by gender is uniform, there is a significant difference in PFS and OS, with males performing worse than females, p=0.001 and p=0.0004 respectively. Analysis of the exome sequencing data from the 746 baseline BM localized tumors identified a median of 122 non-immunoglobulin related mutations per patient, with an interquartile range of 96-155. There is a group of highly mutated (>481 mutations [mean+1SD]) patients who frequently have MAF family translocations (66%) and/or mutations in the DNA repair genes MSH2, MSH3, MSH4, MSH6, or ATM (38%). Across the cohort 21/53 of the DNA repair gene mutations reside in these 21 patients compared to 14/47 MAF family translocations. Analysis of the somatic mutations identified 20 significant genes, which are recurrently mutated and the mutated allele is detectably expressed; BRAF, CYLD, DIS3, FAM46C, FCF1, FGFR3, FUBP1, KRAS, MAX, NFKBIA, NRAS, PRKD2, RASA2, RB1, SAMHD1, SP140, TGDS, TP53, TRAF2, and TRAF3. Integration of the copy number data and the mutation data identified an association between TP53 deletion and mutation, suggesting many patients present with homozygous loss of TP53. Patients with one or two functional TP53 alleles had similar PFS and OS but the patients with zero functional alleles had a significantly reduced OS (p<0.05). Therefore, the existing association between 17p deletion and outcome is driven by the subpopulation of patients with bi-allelic TP53 loss. Analysis of the whole genome sequencing data available from the 719 baseline BM localized tumors for immunoglobulin translocations identified the expected canonical translocations along with events targeting MYC in 14.6% of patients. Unlike the canonical translocations the MYC translocations are enriched in hyperdiploid tumors (22.3%) and often involve light chain loci, particularly the lambda locus. Within the hyperdiploid patients, those with a MYC translocation have a reduced PFS. To identify molecular subtypes we performed unsupervised clustering using a consensus clustering approach on the 613 baseline BM tumors with RNA sequencing data, which identified 12 distinct subtypes. This analysis confirmed previous studies identifing distinct subtypes associated with WHSC1, MAF/MAFA/MAFB translocations and two subtypes associated with CCND1/CCND2/CCND3 subtypes, which can be separated by CD20 expression. Five subtypes are associated with hyperdiploid myeloma, one group is nearly devoid of chromosome 11 gains while this event is ubiquitous in the remaining hyperdiploid groups. The genomic profiles of the paired tumors isolated from the peripheral blood and bone marrow share 87% of the observed events with unique events being more common in the PB compartment suggesting the PB compartments are often derived from a closely related progenitor clone of the bulk BM tumor. Applying our bayesian clonal analysis method to the serial samples identified multiple clones in all patients with some showing no changes in clonal populations while the majority show significant shifts in clonal burden. These analyses have identified tumor initiating mutations and new subtypes of myeloma, which are associated with distinct molecular events and clinical outcomes. Disclosures Niesvizky: Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy, Research Funding, Speakers Bureau; Onyx: Consultancy, Research Funding, Speakers Bureau. Wolf:Takeda: Honoraria; Telomere Diagnostics: Consultancy; Amgen: Honoraria; Celgene: Honoraria; Pharmacyclics: Honoraria. Lonial:Onyx: Consultancy; BMS: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Janssen: Consultancy; Merck: Consultancy; Onyx: Consultancy; Celgene: Consultancy; Millenium: Consultancy; Novartis: Consultancy; BMS: Consultancy; Celgene: Consultancy.

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