Arendt, Bonnie K.

Abstract The loss of skeletal muscle mass during aging is a significant health concern linked to adverse outcomes in older individuals. Understanding the molecular basis of age‐related muscle loss is crucial for developing strategies to combat this debilitating condition. Long noncoding RNAs (lncRNAs) are a largely uncharacterized class of biomolecules that have been implicated in cellular homeostasis and dysfunction across a many tissues and cell types. To identify lncRNAs that might contribute to skeletal muscle aging, we screened for lncRNAs whose expression was altered in vastus lateralis muscle from older compared to young adults. We identified FRAIL1 as an aging‐induced lncRNA with high abundance in human skeletal muscle. In healthy young and older adults, skeletal muscle FRAIL1 was increased with age in conjunction with lower muscle function. Forced expression of FRAIL1 in mouse tibialis anterior muscle elicits a dose‐dependent reduction in skeletal muscle fiber size that is independent of changes in muscle fiber type. Furthermore, this reduction in muscle size is dependent on an intact region of FRAIL1 that is highly conserved across non‐human primates. Unbiased transcriptional and proteomic profiling of the effects of FRAIL1 expression in mouse skeletal muscle revealed widespread changes in mRNA and protein abundance that recapitulate age‐related changes in pathways and processes that are known to be altered in aging skeletal muscle. Taken together, these findings shed light on the intricate molecular mechanisms underlying skeletal muscle aging and implicate FRAIL1 in age‐related skeletal muscle phenotypes.

Abstract Insulin-like growth factors (IGF-I, IGF-II) have long been recognized as important mitogens in many types of malignancies. Because the role of IGFs in growth control of myeloma cells has not been extensively examined, we have used a panel of IL-6-responsive myeloma cell lines to address this issue. Initial studies demonstrated that IGF-I and IGF-II significantly enhanced DNA synthesis by each of the four cell lines, even when assayed in the absence of IL-6. The specificity of the IGF response was confirmed using an IGF-I receptor Ab, and additional studies demonstrated that IGF responsiveness did not result from induction of autocrine IL-6 expression. When IL-6 responsiveness was assayed, three of four cell lines synthesized DNA in response to IL-6 alone; however, the magnitude of responsiveness was greatly enhanced by addition of IGFs. Similar results were obtained when proliferation and cell cycle progression were analyzed. By contrast, the KP-6 cell line was responsive to IL-6 only when IGF was present. Finally, we analyzed the effects of IGF-I on normal B lymphocytes. IGF, however, did not stimulate B cell DNA synthesis, suggesting that IGF responsiveness may represent a key difference between normal and malignant B cells. In summary, these studies suggest that IGFs may play an important role in multiple myeloma by virtue of their ability to directly stimulate tumor cell growth as well as modulate the magnitude of IL-6-driven growth.

8009 Background: Measuring response among patients with multiple myeloma is essential for the care of patients. Deeper responses have been associated with better progression free survival (PFS) and overall survival (OS). Serum (SIFE) and urine immunofixation are the currently used markers for biochemical documentation of CR after which marrow is tested for plasma cell clearance. Next generation flow cytometry and sequencing are used to document the presence of minimal residual disease (MRD). Mass spectrometry of blood by MALDI (Mass-Fix) is a new simple, inexpensive, sensitive, and specific means of detecting monoclonal immunoglobulins. To better test the hypothesis that Mass-Fix is superior to existing methodologies to predict for survival outcomes—especially SIFE-- samples from the STAMINA trial (NCT01109004), a trial comparing 3 transplant approaches among patients who have already received induction, were employed. Methods: Five-hundred and seventy-five patients were included. Samples from enrollment post-induction (post-I) and 1-year post enrollment (1YR) were tested when available. Four response parameters were assessed univariately: Mass-Fix, SIFE, complete response, and MRD by next generation flow cytometry. Mass spectrometry spectra were evaluated in a blinded fashion. Complete response was according to the 2006 International Myeloma Working Group criteria. Multivariate Cox proportional hazard models using stepwise regression were developed to explore the independent effect of the different response parameters on PFS and OS and interactions with other risk factors. Results: Of the 4 response measures, only MRD and Mass-Fix predicted for PFS and OS at multiple testing points on multivariate analyses (Table). Of the 4 post-I measurements, only MRD predicted for PFS; however, Mass-Fix was the only post-I measurement to predict for OS. Of all the 1-year measures, both 1YR Mass-Fix and 1YR MRD positivity predicted for inferior PFS and OS. In models including MRD and Mass-Fix, SIFE and CR were not prognostic for PFS or OS. Conclusions: Mass-Fix is a powerful means to track monoclonal proteins. The full utility of Mass-Fix was not exploited given the absence of a diagnostic sample and the fact that only serum (and not urine) was tested. Despite these limitations, it performed well at pre-induction and at 1 year. Mass-Fix provides a convenient and non-invasive means of predicting for myeloma outcomes. Clinical trial information: NCT01109004. [Table: see text]

SummaryMeasurable residual disease (MRD) assessment by marrow‐based next‐generation flow cytometry (NGF) following autologous stem cell transplantation (ASCT) may lead to false‐negative results due to patchy marrow involvement and extramedullary disease in patients with multiple myeloma. We assessed the value of simultaneous MRD evaluation with NGF and serum matrix‐assisted laser desorption ionization time‐of‐flight mass spectrometry (MASS‐FIX). Of all 61 complete responders who were NGF‐negative for MRD, around day‐100 post ASCT, 59% were MASS‐FIX‐positive. At median follow‐up of 26 months, 69% of MASS‐FIX(+)/NGF(−) patients were alive and progression‐free versus 96% of MASS‐FIX(‐)/NGF(−) patients, P = 0·02. MASS‐FIX, a simple peripheral blood‐based assay complements marrow‐based NGF to accurately prognosticate patients with myeloma.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX has advantages including increased sensitivity, specificity, and the ability to distinguish therapeutic monoclonal antibodies. Herein, we report the laboratory characteristics and distribution of diagnoses of patients tested clinically at Mayo Clinic. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. We identified 9195 unique patients with MASS-FIX performed between 7/24/2018 and 3/6/2020. Seven-thousand nine hundred and forty-six patients provided consent for study enrollment, and 7689 had data available on index diagnosis. Given considerable variability in the interpretation of diagnostic criteria for light chain (LC) MGUS, patients with this diagnosis (1360, 18%) were excluded. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). Results: The final cohort consisted of 4118 patients with a positive MASS-FIX and 2211 patients with a negative MASS-FIX, all in the setting of underlying PCDs. Figure 1 illustrates the numbers and percentages of patients who are MASS-FIX positive versus MASS-FIX negative by diagnosis. MGUS and multiple myeloma (MM) were the most common diagnoses overall, and both were more common in the MASS-FIX positive cohort. More than 90% of patients with Waldenstrom's macroglobulinemia (WM), smoldering WM, smoldering MM, and cold agglutinin disease were positive by MASS-FIX. For MASS-FIX positive patients, IgG isotype was identified in 2575 patients (63%), IgA in 703 (17%) and IgM in 710 (17%). Bence Jones proteinemia was identified in 283 patients (7%) with lambda restriction being the most common (57%). 3625 patients (88%) had a monoclonal pattern, 228 patients (6%) had a bi-clonal pattern, and 7 (<1%) had a tri-clonal pattern. The majority of patients (58%) were kappa LC restricted by MASS-FIX, 222 (5%) had N-glycosylated LC, and 2 patients (<1%) had a heavy chain with no light chain. Conclusions: This single institution experience illustrates the practicality of MASS-FIX in detecting and following monoclonal proteins for a wide range of PCDs in a tertiary center. In this cohort, the percentage of patients who were MASS-FIX positive varied by diagnosis, reflecting cross sectional sampling of patients throughout their disease course. Disclosures Gertz: Research to Practice: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Johnson and Johnson: Speakers Bureau; Sanofi: Other; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Proclara: Other; DAVA oncology: Speakers Bureau; Celgene: Other; Teva: Speakers Bureau; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau. Kumar:AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Adaptive Biotechnologies: Consultancy; Novartis: Research Funding; MedImmune: Research Funding; Sanofi: Research Funding; Tenebio: Other, Research Funding; Cellectar: Other; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Kapoor:Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Millenium: Consultancy. Lin:Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cells: Consultancy; Takeda: Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced standard gel-based immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX can readily identify N-glycosylation of involved light chains (LC N-glycosylation) by its unique, polytypic spectral pattern. LC N-glycosylation is identified more commonly in light chain amyloidosis (AL) than other plasma cell disorders (PCDs), and is associated with an increased risk of progression from MGUS to both AL and other PCDs (Dispenzieri et. al. Leukemia 2020). Herein, we report the mass spectral characteristics and distribution of diagnoses among 222 patients with LC N-glycosylation detected during a 20 month period in our clinical lab. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. 9195 unique patients had MASS-FIX performed from 7/24/2018 to 03/06/2020. Inclusion criteria for this retrospective study included: 1) consent for record review; 2) a monoclonal protein identified on MASS-FIX; 3) an underlying PCD. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). The final positive cohort consisted of 4118 patients with definitive monoclonal proteins on MASS-FIX. Results: Two-hundred and twenty-two (5%) of the 4118 patients with a positive MASS-FIX had LC N-glycosylation. 202 patients (91%) had FLC assays performed. Of these, 110 (54%) were kappa LC restricted, 22 (11%) were lambda restricted, and 70 (35%) were normal. A quantifiable M-spike was identified in 110 patients (85%) of 129 patients who had serum protein electrophoresis performed. By MASS-FIX, 139 patients (63%) had an IgG isotype, 18 (8%) an IgA, and 55 (25%) an IgM. Two of these patients had a bi-clonal pattern in which both IgG kappa and IgM kappa LCs were N-glycosylated. 12 patients (5%) had monoclonal light chains with no corresponding heavy chain. Overall, 173 (78%) of 222 patients were kappa LC restricted and 44 (22%) were lambda. 189 patients (85%) had a monoclonal pattern, 18 (8%) had a bi-clonal pattern, and 3 (1%) had a tri-clonal pattern. The most common PCD diagnoses for the 222 patients with LC N-glycosylation were MGUS (45%), multiple myeloma (MM) (31%), and immunoglobulin light chain amyloidosis (AL) (8%). The percentage of MASS-FIX positive patients with LC N-glycosylation by diagnosis, stratified by kappa and lambda LC restriction, is illustrated in Figure 1. Cold agglutinin disease (CAD) had the highest relative percentage of patients with LC N-glycosylation, regardless of LC restriction. Eighteen AL patients (5%) had LC N-glycosylation; the percentage was higher in kappa restricted (13%) than lambda restricted AL patients (2%). Of note, LC N-glycosylation was not detected in patients with plasma cell leukemia, non-AL amyloidosis with associated MGUS, POEMS Syndrome or Castleman's Disease in this cross sectional sampling of patients. Conclusions: This retrospective study demonstrates that 5% of patients in a routine clinical setting with positive MASS-FIX have glycosylated LCs. Consistent with prior observations, CAD had the highest relative percentage of LC N-glycosylated patients. The percentage of AL patients with LC N-glycosylation in this cohort is lower than previously reported for newly diagnosed AL patients (Kumar et. al. Leukemia 2019), which is not surprising given that the current cohort study is a cross sectional evaluation of patients at various stages of diagnosis and treatment rather than a prevalence study. Further study will be done to exclude the presence of latent AL in patients with N-glycosylated LC and diagnoses of MGUS, SMM, MM, and Waldenstrom's macroglobulinemia. Disclosures Gertz: Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Sanofi: Other; Research to Practice: Other; Celgene: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other. Kumar:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other. Kapoor:Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy. Dingli:Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy. Lin:Janssen: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Alnylam: Research Funding.

Abstract One of the major mechanisms by which the immune system combats unpredictable foreign pathogens is to produce highly specific and effective antibodies by B cells. Somatic hypermutation (SHM) and class switch recombination (CSR) are two key events required for the production of highly specific and effective antibodies. Both SHM and CSR occur in the germinal center (GC), and are mediated by a common enzyme, activation-induced cytidine deaminase (AID) that specifically mutates the variable regions (IgV) and switch regions (IgS) of immunoglobulin genes by converting cytidines to uridines. It has been shown that in addition to the central deaminase domain, an N-terminal domain is essential to target SHM to the IgV region whereas a C-terminal domain is necessary for Ig CSR. Given its mutagenic nature, it has been postulated that AID may play causative roles in B cell lymphomagenesis. Consistent with this notion, AID is expressed and alternatively spliced in B cell tumors such as B-cell chronic lymphocytic leukemia (B-CLL) and non-Hodgkin’s lymphoma (NHL). However, it remains unclear whether post-GC malignant B cell AID expression and alternative splicing is a consequence of B cell transformation and/or is required to maintain growth and/or malignant B-cell survival, or whether post-GC AID expression and alternative splicing may also occur in normal B cells. To discriminate between these two possibilities, we analyzed AID expression and splicing in normal human B cells. Our data demonstrate that human tonsillar B cells prominently express the full-length AID transcript, and of interest, also express all four alternative transcripts that have been previously described in B-CLL and NHL B cells. To determine if all normal B cells express all of the AID transcripts, we performed limiting dilution of tonsillar B cells and used RT-PCR to detect AID expression. We surprisingly discovered that AID splicing variants are singly expressed by individual B-cells. To address the functional significance of each splicing variant, we considered the possibility that B cells expressing the alternative transcripts may be by-products of the normal GC reaction and are eliminated prior to GC exit. Conversely those B cells may contribute to the memory B cell pool if those AID variants are functional. Therefore, we examined AID expression and splicing in memory B cells using a more sensitive nested PCR approach. Our data show that AID is indeed expressed in peripheral blood memory cells but not in naïve B cells. Moreover, at least one splicing variant was expressed at levels comparable to the full-length AID transcript. Using limiting dilution, we again found that the full-length and alternatively spliced AID transcripts are singly expressed by individual memory B cells. Our results suggest that AID expression beyond the GC stage may play a role in sustaining selection pressure. Since the AID domains specific for SHM and CSR are encoded by different exons, we hypothesize that those variants may function differentially in SHM and CSR and this concept is under current study. Since each B cell only expressed one AID transcript, our data strongly suggest that SHM and CSR are coordinated in a stepwise process by generation of alternative AID splice variants that exhibit selective activity thereby allowing fine-tuning of humoral immunity.

Abstract Our understanding of the molecular pathogenesis of myeloma is largely based on observations made from the available human myeloma cell lines. Cell lines have proved invaluable to the characterization of the known immunoglobulin translocations, recurrent deletions and amplifications, and the development of novel therapies. However, it has long been perceived that the cell lines are not representative of patient samples as they often have complex genomes and not even a single cell line has been described with a typical hyperdiploid karyotype. The absence of a hyperdiploid model system is significant as conventional cytogenetic studies of myeloma patient samples has established that patients can be almost evenly split into two broad categories of hyperdiploid and non-hyperdiploid based on their chromosome counts, with the hyperdiploid patients having recurrent trisomies of chromosomes 3, 5, 7, 9, 11, 15, 19, and 21 plus periodic gains of 1q, 18, 20 and loss of 13. Though all of the cell lines have abnormal genomes none of the previously tested cell lines had the characteristic pattern of chromosomal gains seen in hyperdiploid patients and the majority have immunoglobulin translocations, which are more commonly associated with non-hyperdiploid patients. These observations have provided the basis for the assumption that the cell lines are only representative of the non-hyperdiploid patient population. Furthermore, even though very few cell lines have been directly compared to the patient sample from which they were derived it is widely believed that the cell line genomes are unstable and have diverged significantly from the patient samples from which they were derived. Therefore, we decided to compare patient-cell line pairs available from the Mayo Clinic using Agilent 244k array-based comparative genomic hybridization (aCGH) and Affymetrix U133Plus2.0 gene expression profiling and repeated the analysis of our previously studied 46 cell lines on the higher resolution Agilent 244k platform. To date we have completed the analysis of four patient cell line pairs (ALMC-1; ALMC-2; KP-6; KAS-6/1, KAS-6/2) and have repeated our entire cell line panel on the higher resolution array. Four additional patient-cell line pairs (DP-6, JMW-1, SPMC, and VPC-6) are currently being completed. The first compelling observation from this study was that the patient sample from which KP-6 was derived is a perfect match to the characteristic hyperdiploid karyotype with a CGH defined karyotype (51, XY, −1p, +1q, +3, +7, +11, −13, +15, −16q, −17p, +19, +21). The KP-6 cell line showed a similar aCGH defined karyotype (50, X, −Y, −1p, +1q, +3q, +7, −8p, +9p, +11, +15, −16q, −17p, +17q, +19, +21) with the most significant changes occurring on the trisomic chromosomes as many transitioned from trisomies to single arm gains. Therefore, KP-6 appears to be the first myeloma cell line derived from a patient with a characteristic hyperdiploid phenotype. The ALMC patient cell line series is comprised of patient samples at diagnosis and relapse and cell lines derived from both stages. The two patient-cell line pairs only show five and two aCGH definable changes, respectively. In comparison the two matched patient sample pairs have diverged at six regions in the genome. The KAS patient-cell line series is actually two cell lines derived from pre- (KAS-6/1) and post-transplant (KAS-6/2) samples and the KAS-6/2 matching post-transplant patient sample. The comparison of the paired patient sample and derived cell line shows only four aCGH detectable changes. Similarly, there are only three changes between the KAS-6/1 cell line and post-transplant patient sample suggesting that the evolution of this tumor in both the patient and tissue culture is very limited. In conclusion, this study has identified the first bona fide hyperdiploid cell line, thereby providing a valuable investigative tool to better understand the biological differences between the two broad genetic categories of myeloma. Moreover, we demonstrate that the genomes of myeloma cell lines are typically stable and highly representative of the patient sample that was placed into culture to establish the cell line thereby validating their use in the study of this disease.

Abstract Malignant plasma cell (PC) disorders are clonal diseases based on their immunoglobulin variable region sequence signature. However, intratumor phenotypic, genetic, and morphologic heterogeneity is often observed, fueling the notion that a subpopulation of the malignant PC clone may have extensive self-renewal properties whereas others may not. Little information exists regarding the relationship between these putative tumor subpopulations that is instrumental to our understanding of the growth, progression and therapeutic targeting of PC disorders. We recently described establishment of two novel cell lines from one patient initially diagnosed with primary amyloidosis (ALMC-1), who eventually progressed to a combination of AL and symptomatic multiple myeloma (MM; ALMC-2). Although both cell lines are clonally related, they exhibit a number of intriguing differences, including a marked variability in their makeup of mononuclear (MoN) and multinuclear cells (2 − >10 nuclei; MuN). The ALMC-1 cell line consistently displays a much larger fraction of MuN cells (~50%) than the ALMC-2 cell line (~20%). By contrast, the growth rate of the ALMC-2 cells is significantly higher than ALMC-1 cells suggesting an inverse relationship between growth rate and fraction of MuN cells. It has been demonstrated that MoN plasmablastic morphology is a predictor of poor survival in MM, however the clinical significance of MuN PCs, which are frequently observed in bone marrow biopsies, has yet to be determined. We therefore used the ALMC-1 and ALMC-2 cell lines to begin to test the hypothesis that the MoN fraction in both cell lines contains cells with extensive self-renewal properties whereas the MuN cells are no longer capable of cell division. The central questions become by what mechanism are MuN PCs generated and how are MoN PCs maintained? Two hypotheses that can explain the dual persistence of both types of cells are: random cell fusion; regulated or sporadic cell division of MoN cells into 2 daughter cells, one of which divides normally and the other one fails to undergo cytokinesis. To address the first possibility, each cell line was transfected with GFP or YFP. Single positive (GFP or YFP) cells were then mixed and cocultured for assessing the frequency of dual positive cells by flow cytometry at various time points. However, studies to date suggest this mechanism does not occur. To begin to address the second possibility and determine whether extrinsic factors, e.g., cytokines, may regulate the rate of generation of MuN PCs, we cultured both cell lines +/− IL-6 and IGF-I and assessed numbers of MoN and MuN PCs. Initial analyses suggest that IL-6, but not IGF-I, increases the proportion of MoN PCs in both cell lines. To address the hypothesis that MuN PCs are no longer capable of growth, cells were labeled with bromodeoxyuridine (BrDU) to assess the capability of MuN cells to synthesize DNA. We observed that MuN PCs incorporating BrDU did so uniformly in each nucleus present in the cell. We then assessed the ability of cell division of MuN cells by quantitating normal vs abnormal metaphases in both cell lines and observed that >90% of metaphases were present in MoN PCs, suggesting that MoN PCs largely give rise to MuN PCs and the latter are likely compromised in cytokinesis. As centrosomes play a critical role in regulating cell division and centrosome abnormalities have been noted in MM by others, we next used gamma-tubulin immunofluorescence to detect centrosomes. MoN PCs exhibited uniformly normal centrosome numbers and positioning while MuN PCs showed clear centrosomal abnormalities including accumulation of centrosomes, centrosome clustering, and multiple directional centrosome polarization, suggesting a mechanism by which the MuN cells may be generated. In summary, our data suggest that MuN PCs lack growth potential and that intrinsic and/or extrinsic factors may drive accumulation of these cells. These observations support the possibility that patients with a larger proportion of MuN PCs may have differences in clinical outcome from those patients with largely MoN PCs. To test this, we have begun hematopathological analysis of a large series of patients diagnosed with various plasma cell disorders. Knowledge of the signals that regulate the balance between MoN and MuN cells could lend itself toward identification of therapeutic modalities that may maximize differentiation of tumor cells into end-stage cells.