scholarly journals CHARACTERIZATION OF MULTIPLE MYELOMA PATIENTS THROUGH FLOW CYTOMETRY AND CYTOGENETIC STUDIES 2013 – 2018

2020 ◽  
Vol 42 ◽  
pp. 254
Author(s):  
J.M. Gil-Ramos ◽  
L.M. Martínez ◽  
L. López ◽  
L.I. Jaramillo ◽  
J.D. Villegas ◽  
...  
Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3966-3966
Author(s):  
David K Edwards ◽  
Venkata D Yellapantula ◽  
Kristi Allen ◽  
Wen Yu Wong ◽  
Jessica Albanese ◽  
...  

Abstract Abstract 3966 The drug treatments currently available for multiple myeloma patients are dramatic improvements over historical regimens, stopping or slowing cancer growth in 80–90% of patients and leading to complete remission in approximately 40% of patients. Many of the new treatment regimens include “novel agents” in combination with dexamethasone, one of the most effective agents used to treat myeloma. The direct mechanism by which dexamethasone works in myeloma is not well characterized but it is assumed that it activates glucocorticoid receptors which results in gene expression changes that promote apoptosis in lymphoid cells. However, often the disease becomes resistant to dexamethasone, and the mechanism for this resistance is not entirely known. To study the mechanism of resistance, two isogenic cell lines, MM.1R and MM.1S, were independently created from the parental cell line MM.1 to represent models of resistance and sensitivity, respectively, to dexamethasone. This model system was created by Steve Rosen and colleagues in the 1990s and was recently deposited in ATCC. Previous studies have demonstrated differential expression of the glucocorticoid receptor NR3C1 but have not precisely identified the genetic difference between MM.1R and MM.1S across the whole genome. To better understand the mechanism behind the differences in drug sensitivity between these isogenic cell lines, we performed extensive characterization of MM.1R and MM.1S. We purchased both lines from ATCC and analyzed each using flow cytometry, CGH, CGH-SNP, mRNA sequencing, and exome sequencing. First, we broadly examined both cell lines, demonstrating a 300,000-fold difference in IC50 of MM.1R to MM.1S after 6 days of dexamethasone treatment. No significant ploidy difference was found between the two lines by flow cytometry analysis. Our CGH results identified 4 copy number differences unique to MM.1R (chr2:p37.1–37.3 deletion, chr4:q32.3–33 deletion, chr5:31.3 deletion, and chr7:q36.3 amplification), the third of which suggested a possible homozygous deletion within NR3C1. To confirm this deletion, we designed primer sets at ∼1kb intervals spanning the entire NR3C1 gene and performed PCR on MM.1R and MM.1S. Our results indicate the presence of a ∼5–8kb deletion of NR3C1 in MM.1R. Additionally, we analyzed our mRNA sequencing data using TopHat-Fusion and identified an inverted fusion between NR3C1 and ARHGAP26, which we confirmed through PCR amplification and Sanger sequencing. From mRNA sequencing, we identified 63 genes with differential expression between MM.1R and MM.1S (FPKM > 5 in either cell line and greater than fourfold change between them). These results demonstrate a reduction in expression of NR3C1 caused by the two independent deletions identified by CGH. The gene with the larges fold change was MGST1, which is associated with drug resistance and thus may be associated with dexamethasone resistance in this model system based on its expression profile. We analyzed our exome sequencing results for high-confidence (called by both SAMtools and GATK) non-synonymous mutations not present in the 1000 Genomes Project and filtered them for expression (FPKM > 5). We identified 218 mutations in MM.1R, 208 mutations which were also expressed in MM.1S and 10 mutations which were not expressed in MM.1S. The 10 genes with these mutations—PDIA5, TCERG1, RANBP9, MMS22L, PHF19, RNMTL1, AURKB, ERN1, GPCPD1, PIGT—present potential additional contributors to dexamethasone resistance. Specifically, for example, overexpression of RANBPM (the protein from RANBP9) results in increased glucocorticoid activity, suggesting that it may work in concert with NR3C1 to mediate the effects of dexamethasone. Ultimately, our results indicate that, unlike previous assumptions, there are several contributors to dexamethasone resistance in this model system and likely even more in the general patient populations, not just differential expression of NR3C1. Furthermore, we have discovered that this differential expression is due to biallelic inactivation of NR3C1 in MM.1R. Future studies will test the relative contribution of each factor to the differential sensitivity to dexamethasone observed in this model system and a broader understanding of this problem in multiple myeloma. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1906-1906
Author(s):  
Bruno Paiva ◽  
Lucía López-Corral ◽  
María-Belén Vidriales ◽  
Luis Ignacio Sánchez Abarca ◽  
Miguel T. Hernandez ◽  
...  

Abstract Abstract 1906 Lenalidomide is an immunomodulatory agent that interacts with different components of the immune system by altering cytokine production, regulating T cells and increasing NK cell cytotoxicity. In multiple myeloma (MM), lenalidomide is approved for use in combination with dexamethasone in patients who have received at least one prior therapy. Recent observations have shown that dexamethasone enhances the anti-myeloma effect of lenalidomide; however, dexamethasone may also antagonize the immunomodulatory properties of lenalidomide. In the present study we evaluated by multiparameter flow cytometry (MFC) peripheral blood (PB) T, NK and dendritic (plasmacytoid, myeloid and monocytic) cells (DC) from high-risk smoldering MM (SMM) patients, defined by the presence of at least 2 of the 3 following criteria at diagnosis: bone marrow plasma cell (BMPC) infiltration ≥10%; and/or high M-component (IgG≥30g/L or IgA≥20g/L or B-J Protein>10g/L); and/or ≥95% myelomatous-PC/BMPC and immune paresis. SMM patients were treated according to the QuiReDex trial (NCT 00480363): an induction phase of nine four-week cycles of lenalidomide plus dexamethasone (LenDex) followed by maintenance with lenalidomide until disease progression. In this ongoing study, immunophenotypic data is available in 53 patients at diagnosis (baseline), 30 after 3 cycles of LenDex and 22 at the end of induction therapy (9th cycle). Here we will focus on the 22 cases with information at the 3 time points. For MFC analysis, PB samples were stained using a four-color direct immunofluorescence technique that allowed the quantification and characterization of T, NK and DC cells, including cell cycle analysis. The percentage of PB T cells in total PB cellularity was stable from baseline vs 3 vs 9 cycles of LenDex (22% vs 21% vs 21%; respectively, NS), with similar results also obtained for T CD4 (12% vs 11% vs 9%; respectively, NS) and T CD8 (8% vs 6% vs 8%; respectively, NS) cells. NK cells were slightly increased after 9 cycles of LenDex for both the CD56dim (4.1%, 3.4% and 6%; respectively; NS) and CD56bright (0.05%, 0.04% and 0.15%; respectively; NS) NK cell compartments. Similarly, the percentage of DC slightly increased along treatment, especially for plasmacytoid DC (0.2% at baseline vs 0.4% after 9 cycles; p=0.09). However, when a more detailed immunophenotypic characterization of T and NK cells was carried out significant differences emerged following LenDex treatment (Figure 1A). Accordingly, after 3 and 9 cycles of LenDex both T CD4 and CD8 cells showed increased expression of activation markers such as CD69 (p=.03), CD25 (p=.02 and NS, respectively), CD54 (p<.001), CD28 (p≤.03) and CD120b (p≤.01), together with increased production of IFNγ (p=.03) and IL-2 (p=.1 and p=.008, respectively). Interestingly, after induction therapy an up-regulation of chemokine receptors related to the Th1 (CCR5; p<.001) but also Th2 (CCR4; p≤.002) immune response was detectable in CD4 and CD8 T cells. T CD4 cells displayed a clear maturation into a central memory phenotype following LenDex treatment (38% at baseline vs 50% and 66% at 3 and 9 cycles, respectively; p<.001) while T CD8 cells displayed an increased effector memory phenotype (44% vs 59% vs 62%; p=.004). Further analysis showed increased expression of HLA-DR (p≤.008), the antibody-dependent cell-mediated cytotoxicity associated receptor CD16 (p≤.03), and the adhesion molecules CD11a (p’.006) and CD11b (p≤.004) both on NK (CD56dim and CD56bright) and T cells. No consistent changes were observed in other NK cell receptors, such as CD94 and the immunoglobulin like receptors CD158a, CD161, NKB1 (3DL1) and NKAT2 (2DL3). Concerning cell cycle analysis, the percentage of cells in S-phase was significantly increased from baseline vs 3 vs 9 cycles of LenDex in T CD4 (0.05% vs 0.15% vs 0.16%; p<.001), CD8 (0.05% vs 0.11% vs 0.23%; p<.001) and NK cells (0.09% vs 0.17% vs 0.20%; p=.001). Finally, an unsupervised cluster analysis of the overall immunophenotypic profile obtained after 9 cycles of LenDex (Figure 1B) was able to discriminate two groups of patients (A and B). Interestingly, within the group with higher activation profile (A) 50% of patients achieved ≥VGPR vs 23% in group B (p=.2). In summary, these preliminary results show that in high risk SMM patients the combination of lenalidomide and dexamethasone modulates PB T and NK cells, with increased activation status that may contribute to disease control. Disclosures: Off Label Use: Lenalidomide is not approved for the treatment of smoldering multiple myeloma. De La Rubia:Janssen-Cilag: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Rosiñol:Celgene: Honoraria. Oriol:Celgene: Consultancy; Janssen-Cilag: Consultancy; Novartis: Consultancy. Hernández:Celgene: Honoraria. de Arriba:Janssen-Cilag: Honoraria; Celgene: Honoraria. Mateos:Celgene: Honoraria. San Miguel:Janssen-Cilag: Honoraria; Celgene: Honoraria, Speakers Bureau.


Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1596
Author(s):  
Marta Diaz-delCastillo ◽  
Rebecca E. Andrews ◽  
Aritri Mandal ◽  
Thomas L. Andersen ◽  
Andrew D. Chantry ◽  
...  

Multiple myeloma (MM) is a bone marrow neoplasia that causes bone pain in 70% patients. While preclinical models of MM have suggested that both nerve sprouting and nerve injury may be causative for the pain, there is a lack of clinical data. Thus, the primary aims of this clinical study are: (1) to provide a deep characterization of the subjective experience of pain and quality of life in MM patients; (2) to investigate disturbances in the bone innervation of MM patients. Secondary aims include exploring correlations between pain and serum inflammatory and bone turnover biomarkers. In a prospective, observational study (clinicaltrials.gov: NCT04273425), patients with suspected MM requiring a diagnostic iliac crest biopsy at Sheffield Teaching Hospital (UK) are invited to participate. Consenting patients answer seven standardized questionnaires assessing pain, quality of life and catastrophizing. Bone turnover biomarkers and inflammatory cytokines are measured in fasting serum samples, and bone innervation is evaluated in diagnostic biopsies. MM patients are invited to a follow-up upon completion of first line treatment. This will be the first deep characterization of pain in MM patients and its correlation with disturbances in bone innervation. Understanding how bone turnover and inflammation correlate to pain in MM is crucial to identify novel analgesic targets for this condition.


2020 ◽  
Vol 401 (10) ◽  
pp. 1153-1165 ◽  
Author(s):  
Antônio F. da Silva Filho ◽  
Lucas B. Tavares ◽  
Maira G. R. Pitta ◽  
Eduardo I. C. Beltrão ◽  
Moacyr J. B. M. Rêgo

AbstractPancreatic ductal adenocarcinoma is one of the most aggressive tumors with a microenvironment marked by hypoxia and starvation. Galectin-3 has been evaluated in solid tumors and seems to present both pro/anti-tumor effects. So, this study aims to characterize the expression of Galectin-3 from pancreatic tumor cells and analyze its influence for cell survive and motility in mimetic microenvironment. For this, cell cycle and cell death were accessed through flow cytometry. Characterization of inside and outside Galectin-3 was performed through Real-Time Quantitative Reverse Transcription PCR (qRT-PCR), immunofluorescence, Western blot, and ELISA. Consequences of Galectin-3 extracellular inhibition were investigated using cell death and scratch assays. PANC-1 showed increased Galectin-3 mRNA expression when cultivated in hypoxia for 24 and 48 h. After 24 h in simultaneously hypoxic/deprived incubation, PANC-1 shows increased Galectin-3 protein and secreted levels. For Mia PaCa-2, cultivation in deprivation was determinant for the increasing in Galectin-3 mRNA expression. When cultivated in simultaneously hypoxic/deprived condition, Mia PaCa-2 also presented increasing for the Galectin-3 secreted levels. Treatment of PANC-1 cells with lactose increased the death rate when cells were incubated simultaneously hypoxic/deprived condition. Therefore, it is possible to conclude that the microenvironmental conditions modulate the Galectin-3 expression on the transcriptional and translational levels for pancreatic cancer cells.


Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3523
Author(s):  
Wancheng Guo ◽  
Haiqin Wang ◽  
Peng Chen ◽  
Xiaokai Shen ◽  
Boxin Zhang ◽  
...  

Multiple myeloma (MM) is a B-cell tumor of the blood system with high incidence and poor prognosis. With a further understanding of the pathogenesis of MM and the bone marrow microenvironment, a variety of adjuvant cell therapies and new drugs have been developed. However, the drug resistance and high relapse rate of MM have not been fundamentally resolved. Studies have shown that, in patients with MM, there is a type of poorly differentiated progenitor cell (MM stem cell-like cells, MMSCs). Although there is no recognized standard for identification and classification, it is confirmed that they are closely related to the drug resistance and relapse of MM. This article therefore systematically summarizes the latest developments in MMSCs with possible markers of MMSCs, introduces the mechanism of how MMSCs work in MM resistance and recurrence, and discusses the active pathways that related to stemness of MM.


Author(s):  
Diana Spiegelberg ◽  
Jonas Stenberg ◽  
Pascale Richalet ◽  
Marc Vanhove

AbstractDesign of next-generation therapeutics comes with new challenges and emulates technology and methods to meet them. Characterizing the binding of either natural ligands or therapeutic proteins to cell-surface receptors, for which relevant recombinant versions may not exist, represents one of these challenges. Here we report the characterization of the interaction of five different antibody therapeutics (Trastuzumab, Rituximab, Panitumumab, Pertuzumab, and Cetuximab) with their cognate target receptors using LigandTracer. The method offers the advantage of being performed on live cells, alleviating the need for a recombinant source of the receptor. Furthermore, time-resolved measurements, in addition to allowing the determination of the affinity of the studied drug to its target, give access to the binding kinetics thereby providing a full characterization of the system. In this study, we also compared time-resolved LigandTracer data with end-point KD determination from flow cytometry experiments and hypothesize that discrepancies between these two approaches, when they exist, generally come from flow cytometry titration curves being acquired prior to full equilibration of the system. Our data, however, show that knowledge of the kinetics of the interaction allows to reconcile the data obtained by flow cytometry and LigandTracer and demonstrate the complementarity of these two methods.


Author(s):  
Kenji Nozaki ◽  
Yuki Fujioka ◽  
Daisuke Sugiyama ◽  
Jun Ishikawa ◽  
Masato Iida ◽  
...  

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