Sophie Maïga

A high-risk signature for patients with multiple myeloma established from the molecular classification of human myeloma cell lines

Background Multiple myeloma is a plasma-cell tumor with heterogeneity in molecular abnormalities and treatment response. Design and Methods We have assessed whether human myeloma cell lines have kept patients’ heterogeneity using Affymetrix gene expression profiling of 40 human myeloma cell lines obtained with or without IL6 addition and could provide a signature for stratification of patient risk. Results Human myeloma cell lines, especially those derived in the presence of IL6, displayed a heterogeneity that overlaps that of the patients with multiple myeloma. Human myeloma cell lines segregated into 6 groups marked by overexpression of MAF, MMSET, CCND1, FRZB with or without overexpression of cancer testis antigens (CTA). Cell lines of CTA/MAF and MAF groups have a translocation involving C-MAF or MAFB, cell lines of groups CCND1-1 and CCND1-2like have a t(11;14) and cell lines of group MMSET have a t(4;14). The CTA/FRZB group comprises cell lines that had no or no recurrent 14q32 translocation. Expression of 248 genes accounted for human myeloma cell line molecular heterogeneity. Human myeloma cell line heterogeneity genes comprise genes with prognostic value for survival of patients making it possible to build a powerful prognostic score involving a total of 13 genes. Conclusions Human myeloma cell lines derived in the presence of IL6 recapitulate the molecular diversity of multiple myeloma that made it possible to design, using human myeloma cell line heterogeneity genes, a high-risk signature for patients at diagnosis. We propose this classification to be used when addressing the physiopathology of multiple myeloma with human myeloma cell lines.

ABT-737 is highly effective against molecular subgroups of multiple myeloma.

Multiple myeloma is a plasma cell malignancy that is heterogeneous with respect to its causative molecular abnormalities and the treatment response of patients. The Bcl-2 protein family is critical for myeloma cell survival. ABT-737 is a cell-permeant compound that binds to Bcl-2 and Bcl-x(L) but not to Mcl-1. Using a myeloma cell line collection (n = 25) representative of different molecular translocations, we showed that ABT-737 effectively kills a subset of cell lines (n = 6), with a median lethal dose ranging from 7 ± 0.4 nM to 150 ± 7.5 nM. Of interest, all sensitive cell lines harbored a t(11;14). We demonstrated that ABT-737-sensitive and ABT-737-resistant cell lines could be differentiated by the BCL2/MCL1 expression ratio. A screen of a public expression database of myeloma patients indicates that the BCL2/MCL1 ratio of t(11;14) and hyperdiploid patients was significantly higher than in all other groups (P < .001). ABT-737 first induced the disruption of Bcl-2/Bax, Bcl-2/Bik, or Bcl-2/Puma complexes, followed by the disruption of Bcl-2 heterodimers with Bak and Bim. Altogether, the identification of a subset of cell lines and primary cells effectively killed by ABT-737 alone supported the evaluation of ABT-263, an orally active counterpart to ABT-737, for the treatment of t(11;14) and hyperdiploid groups of myeloma harboring a Bcl-2(high)/Mcl-1(low) profile.

Expression Profile of BCL-2, BCL-XL, and MCL-1 Predicts Pharmacological Response to the BCL-2 Selective Antagonist Venetoclax in Multiple Myeloma Models

BCL-2 family proteins dictate survival of human multiple myeloma cells, making them attractive drug targets. Indeed, multiple myeloma cells are sensitive to antagonists that selectively target prosurvival proteins such as BCL-2/BCL-XL (ABT-737 and ABT-263/navitoclax) or BCL-2 only (ABT-199/GDC-0199/venetoclax). Resistance to these three drugs is mediated by expression of MCL-1. However, given the selectivity profile of venetoclax it is unclear whether coexpression of BCL-XL also affects antitumor responses to venetoclax in multiple myeloma. In multiple myeloma cell lines (n = 21), BCL-2 is expressed but sensitivity to venetoclax correlated with high BCL-2 and low BCL-XL or MCL-1 expression. Multiple myeloma cells that coexpress BCL-2 and BCL-XL were resistant to venetoclax but sensitive to a BCL-XL–selective inhibitor (A-1155463). Multiple myeloma xenograft models that coexpressed BCL-XL or MCL-1 with BCL-2 were also resistant to venetoclax. Resistance to venetoclax was mitigated by cotreatment with bortezomib in xenografts that coexpressed BCL-2 and MCL-1 due to upregulation of NOXA, a proapoptotic factor that neutralizes MCL-1. In contrast, xenografts that expressed BCL-XL, MCL-1, and BCL-2 were more sensitive to the combination of bortezomib with a BCL-XL selective inhibitor (A-1331852) but not with venetoclax cotreatment when compared with monotherapies. IHC of multiple myeloma patient bone marrow biopsies and aspirates (n = 95) revealed high levels of BCL-2 and BCL-XL in 62% and 43% of evaluable samples, respectively, while 34% were characterized as BCL-2High/BCL-XLLow. In addition to MCL-1, our data suggest that BCL-XL may also be a potential resistance factor to venetoclax monotherapy and in combination with bortezomib. Mol Cancer Ther; 15(5); 1132–44. ©2016 AACR.

Canonical Nuclear Factor κB Pathway Inhibition Blocks Myeloma Cell Growth and Induces Apoptosis in Strong Synergy with TRAIL

Purpose: Intrinsic activation of nuclear factor κB (NF-κB) characterizes various hematologic malignancies. In this study, we specifically address the role of NF-κB blockade in mediated antimyeloma activity using the IκB kinase-2 pharmacologic inhibitor, AS602868. Experimental Design: Human myeloma cell lines (n = 16) and primary myeloma cells (n = 10) were tested for their sensitivity to AS602868 in terms of proliferation and apoptosis. Both in vitro and in vivo experiments were conducted. Functional mechanisms regarding the apoptotic pathways triggered by AS602868 were studied. The potential proapoptotic synergy between AS602868 and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) was also evaluated. Results: Our results show that AS602868 efficiently targeted the canonical NF-κB pathway in myeloma cells and potently inhibited their growth in inducing apoptosis through Bax and caspase-3 activation. AS602868 also induced apoptosis in primary myeloma cells even in the presence of bone marrow mononuclear cells. Moreover, the IκB kinase-2 inhibitor targeted the paracrine effect on the bone marrow environment. Indeed, it decreased the intrinsic and myeloma-induced secretion of interleukin-6 from bone marrow stromal cells. In addition, AS602868 inhibited myeloma cell growth in the MM.1S xenograft myeloma model. Of particular interest, AS602868 strongly increased myeloma sensitivity to TRAIL in blocking TRAIL-induced NF-κB activation and in decreasing the expression of antiapoptotic proteins such as cFLIP and cIAP-1/2. Conclusions: Taken together, our data point out the interest to inhibit the canonical NF-κB pathway in myeloma and clearly encourage clinical evaluation of novel therapies based on targeting NF-κB, especially in combination with TRAIL.

Critical role of the NOTCH ligand JAG2 in self-renewal of myeloma cells.

The purpose of this study was to identify the pathways associated with the ability of CD138(+) human myeloma cells to form colonies in a serum-free semi-solid human collagen-based assay. Only 26% (7 of 27) of human myeloma cell lines were able to spontaneously form colonies. This spontaneous clonogenic growth correlated with the expression of the NOTCH ligand JAG2 (p<0.001). Blocking JAG-NOTCH interactions with NOTCH-Fc chimeric molecules impaired self-colony formation, indicating a role for JAG-NOTCH pathway in colony formation. In two cell lines, silencing of JAG2 blocked both colony formation and in vivo tumor formation in immunocompromised mice. RT-PCR and flow cytometry analysis revealed that JAG2 is often expressed by CD138(+) primary cells. Our results indicate that spontaneous clonogenic growth of myeloma cells requires the expression of JAG2.

Cereblon expression in multiple myeloma: not ready for prime time

One of the major recent advances in the biology of multiple myeloma (MM) is the discovery of Cereblon (CRBN) as a potential target for immunomodulatory drugs (IMiDs) activity (Zhu et al, 2011). The use of lenalidomide and dexamethasone (Len-Dex) as frontline therapy might become one of the future standards of care in the treatment of symptomatic MM. Therefore, identification of a biological test able to predict individual patients’ response to lenalidomide is a major challenge, especially in the dawning world of personalized medicine. Recently Heintel et al (2013) reported on a moderate correlation between baseline CRBN expression and clinical response in patients treated with upfront Len-Dex (r = 0 48), CRBN expression being additionally associated with that of CTNNB1 (r = 0 7). These interesting results, providing two possible predictive markers of clinical response, have however to be carefully evaluated before drawing final conclusions, and we would like to discuss at least three important issues in this setting. Firstly, and this point is indeed well addressed by the authors, it is commonly admitted that biological analyses in MM patients have to be performed on sorted CD138 plasma cells. Yet Heintel et al (2013) explored results on sorted MM plasma cells in only six out of 49 patients. Because of the potential role of lenalidomide on CRBNexpressing microenvironmental cells, it will be necessary to clarify the issue of the type of samples that should be used to best assess CRBN expression in patients. It however seems quite obvious that the CD138 population of plasma cells would be the key target of such therapy and therefore that in which CRBN expression should be assessed. Secondly, the complexity of CRBN physiology should be considered. In order to evaluate CRBN expression in patients, Heintel et al (2013) used a real time reversetranscription polymerase chain reaction (RTqPCR) Taqman assay designed on exons 8–9 junction, which is different from the exons 10–11 junction design used by Broyl et al (2012). Other Taqman predesigned probes spanning different exon junctions are also currently available (Life Tech, Grand Island, NY, USA) but standardization of RTqPCR has not been proposed so far. Moreover, as do most of the genes in the human genome, CRBN undergoes mRNA alternative splicing (http://genome.ucsc.edu) and several isoforms have been described in MM (Gandhi et al, 2012). We performed overlapping RT-PCR designed on all CRBN exons in sorted CD138 plasma cells from 19 MM patients (purity > 90%). We showed multiple bands on gel in addition to expected size band (‘full-length’ CRBN-001/004) in virtually all of these patients (Fig 1A). By sequencing these RT-PCR products and alignment on a public genome database, we confirmed the presence of frequent alternative spliced transcripts including CRBN-002, lacking exon 10, and several other in frame alternative transcripts not described in Ensembl (http://www.ensembl.org) to date and that we named CRBN D8, CRBN D 8, 10 and CRBN D 7,8,10 as they had lost exon 8 only, exons 8 and 10 or exons 7, 8 and 10, respectively (Fig 1B). In some patients, these alternative spliced variants accounted for more than 50% of total CRBN (data not shown). This result shows that the design of the RTq-PCR test chosen to assess CRBN expression level is critical and could yield variable results. Evaluation of the CRBN splicing profile of each patient should therefore be considered prior to performing RTqPCR because the latter might yield irrelevant data if the exon assessed by the RTqPCR has been lost, and particularly if exon 10 has been removed (CRBN -002) as it contains a portion of the IMiD-binding domain (Ito et al, 2010; LopezGirona et al, 2012). Thirdly, because both CRBN and CNNTB1 genes are located on chromosome 3 (3p26 2 and 3p21, respectively), and given that chromosome 3 trisomy is the most frequent hyperdiploidy (HY) in MM (Kumar et al, 2012), we looked at the impact of HY with respect to other molecular MM subgroups for CRBN and CNNTB1 expression levels. Publicly available Affymetrix (Santa Clara, CA, USA) gene expression levels of 414 newly diagnosed MM patients enabled us to assess CRBN expression in each of the subgroups, designed according to Zhan et al (2006) (Fig 2). Of note, none of the patients completely lacked CRBN or CNNTB1 expression. Yet, HY patients significantly expressed higher levels of CRBN than all other subgroups (Kruskall–Wallis P < 0 0001), together with a trend for a higher level of CNNTB1 expression (P = 0 07). Comparison of CRBN and CNNTB1 expression between HY patients and all other subgroups revealed a significantly higher level of both genes in HY patients (Mann– Whitney P < 0 0001 and P = 0 006, respectively; Fig 2A). We also confirmed in this cohort of newly diagnosed patients a direct correlation between CRBN and CNNTB1 expression (P < 0 001; r = 0 52, Spearman test; Fig 2B). Given the wellknown better prognosis and survival observed in HY patients and the beneficial effect of odd chromosomes trisomy in high-risk MM patients, further investigations of CRBN expression in relation to the response to IMiDs should also

Bendamustine and melphalan kill myeloma cells similarly through reactive oxygen species production and activation of the p53 pathway and do not overcome resistance to each other

Abstract Because the old alkylating drug bendamustine (BDM) is currently under evaluation in patients with multiple myeloma, we compared its efficacy to that of melphalan in 29 human myeloma cell lines (HMCLs). The concentrations of BDM and melphalan that killed 50% of cells (LD50) in HMCLs were linearly correlated (p < 0.001), and reactive oxygen (ROS) scavengers similarly inhibited cell death induced by both drugs. Sensitivity of HMCLs to both drugs was correlated to p53: the BDM and melphalan median LD50 values of TP53wild-type HMCLs were more than two-fold lower than those of TP53abnormal HMCLs (p < 0.001), and p53 silencing in TP53wt NCI-H929 cells inhibited BDM- and melphalan-induced cell death. Both drugs induced expression of p53 targets, p21, Puma and DR5, only in TP53wt HMCLs. In primary cells, both drugs induced an increase in DR5 expression in cells without del(17p). Finally, we demonstrated that the combined effect of BDM and melphalan was additive, and that BDM did not overcome melphalan resistance and vice versa.

Curcumin induces cell death of the main molecular myeloma subtypes, particularly the poor prognosis subgroups

Multiple myeloma (MM), a plasma cell malignancy, remains incurable despite the development of new therapies. Curcumin anti-tumor effects were previously characterized in multiple myeloma, however only few MM cell lines were included in these studies. Since myeloma is a heterogeneous disease it is important to address the impact of myeloma molecular heterogeneity in curcumin cell death induction. In the present study, a large panel of human myeloma cell lines (HMCLs) (n = 29), representing the main molecular MM subgroups, was screened for curcumin sensitivity. We observed that curcumin cell death induction was heterogeneous, of note 16 HMCLs were highly sensitive to curcumin (LD50 < 20.5 μM), 6 HMCLs exhibited intermediate LD50 values (20.5 μM ≤ LD50 < 32.2 μM) and only 7 HMCLs were weakly sensitive (35 < LD50 < 56 μM). Cell lines harboring the t(11;14) translocation were less sensitive (median LD50 32.9 μM) than non-t(11;14) (median LD50 17.9 μM), which included poor prognosis t(4;14) and t(14;16) cells. Interestingly, curcumin sensitivity was not dependent on TP53 status. For the first time we showed that primary myeloma cells were also sensitive, even those displaying del(17p), another poor prognosis factor. We also unravel the contribution of anti-apoptotic Bcl-2 family molecules in curcumin response. We found that down-regulation of Mcl-1, an essential MM survival factor, was associated with curcumin-induced cell death and its knockdown sensitized myeloma cells to curcumin, highlighting Mcl-1 as an important target for curcumin-induced apoptosis. Altogether, these results support clinical trials including curcumin in association with standard therapy.

BH3 profiling as a tool to identify acquired resistance to venetoclax in multiple myeloma

BH3 profiling as a tool to identify acquired resistance to venetoclax in multiple myeloma Venetoclax/ABT-199 is the first in the class of BCL2-specific BH3 mimetics and the most promising targeted therapy in oncology (Souers et al, 2013). Venetoclax is currently under investigation in multiple myeloma (MM), which is heterogeneous and includes either patients with a translocation on chromosome 14 with different chromosomes (4, 6, 11 or 16) or a hyperdiploidy. We demonstrated that venetoclax induces cell death in a subgroup harbouring the t(11;14) transloca-tion, expressing a high BCL2/MCL1 gene expression ratio, and that intrinsic venetoclax resistance is mediated by high MCL1 expression in MM cells (Touzeau et al, 2014). Preliminary results from an ongoing phase I clinical trial testing venetoclax in relapsed/refractory MM patients indicate that BCL2 inhibition has a tolerable safety profile and single agent activity mostly in t(11;14) patients (Kumar et al, 2015). The anticipated use of venetoclax in the treatment of MM lead us to explore the mechanisms of acquired veneto-clax resistance. We generated two venetoclax-resistant mye-loma cell lines using in vitro selection and derived resistant sublines (named-199R) from KMS12-PE and XG5 t(11;14) myeloma venetoclax-sensitive cell lines (Figs 1A, 2A) (Data S1). Both resistant sublines showed a strong reduction in V

A simple flow cytometry‐based barcode for routine authentication of multiple myeloma and mantle cell lymphoma cell lines

lines are widely used in laboratories for in vitro experi-ments, especially for investigating abnormal hallmarks in can-cer cells and identifying therapeutic targets. Human cell linesare typically derived in academic laboratories from a widerange of cancer samples. To achieve a representation of intra-cancer heterogeneity, several laboratories, including ours, haveestablished cell line collections. However, the establishmentand maintenance of such collections significantly increase therisk of cross-contaminations and misidentification of celllines, leading to the publication of false data/interpretation(1). In addition to the risk of cross-contamination, widelyused cell lines can be described in contrasting manners for aparticular feature (e.g., the JJN3 myeloma cell line appearseither TP53