scholarly journals Selinexor (KPT-330) Is Not Cross-Resistant with Chemotherapy and Demonstrates Strong Synergy with Targeted Therapy in DLBCL

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4503-4503
Author(s):  
Jingda Xu ◽  
R Eric Davis ◽  
Zhiqiang Wang ◽  
Jason R. Westin
Keyword(s):  
Gene Expression ◽  
Targeted Therapy ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Expression Profiling ◽  
Single Agent ◽  
B Cell Lymphoma ◽  
Dose Titration ◽  
Ic50 Values

Abstract Introduction: XPO1 (CRM1, Exportin 1) is the sole transporter of many tumor suppressor proteins (including MYC, BCL2, BCL6, BTK, IkB) and is elevated in non-Hodgkin Lymphoma. Selinexor (Sel, KPT-330) is an oral covalent inhibitor of XPO1, the first clinical molecule of the Selective Inhibitors of Nuclear Export drug class. The phase I clinical trial of Sel in hematologic malignancies showed promising early single-agent efficacy with modest toxicity in relapsed Diffuse Large B-cell Lymphoma (DLBCL, Gutierrez et al, ASCO 2014). DLBCL, the most common lymphoid malignancy, is currently cured in only 10% of relapsed patients, and consists of 2 subtypes based on putative cell of origin (COO): activated B-cell (ABC) and germinal center B-cell (GCB). We performed preclinical studies of Sel, modeling its single-agent efficacy in frontline and relapsed DLBCL and its potential synergy with other clinically relevant therapeutics. Methods: To model drug resistant DLBCL, resistant subpopulations of 12 patient-derived DLBCL cell lines were created by in vitro intermittent exposure to active congeners of cyclophosphamide, doxorubicin, and vincristine (ivCHOP), approximating clinical practice. To determine if CHOP-resistant DLBCL is also resistant to other agents, we determined single-agent dose response curves and IC50 values for both parental and ivCHOP resistant (CHOP-res) subclones of 4 of these lines at submission (HBL1 & TMD8 of ABC subtype, OCI-Ly7 & HT of GCB subtype, with 8 lines in progress) with Sel, chemotherapy (CT, ivCHOP, DHAP, and ICE), and targeted therapy (TT, ibrutinib, ABT-199, idelalisib, everolimus, MLN0128, alisertib, lenalidomide, bortezomib, I-BET151, and ONC201). Viability was assessed with CellTiter-Glo (Promega) after a 3 day cell culture. IC50 values were determined using GraphPad Prism. Based on these results, we evaluated the ability of Sel to synergize with other agents or restore sensitivity in CHOP-res with a combination “checkerboard” (orthogonal dose titration for each drug). The Combination Index (CI) for pairs at all concentrations was calculated with ComboSyn, with CI values <1 indicating synergy. Gene expression profiling with Illumina HT12v4 arrays will compare parental and CHOP-res of 12 DLBCL lines. Results: All CHOP-res lines of both COO types had higher IC50 for both ivCHOP (mean, 3.7x) and DHAP (4.5x) as compared to parental cells (Table 1). In contrast, the IC50 of Sel is unchanged between parental and CHOP-res, for both COO types. Other targeted agents displayed variable activity between parental and CHOP-res and between COO types, with the IC50 of ibrutinib being nearly 2 log lower in ABC lines. CI values showed that Sel was generally a strong synergizer (Table 1), especially with TT and in ABC lines. Sel had lower CI values with CT, but restored sensitivity to ivCHOP in HBL1 (Figure 1). Bortezomib and Sel were moderately antagonistic, although further tests are ongoing. Gene expression profiling, comparing parental vs. CHOP-res and Sel synergizing vs. non-synergizing lines, is ongoing. Conclusions: Our data suggest that Sel: 1) is equally active, and thus not cross-resistant, in cell lines made resistant to standard chemotherapeutics, 2) is a potent, broadly active synergizer with targeted therapy against lines modeling relapsed DLBCL, and 3) has greater synergy in ABC DLBCL, in which it may be able to reverse acquired resistance to frontline therapy. This behavior fits with the broad effects of XPO1 inhibition. The cross-resistance of CHOP-res lines to DHAP models clinical outcomes, and re-sensitization of CHOP-res lines with Sel suggests the potential for relapsed and frontline clinical trials. Further work with our model may discover more synergies of Sel, suggesting future clinical combinations and biomarkers associated with response. Table 1HBL1TMD8OCI-Ly7HTABCGCBIC50SR ΔSR ΔSR ΔSR ΔivCHOP2E-62.31E-75.51E-63.78E-63.2DHAP6E-73.65E-85.52E-73.71E-75.2Selinexor5E-80.66E-81.57E-80.94E-71.3Ibrutinib8E-81.02E-70.43E-60.92E-61.0ABT-1992E-60.53E-61.23E-60.38E-940.3Bortezomib4E-100.61E-101.03E-102.84E-100.9MLN01282E-71.22E-89.44E-85.42E-73.4CI with selinexorivCHOP 0.27 0.27 1.26 3.24DHAP 0.65 0.65 2.23 0.49Ibrutinib 0.06 0.06 0.02 0.95ABT-199 0.47 0.47 0.26 0.89Bortezomib 3.23 3.23 3.53 10Dexamethasone 0.19 0.19 0.39 2.09MLN0128 0.11 0.35 0.47 0.09 ivCHOP sensitive=S, Resistant=R, Δ fold change from S to R Disclosures No relevant conflicts of interest to declare.

New Pathogenetic Insights Into Classical Hodgkin Lymphoma Revealed by Gene Expression Profiling of Microdissected Hodgkin/Reed-Sternberg Cells.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 266-266 ◽  
Author(s):  
Enrico Tiacci ◽  
Verena Brune ◽  
Susan Eckerle ◽  
Wolfram Klapper ◽  
Ines Pfeil ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Cell Lines ◽  
Expression Profiling ◽  
Expression Profiles ◽  
B Cell Lymphoma ◽  
Cell Phenotype

Abstract Abstract 266 Background. Previous gene expression profiling studies on cHL have been performed on whole tissue sections (mainly reflecting the prominent reactive background in which the few HRS cells are embedded), or on cHL cell lines. However, cultured HRS cells do not likely reflect primary HRS cells in all aspects, being derived from end-stage patients and from sites (e.g. pleural effusions or bone marrow) which are not typically involved by cHL and where HRS cells lost their dependence on the inflammatory microenvironment of the lymph node. Methods. ∼1000–2000 neoplastic cells were laser-microdissected from hematoxylin/eosin-stained frozen sections of lymph nodes taken at disease onset from patients with cHL (n=16) or with various B-cell lymphomas (n=35), including primary mediastinal B-cell lymphoma (PMBL) and nodular lymphocyte-predominant Hodgkin lymphoma (nLPHL). After two rounds of in vitro linear amplification, mRNA was hybridized to Affymetrix HG-U133 Plus 2.0 chips. Expression profiles were likewise generated from sorted cHL cell lines and several normal mature B-cell populations. Results. Primary and cultured HRS cells, although sharing hallmark cHL signatures such as high NF-kB transcriptional activity and lost B-cell identity, showed considerable transcriptional divergence in chemokine/chemokine receptor activity, extracellular matrix remodeling and cell adhesion (all enriched in primary HRS cells), as well as in proliferation (enriched in cultured HRS cells). Unsupervised and supervised analyses indicated that microdissected HRS cells of cHL represent a transcriptionally unique lymphoma entity, overall closer to nLPHL than to PMBL but with differential behavior of the cHL histological subtypes, being HRS cells of the lymphocyte-rich and mixed-cellularity subtypes close to nLPHL cells while HRS cells of NS and LD exhibited greater similarity to PMBL cells. HRS cells downregulated a large number of genes involved in cell cycle checkpoints and in the maintenance of genomic integrity and chromosomal stability, while upregulating gene and gene signatures involved in various oncogenic signaling pathways and in cell phenotype reprogramming. Comparisons with normal B cells highlighted the lack of consistent transcriptional similarity of HRS cells to bulk germinal center (GC) B cells or plasma cells and, interestingly, a more pronounced resemblance to CD30+ GC B cells and CD30+ extrafollicular B cells, two previously uncharacterized subsets that are transcriptionally distinct from the other mature B-cell types. Conclusions. Gene expression profiling of primary HRS cells provided several new insights into the biology and pathogenesis of cHL, its relatedness to other lymphomas and normal B cells, and its enigmatic phenotype. Disclosures: No relevant conflicts of interest to declare.

Pharmacogenetic Approaches Identify ANTXR1 As a Potential Mediator of Response to Therapeutic NF-κB Inhibition in Diffuse Large B Cell Lymphoma

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 234-234
Author(s):  
Soham D. Puvvada ◽  
Cassandra L Love ◽  
Vladimir Grubor ◽  
Jenny Zhang ◽  
Jason Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Exome Sequencing ◽  
Cell Lines ◽  
Expression Profiling ◽  
B Cell Lymphoma ◽  
Lymphoid Malignancies ◽  
Whole Exome

Abstract Abstract 234 Background: NF-κB is a family of transcription factors known to play an essential role in the development & survival of lymphocytes. In recent years, it has been clear that aberrant NF-κB activation is a hallmark of various lymphoid malignancies and appears to be associated with chemotherapy resistance and adverse prognosis. The canonical NF-κB pathway is frequently engaged in lymphoid malignancies wherein activated IKK phosphorylates IκB proteins inducing IκB polyubiquination and subsequent proteasomal proteolytic degradation; this allows for release and nuclear translocation of NF-κB dimers to activate target gene transcription. Gene Expression Profiling (GEP) has identified two distinct sub groups of Diffuse Large B cell Lymphoma (DLBCL). While the Activated B cell (ABC) type shows constitutive activation of NF-κB, the role for NF-κB activation in Germinal Center B Cell (GCB) DLBCL is currently unclear. Since NF-κB inhibition has been identified as a therapeutic possibility in DLBCLs, it is important to define the role of this pathway and its modulators. In this study, we sought to investigate key regulators of the NF-κB pathway that might mediate a therapeutic response to IKKβ inhibition of NF-κB in DLBCL including the GCB subtype. Through GEP and Exome Sequencing, we demonstrate that ANTXR1 is a key mediator of response to IKKβ inhibition in DLBCL. Methods/Results: We obtained a novel selective inhibitor of IKKβ, TLX-2001 that has been found to be safe in animal models. IC50 were obtained on 61 cell lines representing various lymphomas including DLBCL (N=25) using cell viability MTT assays. The drug showed efficacy in both ABC and GCB DLBCL cell lines at physiologically achievable concentrations. These results were unsurprising in ABC DLBCLs which are known to depend on NF-κB activation, but the lethality of this selective drug in GCB DLBCLs was unexpected. To better understand the role of individual genes in the response in GCB DLBCLs, gene expression profiling was performed on 61 cell lines using Human Gene 1.0 ST Array. We found that ANTXR1 expression significantly correlated with NF-κB resistance (p = 0.035). Additionally, we sequenced the exomes of DLBCL tumors (N=95) and matched normal tissue (N=34). 95 cases of DLBCLs consisted of 73 cases of primary human DLBCLs and 22 DLBCL cell lines. Whole exome sequencing was performed using the Agilent solution-based system of exon capture to sequence all protein coding exons in the CCDS database. We identified 465 recurrently somatically mutated genes in these DLBCL cases, and found that mutation status of ANTXR1 was associated with high sensitivity to IKKβ inhibition (p =0.015) of NF-κB. Cell lines with non-synonymous mutations in ANTXR1 had over 3-fold lower IC50 (mean= 2.39 μM) compared to cell lines with no mutation in ANTXR1 (mean IC50 = 8.72μM). Discussion/Conclusion: ANTXR1 is the docking receptor for bacillus anthracis toxin, and anti-tumor responses have been observed in mice injected with recombinant engineered anthrax toxin. It is also known as TEM8 and maps to chromosome 2p13.1. Increased levels of TEM8 (tumor endothelial marker 8) have been noted in various malignancies including melanoma. Our data suggest that pharmacogenetic approaches that combine gene expression profiling and whole exome sequencing are useful tools for identifying novel genes that modulate therapeutic responses in lymphoma. Disclosures: No relevant conflicts of interest to declare.

Gene Expression Profiling Data in Lymphoma and Leukemia: Review of the Literature and Extrapolation of Pertinent Clinical Applications

2006 ◽  
Vol 130 (4) ◽  
pp. 483-520 ◽  
Author(s):  
Cherie H. Dunphy
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Lymphoblastic Leukemia ◽  
B Cell Lymphoma ◽  
Clinical Applications

Abstract Context.—Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice. Objectives.—To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text. Data Source.—PubMed was searched for pertinent literature from 1993 to 2005. Conclusions.—Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte–predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

Cell-of-Origin in Diffuse Large B-Cell Lymphoma: Are the Assays Ready for the Clinic?

2015 ◽  
pp. e458-e466 ◽  
Author(s):  
David W. Scott
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Practical Implementation ◽  
Cell Of Origin ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma worldwide and consists of a heterogeneous group of cancers classified together on the basis of shared morphology, immunophenotype, and aggressive clinical behavior. It is now recognized that this malignancy comprises at least two distinct molecular subtypes identified by gene expression profiling: the activated B-cell-like (ABC) and the germinal center B-cell-like (GCB) groups—the cell-of-origin (COO) classification. These two groups have different genetic mutation landscapes, pathobiology, and outcomes following treatment. Evidence is accumulating that novel agents have selective activity in one or the other COO group, making COO a predictive biomarker. Thus, there is now a pressing need for accurate and robust methods to assign COO, to support clinical trials, and ultimately guide treatment decisions for patients. The “gold standard” methods for COO are based on gene expression profiling (GEP) of RNA from fresh frozen tissue using microarray technology, which is an impractical solution when formalin-fixed paraffin-embedded tissue (FFPET) biopsies are the standard diagnostic material. This review outlines the history of the COO classification before examining the practical implementation of COO assays applicable to FFPET biopsies. The immunohistochemistry (IHC)-based algorithms and gene expression–based assays suitable for the highly degraded RNA from FFPET are discussed. Finally, the technical and practical challenges that still need to be addressed are outlined before robust gene expression–based assays are used in the routine management of patients with DLBCL.

Gene-expression profiling and not immunophenotypic algorithms predicts prognosis in patients with diffuse large B-cell lymphoma treated with immunochemotherapy

Blood ◽  
2011 ◽  
Vol 117 (18) ◽  
pp. 4836-4843 ◽  
Author(s):  
Gonzalo Gutiérrez-García ◽  
Teresa Cardesa-Salzmann ◽  
Fina Climent ◽  
Eva González-Barca ◽  
Santiago Mercadal ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Progression Free Survival ◽  
B Cell Lymphoma ◽  
Tissue Microarrays ◽  
Prognostic Impact ◽  
Germinal Center B Cell ◽  
Large B Cell

Abstract Diffuse large B-cell lymphomas (DLBCLs) can be divided into germinal-center B cell–like (GCB) and activated-B cell–like (ABC) subtypes by gene-expression profiling (GEP), with the latter showing a poorer outcome. Although this classification can be mimicked by different immunostaining algorithms, their reliability is the object of controversy. We constructed tissue microarrays with samples of 157 DLBCL patients homogeneously treated with immunochemotherapy to apply the following algorithms: Colomo (MUM1/IRF4, CD10, and BCL6 antigens), Hans (CD10, BCL6, and MUM1/IRF4), Muris (CD10 and MUM1/IRF4 plus BCL2), Choi (GCET1, MUM1/IRF4, CD10, FOXP1, and BCL6), and Tally (CD10, GCET1, MUM1/IRF4, FOXP1, and LMO2). GEP information was available in 62 cases. The proportion of misclassified cases by immunohistochemistry compared with GEP was higher when defining the GCB subset: 41%, 48%, 30%, 60%, and 40% for Colomo, Hans, Muris, Choi, and Tally, respectively. Whereas the GEP groups showed significantly different 5-year progression-free survival (76% vs 31% for GCB and activated DLBCL) and overall survival (80% vs 45%), none of the immunostaining algorithms was able to retain the prognostic impact of the groups (GCB vs non-GCB). In conclusion, stratification based on immunostaining algorithms should be used with caution in guiding therapy, even in clinical trials.

scholarly journals Constitutive Nuclear Factor κB Activity Is Required for Survival of Activated B Cell–like Diffuse Large B Cell Lymphoma Cells

2001 ◽  
Vol 194 (12) ◽  
pp. 1861-1874 ◽  
Author(s):  
R. Eric Davis ◽  
Keith D. Brown ◽  
Ulrich Siebenlist ◽  
Louis M. Staudt
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Nuclear Factor ◽  
Large B Cell Lymphoma ◽  
Dlbcl Subtype ◽  
Large B Cell

Gene expression profiling has revealed that diffuse large B cell lymphoma (DLBCL) consists of at least two distinct diseases. Patients with one DLBCL subtype, termed activated B cell–like (ABC) DLBCL, have a distinctly inferior prognosis. An untapped potential of gene expression profiling is its ability to identify pathogenic signaling pathways in cancer that are amenable to therapeutic attack. The gene expression profiles of ABC DLBCLs were notable for the high expression of target genes of the nuclear factor (NF)-κB transcription factors, raising the possibility that constitutive activity of the NF-κB pathway may contribute to the poor prognosis of these patients. Two cell line models of ABC DLBCL had high nuclear NF-κB DNA binding activity, constitutive IκB kinase (IKK) activity, and rapid IκBα degradation that was not seen in cell lines representing the other DLBCL subtype, germinal center B-like (GCB) DLBCL. Retroviral transduction of a super-repressor form of IκBα or dominant negative forms of IKKβ was toxic to ABC DLBCL cells but not GCB DLBCL cells. DNA content analysis showed that NF-κB inhibition caused both cell death and G1-phase growth arrest. These findings establish the NF-κB pathway as a new molecular target for drug development in the most clinically intractable subtype of DLBCL and demonstrate that the two DLBCL subtypes defined by gene expression profiling utilize distinct pathogenetic mechanisms.

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