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  • 1
  • 2
    Publication Date: 2016-12-02
    Description: Genome wide association studies (GWAS) in multiple myeloma (MM), and other neoplasias, have provided important insights into candidate germline variations, which may influence the risk of an individual to develop a given cancer, experience adverse clinical outcomes or develop side effects after treatment. However, it has been typically challenging to pursue further mechanistic evaluation of all these germline variants. Consequently, the role of many such variants in myeloma biology and clinical behavior often remains to be elucidated. We reasoned that recently developed functional genomics platforms, such as the CRISPR/Cas9 gene editing methodology, could provide insight into the role of GWAS-derived germline variants in MM. Specifically, we hypothesized that at least some germline variants previously proposed to correlate with higher risk for development of MM or its adverse clinical outcome could reside in or be proximal to genes which influence the proliferation and survival of MM cells. To address this hypothesis, we examined the results from our genome-wide CRISPR/Cas9-based gene editing screens in 2 MM cell lines (MM1.S and RPMI-8226; using the GeCKOv2 library of single guide RNAs [sgRNAs]), as well as additional results from other in-house or publicly available genome-wide CRISPR/Cas9 gene editing studies in 50 cell lines from other hematologic malignancies and 8 different types of solid tumors. In this functional genomic dataset, we examined the performance of 50 genes located in close proximity to over 60 risk loci identified in 6 different previously published GWAS studies for MM. Many of these genes had plausible potential involvement in MM/tumor biology, given their participation in transcriptional control or epigenetic regulation (e.g. CBX7, ASXL2, LCOR, MED24, SMARCD3, POU5F1); immunoglobulin secretion in plasma cells (ELL2), cell-to-cell adhesion (e.g. CDH12, CDH13); DNA repair (e.g. POLQ). We determined whether sgRNAs against these genes exhibited statistically significant (for 3 or more sgRNAs/gene, FDR=0.05) depletion or enrichment among the MM or non-MM cell lines of our study. While 14 and 6 of these genes exhibited statistically significant depletion (FDR=0.05) of their sgRNAs (3 or more per gene) in RPMI8226 and MM.1S cells, respectively, almost all of these genes were not ranked within the top 2000 genes with the most pronounced sgRNA depletion (in terms of log2 fold change and number of depleted sgRNAs/gene) in either MM or non-MM cell lines. Similarly, statistically significant sgRNA enrichment was not observed for the overwhelming majority of the genes in question in MM or non-MM cell lines. Interestingly, however, several genes showed a statistically significant association with clinical outcome in at least one clinically annotated gene expression profiling dataset in MM (e.g. correlation of ELL2, CDH13 transcript levels with clinical outcome of bortezomib-treated MM patients). These results taken together suggest that the majority of genes identified through prior GWAS studies for MM risk or adverse clinical outcome in this disease may have modest, if any, impact of the proliferation or survival of MM cells, as well as many other types of non-MM tumor cells, in CRISPR/Cas9-based screens conducted in cell-autonomous assay systems. In turn, these observations imply that, if these candidate genes are validated to play important roles in the pathophysiology of MM cells in vivo, this may likely involve cell-nonautonomous roles of these genes, e.g. in regulating tumor cell interaction with non-malignant cells in the local microenvironment or immune evasion. Our results highlight the value of a previously underappreciated approach in integrating genome-wide CRISPR/Cas9 in vitro genomic results with GWAS studies, in order to more comprehensively examine the putative roles of candidate germline variants and their proximal genes in the pathophysiology of myeloma and other neoplasias. Disclosures No relevant conflicts of interest to declare.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 3
    Publication Date: 2016-12-02
    Description: Multiple Myeloma (MM) remains an incurable malignancy in part because of an incomplete understanding of which genes are critically responsible for MM cell survival and proliferation. To address this unmet need, and building on our recent functional genomics studies with the CRISPR/Cas9 gene editing platform (ASH 2015; Int. MM Workshop, Rome 2015), we reasoned that quantification of sgRNA depletion in the absence of any treatment could identify genes essential for the survival or proliferation of MM cells and better define their role as candidate therapeutic targets. To this end, we transduced Cas9-expressing RPMI-8226 and MM.1S cells with the lentiviral genome-scale GeCKO pooled library of sgRNAs. After culture of these cell lines for 2, 6, 8 or 12 weeks without any treatment, we identified, based on next generation sequencing for the sgRNA sequences, genes with significantly depleted sgRNAs (4-6 sgRNAs/gene, 〉2-fold average depletion, FDR=0.05, based on MAGECK algorithm) in Cas9+ cells compared to their initial sgRNA plasmid pools, baseline cultures, or isogenic parental Cas9-negative cells. These results were confirmed for each cell line with a 2nd independent genome-wide analysis and with a focused sgRNA library containing a subset of candidates defined by the genome-wide analyses. We compared these results with data from our in-house or publicly available CRISPR/Cas9 gene editing studies, involving a total of 50 cell lines from other hematologic malignancies (leukemia, lymphoma) and from 8 different types of solid tumors. We identified 3 broad categories of essential genes in MM cells: a) core essential genes, with sgRNA depletion across the majority of MM and non-MM lines of our study, representing cellular processes critical for practically all lineages (e.g. genes involved in regulation of basic transcription factor complexes, ribosomal function, proteasome, spliceosome, structural proteins for mitochondria and other key organelles, et.c.); b) genes selectively essential for MM cell lines, but not for the overwhelming majority of leukemia, lymphoma or solid tumor cell lines; c) genes with a role in small subset(s) of cell lines, across diseases, which harbor defined genetic features correlating with this dependency. We integrated our CRISPR/Cas9-based data on MM-selective essential genes with a reanalysis of the Achilles Heel shRNA screen in MM and non-MM cell lines (10 and 493, respectively) of the Cell Line Encyclopedia Program (CCLE) program. We applied a series of statistical tests (e.g. Wilcoxon rank test or marker selection feature of GENE-E algorithm with 1000 permutation tests) to identify genes with a significantly lower rank in sgRNA or shRNA depletion in MM vs. non-MM cell lines, across different specific thresholds for fold change and statistical significance. We identified more than 50 high-value candidate target genes with preferential essentiality in MM, compared to non-MM cell lines of diverse lineages. Prominent examples of such MM-selective, essential genes included: transcription factors (e.g. IRF4, CCND2, MAF, NFKB1, NFKB2, RELA, RELB); otherNF-kB-related genes (e.g. IKBKB); PIM2 (but not PIM1 or PIM3 in this cell line panel); regulators of protein homeostasis, including diverse E2 and E3 ubiquitin ligases; and several other known or biologically-plausible dependencies which are under further evaluation. Many of these MM-selective dependencies exhibited significantly higher expression in MM, compared to non-MM cells, both in cell lines (based on the CCLE dataset) and patient-derived samples (comparison of Broad/MMRF vs. TCGA datasets, respectively). Notable observations of context-dependent essential genes include ARID1A in MM.1S cells (plausibly due to deficiency in its paralog ARID1B); and cases of both MM and non-MM cells with RAS mutations but lack of dependency on that gene. Targeting of lineage-specific dependencies (e.g. ER or AR in breast or prostate Ca, respectively) has provided major clinical benefit in some tumors; while context-specific dependencies are a cornerstone of molecularly-guided individualized treatments. Therefore, by identifying lineage- and context-dependent essential genes for MM, our integrated genome-wide CRISPR/Cas9 and shRNA analyses in molecularly annotated panels of MM vs. non-MM cell lines provide an attractive framework towards designing novel therapies for MM. Disclosures No relevant conflicts of interest to declare.
    Print ISSN: 0006-4971
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  • 4
    Publication Date: 2019-11-13
    Description: Immunotherapy has remarkably changed the treatment paradigm in hematologic malignancies and natural killer (NK) cell therapy represents an attractive option, as it has been feasible and safe in early clinical trials, without graft-versus-host effects. Nevertheless, the molecular markers determining cancer cell sensitivity or resistance to NK cells, especially in the context of tumor cell interaction with the bone marrow (BM) stromal microenvironment remain incompletely understood, but have major translational relevance since these tumor-stromal interactions have been known to attenuate the response of blood cancer cells to diverse classes of pharmacological agents. To address these questions, we performed NK cell treatment of a series of cell lines from hematologic malignancies by applying a pooled "DNA-barcoded" format of these cell lines (PRISM system). We specifically quantified the dose-dependent responses to primary NK cells for 70 molecularly-annotated blood cancer cell lines, including myeloid and lymphoblastic leukemia, diffuse large B cell lymphoma and 15 multiple myeloma (MM) lines, either in presence or in absence of BM stromal cells (BMSCs) and interferon gamma (IFNg), followed by integrated computational analyses to identify candidate molecular markers correlating with tumor cell sensitivity or resistance to NK cells. NK cell cytotoxicity, quantified by the relative abundance of barcodes in treated cells compared to controls, was correlated with the transcriptional, mutational and other molecular features of each of the 70 cell lines from publicly available databases. Furthermore, data from MM cell lines were compared to our genome-wide loss of function (LOF) and gain of function (GOF) CRISPR screen data in the MM cell line MM.1S. Two distinct clusters of cell lines, sensitive and resistant to NK cell treatment, were identified. Such clusters retained distinct pattern of in vitro resistance in the presence of stroma, while showing an overall markedly decreased NK cell responsiveness, which underscores the protective effect of stromal microenvironment in blood malignancies, regardless of the addition of IFNg. RNA-seq data showed no differences in dependencies between the two clusters and no distinct gene expression patterns at baseline that clearly allows to predict NK cell response, which underscores the heterogeneity of resistance patterns at single gene level, across different hematologic malignancies. However, when comparing baseline RNAseq data to data obtained from previous GOF and LOF CRISPR screens in MM.1S, surface antigens such as PVR, ULBP1, ULBP3 were more frequently downregulated, whereas MUC1 was upregulated in resistant cells clusters. An important observation is that gene lesions such as TP53, PTEN, MMSET, commonly associated with high-risk diseases, do not affect NK cell responses in the cell lines tested. Interestingly, a gene set enrichment analysis (GSEA) showed that the cluster of resistant cells displays upregulation of class I MHC complex, class II MHC complex binding, IL7 pathway and a downregulation of transmembrane receptor protein serine/threonine kinase signaling pathway. GSEA also showed that baseline state of IFN-JAK-STAT signaling correlates with BMSCs-induced NK cell resistance, a result further confirmed by addition of IFNgto tumor-NK cocultures in the absence of BMSCs. No significant differences in NK cell response were observed when comparing cell lines of different hematologic neoplasms, suggesting that candidate markers from these studies may be relevant across different hematologic malignancies. In conclusion, this is the first study of this size correlating the molecular annotation of different concurrently-treated hematologic cell lines with their response to a NK-based treatment in the context of BMSC interaction. This study of a large panel of pooled "DNA-barcoded" cell lines provided complementary and orthogonal information to our LOF and GOF screens, expanding our potential to identify and validate molecular markers for individualized use of NK cell-based therapies in hematologic malignancies. Disclosures Mustjoki: BMS: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Research Funding. Mitsiades:EMD Serono: Research Funding; Abbvie: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Arch Oncology: Research Funding; Fate Therapeutics: Honoraria; Ionis Pharmaceuticals: Honoraria; Takeda: Other: employment of a relative ; Janssen/Johnson & Johnson: Research Funding; TEVA: Research Funding.
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  • 5
    Publication Date: 2018-11-29
    Description: As multiple myeloma (MM) remains incurable, development of more effective novel therapies will require a deeper understanding of which genes, pathways and molecular networks thereof that govern the biological behavior of MM cells. The emergence of new CRISPR-based functional genomics approaches, including gene editing for loss-of-function (LOF) studies, allowed our group to obtain insight into the role of individual genes for MM survival and cell proliferation in vitro, in vivo and in the context of treatment resistance (e.g. De Matos Simoes et al., Shirasaki et al., Gandolfi et al. ASH 2017). Through these studies, we identified 50+ genes with more pronounced sgRNA depletion in MM cells vs. non-MM lines, which we consider MM-preferential essential genes. These genes include many transcription factors (TFs) such as IRF4, PRDM1, NF-κB, and MAF. We hypothesized that, while these transcription factors are individually important for MM cell survival and proliferation, they cooperate to regulate MM cell behavior in a manner that cannot be fully captured by 1st-generation, single knockout, CRISPR studies. To address this hypothesis, we performed CRISPR/Cas9 dual knockout (DKO) screens against a collection of ~100 genes, which included ~50 MM preferential dependencies; additional genes with broad-spectrum as dependency in in MM and other neoplasias (e.g. KRAS, BRD4, MCL1, BCL2); tumor suppressors (TP53, PTEN); genes which are frequently expressed in MM cells, but not are major dependencies for them in single knockout studies with CRISPR (e.g. ZBP1); as well as control sgRNAs). For these studies, we applied an "orthogonal Cas9" system: MM.1S cells expressing 2 different Cas9 nucleases (from S. pyogenes and S. aureus, respectively) received a pooled lentiviral library of constructs containing 2 sgRNAs per construct, with each sgRNA operating under one of these 2 Cas9 versions, to avoid possible imbalance in editing due to 2 sgRNAs competing for a single Cas9. Our custom library contained all the 5,000 pairwise combinations of dual KOs of the 100 selected genes and their respective single-gene KOs; with at least 4 sgRNAs per gene for each type of cas9, and for a total of ~54,000 single or double KOs represented in the screen. The study contained multiple different types of controls, including the ability to compare the single gene KO data contained within this DKO study vs. our single gene KO genome-scale screens, which we observed to be very similar. In our DKO study, IRF4 was identified as the most common and strongest synergistic partner with synergy scores (SynDKO score) 50% of its pairwise interactions with other genes of our study: the synergistic partners of IRF4 included MM-preferentially essential genes, broad-spectrum dependencies and non-essential genes for MM cells, indicating functional interactions of IRF4 with a broad spectrum of genes and its importance as a master regulator of MM cells. Other highly recurrent partners for synergistic interactions included MM-preferential dependencies such as TCF3, ZBTB38, PIM2, IKZF1 and EP300; other chromatin remodeling regulators such as CREBBP and ARID1A; or the anti-apoptotic Bcl-2 family members BCL2L1and MCL1. Interestingly, we observed that dual CRISPR knockout for both IKZF1 and IKZF3 did not produce a stronger anti-MM effect than the dual KO of either gene with IRF4 or single KO IRF4 alone. These results suggest that dual genetic depletion of IKZF1 and IKZF3, which simulates the pharmacological depletion of these transcription factors by thalidomide derivatives, induces an anti-MM effect that is quantitatively less pronounced than the knock-down of IRF4, alone or in combination with LOF of either IKZF1 or IKZF3, suggesting the value of further efforts to develop novel therapies to potently and comprehensively suppress the activity of IRF4. Interestingly, we noted that LOF of TP53 or PTEN attenuates the effect of LOF for several essential genes examined in our study, but not IRF4. To our knowledge this is the first study that leverages the power of CRISPR editing to systematically examine the functional interactions between pairs of MM genes. Our results point to several transcription factors, chromatin remodeling genes and anti-apoptotic regulators as "nodes" for recurrent synergistic pairwise-interactions with other genes and importantly identify IRF4 as central regulator in the hierarchy of these interactions in MM cells. Disclosures Mitsiades: EMD Serono: Research Funding; Janssen/ Johnson & Johnson: Research Funding; Abbvie: Research Funding; TEVA: Research Funding; Takeda: Other: employment of a relative.
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  • 6
    Publication Date: 2018-11-29
    Description: During the last two decades, cell lines and patient-derived samples from multiple myeloma (MM) have been extensively profiled for alterations in their genome with the anticipation that those genes with the most recurrent lesions could represent attractive novel therapeutic targets or markers for aggressive disease. Yet for many of these genes, their functional significance for MM cells has not been formally evaluated. With the advent of new CRISPR/Cas9-based functional genomics platforms, it is possible to generate in genome- or subgenome-scale direct quantitative information on the impact that perturbation of these genes exerts on tumor cell survival, proliferation or other phenotypes. We therefore examined the landscape of our CRISPR-based functional genomic data for these recurrently dysregulated genes We specifically curated information from the MMRF CoMMpass study and multiple other publicly available studies, to identify genes which are recurrently identified to harbor nonsynonymous mutation (SNV or indel), DNA copy number loss or gain, or participation in chromosomal translocations. We then examined the patterns of results for these genes in our genome scale CRISPR-based gene-editing studies for loss-of-function in n=18 MM cell lines. We identified a subset of genes (e.g. FAM46C, CDKN2C, RASA2) which are considered targets for recurrent loss-of-function events and indeed exhibit, for large fractions of the cell lines tested enrichment, of their sgRNAs in CRISPR knock-out studies, consistent with a role of these genes as suppressors of tumor cell survival or proliferation. CRISPR KO of TP53 leads to increased survival/proliferation of only a small minority (2/18 of cell lines tested thus far), which reflects the fact that the overwhelming majority of MM cell lines already harbor LOF events for this gene. Interestingly, a substantial number of genes which have been considered to harbor recurrent LOF events in MM patient samples (e.g. NF1, NF2, CYLD) do not exhibit sgRNA enrichment in CRISPR KO screens in the MM cell lines tested so far. In addition, several other recurrently mutated genes for which their loss- or gain-of-function status had not been previously evaluated with extensive functional studies in MM (e.g. SP140, LTB, EGR1, ATM, PARK2, PRKD2, RAPGEF5, DOCK5, TGDS, TNFAIP8) exhibit in the majority of cell lines tested in in CRISPR knockout studies no significant enrichment or depletion of their sgRNAs. In contrast, PTPN11, CREBBP, EP300, KMT2B, KMT2C, SETD2, SF3B1 and UBR5, are notable examples of recurrently mutated genes which represent dependencies for large fractions of MM cell lines in vitro. These results highlight the value of interpreting results from next generation sequencing studies in the context of information provided by the genome scale by use of functional genomic characterization of available cell line models. We envision that, similar sub-genome scale assays were performed at the level of patient derived samples will also provide direct information about the relevance of some of these genes. In addition, functional studies conducted with context of tumor-microenvironemtn compartment interactions and tumor interface will be needed to evaluate several genes identified in the study. Disclosures Licht: Celgene: Research Funding. Mitsiades:Takeda: Other: employment of a relative; Janssen/ Johnson & Johnson: Research Funding; Abbvie: Research Funding; EMD Serono: Research Funding; TEVA: Research Funding.
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  • 7
    Publication Date: 2019-11-13
    Description: In the last 2 decades, the improved clinical outcomes for multiple myeloma (MM) patients have been driven predominantly by therapeutics which exhibit limited activity outside plasma cell (PC) dyscrasias; do not target specific oncogenic mutations in MM cells, but rather pathways which are critical for PCs and dispensable for normal or malignant cells of most other lineages. We reasoned that identification of genes that are more potently / recurrently essential for MM cells, but less so for other neoplasias, would allow us to "re-identify" targets of currently used "PC-selective" anti-MM therapies. We also reasoned that systematic identification of MM-preferential dependencies could also uncover additional, previously underappreciated, genes which can serve as targets for potential future therapies and hopefully contribute to additional improvements in the therapeutic outcome for MM. To this end, we performed genome-scale CRISPR gene-editing studies to systematically characterize the molecular vulnerabilities of 20 MM cell lines and define which of these genes are more pronounced and/or recurrent dependencies for MM vs. cell lines (n=679) from other blood cancers and solid tumors. We identified 90+ genes whose function was significantly more essential for MM lines than other neoplasias. These MM-preferential dependencies included a large collection of transcription factors (e.g. IRF4, PRDM1, MAF, NFKB1, RELB, IKZF3, IKZF1, TCF3, CCND2, CBFB, MEF2C); transcriptional cofactors (e.g. POU2AF1); epigenetic regulators (e.g. EP300, DOT1L, HDAC1,ARID1A, CARM1); kinases such as IKBKB and CHUK/IKKa (both upstream of NF-κB), PIM2, IGF1R, SIK3,STK11; genes related to endoplasmic reticulum (ER) or Golgi function (e.g. HERPUD1, SYVN1,UBE2J1, SEC23B); as well as BCL2 and SMAD7. Results for several of these genes were further supported by in vitro studies with individual sgRNAs for CRISPR-based gene editing or activation of the respective genes; "addback" experiments with CRISPR-resistant cDNAs; shRNA studies in MM lines; use of small molecule inhibitors (e.g. against PIM kinases, CBFB, CARM1); and a focused in vivo CRISPR screen with MM.1S cells implanted in mice with BM-like scaffolds harboring a "humanized" stromal compartment: this latter in vivo study examined 46 MM-preferential dependencies which are also essential for MM.1S cells in vitro and observed that 41 of these genes were also essential for MM.1Scells in the "humanized" BM-like in vivo system. Some MM-preferential dependencies are essential for subsets of leukemia or lymphoma lines, but most have more pronounced/recurrent essentiality in MM vs. other blood cancers. In terms of overexpression (in high- vs. standard-risk MM; MM vs. normal PCs; or MM vs other cancers); frequency of mutations, DNA copy number gain or proximity to superenhancers, most of the MM-preferential dependencies do not exhibit such alterations or are not ranked in the top-100 genes in terms of the magnitude or frequency of these alterations. Notably, among the MM-preferential dependencies identified in our study, the majority are universally expressed in MM patient samples, while 〉80% and 〉75% of these genes have detectable transcript levels (RPKM〉1) in CD138+ cells from at least 50% or 80%, respectively, of newly-diagnosed MM patients (MMRF CoMMpass study), suggesting broad expression of these dependencies across MM patients, including individuals with high-risk disease. It was reassuring to observe that MM-preferential dependencies identified in our study include prominent known targets for therapeutics with relatively MM-selective clinical activity (e.g. thalidomide derivatives [IKZF1/IKZF3], proteasome inhibitors [NF-kappaB genes and ER function] or panobinostat [HDAC1]). The identification of these known genes as preferential MM dependencies provides a mechanistic explanation for the relatively selective clinical activity of the respective therapies in MM/PC dyscrasias and also underscores the promising therapeutic implications of the large number of additional and previously underappreciated / understudied MM-preferential dependencies identified in our CRISPR-based functional studies. Disclosures Boise: Genentech Inc.: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Research Funding. Gray:Gatekeeper, Syros, Petra, C4, B2S and Soltego.: Equity Ownership; Novartis, Takeda, Astellas, Taiho, Janssen, Kinogen, Voronoi, Her2llc, Deerfield and Sanofi.: Equity Ownership, Research Funding. Tsherniak:Tango Therapeutics: Consultancy. Mitsiades:Takeda: Other: employment of a relative ; Ionis Pharmaceuticals: Honoraria; Fate Therapeutics: Honoraria; Arch Oncology: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Abbvie: Research Funding; TEVA: Research Funding; EMD Serono: Research Funding; Janssen/Johnson & Johnson: Research Funding.
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  • 8
    Publication Date: 2018-11-29
    Description: Natural killer (NK) cells represent a promising immunotherapeutic approach as they can potently kill tumor cells without triggering graft-versus-host reactions. Indeed, infusion of high numbers of NK cells, either autologous or allogeneic, after their ex vivo expansion and activation, has been feasible and safe in clinical studies. However, prior studies and early clinical trials indicate that tumor cells can exhibit decreased response to NK due to the protective effect of nonmalignant mesenchymal stromal cells; and depending on the genetic background of the tumor cells. To our knowledge, since earlier subgenome-scale RNAi-based studies, there have been no genome-wide CRISPR-based screens to identify candidate markers conferring tumor cell resistance or sensitivity to NK cells in multiple myeloma (MM). To address this void, and building on a recent loss-of-function (LOF) study by our group on solid tumors, we sought to identify genes regulating the response of MM cells to the cytotoxic activity of NK cells by conducting a genome-wide CRISPR/Cas9-based gene editing (Brunello library of sgRNA) and gene activation (Calabrese library of sgRNA) screens in MM.1S cells co-cultured with primary NK (pNK) cells (effector-to-target [E:T] ratio of 3.75:1) derived from healthy donor peripheral blood mononuclear cells (PBMCs) cultured in vitro in GMP SCGM medium with IL-2. Briefly, MM.1S cells engineered to stably express the nuclease SpCas9 (Brunello) or a catalytically inactive programmable RNA-dependent DNA-binding protein (dCas9)-VP64 (Calabrese) were also transduced with lentiviral particles for a pool of ~70,000 (Brunello library) or ~120,000 (Calabrese) sgRNAs, targeting exons of ~20,000 genes (plus non-targeting control sgRNAs), under conditions of transduction which allow for an average of no more than 1 sgRNA to be incorporated in a given cell. This allowed us to convert the initial population of MM.1S cells into heterogeneous pools in which each gene is subject to individual LOF or gain-of-function (GOF), due to Cas9-mediated editing, by only 1 sgRNA. Flow cytometry was performed to verify pNK viability, purity (CD56 and CD3), and expression of p46 receptor, surrogate marker of NK cell activity. These screens identified genes whose knock-out (Brunello sgRNA library) or activation (Calabrese sgRNA library) led to NK cells resistance or potential sensitivity. The hits observed in the current MM-oriented study exhibited, compared to our similar studies in solid tumor model, substantial gene level differences, but notable overlap at the pathway level (including death receptor pathways, NK activating pathways), which suggests that mechanisms determining tumor cell response vs. resistance to NK cells operate through modules consistent across tumors, but manifested through potentially different members of the respective pathways in different neoplasms. For instance, in this MM-oriented study, we identified that NK cell sensitivity of tumor cells is modulating by activation of several metabolic and homeostatic genes, receptor kinases, and interestingly membrane-bound proteins of the mucin family, e.g. MUC1, and MUC4, which have been reported to play a role in NK-mediated tumor killing in other types of cancer. MUC1 in particular has a clinical relevance as a small molecule inhibitor with prior preclinical studies in MM is available. Interestingly, our GOF screen identified as potential NK cell sensitizers TNFRSF10B, a death receptor related to TNFRSF10A (a hit identified in our studies in solid tumors), the putative death receptor adaptor TRADD, and the NK ligands PVR and ULBP1. Interestingly, genes such as PTEN and TP53, commonly associated with high-risk MM, didn't affect the response to NK cell, suggesting that NK cell-based therapies may potentially have a role in treatment of MM patients with high-risk clinical or biological features. In conclusion, this is the first study applying both LOF and GOF genome-wide screens to NK cell response in MM. The combination of such screens performed in parallel provide complementary and orthogonal information that allows us to identify genes that might not have been appreciated if only either LOF or GOF alone screens had been performed. We envision that the methodology and results presented herein will provide a framework towards validation of molecular markers which can help to optimize and individualize the use of NK cell-based therapy in MM. Disclosures Mitsiades: Abbvie: Research Funding; TEVA: Research Funding; EMD Serono: Research Funding; Janssen/ Johnson & Johnson: Research Funding; Takeda: Other: employment of a relative.
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  • 9
    Publication Date: 2018-11-29
    Description: Heterobifunctional proteolysis-targeting chimeric compounds leverage the activity of E3 ligases (e.g. CRBN and VHL) to induce neopmorphic ubiquitination and proteasomal degradation of target oncoproteins, with potent preclinical activity against diverse neoplasias. Despite intense recent efforts to develop pharmacological "degraders" against many different oncoproteins, the mechanisms regulating tumor cell sensitivity to different classes of these "degraders" remain incompletely understood. To address this question in an unbiased manner, we performed genome-scale CRISPR/Cas9-based gene editing loss-of-function (LOF) studies in MM.1S multiple myeloma (MM) cells treated with CRBN-mediated degraders of BET bromodomain proteins (dBET6) or CDK9 (Thal-SNS-032); or with VHL-mediated degraders of BET bromodomain proteins (ARV-771 or MZ-1). We observed that MM cell resistance to any of these "degraders" does not involve genes with recurrent LOF in MM patients and association with high-risk MM (e.g. for TP53, PTEN, negative regulators of cell cycle, et.c.), suggesting that these degraders may exhibit activity against tumor cells with prognostically adverse genetic features. In tumor cells resistant to the CRBN-mediated degraders dBET6 and Thal-SNS-032, we observed significant enrichment of sgRNAs targeting CRBN itself or (to a lesser extent) other components or regulators of its cullin RING ligase (CRLCUL4A) complex, including members of the COP9 signalosome (COPS7A, COPS7B, COPS2, COPS3, COPS8, GPS1, etc.), DDB1, or the E2 ubiquitin conjugating enzyme UBE2G1. In tumor cells resistant to the VHL-mediated degraders MZ-1 and ARV-771, we observed pronounced enrichment of sgRNAs for CUL2, VHL itself, other members (e.g. RBX1, elongin B/C [TCEB1, TCEB2] of the CUL2 complex with VHL), as well as COP9 signalosome genes (COPS7B, COPS8) and UBE2R2. We also validated, using individual sgRNAs for several of these candidate genes that their CRISPR knockout can decrease tumor cell response to dBET6 and Thal-SNS-032 treatment (e.g. for CRBN, COPS7B, COPS2, or COPS8) or MZ-1 and ARV-771 (e.g. for VHL, COP7B and COPS8). Notably, the sgRNAs against COP9 signalosome genes conferred less pronounced decrease in sensitivity to VHL-, than CRBN-based, degraders, suggesting that COP9 signalosome loss has differential roles in the function of CUL4ACRBN vs. CUL2VHL and potentially other CRL complexes. Tumor cells isolated from our CRISPR knockout screens with confirmed resistance to a given degrader were then treated with other degraders operating through the same or different E3 ligase; and against the same or different oncoprotein: we observed cross-resistance between degraders operating through the same E3 ligase against different oncoproteins, but not for degraders targeting the same protein via different E3 ligase/CRLs: this result is consistent with our observation for substantial gene-level differences (despite pathway-level similarities) for resistance mechanisms for CRBN- vs. VHL-based degraders. In conclusion, our study systematically defined at genome-scale the resistance mechanisms of tumor cells against degraders which leverage the same E3 ligase against different targets; or target the same oncoprotein through different E3 ligases/CRL complexes. We observed that for multiple types of degraders, tumor cell resistance is primarily mediated by prevention of, rather than adaptation to, breakdown of the target oncoprotein. The observed pathway-level similarities and major individual gene-level differences in resistance mechanisms for CRBN- and VHL-mediated degraders likely reflects the different composition and regulation of the respective CRL complexes mediating the action of these classes of degraders Our observations suggest that preventing or delaying resistance to pharmacological degradation of oncoproteins may require concurrent or sequential/alternating use of degraders operating through different E3 ligases and ideally, different CRL complexes; while synthetic lethal strategies to prevent COP9 signalosome LOF may also be contemplated to counteract a common, but quantitatively less pronounced, potential mechanism of resistance for several different classes of degraders. Collectively, our study highlights important new directions in the development of new pharmacological degraders for blood cancers and other neoplasias. Disclosures Richardson: Karyopharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Licht:Celgene: Research Funding. Boise:Abbvie: Consultancy; AstraZeneca: Honoraria. Gray:C4 Therapeutics: Consultancy. Mitsiades:TEVA: Research Funding; Janssen/ Johnson & Johnson: Research Funding; EMD Serono: Research Funding; Takeda: Other: employment of a relative; Abbvie: Research Funding.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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    Publication Date: 2016-07-10
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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