ALBERT

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.

Description: Myeloablative high-dose melphalan (HDM) followed by autologous stem cell transplantation (ASCT) remains one of the cornerstones of multiple myeloma (MM) treatment. Conceptually, HDM is based on the notion that a single melphalan dose (typically 200 mg/m2) exceeding the myelotoxicity threshold is associated with a steep increase in the dose response curve and higher degree of MM cell killing compared to fractionated delivery (without the need for hematopoietic stem cell support) of the same cumulative dose. Despite its importance in the therapeutic management of MM, HDM-ASCT is not considered a curative procedure, presumably because chemoresistant subpopulations of MM cells survive HDM and lead to eventual relapse. Elucidating the molecular mechanisms responsible for resistance to HDM in MM could have major implications for the identification of patients with the highest probability of major clinical benefit from this procedure. However, these resistance mechanisms remain incompletely understood. To address this void in the field, we examined whether an open-ended unbiased genome-wide functional characterization of MM cells could uncover genes associated with resistance to HDM and quantify the degree to which other, non-genetically determined, mechanisms of resistance contribute to this process. Specifically, we used the human myeloma cell line MM1.S, transduced with lentiviral construct for the Cas9 nuclease and with pooled lentiviral particles of the GeCKO library (Shalem et al., 2014), which consists of 2 pooled single guide RNA (sgRNA) sub-libraries (~120,000 sgRNAs; targeting ~19,000 genes and ~1800 miRNAs). Using this CRISPR/Cas9-based approach to mutagenize and cause loss of function of the genes recognized by the respective sgRNAs, we sought to facilitate the prospective isolation of MM cells resistant to HDM. To better simulate the exposure of MM cells to HDM in the autologous transplant setting, we adapted our in vitro treatment to include an initial dose of 25 µM of melphalan and sequential one-hour interval partial wash-outs, to achieve gradual reduction of melphalan concentrations, consistent with the pharmacokinetic profile observed in the clinical setting (Nath et al., 2010). We repeated twice the genome-wide knock-out screens, with biological replicates on both the transduction and cell culture level (maintaining a coverage of at least 1000 cells per individual sgRNA). While the in vitro simulation of clinical HDM with our wash-out regimen achieved 〉99% estimated reduction in MM cell viability in both screens, viable cells re-emerged in cultures from all biological and technical replicates. HDM-resistant cells were processed to quantify their sgRNA enrichment or depletion, using next generation sequencing, and also characterize the sensitivity of these MM cells to repeat exposure to HDM concentrations consistent with the genome-wide CRISPR screens. We observed that, despite having survived a previous round of exposure to HDM, the majority (〉90%) of these sgRNA-transduced cells were again highly responsive to repeat treatment with HDM. A similar result was also obtained with MM1.S cells which had not been previously transduced with the sgRNA sub-libraries. While ongoing investigation in our lab addresses these findings on additional MM cell lines, these observations on a well-established MM cell line model of melphalan responsiveness raises the intriguing possibility that genetically-determined forms of HDM resistance, conferred after an unbiased genome scale evaluation through the CRISPR/Cas9-editing methodology, may only represent a small fraction of the MM cells which survive a round of HDM treatment, and that other non-genetically determined mechanisms may mediate the principal mode of resistance, even in the cell autonomous context of our experiments. In turn, this suggests that future efforts to individualize the administration of HDM-ASCT in patients and their post-ASCT monitoring should not rely exclusively on genetic markers identified and validated from preclinical experimentation with repeated rounds of MM cell exposure to the equivalent of myelotoxic melphalan concentrations. Instead, renewed emphasis is warranted on identification of functional markers correlating with the ability of MM cells to develop transient resistance to HDM, even in the absence of constitutive genetically-determined mechanisms of resistance. Disclosures Mitsiades: Novartis: Research Funding; TEVA: Research Funding; Janssen/Johnson & Johnson: Research Funding.

Description: The discovery that thalidomide derivatives recruit the E3 ligase CRBN to induce neomorphic degradation of proteins critical for multiple myeloma (MM) cells stimulated the research into proteolysis-targeting chimeric compounds (PROTACs), led to development of several CRBN- or VHL-based PROTACs against various oncoproteins and put a new spotlight on the biology and therapeutic targeting of E3 ligases in human neoplasias. However, so far only a few of the ~600 known/presumed E3 ligases have been leveraged for generation of PROTACs. The mechanisms regulating the function of most E3 ligases have not been systematically examined. Because the function of an E3 ligase is considered essential for anti-tumor activity of its respective PROTACs, we applied CRISPR knock-out (KO) systems to identify candidate regulators of E3 ligase function, via characterizing the the network of genes which modulate MM cell responses to PROTACs. We thus performed genome-scale CRISPR-based gene editing (for loss-of-function, LOF) studies in MM.1S cells treated with PROTACs targeting BET bromodomain proteins through MDM2 (A1874), CRBN (dBET6) or VHL (ARV-771 or MZ-1) or targeting CDK9 through CRBN (Thal-SNS-032); and validated key hits with individual sgRNAs in different MM cell lines. The top individual LOF events conferring resistance to PROTACs did not involve a compensatory mechanism or "work-around" the loss of the respective oncoprotein, but were predominantly associated with LOF of the respective E3 ligase; or with LOF for genes with known or plausible role in regulating the respective E3 ligases. For instance, sgRNAs against members of the COP9 signalosome complex decreased MM cell responses to CRBN- and (to a lesser extent) VHL-, but not MDM2-based PROTACs. PROTACs leveraging different E3 ligases were regulated by different cullin ring ligase (CRL) complex members (e.g. CUL2, RBX1, TCEB1, TCEB2 for VHL- vs. DDB1 for CRBN- vs. no CRL member for MDM2-based PROTACs) or E2 conjugating enzymes (UBE2R2 vs. UBE2G1 for VHL- vs. CRBN-based PROTACs). Collectively, these results suggest that MDM2 regulation is largely CRL- and COP9-signalosome independent; while VHL regulation is less COP9 signalosome-dependent compared to CRBN. These mechanistic differences suggest that PROTACs targeting the same oncoprotein through different E3 ligases should not be associated with cross-resistance, a result which we validated in experiments involving sequential administration of different PROTACs against BRD4/3/2. In turn, this observation implied that developing PROTACs that leverage a more extended spectrum of E3 ligases may facilitate sequential uses of existing and these new PROTACs to delay or prevent treatment resistance. Building on results of our genome-scale CRISPR essentiality screens, we examined the dependency landscape of known E3 ligases of MM (n=20 cell lines) and 500+ non-MM cell lines. CRBN is redundant for nearly all MM or non-MM cell lines tested, while most other E3 ligases leveraged for PROTACs (e.g. MDM2, BIRC2, DCAF15, DCAF16, RNF114) are essential for only modest or small subsets of human cancer cell lines, suggesting that resistance to respective PROTACs may readily emerge through LOF of these E3 ligases without major fitness cost to tumor cells. We thus sought to identify E3 ligases which are highly expressed in subsets of human tumor cell lines (at levels well above the large majority of normal tissues) and are major dependencies for these "high expressor" cell lines: we identified MDM2 as a major dependency for p53-wild-type cell lines (consistent with MDM2 role as E3 ligase for p53) and we validated this result by documenting the preferential activity of a MDM2-based PROTAC for BRD4/3/2 against p53 wild-type cells. We also identified other E3 ligases genes with well-known roles in tumor cell biology (e.g. members of anaphase promoting complex/cyclosome); as well as E3 ligases (e.g. KCMF1, RNF4) which, to our knowledge, have not been leveraged for design of PROTACs, but warrant consideration given their patterns of essentiality in "high expressor" tumor cells. Our study provides insights on differential regulation and distinct patterns of essentiality for different E3 ligases and informs the design of new PROTACs which leverage different E3 ligases to help delay/overcome treatment resistance in MM and beyond. Disclosures Schlossman: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Richardson:Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: 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; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees. Ebert:Broad Institute: Other: Contributor to a patent filing on this technology that is held by the Broad Institute.; Celgene: Research Funding; Deerfield: Research Funding. Tsherniak:Tango Therapeutics: Consultancy. 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. 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.