ALBERT

Description: Waldenström macroglobulinemia (WM), a malignant B-cell lymphoplasmacytic lymphoma, is a rare subtype of non-Hodgkin lymphoma representing about 1% of all cases. To better understand the WM pathogenesis, we performed large-scale data-driven proteomic profile of WM tumor cells associated with tumor-driven immune changes in the tumor microenvironment of 66 bone marrow (BM) samples from WM patients compared to 10 age-matched healthy donors (HD) by time-of-flight mass cytometry (CyTOF) technology. Our workflow has been designed based on extensive 3 CyTOF antibody panels to evaluate WM tumor within B cell lymphopoiesis concurrently with immune landscape of the tumor microenvironment in WM by state-of-art technology CyTOF. To map B cell lymphomagenesis in WM, we defined whole spectrum of maturation of B cell development, from hematopoietic stem cells and B cell precursors through immature B cells, transitional B cells, and naïve B cells together with memory un-switched and switched B cells, plasmablasts and plasma cells in BM samples of WM patients by positive and negative co-expression of 13 B cell-stage specific markers. Various immunophenotyping aberrancies within WM B lymphomagenesis were associated with WM clones characterized by significant increase of 11 B subset clusters from un-switched and switched memory B cells to plasma cells. Interestingly, WM clusters differ in intra-clonal expression of activation surface molecules (CD23, CD24, CD25, CD81, CD329, CD200, and CD319); transcriptional factors and regulators controlling B cell development (MYD88, Bcl-6, IRF-4, sXBP-1, and FGFR-3) and stemness-related markers (Oct3/4, Nanog, Sox-2, c-Myc, and Notch-1) in WM supporting the idea of sub-clonal heterogeneity insight of WM tumor. Moreover, decrease in cell frequency of B cell precursors (pro-B and pre-BI), naive B cells, and plasmablasts were observed in WM patients versus HD. To generate a comprehensive view of the tumor microenvironment, we observed significant upregulation of g/dT cells, CD4+ and CD8+ T effector cells, CD8+ T effector memory cells, monocytes, and neutrophils immune subsets and downregulation of immature T cells, CD8+ T naïve cells, plasmacytoid dendritic cells, myelo/mono progenitor clusters. Ibrutinib (IBRU) treatment has been effective in relapsed/refractory WM patients; therefore highest numbers of WM patients were receiving IBRU therapy in our cohort. IBRU treated WM patients had decreased frequency of naive B, CD4+ T naive cells and specific clusters of un-switched and switched memory B cells. Moreover, responder versus non-responders to IBRU therapy revealed increase of CD8+T effector memory cells. In sum, correspondence analysis reflecting data of each patient and immune subsets revealed stratification of WM patients with reflection on their clinical outcome, therefore providing the rational for prediction of WM patient status. This study was supported by APVV-16-0484 and VEGA 2/0076/17. Disclosures Hunter: Janssen: Consultancy. Richardson:Karyopharm: 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; 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. Kastritis:Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria. Treon:BMS: Research Funding; Janssen: Consultancy; Pharmacyclics: Research Funding. Anderson:Celgene: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board; Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau.

Description: Lymphomas represent nearly 70 distinct diseases with unique clinical presentations, therapeutic responses and underlying biology. There is a pressing shortage of publically available cell line and in vivo models of nearly all of these diseases, which has severely hampered efforts to understand and target their biology. To address this issue, we have established a repository of patient-derived xenografts (PDX) of lymphomas by engrafting human tumors into immunodeficient NOD/SCID/IL2rgnull (NSG) mice. These lymphomas, along with a spectrum of other PDXs of hematologic malignancies, are available to collaborators through the online portal PRoXe (Public Repository of Xenografts) at http://PRoXe.org. Blood and bone marrow specimens involved with tumor are injected by tail vein (IV) injection. Lymph node and extranodal biopsy specimens are implanted under the renal capsule as a 1x1x2mm tumor seed (renal), which maintains the in situ microarchitecture. A full description of xenografted lymphomas is included in the Table. Table 1.DiseaseType of implant# in 1st passage# in 2nd passage or higherT-cell prolymphocytic leukemiaIV1Angioimmunoblastic T-cell lymphomaIV11Mantle cell lymphomaIV12Double-hit DLBCLIV2Sézary SyndromeIV1Adult T-cell Leukemia/LymphomaIV1Diffuse large B cell lymphomaIV2Diffuse large B cell lymphomarenal2Marginal zone lymphomarenal11NK/T-cell lymphomarenal1Peripheral T-cell lymphoma-NOSrenal1Breast implant-associated anaplastic large cell lymphomarenal1 Engrafted PDXs have been extensively characterized by immunohistochemistry, flow cytometry, transcriptome sequencing and targeted DNA sequencing. Flow cytometric analysis of patient tumors and their respective xenografts consistently revealed highly concordant immunophenotypes compared to the original tumors. Similarly, immunohistochemistry of involved tissues confirmed retention of tumor immunophenotypes, architecture, and even tissue tropism in the PDXs. Examples include a Sézary syndrome PDX that was injected by tail vein and trafficked to spleen, bone marrow, blood and skin, a diffuse large B-cell lymphoma (DLBCL) PDX that infiltrated the CNS, and a second DLBCL PDX that was implanted into the renal capsule of the left kidney and progressed within 8 weeks to bilateral renal involvement. Other notable models include a breast implant-associated, ALK-negative anaplastic large cell lymphoma implanted under the renal capsule that metastasized to the liver and spleen while uniformly retaining CD30 positivity. Two double-hit lymphoma (DHL) PDXs maintained their CD20-negative phenotype through serial passage to P1. A peripheral T-cell lymphoma-NOS (PTCL) specimen implanted under the renal capsule engrafted in the spleen, with a notable admixture of nonmalignant T cells and scattered EBV-positive B cells. T-cell receptor gene rearrangement PCR performed on this PTCL demonstrated an identical rearrangement pattern in the primary tumor and the PDX. Luciferized mantle cell lymphoma and DHL PDXs clearly home to bone marrow, lymph nodes, spleen, and liver as early as two weeks after injection. These findings support the utility of these PDX lines as in vivo models that more accurately recapitulate the human disease than commonly used subcutaneous cell line models. In addition to generating PDXs that remain faithful to their source tumors, we have witnessed interesting examples of in vivo histologic transformation, opening the door to studies of disease progression. One primary follicular lymphoma specimen injected into a cohort of mice transformed to DLBCL in one mouse and a lymphoblastic lymphoma-like disease in another mouse, as confirmed by IHC and flow cytometry. Further xenografting of primary tumors is underway with the goal of establishing a large repository of lymphoma PDXs useful for biologic interrogation and preclinical trials. Disclosures Davids: Genentech: Other: ad board; Pharmacyclics: Consultancy; Janssen: Consultancy. Shipp:Gilead: Consultancy; Sanofi: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees.

Description: To expedite the translation of biologic discoveries into novel therapeutics, there is a pressing need for panels of in vivo models that capture the molecular complexity of human disease. While traditional cell lines and genetically engineered mouse models are useful tools, they are insufficient to assess the broad diversity of human tumors within a context that recapitulates in situ biology. Patient-derived xenografts (PDXs), generated by transplanting primary human tumor cells into immune-deficient NOD.Cg-Prkdcscid/Il2rgtm1Wjl/SzJ (NSG) mice, surmount some of the limitations of these traditional platforms and have been increasingly utilized as tools for preclinical investigation. However, the infrastructure required to generate, bank, and characterize PDX models limits their availability to only a few investigators. To address this issue, we established a repository of PDX models of leukemia and lymphoma, which we have named the Public Repository of Xenografts (PRoXe). At the time of this writing, PRoXe contains 213 independent lines that have been passaged through mice once (P0), 123 of which have been repassaged in a second generation (P1) or further repassaged. The repository encompasses AML, B- and T-ALL, and B- and T-cell non-Hodgkin lymphoma (NHL) across a range of cytogenetic- and molecularly-defined subtypes (Table 1). PRoXe is extensively annotated with patient-level information, including demographics, phase of treatment, prior therapies, tumor immunophenotye, cytogenetics, and molecular diagnostics. PDX lines available for distribution are characterized by immunophenotyping, whole transcriptome sequencing (RNAseq), and targeted exon sequencing of ~300 genes. To confirm fidelity of engrafted tumors to their corresponding clinical samples, lymphomas were morphologically assessed in P0 mice by H&E and, when pathologic adjudication was required, by immunohistochemistry. Xenografted leukemias were compared to their original tumors immunophenotypically. Unsupervised hierarchical clustering was performed on 132 of these lines based on transcriptome sequencing data and demonstrated 94% concordance between classification of the PDX lines by RNA expression and by the annotated clinical-pathologic diagnoses. Discordant cases highlighted unusual variants, such as B-ALL with aberrant expression of myeloid markers and a follicular lymphoma that underwent blastic transformation in the mouse. Multiple lines have been luciferized and confirmed to home to bone marrow, spleen, and liver. Existing lines from PRoXe have already been shared with more than ten academic laboratories and multiple industrial partners. All of the data referenced here are freely available through a customized web-based search application at http://proxe.org, and lines can be requested for in vitro or in vivo experiments. We are actively expanding the size of PRoXe to allow for large pre-clinical studies that are powered to detect differences across genetically defined subsets. Thus, we are happy to host additional lines from outside investigators on PRoXe and thereby expand the availability of these valuable reagents. Finally, we have made the source code for PRoXe (in R Shiny) open-access, so that other investigators can establish their own portals. Table 1. WHO diagnostic entities encompassed within PRoXe at P1 or later, or P0 or later for B-ALLs. WHO Classification - number of lines per diagnostic entity AML, Other Myeloid, and Ambiguous Lineage [n=32] ALL [n=107] AML - recurrent gene mutations 6 B-ALL - NOS 44 AML - MDS-related changes 5 B-ALL - MLL-rearranged 11 AML - NOS 4 B-ALL - BCR-ABL 10 AML - MLLT3-MLL 2 B-ALL - hyperdiploidy 9 Acute myelomonocytic leukemia 1 B-ALL - TEL-AML1 8 Acute monocytic leukemia 1 B-ALL - E2A-PBX1 3 AML unable to classify 2 B-ALL unable to classify 1 Blastic plasmacytoid dendritic cell neoplasm 8 T-ALL 21 Mixed phenotype, MLL rearranged 1 B/myeloid acute leukemia 1 Myelodysplastic syndrome 1 Mature B cell neoplasms[n=11] Mature T and NK cell neoplasms [n=4] DBLCL - NOS 4 Angioimmunoblastic T-cell lymphoma 1 Mantle cell lymphoma 3 Adult T-cell leukemia/lymphoma 1 Extranodal marginal zone lymphoma 1 Extranodal NK/T-cell lymphoma 1 B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and BL 3 SŽzary syndrome 1 Disclosures Konopleva: Novartis: Research Funding; AbbVie: Research Funding; Stemline: Research Funding; Calithera: Research Funding; Threshold: Research Funding. Etchin:Karyopharm: Research Funding. Lane:Stemline Therapeutics, Inc.: Research Funding. Stone:Abbvie: Consultancy; Novartis: Research Funding; Celator: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Agios: Consultancy; Sunesis: Consultancy, Other: DSMB for clinical trial; Merck: Consultancy; Karyopharm: Consultancy; Roche/Genetech: Consultancy; Pfizer: Consultancy; AROG: Consultancy; Juno: Consultancy.

Description: Background: Despite mycosis fungoides (MF) and Sezary syndrome (SS) comprising the most common forms of cutaneous T cell lymphoma, the pathophysiology underlying these disorders remains poorly understood. Consequently, current prognostic guidelines based on disease spread exhibit wide variations in clinical outcome within each stage, underscoring an urgent need for novel approaches to MF/SS disease evaluation. A growing body of research suggests that systemic immune dysregulation represents an early, cardinal feature of MF/SS. We hypothesized that tracking this immune dysfunction in conjunction with disease spread may generate important pathophysiologic and prognostic information for patients. We focused on myeloid-derived suppressor cells (MDSCs), a recently discovered population of immunosuppressive innate immune cells related to neutrophils and monocytes, because their expansion in numerous solid tumor settings have correlated reliably with poor patient outcomes. Whether MF/SS augments circulating MDSC abundance remains unexplored, prompting us to evaluate whether this could serve as a marker for disease progression and treatment response. Methods: We used multiparametric flow cytometry to analyze the frequency and immunophenotype of MDSCs from the peripheral blood of 15 healthy donors and 30 patients with MF/SS. Patients at varying stages of MF/SS disease progression and treatment were included in the study. We defined granulocytic MDSCs (G-MDSCs) as cells positive for CD15, CD11b, and the recently discovered surface marker LOX-1, and negative for CD14. Monocytic MDSCs (M-MDSCs) were defined as cells positive for CD14 and CD11b, negative for CD15, and low/negative for HLA-DR. Each patient sample also underwent flow cytometry evaluating for circulating neoplastic T cells. These results were correlated with each participant's other hematologic parameters and clinical information through manual chart review. Results: We found that healthy donors harbored no quantifiable circulating MDSCs of either monocytic or granulocytic lineage, a result in keeping with previous studies. In contrast, MF/SS patients exhibited robust, statistically significant increases in the frequencies of both G-MDSCs and, to a lesser extent, M-MDSCs. G-MDSCs exceeded 20% of all CD15-positive cells in some patients. When patients were stratified by MF/SS clinical stage, those with more advanced disease displayed significantly higher G-MDSC abundance than early-stage patients. G-MDSC frequency was positively correlated with circulating CD4+ CD26- T cell counts often used in evaluating Sezary syndrome (R2 = 0.498; p 〈 0.0001). However, patients with early, skin-restricted disease also showed statistically significant increases in circulating G-MDSCs compared to healthy controls. This suggested that G-MDSC expansion may serve as a sensitive, blood-based disease marker even in the absence of systemic involvement by neoplasia. Patients who underwent recent treatment exhibited variable G-MDSC counts in the peripheral blood that were lower than in similar untreated patients on average. Serial measurements for two patients enrolled in a clinical trial for dual phosphoinositide 3-kinase and histone deacetylase inhibition revealed that G-MDSC frequencies markedly decreased over the course of treatment, mirroring the decrements of aberrant T cells circulating in the blood. Conclusion: These findings provide clear evidence of G-MDSC expansion in the peripheral blood of MF/SS patients that begins in early/locally restricted disease, grows with disease progression, and responds to systemic therapy. Such immunometric assays may illuminate a novel source of staging and prognostic information and may permit less invasive disease monitoring than current methods require. Disclosures No relevant conflicts of interest to declare.

Description: Introduction. Growing evidence suggests that immune cells that reside within the tumor microenvironment are dysregulated and functionally impaired, leading to defective anti-tumor immunity of the host. One of the major immunosuppressive mechanisms during tumor progression is expansion of regulatory immune cells. Here, we analyzed the immune cells within the bone marrow (BM) and the peripheral blood (PB) of 2 immunocompetent multiple myeloma (MM) mouse models. We next studied the role of regulatory T cells (Tregs) in MM pathogenesis. Materials and methods. To study the immune cell populations of the BM and PB, we used two immuncompetent mouse models and transplanted VK*MYC cells or 5TGM1 cells into C57BL/6 and C57BL/Kalwrij mice respectively. The immune cell populations and checkpoint receptor expressions were analyzed by CyTOF mass cytometer or flow-cytometry. Treg induction assay was performed in vitro to study the mechanism of Treg increase in the BM of myeloma injected mice. CD4+ CD25- cells were obtained from C57BL/Kalwrij mice and were co-cultured with 5TGM1 cells or B cells from C57BL/Kalwrij mice in vitro. Treg induction was compared by flow-cytometry. Transplantable VK*MYC cells were injected into "depletion of regulatory T cell" (DEREG) mice, which expresses a simian diphtheria toxin (DT) receptor-enhanced GFP fusion protein under the control of the FOXP3 gene locus, or their wild type littermates. DT injection into these mice leads to depletion of Tregs as previously described (J Exp Med. 2007; 204: 57-63). DT was given once every week for a total 3 times i.p to the DEREG mice or the littermate controls to specifically deplete Tregs and to study the role of Tregs during MM progression. Tregs (CD4+ FOXP3-GFP+ cells) were sorted from VK*MYC injected mice or non-injected DEREG mice BM using FACSAria cell sorter. Cells isolated were subjected to RNA sequencing. Gene Set Enrichment Analysis (GSEA) was performed to define differences in molecular signatures between MM-associated and normal Tregs. Results. The Treg proportion was significantly increased within the CD4+ T cells in the BM of myeloma cell injected mice from the early stage of disease compared to control mice, while in the PB, the increase was observed only at the late stages of disease progression. The effector T cell (Teff)/Treg ratio was significantly decreased in the BM at the end-stage myeloma bearing mice (P

Description: Background: Receptor for hyaluronan-mediated motility (RHAMM) or CD168 has been a promising target for MM immunotherapy because it is overexpressed in MM cells. RHAMM has been tested as a target for an anti-RHAMM peptide vaccination approach in MM and other hematological malignancies. Although RHAMM peptide-induced immune response in patients, clinical outcomes were mixed, that can be a result of equal expression levels of RHAMM in different subpopulation of bone marrow (BM) cells in MM patients and healthy donors (HD). To enhance current RHAMM-peptide and future immunotherapeutic approaches, we investigated the cause of altered RHAMM mRNA splicing in MM patients. mRNA splicing has the potential to produce numerous mis-spliced genes, creating novel disease markers; some resulting proteins are likely to contain neoantigens selectively expressed on MM tumor cells. Methods/results: Splicing alterations can be caused by single nucleotide variations (SNVs) that affect splicing regulatory elements (SREs), or by deregulated splicing factors (SFs). We evaluated the incidence of SNVs located in the vicinity of the RHAMM. We identified a total of 57 SNVs: 72% SNVs are in the intronic region, and 28% are in the RHAMM coding region. We used the "HEXplorer" tool and predicted that four SNVs have the potential to contribute to aberrant RHAMM splicing in MM either by altering SF binding to SREs or by impacting splice site selection. Predicted SNVs were evaluated using an in vivo splicing assay to identify SNV-clusters causing aberrant RHAMM splicing. We have observed progressive overexpression of core SF PTBP1/2 (polypyrimidine track-binding protein) in MM patients and associated with disease progression. Since SNVs on the RHAMM modulate canonical SF binding sites, we tested the effects of PTBP1/2 deregulation on RHAMM splicing. We expressed PTBP1/2 in H929 cells, and then evaluated the RHAMM splicing pattern in transfected cells at a single cell (SC) level. SC analyses showed that overexpression of PTBP1/2 increased (2.5-fold) the RHAMM-V3:FL ratio in MM cells. SC analyses also identified overexpression of the RHAMM-V3 splice variant in 18% of H929 SCs expressing PTBP1, and in 37% of cells expressing PTBP2, confirmed at the single cell (SC) level. In BM-infiltrating myeloid cells, analyses showed 50% of myeloid cells express the RHAMM-V3 variant alone, and 79% of plasma cells (PCs) express this variant in combination with RHAMM-FL. Moreover, the RHAMM-V3/FL ratio in PCs is elevated (2.6-fold), further confirming a correlation between the RHAMM variant ratio and the clinical outcome. Next, we determined RHAMM-V3/FL ratios in BM stromal cells from 16 MM patients: MM-BMSC samples exclusively express the RHAMM-V3 in combination with RHAMM-FL and the RHAMM-V3:FL is 1.8 fold. In BMSC samples derived from healthy donors (HD), we detected relatively low-level expression of RHAMM-FL as compared to expression levels of RHAMM-FL in MM patients, while RHAMM-V3 transcripts were undetectable. SC analysis of RHAMM FL and splice variant transcripts in MM BMSC and HD-BMSC agreed with the analyses done on the MM HD-BMSC bulk population. We did not detect any MM BMSC cells expressing RHAMM-V3 alone and the RHAMM V3/FL ratio was 1.6-fold, which is lower than that in MM-PCs. MM-BMSC screening also identified a new splice variant of RHAMM, that was absent in MM PCs or in MM myeloid cells. Conclusions: Our study suggests that aberrant RHAMM splicing in MM can result from SNPs/SNVs affecting SRE due to the upregulation of PTBP1/2. Our study is the first to show that the RHAMM-V3 variant is associated with PTBP2 overexpression. The identification of cell type-specific RHAMM splicing events identifies novel targets for improved immunotherapy in MM. Disclosures Chu: Celgene: Honoraria; AstraZeneca: Honoraria; Gilead: Honoraria; Teva: Consultancy; Amgen Inc.: Honoraria. Anderson:C4 Therapeutics: Other: Scientific founder ; OncoPep: Other: Scientific founder ; Gilead Sciences: Other: Advisory Board; Janssen: Other: Advisory Board; Sanofi-Aventis: Other: Advisory Board.

Description: Background: Novel drug discoveries have shifted the treatment paradigms of most hematological malignancies including multiple myeloma (MM), but minimal residual disease and drug resistance underlie relapses in MM. Although many genetic and epigenetic alterations regulate MM progression, MM cells are not autonomous. Dynamic interactions between MM cells and cells of the bone marrow (BM) microenvironment have been reported by our group and others. MM plasma cells (PCs) depend on interactions with bone marrow stromal cells (BMSCs) for their survival and growth, but little is known about the specific genetic events taking place in the MM BM microenvironment. Methods: Here we report a detailed analysis of the genetic and epigenetic events that are characteristic of MM BMSC as compared to HD-BMSC interacting with BM PCs. To evaluate genetic and epigenetic landscapes, RNA was extracted from bulk sorted populations of 16 MM-BMSC, 3 HD-BMSC, and 10 autologous MM cells. We prepared libraries for 32 samples using the NEBNext Ultra II Stranded Poly A kit, and then sequenced on the NextSeq 500, PE150. Sequencing data were analyzed using a custom computational and statistical pipeline at the Department of Biostatistics, School of Public Health and Partek software. Results: Unsupervised clustering showed that MM-BMSC samples clustered as a distinct and completely separate cluster from HD-BMSC and autologous MM cells. Gene level analyses of these three groups identified 990 genes differentially expressed (upregulated or downregulated, P〈 0.005). Sequential filtration analyses of the differentially expressed genes in MM-BMSC identified significant deregulation of : transcripts in the Jak-STAT signaling pathway (JAK3, PIM1, IL6, CSF2R, AKT1/2, BCL2L1, CDKN1A and range of IL transcripts); genes encoding extracellular matrix interacting proteins (CD36, CD49, LAMA3, CD44, CD47); and various plasma membrane proteins that define different subpopulations of hematopoietic cells. These genes were deregulated in 〉24% of MM-BMSC samples analyzed as compared to HD-BMSC samples. These transcripts were downregulated in autologous tumor cells. Next, we interrogated the epigenomic landscape and identified the splicing signature of MM-BMSC as compared to HD-BMSC, and autologous MM cells. Comparison of the splicing patterns (exon skipping, intron retention, novel splice acceptor and/or donor activation) of these three distinct groups showed that a total of 2,100 genes were differentially expressed and 566 were alternatively spliced among the three groups (P 〈 0.01). These analyses identified a limited number of the transcripts with ~3% significantly spliced in MM-BMSC compared to HD-BMSC. However, comparing MM-BMSC splicing events to MM cells splicing events, we identified 〉30% of genes which were alternatively spliced in MM cells but not in MM-BMSC. Further, gene enrichment and pathway analyses identified a selective set of transcripts that were alternatively and differentially spliced in MM-BMSC including genes involved in MAPK and Ras signaling pathways, homologous recombination, mismatch repair, and adherens junction. Conclusions: Taken together, our studies identified marked differences between important stromal elements in MM- and HD-BM. We identified genes that were specifically upregulated/suppressed in MM-BMSC compared to MM-cells and HD-BMSC. Within MM BMSCs, we identified several splicing events on genes of signaling pathways implicated in development and progression of MM. Furthermore, altered splicing events identified on these transcripts represent potential new immunotherapeutic targets. Disclosures Chu: Gilead: Honoraria; Celgene: Honoraria; Teva: Consultancy; Amgen Inc.: Honoraria; AstraZeneca: Honoraria. Anderson:C4 Therapeutics: Other: Scientific founder ; Gilead Sciences: Other: Advisory Board; OncoPep: Other: Scientific founder ; Sanofi-Aventis: Other: Advisory Board; Janssen: Other: Advisory Board.

Description: Alternative pre-mRNA splicing (AS) is a normal epigenetic phenomenon, a key regulator of gene expression, yields multiple transcripts and thus a variety of proteins from a single gene. Mutations in the spliceosome components resulting in aberrant splicing isoforms are common in AML, and other myeloid neoplasms, and may generate leukemia-specific neoantigens targetable with an antibody-drug conjugates (ADCs) or blocking antibodies. Our previous studies revealed that the FLT3 cell surface receptor is one of the most commonly misspliced genes in AML (54-63% of ~400 AML patients). We conducted cloning and sequencing analyses in AML cells and identified multiple aberrant splice-variants of FLT3 that resulted from either skipping of one or more exons or activation of cryptic splicing sites. Transfection of cDNA with three of these variants in TF-1 (AML cell line) cells resulted in expression of Flt3 variant proteins on the cell surface. We successfully generated rabbit polyclonal antiserum against a unique peptide sequence present in the most commonly expressed abnormal splice variant, which we termed Flt3Va. Immunoblots performed with the polyclonal antibody identified a ~160 kDa protein expressed by TF-1 cells transfected with FLT3Va, and the antibody did not react with untransfected TF-1 cell lysate. Using standard techniques, we generated rabbit hybridomas and evaluated the clones by flow cytometry and western blotting experiments. Based on these data, we selected one antibody clone (15-7) for further experiments. The 15-7 anti-Flt3Va rabbit monoclonal antibody identified Flt3Va protein expressed on the cell surface and within the cytoplasm of transfected TF-1 cells by flow cytometry and western blotting. However, no Flt3Va protein was detected in untransfected TF-1 cells or normal CD34+ bone marrow cells. The 15-7 antibody bound to 26 of 52 primary AML samples and 5 of 10 primagraft samples (PDX models) of human AML. Immunoblotting analyses of PDX models and patient samples confirmed binding to a protein of the expected size (130-160 kDa). Additionally, multi-parameter flow cytometry in 10 PDX models and 52 primary demonstrated that putative AML stem cells (as defined by the CD45dim, CD34, CD38, CD33, c-Kit cell surface expression) co-expressed Flt3Va antigen in 50% samples evaluated. An analysis of Flt3Va protein localization by live cell imaging showed a punctate distribution of Flt3Va on the cell surface. Furthermore, we observed that overexpression of Flt3Va in TF-1 cells led to GM-CSF growth factor independence. Analysis of TF-1 cells in the absence of GM-CSF and Flt3 ligand demonstrated constitutive activation of STAT5, an important mediator of Flt3 signaling, in Flt3Va overexpressing cells. In addition, Erk1/2 phosphorylation was also increased in Flt3Va overexpressing cells, another downstream effector of Flt3. In an effort to determine if Flt3Va+ cells had tumor repopulating ability, we sorted 0.3X10^6 Flt3Va+ and Flt3Va- cells from a PDX sample and injected the sorted populations or unsorted bulk tumor cells into NSG mice. The human cell engraftment in the mice was detected by the expression of human CD45, CD33, CD34, CD38, and c-kit antigens in the peripheral blood. In two experiments, mice injected with Flt3Va+ cells had detectable circulating leukemic cells by ~18 days after injection, while those injected with Flt3Va- cells had detectable circulating leukemic cells after the 4th week. These results suggest both Flt3Va+ and Flt3Va- cell populations are able to reconstitute leukemia after transplantation in NSG mice. However, Flt3Va+ may be expressed by an aggressive AML clone that facilitate early tumor engraftment. Overall, these studies suggest that Flt3Va is a leukemia-specific neoantigen and is an attractive potential immunotherapeutic target in AML. Proteins such as Flt3Va generated by alternative splicing are common in AML and may be targets for of novel blocking antibodies or ADCs, minimizing effects on normal tissues. Disclosures Adamia: Janssen: Research Funding. Nemeth:Janssen: Employment. Attar:Janssen: Employment. Letai:AbbVie: Consultancy, Research Funding; Tetralogic: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Research Funding. Steensma:Millenium/Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Ariad: Equity Ownership; Genoptix: Consultancy. Weinstock:Novartis: Consultancy, Research Funding. DeAngelo:Novartis: Consultancy; Ariad: Consultancy; Pfizer: Consultancy; Baxter: Consultancy; Celgene: Consultancy; Incyte: Consultancy; Amgen: Consultancy. Stone:Agios: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celator: Consultancy; Juno Therapeutics: Consultancy; Roche: Consultancy; Jansen: Consultancy; Pfizer: Consultancy; ONO: Consultancy; Sunesis Pharmaceuticals: Consultancy; Merck: Consultancy; Xenetic Biosciences: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; Amgen: Consultancy; Karyopharm: Consultancy; Seattle Genetics: Consultancy. Griffin:Janssen: Research Funding; Novartis: Consultancy, Research Funding.