Bergsagel, P. Leif

Abstract Purpose: Structural variants (SV) of the MYC gene region are common in multiple myeloma and influence disease progression. However, the prognostic significance of different MYC SVs in multiple myeloma has not been clearly established. Experimental Design: We conducted a retrospective study of multiple myeloma comparing MYC SV subtypes identified by next-generation sequencing (NGS) and FISH to MYC expression and disease survival using 140 cases from Mayo Clinic and 658 cases from the MMRF CoMMpass study. Results: MYC SVs were found in 41% of cases and were classified into nine subtypes. A correlation between the presence of a MYC SV and increased MYC expression was identified. Among the nine MYC subtypes, the non-immunoglobulin (non-Ig) insertion subtype was independently associated with improved outcomes, while the Ig insertion subtype, specifically involving the IgL gene partner, was independently associated with poorer outcomes compared with other MYC SV subtypes. Although the FISH methodology failed to detect approximately 70% of all MYC SVs, those detected by FISH were associated with elevated MYC gene expression and poor outcomes suggesting a different pathogenic role for FISH-detected MYC subtypes compared with other MYC subtypes. Conclusions: Understanding the impact of different MYC SVs on disease outcome is necessary for the reliable interpretation of MYC SVs in multiple myeloma. NGS approaches should be considered as a replacement technique for a more comprehensive evaluation of the multiple myeloma clone.

2500 Background: Oncolytic virotherapy is a novel immunomodulatory therapeutic approach for relapsed refractory hematologic malignancies. The Indiana strain of Vesicular Stomatitis Virus was engineered to encode interferon beta (IFNβ) and sodium iodine symporter (NIS) to produce VSV-IFNβ-NIS. Virally encoded IFNβ serves as an index of viral proliferation and enhances host anti-tumor immunity. NIS was inserted to noninvasively assess viral biodistribution using SPECT/PET imaging. We present the results of the phase 1 clinical trial NCT03017820 of systemic administration of VSV-IFNβ-NIS among patients (pts) with relapsed refractory Multiple Myeloma (MM), T cell Lymphoma (TCL) and Acute myeloid Leukemia (AML). Methods: VSV-IFNβ-NIS was administered at 5x109 TCID50 (50% tissue culture infectious dose) dose level 1 to dose level 4, 1.7x1011 TCID50. The primary objective was to determine the maximum tolerated dose of VSV-IFNβ-NIS as a single agent. Secondary objectives were determination of safety profile and preliminary efficacy of VSV-IFNβ-NIS. Correlative objectives included monitoring viremia and virus shedding. Adverse events (AEs) are reported based on CTCAE V4; cytokine release syndrome (CRS) grading was based on Lee (Blood 2014) criteria. Results: 15 pts received VSV-IFNβ-NIS: MM (7), TCL(7) and AML(1); 3 pts were treated at each dose level (DL) 1 through 3 (respectively 0.05, 0.17, and 0.5 x 1011 TCID50), & 6 pts were treated at dose level 4 (1.7x1011 TCID50). There were no dose limiting toxicities. The most frequent grades 3 & 4 AEs were hematologic: lymphopenia (46.6 & 26.6%), neutropenia (13.3% & 6.7%). CRS grades 1 (6.7%) and 2 (46.6%) were the non-hematologic AEs of note; mostly at DL 4. Only 1 pt required transient pressor support. Responses were seen in pts with T cell lymphoma. At DL2, there was a partial response (PR) lasting 3 months in a pt, post 12 prior lines of therapy. At DL4 there was a 6 month PR in a pt with PTCL and another pt with cutaneous relapse of PTCL who enjoys an ongoing CR, more than 1 year post VSV infusion; both pts received 5 prior lines of therapy. Viremia was detected in all pts at the end of infusion only up to 72 hrs post infusion; no infectious virus was recovered in buccal swabs or urine. Neutralizing anti-VSV antibodies were present by day 29. IFN levels were detectable within 30 mins of infusion, peaking between 4 & 48 hrs. TCL pts mounted higher hIFNβ levels within 48 hrs; the pt with CR mounted peak hIFNβ response of 18213.3pg/ml at 48 hrs post infusion, 15-fold higher than any other pt. Conclusions: VSV-IFNβ-NIS can be safely administered by IV infusion among heavily pretreated pts with hematologic malignancies. VSV-IFNβ-NIS as a single agent appears to be most effective at DL4 among patients with TCL, with an ongoing CR in a patient at DL4 more than 1 year post administration. Future trials of combination strategies with immune-modulatory drugs are currently being planned. Clinical trial information: NCT03017820.

Abstract BCMA/CD3-targeting bispecific antibodies (BsAb) are a recently developed immunotherapy class that shows potent tumor killing activity in multiple myeloma. Here, we investigated a murine BCMA/CD3-targeting BsAb in the immunocompetent Vk*MYC model and its immunomodulatory imide drug (IMiD)–sensitive derivative Vk*MYChCRBN model of multiple myeloma. The BCMA/CD3 BsAb was safe and efficacious in a subset of mice but failed in those with high tumor burden, consistent with clinical reports of BsAb in leukemia. The combination of BCMA/CD3 BsAb with pomalidomide expanded lytic T cells and improved activity even in IMiD-resistant high–tumor burden cases. Yet, survival was only marginally extended due to acute toxicity and T-cell exhaustion, which impaired T-cell persistence. In contrast, the combination with cyclophosphamide was safe and allowed for a tempered proinflammatory response associated with long-lasting complete remission. Concurrent cytotoxic therapy with BsAb actually improved T-cell persistence and function, offering a promising approach to patients with a large tumor burden. Significance: BCMA-targeted therapy induces deep but transient clinical responses. We developed an immunocompetent, IMiD-sensitive genetically engineered mouse model and show that IMiDs potentiate T-cell activation, increasing short-term efficacy of anti-BCMA/CD3 BsAb, but exacerbate T-cell exhaustion. Surprisingly, by reducing tumor burden and depleting regulatory T cells, cyclophosphamide prevents BsAb-induced T-cell exhaustion and promotes long-term multiple myeloma control. See related commentary by Louvet et al., p. 297.

Abstract Background: Immunoglobulin (IGH, IGL, IGK) and non-immunoglobulin (PVT1, TXNDC5, FAM46C, DUSP22, etc.) enhancers hijacking by variable genes (MYC, MAF, MAFB, CCND1/2/3, MMSET, IRF4) is a recognized oncogenic driver event in MM. However, the identity of the transcription factors (TFs) or transcriptional regulatory complexes binding and regulating the activity of these enhancers remains to be fully elucidated and may yield valuable therapeutic targets. As such the discovery of the BET family member BRD4 as the master histone acetyl mark reader at enhancers loci regulating MYC lead to promising therapeutic developments in MM and numerous other cancers. Immunomodulatory drugs (IMiDs) promote the proteasomal degradation of IKAROS (IKZF1) and AIOLOs (IKZF3) leading to the transcriptional repression of MYC and the suppression of MM cells survival and proliferation. However, acquired resistance to IMIDs and the loss of the transcriptional repression of MYC are nearly universal and occur in spite of sustained IKZF1/3 degradation suggesting that transcriptional rewiring may be sustaining hijacked enhancers activity and transcription of driver oncogenes. Methods and Results: In order to define how IMiDs repress MYC transcription, we first defined IKZF1, BRD4, the lysine acetyl transferase P300 and the mediator complex subunit MED1 mapping within the MM genome using ChIPseq. In MM cell lines (MM1S, RPMI8226, ARP1 and AMO1), IKZF1 predominantly mapped to intronic and intergenic loci which are typically enriched with enhancer and superenhancer elements. Indeed, IKZF1 mapping to the genome nearly completely (96.5%) overlapped that of P300, MED1 and BRD4 co-occupied enhancer and superenhancer loci. We also confirmed that in the MM1S sensitive cell lines IMiDs (lenalidomide 10 μM, 24h) exposure efficiently depleted IKZF1, BRD4, P300 and MED1 at enhancer loci with ensuing MYC (and MAF) downregulation. In contrast, in resistant cell lines (RPMI8226) and in spite efficient IKZF1 displacement, BRD4, P300 and MED1 were retained at the oncogenic enhancer (IGLL5) driving MYC (and MAF). These findings lead us to postulate that in IMiDs resistant cells retention of BRD4 and MED1 at oncogenic enhancers in the absence of IKZF1 likely results from rewiring of the TFs regulating MYC. To identify TFs that may co-localize with BRD4 and IKZF1, we analyzed the enrichment of DNA motifs at IKZF1and BRD4 co-occupied enhancers using the MEME suite motif-finding algorithms. This computational analysis revealed a strong enrichment at these MM enhancers of the GGAA motif recognized by the ETS family of TFs (P= 3.2 e-743) and other motifs boxes for the RUNX (P= 9.6 e-725), MYC/MYB ( P= 8.8 e-52) and interferon regulatory (IRF) (P= 3.1 e-293) TFs. We next confirmed that the ETS family TF ETV4 was indeed expressed in IMiDs resistant, but not sensitive, MM cell lines. ChiPseq occupancy profiles in IMiDs resistant RPMI8226 cell line revealed co-localization of ETV4 with IKZF1, P300 and BRD4. As predicted, lenalidomide treatment induced global depletion of IKZF1 but not ETV4 at BRD4 occupied enhancers in resistant cell lines (RPMI8226 and ARP1). Importantly, Cas9-mediated knock out of ETV4 in RPMI8226 cells sensitized them to lenalidomide with ensuing MYC downregulation and cell death. Confirming its role in MM, ETV4 transcript was indeed detectable in primary patients' samples in the CoMMpass data repository (ETV4 FPKM >1.0 in 112/724) and its expression was associated with significantly reduced survival outcomes (HR 0.64; P=0.0008). Similarly, high expression (top quartiles) of RUNX2 or MYB, TFs with enriched motifs at IKZF1 co-occupied enhancer loci, was also associated with decreased survival. Of note RNAseq analysis of paired patient samples pre- and post-IMiDs treatment (n=14 pairs) revealed significant upregulation of ETV4 at the time of acquired IMiDs resistance (7/14). Lastly transcriptome analysis of 101 patients enrolled in the RD arm (lenalidomide and dexamethasone) of the POLLUX trial (NCT02076009) confirmed the reduced survival of patients with top quartiles expression of ETV4 as well as MYB and RUNX2 (Fig.1) Conclusion: Transcriptional plasticity with expression of extra-lineage TFs such as the ETS family member ETV4 sustains oncogenic enhancers in MM overcoming IKAROS and AIOLOS dependency and promoting IMiDs resistance. Figure 1 Figure 1. Disclosures Neri: Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding. Soong: Jannsen: Employment. Chiu: Janssen: Employment. Bahlis: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau.

Background: Bortezomib, a proteasome inhibitor, has shown efficacy in the treatment of newly diagnosed and relapsed light chain (AL) amyloidosis, and the combination of bortezomib, cyclophosphamide and dexamethasone is a commonly used regimen in AL. Ixazomib is the first oral proteasome inhibitor to be approved, and the combination of ixazomib with cyclophosphamide and dexamethasone is an all oral effective regimen for the treatment of multiple myeloma. This phase 2 trial was designed to evaluate the efficacy of this regimen in patients with AL, who have not received any therapy. Patients and methods: Newly diagnosed patients with biopsy proven AL amyloidosis, with organ involvement requiring therapy, were enrolled if they had measurable disease (Serum immunoglobulin free light chain ≥5 mg/dL AND abnormal serum free light chain ratio) and adequate organ function. Patients with severe organ involvement were excluded (Alkaline phosphatase >750 U/L, creatinine clearance <30 mL/min or NT-ProBNP ≥ 7500 ng/dL). Treatment consisted of ixazomib 4 mg days 1, 8, 15; cyclophosphamide 500 mg PO weekly and dexamethasone 40 mg, weekly for twelve 28-day cycles, followed by ixazomib maintenance (days 1, 8, 15) at the last tolerated dose till progression. The primary objective was to determine the hematologic response rate of ixazomib, used in combination with cyclophosphamide and dexamethasone in patients with previously untreated AL. A one-stage binomial design was utilized to test the null hypothesis that the hematologic response rate is at most 30% against the alternative hypothesis that it is at least 50%, with 85% power and 9% type I error. Results: Thirty-five patients were enrolled, median age was 67 (range 38-78) years; 69% were male. Organ involvement included cardiac in 23 (65.7%), renal in 19 (54.3%), and nervous system involvement in 5 (14.3%). At data cutoff 8 patients still remain on study with a median follow up of 4.4 months for those who are alive. Across the trial a median of 4 cycles (range 0-23) of treatment have been completed; the most common reason for going off study was institution of alternate therapy in 17 patients (63%). The overall hematologic response was 57% (20/35) and included amyloid CR in 5 (14%), VGPR in 9 (26%) and a PR in 6 (17%) patients. Confirmed organ responses have been observed in 5 patients so far, 2 each for cardiac and renal and 1 hepatic. The median PFS and OS have not been reached; 4 patients had hematological progression; 6 patients (17%) have died. Across 193 cycles of treatment administered, dose modification was required in 5, 3, and 10 patients, respectively, for ixazomib, cyclophosphamide and dexamethasone. A grade 3 or higher adverse event (AE), at least possibly attributed to the study drugs, was observed in 41% of patients. The figure shows the maximum grade of adverse events for individual patients seen in more than one patient across the study. Conclusions: The all-oral regimen of ixazomib, cyclophosphamide, and dexamethasone is active in patients with previously untreated AL amyloidosis with hematologic responses observed in 57% of patients, including complete responses. Organ response has been observed but will likely need longer follow up for accurate assessment, given the delay in organ responses in this disease. Further evaluation of this combination is warranted. Disclosures Gertz: Alnylam: Consultancy; Ionis/Akcea: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Consultancy; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; NCI SPORE MM: Research Funding; Prothena: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy. Kapoor:Celgene: Honoraria; GlaxoSmithKline: Research Funding; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy. Larsen:Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Dingli:Apellis: Consultancy; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Alexion: Consultancy; Millenium: Consultancy. Dispenzieri:Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Pfizer: Research Funding; Takeda: Research Funding. Kumar:Adaptive Biotechnologies: Consultancy; Carsgen: Other, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Dr. Reddy's Laboratories: Honoraria; Tenebio: Other, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Karyopharm: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; MedImmune: Research Funding.

Background: Oncolytic virotherapy is a novel immunomodulatory therapeutic approach for relapsed refractory hematologic malignancies. The Indiana strain of Vesicular Stomatitis Virus (VSV) has been engineered to encode interferon beta (IFNβ) and sodium iodine symporter (NIS) to produce VSV-IFNβ-NIS. The virally encoded IFNβ serves as an index of viral proliferation and enhances host anti-tumor immunity. The NIS is inserted as a reporter gene into the viral genome to enable noninvasive monitoring of viral spread using PET/CT imaging. Here we present results of Arm A (patients with low tumor burden) of the Phase I clinical trial (NCT03017820) of intravenous administration of VSV-IFNβ-NIS for patients (pts) with relapsed refractory hematological malignancies: MM, AML, and TCL. Methods: This was a classical 3+3 phase I trial, starting at 5x10^9 TCID50 (50% tissue culture infectious dose) level 1 through 1.7x10^11 TCID50 dose level 4 given as a single IV dose. The primary objective was determining the maximum tolerated dose of VSV-IFNβ-NIS alone; secondary objectives include estimating the safety profile and preliminary efficacy. Correlative objectives include monitoring the pharmacodynamics of viral replication through SPECT/CT imaging with NIS gene, viremia, virus shedding and changes in the immune profile of peripheral blood leukocytes. Adverse events (AEs) are reported based on CTCAE v4; cytokine release syndrome (CRS) grading was based on Lee (Blood 2014; 124(2):188-195) criteria. Results: From April 2017, 12 pts have received IV VSV-IFNβ-NIS in Arm A: MM (7), TCL(4) and AML(1); 3 pts were treated at each dose level (DL) 1 to 4. At DL1, there were five grade 3 hematologic AEs (leukopenia [1], neutropenia [1], lymphopenia [3]) and no grade 3+ non-hematologic AEs. At DL2, three grade 3 hematologic AEs (anemia [2], lymphopenia [1]), four grade 4 hematologic AEs (neutropenia [1], leukopenia [1], lymphopenia [1] and thrombocytopenia [1]). There was 1 event of grade 2 CRS at DL2, two grade 3 non-hematologic AEs (nausea [1], dehydration [1]). At DL3, there was one grade 4 hematologic AE (neutropenia [1]), three grade 3 hematologic AEs (lymphopenia [2], leukopenia [1]), and one grade 3 non-hematologic AE (vasovagal reaction [1]). One grade 2 and grade 1 CRS by Lee criteria were observed. At DL4, there were three grade 3 hematologic AEs (lymphopenia [1], neutropenia [1], thrombocytopenia [1]), and three grade 3 non-hematologic AEs (AST increase [1], skin infection [1], soft tissue infection [1])and two grade 2 CRS. There were no dose limiting toxicities. There was one partial response (DL2) and one complete response (DL4); 3 pts had stable disease, 7 pts progressed. The MM pts receiving VSV-IFNβ-NIS at DL4 had stable disease. Six of the 7 MM pts demonstrated transient reduction in serum level of involved free light chain (LC) after VSV-IFNβ-NIS infusion, with median 20.4% reduction of the involved LC within 48 hrs. Viremia was detectable in all pts at the end of infusion, to varying levels at 30 mins, 1, 2, 4, 24, 48h or 72 hrs post infusion. No persistent viremia was observed. No infectious virus was recovered in buccal swabs or urine and neutralizing anti-VSV antibodies were present by day 29. The IFN levels were detectable within 30 minutes of infusion and peaked between 4 and 48 hrs. The pts with a diagnosis of TCL mounted higher hIFNβ levels within 48 hrs. Remarkably, the TCL pt with CR (DL4) mounted a peak hIFNβ response of 18213.3pg/ml at 48 hrs post infusion, approximately 15-fold higher than any other pt enrolled in the study; and highest neutralizing antibody titer (1:40960). Conclusion: VSV-IFNβ-NIS can be safely administered by intravenous infusion in pts with hematological malignancies, up to a dose level of 1.7 x 1011 TCID50, without dose limiting toxicities and no CRS higher than grade 2. In this small phase 1 study, pts with T-cell lymphoma demonstrated the strongest signal of response, with one confirmed partial response at DL2 and one complete response at DL4. IFNβ is an early biomarker of tumor susceptibility; the magnitude of IFNβ elevation appears to correlate with treatment response. There were no confirmed responses in pts with MM, but the 20.4% transient reduction in LC suggests that combination strategies with VSV-IFNβ-NIS may result in deeper and sustained responses in MM. Future trials investigating combination strategies with immune modulatory drugs are being planned. Disclosures Peng: Imanis: Other: Equity Ownership. Witzig:Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Incyte: Consultancy; Acerta: Research Funding; MorphSys: Consultancy; AbbVie: Consultancy; Celgene: Consultancy, Research Funding. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Alnylam: Research Funding; Janssen: Research Funding; Celgene: Research Funding. Gertz:Celgene: Consultancy; Annexon: Consultancy; Sanofi: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; NCI SPORE MM: Research Funding; Johnson and Johnson: Speakers Bureau; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy; Ionis/Akcea: Consultancy; Spectrum: Consultancy, Research Funding; Prothena: Consultancy; DAVA oncology: Speakers Bureau; i3Health: Consultancy; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; International Waldenstrom Foundation: Research Funding. Dingli:Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy; Karyopharm Therapeutics: Research Funding; Millenium: Consultancy; Sanofi-Genzyme: Consultancy. Kapoor:Cellectar: Consultancy; Celgene: Honoraria; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding. Lin:Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Kumar:Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Carsgen: Other, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Sanofi: Research Funding; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Karyopharm: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding. Russell:Imanis: Other: Equity Ownership. OffLabel Disclosure: This describes of administration of Vesicular Stomatitis Virus Genetically Engineered to Express NIS and human interferon, in Patients with Relapsed or Refractory Hematologic malignacies

BACKGROUND Aneuploidy, defined by abnormal copy number changes of chromosomes, contributes to genome instability in multiple myeloma and has potential prognostic impact. Previous research has explored transcriptional pathways affected by aneuploidy. We aim to evaluate aneuploidy, clinical prognosis, and gene expression in RRMM patients (pts) who participated in MMRF (Multiple Myeloma Research Foundation) sequencing study at University of Michigan. We further used gene set analysis to identify enrichment and variation of genetic pathways associated with aneuploidy and overall survival (OS). This was a pilot study in view of applying similar methods to larger populations. METHODS DNA and RNA materials were obtained from 51 RRMM pts at the time of disease relapse. Targeted sequencing was performed with the Onco1700 panel and RNA sequencing was performed with a capture protocol using Agilent SureSelect All Exon V4, followed by paired end sequencing. Copy number variation (CNV) was estimated using an in-house pipeline using matched normal samples. Arm-level aneuploidy was defined as copy number status (gain, loss or neutral) with maximal proportion for each chromosomal arm. Aneuploidy score was determined by total number of arm-level CNV aberrations, with the median score defining high and low aneuploidy groups. Survival analysis was performed using Kaplan-Meier (KM) and Cox regression. RNA-seq libraries were aligned with STAR aligner to the hg38 reference and read quantification were performed with featureCounts. We used gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to obtain genetic pathway-level summaries for 50 hallmark pathways representative of cancer from the GSEA Molecular Signatures Database (https://www.gsea-msigdb.org/). Supervised GSEA was performed, based on differential analyses comparing gene expression profiles between high versus low aneuploidy groups to identify the differences in genetic pathways in RRMM pts. Unsupervised GSVA was applied to RNAseq count data of RRMM and newly-diagnosed multiple myeloma (NDMM) pts from the MMRF CoMMpass study (797 pts). Univariate Cox proportional hazard model was used to identify pathways having significant association with OS. RESULTS Arm scale aneuploidy analysis revealed high frequency of gains and losses in multiple chromosomes (Figure 1). RRMM pts with high aneuploidy scores had worse OS (median 15.9 months since study enrollment) compared to those with low scores (median not reached, p=0.027). Multivariate analysis demonstrated that high aneuploidy score is persistently associated with poor OS (hazard ratio (HR): 3.9, p=0.006), adjusting for t(4;14) and t(11;14). Hyperdiploidy (any whole chromosome carrying >2 copies) was identified in chromosomes 3, 5, 7, 9, 11, 19, 21, with frequency >20%. Pts with hyperdiploidy had better OS via KM (p=0.04). Using RNAseq gene expression data and GSEA analysis, we found enrichment of gene markers involving the pathways for targets of E2F transcription factors (Normalized Enrichment Score (NES) = 2.07), G2-M checkpoint in the cell division cycle (NES = 1.87), MYC proto-oncogene (NES = 1.93 and 1.85), and DNA repair (NES = 1.68) in RRMM pts with high aneuploidy compared against those with low scores (Benjamini-Hochberg adjusted p-value <0.001 for all pathways, Figure 2). GSVA analysis revealed 21 genetic pathways associated with survival in NDMM and RRMM pts, with 8, 2, and 11 pathways associated with OS in NDMM only, RRMM only, and both, respectively (Figure 3). Enrichment of several biological pathways involved with cellular growth, cell cycle regulation, and stress response (E2F, G2-M, MYC, DNA repair, mTORC1 signaling, UV radiation, mitotic spindle assembly, unfolded protein response, and peroxisome) are associated with poor survival (HR>1) in both NDMM and RRMM pts. Downregulation of KRAS signaling pathway is associated with better survival (HR<1) in both groups. CONCLUSION Aneuploidy, adjusted for chromosomal translocations, is an independent adverse prognostic factor for RRMM. Aneuploidy is correlated with dysregulation of major biological pathways involving cell cycle regulation, cellular division, oncogenes, and DNA damage repair. The majority of common pathways shared between RRMM and NDMM are linked to or reflective of genomic instability, and may explain association with poor survival. Disclosures Talpaz: IMAGO: Consultancy; Takeda: Research Funding; Novartis: Research Funding; Constellation Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Ye:Janssen: Research Funding; Portola: Research Funding; Millennium: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Nektar: Research Funding; AbbVie: Research Funding.

Background: Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Despite improvements in clinical outcomes, variability in treatment response exists. Some patients experience innate resistance, while others develop resistance over the course of treatment. Identifying signatures of treatment response and resistance is essential to predicting effective treatment strategies. Given the phenotypic clonal heterogeneity observed in MM, we hypothesize that resistant and sensitive subpopulations have unique phenotypic signatures. We used mass cytometry (CyTOF) to characterize primary MM samples and correlated their phenotypic signatures with treatment response. Methods: We characterized 102 primary MM samples by CyTOF using 37 antibodies (see figure). Frozen whole BM specimens were thawed, stained with antibodies, barcoded, and analyzed on a Helios mass cytometer. Data was processed using Cytobank or Pathsetter and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm. T-SNE plots for CD45+ cells were created using lineage defining markers. T-SNE plots of neoplastic PCs (CD138+,CD3-,CD16-,CD19-,cytoplasmic kappa or lambda+) were created using all remaining markers. A differential analysis of each sample's clusters was performed against all other events. Z-score values, representing marker changes from the differential analysis, for each cluster were used to group similar clusters across all samples, allowing us to compare sub populations of PCs between patients (see figure). From these groups of clusters with similar changes in markers, we calculated the proportion of cells with increases or decreases in markers for each sample. Results were compared to IMWG 90-day response criteria using a random forest model. Results: We performed mass cytometry on 102 samples from 68 unique MM patients. Median age was 66 years (range 34-95) with a 1.5:1 male:female ratio. 37 (36%) had NDMM, 55 (54%) had RRMM, 2 (2%) had SMM and 8 cases (8%) had unknown status. FISH studies revealed 47 (46%) had hyperdiploidy without a recurrent primary IgH rearrangement, 31 (30%) had t(11;14), 13 (13%) had t(4;14), 5 (5%) had 14;16 or 14;20, 3 (3%) had hyperhaploidy and 3 (3%) had an undefined primary. 54 (53%) had 1q gain/amp, 22 (22%) had TP53 deletion, 22 (22%) had a MYC rearrangement and 71% had high mSMART risk. Nearly all patients received an immunomodulatory compound, a proteasome inhibitor and dexamethasone. 2 (2%) had complete response (CR), 10 (9.8%) very good partial response (VGPR), 36 (35%) had partial response (PR), 14 (14%) had minimal response (MR), 13 (13%) had stable disease (SD) and 17 (17%) had progressive disease (PD). Characterization of CD45+ cells identified a relatively conserved and reproducible map from each patient. Notable differences included an ~2-fold reduction in the percentage of total B cells (CD45+,CD3-,CD19+)/total CD45+ cells in cases with high risk mSMART, RRMM and TP53 deletion compared to cases with standard risk, NDMM or normal TP53 status. Similar B-cell reductions were found in RRMM vs. NDMM samples from matched-patients. In contrast to the conserved t-SNE structure of the CD45+ population, the neoplastic PC population displayed dramatically reduced t-SNE structural consistency. Heterogeneity between patient samples and between the same patient samples over time was observed. We focused our analysis on 22 patients with serial samples. The proportion of each t-SNE group present in each patient sample was calculated and then correlated to the 90-day response metric. We identified a phenotypic group whose proportion increased in relation to disease progression (R2=0.85). This group had elevated BCL-2, pSTAT3, CD56 levels and reduced CD45 and CD81 levels. Evaluating individual markers, we found an increase in the proportion of cells with elevated BCL-2, pS6, Ki67, and IKZF1 levels in relation to disease progression. We also observed an increase in the proportion of cells with reduced pCREB levels and a reduction in the proportion of cells with reduced CD147 levels in relation to disease progression. Conclusions: We have utilized CyTOF to characterize phenotypic and functional markers in MM cells on a single cell level and can identify unique subgroups that change in relation to disease progression. Future analysis will correlate phenotypic signatures with ISS stage, mSMART risk, cytogenetic abnormality and type of treatment. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria.

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P <0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P<0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P <0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.