Sharma, Neeraj

The immune tumor microenvironment (iTME) plays a crucial role in disease biology of plasma cell (PC) dyscrasias, but remains poorly characterized in self-identified Black individuals, a population at increased risk. Mass cytometry and scRNA-seq of 128 bone marrow aspirates revealed significant changes in immune cell composition across the disease spectrum, including shifts from naïve to effector T cells with declines in B cells, MAIT, pDCs, and increases in monocytes with disease progression. Self-identified Black patients had higher relative proportions of terminally differentiated T cells and lower monocytes in newly diagnosed and treated multiple myeloma (MM). ScRNA-seq revealed genes overexpressed in self-identified Black individuals were enriched for E2F targets and G2-M checkpoints, while reduced genes were enriched for TNF-α/NF-kB, interferon and inflammatory responses pathways. These findings were supported by genetic ancestry and validated in an independent dataset of 286 patients with MM from the MMRF Immune Atlas. Self-identified race and African genetic similarity are significantly associated with remodeling the MM iTME, with potential implications for disease biology and treatment response.

Multiple myeloma is the second-most common hematological malignancy in the US that remains a challenging disease to cure despite recent advancements in treatment strategies. Drug resistance is a major cause of concern in myeloma chemotherapy. We have created an optimization-regularization-based computational prediction method called secDrug that identified several novel secondary drug (‘secDrug‘) combinations against drug-resistant myeloma (relapsed/refractory multiple myeloma or RRMM). Top among our predicted secDrugs includes the survivin inhibitor, YM155. Survivin is a member of the inhibitor of apoptosis protein (IAP) family that has dual roles in mitosis and apoptosis. YM155 inhibits survivin at the transcriptional level by inhibiting the survivin gene promoter. Several studies have demonstrated the efficacy of YM155 in solid tumors and heme malignancies, including myeloma. However, the precise mechanism of action is not yet known. MM cell lines express high levels of IAPs. We observed high in vitro cytotoxicity of YM155 as a single agent (IC 50 range 0.41 to 12.85nM) as well as in combination with the primary drugs like proteasome inhibitors and Immunomodulatory drugs (IMiDs) against >15 human myeloma cell lines representing innate/refractory and acquired/emerging (relapse) resistance. Next, we explored the molecular mechanisms underlying the efficacy of YM155 using pre-vs-post-treatment tumor whole-transcriptome analysis (RNAseq). The top differentially regulated genes include DDIT3 (CHOP), ATF3, TXNDC5 SEC24D, and DHX15 ( Figure 1A). Ingenuity Pathway Analysis (IPA) predicted that, in addition to regulating apoptosis, survivin inhibition in myeloma significantly upregulated unfolded protein response and downregulated vehicle trafficking and genes associated with immune cell function. Further, we performed single-cell transcriptomics (scRNAseq; 10X Genomics) analysis to explore treatment-induced changes to the subclonal architecture. Our scRNAseq results revealed a distinct shift in clusters representing myeloma single-cell subpopulations following YM155 treatment ( Figure 1B). For example, Cluster 1 (53.11%), characterized by high expression of cell survival markers Ki67 and MYC, was pre-dominant in untreated myeloma cells, while Cluster 4 (52.19%) was the primary subclone in post-treatment tumors. Cluster 3 was shared between the untreated and treated groups. Detailed distinctions between each single-cell cluster will be presented. Furthermore, our scRNAseq data alluded to the benefits of combining survivin-inhibitors and Hsp90-inhibitors based on the expression of drug target genes. Hsp90 inhibitors indirectly target survivin by disrupting the interaction between survivin and Hsp90, resulting in a destabilized survivin protein that ultimately results in survivin degradation. In fact, we have earlier shown the effectiveness of Hsp90 inhibitors (17-AAG, AICAR, and CCT018159) as potent secDrugs against RRMM. Finally, high-dimensional mass cytometry or CyTOF analysis using heavy metal-conjugated proteins in patient bone marrow-derived primary myeloma cells ( ex vivo model system) showed that YM155 induced dose-dependent reduction of several protein markers implicated in cell survival and chemotherapeutic resistance in multiple myeloma, including myc, Ki-67, CD28, CD81, and CD274 (PD-L1). Previous studies have shown that CD28 and CD81 are high-risk immunophenotypes associated with significantly worse prognosis in patients with myeloma. PD-L1 (Programmed death-ligand 1) is a cell-surface glycoprotein expressed in a large number of malignancies that is involved in the termination of immune response and immune evasion. An earlier study has shown that YM155 enhances daratumumab-mediated cellular lysis of multiple myeloma cells. Our RNAseq and CyTOF results thus suggest a potential basis of synergy between YM155 with immunotherapies approved for myeloma, which we will test further. Our approach thus integrates in silico prediction with single-cell multi-ome analysis to identify molecular mechanisms potentially underlying subclonal response to novel combination therapy candidates (secDrugs) for the treatment of RRMM.

Abstract Purpose: Multiple myeloma (MM) is a plasma cell malignancy characterized by a collection of cytogenetic abnormalities that drive clinical presentation, response to treatment, and prognosis. The most common immunoglobulin heavy chain (IGH) translocation found in MM, t(11;14), results in CCND1 overexpression. Although t(11;14) is considered a standard risk cytogenetic abnormality, heterogeneity in patient outcomes and response to therapy within the t(11;14) group has been reported. In contrast to t(11;14) mantle cell lymphoma, where most cases (73%) have a typical, balanced t(11;14) rearrangement, only 47% of t(11;14) MM have a typical, balanced t(11;14) FISH pattern; the remaining 53% of MM are characterized by an atypical t(11;14) FISH result (Dalland, Genes Chromosomes Cancer, 2021). Here, we compared the genetic characteristics of typical vs. atypical t(11;14) MM and the association with other genomic abnormalities, CCND1 expression, IGH breakpoint location and patient outcomes. Methods: We performed a retrospective study of newly diagnosed t(11;14) MM patients seen at Mayo Clinic (N=411) or enrolled in the MMRF CoMMpass trial (N=167). The t(11;14) FISH results of the Mayo Clinic samples were segmented into two groups: typical CCND1/IGH signal pattern (n=179, 3 red, 3 green, 2 fusion signals) and atypical CCND1/IGH signal pattern (n=232, any FISH pattern deviating from typical). The CoMMpass cases had both RNAseq and long-insert WGS data and were analyzed to detect gene expression, structural and copy number variants and IGH breakpoint locations. These data were used to classify the t(11;14) as typical (n=63) or atypical (n=104) and whether there was a single t(11;14) fusion (n=107) or a gain of the t(11;14) fusion (n=60), and whether these cases were associated with changes in gene expression or breakpoint location. Differences between the groups were measured using χ2 and Wilcoxon tests. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical significance was determined at p<0.05. Results: Of the Mayo t(11;14) cohort, 232/411 (56%) had an atypical t(11;14) FISH pattern and 179/411 (44%) had a typical t(11;14) FISH pattern. Although an atypical t(11;14) FISH pattern was not significantly associated with monosomy 17/17p deletion, MYC rearrangements, 1q gain or ISS stage III, it was significantly associated with the presence of any trisomy in comparison to typical t(11;14) cases (40/222=18% vs.12/166=7%, p=0.002). Atypical t(11;14) cases had an increase in CCND1 gene expression compared to typical t(11;14) cases (median 375.0 RPKM vs. 266.4 RPKM, p<0.0001) and cases with a gain of the t(11;14) fusion were associated with even greater CCND1 expression compared to cases with a single t(11;14) fusion (median 459.4 RPKM vs. 263.2 RPKM, p<0.0001). We next evaluated whether the t(11:14) FISH pattern was associated with differences in IGH breakpoint locations. Nearly 80.0% of atypical t(11;14) cases had a breakpoint within the constant region of the IGH locus commonly reported for MM, while only 61.0% of the typical cases had constant region breakpoints (p=0.035); the remaining cases had breakpoints involving the VDJ region. We next evaluated the impact of atypical t(11;14) FISH on OS. In Mayo cases, OS was significantly shorter in patients with atypical FISH patterns compared to typical t(11;14) FISH patterns (6.9 years [95% CI: 5.1-7.8] vs. 9.0 years [95% CI: 7.0-11.6], p=0.019). Although atypical t(11;14) was associated with increased risk of death (RR 1.45, p=0.021), this finding was not retained in a multivariate model including high risk abnormalities such as age, ISS stage, 17p deletion and 1q gain demonstrating atypical t(11;14) is not an independent predictor of poor outcome when treated with standard therapies. Conclusions: Atypical t(11;14) FISH in MM is found in approximately half of t(11;14) cases, is associated with trisomies, higher CCND1 expression and is more likely to have a breakpoint involving the constant region of the IGH locus. The enrichment of VDJ breakpoints within typical t(11;14) MM is consistent with enrichment of VDJ IGH breakpoints in MCL, which are mostly characterized by typical t(11;14) FISH patterns. While not an independent predictor of outcome with standard therapies, it remains to be evaluated whether patients with typical or atypical t(11;14) have a differential response to novel agents, such as venetoclax. Disclosures Fonseca: Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Juno: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees. Bergsagel: Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse. Kumar: Merck: Research Funding; Carsgen: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Sanofi: Research Funding.

Abstract Multiple myeloma (MM) is the second-most common hematological malignancy in the US. MM is an incurable, age-dependent plasma cell neoplasm with a 5-year survival rate of less than 50%. Extensive inter-individual variation in response to standard-of-care drugs like proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs), drug resistance, and dose-limiting toxicities are critical problems for the treatment of MM. Clinical success in anti-myeloma treatment, therefore, warrants continuous development of novel combination therapy strategies with the explicit goal to improve the therapeutic efficacy by concomitantly targeting multiple signaling pathways. Previously, we have reported the development of an in-house computational pipeline called secDrug that applies greedy algorithm-based set-covering computational optimization method followed by a regularization technique to predict secondary drugs that can be repurposed as novel synergistic partners of standard-of-care drugs for the management of refractory/ resistant MM. Top among these secondary drugs (secDrugs) were the HSP90 inhibitor 17-AAG. In this study, we used 17-AAG as a proof of principle to establish a pipeline that integrates our in silico predictions with in vitro and ex vivo validation as well as multi-omics technologies to identify, validate, and characterize therapeutic agents that could be used either alone or in combination with standard-of-care drugs for the treatment of R/R MM patients (Figure 1). To screen and validate our in silico prediction results, we performed in vitro cytotoxicity assays using 17-AAG on a panel of human myeloma cell lines (HMCLs; in vitro model systems) that captures a wide range of biological and genetic heterogeneity representing the complexities encountered in clinical settings. These cell lines include HMCLs representing innate sensitive/resistance, >10 pairs of parental and clonally-derived PI- and IMiD-resistant pairs (P vs VR or LenR; representing acquired/emerging resistance/relapse), NRAS mutants which leads to the constitutive activation of oncogenic Ras signaling, and CRISPR-edited HSP90 knockdown cell line. Our results showed that 17-AAG has high synergistic activity in combination with PI in inducing apoptosis even in innate and acquired PI-resistant HMCLs and significantly reduces the effective dose of PI required to achieve IC 50 (Chou-Talalay's Dose Reduction Index or DRI 7±1.4). Moreover, 17-AAG+IMiD showed synergistic cell killing activity in clonally-derived IMiD resistant HMCL. Further, 17-AAG induced cell death was comparable with Hsp90 knockdown as evident from the cytotoxicity assay using PI and 17-AAG in combination in RPMI8226-wild type and RPMI-HSP90AA1 knocked down cell line. Notably, 17-AAG was strikingly effective against the NRAS-mutant cell line indicating an additional niche (NRas mutant myeloma) where 17-AAG could be most effective. Next, we performed RNA sequencing to elucidate the molecular mechanisms behind 17-AAG drug action, drug synergy, 17-AAG-induced cell death. Our gene expression profiling (GEP) followed by Ingenuity Pathway Analysis (IPA) analysis revealed protein ubiquitination, aryl hydrocarbon receptor signalling pathway as the top canonical pathways. 17-AAG induced apoptosis via mitochondrial mediated pathway in myeloma. 17-AAG exerts its cytotoxic effect by activating intrinsic pathway of apoptosis which we further confirmed through the increase in reactive oxygen species generation and decrease in mitochondrial membrane potential. 17-AAG was also effective in reducing the expression of hallmarks of MM such as p65/NF-kB, IRF4, c-Myc. Finally, we performed mass cytometry (CyTOF; Cytometry by time of flight) on primary bone-marrow cells (PMCs) from myeloma patients for further validation of proteomic signatures at the single-cell level. CyTOF analysis confirmed 17-AAG-induced cell death and key changes in MM-specific proteomic markers. 17-AAG treated PMCs showed elevated cleaved caspase levels and down-regulation of IRF4 and phospho-STAT3. GEP and CyTOF results were confirmed using immunoblotting assays. Together, our study demonstrates a unique pipeline for drug repositioning that has the potential to revolutionize clinical decision-making by minimizing the number of drugs required for discovering successful combination chemotherapy regimens against drug-resistant myeloma. Figure 1 Figure 1. Disclosures Kumar: BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Purpose: Multiple myeloma (MM) is a plasma cell (PC) malignancy with an increasing incidence in the United States. Fluorescence in situ hybridization (FISH) is currently the gold-standard diagnostic assay to detect recurrent genomic abnormalities of prognostic and therapeutic significance in MM. Hyperdiploid MM, a standard risk abnormality, is characterized by gains of odd-numbered chromosomes including chromosome 15. While gains of chromosome 15 have been reported in approximately 53% of standard risk MM patients (Chretien, Blood, 2015), losses of chromosome 15 are rarely reported. Enumeration of chromosome 15 centromere is detected using the alpha satellite FISH probe. We previously discovered ~9% of cases had false-negative chromosome 15 FISH results when compared to Mate Pair Sequencing (MPseq) (Smadbeck, BCJ, 2019). To our knowledge, no previous studies have reported a reduced performance of the alpha satellite D15Z4 FISH probe in PC FISH studies. A false-negative result for D15Z4 could result in an underreporting of trisomy 15 and overreporting of monosomy 15. Here, we investigated the incidence of false-negative D15Z4 FISH results by examining the presence of monosomy 15 from patients with a monoclonal gammopathy. Methods: We identified 1231 samples from patients with a monoclonal gammopathy who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from bone marrow samples was genotyped on the Precision Medicine Research Array and biogeographical ancestry was assessed using the Geographic Population Structure Origins tool (Elhaik, Nat Commun, 2014; Home DNA 2016). FISH of immunoglobulin (cIg)-stained PCs was performed as described (Baughn, BCJ, 2018). Chromosome 15 centromere probe (Vysis CEP 15 D15Z4, Abbott Molecular, Abbott Park, IL) was used for chromosome 15 enumeration. Samples were divided into two groups: Cases with or without evidence of monosomy 15 by FISH. Mann-Whitney U test was applied to compare difference between groups for data deviating from normal distribution. A Chi-squared test evaluating the differences across these two groups was used. Results: We identified monosomy 15 in 31 cases (2.5% of cohort). Monosomy 15 was observed in nearly 100% of both the PC (cIg+) and non-PC (cIg-) populations, by contrast to the other recurrent PC-specific genomic abnormalities which were restricted to only the PC population. All samples with a banded analysis revealed most metaphases had two normal chromosome 15s demonstrating that the D15Z4 FISH probe failed to correctly enumerate the number of chromosome 15 centromere signals. Of the samples with a monosomy 15 result, the median African ancestry was 76.2% (95% percentiles: 77.5%-89.0%), while the median African ancestry of the non-monosomy 15 cohort was 2.3% (95% percentiles: 0%-87.7%) (). Although not all patients with >50% African ancestry had evidence of monosomy 15, 26/31 (83.9%) of patients with monosomy 15 had >50% African ancestry. Accordingly, patients with African ancestry (similarity ≥ 0.70) had 8.02-fold (95% confidence interval: 3.73-17.25, P = 9.92 X10 -8) increased possibility to have monosomy 15. Of cases with monosomy 15, 22 (71.0%) had an IGH rearrangement with the most prevalent IGH partner being CCND1. The incidence of t(11;14) was greater in the monosomy 15 group (13/31:41.9%), in contrast to the non-monosomy 15 group (330/1200=27.5%) (P = 0.12). Conclusions: We report a polymorphic variant of the chromosome 15 centromere resulting in a false-negative FISH result using the D15Z4 FISH probe. Surprisingly, the false-negative FISH result was not uniformly distributed among patients and was highly enriched in individuals of African ancestry. This may be due to a variation of the chromosome 15 alpha satellite in some individuals that prevents the D15Z4 FISH probe from sufficiently binding (O'Keefe, Genome Research, 2000). Although this study focused on identification of monosomy 15, the incidence of a false-negative result is likely greater than we have reported in this study since we did not evaluate cases that had a true trisomy 15 that was reported as normal chromosome 15 enumeration by FISH. This study highlights a critical need to ensure diagnostic reagents have equal performance for all patients independent of their ancestry. Evaluation of genomic events using unbiased approaches such as whole genome sequencing may circumvent some of these limitations. Disclosures Elhaik: DDC: Consultancy. Baird: DDC: Current Employment. Kumar: Antengene: Consultancy, Honoraria; Bluebird Bio: Consultancy; Beigene: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Carsgen: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

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.

AbstractPlasma cell neoplasms (PCN) and mantle cell lymphoma (MCL) can both harbor t(11;14)(q13;q32) (CCND1/IGH), usually resulting in cyclin D1 overexpression. In some cases, particularly at low levels of disease, it can be morphologically challenging to distinguish between these entities in the bone marrow (BM) since PCN with t(11;14) are often CD20‐positive with lymphoplasmacytic cytology, while MCL can rarely have plasmacytic differentiation. We compared the difference in CCND1/IGH by fluorescence in situ hybridization (FISH) in PCN and MCL to evaluate for possible differentiating characteristics. We identified 326 cases of MCL with t(11;14) and 279 cases of PCN with t(11;14) from either formalin‐fixed, paraffin‐embedded tissue or fresh BM specimens. The “typical,” balanced CCND1/IGH FISH signal pattern was defined as three total CCND1 signals, three total IGH signals, and two total fusion signals. Any deviation from the “typical” pattern was defined as an “atypical” pattern, which was further stratified into “gain of fusion” vs “complex” patterns. There was a significantly higher proportion of cases that showed an atypical FISH pattern in PCN compared with MCL (53% vs 27%, P < .0001). There was also a significantly higher proportion of cases that showed a complex FISH pattern in PCN compared with MCL (47% vs 17%, P < .0001). We confirmed these findings using mate‐pair sequencing of 25 PCN and MCL samples. PCN more often have a complex CCND1/IGH FISH pattern compared with MCL, suggesting possible differences in the genomic mechanisms underlying these rearrangements in plasma cells compared with B cells.