Low Expression Of The FUCA1 Gene Is An Adverse Prognostic Factor In Myeloma and Combined With High Sialyltransferase Gene Expression Identifies Patients At Increased Risk Of Early Disease Progression and Death

Abstract Background Glycosylation is a post translational modification which results in the addition of carbohydrate determinants to proteins and lipids. This has a major influence on the function of molecules known to be important in myeloma cell adhesion and trafficking such as integrins and selectins. We previously reported that ST3GAL6, a sialyltransferase involved in the synthesis of functional selectin ligands in humans, is over expressed in myeloma cells and associated with inferior survival in the MRC Myeloma IX study (MRC IX). We now extend our analysis of the MRC IX dataset to evaluate the potential prognostic significance of other glycosylation genes that are differentially regulated between normal and malignant plasma cells. Methods Analyzing publically available microarray transcriptomic datasets (Mayo Clinic GSE6477, University of Arkansas (UAMS) GSE24080, GSE2658) we first identified dysregulated glycosylation genes in MM. The prognostic significance of these candidate genes in MRCIX (singly and in combination) was analyzed using Kaplan Meier survival estimates for progression free survival and overall survival (PFS, OS). These results were validated in independent datasets (TT2 and TT3). Any genes significantly associated with survival were correlated with FISH abnormalities and ISS and multivariate analysis was performed to determine their independence as prognostic factors. QPCR was performed in cell lines to validate GEP findings. Matching SNP-based mapping array and methylation array data were analyzed. Membrane protein extracts from MM cell lines were applied directly to lectin microarrays following fluorescent labeling to generate cell surface glycan profiles. Immunohistochemistry for glycosylation enzymes and glycans was performed on patient bone marrow samples. Results High expression (top quartile as cut-off) of the sialyltransferase gene ST3GAL1 showed a trend towards inferior OS (median survival 35 mos .v. 45 mos, p=0.07) with significantly reduced PFS (19 .v. 14 mos, p=0.015). Increased expression of ST3GAL1 correlated with the presence of t(4;14) (p=0.009), del13q (p=0.001), +1q (p=0.01) and hypodiploidy (p=0.00001). Low expression (lower quartile by GEP) of the gene FUCA1, which encodes tissue alpha-L-fucosidase, was linked to inferior outcome (median OS 44 .v. 38 mos, p=0.025). On multivariate analysis low FUCA1 expression was independent of other important prognostic factors (HR=1.61, p=0.017). Patients with t(11;14) by FISH were more likely to have low FUCA1 than t(11;14) negative patients. There was no significant association between ISS and ST3GAL6, ST3GAL1 or FUCA1. We verified the effect of low FUCA1 in the GSE24080 dataset from TT2 and TT3 combined. Patients with low FUCA1 had significantly worse OS (p=0.0002). SNP mapping array and methylation array analysis did not show any evidence of correlation between copy number alterations or hypermethylation of FUCA1 and its low expression level. Since FUCA1 participates in N-glycan degradation with removal of fucose residues, this raises the possibility that a reduction in FUCA1 may lead to excessive fucosylation of cancer related glycans involved in adhesion and trafficking, such as sLex. Indeed, lectin arrays of MM cell lines revealed high levels of a-1,3/a-1,6 linked fucose, as determined by binding of Aleuria Aurantia Lectin (AAL). The HECA-452 antibody recognizes a functional trisaccharide domain shared by sialyl Lewis a and sLex and known to bind to E-selectin. Preliminary immunohistochemistry revealed increased HECA452 staining in bone marrow samples, which had both strong ST3GAL6 and low FUCA1 staining. Combining gene expression data showed that reduced expression of FUCA1 with increased expression of either ST3GAL6 or ST3GAL1 or both, identified a subgroup of patients (18%) in MRC Myeloma IX with particularly poor outcome (figure 1). Similar results were found in TT2 and TT3 with 17% of patients affected. Conclusions Altered glycosylation gene expression patterns may identify patients at high risk of disease progression and early death. Our data implicates sialyltransferases and selectin ligands as potential therapeutic targets in MM. Disclosures: Morgan: Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Millenium: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Johnson and Johnson: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees. Ghobrial:Onyx: Advisoryboard Other; BMS: Advisory board, Advisory board Other, Research Funding; Noxxon: Research Funding; Sanofi: Research Funding.

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The Combination Of Hypomethylating Agents and Histone Deacetylase Inhibitors(HDACi) Are Synergistically Cytotoxic and Reverse The Malignant Phenotype In Preclinical Models Of T-Cell Lymphoma

Blood ◽

10.1182/blood.v122.21.646.646 ◽

2013 ◽

Vol 122 (21) ◽

pp. 646-646 ◽

Cited By ~ 3

Author(s):

Owen A. O'Connor ◽

Enrica Marchi ◽

Kelly Zullo ◽

Luigi Scotto ◽

Jennifer E. Amengual ◽

...

Keyword(s):

Gene Expression ◽

T Cell ◽

Board Of Directors ◽

Cell Lines ◽

Single Agent ◽

Hematologic Malignancies ◽

Advisory Committees ◽

Methylation Array ◽

Simultaneous Exposure ◽

The Mean

Abstract Both HDAC inhibitors (HDACIs) and DNA methyltransferase inhibitors (DNMTIs) are known to influence global expression patterns in hematologic malignancies. Little is known about the combination of these two drug classes in lymphoid malignancies. HDACIs have marked single agent activity in the T- cell lymphomas (TCL), although the mechanism of action is not well defined. DNMTIs affect cytosine methylation of genomic DNA and have activity mainly restricted to the myeloid derived hematologic malignancies. The single agent efficacy and synergistic interaction of a panel of HDACIs (panobinostat, belinostat, romidepsin and vorinostat) and DNMTIs (decitabine (DEC), 5-azacytadine (5-AZA)) was evaluated in models of TCL. The molecular basis for the synergistic effect of HDACIs and DNMTIs was evaluated by gene expression profiling (GEP) and CpG methylation CTCL. Single agent concentration and time effect relationships were generated for 2 CTCL (HH, H9) and 2 T-ALL (P12, PF382) cell lines. Romidepsin and belinostat were the most potent HDACIs with the mean 48 hour IC50 of 8.8 nM (range 1.7-2.7 nM) and 85 nM (range 36-136 nM), respectively. Cell viability was not affected by treatment with DEC or 5-AZA at 24 and 48 hours at concentrations as high as 20 μM. Reduction in viability was first demonstrated after 72 hours of exposure to DEC, with the mean IC50 of 14.8 μM (range 0.4 μM- >20uM). Simultaneous exposure of combinations of DEC plus romidepsin or DEC plus belinostat at their IC10, IC20, and IC50 produced marked synergy in all TCL derived cell lines. Simultaneous exposure of DEC plus romidepsin demonstrated the deepest synergy at 72 hours with synergy coefficients in the range of 0.3. Cells treated with the combination of DEC plus romidepsin also demonstrated significant induction of apoptosis as evaluated by annexinV/propridium iodide via FACS analysis and an increase in acetylated histone 3 by immunoblot. The in vivo activity of the combination of DEC plus belinostat was investigated in a xenograft model of CTCL using HH, the most resistant TCL derived cell line. Mice were treated with DEC 1.5 mg/kg (day 29, 33, 35, 37, 39, 41, 43) and/or belinostat 100 mg/kg (day 29-day 47). The combination mouse cohort demonstrated statistically significant tumor growth delay compared to DEC alone (p=0.002) and belinostat alone (p=0.001). The interaction of DEC and romidepsin was analyzed by GEP and methylation array. Interestingly, the baseline malignant phenotype seen in the CTCL cell-lines was reversed. A significant down-regulation of genes involved in biosynthetic pathways including protein and lipid synthesis, and a significant up-regulation of genes responsible for cell cycle arrest were seen. The vast majority (114/138; 92%) of genes modulated by the single agents were similarly modulated by the combination. However, the latter induced a further significant change in the transcriptome, affecting an additional 390 genes. Similarly, methylation array data was analyzed following treatment of these drugs alone and in combination. DEC induced de-methylation of 190 different gene regions corresponding to 175 genes and an additional 335 loci. Interestingly, when combined with romidepsin the number of demethylated gene regions decreased to 85 corresponding to 79 genes, 78 of which were common with DEC and 148 additional loci. The comparison of gene expression and methylation demonstrated a significant inverse relationship (R2 = 0.657) with genes found to be differentially expressed in GEP and methylation analysis. (Figure 1)Figure 1Summary of gene expression and methylation analysis.Figure 1. Summary of gene expression and methylation analysis. These data support the observation that DNMTIs in combination with HDACIs produces significant synergistic activity in models of TCL. Further evaluation of the mechanism of action with DNMTIs in combination with HDACIs is ongoing, and a clinical trial of the combination is now open. Disclosures: O'Connor: Celgene Pharmaceuticals: Consultancy; Spectrum Pharmaceuticals: Membership on an entity’s Board of Directors or advisory committees; Allos Therapeutics: Consultancy, Membership on an entity’s Board of Directors or advisory committees. Off Label Use: Hypomethylating Agents in T-cell lymphoma. Amengual:Acetylon Pharmacueticals, INC: Membership on an entity’s Board of Directors or advisory committees, Research Funding.

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Multiomic Mapping of Copy Number and Structural Variation on Chromosome 1 (Chr1) Highlights Multiple Recurrent Disease Drivers

Blood ◽

10.1182/blood-2021-148439 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 721-721

Author(s):

Patrick Blaney ◽

Eileen M Boyle ◽

Yubao Wang ◽

Hussein Ghamlouch ◽

Jinyoung Choi ◽

...

Keyword(s):

Gene Expression ◽

Cell Line ◽

Board Of Directors ◽

Cell Lines ◽

Chromatin Structure ◽

Copy Number ◽

Research Funding ◽

Chromosome 1 ◽

Structural Variants ◽

Advisory Committees

Abstract Introduction Copy number abnormalities (CNA) and structural variants (SV) are crucial to driving cancer progression and in multiple myeloma (MM). Chr1 CNA are seen in up to 40% of cases and associate with poor prognosis. Variants include deletions, gains, translocations and complex SV events such as chromothripsis (CT), chromoplexy (CP) and templated insertions (TI) which result in aberrant transcriptional patterns. Abnormal expression of genes on chr1 lead to the adverse clinical outcome and studies focussed on 1p12, 1p32.3 and 1q12-21 identified potential causal genes including TENT5C, CDKN2C, CKS1B, PDZK1, BCL9, ANP32E, ILF2, ADAR, MDM2 and MCL1 but none fully explain the clinical behavior. To address this deficiency and to relate chromatin structure to gene deregulation we present a multiomic bioinformatic analysis of SV, CNA, mutation and expression changes in relation to the chromatin structure of chr1. Methods We analysed data derived from 1,154 CoMMpass trial patients. We analyzed 972 NDMM patients with whole exome for mutations, and 752 whole genomes for copy number, translocations, complex rearrangements such as CP, CT and TI as previously described. Using GISTIC 2.0, we identified hotspots of CNA. This information was then analyzed in conjunction to the RNA-seq data derived from 643 patients to determine the aberrant transcriptional landscape of chr1. Using HiC data derived from U266 MM cell line, we associated these changes with TAD structures, A/B compartments, and histone marks along chr1, to gene expression changes, and recurrent SV. Using the cell line dependency map for CRISPR knockdown of the gene set on chr1 derived from 20 MM cell lines we related cell viability to chr1 copy number status. Results We identified 7 hotspots of deletion, 9 of gain, 3 of CT and 2 of templated-insertion across chr1. We mapped these regions to epigenetic plots and show that gained regions are hypomethylated compared to the rest of chr1 (Wilcoxon, p=0.0002). Overall 69% of gain(1q) and 45% of the non-gained hotspots were in A compartments (χ 2=11, p=0.0009) and had an overall higher compartment score (p=0.01).The recurrent regions of loss on 1p confirm the clinical relevance of this region. The critical importance of TENT5C, CDKN2C and RPL5 is identified by the impact of deletion, mutation and the rearrangement of superenhancers. Further this convergence of multiple oncogeneic mechanisms to a single locus points to a number of novel candidate drivers including FUB1 and NTRK1.We provide important new information on 1q21.1-1q25.2 encompassing 145-180Mb a transcriptionally dense region containing 6 GISTIC 2.0 hotspots of gain (G2-G7). The hotspots occur within TAD structures that correlate upregulation of known drivers listed above and also identified novel potential upregulated drivers including POU2F1, a transcription factor, CREG1, an adenovirus E1A protein that both activates and represses gene expression promoting proliferation and inhibiting differentiation (G6) and BTG2 a G1/S transition regulator (G8). These data for copy number gain provides strong evidence for the prognostic relevance of of multiple drivers within deregulated TADs rather than single candidate genes. It also highlights the importance of the chromatin structure of Chr1 in the generation of these events.Using dependency map CRISPR data we identified 320 essential genes for at least one cell line (>1). A common set of 31 genes were identified including 3 proteasome subunits (PSMA5, PSMB2, PSMB4), three regulators of ubiquitin-protein transferase activity (RPL5, RPL11, CDC20), splicing (SF3B4, SF3A3, SFPQ, RNPC3, SRNPE, PRPF38A, PRPF38B) and DTL. A common dependency for 1q+ or 1p- was not identified but a number of dependencies were identified in more than one cell line including UQCRH, SLCA1, CLSPN in 1p- cell lines and IPO9, PPIAL4G, and MRPS2 in 1q+. Conclusion We present an elegant anatomic map of chr1 at the genetic and epigenetic levels providing an unprecedented level of resolution for the relationships of structural variants to epigenetic, expression and mutation status. The analysis highlights the importance of active chromatin in gene deregulation by SV and CNA where the importance of multiple gene deregulation within TAD structures is critical to MM pathogenesis. The implications are that we could improve prognostic assignment and identify new targets for therapy by further characterizing these relationships. Figure 1 Figure 1. Disclosures Braunstein: Jansen: Membership on an entity's Board of Directors or advisory committees, 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; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Davies: Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees.

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MLN4924, a Novel Investigational NEDD8 Activating Enzyme Inhibitor, Exhibits Preclinical Activity In Multiple Myeloma and Waldenström's Macroglobulinemia through Mechanism Distinct From Existing Proteasome Inhibitors

Blood ◽

10.1182/blood.v116.21.2988.2988 ◽

2010 ◽

Vol 116 (21) ◽

pp. 2988-2988

Author(s):

Douglas W. McMillin ◽

Zachary Hunter ◽

Jake Delmore ◽

Val Monrose ◽

Peter G Smith ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Board Of Directors ◽

Cell Lines ◽

Research Funding ◽

Normal Donor ◽

Advisory Committees ◽

Safety Studies ◽

Ubiquitin Proteasome ◽

Efficacy Studies

Abstract Abstract 2988 Background: Multiple myeloma (MM) and Waldenström Macroglobulinemia (WM) have both shown clinical responses to Bortezomib therapy which blocks the elimination of ubiquitin tagged regulatory proteins by the proteasome. The NEDD8 activating enzyme (NAE)-inhibitor MLN4924 is a novel agent which demonstrates selective inhibition of the proteins for degradation in the ubiquitin pathway and may offer benefits to MM and WM patients through the more targeted approach. Methods: A panel of human MM and WM cell lines were tested for their in vitro response to MLN4924 using MTT colorimetric survival assays. MM and WM cell lines tested exhibited dose and time dependent decrease of their viability upon exposure to MLN4924 (IC50=25-150 nM). In addition, miRNA and gene expression studies in response to MLN4924 were compared to treatment of the same cells with bortezomib. In vivo safety studies were performed in mice and animal efficacy studies are ongoing in both MM and WM engrafted mice. Results: A panel of MM and WM cells were treated with MLN4924 for 72hrs and compared to the colon carcinoma line HCT116 and normal cell lines HS-5 (stroma) and THLE-3 (hepatocytes). In addition, a longitudinal assessment of viability of MM1S (MM) and BCWM1 (WM) cells during a 72hr incubation with MLN4924 (500nM) showed commitment to death <48hrs. This result, coupled with the observation that normal donor peripheral blood mononuclear cells (PBMCs) and HS-5 stromal cells were less sensitive (IC50 >1000 nM) than the MM or WM cell lines tested, suggest that this compound exhibits a rapid, tumor-selective effect at clinically relevant conditions. We also evaluated primary MM (CD138+) and WM (CD19+) patient bone marrow cells and observed sub-μ M activity by MLN4924. In addition, we tested a series of combinations of MLN4924 with dexamethasone, doxorubicin and bortezomib in both MM1S and BCWM1 cells lines and observed additive activity or greater with MLN4924. Gene expression profiling revealed distinct signatures, in MM1S and BCWM1 lines, as well as distinct patterns of gene expression changes which were induced by MLN4924 vs. bortezomib. For instance, while bortezomib potently induces a compensatory upregulation of transcripts for ubiquitin/proteasome and heat shock protein genes which, in MM1S or BCWM1 cells, were not observed in response to MLN4924 treatment. Additional studies with the proteasome inhibitor MLN9708 revealed similar patterns of expression as bortezomib. These results indicate that MLN4924 does not induce pronounced proteotoxic stress in MM or WM cells, highlighting the distinct effect of MLN4924 on the ubiquitin/proteasome pathway compared to inhibitors which target the 20S proteasome subunit. Longitudinal miRNA profiling revealed a distinct pattern of miRNA expression in MLN4924-treated vs. bortezomib-treated MM and WM cells. Lastly, animal safety studies showed that MLN4924 was tolerated at doses up to 60mg/kg 2x daily for 1 week. Efficacy studies in MM and WM are ongoing. Conclusions: MLN4924 induces cell killing at sub-μ M concentrations for both MM and WM cells with higher sensitivity of tumor cells compared to normal tissues, exhibits selective gene expression and miRNA regulation and can be safely administered to mice. These studies provide the framework for the clinical investigation of MLN4924 in MM and WM. Disclosures: McMillin: Axios Biosciences: Equity Ownership. Smith:Millennium: Employment. Birner:Millennium: Employment. Richardson:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees. Anderson:Millennium Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Treon:Millennium Pharmaceuticals, Genentech BiOncology, Biogen IDEC, Celgene, Novartis, Cephalon: Consultancy, Honoraria, Research Funding; Celgene Corporation: Research Funding; Novartis Corporation: Research Funding; Genentech: Consultancy, Research Funding. Mitsiades:Millennium: Consultancy, Honoraria; Novartis Pharmaceuticals: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Merck &Co.: Consultancy, Honoraria; Kosan Pharmaceuticals: Consultancy, Honoraria; Pharmion: Consultancy, Honoraria; Centrocor: Consultancy, Honoraria; PharmaMar: Patents & Royalties; OSI Pharmaceuticals: Research Funding; Amgen Pharmaceuticals: Research Funding; AVEO Pharma: Research Funding; EMD Serono: Research Funding; Sunesis: Research Funding; Gloucester Pharmaceuticals: Research Funding.

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Biomarkers Predicting Venetoclax Sensitivity and Strategies for Venetoclax Combination Treatment

Blood ◽

10.1182/blood-2018-175 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 175-175 ◽

Cited By ~ 7

Author(s):

Haijiao Zhang ◽

Beth Wilmot ◽

Daniel Bottomly ◽

Stephen E Kurtz ◽

Christopher A. Eide ◽

...

Keyword(s):

Gene Expression ◽

Board Of Directors ◽

Cell Lines ◽

Combination Treatment ◽

Research Funding ◽

Mouse Bone Marrow ◽

Advisory Committees ◽

Kras Mutations ◽

Poor Prognostic Factor ◽

Equity Ownership

Abstract BCL2 is an antiapoptotic protein commonly expressed in hematologic malignancies. Overexpression of BCL-2 is a poor prognostic factor in acute myeloid leukemia (AML). Venetoclax (ABT-199) is a highly selective BCL2 inhibitor that can induce cell death in multiple leukemia cell lines. Recently, venetoclax received an FDA breakthrough therapy designation for use in combination with hypomethylating agents in treatment-naïve patients with AML who are unfit for intensive chemotherapy. However, venetoclax was only modestly effective as monotherapy in relapsed/refractory AML (19% CR/CRi). The aim of the current study is to integrate genomic and functional screen data to identify biomarkers to predict venetoclax sensitivity and resistance in AML, and to identify potential venetoclax combination treatment strategies. In this study, we investigated approximately 200 AML patient samples and correlated clinical parameters, whole exome sequence data, and RNAseq gene expression data with in vitro drug screening data (drug area under the curve (AUC)) to identify subsets of AML samples with sensitivity or resistance to venetoclax alone and in combinations with 10 small molecular inhibitors (Array-382, dasatinib, JQ-1, idelalisib, quizartinib, palbociclib, panobinostat, ruxolitinib, sorafenib, and trametinib). For gene expression, we observed that venetoclax correlated with 3 gene expression clusters (coefficient frequency: 0.94, 0.80 and 0.71 respectively) among 21 gene expression clusters in AML, associated with innate immune system, neutrophil degranulation, and interleukin-10 signaling. Among the BCL2 gene family, venetoclax AUC positively correlated with BCL2A1 (r=0.59, p<0.0001) and MCL1 (r=0.26, p=0.001) expression, whereas it negatively correlated with BCL2 (r=-0.53, p<0.0001) expression. BCL2A1 is the only BCL2 family gene within all three clusters and correlated the best with venetoclax sensitivity. Interestingly, within the three gene clusters, we observed that cell surface markers CLEC7A (CD369) and CD14 correlated with venetoclax sensitivity (r=0.68 and 0.64, p<0.0001). AML patient samples expressing CD14 detected by flow cytometry also demonstrated reduced venetoclax sensitivity (p=0.005), which could potentially serve as a biomarker to identify venetoclax resistant patients. For cytogenetic categories and mutations, we observed that AML samples harboring PML-RARA translocations, WT1, and FLT3 with IDH1 mutations are more sensitive to venetoclax, and samples with TET2, KRAS, PTPN11 and SF3B1 mutations are more resistant. We validated the effect of WT1, KRAS, and PTPN11 mutations on venetoclax sensitivity by performing drug assays on mouse bone marrow stem cells and/or AML cell lines overexpressing each mutant. Samples harboring PTPN11 mutations demonstrated high MCL1 expression, and PTPN11 mutant-transduced cells remain sensitive to Idasanutlin, which was previously shown to downregulate MCL1 expression. Samples with KRAS mutations demonstrated high BCL2A1 expression, which potentially mediate venetoclax resistance. For venetoclax drug combinations, we observed that venetoclax-trametinib demonstrated a synergistic effect on samples that are sensitive to venetoclax, whereas venetoclax-palbociclib, venetoclax-Array-382, venetoclax-sorafenib, venetoclax-ruxolitinib, venetoclax-dasatinib, and venetoclax-idelalisib are active against samples that are resistant to venetoclax, indicating potential therapeutic combinations. Interestingly, the CDK inhibitor palbociclib demonstrated no effect on the majority of AML samples and does not correlate with the BCL2A1 expression as a single agent, yet shows the most robust synergy with venetoclax, especially on samples that are resistant to venetoclax and with high BCL2A1 expression, indicating a potential synthetic lethal interaction. Venetoclax-palbociclib AUC also negatively correlated with CLEC7A and CD14 expression, indicating that venetoclax-palbociclib could circumvent venetoclax resistance to treat patients with high CLEC7A and/or CD14 expression. In summary, we have identified that CD14 and/or CLEC7A could be used as biomarkers to predict venetoclax sensitivity in AML, and we propose to combine venetoclax and palbociclib to treat patients with a venetoclax resistant profile (high CD14/CLEC7A expression or high BCL2A1 expression, or presence of KRAS mutations). Disclosures Druker: Beta Cat: Membership on an entity's Board of Directors or advisory committees; Fred Hutchinson Cancer Research Center: Research Funding; McGraw Hill: Patents & Royalties; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees; Oregon Health & Science University: Patents & Royalties; Bristol-Meyers Squibb: Research Funding; GRAIL: Consultancy, Membership on an entity's Board of Directors or advisory committees; ARIAD: Research Funding; Third Coast Therapeutics: Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; Monojul: Consultancy; Novartis Pharmaceuticals: Research Funding; Millipore: Patents & Royalties; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; ALLCRON: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Patient True Talk: Consultancy; Cepheid: Consultancy, Membership on an entity's Board of Directors or advisory committees; Henry Stewart Talks: Patents & Royalties; Celgene: Consultancy; Amgen: Membership on an entity's Board of Directors or advisory committees; MolecularMD: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose Therapeutics: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Majeti:BioMarin: Consultancy; Forty Seven, Inc: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Tyner:Incyte: Research Funding; AstraZeneca: Research Funding; Janssen: Research Funding; Takeda: Research Funding; Leap Oncology: Equity Ownership; Seattle Genetics: Research Funding; Genentech: Research Funding; Gilead: Research Funding; Syros: Research Funding; Aptose: Research Funding; Agios: Research Funding.

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Distinct Gene Expression Signatures in Patients with Richter's Syndrome and Chronic Lymphocytic Leukemia with Prior Exposure to Ibrutinib

Blood ◽

10.1182/blood-2020-136172 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 30-31

Author(s):

Hanyin Wang ◽

Shulan Tian ◽

Qing Zhao ◽

Wendy Blumenschein ◽

Jennifer H. Yearley ◽

...

Keyword(s):

Gene Expression ◽

B Cell ◽

Board Of Directors ◽

Research Funding ◽

Cell Activation ◽

Expression Profiles ◽

Lymphocytic Leukemia ◽

B Cell Activation ◽

Advisory Committees ◽

Upregulated Genes

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.

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High-Throughput Immunofluorescence and Electron Tomography to Characterize Centrosomal Aberrations in Plasma Cell Neoplasia

Blood ◽

10.1182/blood-2019-130713 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 3077-3077

Author(s):

Tobias Dittrich ◽

Martin Schorb ◽

Isabella Haberbosch ◽

Elena Bausch ◽

Mandy Börmel ◽

...

Keyword(s):

Board Of Directors ◽

Cancer Patients ◽

Genomic Instability ◽

Cell Lines ◽

Plasma Cell ◽

High Throughput ◽

Research Funding ◽

Electron Tomography ◽

Automated Analysis ◽

Advisory Committees

Introduction Genomic instability is the basic prerequisite for a Darwinian-type evolution of neoplasia and as such represents a fundamental hallmark of cancer. Centrosomal aberrations have been identified as potent drivers of genomic instability (Cosenza et al., Cell Reports 2017; Krämer et al., Leukemia 2003). The current standard to investigate centrosomal aberrations in cancer patients is immunofluorescence (IF) staining. Although this method is fast and easily scalable, its diagnostic significance is controversially discussed. Moreover, ultrastructural analysis of centrosomes in cancer patients is required to gain a mechanistical understanding of the relationship between genomic instability and centrosomal aberrations. To address this, we combined semi-automated analysis of immunofluorescence (IF) images with high-throughput electron tomography (ET) of different cell lines and subentities of primary plasma cell neoplasia, which serve as surrogate for clonal evolution. Methods CD138+ plasma cells were isolated from bone marrow aspirates of consenting patients with plasma cell neoplasia. Each sample was split to be subsequently processed for IF and ET. The IF workflow included (1) chemical fixation, (2) staining for nuclei, cells, centrin and pericentrin, (3) semi-automated acquisition of >1000 cells, (4) semi-automated analysis of IF data using the software Konstanz Information Miner (KNIME) (Berthold et al., GfKL 2007). The ET workflow included (1) chemical fixation (2) agarose embedding, (3) dehydration and epoxy resin embedding, (4) serial sectioning at 200 nm, (5) semi-automated screening for centrioles with transmission electron microscopy (TEM) (Schorb et al., Nature Methods 2019), (6) semi-automated acquisition of previously identified centriole regions with serial section ET. Results So far, four patients with relapsed refractory myeloma as well as two cell lines (U2OS-PLK4, RPMI.8226) have been screened with TEM. No centrosomal amplification was apparent by IF in any of these patients. Within 5598 cells, 205 centrosomes have been detected. A total of 659 electron tomograms were performed on 141 regions of interest that were distributed on average over five sections. One patient with highly refractory multiple myeloma (resistance to eight prior therapies) showed over-elongated and partially fragmented centrioles (Figure), similar to recently reported findings in tumor cell lines (Marteil et al., Nature Communications 2018). Six out of 10 mother centrioles in this patient were longer than 500 nm, which is supposed to be the physiological length. The dimensions (mean [range]) of mother (decorated with appendages) and daughter centrioles in this patient were: length 919 nm [406 nm - 2620 nm] and 422 nm [367 nm - 476 nm]; diameter 221 nm [99 nm - 470 nm] and 236 nm [178 nm - 450 nm]. Moreover, the mother centrioles showed multiple sets of appendages (mean [range]: 5.9 [2 - 13]), while one set of appendages would be physiological. This is an ongoing study and additional results are expected by the date of presentation. Conclusions We present a semi-automated methodological setup that combines high-throughput IF and cutting-edge ET to study centrosomal aberrations. To our knowledge, this is the first study that systematically analyzes the centrosomal phenotype of cancer patients at the ultrastructural level. Our preliminary IF results suggest that supernumerary centrosomes in plasma cell neoplasia might be less common than previously reported. Moreover, we for the first time describe and characterize over-elongated centrioles in myeloma patients, reminiscent of previous findings in tumor cell lines. With increasing numbers of patients, we will be also able to correlate results from IF and ET to address the current uncertainty with respect to IF screens for centrosomal aberrations. Better insight into centrosomal aberrations will likely increase our understanding on karyotype evolution in plasma cell neoplasia and possibly facilitate the development of novel targeted therapies. Figure Disclosures Goldschmidt: John-Hopkins University: Research Funding; John-Hopkins University: Research Funding; MSD: Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Research Funding; Molecular Partners: Research Funding; Janssen: Consultancy, Research Funding; Mundipharma: Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Müller-Tidow:MSD: Membership on an entity's Board of Directors or advisory committees. Schönland:Medac: Other: Travel Grant; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Krämer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Daiichi-Sankyo: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding.

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DYRK1A Is Regulated By Oncogenic KMT2A and Required for Survival of KMT2A-Rearranged Acute Lymphoblastic Leukemia

Blood ◽

10.1182/blood-2019-123475 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2742-2742

Author(s):

Christian Hurtz ◽

Gerald Wertheim ◽

Rahul S. Bhansali ◽

Anne Lehman ◽

Grace Jeschke ◽

...

Keyword(s):

Gene Expression ◽

B Cells ◽

Board Of Directors ◽

Research Funding ◽

Lymphoblastic Leukemia ◽

Leukemia Cell ◽

Negative Regulator ◽

Advisory Committees ◽

Normal Tissues ◽

Pharmacologic Inhibition

Background: Research efforts have focused upon uncovering critical leukemia-associated genetic alterations that may be amenable to therapeutic targeting with new drugs. Targeting the oncogenic BCR-ABL1 fusion protein in Philadelphia chromosome-positive B-cell acute lymphoblastic leukemia (B-ALL) with tyrosine kinase inhibitors to shut down constitutive signaling activation and induce leukemia cell cytotoxicity has remarkably improved patients' survival and has established a precision medicine paradigm for kinase-driven leukemias. However, multiple subtypes of B-ALL are driven through non-tyrosine fusion proteins, including the high-risk KMT2A-rearranged (KMT2A-R) subtype common in infants with B-ALL, leaving many patients with insufficient treatment options. Objectives: KMT2A-R B-ALL is associated with chemoresistance, relapse, and poor survival with a frequency of 75% in infants and 10% in older children/adults with B-ALL. Current intensive multiagent chemotherapy regimens induce significant side effects yet fail to cure the majority of patients, demonstrating continued need for novel therapeutic approaches. The goals of our study were to i) identify signaling molecules required for KMT2A-R B-ALL cell survival, ii) select ALL-associated targets that are not essential in normal tissues, and iii) develop new treatment strategies that may benefit patients with KMT2A-R ALL. Results: We performed a genome-wide kinome CRISPR screen using the pediatric KMT2A-R cell line SEM and identified DYRK1A among other signaling molecules as required for leukemia cell survival. DYRK1A is a member of the dual-specificity tyrosine phosphorylation-regulated kinase family and has been reported as a critical oncogene in a murine Down syndrome (DS) model of megakaryoblastic leukemia. In normal hematopoiesis, DYRK1A controls the transition from proliferation to quiescence during lymphoid development. Deletion of DYRK1A results in increased numbers of B cells in S-G2-M phase, yet also significantly reduces cell proliferation. Meta-analysis of ChIP-Seq data from two KMT2A-AFF1 cell lines (SEM and RS4;11) and a human KMT2A-Aff1-FLAG-transduced ALL model demonstrates that both N-terminal (KMT2AN) and C-terminal (AFF1C) and the FLAG-tagged KMT2A-Aff1 fusion directly bind to the DYRK1A promoter. Gene expression and RT-PCR analyses of SEM cells treated with inhibitors against two important KMT2A fusion complex proteins, DOT1L (histone methyltransferase) and menin (tumor suppressor), demonstrate that only menin inhibition induced DYRK1A downregulation. Interestingly, deletion of germline KMT2A in murine B-cells did not decrease DYRK1A expression. Taken together, these results suggest direct transcriptional regulation through the KMT2A fusion complex. Surprisingly, RNA and protein expression of DYRK1A was reduced in KMT2A-R ALL compared to other B-ALL subtypes. We then identified MYC as a potential negative regulator of DYRK1A that could explain the lower RNA and protein expression levels observed. A gain-of-function experiment showed marked downregulation of DYRK1A when MYC was ectopically expressed in murine B-cells, while loss of MYC resulted in DYRK1A upregulation. Parallel analysis of publicly available gene expression data from children with high-risk B-ALL (NCI TARGET database) showed significantly higher MYC RNA expression levels in KMT2A-R ALL as compared to other ALL subtypes, further validating our findings that MYC acts as a negative regulator of DYRK1A. Finally, to assess pharmacologic inhibition, we treated multiple KMT2A-rearranged ALL cell lines with the novel DYRK1A inhibitor EHT 1610 and identified sensitivity to DYRK1A inhibition. We then queried the Achilles database and identified that DYRK1A is not a common essential gene in normal tissues, suggesting minimal potential for on-target/off-tumor effects of DYRK1A inhibition. Conclusions: We identified a novel mechanism in KMT2A-R ALL in which DYRK1A is positively regulated by the KMT2A fusion protein and negatively regulated by MYC. Genetic deletion and pharmacologic inhibition of DYRK1A resulted in significant growth disadvantage of KMT2A-R ALL cells. While further studies are needed, we predict that combining DYRK1A inhibitors with chemotherapy could decrease relapse risk and improve long-term survival of patients with KMT2A-R B-ALL. Disclosures Crispino: MPN Research Foundation: Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy; Scholar Rock: Research Funding; Forma Therapeutics: Research Funding. Tasian:Incyte Corportation: Research Funding; Gilead Sciences: Research Funding; Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees. Carroll:Astellas Pharmaceuticals: Research Funding; Incyte: Research Funding; Janssen Pharmaceuticals: Consultancy.

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Dynamic Epigenetic Landscapes Define Multiple Myeloma Progression and Drug Resistance

Blood ◽

10.1182/blood-2020-142872 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 32-33

Author(s):

Rafael Renatino-Canevarolo ◽

Mark B. Meads ◽

Maria Silva ◽

Praneeth Reddy Sudalagunta ◽

Christopher Cubitt ◽

...

Keyword(s):

Gene Expression ◽

Drug Resistance ◽

Disease Progression ◽

Board Of Directors ◽

Research Funding ◽

Chromatin Accessibility ◽

Refractory Disease ◽

Advisory Committees ◽

Cytogenetic Abnormalities ◽

Genome Wide

Multiple myeloma (MM) is an incurable cancer of bone marrow-resident plasma cells, which evolves from a premalignant state, MGUS, to a form of active disease characterized by an initial response to therapy, followed by cycles of therapeutic successes and failures, culminating in a fatal multi-drug resistant cancer. The molecular mechanisms leading to disease progression and refractory disease in MM remain poorly understood. To address this question, we have generated a new database, consisting of 1,123 MM biopsies from patients treated at the H. Lee Moffitt Cancer Center. These samples ranged from MGUS to late relapsed/refractory (LR) disease, and were comprehensively characterized genetically (844 RNAseq, 870 WES, 7 scRNAseq), epigenetically (10 single-cell chromatin accessibility, scATAC-seq) and phenotypically (537 samples assessed for ex vivo drug resistance). Mutational analysis identified putative driver genes (e.g. NRAS, KRAS) among the highest frequent mutations, as well as a steady increase in mutational load across progression from MGUS to LR samples. However, with the exception of KRAS, these genes did not reach statistical significance according to FISHER's exact test between different disease stages, suggesting that no single mutation is necessary or sufficient to drive MM progression or refractory disease, but rather a common "driver" biology is critical. Pathway analysis of differentially expressed genes identified cell adhesion, inflammatory cytokines and hematopoietic cell identify as under-expressed in active MM vs. MGUS, while cell cycle, metabolism, DNA repair, protein/RNA synthesis and degradation were over-expressed in LR. Using an unsupervised systems biology approach, we reconstructed a gene expression map to identify transcriptomic reprogramming events associated with disease progression and evolution of drug resistance. At an epigenetic regulatory level, these genes were enriched for histone modifications (e.g. H3k27me3 and H3k27ac). Furthermore, scATAC-seq confirmed genome-wide alterations in chromatin accessibility across MM progression, involving shifts in chromatin accessibility of the binding motifs of epigenetic regulator complexes, known to mediate formation of 3D structures (CTCF/YY1) of super enhancers (SE) and cell identity reprograming (POU5F1/SOX2). Additionally, we have identified SE-regulated genes under- (EBF1, RB1, SPI1, KLF6) and over-expressed (PRDM1, IRF4) in MM progression, as well as over-expressed in LR (RFX5, YY1, NBN, CTCF, BCOR). We have found a correlation between cytogenetic abnormalities and mutations with differential gene expression observed in MM progression, suggesting groups of genetic events with equivalent transcriptomic effect: e.g. NRAS, KRAS, DIS3 and del13q are associated with transcriptomic changes observed during MGUS/SMOL=>active MM transition (Figure 1). Taken together, our preliminary data suggests that multiple independent combinations of genetic and epigenetic events (e.g. mutations, cytogenetics, SE dysregulation) alter the balance of master epigenetic regulatory circuitry, leading to genome-wide transcriptional reprogramming, facilitating disease progression and emergence of drug resistance. Figure 1: Topology of transcriptional regulation in MM depicts 16,738 genes whose expression is increased (red) or decreased (green) in presence of genetic abnormality. Differential expression associated with (A) hotspot mutations and (B) cytogenetic abnormalities confirms equivalence of expected pairs (e.g. NRAS and KRAS, BRAF and RAF1), but also proposes novel transcriptomic dysregulation effect of clinically relevant cytogenetic abnormalities, with yet uncharacterized molecular role in MM. Figure 1 Disclosures Kulkarni: M2GEN: Current Employment. Zhang:M2GEN: Current Employment. Hampton:M2GEN: Current Employment. Shain:GlaxoSmithKline: Speakers Bureau; Amgen: Speakers Bureau; Karyopharm: Research Funding, Speakers Bureau; AbbVie: Research Funding; Takeda: Honoraria, Speakers Bureau; Sanofi/Genzyme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive: Consultancy, Honoraria; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Siqueira Silva:AbbVie: Research Funding; Karyopharm: Research Funding; NIH/NCI: Research Funding.

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Euroclonality-NGS DNA Capture Panel for Integrated Analysis of IG/TR Rearrangements, Translocations, Copy Number and Sequence Variation in Lymphoproliferative Disorders

Blood ◽

10.1182/blood-2019-127822 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 888-888 ◽

Cited By ~ 1

Author(s):

Peter Stewart ◽

Jana Gazdova ◽

Nikos Darzentas ◽

Dorte Wren ◽

Paula Proszek ◽

...

Keyword(s):

T Cell ◽

Board Of Directors ◽

Cell Lines ◽

Research Funding ◽

Advisory Committees ◽

Proficiency Assessment ◽

Dna Capture ◽

Tumour Infiltration ◽

T Cell Malignancies ◽

Cell Clonality

Introduction: Current diagnostic standards for lymphoproliferative disorders include detection of clonal immunoglobulin (IG) and/or T cell receptor (TR) rearrangements, translocations, copy number alterations (CNA) and somatic mutations. These analyses frequently require a series of separate tests such as clonality PCR, fluorescence in situ hybridisation and/or immunohistochemistry, MLPA or SNParrays and sequencing. The EuroClonality-NGS DNA capture (EuroClonality-NDC) panel, developed by the EuroClonality-NGS Working Group, was designed to characterise all these alterations by capturing variable, diversity and joining IG and TR genes along with additional clinically relevant genes for CNA and mutation analysis. Methods: Well characterised B and T cell lines (n=14) representing a diverse repertoire of IG/TR rearrangements were used as a proficiency assessment to ensure 7 testing EuroClonality centres achieved optimal sequencing performance using the EuroClonality-NDC optimised and standardised protocol. A set of 56 IG/TR rearrangements across the 14 cell lines were compiled based on detection by Sanger, amplicon-NGS and capture-NGS sequencing technologies. For clinical validation of the NGS panel, clinical samples representing both B and T cell malignancies (n=280), with ≥ 5% tumour infiltration were collected from 10 European laboratories, with 88 (31%) being formalin fixed paraffin-embedded samples. Samples were distributed to the 7 centres for library preparation, hybridisation with the EuroClonality-NDC panel and sequencing on a NextSeq 500, using the EuroClonality-NDC standard protocol. Sequencing data were analysed using a customised version of ARResT/Interrogate, with independent review of the results by 2 centres. All cases exhibiting discordance between the benchmark and capture NGS results were submitted to an internal review committee comprising members of all participating centres. Results: All 7 testing centres detected all 56 rearrangements of the proficiency assessment and continued through to the validation phase. A total of 10/280 (3.5%) samples were removed from the validation analysis due to NGS failures (n=1), tumour infiltration < 5% (n=7), and sample misidentification (n=2). The EuroClonality-NDC panel detected B cell clonality (i.e. detection of at least one clonal rearrangement at IGH, IGK or IGL loci) in 189/197 (96%) B cell malignancies. Seven of the 8 discordant cases were post-germinal centre malignancies exhibiting Ig somatic hypermutation. The EuroClonality-NDC panel detected T cell clonality (i.e. detection of at least one clonal rearrangement at TRA, TRB, TRD or TRG loci) in 70/73 (96%) T cell malignancies. In all 3 discordant cases analysis of benchmark PCR data was not able to detect clonality at any TR loci. Next, we examined whether the EuroClonality-NDC panel could detect clonality at each of the individual loci, resulting in sensitivity values of 95% or higher for all IG/TR loci, with the exception of those where limited benchmark data were available, i.e. IGL (n=3) and TRA (n=7). The specificity of the panel was assessed on benign reactive lesions (n=21) that did not contain clonal IG/TR rearrangements based on BIOMED-2/EuroClonality PCR results; no clonality was observed by EuroClonality-NDC in any of the 21 cases. Limit of detection (LOD) assessment to detect IG/TR rearrangements was performed using cell line blends with each of the 7 centres receiving blended cell lines diluted to 10%, 5.0%, 2.5% and 1.25%. Across all 7 centres the overall detection rate was 100%, 94.1%, 76.5% and 32.4% respectively, giving an overall LOD of 5%. Sufficient data were available in 239 samples for the analysis of translocations. The correct translocation was detected in 137 out of 145 cases, resulting in a sensitivity of 95%. Table 1 shows how translocations identified by the EuroClonality-NDC protocol were restricted to disease subtypes known to harbour those types of translocations. Analysis of CNA and somatic mutations in all samples is underway and will be presented at the meeting. Conclusions: The EuroClonality-NDC panel, with an optimised laboratory protocol and bioinformatics pipeline, detects IG and TR rearrangements and translocations with high sensitivity and specificity with a LOD ≤ 5% and provides a single end-to-end workflow for the simultaneous detection of IG/TR rearrangements, translocations, CNA and sequence variants. Table. Disclosures Stamatopoulos: Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Klapper:Roche, Takeda, Amgen, Regeneron: Honoraria, Research Funding. Ferrero:Gilead: Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EUSA Pharma: Membership on an entity's Board of Directors or advisory committees; Servier: Speakers Bureau. van den Brand:Gilead: Speakers Bureau. Groenen:Gilead: Speakers Bureau. Brüggemann:Incyte: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy. Langerak:Gilead: Research Funding, Speakers Bureau; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; Janssen: Speakers Bureau. Gonzalez:Roche: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau.

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A Comprehensive Analysis of Single-Cell Chromatin Accessibility and Gene Expression Identifies Intra-Tumor Heterogeneity and Molecular Treatment Responses in Relapsed/Refractory Multiple Myeloma

Blood ◽

10.1182/blood-2019-130051 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 575-575

Author(s):

Alexandra M Poos ◽

Jan-Philipp Mallm ◽

Stephan M Tirier ◽

Nicola Casiraghi ◽

Hana Susak ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Tumor Heterogeneity ◽

Mek Inhibitor ◽

Chromatin Accessibility ◽

University Research ◽

Sample Processing ◽

Advisory Committees

Introduction: Multiple myeloma (MM) is a heterogeneous malignancy of clonal plasma cells that accumulate in the bone marrow (BM). Despite new treatment approaches, in most patients resistant subclones are selected by therapy, resulting in the development of refractory disease. While the subclonal architecture in newly diagnosed patients has been investigated in great detail, intra-tumor heterogeneity in relapsed/refractory (RR) MM is poorly characterized. Recent technological and computational advances provide the opportunity to systematically analyze tumor samples at single-cell (sc) level with high accuracy and througput. Here, we present a pilot study for an integrative analysis of sc Assay for Transposase-Accessible Chromatin with high-throughput sequencing (scATAC-seq) and scRNA-seq with the aim to comprehensively study the regulatory landscape, gene expression, and evolution of individual subclones in RRMM patients. Methods: We have included 20 RRMM patients with longitudinally collected paired BM samples. scATAC- and scRNA-seq data were generated using the 10X Genomics platform. Pre-processing of the sc-seq data was performed with the CellRanger software (reference genome GRCh38). For downstream analyses the R-packages Seurat and Signac (Satija Lab) as well as Cicero (Trapnell Lab) were used. For all patients bulk whole genome sequencing (WGS) data was available, which we used for confirmatory studies of intra-tumor heterogeneity. Results: A comprehensive study at the sc level requires extensive quality controls (QC). All scATAC-seq files passed the QC, including the detected number of cells, number of fragments in peaks or the ratio of mononucleosomal to nucleosome-free fragments. Yet, unsupervised clustering of the differentially accessible regions resulted in two main clusters, strongly associated with sample processing time. Delay of sample processing by 1-2 days, e.g. due to shipment from participating centers, resulted in global change of chromatin accessibility with more than 10,000 regions showing differences compared to directly processed samples. The corresponding scRNA-seq files also consistently failed QC, including detectable genes per cell and the percentage of mitochondrial RNA. We excluded these samples from the study. Analysing scATAC-seq data, we observed distinct clusters before and after treatment of RRMM, indicating clonal adaptation or selection in all samples. Treatment with carfilzomib resulted in highly increased co-accessibility and >100 genes were differentially accessible upon treatment. These genes are related to the activation of immune cells (including T-, and B-cells), cell-cell adhesion, apoptosis and signaling pathways (e.g. NFκB) and include several chaperone proteins (e.g. HSPH1) which were upregulated in the scRNA-seq data upon proteasome inhibition. The power of our comprehensive approach for detection of individual subclones and their evolution is exemplarily illustrated in a patient who was treated with a MEK inhibitor and achieved complete remission. This patient showed two main clusters in the scATAC-seq data before treatment, suggesting presence of two subclones. Using copy number profiles based on WGS and scRNA-seq data and performing a trajectory analysis based on scATAC-seq data, we could confirm two different subclones. At relapse, a seemingly independent dominant clone emerged. Upon comprehensive integration of the datasets, one of the initial subclones could be identified as the precursor of this dominant clone. We observed increased accessibility for 108 regions (e.g. JUND, HSPA5, EGR1, FOSB, ETS1, FOXP2) upon MEK inhibition. The most significant differentially accessible region in this clone and its precursor included the gene coding for krüppel-like factor 2 (KLF2). scRNA-seq data showed overexpression of KLF2 in the MEK-inhibitor resistant clone, confirming KLF2 scATAC-seq data. KLF2 has been reported to play an essential role together with KDM3A and IRF1 for MM cell survival and adhesion to stromal cells in the BM. Conclusions: Our data strongly suggest to use only immediately processed samples for single cell technologies. Integrating scATAC- and scRNA-seq together with bulk WGS data showed that detection of individual clones and longitudinal changes in the activity of cis-regulatory regions and gene expression is feasible and informative in RRMM. Disclosures Goldschmidt: John-Hopkins University: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Chugai: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees.

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