MYC Rearrangements in Multiple Myeloma Are Complex, Can Involve More Than Five Different Chromosomes, and Correlate with Increased Expression of MYC and a Distinct Downstream Gene Expression Pattern

Abstract Introduction: The proto-oncogene MYC (locus 8q24.21) is a key transcription factor in multiple myeloma (MM) resulting in significant gene deregulation and impacting on many biological functions, including cell growth, proliferation, apoptosis, differentiation, and transformation. Chromosomal rearrangement and copy number change at the MYC locus are secondary events involved in MM progression, which are thought to lead to aggressive disease. Current analyses of the MYC locus have not been large and have reported rearrangements in 15% of new-diagnosed MM. However, more recent studies using advanced genomic techniques suggest that the frequency of MYC rearrangements may be much higher, and that a full reassessment of the role of MYC in MM pathogenesis may be critical. In this study, we analyzed 1280 MM patients to provide a better understanding of the role of this important genomic driver in MM pathogenesis. Methods: In total, 1280 tumor normal pairs of CD138 sorted bone marrow plasma cells and their germline control samples were analyzed by: 1. Targeted sequencing of 131 genes and 27 chromosome regions (n=100) with 4.5 Mb captured region surrounding MYC ; 2. Exome sequencing (n=461) with 2.3 Mb captured region surrounding MYC ; 3. Whole genome sequencing (n=719). Normalized tumor/germline depth ratio in targeted-sequencing cases and MANTA were used for detection of somatic copy number and structural variants. Expression analysis was performed using RNA-seq or microarrays. Results: MYC translocations were found in 25% (323/1280) of patients and occurred most frequently as inter-chromosomal translocations involving 2-5 chromosomes (90%, 291/323). Of the remaining cases, 5% (17/323) of the translocations involved inversion of chromosome 8 and 5% (15/323) were complex, affecting more than 5 chromosomal loci. The proportion of MYC translocations involving 2, 3, 4, and 5 loci was 62% (200/323), 23% (74/323), 8% (26/323) and 3% (8/323), respectively. Using abnormal rearranged cases (29/100), we found copy number imbalances >14.2 kb in size associated with a MYC translocation in 76% (22/29). Another 7% (2/29) of cases with translocations showed complex intra-chromosomal rearrangement. A region of 2.0 Mb surrounding MYC was identified as a translocation breakpoint hot-spot incorporating 96% of breakpoints. This region also contained two hotspots for chromosomal gain and tandem duplications. MYC rearrangements were not randomly distributed across the spectrum of MM with an excess being seen in hyperdiploidy (76% of rearranged samples, P <0.0001). Importantly, 67% (207/308) of cases with a MYC translocation involving 5 or less chromosomes had one of the commonly known super-enhancers involved in the translocation. Gene expression analysis was used to explore the impact of these events on downstream gene expression patterns. The results showed that inter- and/or intra-chromosomal rearrangements were associated with a significantly (P <0.0001) higher MYC expression (4.1-fold). In patients where rearrangements were associated with additional copies of MYC there was higher expression of MYC in comparison to cases with a translocation but lacking copy number gain (P=0.04). To identify downstream genes deregulated by MYC rearrangements we compared gene expression between those with and without a translocation, independently of hyperdiploidy. Genes that showed >2-fold change in expression (P <0.01) included MYC and the non-protein coding oncogene PVT1 that is located next to MYC . Genes with significantly lower levels of expression were involved in B-cell biology including CD79A and AHR, or were associated with cell proliferation, migration, adhesion, apoptosis and/or angiogenesis (FGF16, ADAMTS1, FBXL7, HRK, PDGFD, and PRKD1) . Conclusions: This study confirms the central role of MYC in the pathogenesis of clinical cases of MM, and as such defining it as a critical therapeutic target. We will be able to target MYC better if we understand how it is deregulated and in this respect we show that the MYC locus rearrangements are complex and it is a hot-spot for heterogeneous inter- as well intra-chromosomal rearrangements, including complex rearrangements involving >5 chromosomes. These events lead to increased MYC expression consistent with it being a driver of disease progression, particularly in the hyperdiploid subset of MM. Disclosures Mavrommatis: Celgene Corporation: Employment. Trotter: Celgene Corporation: Equity Ownership; Celgene Institute for Translational Research Europe: Employment. Davies: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Thakurta: Celgene Corporation: Employment, Equity Ownership. Morgan: Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Bristol Myers: Consultancy, Honoraria.

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Genomic Landscape Predictive of Minimal Residual Disease (MRD) in Multiple Myeloma (MM)

Blood ◽

10.1182/blood.v126.23.4212.4212 ◽

2015 ◽

Vol 126 (23) ◽

pp. 4212-4212

Author(s):

Mehmet K Samur ◽

Stephane Minvielle ◽

Florence Magrangeas ◽

Giovanni Parmigiani ◽

Kenneth C Anderson ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Board Of Directors ◽

Copy Number ◽

Residual Disease ◽

Copy Number Alterations ◽

Advisory Committees ◽

Genomic Landscape ◽

Equity Ownership ◽

Minimal Residual

Abstract Progress in the treatment of multiple myeloma (MM) has increased extent and frequency of response, as well as prolonged progression-free (PFS) and overall survival (OS). Today complete remission (CR) rates up to 70% are achieved with new drug combinations. This has lead to development of sensitive next generation sequencing (NGS) -based methods to predict deeper responses that may more accurately predict survival outcomes in MM. Our large recent study has confirmed the clinical impact of achieving MRD- status in MM. Here we are evaluating the genomic alterations that may predict attainment of MRD negative status in MM. MRD status was evaluted in 279 patients from IFM/DFCI 2009 trial. We obtained gene expression by RNA-seq, and copy number profile by cytoScan HD array to evaluate genomic differences between MRD negative and MRD positive groups. We generated copy number data for 175 / 279 patients (72 MRD- and 103 MRD+) with Affymetrix Cytoscan HD array and compared genome wide copy number alterations. We observed statistically significant copy number alterations in chromosome 1p, 2, 4q, 11q, 13, 14 and 20 between MRD- and MRD+ patients. However, the extent of alterations in these regions is limited. The largest difference was on chromosome 11q arm where MRD- patients had 2.2 copies on average and MRD+ had 2.4 (p value < 0.001). Similarly, we generated gene expression profiles with RNAseq for 69 MRD- patients and 92 MRD+ patients to study gene expression alterations that may predict attainment of MRD negative status and to examine possible biological pathways. Although first two component of principle component analysis (PCA) showed that two groups have similar expression profile, we were able to identify 586 differentially expressed genes; 333 of those were up and 253 were down regulated in MRD+ compared to MRD- groups. We found that seven oncogenes (CCND1, CD79B, IDH1, PATZ1, PAX5, POU2AF1, RUNX1) were significantly high in MRD+ and two (CCND2 and MYCN) were high in MRD-. Additional genes that were high in MRD+ samples were enriched in genes regulated by NF-kB in response to TNF, P53 pathway, KRAS signaling and genes down-regulated in response to ultraviolet (UV) radiation. Genes that were high in MRD- compared to MRD+ were also enriched in genes up-regulated by STAT5 in response to IL2 stimulation, p53 pathways and networks, and genes up-regulated in response to ultraviolet (UV) radiation pathways. Finally, we have created a signature to predict MRD+ and MRD- in MM samples from differentially expressed genes. We used 40 genes that has at least 2 fold change difference between MRD+ and MRD- groups as a predictor and we randomly separated 161 RNAseq samples into train (n=99) and test group (n=62). We developed our classifiers with diagonal discriminant analysis and we achieved 0.79 classifier performance on test dataset. Then we tested our signature against 1000 random signature and it was significantly different than random signatures (Figure). In conclusion, we here report a first genomic landscape predictive of minimal residual disease (MRD) in Multiple Myeloma (MM). This analysis will help understand genomic and molecular correlates of achieving minimal residula disease and confirms feasibility of using RNAseq data from diagnosis sample to predict MRD status. The ongoing integration of other genomic correlates such as copy number status as well as alternate splicing may allow further improvement in the performance of prediction. Figure 1. Figure 1. Disclosures Anderson: Gilead: Consultancy; acetylon pharmaceuticals: Equity Ownership; Oncocorp: Equity Ownership; Celgene Corporation: Consultancy; BMS: Consultancy; Millennium: Consultancy. Attal:jansen: Honoraria; celgene: Membership on an entity's Board of Directors or advisory committees. Munshi:onyx: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; novartis: Membership on an entity's Board of Directors or advisory committees.

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Role of Remission Status and Prior Transplant in Optimizing Survival Outcomes Following Allogeneic Hematopoietic Stem Transplantation (HSCT) in Patients Who Received Inotuzumab Ozogamicin (INO) for Relapsed / Refractory (R/R) Acute Lymphoblastic Leukemia (ALL)

Blood ◽

10.1182/blood.v130.suppl_1.886.886 ◽

2017 ◽

Vol 130 (Suppl_1) ◽

pp. 886-886

Author(s):

Partow Kebriaei ◽

Matthias Stelljes ◽

Daniel J. DeAngelo ◽

Nicola Goekbuget ◽

Hagop M. Kantarjian ◽

...

Keyword(s):

Board Of Directors ◽

Survival Probability ◽

Research Funding ◽

Employment Equity ◽

Inotuzumab Ozogamicin ◽

Advisory Committees ◽

Allogeneic Hsct ◽

Post Transplant ◽

Equity Ownership

Abstract Introduction: Attaining complete remission (CR) prior to HSCT is associated with better outcomes post-HSCT. Inotuzumab ozogamicin (INO), an anti-CD22 antibody conjugated to calicheamicin, has shown significantly higher remission rates (CR/CRi and MRD negativity) compared with standard chemotherapy (SC) in patients (pts) with R/R ALL (Kantarjian et al. N Engl J Med. 2016). Pts treated with INO were more likely to proceed to HSCT than SC, which allowed for a higher 2-yr probability of overall survival (OS) than patients receiving SC (39% vs 29%). We investigated the role of prior transplant and proceeding directly to HSCT after attaining remission from INO administration as potential factors in determining post-HSCT survival to inform when best to use INO in R/R ALL patients. Methods: The analysis population consisted of R/R ALL pts who were enrolled and treated with INO and proceeded to allogeneic HSCT as part of two clinical trials: Study 1010 is a Phase 1/2 trial (NCT01363297), while Study 1022 is the pivotal randomized Phase 3 (NCT01564784) trial. Full details of methods for both studies have been previously published (DeAngelo et al. Blood Adv. 2017). All reference to OS pertains to post-HSCT survival defined as time from HSCT to death from any cause. Results: As of March 2016, out of 236 pts administered INO in the two studies (Study 1010, n=72; Study 1022, n=164), 101 (43%) proceeded to allogeneic HSCT and were included in this analysis. Median age was 37 y (range 20-71) with 55% males. The majority of pts received INO as first salvage treatment (62%) and 85% had no prior SCT. Most pts received matched HSCTs (related = 25%; unrelated = 45%) with peripheral blood as the predominant cell source (62%). The conditioning regimens were mainly myeloablative regimens (60%) and predominantly TBI-based (62%). Dual alkylators were used in 13% of pts, while thiotepa was used in 8%. The Figure shows post-transplant survival in the different INO populations: The median OS post-HSCT for all pts (n=101) who received INO and proceeded to HSCT was 9.2 mos with a 2-yr survival probability of 41% (95% confidence interval [CI] 31-51%). In patients with first HSCT (n=86) the median OS post-HSCT was 11.8 mos with a 2-yr survival probability of 46% (95% CI 35-56%). Of note, some patients lost CR while waiting for HSCT and had to receive additional treatments before proceeding to HSCT (n=28). Those pts who went directly to first HSCT after attaining remission with no intervening additional treatment (n=73) fared best, with median OS post-HSCT not reached with a 2-yr survival probability of 51% (95% CI 39-62%). In the latter group, 59/73 (80%) attained MRD negativity, and 49/73 (67%) were in first salvage therapy. Of note, the post-HSCT 100-day survival probability was similar among the 3 groups, as shown in the Table. Multivariate analyses using Cox regression modelling confirmed that MRD negativity during INO treatment and no prior HSCT were associated with lower risk of mortality post-HSCT. Other prognostic factors associated with worse OS included older age, higher baseline LDH, higher last bilirubin measurement prior to HSCT, and use of thiotepa. Veno-occlusive disease post-transplant was noted in 19 of the 101 pts who received INO. Conclusion: Administration of INO in R/R ALL pts followed with allogeneic HSCT provided the best long-term survival benefit among those who went directly to HSCT after attaining remission and had no prior HSCT. Disclosures DeAngelo: Glycomimetics: Research Funding; Incyte: Consultancy, Honoraria; Blueprint Medicines: Honoraria, Research Funding; Takeda Pharmaceuticals U.S.A., Inc.: Honoraria; Shire: Honoraria; Pfizer Inc.: Consultancy, Honoraria, Research Funding; Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Research Funding; BMS: Consultancy; ARIAD: Consultancy, Research Funding; Immunogen: Honoraria, Research Funding; Celgene: Research Funding; Amgen: Consultancy, Research Funding. Kantarjian: Novartis: Research Funding; Amgen: Research Funding; Delta-Fly Pharma: Research Funding; Bristol-Meyers Squibb: Research Funding; Pfizer: Research Funding; ARIAD: Research Funding. Advani: Takeda/ Millenium: Research Funding; Pfizer: Consultancy. Merchant: Pfizer: Consultancy, Research Funding. Stock: Amgen: Consultancy; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wang: Pfizer: Employment, Equity Ownership. Zhang: Pfizer: Employment, Equity Ownership. Loberiza: Pfizer: Employment, Equity Ownership. Vandendries: Pfizer: Employment, Equity Ownership. Marks: Pfizer: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau.

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Role of Polycomb Repressive Complex 1 (PRC1) In Runx1 Mediated Gene Regulation

Blood ◽

10.1182/blood.v116.21.3863.3863 ◽

2010 ◽

Vol 116 (21) ◽

pp. 3863-3863

Author(s):

Ming Yu ◽

Tali Mazor ◽

Hui Huang ◽

Emily Huang ◽

Katie Kathrein ◽

...

Keyword(s):

Gene Regulation ◽

Board Of Directors ◽

Target Genes ◽

Polycomb Repressive Complex ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Human T Cell ◽

Equity Ownership ◽

Polycomb Repressive Complex 1

Abstract Abstract 3863 The transcription factor Runx1 is required for the generation of all definitive hematopoietic stem cells (HSCs), and for normal megakaryocyte, lymphocyte and granulocyte terminal maturation. Runx1 and its cofactor CBF-β are also the most common targets of chromosomal translocations in human leukemias. Somatic and germline point mutations in Runx1 occur in myelodysplastic syndrome and undifferentiated leukemias, and are associated with a poor prognosis. Despite the key roles that Runx1 plays in normal and malignant hematopoiesis, its transcriptional mechanisms remain incompletely understood. In this study, we purified Runx1 containing multiprotein complexes from megakaryocytic cells and identified several associated chromatin-remodeling complexes, including Polycomb Repressive Complex 1 (PRC1), NuRD, SWI/SNF and MLL/TrxG. Interactions were validated by independent biochemical assays and demonstrate a direct interaction between Runx1 and the PRC1 component Bmi1. ChIP-seq studies identified a large overlap between Runx1/CBF-β and Ring1b (another PRC1 core component) occupied sites, with 45% of the peaks at these genes < 200 bp from each other. ShRNA mediated gene knockdown of CBF-β shows differential gene expression of many of the co-occupied genes. Among the direct CBF-β/Ring1b co-occupied targets are other key hematopoietic transcription factors including FOG-1, SCL and Lyl1, and a number of cell adhesion related genes. ShRNA knockdown of Ring1b impairs megakaryocyte endomitosis, partially phenocopying Runx1 deficient megakaryocytes. Morpholino mediated knockdown of Ring1b or Bmi1 in zebrafish embryos reduces the number of phenotypic definitive HSCs, also partially phenocopying Runx1 morphants. We also show that Runx1/CBF-β interact with Ring1b in the human T cell line Jurkat, and that Ring1b occupies Runx1/CBF-β bound sites of key direct target genes in primary murine thymocytes, including CD4, TCRβ, and Th-POK. Surprisingly, we did not find enrichment for histone 2A monoubiquitination at most of the megakaryocytic and T-lymphocyte co-occupied sites examined, suggesting that PRC1 acts through alternate mechanisms at these genes. Collectively, these data provide evidence for a broad role of PRC1 in Runx1 mediated gene regulation. Disclosures: Zon: FATE, Inc.: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Stemgent: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Cantor:Amgen, Inc: Consultancy.

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Deregulation of TNFRSF18 (GITR) Through Promoter CpG Island Methylation Induces Tumor Proliferation in Multiple Myeloma

Blood ◽

10.1182/blood.v118.21.2424.2424 ◽

2011 ◽

Vol 118 (21) ◽

pp. 2424-2424

Author(s):

Yang Liu ◽

Yong Zhang ◽

Phong Quang ◽

Hai T Ngo ◽

Feda Azab ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Flow Cytometry ◽

Board Of Directors ◽

Research Funding ◽

Plasma Cells ◽

Cpg Island ◽

Advisory Committees ◽

Brdu Assay

Abstract Abstract 2424 Introduction Tumor necrosis factor receptor super families (TNFRSFs) play an important role in activation of lymphocyte and cell apoptosis. However the function of TNFRSFs in multiple myeloma (MM) remains unknown. Loss of function mutation of Fas antigen (TNFRSF6) was identified in MM cells, thus suggesting the possible role of TNFRSFs in regulating MM pathogenesis. We therefore investigated the epigenetic mechanisms that may mediate inactivation of TNFRSFs and its functional role in MM. Methods Dchip software was utilized for analyzing gene expression dataset. DNA was extracted from both primary CD138+ MM plasma cells and MM cell lines using blood & tissue DNA isolation kit (Qiagen, Inc.). Expression of GITR in primary CD138+ plasma cells was detected by Imunohistochemistry (IHC) DNA methylation was analyzed by methylated DNA immunoprecipitation (Medip) assay and bisulfate sequencing. 5'azacytidine was used to demethylate genomic DNA. Gene expression was detected by qRT-PCR and confirmed at the protein level by flow cytometry and western-blot. Over-expression of GITR was obtained in MM1.S cells by using GITR recombinant plasmid and electroporation. Apoptosis was determined using Annexin/PI staining and flow cytometry analysis. Activation of apoptotic signaling was studied by western blot. Cell survival and proliferation were analyzed by MTT and BrdU assay, respectively. Recombinant GITR-lentivirus was obtained from the supernatant of culture medium after 72 hours transfection in 293 cells. GFP positive MM cells were sorted and analyzed by flow cytometry. In vivo effect of GITR on MM tumor growth was determined by injection of GITR over-expressing MM cells in null mice. Mice skull, femur and vertebrae were isolated after 4 weeks injection. Anti-human CD138+ mAb microbead was used to detect MM cells extracted from mice tissue by flow cytometry. Results Gene-expression profiling showed down-regulation of TNFRSFs, including TNFRSF11A, TNFRSF11B, TNFRSF8, TNFRSF10C, TNFRSF9, TNFRSF21, TNFRSF1B, TNFRSF1A and TNFRSF18, compared to normal plasma cells. Moreover, Our IHC results also showed that GITR expression was positive in primary CD138+ plasma cells from 9 normal bone marrow, but negative in 9 MM samples. Importantly, we found that low GITR expression significantly correlated with MM progression. Indeed, GITR gene levels were lower in smoldering and active MM patients compared to MGUS patients and normal donors. Promoter CpG island (CGI) methylation of GITR was indentified in 5 out of 7 MM primary bone marrow (BM)-derived CD138+ cells but not in normal BM-derived plasma cells. Bisulfate sequencing and Medip assay showed that methylation of GITR was significantly associated with GITR expression in 5 MM cell lines, including MM1.S, OPM1, U266, RPMI and INA6. Promoter CGI of GITR was highly methylated leading to complete silencing of GITR in MM1.S cell line. GITR expression was significantly up-regulated in MM cells upon treatment with the 5'azacytidine. MTT and BrdU assay revealed that the proliferation and survival of MM1.S cells was disrupted in the GITR over-expressing MM1.S cells, notably with inhibition of cell proliferation compared to control vector infected cells. Moreover induction of cytotoxicity in GITR over-expressing cells was confirmed by using GFP competition assay. GITR-induced apoptosis was supported by induction of caspase 8 and 3 cleavage. The inhibition of human CD138+ plasma cell growth in the bone marrow of SCID mice using a disseminated MM xenograft model was observed in the experimental group injected with GITR expressing cells compared to the control group after 4 weeks injection. Conclusion Our findings uncovered a novel epigenetic mechanism contributing to MM pathogenesis, showing the role of GITR methylation as a key regulator of MM cell survival. Disclosures: Roccaro: Roche:. Ghobrial:Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Noxxon: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Absence Of Mutation In Cereblon (CRBN) and DNA Damage Binding Protein 1 (DDB1) Genes In Myeloma Cells and Patients and Its Clinical Significance

Blood ◽

10.1182/blood.v122.21.3139.3139 ◽

2013 ◽

Vol 122 (21) ◽

pp. 3139-3139

Author(s):

Anjan Thakurta ◽

Anita K Gandhi ◽

Michelle Waldman ◽

Chad C. Bjorklund ◽

Suzanne Lentzsch ◽

...

Keyword(s):

Board Of Directors ◽

Cell Lines ◽

Research Funding ◽

Heterozygous Mutation ◽

Employment Equity ◽

Advisory Committees ◽

Single Nucleotide ◽

Truncating Mutation ◽

Equity Ownership

Abstract Background CRBN, a target of thalidomide and IMiDs® immunomodulatory agents lenalidomide (LEN) and pomalidomide (POM), is a component of the E3 ubiquitin cullin 4 ring ligase (CRL4) complex that also includes DDB1, Roc1, and Cul4. Two CRBN mutations have been reported in multiple myeloma (MM) patients: truncating mutation (Q99) and point mutation (R283K). One copy of the CRBN gene was shown to be deleted in the MM1S and MM1S.R cell lines. No DDB1 mutation has been described previously. Results We investigated the incidence of CRBN and DDB1 mutations by next-generation sequencing in 20 MM cell lines and MM subjects. Of 90 MM patients, 24 were newly diagnosed and 66 were relapsed and refractory of which 36 patients were LEN resistant. Out of the cell lines tested, 1 heterozygous CRBN mutation (D249Y) was found in the LEN-resistant ANBL6R cells, which is located in the putative DDB1 binding domain, and 2 single silent mutations were identified in the KMS-12-BM (rs17027638) and OPM-2 cells. One DDB1 heterozygous mutation (E303D) was identified in ANBL6 cells. In the cohort of patients assessed, no CRBN mutation was detected; however, 5 single nucleotide variations (SNV) were identified. Three of the 5 SNVs were at position 735 (Y245Y) and 1 each at position 219 (H73H) and 939 (C313C), respectively. The first 2 SNVs (rs17027638 and rs1045309) are described but not the last. We found a single SNV (P51P; rs2230356) in DDB1 gene the patient samples. Conclusion Mutations within the coding sequences of CRBN and DDB1 are rare in MM patients and cell lines. Most intrinsically LEN-resistant cells and cell lines made resistant to LEN or POM do not have CRBN or DDB1 mutations, suggesting the potential role of other sources, such as genetic or epigenetic pathways in developing resistance to IMiD drug–based therapy. Disclosures: Thakurta: Celgene: Employment, Equity Ownership. Gandhi:Celgene: Employment, Equity Ownership. Waldman:Celgene: Employment, Equity Ownership. Bjorklund:Celgene: Employment, Equity Ownership. Lentzsch:Celgene: Research Funding. Schey:Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; NAPP: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau. Orlowski:Bristol-Myers Squibb: Honoraria, 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; Millennium: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Resverlogix: Research Funding; Array: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Membership on an entity’s Board of Directors or advisory committees. Madan:Covance Genomics Lab: Employment. Ning:Celgene: Employment, Equity Ownership. Mendy:Celgene: Employment, Equity Ownership. Lopez-Girona:Celgene: Employment, Equity Ownership. Schafer:Celgene: Employment, Equity Ownership. Avet-Loiseau:Celgene: Research Funding. Chopra:Celgene: Employment, Equity Ownership.

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Two Novel Distinct Subtypes of Myeloid Neoplasms Molecularly Associated with Histone H3K36 Methylations

Blood ◽

10.1182/blood.v126.23.2841.2841 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2841-2841 ◽

Cited By ~ 1

Author(s):

Yosaku Watatani ◽

Yasunobu Nagata ◽

Vera Grossmann ◽

Yusuke Okuno ◽

Tetsuichi Yoshizato ◽

...

Keyword(s):

Gene Expression ◽

Copy Number ◽

Copy Number Variations ◽

Healthy Controls ◽

Employment Equity ◽

Gene Deletions ◽

Myeloid Neoplasms ◽

Frequent Mutations ◽

Equity Ownership

Abstract Myelodysplastic syndromes (MDS) and related disorders are a heterogeneous group of chronic myeloid neoplasms with a high propensity to acute myeloid leukemia. A cardinal feature of MDS, as revealed by the recent genetic studies, is a high frequency of mutations and copy number variations (CNVs) affecting epigenetic regulators, such as TET2, IDH1/2, DNMT3A, ASXL1, EZH2, and other genes, underscoring a major role of deregulated epigenetic regulation in MDS pathogenesis. Meanwhile, these mutations/deletions have different impacts on the phenotype and the clinical outcome of MDS, suggesting that it should be important to understand the underlying mechanism for abnormal epigenetic regulation for better classification and management of MDS. SETD2 and ASH1L are structurally related proteins that belong to the histone methyltransferase family of proteins commonly engaged in methylation of histone H3K36. Both genes have been reported to undergo frequent somatic mutations and copy number alterations, and also show abnormal gene expression in a variety of non-hematological cancers. Moreover, germline mutation of SETD2 has been implicated in overgrowth syndromes susceptible to various cancers. However, the role of alterations in these genes has not been examined in hematological malignancies including myelodysplasia. In this study, we interrogated somatic mutations and copy number variations, among a total of 1116 cases with MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), who had been analyzed by target deep sequencing (n=944), and single nucleotide polymorphism-array karyotyping (SNP-A) (n=222). Gene expression was analyzed in MDS cases and healthy controls, using publically available gene expression datasets. SETD2 mutations were found in 6 cases, including 2 with nonsense and 4 with missense mutations, and an additional 10 cases had gene deletions spanning 1.8-176 Mb regions commonly affecting the SETD2 locus in chromosome 3p21.31, where SETD2 represented the most frequently deleted gene within the commonly deleted region. SETD2 deletion significantly correlated with reduced SETD2 expression. Moreover, MDS cases showed a significantly higher SETD2 expression than healthy controls. In total, 16 cases had either mutations or deletions of the SETD2 gene, of which 70% (7 out of 10 cases with detailed diagnostic information) were RAEB-1/2 cases. SETD2 -mutated/deleted cases had frequent mutations in TP53 (n=4), SRSF2 (n=3), and ASXL1 (n=3) and showed a significantly poor prognosis compared to those without mutations/deletions (HR=3.82, 95%CI; 1.42-10.32, P=0.004). ASH1L, on the other hand, was mutated and amplified in 7 and 13 cases, respectively, of which a single case carried both mutation and amplification with the mutated allele being selectively amplified. All the mutations were missense variants, of which 3 were clustered between S1201 and S1209. MDS cases showed significantly higher expression of ASH1L compared to healthy controls, suggesting the role of ASH1L overexpression in MDS development. Frequent mutations in TET2 (n=8) and SF3B1 (n=6) were noted among the 19 cases with ASH1L lesions. RAEB-1/2 cases were less frequent (n=11) compared to SETD2-mutated/deleted cases. ASH1L mutations did not significantly affect overall survival compared to ASH1L-intact cases. Gene Set Expression Analysis (Broad Institute) on suppressed SETD2 and accelerated ASH1L demonstrated 2 distinct expression signatures most likely due to the differentially methylated H3K36. We described recurrent mutations and CNVs affecting two histone methyltransferase genes, which are thought to represent novel driver genes in MDS involved in epigenetic regulations. Given that SETD2 overexpression and reduced ASH1L expression are found in as many as 89% of MDS cases, deregulation of both genes might play a more role than expected from the incidence of mutations and CNVs alone. Although commonly involved in histone H3K36 methylation, both methyltransferases have distinct impacts on the pathogenesis and clinical outcome of MDS in terms of the mode of genetic alterations and their functional consequences: SETD2 was frequently affected by truncating mutations and gene deletions, whereas ASH1L underwent gene amplification without no truncating mutations, suggesting different gene targets for both methyltransferases, which should be further clarified through functional studies. Disclosures Alpermann: MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Shih:Novartis: Research Funding.

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CD200 Is a Stem Cell-Specific Immunosuppressive Target in AML

Blood ◽

10.1182/blood-2018-99-114818 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2768-2768

Author(s):

Shelley Herbrich ◽

Keith Baggerly ◽

Gheath Alatrash ◽

R. Eric Davis ◽

Michael Andreeff ◽

...

Keyword(s):

Gene Expression ◽

Flow Cytometry ◽

T Cells ◽

Stem Cell ◽

Board Of Directors ◽

Research Funding ◽

Advisory Committees ◽

Cd200 Receptor ◽

Blast Cells ◽

Equity Ownership

Abstract Acute myeloid leukemia (AML) stem cells (LSC) are an extremely rare fraction of the overall disease (likely <0.3%), largely quiescent, and capable of both long-term self-renewal and production of more differentiated leukemic blasts. Besides their role in disease initiation, they are also hypothesized as the likely source of deadly, relapsed leukemia. Due to the quiescent nature of the LSCs, they are capable of evading the majority of chemotherapeutic agents that rely on active cell-cycling for cytotoxicity. Therefore, novel therapeutic approaches specifically engineered to eradicate LSCs are critical for curing AML. We previously introduced a novel bioinformatics approach that harnessed publically available AML gene expression data to identify genes significantly over-expressed in LSCs when compared to their normal hematopoietic stem cell (HSC) counterparts (Herbrich et al Blood 2017 130:3962). These datasets contain gene expression arrays on human AML patient samples sorted by leukemia stem, progenitor, and blast cells (with normal hematopoietic cell subsets for comparison). We have since expanded our statistical model to identify targets that are both significantly overexpressed in AML LSCs when compared to HSC as well as LSCs compared to their corresponding, more differentiated blast cells. Instead of traditional methods for multiple testing corrections, we looked at the intersection of genes that met the above criteria in 3 independently generated datasets. This resulted in a list of 30 genes, 28 of which appear to be novel markers of AML LSCs. From this list, we first chose to focus on CD200, a type-1 transmembrane glycoprotein. CD200 is broadly expressed on myeloid, lymphoid, and epithelial cells, while the CD200 receptor (CD200R) expression is strictly confined to myeloid and a subset of T cells. CD200 has been shown to have an immunosuppressive effect on macrophages and NK cells and correlates with a high prevalence FOXP3+ regulatory T cells (Coles et al Leukemia 2012; 26:2146-2148). Additionally, CD200 has been implicated as a poor prognostic marker in AML (Damiani et al Oncotarget 2015; 6:30212-30221). To date, we have screened 20 primary AML patient samples by flow cytometry, 90% of which are positive for CD200. Expression is significantly enriched in the CD34+/CD123+ stem cell compartment. To examine the role of CD200 in AML, we established two in vitro model systems. First, we used CRISPR/Cas9 to knockout the endogenous CD200 protein in Kasumi-1. Further, we induced CD200 in the OCI-AML3 cell line that had no expression at baseline. Both cell lines did not express the CD200 receptor before or after manipulation, negating any autocrine signaling. In both systems, CD200 manipulation did not affect the proliferation rate or viability of the cells. To examine the immune function of CD200 in AML, we performed a series of mixed lymphocyte reactions. We cultured normal human peripheral blood mononuclear cells (PBMCs) with the CD200+ or CD200- cells from each line both. Cells were incubated in the culture media for 4-48 hours before being harvested and measured by flow cytometry for apoptosis or intracellular cytokine production. The presence of CD200 on the cell surface reduced the rate of immune-specific apoptosis among these leukemia cells. The difference in cell killing was most likely attributable to a CD200-specific suppression of CD107a, a surrogate marker or cytotoxic activity. In the OCI-AML3 model, PBMCs co-cultured with CD200+ cells produced approximately 40% less CD107a when compared to the CD200- co-culture. Additionally, we characterized our new cell lines using RNA sequencing. By comparing the CD200+ to the CD200- cells within each line, we observed that CD200+ cells significantly downregulate genes involved in defining an inflammatory response as well as genes regulated by NF-κB in response to TNFα. This indicates that CD200 may have an undiscovered intrinsic role in suppressing the immune microenvironment of AML LSCs. In conclusion, we have expanded our novel bioinformatics approach for robustly identifying AML LSC-specific targets. Additionally, we have shown that one of these markers, CD200, has a potential role as a stem cell-specific immunosuppressive target by reducing immune-mediated apoptosis and transcriptionally suppressing inflammatory cell processes. We are extending our study to explore CD200 in primary patient samples using a CD200-blocking antibody. Disclosures Andreeff: SentiBio: Equity Ownership; Amgen: Consultancy, Research Funding; Oncolyze: Equity Ownership; Reata: Equity Ownership; United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; Jazz Pharma: Consultancy; Astra Zeneca: Research Funding; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy. Konopleva:Stemline Therapeutics: Research Funding.

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Comparative Analysis of Independent Ex Vivo functional Drug Screens Identifies Predictive Biomarkers of BCL-2 Inhibitor Response in AML

Blood ◽

10.1182/blood-2018-99-111916 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2763-2763 ◽

Cited By ~ 1

Author(s):

Brian S. White ◽

Suleiman A. Khan ◽

Muhammad Ammad-ud-din ◽

Swapnil Potdar ◽

Mike J Mason ◽

...

Keyword(s):

Gene Expression ◽

Board Of Directors ◽

Research Funding ◽

Drug Response ◽

Ex Vivo ◽

Predictive Performance ◽

Data Sets ◽

Advisory Committees ◽

Data Set ◽

Equity Ownership

Abstract Introduction: Therapeutic options for patients with AML were recently expanded with FDA approval of four drugs in 2017. As their efficacy is limited in some patient subpopulations and relapse ultimately ensues, there remains an urgent need for additional treatment options tailored to well-defined patient subpopulations to achieve durable responses. Two comprehensive profiling efforts were launched to address this need-the multi-center Beat AML initiative, led by the Oregon Health & Science University (OHSU) and the AML Individualized Systems Medicine program at the Institute for Molecular Medicine Finland (FIMM). Methods: We performed a comparative analysis of the two large-scale data sets in which patient samples were subjected to whole-exome sequencing, RNA-seq, and ex vivo functional drug sensitivity screens: OHSU (121 patients and 160 drugs) and FIMM (39 patients and 480 drugs). We predicted ex vivo drug response [quantified as area under the dose-response curve (AUC)] using gene expression signatures selected with standard regression and a novel Bayesian model designed to analyze multiple data sets simultaneously. We restricted analysis to the 95 drugs in common between the two data sets. Results: The ex vivo responses (AUCs) of most drugs were positively correlated (OHSU: median Pearson correlation r across all pairwise drug comparisons=0.27; FIMM: median r=0.33). Consistently, a samples's ex vivo response to an individual drug was often correlated with the patient's Average ex vivo Drug Sensitivity (ADS), i.e., the average response across the 95 drugs (OHSU: median r across 95 drugs=0.41; FIMM: median r=0.58). Patients with a complete response to standard induction therapy had a higher ADS than those that were refractory (p=0.01). Further, patients whose ADS was in the top quartile had improved overall survival relative to those having an ADS in the bottom quartile (p<0.05). Standard regression models (LASSO and Ridge) trained on ADS and gene expression in the OHSU data set had improved ex vivo response prediction performance as assessed in the independent FIMM validation data set relative to those trained on gene expression alone (LASSO: p=2.9x10-4; Ridge: p=4.4x10-3). Overall, ex vivo drug response was relatively well predicted (LASSO: mean r across 95 drugs=0.62; Ridge: mean r=0.62). The BCL-2 inhibitor venetoclax was the only drug whose response was negatively correlated with ADS in both data sets. We hypothesized that, whereas the predictive performance of many other drugs was likely dependent on ADS, the predictive performance of venetoclax (LASSO: r=0.53, p=0.01; Ridge: r=0.63, p=1.3x10-3) reflected specific gene expression biomarkers. To identify biomarkers associated with venetoclax sensitivity, we developed an integrative Bayesian machine learning method that jointly modeled both data sets, revealing several candidate biomarkers positively (BCL2 and FLT3) or negatively (CD14, MAFB, and LRP1) correlated with venetoclax response. We assessed these biomarkers in an independent data set that profiled ex vivo response to the BCL-2/BCL-XL inhibitor navitoclax in 29 AML patients (Lee et al.). All five biomarkers were validated in the Lee data set (Fig 1). Conclusions: The two independent ex vivo functional screens were highly concordant, demonstrating the reproducibility of the assays and the opportunity for their use in the clinic. Joint analysis of the two data sets robustly identified biomarkers of drug response for BCL-2 inhibitors. Two of these biomarkers, BCL2 and the previously-reported CD14, serve as positive controls credentialing our approach. CD14, MAFB, and LRP1 are involved in monocyte differentiation. The inverse correlation of their expression with venetoclax and navitoclax response is consistent with prior reports showing that monocytic cells are resistant to BCL-2 inhibition (Kuusanmäki et al.). These biomarker panels may enable better selection of patient populations likely to respond to BCL-2 inhibition than would any one biomarker in isolation. References: Kuusanmäki et al. (2017) Single-Cell Drug Profiling Reveals Maturation Stage-Dependent Drug Responses in AML, Blood 130:3821 Lee et al. (2018) A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia, Nat Commun 9:42 Disclosures Druker: Cepheid: Consultancy, Membership on an entity's Board of Directors or advisory committees; ALLCRON: Consultancy, Membership on an entity's Board of Directors or advisory committees; Fred Hutchinson Cancer Research Center: Research Funding; Celgene: Consultancy; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Third Coast Therapeutics: Membership on an entity's Board of Directors or advisory committees; Oregon Health & Science University: Patents & Royalties; Patient True Talk: Consultancy; Millipore: Patents & Royalties; Monojul: Consultancy; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; GRAIL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Beta Cat: 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; Henry Stewart Talks: Patents & Royalties; Bristol-Meyers Squibb: Research Funding; 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; McGraw Hill: Patents & Royalties; ARIAD: Research Funding; Novartis Pharmaceuticals: Research Funding. Heckman:Orion Pharma: Research Funding; Novartis: Research Funding; Celgene: Research Funding. Porkka:Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Tyner:AstraZeneca: Research Funding; Incyte: Research Funding; Janssen: Research Funding; Leap Oncology: Equity Ownership; Seattle Genetics: Research Funding; Syros: Research Funding; Takeda: Research Funding; Gilead: Research Funding; Genentech: Research Funding; Aptose: Research Funding; Agios: Research Funding. Aittokallio:Novartis: Research Funding. Wennerberg:Novartis: Research Funding.

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Biomarkers of Overall Survival and Response to Glasdegib and Intensive or Non-Intensive Chemotherapy in Patients with Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2018-99-111239 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2733-2733 ◽

Cited By ~ 1

Author(s):

Jorge E. Cortes ◽

Akil Merchant ◽

Catriona Jamieson ◽

Daniel A Pollyea ◽

Michael Heuser ◽

...

Keyword(s):

Gene Expression ◽

Board Of Directors ◽

Research Funding ◽

Intensive Therapy ◽

Employment Equity ◽

Advisory Committees ◽

Expression Levels ◽

Biomarker Analysis ◽

Cytokine Levels ◽

Equity Ownership

Abstract Background: In a previously reported Phase 2 randomized study of patients with acute myeloid leukemia (AML), addition of the investigational agent glasdegib (PF-04449913) to low-dose cytarabine (LDAC) improved overall survival (OS) when compared with LDAC alone. In a non-randomized study arm, glasdegib together with 7+3 chemotherapy was well tolerated and associated with clinical activity. We used a comprehensive biomarker analysis, evaluating gene expression, circulating cytokine levels, and gene mutations, to identify molecular drivers that predict overall response (OR) and OS. Methods: In this Phase 2 multicenter study (NCT01546038), patients with AML who were suitable for non-intensive therapy were randomized (2:1) to LDAC + glasdegib 100 mg QD or LDAC alone, and patients suitable for intensive therapy were assigned 7+3 plus glasdegib 100 mg QD. Whole blood, serum, and bone marrow aspirate samples were collected at baseline, and used to assess 19 genes for expression analysis, 38 analytes for circulating cytokine levels, and 109 genes for mutation analysis. Gene expression was analyzed using TaqMan Low Density Array Cards (TLDCs), cytokine levels were analyzed using quantitative, multiplexed immunoassays (Myriad RBM), and mutation analysis was performed using the Illumina® MiSeq instrument (San Diego, CA). All correlations were performed either for OS or for OR. For gene expression and cytokine analysis, a cut-off value above or below the median expression level for each treatment arm was used to separate samples into two subgroups (< or ≥ the median value) to explore the relationship of expression levels with OS data. Criteria for significance in the non-intensive cohort required one subgroup to have a p-value of <0.05 in the between-treatment arms comparison and the HR difference between the two subgroups to be ≥2 fold. Responses were defined as patients with a complete remission (CR), CR with incomplete blood count recovery (CRi), morphologic leukemia-free state, partial remission (PR), or PRi. For response correlations, genes or cytokines were considered to be differentially expressed if they had a p-value <0.05 and were differentially expressed by ≥2-fold. Results: Within the non-intensive arm (LDAC + glasdegib, n=68; LDAC alone, n=30), expression levels of several genes correlated with improved OS with glasdegib plus LDAC. Lower levels of expression of FOXM1 and MSI2, and higher expression levels of BCL2 and CCND2 correlated with improved OS with the combination. Additionally, lower levels of the cytokines 6CKINE (CCL21), ICAM-1, MIP-1α, and MMP-3 correlated with improved OS. An analysis of correlations of gene expression and cytokine levels with OR could not be completed due to the low number of responders in the LDAC only group (n=2). In the intensive treatment arm (glasdegib and 7+3, n=59), higher PTCH1 expression correlated with improved OS (p=0.0219, median OS 10.8 versus 39.5 months). In this cohort, lower levels of IL-8 (p=0.0225) and MIP-3β (p=0.0403) correlated with lower OS. Expression levels of no genes or cytokines significantly correlated with OR in this arm. We also examined correlations between gene mutation status and OS in both study arms. In the non-intensive arm (LDAC + glasdegib, n=58; LDAC alone, n=25), no genes mutated in at least 5 patients correlated with OS. In the intensive treatment arm (n=47), mutations in FLT3, TP53, CEP170, NPM1, and ANKRD26 correlated with OS (all p<0.05). Patients in this arm with FLT3 mutations responded better than patients with wild type FLT3 (p=0.0336, median OS of 13.1 months versus unreached for FLT3 mutant). Conclusions: In this biomarker analysis, we found that expression levels of a select number of genes and circulating cytokines implicated in AML correlated with OS in the non-intensive and the intensive arms. The improved response for patients with FLT3 mutations and high PTCH1 expression levels in the intensive arm deserves further investigation. These findings need to be verified in larger controlled studies, which are ongoing. Disclosures Cortes: Novartis: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Arog: Research Funding. Pollyea:Argenx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy; Celyad: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding; Curis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Heuser:Astellas: Research Funding; Daiichi Sankyo: Research Funding; Sunesis: Research Funding; Tetralogic: Research Funding; Bayer Pharma AG: Consultancy, Research Funding; StemLine Therapeutics: Consultancy; Janssen: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; BergenBio: Research Funding; Karyopharm: Research Funding. Chan:Pfizer: Employment, Equity Ownership. Wang:Pfizer: Employment, Equity Ownership. Ching:Pfizer Inc: Employment, Equity Ownership. Johnson:Pfizer Inc: Employment, Equity Ownership. O'Brien:Pfizer Inc: Employment, Equity Ownership.

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Chromothripsis and Chromoplexy Are Associated with DNA Instability and Adverse Clinical Outcome in Multiple Myeloma

Blood ◽

10.1182/blood-2018-99-117359 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 408-408 ◽

Cited By ~ 1

Author(s):

Cody Ashby ◽

Michael A Bauer ◽

Yan Wang ◽

Christopher P. Wardell ◽

Ruslana G. Tytarenko ◽

...

Keyword(s):

Dna Repair ◽

Board Of Directors ◽

Copy Number ◽

Structural Rearrangements ◽

Employment Equity ◽

Advisory Committees ◽

Oxford Nanopore ◽

Long Read ◽

Equity Ownership ◽

Median Expression

Abstract Introduction: Chromothripsis and chromoplexy are gross structural events that deregulate multiple genes simultaneously and may help explain rapid changes in clinical behavior. Previous screening studies in multiple myeloma (MM) using copy number arrays have identified chromothripsis at a low frequency (1.3%) and suggested it adversely impacts prognosis. Here, using whole genome sequencing (WGS) data we have identified a higher frequency of these events, suggesting they are more common than previously thought. Methods: 10X ChromiumWGS (10XWGS) from 76 newly diagnosed MM (NDMM) patients were analyzed for structural rearrangements using Longranger. Oxford Nanopore long read sequencing was performed on 2 samples. Long insert WGS data from 813 NDMM patient samples from the Myeloma Genome Project (MGP) were analyzed for structural rearrangements using Manta. Whole exome sequencing was available for 712 samples. RNA-seq was available for 643 samples. Chromothripsis was determined by manual curation of breakpoint and copy number data. Chromoplexy was defined as rearrangements within 1 Mb of one another involving 3 or more chromosomes. Results: Chromoplexy was detected in 33/76 (46%) cases using 10XWGS data, and cross validated in the MGP WGS dataset being found in 30% (247/813) of samples and was most frequent on chromosomes 8 (11.7% of samples), 14 (10.6%), 11 (9.6%), 1 (9.5%), 6 (8.0%), 22 (7.6%), 12 (6.7%), and 17 (6.7%). The gene regions most involved in chromoplexy events were MYC (chr8; 7.3%), IGH (chr14, 8.8%), IGL (chr22; 4.6%), CCND1 (chr11; 3.9%), TXNDC5 (chr6; 1.7%), FCHSD2 (chr11; 1.4%), FAM46C (chr1; 1.2%), MMSET (chr4; 1.2%), and MAP3K14 (chr17; 0.7%). Chromoplexy samples involved pairings of super-enhancer donors (IGH, IGL, FAM46C, TXNDC5) and oncogenic receptors (CCND1, MMSET, MAP3K14, MYC) implicating transcriptional deregulation. To confirm, RNASeq showed an elevation of expression over median in the oncogenic receptors when paired with a donor: CCND1 (median expression = 12.0 vs. median expression with donor = 17.9), MAP3K14 (10.8 vs. 14.7), MYC (12.7 vs. 14.1) and MMSET (11.9 vs. 16.7). We also identified elevated expression of PAX5 (8.23 vs. 13.79) and two cases where BCL2 (13.32 vs. 14.68) partnered with MYC, one involved IGH similar to follicular lymphoma. To determine if chromoplexy events were happening on the same allele, we performed long read sequencing using Oxford Nanopore on a sample with a t(2;6;8;11) event. We observed a read mapped to chromosome 2, with secondary alignment to chromosomes 6 and 8. This single 32 kb read was a continuous t(2;6;8) event, proving these events occurred on the same allele. However, despite close proximity, the data did not put the t(8;11) in the same read meaning this event occurred on a different allele or sub-clone, suggesting ongoing genomic instability. Chromothripsis was detected in 16/76 (21%) cases using 10XWGS, and was consistent in MGP data, (170/813; 21%). Chromothripsis occurred on all chromosomes but at different frequencies where chromosome 1 had most events (5.1%), followed by 14 (2.4%), 11 (2.3%), 12 (2.2%), 20 (1.9%), 17 (1.9%), and 8 (1.9%). We hypothesized the presence of both chromoplexy and chromothripsis could be associated with ineffective DNA repair and indeed, using WES data, patients with both events show more mutations in TP53 (19% vs. 5%) and ATM (10% vs. 4%) implicating homologous recombination deficiency as an etiologic mechanism. Gene set enrichment analysis showed significant enrichment and positive normalized enrichment score (NES) for the DNA Repair (P = 0.01; NES = 1.7) and MYC pathways (P = 0.01; NES = 3.2) consistent with previous results. In relation to prognosis, chromoplexy and chromothripsis have a negative impact on progression free survival (28.6 months vs. 42.8 months, P=0.03 and 28.6 months vs. 40.7 months P=0.01, respectively). When patients with both chromoplexy and chromothripsis (9%) were examined there was a pronounced effect on PFS (40.7 months vs. 22.7 months, P<0.001). Conclusion: Complex structural events are seen frequently in MM and could help explain disease progression. Severe cases with both chromoplexy and chromothripsis are associated with acquired genomic instability and an adverse impact on prognosis either directly or due to their association with DNA repair abnormalities. This opens the possibility of specifically therapeutically targeting the underlying DNA abnormalities. Disclosures Flynt: Celgene Corporation: Employment, Equity Ownership. Ortiz:Celgene Research SL (Spain), part of Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Gockley:Celgene Corporation: Employment. Davies:Janssen: Consultancy, Honoraria; TRM Oncology: Honoraria; Abbvie: Consultancy; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; ASH: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees. Thakurta:Celgene Corporation: Employment, Equity Ownership. Morgan:Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding.

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