Mytype: A Capture Based Sequencing Approach to Detect Somatic Mutations, Copy Number Changes and IGH Translocations in Multiple Myeloma

Abstract Introduction At diagnosis, Multiple Myeloma (MM) is traditionally classified into two clinical and prognostic subgroups groups on the basis of initiating cytogenetic abnormalities: IGH translocations and hyperdiploidy. Currently, these events are clinically ascertained by Fluorescent In-Situ Hybridization (FISH). In recent years, comprehensive genome profiling studies have shown that MM pathogenesis is defined by a spectrum of acquired somatic lesions, many of which are biologically and clinically relevant. To this effect, targeted gene sequencing approaches are becoming routine in the upfront diagnostic settings. Here we present myTYPE, a MM-specific targeted next generation sequencing panel to identify germline and somatic substitutions, indels, Copy Number Aberrations (CNA) and IGH translocations. Methods A multiplex bait panel was designed to capture the exons of 120 genes implicated in MM pathogenesis, entire IGH locus as well as genome wide representation of single nucleotide polymorphisms (SNPs) (1 in 3Mb) to enable detection of arm level copy number events and recurrent focal events. These 120 genes were selected on the basis of 1) frequently mutated and driver genes in MM 2) genes in important signaling pathways, e.g the NFKB pathway 3) treatment targets and candidate genes for drug resistance, e.g. cereblon.To validate the efficacy of the assay, 16 constitutional bone marrow samples and 18 tumor samples were sequenced using myTYPE. For validation, 6/18 tumor/normal pairs sequenced using myTYPE were subject to WGS and remaining 12/18 tumor samples were subject to FISH. After sequencing, we obtained an overall median target coverage of 815x. Results After alignment, substitutions and indels were called using Caveman, Pindel and Strelka. CNAs were identified using Facets and IGH translocations were identified using Delly along with a modified version of BRASS. Below is a description of the genomic abnormalities captured by the myTYPE assay. SNVs and Indels For the 6 tumor/normal pairs sequenced using myTYPE and WGS, we obtained a total of 21 (median = 3) non-synonymous mutations using myTYPE. When limiting the WGS calls to myTYPE targets, we recovered 20/21 non-synonymous mutations identified by myTYPE. These involved SNVs and indels in key MM related drivers including NRAS, KRAS, FAM46C and TP53 among others. For the mutations identified by both myTYPE and WGS, there was a high correlation between the variant VAFs, R2= 0.99 and as expected is better in capturing subclonal mutations. IGH rearrangements and Copy Number Aberrations (CNA) Next we compared myTYPE and WGS results for recurrent CNAs in MM. We specifically looked at deletions of 1p, 13p, 16q, 17p and gains of 1q, 11q and found a 100% concordance of these aberrations identified by both assays. The remaining 12 samples sequenced using myTYPE also had orthogonal FISH. myTYPE identified a total of 7 IGH rearrangements, 4 of which are also reported by FISH. Three additional t(11;14) translocations were uniquely identified by myTYPE in cases that remained clinically uncharacterized. FISH was also used to probe deletions in 17q, 13q, 1p and 1q gain. All aberrations identified by FISH were also identified in myType. Additionally, 13q- in four samples and 1p- in one sample were uniquely identified by myTYPE. Conclusion In summary, we present a targeted assay capable of identifying somatic mutations, CNAs and IGH translocations of prognostic and diagnostic relevance in MM. When compared to conventional assays currently used in clinical practice, myTYPE identified at least one disease defining alterations in all samples screened. Evaluation of sensitivity and specificity will require larger clinical cohorts. Importantly, myTYPE enables comprehensive profiling, large sample multiplexing and short turn around times which renders it as an optimal assay for utilisation in the upfront clinical setting. Disclosures Korde: Amgen: Research Funding. Mailankody:Juno: Research Funding; Janssen: Research Funding; Takeda: Research Funding; Physician Education Resource: Honoraria. Landgren:Pfizer: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy.

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Identification of Initiating Trunk Mutations and Distinct Molecular Subtypes: An Interim Analysis of the Mmrf Commpass Study

Blood ◽

10.1182/blood.v126.23.722.722 ◽

2015 ◽

Vol 126 (23) ◽

pp. 722-722 ◽

Cited By ~ 1

Author(s):

Jonathan J Keats ◽

Gil Speyer ◽

Legendre Christophe ◽

Christofferson Austin ◽

Kristi Stephenson ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Board Of Directors ◽

Copy Number ◽

Interim Analysis ◽

Research Funding ◽

Molecular Subtypes ◽

Bayesian Clustering ◽

Clustering Method ◽

Advisory Committees

Abstract The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) is a longitudinal study of 1000 patients with newly-diagnosed multiple myeloma from clinical sites in the United States, Canada, Spain, and Italy. Each patient receives a treatment regimen containing a proteasome inhibitor, immunumodulatory agent, or both. Clinical parameters are collected at study enrollment and every three months through the five-year observation period. To identify molecular determinants of clinical outcome each baseline and progression tumor specimen is characterized using Whole Genome Sequencing, Exome Sequencing, and RNA sequencing. This will be the first public presentation of the interim analysis seven cohort with 760 enrolled patients of whom 565 are molecularly characterized. This cohort of patients includes 14 patients with baseline and secondary samples along with 7 patients with characterized tumor samples from the bone marrow and peripheral blood. Although the median follow-up time for the cohort is only 260 days the patients on proteasome and IMiD based combinations are currently showing a PFS and OS benefit compared to those receiving combinations with each agent alone. From the raw mutational analysis we identified 24 significant genes that are recurrently mutated and the mutated allele is detectably expressed in all but one, DNAH5. Suggesting these mutations are likely contributing to myelomagenesis through an unconventional mechanism. Interestingly, DIS3 mutations are independent of KRAS, NRAS, and BRAF indicating a potential mechanistic link while PRKD2 mutations are associated with t(4;14). To identify events driving the initiation of myeloma we performed a detailed clonality analysis using a bayesian clustering method that corrects for copy number abnormalities and tumor purity to assign mutations into distinct clonal branches versus the initiating trunk mutations. On average 63.8% of mutations are trunk mutations and in 86.7% of patients at least one trunk mutation is associated with somatic hypermutation of an immunoglobulin gene as expected in a late stage B-cell malignancy. This identified many expressed trunk mutations that did not come out in the classic significance analysis like ATM, EGR1, and CCND1. To identify molecular subtypes we performed unsupervised clustering using a consensus clustering approach on independent discovery and validation cohorts, which identified 12 distinct subtypes, using a combination of silhouette score and cumulative distribution of consensus scores. This analysis identified two distinct groups associated with t(4;14) with mutations in FGFR3 and DIS3 being exclusive to one subgroup. In addition, this analysis separates patients with cyclin D translocations into three different groups, with one group having the second lowest PFS proportion. Three patients without CCND1 or CCND3 translocations were found to have IgH translocations targeting CCND2. The MAF subgroup was associated with the lowest OS and PFS proportion, and the three MAF/MAFB translocation negative patients in the subgroup all had MAFA translocations. The remaining 6 subgroups are associated with hyperdiploid copy number profiles and harbor the majority of the IgH-MYC translocation events. Two of the hyperdiploid groups are associated with a low level of NFKB activation compared to the remaining four, one of these is defined by the highest proliferation index but paradoxically the other has the second worst OS proportion. Another group is enriched with FAM46C and NRAS mutations. The genomic profiles of the paired tumors isolated from the peripheral blood and bone marrow are highly similar indicating these are not genetically distinct tumor compartments, at least in this subset of seven patients. Applying our bayesian clustering method to the serial samples resolved additional clonal clusters as mutations with similar cancer cell fractions at diagnosis clearly diverged at later timepoints. These analyses have identified tumor initiating mutations and new subtypes of myeloma, which are associated with distinct molecular events and clinical outcomes. Disclosures Jagannath: Novartis: Honoraria; Bristol Myers Squibb: Honoraria; Celgene: Honoraria; Merck: Honoraria; Janssen: Honoraria. Siegel:Celgene Corporation: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau; Novartis: Speakers Bureau; Merck: Speakers Bureau. Vij:Takeda, Onyx: Research Funding; Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy. Zimmerman:Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria. Niesvizky:Celgene: Consultancy, Speakers Bureau. Rifkin:Onyx Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lonial:Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

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Molecular Insights into Clonal Hematopoiesis and Therapy-Related Myeloid Neoplasm in Patients with Multiple Myeloma and Cytopenia(s)

Blood ◽

10.1182/blood-2020-141656 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 6-7

Author(s):

Jinming Song ◽

Hailing Zhang ◽

Xiaohui Zhang ◽

Mohammad Hussaini ◽

Ning Dong ◽

...

Keyword(s):

Multiple Myeloma ◽

Board Of Directors ◽

Research Funding ◽

Somatic Mutations ◽

Diagnostic Value ◽

Research Support ◽

Advisory Committees ◽

Cytogenetic Abnormalities ◽

Tp53 Mutations ◽

Clinical Databases

Background: Multiple myeloma (MM) is a clonal plasma cell neoplasm typically associated with chronic therapy and resultant potential toxicities, including clonal cytopenias, myelodysplastic syndrome (MDS), or therapy-related myeloid neoplasms (tMN). Early identification of myelodysplasia is important for patient management and outcome. Next generation sequencing (NGS) is playing an ever increasing role in this field. Materials and Methods: The retrospective study was approved by Moffitt institutional review board (IRB). We searched our in-house NGS database with ~6000 patients and clinical databases to identify the patients with MM and sustained cytopenia with accompanying NGS data. The NGS results were analyzed for associations with myeloma and myelodysplasia. Results: Of the 196 identified patients identified (Table 1), there were 114 males (58%) and 82 females (42%) with a median age of 68 years. Eighty-four myeloma patients with cytopenia (43%) were found to have one or more somatic mutations and 112 patients (57%) showed no mutations. The most frequently mutated genes are as following: TP53 (12%), DNMT3A (8%), TET2 (6%), ASXL1 (5%), KRAS (5%), ETV6 (3%), RUNX1 (2%), CUX1 (2%), BCOR (2%), SF3B1 (2%), ZRSR2 (2%), EZH2 (2%), IDH2 (2%), SRSF2 (2%), and BRAF (1%). We divided the patients into four groups according their disease status at the time of NGS testing: 1) patients with myeloma but no myelodysplasia (MM_Only, 105 patients and 53.57%); 2) Patients with myelodysplasia but no overt residual myeloma (Myelodysplasia_Only, 14 patients, 7.14%); 3) Patients with both myeloma and myelodysplasia (MM+Myelodysplasia, 27 patients, 13.78%); 4) Patients with neither myeloma or myelodysplasia (Negative_for_Both, 50 patients, 25.51%). The "Myelodysplasia" in this study is defined as having either overt morphologic dysplasia (>10% of the lineage cells), or equivocal dysplasia but having myeloid-related (non-myeloma) cytogenetic abnormalities. NGS results were not included in the classification to assess the added diagnostic value of NGS. The Mutational profiles of the four disease groups are displayed in Figure 1 and compared in Table 1 and 2. The MM+Myelodysplasia group showed highest percentage of mutations (88.89% of patients tested), followed by Myelodysplasia_Only group (57.14%) and MM_Only group (35.24%), with Negative_for_Both group showing the lowest mutation rate (30.00%). The average number of somatic mutations/case also followed the same order: 1.63, 1.00, 0.48, and 0.36, respectively. Of the 196 patients, 58 patients (29.59%) had no morphologic dysplasia or myeloid-related cytogenetic abnormalities but showed one or more somatic mutations by NGS. These patients harbored clonal cytopenia of uncertain significance (CCUS) clones and would have been missed without NGS testing. Of these 58 patients, retrospective review actually identified 7 patients with morphologic dysplasia and were reclassified as MDS. Further mutational analysis revealed the following interesting findings. ASXL1, DNMT3A, KRAS, and SF3B1 mutations showed highest frequencies in MM+Myelodysplaisa group when compared with other 3 groups (Table 2), indicating a close association with myelodysplasia development in patients with persistent myeloma. In contract, among the 4 groups, RUNX1 mutations were most common in Myelodysplasia_only patients, suggesting a potential alternative pathway for myelodysplasia development in patient with myeloma in remission. It is possible that presence of myeloma clones create different evolution pressure on neoplastic myeloid clones. TP53 mutations were present in MM_Only group, but were much more frequent in patients with MM+Myelodysplasia and Myelodysplasia_only groups. The presence of TP53 mutations might therefore suggest increased risk for myelodysplasia. Finally, TET2 were similar between these groups and therefore not of significant diagnostic value. Conclusion: NGS testing is valuable in identifying CCUS, MDS, or tMN in myeloma patients, especially in those with no morphologic or cytogenetic abnormalities. Statistically significant differences are seen in the mutational profiles of the four groups of patients, suggestive of different roles in myelodysplasia development. Further studies are necessary to better distinguish the origin of these mutations as being derived from the myeloma versus the myeloid components of the disease. Disclosures Hussaini: Stemline: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Boston Biomedical: Consultancy. Shain: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; Amgen: Speakers Bureau; GlaxoSmithKline: Speakers Bureau; Adaptive: Consultancy, Honoraria; BMS: 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. Nishihori:Novartis: Other: Research support to institution; Karyopharm: Other: Research support to institution.

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Clonal-Heterogeneity and Propensity for Bone Metastasis in Multiple Myeloma

Blood ◽

10.1182/blood.v124.21.3370.3370 ◽

2014 ◽

Vol 124 (21) ◽

pp. 3370-3370

Author(s):

Yuji Mishima ◽

Michele Moschetta ◽

Jiantao Shi ◽

Francois Mercier ◽

Salomon Manier ◽

...

Keyword(s):

Multiple Myeloma ◽

Board Of Directors ◽

Research Funding ◽

Gene Signature ◽

Advisory Board ◽

Clonal Heterogeneity ◽

Advisory Committees ◽

Primary Tumors ◽

Synonymous Mutations ◽

Bm Niche

Abstract Rationale Multiple Myeloma (MM) is characterized by the presence of multiple disease foci disseminated throughout the skeleton suggesting continuous circulation and metastasis of myeloma cells from one site of the bone marrow (BM) to another leading disease progression. However the metastatic process in MM has not been well characterized. In addition, the role of specific subclones that have the propensity for metastasis and tumor colonization in the BM niche has not been investigated. In this study, we developed a new BM metastasis xenograft model to examine clonal heterogeneity in tumor colonization of distant bone niches. We identified a set of genes that characterize potential driver genes for metastasis in MM by genomic and transcriptomic profiles of metastatic and primary tumor clones. Methods The model was developed by performing bilateral femur transplantation from donor SCID-bg mice to the dorsum of recipient mice of the same background. To study metastasis, the donor femurs were injected with MM cells (human MM1S, IM-9 and murine 5TGM1) and then implanted in the recipient mice. At the time of hind limb paralysis, the BM cells were flushed from the host or implanted femurs and analyzed by flow-cytometry. To investigate clonal heterogenity, IM-9 cells were transformed with four fluorescent proteins (FPs) simultaneously and sorted into fifteen subpopulations of all combinations of FPs. A mixture composed by equal proportion of all 15 FPs-labeled cells (rainbow mixture) was prepared and then used for in vivo experiment. At the time of sacrifice, clonal distribution of metastasized tumors were analyzed and the predominant clones (winner clones) were flow-sorted for genomic and transcriptomic studies. Library preparation and sequencing were performed according to manufacturer's protocols. Sequencing data was processed by bcbio_nextgen. Briefly for RNA-seq data, raw reads were aligned to reference human genome GRCh37, and gene-level read counts were calculated. Data normalization and differential expression were analyzed with DESeq2. For DNA-seq data, raw reads were aligned to GRCh37. Somatic single nucleotide variants and INDEL were called by MuTect and Indelocator, respectively. Results All myeloma cell lines studied were able to metastasize from the BM of transplanted femurs to the host BM and mice eventually developed paralysis after 6 to 11 weeks. Experiments using rainbow cells consistently showed that only a sub-clone of single color was able to invade and populate the host BM after metastasis, while all 15 color populations were developed in primary tumors. Interestingly, metastatic clones from different mice had similar expression profiles, although these were labeled by different colors. The studies were confirmed in a second MM cell line (MM1S) showing a similar metastasis gene signature (Fig. A). Differential expression analysis identified 238 genes significantly down regulated in both IM-9 and MM1S metastatic tumors compared to matched primary tumors (FDR < 1%). Pathway enrichment analysis indicated that AP-1, ATF2 and NFAT pathways were significantly over-represented (FDR < 5%) (Fig. A). Moreover, this metastatic signature was significantly repressed in relapsed MM patient samples compared to normal controls (FDR < 7%) using GSE6477 dataset (Fig. B). We also compared mutation fraction (MF) distributions in primary and metastatic tumors using DNA-seq data. There was only one peak in each primary tumor (MF around 0.1), while were two peaks for metastatic samples (MF at 0.1 and 0.4), strongly suggests that metastatic clones are derived from a single subclone (Fig. C). Similar results were observed with analysis of only the non-synonymous mutations (Fig. D). Out of all genes with non-synonymous mutations, we found 11 genes that are also functionally related to the metastatic signature using co-expression networks-based prioritization method. Two genes TET1 and PPP2R3A are indicated as examples (Fig. D). Conclusions Here we show a new model of bone metastasis that can be used to examine mechanisms of cell dissemination and colonization of the BM niche. Our studies demonstrate that specific winner subclones have a higher metastatic potential and are likely driver clones for tumor metastasis in MM. On the molecular level, a metastatic gene signature was found to be consistently down regulated in metastatic tumor samples, and 11 genes were identified as potential drivers. Figure 1 Figure 1. Disclosures Munshi: Janssen Research & Development: Membership on an entity's Board of Directors or advisory committees. Anderson:Celgene: Membership on an entity's Board of Directors or advisory committees; Millennium: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Onyx: Membership on an entity's Board of Directors or advisory committees; Acetylon: Scientific Founder Other; Oncopep: Scientific Founder Other. Scadden:Fate Therapeutics: Consultancy, Equity Ownership. Ghobrial:Sanofi: Research Funding; Noxxon: Research Funding; BMS: Advisory board, Advisory board Other, Research Funding; Onyx: Advisory board Other.

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Molecular Epidemiology of AML: Association of Somatic Gene Mutations with Epidemiologic Exposures and Outcomes in the Mayo Clinic AML Epidemiology Cohort

Blood ◽

10.1182/blood-2020-134353 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 35-36

Author(s):

Zaid Abdel Rahman ◽

Yesesri Cherukuri ◽

Michael G. Heckman ◽

Laura E. Finn ◽

Liuyan Jiang ◽

...

Keyword(s):

Exome Sequencing ◽

Board Of Directors ◽

Mayo Clinic ◽

Copy Number ◽

Research Funding ◽

Somatic Mutations ◽

Patient Characteristics ◽

Advisory Committees ◽

Risk Response ◽

Response To Chemotherapy

Introduction: Population studies have identified genes with germline polymorphisms associated with acute myeloid leukemia (AML) risk and outcome. However, somatic mutations in these genes have not been reported in an AML clinical population and whether they are associated with epidemiologic exposures, clinical AML phenotypes and outcome after therapy. Methods: We systemically interrogated PubMed database (1998-2018), to identify genes with germline polymorphisms associated with AML risk, response to chemotherapy or outcome. To determine the prevalence and relevance of somatic mutations in these genes in an unselected AML population, we performed an analysis using Whole-Exome Sequencing (WES) on remnant diagnostic cytogenetic pellets from 98 patients from the Mayo Clinic AML Epidemiology Cohort, a detailed and highly-annotated cohort of 295 consecutive AML patients treated at Mayo Clinic Florida & Arizona between October, 2000 and December, 2011. Patient characteristics are shown in Table 1. Samples were sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and somatic mutations including non-synonymous and truncating single nucleotide variants and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, & Mayo Clinic internal biobank genetic variants database. Copy number aberrations were identified & filtered using public copy number polymorphism databases. The association analyses were performed at the gene level, with a primary endpoint of whether a given patient harbored a somatic mutation in any genes linked to AML risk or outcome in literature, and to determine the associations of these mutations with epidemiologic exposures, AML phenotype and clinical outcomes. Results: From the literature search, we identified 77 unique genes with known germline polymorphisms associated with AML risk, response to chemotherapy or outcome. Fifty-eight of these were found to be somatically mutated in our WES dataset, with subsequent analysis focusing on the 11 genes (ABCB1, CYP1A1, CYP2B6, EPHX1, ERCC1, ERCC2, ERCC5, JAK2, MEFV, MTRR, and TERT) that had greater than 5 patients with nonsynonymous somatic mutations in the given gene. Significant associations with epidemiologic exposures and outcomes were noted in patients with somatic mutations in ERCC2, CYP1A1 and ERCC5 genes. Table 2 shows a comparison of patient characteristics and associations according to the presence of somatic mutations in these genes. Patients with mutations in CYP1A1 had a significantly younger age at AML diagnosis (Median: 51.7 vs. 71.0 years, P=.02) and significantly shorter OS in age-adjusted analysis (HR=4.45, P=.003). The former is a novel finding, whereas the latter is consistent with previous reports. Patients with mutations in ERCC2 more commonly used statins (66.7% vs. 21.7%, P=.03). Patients with ERCC5 mutations had a lower rate of tobacco use (20.0% vs. 54.5%, P=.049). In unadjusted analysis, there was a significant association between presence of somatic mutations in JAK2 and poorer survival after AML diagnosis (HR=2.83, P=.017), but this attenuated and did not retain significance when adjusting for age at AML diagnosis (HR=2.22, P=.067). Conclusion: Our exploratory study describes a novel association of CYP1A1 somatic nonsynonymous mutations with age of AML onset, as well as novel associations of ERCC2 and ERCC5 mutations with epidemiologic exposures in an unselect cohort of patients with AML. We confirm the association of CYP1A1 with inferior overall survival after AML diagnosis. These findings suggest that some genes associated with AML risk may also harbor somatic mutations that are clinically relevant. These results will guide a planned confirmatory prospective study to determine frequency and impact of both germline and somatic mutations of risk genes in AML patients, and may contribute to a better understanding leukemia risk assessment and potentially to prevention strategies. Disclosures Finn: Jazz Pharmaceuticals: Speakers Bureau; Celgene: Speakers Bureau; Seattle Genetics: Speakers Bureau. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Foran:Revolution Medicine: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Agios: Honoraria, Research Funding.

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Presence of Extrachromosomal DNA (ecDNA) Impacts Both Progression Free and Overall Survival and Is an Independent Poor Prognostic Marker in Multiple Myeloma

Blood ◽

10.1182/blood-2021-151647 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 461-461

Author(s):

Parth Shah ◽

Anil Aktas-Samur ◽

Mariateresa Fulciniti ◽

Raphael Szalat ◽

Masood A. Shammas ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Board Of Directors ◽

Copy Number ◽

Research Funding ◽

P Value ◽

Newly Diagnosed ◽

Extrachromosomal Dna ◽

Publicly Traded ◽

Advisory Committees

Abstract Background Focal amplifications and rearrangements drive tumor growth and evolution in cancer. Focally amplified regions often involve the juxtaposition of rearranged segments of DNA from distinct chromosomal loci into a single amplified region and nearly half of these regions can be explained by circular, extrachromosomal DNA (ecDNA) formation. Cancer-associated ecDNA shows a unique circular placing ecDNA at the interface of cancer genomics and epigenetics. As formation of ecDNA represents a manifestation of genomic instability, we have investigated presence and prognostic impact of ecDNA in multiple myeloma (MM). Methods Whole genome (WGS) and transcriptome (RNAseq) sequencing data from CD138 purified MM cells from 191 uniformly-treated newly diagnosed MM patients were used for this analysis. Copy number variants (CNV), single nucleotide variants (SNV) and structural variants (SV) were identified on all WGS samples using Facets, Mutect2 and Manta. Seed data from these CNV results was passed to the AmpliconArchitect tool to determine presence of focally amplified and rearranged segments of DNA. Seed CNV thresholds were set for a minimum CNV size of 100kb and a copy number of equal or greater to 5. Extrachromosomal calls were then annotated using the Amplicon Classifier to determine the presence of ecDNA. Multivariate survival analysis was performed after segregating samples into the conventional myeloma risk classifications including translocations, copy number alterations, ISS, age and mutations associated with risk. Differential expression analysis was performed on transcriptomic data using DEseq2. Results We identified 6.8% of the newly diagnosed patients with ecDNA, 12.5% with complex non-cyclic DNA amplifications and 10.1% with linear amplifications. ecDNA and complex events were targeting MM dependent genes, including MYC/PVT1, IRF4 as well as known driver genes such as CDYL and TRAF2. We further evaluated association between ecDNA, complex rearrangements, linear amplification and patients with none of these amplification types and found that patients with ecDNA had significantly poor PFS (median PFS 22 months vs. 41 months) and OS (median OS 41 months vs. 105 months). Patients having ecDNA in their MM cells did not show any significant enrichment for known translocations, double hit or TP53 mutations. In a multivariate model including ecDNA and all other known MM risk features, ecDNA was found to be an independent predictor of progression free survival.(HR 2.6, CI: 1.26 -5.6, p=0.0082) and overall survival (HR 7.94 CI:3.5-17.9 p < 0.0001). Patients with ecDNA have higher mutational load probability(8798 vs 6982, effect size = 0.64 , probability is 91.1). However, this was not reflected in heterogeneity by using MATH score. We found that patients with ecDNA are likely to have BRAF mutations (OR= 25.07 [2.57 - 330 95% CI], p value = 0.002), however overall RAS/RAF pathway mutations were similar to other patients. Patients with ecDNA showed fragile DNA with more breaks (median segments 197 vs. 125.5, p value = 0.001). Although ecDNA is defined as copy number gain with fragments having 5 or more copies, overall genomic gain between ecDNA and other patients were similar. However, overall genomic loss in patients with ecDNA were higher than others (7% vs. 4.2%, p = 0.06). By differential gene expression analysis we noted 98 differentially expressed genes in MM cells with ecDNA. The downregulated geneset involved pathways responsible for cell death as well as the RAS pathway. Interestingly, CD38 was upregulated in the ecDNA dataset suggesting greater potential for CD38 targeting therapies in these patients. Conclusions ecDNA, as an unique marker of perturbed genomic integrity, is observed in a subset of patients and is an independent prognostic marker in newly diagnosed MM patients. As patients with ecDNA are not fully captured by other risk features its incorporation in an expanded definition of a high risk group of multiple myeloma should be investigated. Future studies will endeavor to explore the biological mechanism through which ecDNA are formed and influences outcomes in myeloma. Figure 1 Figure 1. Disclosures Richardson: Sanofi: Consultancy; GlaxoSmithKline: Consultancy; Karyopharm: Consultancy, Research Funding; AstraZeneca: Consultancy; AbbVie: Consultancy; Oncopeptides: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy; Protocol Intelligence: Consultancy; Celgene/BMS: Consultancy, Research Funding; Secura Bio: Consultancy; Regeneron: Consultancy; Jazz Pharmaceuticals: Consultancy, Research Funding. Perrot: Abbvie: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Moreau: Abbvie: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Celgene BMS: Honoraria; Oncopeptides: Honoraria. Thakurta: Oxford University: Other: Visiting Professor; BMS: Current Employment, Current equity holder in publicly-traded company. Anderson: Gilead: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Legend: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Celgene: Consultancy; Pfizer: Consultancy.

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Impact on Response and Survival of DNA Repair Single Nucleotide Polymorphisms In Relapsed or Refractory Multiple Myeloma Patients Treated with Thalidomide

Blood ◽

10.1182/blood.v116.21.4041.4041 ◽

2010 ◽

Vol 116 (21) ◽

pp. 4041-4041

Author(s):

Carlos Fernández de Larrea ◽

María Teresa Cibeira ◽

Alfons Navarro ◽

Tania Díaz ◽

Dolors Fuster ◽

...

Keyword(s):

Multiple Myeloma ◽

Dna Repair ◽

Single Nucleotide Polymorphisms ◽

Board Of Directors ◽

Research Funding ◽

Response Rate ◽

Nucleotide Polymorphisms ◽

Wild Type ◽

Advisory Committees ◽

Single Nucleotide

Abstract Abstract 4041 Background: Thalidomide was the first of the so-called new drugs incorporated in the treatment of multiple myeloma (MM). In this era of emerging novel agents, there is a real need for increased knowledge of the pre-treatment genetic profile of patients who will potentially benefit from each drug. The analysis of polymorphisms in drug metabolism pathways and in immune system genes can help to identify patients with possible different treatment response and outcome. Single nucleotide polymorphisms (SNPs) are the most frequent type of genomic polymorphisms and are involved in chemotherapy response in different tumors, including MM. We examined SNPs in 12 genes and correlated our findings with response, toxicity and overall survival (OS) to thalidomide in patients with relapsed MM. Methods: Twenty-eight patients (13M/15F; median age 59 years, range 40 to 82 years) with relapsed or refractory MM from November 1999 to December 2003 were treated with single agent thalidomide at a single institution. The median duration of thalidomide treatment was 4 months and the median dose was 400 mg/day. Median follow-up for alive patients was 103 months (range 86 to 112). Genomic DNA was isolated from bone marrow slides using a commercial assay (Qiagen). SNPs were analyzed by TaqMan assay in an ABI Prism 7500 Sequence Detection system (Applied Biosystems). The genes explored were those related to multidrug resistance (ABCB1 [rs3842, rs1045642]), drug metabolic pathways (NR1I2 [rs1523130, rs1523127], GSTT1 [rs4630], SULT1C2 [rs1402467]), DNA repair systems (XPA [rs1800975], ERCC1 [rs735482], ERCC2 [rs13181], ERCC5 [rs17655, rs1047768], XRCC1 [rs25487], XRCC5 [rs1051677, rs1051685], TOP2A [rs13695]) and cytokines (VEGFA [rs10434, rs2010963]). Results: Partial response (PR) was attained in 17.9% (5/28) and minimal response (MR) in 28.6% (8/28), while 3 (10.7%) and 12 (42.9%) patients showed no response (NR) or progressive disease (PD), respectively. The response rate (PR+MR vs. NR+PD) to thalidomide was higher (66.7%) in patients with hetero- (AC) or homozygous (CC) SNPs in ERCC1 (rs735482) than in those with wild type (AA) (33.3%) (p=0.006). Patients with the ERCC5 heterozygous SNP rs17655 (CG) had a higher response rate (77.8%) than those with the homozygous SNP (GG) or wild type (CC) (31.6%) (p=0.04). Patients with heterozygous XRCC5 (AG) polymorphism rs1051685 showed a higher response rate (100%) than those with wild type (AA) (34.8%) (p=0.013). Longer OS was associated with the homo- and the heterozygous SNP in ERCC1 (AC + CC vs. AA; p=0.005) and with the heterozygous SNP in XRCC5 (rs1051685) (AG vs. AA; p=0.02) (Figures 1 and 2). A trend to longer OS was also observed in patients with polymorphisms in XRCC1 (p=0.06). The heterozygous polymorphism in GSTT1 (CT vs. TT) was associated with a lower frequency of thalidomide-induced peripheral neuropathy (p=0.04). Conclusion: SNPs in ERCC1 and XRCC5 were strongly associated with higher response rate and longer OS to thalidomide in patients with relapsed/refractory MM. SNPs in ERCC5 were also associated with greater response rate. Since the polymorphism in XRCC1 was not related to a better response to thalidomide, it can be speculated that the trend to prolonged OS could be related to other molecular mechanisms. Our findings could be useful to identify patients with MM who are more likely to benefit from thalidomide-based therapies. Disclosures: Cibeira: Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rosiñol:Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Blade:Janssen-Cilag: 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.

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Prospective Investigation of Genetic Alterations in Osteolytic Lesions Compared to Paired Random Aspirates

Blood ◽

10.1182/blood.v128.22.4419.4419 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4419-4419

Author(s):

Sandra Sauer ◽

Jens Hillengass ◽

Barbara Wagner ◽

Daniel Spira ◽

Marc Andre Weber ◽

...

Keyword(s):

Multiple Myeloma ◽

Board Of Directors ◽

Copy Number ◽

Research Funding ◽

Iliac Crest ◽

Genetic Alterations ◽

Advisory Committees ◽

Single Nucleotide ◽

Osteolytic Lesions ◽

Myeloma Cells

Abstract Background: Bone disease is the most frequent clinical manifestation of multiple myeloma. In this prospective study we ask whether osteolytic lesions (OL) are driven by myeloma cells showing a different background of genetic alterations in terms of chromosomal aberrations and expressed single nucleotide variants (SNVs) compared to random aspirates (RA) from diffuse myeloma cell infiltration at the iliac crest (spatial genetic heterogeneity). Material and Methods: Consecutive sample-pairs (n=41) were prospectively obtained by CT-guided biopsies of OLs as well as simultaneous random bone marrow aspirates of the iliac crest, the latter undergoing CD138-purification of myeloma cells, in transplant eligible patients with previously untreated symptomatic multiple myeloma, after written informed consent. Peripheral blood mononuclear cells were used as germline control. Plasma cell infiltration in biopsies was quantified histologically. Samples pairs (n=8) were subjected to RNA-sequencing (Illumina HiSeq2000), gene expression profiling using DNA-microarrays (Affymetrix U133 2.0), whole exome sequencing (Illumina NextSeq 500), and arrayCGH (Affymetrix cytoscan array). Results and Discussion: Expressed single nucleotide variants.The spectrum of mutated genes in our samples comprises two of the most frequently mutated in symptomatic myeloma, i.e. KRAS and FAM46C, alongside those implicated in myeloma pathophysiology, e.g. mutations in IRF4, FGFR3, and CD200. In total, 1-10 clonal expressed non-synonymous SNVs were exclusively found in OL compared to RA, comprising e.g. WHSC1, FAM46C, and ROCK1P1. In 2/8 patients (25%), no expressed clonal differences between RA and OL were present. Single nucleotide variants.In investigated samples, 77-1569 non-synonymous SNVs appear with an allele frequency of ≥10% in OL and RA, clustering in 4-5 groups. The clonal constitution can vary, but subclones are detectable in both. Subclonal complexity is maintained (subclones remain present) in OL compared to RA, and the vast majority of subclonal changes is present in both, especially for expressed non-synonymous SNVs, incompatible with an "osteolytic clonal variant" driving OL in the majority of patients. Copy number alterations and loss of heterozygosity.Subtle differences in copy number between OL and RA are present. However, only 1/8 patients (12.5%) showed further "gained" aberrations in OL compared to RA, i.e. deletions on chromosome 7p, 8p, and 11p as well as 19p gain. Loss of heterozygosity was observed in 3/8 patients (37.5%) with a shared pattern between OL and RA in all of them. Conclusions: In our prospective study, the majority of alterations is shared between RA and OL. Spatial heterogeneity is present, but nature and frequency of alterations detectable exclusively in OL make them unlikely candidates in most myeloma patients for being causative for generation of OL. Disclosures Hillengass: Novartis: Research Funding; Sanofi: Research Funding; BMS: Honoraria; Celgene: Honoraria; Amgen: Consultancy, Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Goldschmidt:Bristol-Myers Squibb: 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; Chugai: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: 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; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Durie:Janssen: Consultancy; Amgen: Consultancy; Takeda: Consultancy. Hose:EngMab: Research Funding; Takeda: Other: Travel grant; Sanofi: Research Funding.

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Extracting Prognostic Molecular Information from PET-CT Imaging of Multiple Myeloma Using Radiomic Approaches

Blood ◽

10.1182/blood-2018-99-117103 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1906-1906

Author(s):

Christopher Wardell ◽

Terri Lynn Alpe ◽

Phil Farmer ◽

Michael W Rutherford ◽

Yan Wang ◽

...

Keyword(s):

Multiple Myeloma ◽

Bone Marrow ◽

Board Of Directors ◽

Research Funding ◽

Somatic Mutations ◽

Ct Scans ◽

Focal Lesions ◽

Advisory Committees ◽

Pet Ct ◽

Ngs Data

Abstract Introduction: Invasive bone marrow sampling is used in multiple myeloma (MM) diagnosis to obtain biological material, which can then be used to generate prognostically important genetic features. Physically sampling the bone marrow can be uncomfortable for the patient. Also, spatial heterogeneity is a common feature in MM, with multiple focal lesions (FLs) occurring throughout the skeleton, meaning a single sample from the iliac crest may be insufficient to capture intrapatient heterogeneity. An alternative strategy is to extract data directly from diagnostic positron emission tomography-computed tomography (PET-CT) scans of patients. These radiomic features can be used as a proxy from which to infer molecular and clinical phenotypes. Compared to physical sampling, there are several advantages, including rapid analysis, minimalizing patient discomfort, reduced cost and widespread availability of the required scanning equipment in hospitals. Methods: A series of 439 newly diagnosed MM patients were selected, all of which had diagnostic PET-CT scans. A radiologist examined these data and identified focal lesions in the axial skeleton of 136/439 (31%) patients. Focal lesions were manually segmented from the PET portion of the original DICOM data using a density-based thresholding method in 3DSlicer version 4.9.0. Pyradiomics version 1.3 was used to resample the voxels in the PET data to 4x4x4 mm and extract radiomic features from each FL. A combination of 10 filters and 7 feature classes were used and a total of 1679 radiomic features were generated per lesion. Radiomic features were a mixture of first order characteristics such as maximum intensity, shape characteristics and gray level matrix features. Hierarchical clustering was applied to the radiomic features, using the Pearson correlation between features as the distance metric and Ward's method for clustering. Next generation sequencing (NGS) data was available for samples from 58/136 (43%) patients with FLs in whole genome (WGS), whole exome (WES) or targeted panel (TP) modalities. The NGS data was used to detect translocations, copy number aberrations and somatic mutations. Results: There were 789 FLs identified in 136 patients, with each patient containing an average of 5.8 FLs. The median FL volume was 4350 mm3, with a median maximum 3D diameter of 29 mm. Hierarchical clustering across all FLs and radiomic features separated the FLs into 5 discrete clusters associated with various clinical and molecular features. However, clustering appeared to be independent of other classification systems based on gene expression profiling (GEP), including the UAMS classification system and GEP70 risk score. Clustering was also independent of the International Staging System (ISS) status suggesting that it can add additional prognostic information. Clusters also appeared to be independent of somatic mutations in genes previously reported as significantly mutated in MM. Patients commonly had FLs occurring in multiple clusters, suggesting that this method takes into account the heterogeneity between lesions in the same patient. Larger FLs were grouped primarily into two clusters consistent with them having distinct features that can be recognized by this approach. Looking across the different clusters distinct differences in clinical outcome were seen between the groups, with significant differences in both PFS (p=0.007) and overall survival (p=0.005), with worse prognosis being led by a cluster of smaller lesions. Conclusions: Radiomics provides a novel method to extract potentially important data from PET-CT scans which can define individual clusters that have different clinical, molecular and prognostic features. This can provide a novel non-invasive method to assess FLs based on both their physical and radiomic characteristics. Larger study sizes will be needed to confirm the differences in outcomes seen between groups. Disclosures Boyle: Celgene: Honoraria, Other: travel grants; Janssen: Honoraria, Other: travel grants; La Fondation de Frace: Research Funding; Abbvie: Honoraria; Amgen: Honoraria, Other: travel grants; Gilead: Honoraria, Other: travel grants; Takeda: Consultancy, Honoraria. Morgan:Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:TRM Oncology: Honoraria; MMRF: Honoraria; Abbvie: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria; Amgen: Consultancy, 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; ASH: Honoraria.

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Mutational Type and Configuration of an Individual Gene May Differentially Impact the Clinical and Phenotypic Features

Blood ◽

10.1182/blood-2019-128893 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2992-2992

Author(s):

Yasunobu Nagata ◽

Hideki Makishima ◽

Cassandra M Kerr ◽

Bhumika J. Patel ◽

Hassan Awada ◽

...

Keyword(s):

Board Of Directors ◽

Copy Number ◽

Research Funding ◽

Somatic Mutations ◽

The Other ◽

Missense Mutations ◽

Advisory Committees ◽

Different Types ◽

Equity Ownership ◽

The Impact

Myelodysplastic syndromes (MDS) arise in older adults through the stepwise acquisition of multiple somatic mutations. The genetic heterogeneity that results includes mutations of diverse genes and their combinations, clonal hierarchy, genetic configuration (e.g., bi-allelic or compound heterozygous, hemizygous lesions), specific positions within a gene including canonical hotspots vs. other positions, and types of mutation (truncations vs. missense), all of which could differentially affect pathogenesis. Given the binary status (e.g. mutated vs. wild-type) used in many clinical analyses, the true impact of specific types of mutations may be obscured and their specific roles underestimated. Deep targeted NGS was carried out for a panel of the 36 most frequently mutated genes in 1,809 MDS patients (low-risk MDS (n=839) vs. high-risk MDS (n=607), MDS/MPN (n=212), and sAML n=151). Copy number alterations (CNA) were also evaluated by combining karyotyping, microarray, and digital copy number analysis. With a mean coverage of 862x, after removing SNPs and errors, 3,971 somatic mutations were identified, the most common (>10% of cases) being TET2, SF3B1, ASXL1, del(5q), SRSF2, complex karyotype, and del(7q). For the purpose of this proof of concept analysis we focused on illustrative genes (TP53, RUNX1, TET2, and EZH2) affected by 2 recurrent hits. Bi-allelic TET2 or TP53 mutations were found in 15% (271/1,809) and 4% (72/1,809) of patients, respectively. TET2 and RUNX1 were most likely biallelic, whereas TP53 and EZH2 were most often affected by mutations and somatic deletion. Comparing the distribution of canonical vs. other types of mutations in genes, DNMT3A mutations affected the canonical site (R882) in 17% (35/203) of patients, were truncating in 39% (79/203) and missense in 44% (89/203) have also been found; deletions affecting the DNMT3A locus are rare. Within U2AF1, U2AF1Q157 are more frequent than U2AF1S34 (54% vs. 35%). Next, we checked correlation between these different types of mutations of one gene. 78 significant combinations were found. For instance, U2AF1Q157 mutations more commonly accompanied ASXL1 mutations and del(7q) and less frequently DNMT3A and BCOR mutations, trisomy8 and del(20) when compared to U2AF1S34 mutations [ASXL1 mutations 53% (42/80) in U2AF1Q157 vs. 16% (8/49) in U2AF1S34, P < .0001]. TET2 Bi-allelic mutations were more commonly associated with ZRSR2 and SRSF2 mutations, and less frequently del(5q) when compared to TET2 mono-allelic mutations [SRSF2 mutations 29% (80/276) in TET2-bi vs. 15% (34/227) in TET2-mono, P = .003]. In addition, patients with SRSF2 missense mutations were more likely to have RUNX1 bi-allelic mutations than those with SRSF2 in-frame mutations. We evaluated the impact of different types of mutations and combinations of them on disease phenotypes and survival. We then evaluated the impact of different types of mutations and their combinations on clinical phenotypes including dichotomous morphological (MDS vs. MDS/MPN) features, progressive (low- vs. high risk) subtypes. EZH2 bi-allelic alterations were more commonly associated with myleoproliferative features` compared to EZH2 mono-allelic alteration (q=.016). TET2 bi-allelic alterations and truncating mutations were found more frequently in higher-risk subtypes than TET2 mono-allelic and missense mutations (q<.001). In survival analyses, patients with DNMT3AR882 mutations had a poorer prognosis than those with truncating and the other missense mutations [P = .033, HR 1.86 (1.05-3.3)]. Next, using the PyClone bioanalytic pipeline, we recapitulated for each patient the clonal hierarchy and defined "dominant" vs. "secondary" mutations. DNMT3AR882 mutations were likely to be dominant/founder lesions compared to truncating or the other missense mutations: 77% (27/35) for R882 vs. 51% (40/79) for truncating vs. 45% (47/98) for the other missense, p=.0046. Specific dominant and secondary mutational pairs also differentially affected survival compared to the reverse configuration (q<.1) including EZH2 and RUNX1 or BCOR and U2AF1 or RUNX1 and BCOR. In conclusion, we report a comprehensive analysis of various types and configurations of lesions of individual commonly affected genes. Our results indicate that establishment of clinical or phenotypic correlations requires consideration of the type, rank and configuration of somatic mutations. Disclosures Mukherjee: McGraw Hill Hematology Oncology Board Review: Other: Editor; Bristol-Myers Squibb: Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Projects in Knowledge: Honoraria; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Partnership for Health Analytic Research, LLC (PHAR, LLC): Consultancy. Nazha:Incyte: Speakers Bureau; Daiichi Sankyo: Consultancy; Jazz Pharmacutical: Research Funding; Tolero, Karyopharma: Honoraria; Abbvie: Consultancy; MEI: Other: Data monitoring Committee; Novartis: Speakers Bureau. Sekeres:Millenium: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Ogawa:Asahi Genomics: Equity Ownership; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; Qiagen Corporation: Patents & Royalties; RegCell Corporation: Equity Ownership; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Kan Research Laboratory, Inc.: Consultancy. Maciejewski:Novartis: Consultancy; Alexion: Consultancy.

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An Observational, Retrospective Analysis of Retreatment with Carfilzomib in the Management of Patients with Multiple Myeloma

Blood ◽

10.1182/blood-2019-124376 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5554-5554

Author(s):

Tim J Peterson ◽

Neha Korde ◽

Hani Hassoun ◽

Sham Mailankody ◽

Alexander M. Lesokhin ◽

...

Keyword(s):

Multiple Myeloma ◽

Treatment Response ◽

Board Of Directors ◽

Research Funding ◽

High Risk Patient ◽

Physician Education ◽

Cancer Center ◽

Advisory Committees ◽

Oncology Research ◽

Select Group

Background: Several studies have indicated that the depth and duration of treatment response in multiple myeloma are both reduced in the relapsed setting. With further lines of therapy, responses continue to weaken in depth and shorten in duration. The National Comprehensive Cancer Network (NCCN) Guidelines suggest that regimens may be repeated in the relapsed setting if there has been a duration of at least 6 months since that regimen was given; however, there is limited information regarding treatment response and duration in the setting of re-treating patients with agents previously utilized. Moreover, preliminary data has suggested that carfilzomib-based regimens in the frontline may be able to attain deeper and longer responses than alternative therapies, which has led to carfilzomib being used more frequently in the frontline. This motivated us to investigate the treatment response, depth, and safety of re-challenging patients with carfilzomib in the relapsed setting. Methods: In this retrospective chart review, we identified all patients who were treated with multiple courses of carfilzomib-based regimens at Memorial Sloan Kettering Cancer Center between January 1, 2014 and November 30, 2018. Our primary objectives were to assess the response, duration of response and treatment, and safety of re-exposure to carfilzomib-based regimens. Responses were assessed as per IMWG 2016 consensus criteria (Lancet Oncol 2016). In this review we describe the clinical course, safety, and efficacy of re-challenging patients with carfilzomib in the relapsed and refractory settings. Results: Fifteen patients were identified as having received multiple, independent lines of carfilzomib-based therapy. The median age of the cohort was 58 years (49-76) with 53% male (8); two patients had R-ISS stage 1, eight stage 2, and five stage 3 disease. Five of these patients received their initial carfilzomib in the frontline as part of KRD; four of whom attained a sCR with the fifth attaining a VGPR. The remaining ten patients received their initial carfilzomib in the second-line (4) or 3rd and subsequent lines (6). Upon re-exposure to carfilzomib, patients were heavily treated with a median of four lines of therapy (2-15). All but three patients had at least one adverse cytogenetic abnormality; eight with 17p-, five with 13q-, three with t4;14, and six with 1q+. Regimens utilized in the relapsed setting included KRD (N=4), KPD (N=3), Cyklone (N=2), KD + HDAC inhibitor (N=3), KD (N=1), KCD (N=1), and KRD + daratumumab (N=1). Four patients received carfilzomib at a dose of 27 mg/m2 while the remaining 10 received > 36 mg/m2. Responses were seen in all but four patients (two VGPR, five PR, and four MR), with one patient experiencing progression during carfilzomib with no response; notably, this patient only attained a MR to primary carfilzomib therapy and their second exposure was the 15th line of therapy. The median time to next therapy was 4.8 months (1.9-19.4) with one patient being bridged to autologous hematopoietic cell transplantation (HCT), one to allogeneic HCT, and three are currently receiving ongoing carfilzomib treatment (13.9, 2.8, 2.5 months with VGPR, MR, and PR, respectively). Exacerbation of baseline hypertension was identified in three patients, but these instances were treated successfully with standard medications with no further complications. No additional cardiovascular events were identified in the frontline or re-treatment settings. Conclusions: We report that in a heavily pre-treated, high risk patient cohort, patients previously treated with carfilzomib-based regimens may be safely re-challenged with carfilzomib. Importantly, none of these patients experienced cardiovascular adverse effects other than exacerbation of underlying hypertension, further supporting the ability to safely re-treat a select group of patients with carfilzomib. We conclude that depending on the patient and treatment history, re-challenging with carfilzomib at relapse may be appropriate salvage therapy, particularly as a bridge towards HCT and/or clinical trials. Disclosures Hassoun: Novartis: Consultancy; Janssen: Research Funding; Celgene: Research Funding. Mailankody:Juno: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Takeda Oncology: Research Funding; CME activity by Physician Education Resource: Honoraria. Lesokhin:Genentech: Research Funding; Serametrix Inc.: Patents & Royalties; Janssen: Research Funding; GenMab: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Juno: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Smith:Celgene: Consultancy, Patents & Royalties, Research Funding; Fate Therapeutics and Precision Biosciences: Consultancy. Landau:Prothena: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Caelum: 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; Takeda: 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; Karyopharm: Consultancy, Honoraria. Shah:Janssen Pharmaceutica: Research Funding; Amgen: Research Funding. Scordo:Angiocrine Bioscience, Inc.: Consultancy; McKinsey & Company: Consultancy. Giralt:Amgen: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Miltenyi: Research Funding; Jazz Pharmaceuticals: Consultancy; Actinium: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Johnson & Johnson: Consultancy, Research Funding; Kite: Consultancy. Landgren:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Theradex: Other: IDMC; Merck: Other: IDMC; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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