ALBERT

Description: The postorogenic collapse of the early Paleozoic Caledonian orogeny is well documented; however, several different plate tectonic models exist for the convergent phase involving closure of the Iapetus Ocean and the collision of Laurentia and Baltica. Receiver function analysis of 11 broadband seismometers along a 270 km transect in the East Greenland Caledonides reveals the existence of an east-dipping high velocity slab. Numerical modeling demonstrates that relict subducted and eclogitized crust is a plausible explanation. Thus, eastward subduction preceded subsequent west-dipping subduction during the formation of the East Greenland and Scandinavian Caledonides. This is a key constraint for understanding the Caledonian and continental margin evolution in the North Atlantic realm.

Description: Introduction: Interphase FISH on CD138-selected bone marrow cells enables genetic risk stratification in newly diagnosed multiple myeloma (MM), however as MM remains incurable, most centres still treat newly diagnosed MM uniformly, utilising the most active regimens available. At relapse an increasing choice of regimens, coupled with co-morbidities and treatment-emergent toxicities, means no uniform approach is possible. Instead, therapy is tailored to disease and patient related risk factors. In this setting, FISH testing may be particularly useful if not done at diagnosis and to identify progression events that may alter prognosis. Aim: To evaluate the outcome of FISH analysis in consecutive patients with relapsed MM undertaken at our centre: success rate, frequency of abnormalities, incidence of progression events and correlation of FISH abnormalities with treatment outcomes. Methods: FISH analysis was performed on 192 samples from 154 relapsed patients (2012-13). Plasma cells were selected using magnetic CD138 MicroBeads and interphase FISH carried out using probes as recommended by the EMN (Ross et al, 2012). If patients had no prior results, a full FISH MM panel was performed, using probes for t(4;14), t(14;16), t(11;14), deletion 17p (17p-), Chr 1 abnormalities (1p-/1q+) and deletion 13q (13q-). If patients had been previously tested for an IgH translocation (Tx), a progression event panel was used: 1p-/1q+, 17p- and 13q-. Patients underwent FISH testing prior to starting the next line of therapy. Results: 79% of samples were successfully analysed, with analysis limited in 16% and failed in 5%. Common reasons for failure were poor quality/aged slides, insufficient material and poor hybridisation. 17% of patients had no cytogenetic abnormality. The most common abnormality was 13q- (43.1%), followed by 1q+ (41.4%), t(11;14) (18.3%), t(4;14) (12.4%), 17p- (12.0%) 1p- (8.9%), and t(14;16) (5.6%) Progression events were more common in t(14;16) and t(4;14) groups. All patients with t(14;16) and 82% with t(4;14) had an additional genetic lesion. Only 21% of patients with t(11;14) and 54% with no IgH Tx had an additional event. 80 patients (51.3%) had prior FISH results and 13 (16.3%) had developed a new abnormality on the later test. In 9 cases the progression event was 17p-, in 2 it was 1q+ and 2 cases developed 17p- and 1q+. The patients developing 1q+ were previously standard risk, so repeat testing altered risk group. Acquisition of 17p- indicates especially poor outcome, thus in all 13 cases repeat FISH analysis altered risk. Among patients with progression events none harboured t(11;14), 8 (64%) had no IgH Tx, 3 had t(14;16) and 2 had t(4;14). FISH results were correlated with clinical outcome. Patients were stratified as having high risk genetics [t(4;14), t(14,16), 17p- in ≥50% cells, 1p-/1q+] or standard risk [t(11;14), normal cytogenetics]. 63 (41%) patients were high risk, 83 (54%) standard risk, with no information available for 8 (5%). Both groups had received a median of 2 prior lines of therapy. Response rates (≥PR) to the next line of therapy were similar (60.4% standard risk vs 56.0% high risk). PFS from time of FISH was significantly longer in the standard risk group (9.8 months vs 5.9, p

Description: Background:Flow cytometric studies are useful in the diagnostic workup of patients with unexplained cytopenias and it has been demonstrated that bone marrow aspirates with immunophenotypic abnormalities by flow cytometry but not diagnostic morphologic or cytogenetic findings frequently evolve into myelodysplastic syndromes (MDS) (Kern 2013). Two flow cytometric scoring systems (FCSSs), the Wells FCSS and the Ogata FCSS, have diagnostic and prognostic utility. The Wells FCSS utilizes a difference from normal algorithm incorporating more than ten phenotypic parameters. The accumulation of these abnormalities is not only useful in diagnosis but is predictive of patient outcome (Wells 2003, Scott 2008, Alhan 2014). The recommended Ogata FCSS has evolved to include four cardinal parameters: (1) CD45 intensity on the myeloid progenitors, (2) frequency of lymphoblasts, (3) frequency of myeloid progenitors, and (4) granularity of the maturing myeloid cells. The Wells FCSS is more comprehensive as it uses more phenotypic characteristics, while the Ogata score is considered straightforward to implement in a routine setting (Della Porta 2012, Ogata 2009). This study compares the Wells FCSS and Ogata FCSS for sensitivity and specificity to detect clonal abnormalities documented by SNP/CGH microarray and conventional cytogenetics. Patients and Methods: The cohort included 99 patients with unexplained cytopenias whose bone marrow aspirates were submitted for SNP/CGH microarray and flow cytometry (HematoLogics). The immunophenotypic data were independently assigned a Wells FCSS (Cutler 2012) and an Ogata FCSS (Della Porta 2012). SNP/CGH microarray was assessed for MDS-associated genetic abnormalities. The findings were further correlated with conventional cytogenetic findings. Results: Of the 99 bone marrow aspirates, 20 exhibited clonal abnormalities associated with MDS. The Wells FCSS identified immunophenotypic abnormalities suggestive of MDS for 18 of 20 CGH positive specimens (sensitivity of 90%) and did not detect phenotypic abnormalities suggestive of MDS in 68 of 79 CGH negative specimens (specificity of 86%). In contrast the Ogata FCSS identified immunophenotypic abnormalities suggestive of MDS for 13 of 20 CGH positive specimens (sensitivity of 65%) and did not detect phenotypic abnormalities suggestive of MDS in 64 of 79 the CGH negative specimens (specificity of 81%). In an attempt to improve the sensitivity and specificity of the Ogata score, the granularity parameter was modified from side scatter channel mode of the granulocytes (compared to the side scatter mode of the lymphocytes) to the side scatter channel at the 15thpercentile of granulocytes (compared to the mean of lymphocytes). This modified parameter detected all specimens defined as hypogranular by the side scatter mode, and detected an additional 11 specimens as hypogranular. All of these specimens were detected as hypogranular by the Wells definition. This modified granularity method was then used along with the other three cardinal parameters to create a modified Ogata FCSS. The granularity modification resulted in improved sensitivity (70% versus 65%); specificity was unchanged. While the modified method outperformed the original, it did not match the performance of the Wells FCSS. Conclusions: In patients with unexplained cytopenias, the Wells FCSS demonstrates superior specificity and sensitivity than the Ogata FCSS for detecting myeloid immunophenotypic clones associated with SNP/CGH array and cytogenetic abnormalities. Modifying the Ogata granularity parameter marginally improves the sensitivity but does not improve the specificity. Implementation of the Wells FCSS requires a comprehensive understanding of phenotypic intensities and relationships in non-clonal hematopoiesis for patients with cytopenias. While the relative ease of implementing the Ogata FCSS is attractive, improvements are essential for diagnostic accuracy; improving the granularity parameter alone is not sufficient. Adding measurements for the maturing myeloid and erythroid compartments may increase the diagnostic utility of the Ogata FCSS but requires further study. Disclosures Brodersen: Hematologics Inc.: Employment. Menssen:Hematologics Inc.: Employment. Zehentner:HematoLogics Inc.: Employment, Equity Ownership. Stephenson:Hematologics Inc.: Employment. de Baca:Hematologics Inc.: Employment. Johnson:Hematologics Inc.: Employment. Singleton:Hematologics Inc.: Employment. Hartmann:Hematologics Inc.: Employment. Loken:Hematologics: Employment, Equity Ownership. Wells:HematoLogics Inc.: Employment, Equity Ownership.

Description: The concept of clonal diversity is becoming well accepted as a hallmark of cancer. As a tumor grows and progresses, the genetic landscape of the cell population can change. These changes are largely due to random errors occurring during each cell division or through mutational events stimulated by various exposures. When one of these random events occurs in the right locus it will result in a survival advantage for all of the subsequent offspring of that initial cell. Understanding the underpinnings of clonal diversity may prove to be an essential part of the treatment plan for patients, helping to guide drug selection and to determine the percentage of clones that may be responsive/resistant to specific treatments. Moreover, many of the therapies used to treat myeloma will likely induce mutations through their mechanisms of action or through unexpected secondary effects. Understanding the effects of individual therapies and specific combinations on the underlying mutation rates that drive the diversity of a tumor population will help to identify regimens that increase the underlying mutation rate and put the patient at an increased risk of developing an aggressive clone. These changes can be identified by next generation sequencing of the bulk tumor population compared to single cell clones that have been selected from that population. In order to identify the diversity of mutations found in the bulk tumor population, we propose that single cell cloning the parent population, and then sequencing and comparing across several individual clones will give a better idea of the random variety of mutations present in individual cells that originate from the same parent population. To identify the diversity present in a random population of myeloma cells we selected the human myeloma cell line KMS-18 as a model system. We sorted single cells from the KMS-18 parent population by FACS with the selection criteria based solely on the viable, single cells. These individually sorted cells expanded over a period of weeks until the population was large enough to be collected for analysis (target approximately 5E6 cells). Four of these single cell clones were selected (SCC_04, SCC_10, SCC_16, SCC_18) for analysis. We prepared whole genome libraries and captured a 3.2Mb region using the Agilent SureSelect Kinome capture kit. The final capture libraries were sequenced on the Illumina MiSeq platform to an average target region depth of 200X. Results were filtered to identify the number of mutations present exclusively in one subclone compared to another. Such events either existed in the original single cell or occurred early in the expansion of the single cell clone. To limit the analysis to events present in the original single cell or very early in the doubling process we identified the variants that were found at a frequency of 〉20%. Many of these events were present in multiple single cell clones that could define the clonal relationship of each original cell, however, 10% of these variants were unique to a single subclone. On average we observed 1.6 mutations per Mb of the target region. If this same mutation rate holds true across the entire genome, we would expect to see over 5000 unique mutations between any two random cells taken from a bulk tumor sample. Studies are currently ongoing to examine clonal diversity between generations of subclones. Further studies are also underway to look at changes in clonal diversity between different myeloma subtypes, with the hypothesis that more aggressive subtypes like t(4;14) and MAF may lead to a more diverse clonal population. If a more diverse clonal population correlates with more aggressive tumor subtype, then this returns full circle to the question of appropriate therapies, and if certain therapies may indeed increase diversity in the tumor population and result in a more aggressive relapse of the disease. Disclosures No relevant conflicts of interest to declare.

Description: Background: Single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) microarray analysis is a powerful tool to assess myelodysplastic bone marrow specimens for the presence of genomic gains and losses as well as loss of heterozygosity (LOH) (reviewed by Nybakken & Bagg, JMD 2014). Its application can be a valuable addition to conventional cytogenetic analysis and may be superior to FISH testing for MDS assessment. Currently, microarray analysis does not have widespread use in an MDS work-up. Several groups have demonstrated that flow cytometric analysis can detect phenotypic aberrations in bone marrow aspirates with cytopenias with more abnormalities identified in patients with poor prognosis or with multiple genotypic abnormalities (Loken et al. 2008; Cutler et al. 2011; van de Loosdrecht et al. 2013). In this study SNP microarray results were compared with conventional cytogenetic and MDS panel FISH findings as well as phenotypic abnormalities detected by flow cytometry. Patients and Methods: 185 bone marrow aspirate specimens submitted to our laboratory for MDS work-up were analyzed by SNP/CGH studies. 36 of these (19.5%) were positive by SNP/CGH microarray analysis. 32 of the positive microarray cases (88.9%) were also analyzed by conventional cytogenetic studies, 35 (97.2%) by MDS FISH panel (5p, 7q, +8, -17p, -20q) and 31 (86.1%) were assessed by multidimensional flow cytometry (FCM) and were assigned an FCSS score (Wells et al. 2003). Results: Of the specimens in which the SNP/CGH array demonstrated genotypic abnormalities, 11/32 (34.4%) were negative by conventional cytogenetic analysis while 12/35 (34.3%) showed no abnormalities by MDS FISH panel analysis. SNP/CGH analysis revealed additional chromosomal gains and losses in 18/32 (56%) in comparison to cytogenetic analysis and in 22/35 (63%) in comparison to FISH analysis. Loss of Heterozygosity regions were detected in 28/36 cases (78%) with 96.4% (27/28) of these being larger than 2 Mb and 53% (19/28) spanning a significant chromosomal region (e.g. 1p, 5q, 7q and 17p) with known oncogenic and other MDS related genes. In 10/32 cases (31%), microarray analysis was able to characterize the origin of marker chromosome material, previously reported with unknown identity by conventional cytogenetic analysis. In an additional subset of 10 out of 32 cases (31%), cytogenetic analysis was able to either characterize balanced translocations or low level sub-clonal abnormalities not identified by microarray analysis alone. In 11/36 (31%) microarray analysis was able to detect clonal heterogeneity and evolution. In none of the specimens did FISH analysis detected abnormalities not revealed by microarray analysis. Flow cytometry performed on 31 of the array positive specimens revealed 6 to have 〉20% abnormal myeloid progenitor cells (classified as AML) while 23 the remaining 25 cases showed phenotypic abnormalities consistent with MDS (FCSS ranging from 1-6). In two specimens with a FCSS of 0, LOH regions on 16q or 1p and 21q were found, respectively, without the presence of numerical aberrations. A FCSS score of 1 with minimal phenotypic abnormalities (n=3), was comprised of one specimen with del(5q), one with LOH of 7q and one with trisomy 8, 1p loss and 1q gain. Specimens with an FCSS of 2 (n=7) showed only one specimen classified as complex (5 or more abnormalities). The two FCSS =3 specimens showed del(5q) with del(12p) and several LOH regions, not complex findings. One of the 4 specimen with FCSS = 4 was classified as complex while the other 3 specimens showed monosomy 7, LOH of 7q or LOH of 1p, respectively. Genotypic abnormalities were also related to phenotypic abnormalities in 4/7 (57%) specimens in the FCSS = 5/6 category which revealed complex microarray findings. Half (3/6) of the AML class had complex findings as well. Conclusions: These results emphasize the additional value that CGH/SNP microarray analysis adds to conventional cytogenetic analysis. Our dataset confirms that FISH studies do not provide additional information for MDS specimens positive by cytogenetic and/or microarray analysis. Most importantly, a high correlation between our phenotypic flow cytometric scoring system for myeloid abnormalities and microarray findings has been identified. Higher flow cytometric abnormality scores correlate with increasing complexity of genomic abnormalities. Disclosures Zehentner: HematoLogics Inc.: Employment, Equity Ownership. Brodersen:Hematologics Inc.: Employment. Stephenson:Hematologics Inc.: Employment. de Baca:Hematologics Inc.: Employment. Menssen:Hematologics Inc.: Employment. Hammock:Hematologics Inc.: Employment. Johnson:Hematologics Inc.: Employment. Hartmann:Hematologics Inc.: Employment. Loken:Hematologics Inc.: Employment, Equity Ownership. Wells:HematoLogics Inc.: Employment, Equity Ownership.

Description: The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT0145429) is a longitudinal study of 1000 patients with newly-diagnosed multiple myeloma. The study opened July 2011 and now includes over 650 patients from 91 sites in the United States, Canada and European Union. Each patient is required to receive an approved proteasome inhibitor, immunumodulatory agent, or both. Enriched tumor and matched constitutional samples are comprehensively analyzed using Long-Insert Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES) and RNA sequencing (RNAseq). Clinical parameters, Quality of Life measurements and health care resource utilization values are collected at study entry and every three months for a minimum of five years. Additional bone marrow aspirates are collected and analyzed at each recurrence or progression of disease. An extensive clinical and molecular database, the MMRF Researcher Gateway (https://research.themmrf.org), has been developed to facilitate the rapid dissemination of the results and provides the myeloma community with a mechanism to analyze the data. In this current interim analysis, we report on 195 patients that are fully characterized at the molecular level. We focused this analysis on immunoglobulin translocations and inter-chromosomal fusion transcripts. As expected we detected the classic canonical t(4;14), t(6;14), t(11;14), and t(14;16) translocations targeting FGFR3/MMSET, CCND3, CCND1, and MAF respectively. Seven patients presented with t(8;14) rearrangements correlating with high expression of MYC. Novel translocations were detected targeting MAP3K14/NIK in two patients and NFKB1, TOP1MT, TXNDC2, APOL3, FCHSD2, PRICKLE1, and BCL2L1 in individual patients. Importantly, the matched RNAseq data confirmed the high expression of MAP3K14, NFKB1, TOP1MT, APOL3 and BCL2L1. Moreover, the anti-apoptotic isoform of BCL2L1, Bcl-xL, was the prominent transcript isoform detected. In several patients we detected multiple IgH translocations. For instance the BCL2L1 translocation occurred in a downstream class switch recombination region from one associated with a co-occurring t(11:14). We also analyzed the RNAseq dataset for inter-chromosomal fusion transcripts and leveraged the independent long-insert WGS data to validate the predicted fusions. The only recurrent fusion partner identified was IgH-MMSET created by t(4:14). Fusion transcripts were detected in individual patients between IgH elements and MYEOV and WWOX along with several of the novel IgH translocation partners; NFKB1, TOP1MT, and APOL3. Several genes are involved in multiple fusions but with different partners. Three independent fusions were detected between the highly expressed gene FCHSD2 and MYC, MAP3K14, and ANKRD55. Three additional fusions were detected between MAP3K14 and ELL, PLCG2, and CDC27, which produce hybrid MAP3K14 isoforms lacking the N-terminal negative regulatory domain. We also detected three independent fusions involving BRF1, which is typically not expressed in myeloma tumors. These appear to be markers of translocations occurring just centromeric of the strong 3’ IgH enhancers. Interestingly, two of the partners are located in a region of chromosome 12 harboring MDM2 and spiked expression of MDM2 was observed. Additional genes with multiple fusion events included NEDD9 and ARHGEF12. Integrating the WES and RNAseq datasets, we identified 3518 variants (median 14 per patient) where the variant allele detected by WES, was also detected in the RNAseq data, suggesting it is potentially biologically relevant. Of these, 44 distinct genes were mutated in at least 2% of patients. The most common mutations (〉7 patients) occurred in KRAS, NRAS, IGLL5, DIS3, BRAF, ACTG1, EGR1, FAM46C, TRAF3, DUSP2, FGFR3, and PRR14L. We also identified a deletion of IKZF3/Aiolos in a patient who progressed rapidly on lenalidomide-dexamethasone. Alterations in Ikaros family members like Aiolos have recently been reported as a potential mechanism of resistance to IMiDs. As the study continues to mature, we expect it will provide unprecedented molecular characterization and correlating clinical datasets that will help define the determinants of response to anti-myeloma agents and facilitate future clinical trial designs, thus serving as a stepping-stone toward personalized medicine for myeloma patients. Disclosures Lonial: Millennium: The Takeda Oncology Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding.