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Simple Summary T-cells defend the human body from pathogenic invasion via specific recognition by T-cell receptors (TCRs). The TCR genes undergo recombination (rearrangement) in a myriad of possible ways to generate different TCRs that can recognize a wide diversity of foreign antigens. However, in patients with T-cell lymphoma (TCL), a particular T-cell becomes malignant and proliferates, resulting in a population of genetically identical cells with same TCR rearrangement pattern. To help diagnose patients with TCL, a polymerase chain reaction (PCR)-based assay is currently used to determine if neoplastic cells in patient samples are of T-cell origin and bear identical (monoclonal) TCR rearrangement pattern. Herein, we report the application of a novel segmentation and copy number computation algorithm to accurately identify different TCR rearrangement patterns using data from the whole genome sequencing of patient materials. Our approach may improve the diagnostic accuracy of TCLs and can be similarly applied to the diagnosis of B-cell lymphomas. Abstract T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, n = 44) and extranodal NK/T-cell lymphomas (ENKTLs, n = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.

Acute promyelocytic leukemia (APL) is a subtype of myeloid leukemia characterized by differentiation block at the promyelocyte stage. Besides the presence of chromosomal rearrangement t(15;17), leading to the formation of PML-RARA (promyelocytic leukemia-retinoic acid receptor alpha) fusion, other genetic alterations have also been implicated in APL. Here, we performed comprehensive mutational analysis of primary and relapse APL to identify somatic alterations, which cooperate with PML-RARA in the pathogenesis of APL. We explored the mutational landscape using whole-exome (n=12) and subsequent targeted sequencing of 398 genes in 153 primary and 69 relapse APL. Both primary and relapse APL harbored an average of eight non-silent somatic mutations per exome. We observed recurrent alterations of FLT3, WT1, NRAS and KRAS in the newly diagnosed APL, whereas mutations in other genes commonly mutated in myeloid leukemia were rarely detected. The molecular signature of APL relapse was characterized by emergence of frequent mutations in PML and RARA genes. Our sequencing data also demonstrates incidence of loss-of-function mutations in previously unidentified genes, ARID1B and ARID1A, both of which encode for key components of the SWI/SNF complex. We show that knockdown of ARID1B in APL cell line, NB4, results in large-scale activation of gene expression and reduced in vitro differentiation potential.

Background: Treatment of multiple myeloma has evolved considerably in the past few years with availability of several news drugs as well as increasing use of multidrug combinations. These changes have no doubt led to the improved survival seen among patients with MM. We have previously shown that outcomes of patients intolerant or refractory to one of the IMiDs and bortezomib had a poor outcome. Since that time, other drugs of the same class as well as new classes of drugs have been introduced for the treatment of MM. We designed this retrospective study to estimate the outcomes in patients with relapsed myeloma, who have become refractory to the current generation IMiDs and proteasome inhibitors. Patients and Methods: Patients with relapsed multiple myeloma who have received at least 3 prior lines of therapy, is refractory to both an IMiD (lenalidomide or pomalidomide) AND a proteasome inhibitor (bortezomib or carfilzomib), and has been exposed to an alkylating agent were identified from multiple centers. The time patients met the above criteria was defined as T0, and details of all treatment regimens before and after T0 were collected using electronic CRFs. The study was approved by the IRB at the respective centers. Results: 543 patients were enrolled in this study; median age was 62 years (31-87) and 61% were males. Patients were enrolled from centers in North America (n=181), Europe (n=318), and Asia Pacific (n=44). Patients were diagnosed between 2006 and 2014, the median duration between diagnosis of myeloma and study entry (T0) was 3.1 years (0.3 to 9). The median (95% CI) estimated follow up from diagnosis and from T0 were 61 (57, 66) months and 13 (11, 15) months respectively. The median number of lines of therapy prior to T0 was 4 (3-13), 48% had a prior transplant. The median OS from T0 for the entire cohort was 13 (11, 15) months. For these 462 patients, the median number of recorded regimens was 2 (1-9). The overall response and the depth of response to each line of treatment following T0 are as shown in the table. The median (95% CI) PFS and OS from T0 was 5 (4, 6), and 15.2 (13, 17), respectively. The overall survival for the 81 patients with no treatment post T0 was only 2.1 months. In a multivariate analysis, duration from diagnosis to T0, ISS stage III and number of lines of therapy were all associated with inferior PFS, as well as OS, and in addition, serum creatinine>2 mg/dL at T0 also predicted inferior OS. Conclusions: The study provides the expected outcome following development of myeloma that is refractory to a PI and an IMiD. The outcomes of these patients appear to be better than we had seen historically in patients refractory/ intolerant to bortezomib and IMiDs, highlighting the increased treatment options available for these patients. However, there is decreasing response rate to sequential regimens highlighting the development of drug resistance. The data provides a bench mark for comparison of new therapies that are being evaluated in this disease. Table Table. Disclosures Dimopoulos: Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: 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; Genesis: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Kastritis:Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Terpos:BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Celgene: Honoraria; Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria, Other: Travel expenses; Amgen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Novartis: Honoraria. Hillengass:Sanofi: Research Funding; Novartis: Research Funding; Amgen: Consultancy, Honoraria; BMS: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria. Leleu:TEVA: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; LeoPharma: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria; Pierre Fabre: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Takeda: Honoraria. Oriol:Janssen: Honoraria, Other: Expert board committee; Amgen: Honoraria, Other: Expert board committee. Cavo:Celgene: Consultancy, Honoraria; Millennium: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Mateos:Janssen: 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Vij:Shire: Consultancy; Takeda: Consultancy, Research Funding; Jazz: Consultancy; Karyopharma: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding. Lokhorst:Genmab: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. van de Donk:Amgen: Research Funding; Janssen: Research Funding; BMS: Research Funding; Celgene: Research Funding. Mark:Onyx: Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Ludwig:Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; BMS: Speakers Bureau; Janssen: Speakers Bureau. Jagannath:Novartis: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene: Consultancy; Merck: Consultancy. Usmani:Array: Research Funding; Britsol-Myers Squibb: Consultancy, Research Funding; Skyline: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: 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; Pharmacyclics: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Speakers Bureau. Dytfeld:Janssen Poland: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Amgen: Consultancy, 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. Moreau:Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau. Lee:Amgen: Membership on an entity's Board of Directors or advisory committees. Shustik:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: 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. de la Rubia:Celgene: Consultancy; Bristol Myers: Consultancy; Amgen,: Consultancy; Janssen: Consultancy. Durie:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

The prognosis for patients multiple myeloma (MM) has improved substantially over the past decade with the development of new, more effective chemotherapeutic agents and regimens that possess a high level of anti-tumor activity. In spite of this important progress, however, nearly all MM patients ultimately relapse, even those who experience a complete response to initial therapy. Management of relapsed MM thus represents a vital aspect of the overall care for patients with MM and a critical area of ongoing scientific and clinical research. This comprehensive manuscript from the International Myeloma Working Group provides detailed recommendations on management of relapsed disease, with sections dedicated to diagnostic evaluation, determinants of therapy, and general approach to patients with specific disease characteristics. In addition, the manuscript provides a summary of evidence from clinical trials that have significantly impacted the field, including those evaluating conventional dose therapies, as well as both autologous and allogeneic stem cell transplantation. Specific recommendations are offered for management of first and second relapse, relapsed and refractory disease, and both autologous and allogeneic transplant. Finally, perspective is provided regarding new agents and promising directions in management of relapsed MM.Leukemia accepted article preview online, 29 December 2015. doi:10.1038/leu.2015.356.

SummaryBy misdirecting the activity of Activation-Induced Deaminase (AID) to a conditional MYC transgene, we have achieved sporadic, AID-dependent MYC activation in germinal center B cells of Vk∗MYC mice. Whereas control C57BL/6 mice develop benign monoclonal gammopathy with age, all Vk∗MYC mice progress to an indolent multiple myeloma associated with the biological and clinical features highly characteristic of the human disease. Furthermore, antigen-dependent myeloma could be induced by immunization with a T-dependent antigen. Consistent with these findings in mice, more frequent MYC rearrangements, elevated levels of MYC mRNA, and MYC target genes distinguish human patients with multiple myeloma from individuals with monoclonal gammopathy, implicating a causal role for MYC in the progression of monoclonal gammopathy to multiple myeloma.