Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
Deciphering genomic architecture is key to identifying novel disease drivers and understanding the mechanisms underlying myeloma initiation and progression. In this work, using the CoMMpass dataset, we show that structural variants (SV) occur in a nonrandom fashion throughout the genome with an increased frequency in the t(4;14), RB1, or TP53 mutated cases and reduced frequency in t(11;14) cases. By mapping sites of chromosomal rearrangements to topologically associated domains and identifying significantly upregulated genes by RNAseq we identify both predicted and novel putative driver genes. These data highlight the heterogeneity of transcriptional dysregulation occurring as a consequence of both the canonical and novel structural variants. Further, it shows that the complex rearrangements chromoplexy, chromothripsis and templated insertions are common in MM with each variant having its own distinct frequency and impact on clinical outcome. Chromothripsis is associated with a significant independent negative impact on clinical outcome in newly diagnosed cases consistent with its use alongside other clinical and genetic risk factors to identify prognosis.
Outcomes of Patients With Hematologic Malignancies Who Received Inpatient Palliative Care Consultation
PURPOSE:Palliative care (PC) plays an established role in improving outcomes in patients with solid tumors, yet these services are underutilized in hematologic malignancies (HMs). We reviewed records of hospitalized patients with active HM to determine associations between PC consultation and length of stay, intensive care unit stay, 30-day readmission, and 6-month mortality compared with those who were not seen by PC. METHODS:We reviewed all oncology admissions at our institution between 2013 and 2019 and included patients with HM actively on treatment, stratified by those seen by PC to controls not seen by PC. Groups were compared using Wilcoxon rank-sum, chi-square, and Fisher's exact tests on the basis of the type and distribution of data. Multiple logistic regression models with stepwise variable selection methods were used to find predictors of outcomes. RESULTS:< .001). These data were confirmed in multivariable models. CONCLUSION:In this retrospective study, more than two thirds of patients with HM did not receive PC consultation despite having similar comorbidities, suggesting that inpatient PC consultation is underutilized in patients with HM, despite the potential for decreased readmission rates.
Chromothripsis as a pathogenic driver of multiple myeloma
Analysis of the genetic basis for multiple myeloma (MM) has informed many of our current concepts of the biology that underlies disease initiation and progression. Studying these events in further detail is predicted to deliver important insights into its pathogenesis, prognosis and treatment. Information from whole genome sequencing of structural variation is revealing the role of these events as drivers of MM. In particular, we discuss how the insights we have gained from studying chromothripsis suggest that it can be used to provide information on disease initiation and that, as a consequence, it can be used for the clinical classification of myeloma precursor diseases allowing for early intervention and prognostic determination. For newly diagnosed MM, the integration of information on the presence of chromothripsis has the potential to significantly enhance current risk prediction strategies and to better characterize patients with high-risk disease biology. In this article we summarize the genetic basis for MM and the role played by chromothripsis as a critical pathogenic factor active at early disease phases.
Inflammation and infection in plasma cell disorders: how pathogens shape the fate of patients
The role of infection and chronic inflammation in plasma cell disorders (PCD) has been well-described. Despite not being a diagnostic criterion, infection is a common complication of most PCD and represents a significant cause of morbidity and mortality in this population. As immune-based therapeutic agents are being increasingly used in multiple myeloma, it is important to recognize their impact on the epidemiology of infections and to identify preventive measures to improve outcomes. This review outlines the multiple factors attributed to the high infectious risk in PCD (e.g. the underlying disease status, patient age and comorbidities, and myeloma-directed treatment), with the aim of highlighting future prophylactic and preventive strategies that could be implemented in the clinic. Beyond this, infection and pathogens as an entity are believed to also influence disease biology from initiation to response to treatment and progression through a complex interplay involving pathogen exposure, chronic inflammation, and immune response. This review will outline both the direct and indirect role played by oncogenic pathogens in PCD, highlight the requirement for large-scale studies to decipher the precise implication of the microbiome and direct pathogens in the natural history of myeloma and its precursor disease states, and understand how, in turn, pathogens shape plasma cell biology.
Characterization of Second Primary Malignancies in Mucosa-Associated Lymphoid Tissue Lymphomas: A SEER Database Interrogation
INTRODUCTION/BACKGROUND:Second primary malignancies (SPMs) are long-term complications in cancer survivors. Mucosa-associated lymphoid tissue (MALT) lymphomas are indolent extra-nodal marginal zone lymphomas, the majority of which typically have long-term survival. In this study, we investigated the incidence and pattern of SPMs in adult patients diagnosed with MALT lymphomas between January 2000 and December 2016. METHODS:Using the SEER-18 database and multiple primary standardized incidence ratio (MP-SIR) session of SEER stat software for statistical analysis, we assessed SPMs in MALT lymphomas. RESULTS:During this time, a total of 12,500 cases of MALT lymphomas were diagnosed, of which 1466 patients developed 1626 SPMs (O/E ratio: 1.48, 95% CI:1.41-1.55, P<.001). The median latency period for development of SPMs was 54 months (range 6-201 months). Secondary non-Hodgkin lymphomas, as defined by SEER as distinct from the primary lymphoma, was the most common SPM with 299 cases, followed by lung cancer (O/E ratio: 6.15, 95% CI:5.47-6.89, P<.0001). There were 898 SPMs that developed between 6- 59 months (O/E ratio: 1.47, 95% CI:1.37-1.57, P<.0001) and 728 after 60 months latency (O/E ratio: 1.5, 95% CI:1.39-1.61, P<.0001) after diagnosis of the primary MALT lymphomas. An increased incidence of both solid and hematologic cancers occurred in patients as early as 6 months after diagnosis of MALT lymphoma. CONCLUSION/CONCLUSIONS:These findings indicate that despite the indolent nature of most MALT lymphomas, there is an increased risk for SPMs warranting long-term follow up.
Improving prognostic assignment in older adults with multiple myeloma using acquired genetic features, clonal hemopoiesis and telomere length
Multiomic Mapping of Copy Number and Structural Variation on Chromosome 1 (Chr1) Highlights Multiple Recurrent Disease Drivers [Meeting Abstract]
Introduction Copy number abnormalities (CNA) and structural variants (SV) are crucial to driving cancer progression and in multiple myeloma (MM). Chr1 CNA are seen in up to 40% of cases and associate with poor prognosis. Variants include deletions, gains, translocations and complex SV events such as chromothripsis (CT), chromoplexy (CP) and templated insertions (TI) which result in aberrant transcriptional patterns. Abnormal expression of genes on chr1 lead to the adverse clinical outcome and studies focussed on 1p12, 1p32.3 and 1q12-21 identified potential causal genes including TENT5C, CDKN2C, CKS1B, PDZK1, BCL9, ANP32E, ILF2, ADAR, MDM2 and MCL1 but none fully explain the clinical behavior. To address this deficiency and to relate chromatin structure to gene deregulation we present a multiomic bioinformatic analysis of SV, CNA, mutation and expression changes in relation to the chromatin structure of chr1. Methods We analysed data derived from 1,154 CoMMpass trial patients. We analyzed 972 NDMM patients with whole exome for mutations, and 752 whole genomes for copy number, translocations, complex rearrangements such as CP, CT and TI as previously described. Using GISTIC 2.0, we identified hotspots of CNA. This information was then analyzed in conjunction to the RNA-seq data derived from 643 patients to determine the aberrant transcriptional landscape of chr1. Using HiC data derived from U266 MM cell line, we associated these changes with TAD structures, A/B compartments, and histone marks along chr1, to gene expression changes, and recurrent SV. Using the cell line dependency map for CRISPR knockdown of the gene set on chr1 derived from 20 MM cell lines we related cell viability to chr1 copy number status. Results * We identified 7 hotspots of deletion, 9 of gain, 3 of CT and 2 of templated-insertion across chr1. We mapped these regions to epigenetic plots and show that gained regions are hypomethylated compared to the rest of chr1 (Wilcoxon, p=0.0002). Overall 69% of gain(1q) and 45% of the non-gained hotspots were in A compartments (chi 2=11, p=0.0009) and had an overall higher compartment score (p=0.01). * The recurrent regions of loss on 1p confirm the clinical relevance of this region. The critical importance of TENT5C, CDKN2C and RPL5 is identified by the impact of deletion, mutation and the rearrangement of superenhancers. Further this convergence of multiple oncogeneic mechanisms to a single locus points to a number of novel candidate drivers including FUB1 and NTRK1. * We provide important new information on 1q21.1-1q25.2 encompassing 145-180Mb a transcriptionally dense region containing 6 GISTIC 2.0 hotspots of gain (G2-G7). The hotspots occur within TAD structures that correlate upregulation of known drivers listed above and also identified novel potential upregulated drivers including POU2F1, a transcription factor, CREG1, an adenovirus E1A protein that both activates and represses gene expression promoting proliferation and inhibiting differentiation (G6) and BTG2 a G1/S transition regulator (G8). These data for copy number gain provides strong evidence for the prognostic relevance of of multiple drivers within deregulated TADs rather than single candidate genes. It also highlights the importance of the chromatin structure of Chr1 in the generation of these events. * Using dependency map CRISPR data we identified 320 essential genes for at least one cell line (>1). A common set of 31 genes were identified including 3 proteasome subunits (PSMA5, PSMB2, PSMB4), three regulators of ubiquitin-protein transferase activity (RPL5, RPL11, CDC20), splicing (SF3B4, SF3A3, SFPQ, RNPC3, SRNPE, PRPF38A, PRPF38B) and DTL. A common dependency for 1q+ or 1p- was not identified but a number of dependencies were identified in more than one cell line including UQCRH, SLCA1, CLSPN in 1p- cell lines and IPO9, PPIAL4G, and MRPS2 in 1q+. Conclusion We present an elegant anatomic map of chr1 at the genetic and epigenetic levels providing an unprecedented level of resolution for the relationships of structural variants to epigenetic, expression and mutation status. The analysis highlights the importance of active chromatin in gene deregulation by SV and CNA where the importance of multiple gene deregulation within TAD structures is critical to MM pathogenesis. The implications are that we could improve prognostic assignment and identify new targets for therapy by further characterizing these relationships. [Formula presented] Disclosures: Braunstein: Jansen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Davies: Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees.
Unifying the Definition of High-Risk in Multiple Myeloma [Meeting Abstract]
Introduction: There is considerable heterogeneity in the clinical outcome of newly diagnosed multiple-myeloma (NDMM) with some patients having a good prognosis while others fail to respond or relapse quickly after therapy progressing rapidly to death. Using risk scores based on clinical, biochemical and genetic features it is possible to predict some of this variation giving an ability to segment the disease into risk strata. Clinical studies have suggested that patients with standard-risk disease have benefited more from the recent advances in therapy compared to those with high-risk disease. The development of clinical trials specifically recruiting patients with high-risk disease features offers the potential to improve the outcome of a subgroup of patients with a very poor clinical outcome. To perform such studies is it important to have a unifying definition of high-risk including standard parameters, group size and outcome of individual risk strata so that clinical trial rigor can be achieved (e.g., common entry criteria, statistical power). In order to understand the size and feasibility of such studies we analyzed the Myeloma Genome Project (MGP) dataset to assess multiple risk factors and scores to determine and compare how they perform as risk stratifiers with each other.
Method(s): The MGP dataset is a large set of molecular and clinical data from 1273 patient with NDMM. Data were available on clinical variables (Albumin (Alb), B2-microglobulin (B2M), LDH, age), cytogenetic variables [t(4;14), t(14;16), t(14;20), 17p-, TP53 mutations, 1q+ and 1p-] and gene expression analysis (GEP70). A literature search was used to identify risk models used in clinical studies. Survival analysis was performed in R. The median follow-up at the time of analysis was 54.5 (53.2-56.5) months.
Result(s): The median patient age was 66 years, with 641 (50.4%) patients over age 65. The sex ratio (M:F) was 1:0.66. African American, White, and Asian constituted 17%, 76%, and 2%, of cases respectively. 26.7% received a stem cell transplant. We determined the size of the strata and actual risk (measure by the hazard ratios, HR) compared to standard risk cases for both PFS and OS of the various clinical models available, data are summarized in Figure 1. When looking at individual risk scores, the HR for progression for t(4;14), TP53 inactivation (deletion and mutations), gain(1q), and del(1p) were 1.4, 1.1, 1.3, and 1.1 respectively. When considering overall survival these HR were 1.4, 1.7, 1.5, and 1.4 respectively. We went on to analyze the impact of these events in combination and show that combined, there is increased specificity, especially for OS (HR 2.3-5.1) but they identify small subsets making up <10% of patients. We then analyzed the purely clinical scores (ISS) and combined clinical/genetic scores. We show again, that the more specific risk scores (double hit, Boyd IV, GEP70) identify between 7-13% of cases with HR (2-3.1) for OS. When we looked specifically at the younger patients (=< 65), similar trends were seen with GEP70 by RNA-seq offering one of the most interesting means of identifying HR cases.
Conclusion(s): In this large NDMM dataset, we demonstrate the clear variation in risk groups that occur dependent upon the approach used resulting in heterogeneous levels of risk, strata size, and performance. With the exception of GEP70, none of the single features are sensitive or specific enough to identify all cases. Risk models based on a combination of markers improve the ability to detect true high-risk disease but there remains variability. At a molecular level the inclusion of TP53 inactivation, and 1q+ improve the performance of the ISS. This analysis provides insights into standardizing the definition of high-risk and the generation of consensus definitions for clinical trial entry. Figure 1 [Formula presented] Disclosures: Braunstein: Jansen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Pawlyn: Celgene / BMS: 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; Amgen: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Cairns: Amgen: Research Funding; Merck Sharpe and Dohme: Research Funding; Takeda: Research Funding; Celgene / BMS: Other: travel support, Research Funding. Jackson: GSK: Consultancy, Honoraria, Speakers Bureau; takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; amgen: Consultancy, Honoraria, Speakers Bureau; celgene BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; J and J: Consultancy, Honoraria, Speakers Bureau; oncopeptides: Consultancy; Sanofi: Honoraria, Speakers Bureau. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Davies: Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees.
Hispanic or Latin American Ancestry Is Associated with a Similar Genomic Profile and a Trend Toward Inferior Outcomes in Newly Diagnosed Multiple Myeloma As Compared to Non-Hispanic White Patients in the Multiple Myeloma Research Foundation (MMRF) CoMMpassstudy [Meeting Abstract]
Introduction Large clinical data sets suggest that the natural history and prognosis of newly diagnosed multiple myeloma (NDMM) differs between patients of European and African ancestry, with the latter group exhibiting an earlier age at onset and poorer overall prognosis in some studies. The use of next generation sequencing (NGS) to characterize the genomic landscape of multiple myeloma (MM) suggests that the observed phenotypic differences between these groups of patients may reflect distinct underlying genomic profiles and mutational processes. Thus far, characterizations of this type have focused principally on patients of African ancestry (AA). Here, we characterize the genomic features and outcomes of a large series of patients of Hispanic or Latin American ancestry (HL) as compared to their Non-Hispanic white (NHW) counterparts. Methods Subjects were selected from the MMRF CoMMpass SM trial, a study that includes 1,154 patients with updated outcome data as of March, 2020. Within this data set, 760 patients had information on race and ethnicity. Among these, 55 HL patients and 478 NHW patients possessed complete clinical and genomic information. We analyzed baseline whole exome sequencing (WES) and long insert whole genome sequencing (WGS) as previously described (Walker, et al. Blood 2019). Our analysis focused on 63 known driver mutations in multiple myeloma and 39 sites of common copy number variation across the study population. Complex structural variants and tumor telomere length were called using previously described bioinformatic tools (Boyle et al. Leukemia 2021). Survival analysis was undertaken using the Kaplan-Meier method with hazard ratios determined by the Cox proportional hazards model. Results In a comparison of clinical features between the Hispanic and NHW population, we did not identify any differences in age of onset, gender, presenting cytogenetics, International Staging System Score (ISS), and IMWG Risk Category. The proportion of patients undergoing autologous stem cell transplantation was similar between groups. We identified no statistically significant differences in the presence of characteristic translocations involving IgH locus or in hyperdiploidy status. No statistically significant differences in tumor mutational burden or loss-of-heterozygosity percentage emerged between HL and NHW patients. We examined non-synonymous variations (NSV) and copy number variations at the loci of known MM driver genes and encountered no statistically significant differences in NSV, copy number, or biallelic status. We further categorized genes into pathways relevant to the pathogenesis of MM and discovered no difference in the proportions of patients harboring mutations in genes related to the MEK/ERK and NF-kappaB pathways, cell cycle regulation, and epigenetic modification. We were unable to the distinguish either population based on the presence of chromothripsis or in the overall preponderance of an APOBEC mutational signature. Tumor telomere length was not significantly different between the populations. An analysis of overall and progression free survival (PFS) with a median duration of follow up of 44 months revealed a trend toward poorer outcomes among the HL population that did not reach statistical significance. Median PFS was 24 months in HL patients and 35 months in the NHW population (p = 0.19). Median OS was not reached in either ethnic subgroup. In terms of overall survival, age, ISS score, overall number of driver mutations, and the presence of chromothripsis emerged with a negative impact on outcome (Figures 1a, 1b). These variables with the exception of chromothripsis retained their significant impact on progression free survival (Figure 2a, 2b). Conclusion The correlation between Hispanic or Latin American ancestry and underlying disease biology in MM has yet to be fully elucidated. In our analysis, which was based on self-declared ancestry as opposed to admixture, no obvious differences in significant measures of genomic variation known to impact prognosis in MM emerged between HL and NHW patients. These results may help to inform the future large-scale studies to ascertain the impact of genomics, disease biology and socioeconomic factors on outcomes in this heterogeneous patient population. [Formula presented] Disclosures: Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees.
A new decade: novel immunotherapies on the horizon for relapsed/refractory multiple myeloma
INTRODUCTION/UNASSIGNED:: Survival in multiple myeloma (MM) has improved due to the ongoing revolution of therapeutic approaches. Nevertheless, many patients relapse, and additional novel approaches are required to prolong remissions and prevent disease progression. AREAS COVERED/UNASSIGNED:Considering the success of monoclonal antibodies (mAbs) against CD38 and SLAMF7 in relapsed/refractory MM (R/R MM), additional antigens expressed on malignant plasma cells are being investigated as treatment targets. Among these, many trials are focusing on B cell maturation antigen (BCMA), using either antibody-drug conjugates (ADCs), bispecific T cell engagers (TCE), or chimeric antigen receptor T cells (CAR-T). Other potential targets include the myeloma markers CD138, GPRC5D, FcRH5, the plasma cell differentiating factors APRIL, TACI and BAFF, and the immune checkpoint proteins CD47 and TIGIT. Additionally, novel immunomodulatory Cereblon E3 Ligase Modulators (CELMoDs) offer the potential to overcome resistance to conventional immunomodulatory agents. Based upon PubMed and abstract searches primarily from the past 4 years, here we review the data supporting novel immunotherapies for R/R MM. EXPERT OPINION/UNASSIGNED:: Overcoming disease resistance remains a challenge in R/R MM. Novel therapeutic approaches targeting MM antigens and/or enhancing immune cell function offer the potential to prolong survival and are actively being investigated in clinical trials.