List of dysregulated oncogenes, tumor suppressor genes, and fusion proteins in the presence or absence of gain(1q) based on the Cancer Gene Census

Co-occurrence of regions of gain(1q) and loss(1p). A. The percentage of patients top and per patient (bottom) with specific region of gain B. A histogram summarising the number of gained regions per patient. C. The percentage of patients top and per patient (bottom) with specific regions of copy number loss D. Histogram summarizing the number of gained regions per patient.

Differentially methylated Illumina HM27 probes in MM vs PC

In the recent few decades, outcomes in patients diagnosed with hematological malignancies have been steadily improving. However, the improved prognosis does not distribute equally among patients from different backgrounds. Besides cancer biology, demographic and geographic disparities have been found to impact overall survival significantly. Specifically, patients from underrepresented minorities including Black and Hispanics, and those with uninsured status, having low socioeconomic status, or from rural areas have had worse outcomes historically, which is uniformly true across all major subtypes of hematological malignancies. Similar discrepancy is also seen in the health care professional field, where a gender gap and a disproportionally low representation of health care providers from underrepresented minorities have been long existing. Thus, a comprehensive strategy to mitigate disparity in the health care system is needed to achieve equity in health care.

Hi-C interaction and TAD map of CT1, TI1, D7 regions. The chromatin confirmation of the region encompassing CT1, TI1, and D7 across the 3 HMCLs (U266, RPMI8226, and KMS11) and PC for comparison. The region shows significant variability in the TAD strucure at the TENT5C locus across all samples in comparision to PC which could explain its dysregulation

Improving the outcome of high-risk myeloma (HRMM) is a key therapeutic aim for the next decade. To achieve this aim, it is necessary to understand in detail the genetic drivers underlying this clinical behavior and to target its biology therapeutically. Advances have already been made, with a focus on consensus guidance and the application of novel immunotherapeutic approaches. Cases of HRMM are likely to have impaired prognosis even with novel strategies. However, if disease eradication and minimal disease states are achieved, then cure may be possible.

AbstractPurpose: Chromosome 1 (chr1) copy-number abnormalities (CNA) and structural variants (SV) are frequent in newly diagnosed multiple myeloma (NDMM) and are associated with a heterogeneous impact on outcomes, the drivers of which are largely unknown. Experimental Design: A multiomic approach comprising CRISPR, gene mapping of CNAs and SVs, methylation, expression, and mutational analysis was used to document the extent of chr1 molecular variants and their impact on pathway utilization. Results: We identified two distinct groups of gain(1q): focal gains associated with limited gene-expression changes and a neutral prognosis, and whole-arm gains, which are associated with substantial gene-expression changes, complex genetics, and an adverse prognosis. CRISPR identified a number of dependencies on chr1 but only limited variants associated with acquired CNAs. We identified seven regions of deletion, nine of gain, three of chromothripsis (CT), and two of templated insertion (TI), which contain a number of potential drivers. An additional mechanism involving hypomethylation of genes at 1q may contribute to the aberrant gene expression of a number of genes. Expression changes associated with whole-arm gains were substantial and gene set enrichment analysis identified metabolic processes, apoptotic resistance, signaling via the MAPK pathway, and upregulation of transcription factors as being key drivers of the adverse prognosis associated with these variants. Conclusions: Multiple layers of genetic complexity impact the phenotype associated with CNAs on chr1 to generate its associated clinical phenotype. Whole-arm gains of 1q are the critically important prognostic group that deregulate multiple pathways, which may offer therapeutic vulnerabilities.

Introduction Treatment options for relapsed/refractory multiple myeloma (RRMM) are limited and associated with a poor median overall survival (OS) of 12.4 months (m) (Mateos et al. Leukemia 2022). The MajesTEC-1 trial demonstrated promising clinical activity of teclistamab (Tec), a BCMAxCD3 bispecific antibody, with an overall response rate (ORR) of 63%, complete response rate (CR) of 39.4%, median progression-free survival (PFS) of 11.3 m, and OS of 18.3 m. Here we present the results of a multicenter, retrospective study examining real-world patient characteristics and outcomes in patients with RRMM receiving Tec outside of a clinical trial, including those who would have been ineligible for the registrational study. Methods An IRB-approved retrospective study of patients with RRMM treated with Tec at 4 academic centers was performed. Patient demographics, prior treatments, clinical outcomes and toxicities with special attention to cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), and infection were extracted from the electronic patient record. Response rate was compared using Fisher's exact test. Median PFS and OS were estimated by Kaplan-Meier and compared using the log-rank test. Trial eligibility was evaluated using the MajesTEC-1 eligibility criteria. Results A total of 45 patients, who received at least 1 dose of Tec, were evaluated. Of these 39% were derived from under-represented minorities (25% Black, 14% Hispanic). Patient characteristics and comparison to the MajesTEC-1 population are summarized, Table 1. High-risk cytogenetic features were present in 42.2% of patients, and 46.7% had extra-medullary disease (EMD). All patients were triple class exposed and 80% were penta-class exposed. Most patients (84.4%) would have been ineligible for MajesTEC-1 due to cytopenias (44.4%), prior BCMA-directed therapy (42.2%), inadequate washout (42.2%), and poor performance status (PS) (26.7%). Therapy was delivered according to protocol with no increased rate of infections or bleeding, even in the group of patients with low blood counts and poor PS. CRS/ICANS events of any grade were observed in 55% and 13% of patients, respectively, during step-up dosing. Most CRS/ICANS events were mild-moderate in severity (CRS 42.2% grade 1, 11.1% grade 2; ICANS 4.4% grade 1, 0% grade 2) and were managed conservatively with antipyretics, tocilizumab (37.8%), and steroids (13.3%). Grade 4 CRS and ICANS were only seen in 1 patient; a separate individual experienced grade 5 ICANS after the third step up dose. The overall response rate (ORR) was 48.9% (95% CI 33.7-64.2) with 22.2% (95% CI 11.2-37.1) achieving at least a very-good partial response (VGPR). On univariate analysis prior anti-BCMA exposure was associated with an adverse ORR (23% vs 61%; p=0.02). Ineligibility for enrollment in MajesTEC-1, the presence of high-risk cytogenetics or EMD were not associated with ORR or depth of response. Updated follow up time, median PFS and OS will be presented at the meeting to allow time for data to mature. The presence of high-risk cytogenetics was associated with worse PFS (median NR vs 2.1 m, HR 2.32; p=0.041). Receipt of prior BCMA therapy and MajesTEC-1 ineligibility were not associated with PFS or OS. At the time of data cut-off, 19 (42.2%) patients remained on Tec; reasons for discontinuation included disease progression, infections, and CRS/ICANS in 19 (42.2%), 4 (8.8%), and 3 (6.7%) patients, respectively. Conclusion Overall, Tec demonstrated significant clinical activity even in a group of heavily pre-treated real-world patients comprising high-risk and extramedullary disease populations. The overall toxicity profile was similar to prior reports demonstrating that side effects can be readily managed using simple approaches with only limited patients needing more intensive interventions. These results also suggest Tec may be used in patients previously excluded from clinical trials because of adverse clinical characteristics with high ORR being seen and an absence of increased toxicity. In the BCMA-naive population ORR were similar to MajesTEC-1, but were lower in the previously BCMA-exposed population. High-risk cytogenetics and EMD remain adverse prognostic features with Tec despite similar ORR.

Background: The prognostic importance of 1q gain, present in 30% of cases, has led to it being extensively studied and incorporated into prognostic systems. Amplification (>3 copies) of 1q is seen in 10% of cases and has a greater degree of specificity for poor outcome than gain alone. Despite this, there is ongoing debate about its value, likely due to differences in the nature and penetrance of deregulated drivers. To gain insight into this we dissected the structural changes seen at the 1q level and integrated them with expression and clinical data to identify potential drivers and gain insight into progression mechanisms. Methods We analyzed data derived from 1,154 CoMMpass trial patients including 972 NDMM patients with whole exome for mutations, and 752 whole genomes for copy number (CNA), translocations, and complex rearrangements. Using GISTIC 2.0 and PFC we identified hotspots of CNA. This information was analyzed in conjunction with the RNA-seq data derived from 643 patients to determine the aberrant transcriptional landscape of 1q. Results: We identified nine regions of gain (numbered G1 to G9), eight of them being on 1q. Several potential oncogenes such as BCL9 (G2), MCL1 (G3), SLAMF7 (G5), POU2F1 (G6), and BTG2 (G8) lay within these regions of gain. Of note, other previously identified drivers lay outside specific hotspots: ANP32E (306 kb downstream of G3) CKS1B and ADAR1 (1209 kb ( and 1561 kb away from G4, respectively), ATF6 (941 kb from G5), and PBX1 (2313 kb upstream of G6). These data suggest that although important, these hotpots do not drive the entire spectrum of genes upregulated as a consequence of gain 1q. We noted that 302 samples (40%) had at least one gained region with 80% (241/302) having gain of 7-9 regions; 69% (207/302) had gain G2-G9. Each of the gained regions occurred at a similar frequency (G2-G9 range 79-87%) with the exception of G1 located at the sub-telomeric border of 1p seen only in 6% (18/302) of patients. There were 219 cases with gain of G2-G9. These results show two broad groups of gain 1q; whole arm gains and a group with focal gain. Patients with whole arm gain had a worse PFS (HR 1.3 (95% CI 1.01-1.6) and OS (HR 1.6 (95% CI 1.15-2.2) than patients with no 1q gain; the outcome for patients focal events was neutral. Whole arm gains strongly associated with a complex genomic background including with t(4;14) (corr=0.10, BF=1.06), loss of acrocentric chromosomes (del(13q) corr=0.23, BF=118623 and del(14q) corr=0.12, BF=2.9) and other deletions (del(4p) corr=0.11, BF=1.89, del(16p) corr=0.12, BF=2.3) and negatively correlated to trisomies and t(11;14) (corr=0.16, BF=184). Interestingly whole arm gains had significantly shorter telomeres and a higher mean age, and patients with critically short tumor telomeres were over-represented (Corr=0.11, BF=1.2). Common associations with CKS1B gain are mostly found in the whole arm gains group. Amp(1q) was over represented in the whole arm gain group (87%) and associated with the worst outcome (data not shown). Similarly, focal events strongly associated with templated insertion (corr=0.34, BF=6e14), MYC translocation (corr=0.24, BF=3034538), and HRD (corr=0.13, BF=4.9). To address expression changes in focal changes we compared patients with no 1q gain (n=297) with patients with a focal event (n=56); we identified 20 genes of which the majority (n=12) were located on chromosome 1 and related to protein handling. We compared patients with no evidence of 1q gain with patients with a whole arm gain (n= 157); the number of deregulated genes was higher both on 1q and overall (n=585 and n=2409 respectively) suggesting that generalized gene deregulation is part of a more complex genome wide mechanism. Interestingly, 101 were transcription factors and included upregulation of BACH2, NR5A1, MYBL1. GLMP, and E2F2 and downregulation of PAX5, SMAD1, TBX21, SIX4, EGR3, and GF1 most of them being involved in histone methylation, intracellular signaling, and regulation of transcription. Conclusions: Our data add precision by which 1q is associated with an adverse outcome and an aggressive disease phenotype by separating out focal gains, that occur on a favorable background and associate with a good outcome and those with arm-length gains, associated with high-risk disease features, deregulation of multiple transcriptional programs, increased metabolism and aggressive clinical behavior. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

In a phase 3 randomised study, Hartmut Goldschmidt and colleagues1 from the German-Speaking Myeloma Multicenter Group (GMMG) explored the addition of an anti-CD38 monoclonal antibody isatuximab to standard induction therapy with lenalidomide, bortezomib, and dexamethasone in transplantation-eligible patients with newly diagnosed multiple myeloma. The primary endpoint of part 1 of this study was minimal residual disease negativity, as assessed by next-generation flow cytometry with a sensitivity cutoff of 1 × 105 cells after induction therapy.

Introduction: Current data suggests Black/African Americans (AA) have an increased risk of developing multiple myeloma (MM), especially in comparison to White/European Americans (EA). However, the underlying causes remain unclear. Genetic definition of the spectrum of acquired mutations and the signatures they contain could help us to understand the mechanism underlying this excess risk. Currently, only limited information is available on the mutational spectra within AAs and the majority of data that has been generated is based on the societal construct of self-identified race/ethnicity alone. To address this deficiency and the potential associated bias, it is critical to examine greater numbers of whole genome sequencing (WGS) data from AAs. Data from a pilot study indicate a prolonged and more intense exposure to the germinal center (GC) reaction in the early evolutionary phases of MM within AAs, suggesting that it is essential to examine sequencing data from early disease stage i.e. smoldering MM (SMM) to better understand genetic predisposition in AAs. Methods: To address the mutational basis of MM and how it varies based on racial origin we carried out two large studies, Polyethnic-1000 and the Smoldering Myeloma Registration Trial (SMRT) study. Furthermore, we examined a cross-sectional series of WGS and whole exome sequencing (WES) data derived from cases with SMM and MM already sequenced to characterize the pattern of mutations and the signatures in both the coding and non-coding regions of the genome. Importantly, to accurately infer racial ancestry, we built an admixture workflow into our sequencing analysis pipeline, enabling us to address the variability in origin from within the MM cases ranging from regions of Europe to subsets of cases with African, North/South American, and Asian origin directly. We showed its use in previous work describing the heterogenous genetic admixture in MM cases that self-identified Hispanic and Latino. Our pipeline uses a suite of well-supported bioinformatic tools for preprocessing sequencing data according to best practices, cataloguing germline variants across a large series of patients, generating ancestry admixture estimations per patient, determining telomere length and composition, and identifying the spectrum of somatic events including single nucleotide variants, small insertions/deletions, copy number variants, and structural variants using consensus calling. All source code and reference data is publicly available via a GitHub repository (https://github.com/pblaney/mgp1000). Results: We generated new WGS data from 65 MM cases (EA n=15, AA n=50), and 44 SMM cases (EA n=36, AA n=18) as part of the Polyethnic 1000 and SMRT study. We also systematically reanalyzed 473 cases with deep (>30x) WGS data and all cases in the CoMMpass study low-depth (5-12x) WGS (n=943). Estimating ancestral composition directly from the genetic data of the CoMMpass study, we identified discrepancies between the self-reported race and the genetically determined admixture composition. Approximately 75% of individuals identified as 'White' but 7% of these cases had a genetic composition that included greater than 10% contribution from African, North/South American, or Asian ancestry. More interesting, 18% identified as 'Black/African American' but 50% of these cases had greater than 10% contribution from European, North/South American, or Asian ancestry. These results demonstrate the underlying genetic heterogeneity in a population that is currently clinically classified as the homogenous and thus lead to skewed evaluations of race and outcome in MM. We will compare the mutational spectra within these groups with different origins to address the risk of developing MM as well as addressing the time of origin of MM within the different populations. Conclusion: We show that there is significant variability of admixture from Europe, North/South America, and Africa within patients who self-identify as White, Black/African American, or Hispanic/Latino in clinical datasets from the U.S. This reinforces the need for complementary genetic admixture with racial self-identification when investigating the links between racial ancestry and outcomes in MM. Figure: Admixture composition of CoMMpass study shows significant contribution of African, North/South American, and East/South Asian origins in predominant European ancestral background. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Background: Targeted immunotherapy combinations including anti-CD38 monoclonal antibody daratumumab have significantly increased the depth of response and clinical outcome in newly diagnosed multiple myeloma (NDMM). Despite this improvement, 30-40% of patients still progress early and fail to achieve sustained minimal residual disease (MRD) negativity through largely unknown resistance mechanisms. Here we integrate whole genome sequencing (WGS) and single cell RNA (scRNA), surface protein (CITE), and TCR sequencing from patients with NDMM to characterize genomic and immune microenvironment features related to the failure to achieve sustained remission. Methods: 5'single-cell RNA-sequencing with an additional capture of the TCR and surface protein markers (CITEseq) was performed at both induction (T1) and at the end of induction (T2) with DKRd (Daratumumab-Carfilzomib, Lenalidomide and dexamethasone). A total of 148,280 cells were analyzed for RNA and CITE from 17 patients at T1 and 18 at T2. Twenty-seven cell types were identified and changes in their gene expression were examined. Data were integrated with 40,000 healthy bone marrow cells from the Human Cell Atlas. For TCR-seq, a total of 22,882 ⍺β clonotypes were analyzed. Fc-mediated antibody effector function is associated with sustained MRD negativity The microenvironment changed drastically between diagnosis and end of induction. The achievement of sustained MRD negativity were associated with an expansion of activated CD56-bright NK cells at T1 (chi-squared=4, p=0.044). Furthermore, significant changes in the monocyte profile were seen between timepoints and response groups. We identified a subset of resident-like macrophages expressing markers such as IL1B and CXCL2 suggesting that there are some immune hot tumors that are associated with suboptimal responses. Although there weren't absolute differences in T-cell subsets, PCA analysis showed that the combination of CD8 effector 1, CD16+monocytes and CD56+NK profiles could be used to identify a subset of good responders achieving sustained MRD negativity. Inflammation resolution is associated with sustained MRD negativity when complete response is achieved, significant changes in the microenvironment were observed and expansion of CD16+ monocytes associated with sustained MRD negativity. These data were validated prospectively using flow cytometry (n=31). These data suggest that the presence of cells mediating Fc-dependent immune effector mechanisms at diagnosis could predict good response and the resolution of tumor induced inflammation after treatment is associated with anti-inflammatory CD16+ monocytes. Oligoclonality in T-cell is associated with treatment and response TCR analysis was available for 22,882 cells and showed that there were significantly fewer clonotypes between T1 and T2 (Kruskal-Wallis chi-squared = 4.0, df = 1, p-value = 0.044) reflecting both the impact of treatment, possible antigen selection, and/or the disappearance of the chronic antigen in the form of the malignant plasma cells. Patients that failed to achieve MRD negativity at T2 had significantly more clonotypes suggesting an ineffective T-cell response to residual tumor. Diversity analysis is currently ongoing. Conclusion: In this multilayered analysis we show changes that the composition of the microenvironment is related to the level of response in the context of DKRd treatment. Fc-mediated antibody effector function and inflammation resolution are associated with sustained MRD negativity phenotypes response suggesting a significant contribution of the microenvironment to response, opening the way for therapeutic manipulation to enhance response. TCR analysis reveals for the first time that oligoclonal profiles seen on treatment may influence the fitness of the immune response.