576 research outputs found

    Germline Risk Contribution to Genomic Instability in Multiple Myeloma

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    Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) – a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME

    The Incidence of Senile Cataract and Glaucoma is Increased in Patients with Plasma Cell Dyscrasias : Etiologic Implications

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    Plasma cell dyscrasias, including monoclonal gammopathy of undetermined significance (MGUS), multiple myeloma (MM), Waldenstrom macroglobulinemia (WM) and light chain AL amyloidosis, are characterized by clonal expansion of plasma cells which produce a vast amount of an immunoglobulin-derived M-protein. We noted that MGUS diagnosis often coincided with diagnoses of senile cataract and glaucoma and tested the associations of MGUS, MM, WM and AL amyloidosis with subsequent eye diseases identified from the Swedish patient registers between 1997 and 2012. Standardized incidence ratios (SIRs) for senile cataract was significantly increased to 1.80 after MGUS, 1.70 after MM, 1.85 after WM and 2.31 after AL amyloidosis. The SIR for glaucoma was 1.60 after MGUS, 1.76 after WM and 2.18 after AL amyloidosis. All SIRs decreased systematically from age below 60 years to over 79 years, but most risks were also significant in age group over 79 years. The M-protein and the related increase in blood viscosity could be a novel etiologic discovery for these common eye diseases. As MGUS prevalence is around 3% at 60 years and close to 10% at age over 80 years, its contribution to the eye disease burden is expected to be remarkably high.Peer reviewe

    Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

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    Purpose: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. Materials and methods: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1–6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian 7 1.1 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 2: liver SUVmedian 7 1.5 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 3: liver SUVmedian 7 2 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. Results: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of β2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. Conclusions: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts

    Enrichment of B cell receptor signaling and epidermal growth factor receptor pathways in monoclonal gammopathy of undetermined significance: a genome-wide genetic interaction study

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    Background: Recent identification of 10 germline variants predisposing to monoclonal gammopathy of undetermined significance (MGUS) explicates genetic dependency of this asymptomatic precursor condition with multiple myeloma (MM). Yet much of genetic burden as well as functional links remain unexplained. We propose a workflow to expand the search for susceptibility loci with genome-wide interaction and for subsequent identification of genetic clusters and pathways. Methods: Polygenic interaction analysis on 243 cases/1285 controls identified 14 paired risk loci belonging to unique chromosomal bands which were then replicated in two independent sets (case only study, 82 individuals; case/control study 236 cases/ 2484 controls). Further investigation on gene-set enrichment, regulatory pathway and genetic network was carried out with stand-alone in silico tools separately for both interaction and genome-wide association study-detected risk loci. Results: Intronic-PREX1 (20q13.13), a reported locus predisposing to MM was confirmed to have contribution to excess MGUS risk in interaction with SETBP1, a well-established candidate predisposing to myeloid malignancies. Pathway enrichment showed B cell receptor signaling pathway (P < 5.3 × 10− 3) downstream to allograft rejection pathway (P < 5.6 × 10− 4) and autoimmune thyroid disease pathway (P < 9.3 × 10− 4) as well as epidermal growth factor receptor regulation pathway (P < 2.4 × 10− 2) to be differentially regulated. Oncogene ALK and CDH2 were also identified to be moderately interacting with rs10251201 and rs16966921, two previously reported risk loci for MGUS. Conclusions: We described novel pathways and variants potentially causal for MGUS. The methodology thus proposed to facilitate our search streamlines risk locus-based interaction, genetic network and pathway enrichment analyses

    Analyzing Longitudinal wb-MRI Data and Clinical Course in a Cohort of Former Smoldering Multiple Myeloma Patients: Connections between MRI Findings and Clinical Progression Patterns

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    The purpose of this study was to analyze size and growth dynamics of focal lesions (FL) as well as to quantify diffuse infiltration (DI) in untreated smoldering multiple myeloma (SMM) patients and correlate those MRI features with timepoint and cause of progression. We investigated 199 whole-body magnetic resonance imaging (wb-MRI) scans originating from longitudinal imaging of 60 SMM patients and 39 computed tomography (CT) scans for corresponding osteolytic lesions (OL) in 17 patients. All FLs >5 mm were manually segmented to quantify volume and growth dynamics, and DI was scored, rating four compartments separately in T1- and fat-saturated T2-weighted images. The majority of patients with at least two FLs showed substantial spatial heterogeneity in growth dynamics. The volume of the largest FL (p = 0.001, c-index 0.72), the speed of growth of the fastest growing FL (p = 0.003, c-index 0.75), the DI score (DIS, p = 0.014, c-index 0.67), and its dynamic over time (DIS dynamic, p < 0.001, c-index 0.67) all significantly correlated with the time to progression. Size and growth dynamics of FLs correlated significantly with presence/appearance of OL in CT within 2 years after the respective MRI assessment (p = 0.016 and p = 0.022). DIS correlated with decrease of hemoglobin (p < 0.001). In conclusion, size and growth dynamics of FLs correlate with prognosis and local bone destruction. Connections between MRI findings and progression patterns (fast growing FL—OL; DIS—hemoglobin decrease) might enable more precise diagnostic and therapeutic approaches for SMM patients in the future

    Characterization of rare germline variants in familial multiple myeloma

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    Multiple myeloma (MM) is a malignancy of plasma cells, characterized by the presence of monoclonal immunoglobulin, known as M protein1. MM is preceded by monoclonal gammopathy of undetermined significance (MGUS) which is also a precursor of immunoglobulin light chain (AL) amyloidosis. Previous studies have reported a 2- to 4-fold increased risk of MGUS or MM in first-degree relatives of MM or MGUS patients, suggesting the existence of inherited susceptibility. For many years, high-risk germline predisposing genes have been lacking for MM. However, recent sequencing efforts have proposed a few novel candidates, most notably loss-offunction (LoF) variants in the tumor suppressor gene DIS3 and in the histone demethylase gene KDM1A, and others as recently reviewed in detail in Pertesi et al. In addition to the suspected rare, high-penetrance variants, genome-wide association studies have identified over 20 common, low-penetrance variants associated with the risk of MM; these were estimated to account for about 15% of the familial MM risk

    Adjusted Comparison of Outcomes between Patients from CARTITUDE-1 versus Multiple Myeloma Patients with Prior Exposure to PI, Imid and Anti-CD-38 from a German Registry

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    Ciltacabtagene autoleucel (cilta-cel) is a Chimeric antigen receptor T-cell therapy with the potential for long-term disease control in heavily pre-treated patients with relapsed/refractory multiple myeloma (RRMM). As cilta-cel was assessed in the single-arm CARTITUDE-1 clinical trial, we used an external cohort of patients from the Therapie Monitor registry fulfilling the CARTITUDE-1 inclusion criteria to evaluate the effectiveness of cilta-cel for overall survival (OS) and time to next treatment (TTNT) vs. real-world clinical practice. Individual patient data allowed us to adjust the comparisons between both cohorts, using the inverse probability of treatment weighting (IPW; average treatment effect in the treated population (ATT) and overlap population (ATO) weights) and multivariable Cox proportional hazards regression. Outcomes were compared in intention-to-treat (HR, IPW-ATT: TTNT: 0.13 (95% CI: 0.07, 0.24); OS: 0.14 (95% CI: 0.07, 0.25); IPW-ATO: TTNT: 0.24 (95% CI: 0.12, 0.49); OS: 0.26 (95% CI: 0.13, 0.54)) and modified intention-to-treat (HR, IPW-ATT: TTNT: 0.24 (95% CI: 0.09, 0.67); OS: 0.26 (95% CI: 0.08, 0.84); IPW-ATO: TTNT: 0.26 (95% CI: 0.11, 0.59); OS: 0.31 (95% CI: 0.12, 0.79)) populations. All the comparisons were statistically significant in favor of cilta-cel. These results highlight cilta-cel’s potential as a novel, effective treatment to address unmet needs in patients with RRMM

    Chemotherapy-induced peripheral neuropathy: evidence from genome-wide association studies and replication within multiple myeloma patients

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    Background: Based on the possible shared mechanisms of chemotherapy-induced peripheral neuropathy (CIPN) for different drugs, we aimed to aggregate results of all previously published genome-wide association studies (GWAS) on CIPN, and to replicate them within a cohort of multiple myeloma (MM) patients. Methods: Following a systematic literature search, data for CIPN associated single nucleotide polymorphisms (SNPs) with P-values&lt; 10− 5 were extracted; these associations were investigated within a cohort of 983 German MM patients treated with bortezomib, thalidomide or vincristine. Cases were subjects that developed CIPN grade 2–4 while controls developed no or sub-clinical CIPN. Logistic regression with additive model was used. Results: In total, 9 GWASs were identified from the literature on CIPN caused by different drugs (4 paclitaxel, 2 bortezomib, 1 vincristine, 1 docetaxel, and 1 oxaliplatin). Data were extracted for 526 SNPs in 109 loci. One hundred fourty-eight patients in our study population were CIPN cases (102/646 bortezomib, 17/63 thalidomide and 29/274 vincristine). In total, 13 SNPs in 9 loci were replicated in our population (p-value&lt; 0.05). The four smallest P-values relevant to the nerve function were 0.0006 for rs8014839 (close to the FBXO33 gene), 0.004 for rs4618330 (close to the INTU gene), 0.006 for rs1903216 (close to the BCL6 gene) and 0.03 for rs4687753 (close to the IL17RB gene). Conclusions: Replicated SNPs provide clues of the molecular mechanism of CIPN and can be strong candidates for further research aiming to predict the risk of CIPN in clinical practice, particularly rs8014839, rs4618330, rs1903216, and rs4687753, which showed relevance to the function of nervous system
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