4 research outputs found

    Beyond the marrow:insights from comprehensive next-generation sequencing of extramedullary multiple myeloma tumors

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    Extramedullary multiple myeloma (EMM) is an aggressive form of multiple myeloma (MM). This study represents the most comprehensive next-generation sequencing analysis of EMM tumors (N = 14) to date, uncovering key molecular features and describing the tumor microenvironment. We observed the co-occurrence of 1q21 gain/amplification and MAPK pathway mutations in 79% of EMM samples, suggesting that these are crucial mutational events in EMM development. We also demonstrated that patients with mutated KRAS and 1q21 gain/amplification at the time of diagnosis have a significantly higher risk of EMM development (HR = 2.4, p = 0.011) using data from a large CoMMpass dataset. We identified downregulation of CXCR4 and enhanced cell proliferation, along with reduced expression of therapeutic targets (CD38, SLAMF7, GPRC5D, FCRH5), potentially explaining diminished efficacy of immunotherapy. Conversely, we identified significantly upregulated EZH2 and CD70 as potential future therapeutic options. For the first time, we report on the tumor microenvironment of EMM, revealing CD8+ T cells and NK cells as predominant immune effector cells using single-cell sequencing. Finally, this is the first longitudinal study in EMM revealing the molecular changes from the time of diagnosis to EMM relapse.</p

    PhyloFisher : A phylogenomic package for resolving eukaryotic relationships

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    Phylogenomic analyses of hundreds of protein-coding genes aimed at resolving phylogenetic relationships is now a common practice. However, no software currently exists that includes tools for dataset construction and subsequent analysis with diverse validation strategies to assess robustness. Furthermore, there are no publicly available high-quality curated databases designed to assess deep (&gt;100 million years) relationships in the tree of eukaryotes. To address these issues, we developed an easy-to-use software package, PhyloFisher (https://github.com/TheBrownLab/PhyloFisher), written in Python 3. PhyloFisher includes a manually curated database of 240 protein-coding genes from 304 eukaryotic taxa covering known eukaryotic diversity, a novel tool for ortholog selection, and utilities that will perform diverse analyses required by state-of-the-art phylogenomic investigations. Through phylogenetic reconstructions of the tree of eukaryotes and of the Saccharomycetaceae clade of budding yeasts, we demonstrate the utility of the PhyloFisher workflow and the provided starting database to address phylogenetic questions across a large range of evolutionary time points for diverse groups of organisms. We also demonstrate that undetected paralogy can remain in phylogenomic "single-copy orthogroup" datasets constructed using widely accepted methods such as all vs. all BLAST searches followed by Markov Cluster Algorithm (MCL) clustering and application of automated tree pruning algorithms. Finally, we show how the PhyloFisher workflow helps detect inadvertent paralog inclusions, allowing the user to make more informed decisions regarding orthology assignments, leading to a more accurate final dataset

    The Oxymonad Genome Displays Canonical Eukaryotic Complexity in the Absence of a Mitochondrion

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    The discovery that the protist Monocercomonoides exilis completely lacks mitochondria demonstrates that these organelles are not absolutely essential to eukaryotic cells. However, the degree to which the metabolism and cellular systems of this organism have adapted to the loss of mitochondria is unknown. Here, we report an extensive analysis of the M. exilis genome to address this question. Unexpectedly, we find that M. exilis genome structure and content is similar in complexity to other eukaryotes and less "reduced" than genomes of some other protists from the Metamonada group to which it belongs. Furthermore, the predicted cytoskeletal systems, the organization of endomembrane systems, and biosynthetic pathways also display canonical eukaryotic complexity. The only apparent preadaptation that permitted the loss of mitochondria was the acquisition of the SUF system for Fe-S cluster assembly and the loss of glycine cleavage system. Changes in other systems, including in amino acid metabolism and oxidative stress response, were coincident with the loss of mitochondria but are likely adaptations to the microaerophilic and endobiotic niche rather than the mitochondrial loss per se. Apart from the lack of mitochondria and peroxisomes, we show that M. exilis is a fully elaborated eukaryotic cell that is a promising model system in which eukaryotic cell biology can be investigated in the absence of mitochondria

    More than 2% of circulating tumor plasma cells defines plasma cell leukemia-like multiple myeloma

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    PURPOSEPrimary plasma cell leukemia (PCL) is the most aggressive monoclonal gammopathy. It was formerly characterized by >= 20% circulating plasma cells (CTCs) until 2021, when this threshold was decreased to >= 5%. We hypothesized that primary PCL is not a separate clinical entity, but rather that it represents ultra-high-risk multiple myeloma (MM) characterized by elevated CTC levels.METHODSWe assessed the levels of CTCs by multiparameter flow cytometry in 395 patients with newly diagnosed transplant-ineligible MM to establish a cutoff for CTCs that identifies the patients with ultra-high-risk PCL-like MM. We tested the cutoff on 185 transplant-eligible patients with MM and further validated on an independent cohort of 280 transplant-ineligible patients treated in the GEM-CLARIDEX trial. The largest published real-world cohort of patients with primary PCL was used for comparison of survival. Finally, we challenged the current 5% threshold for primary PCL diagnosis.RESULTSNewly diagnosed transplant-ineligible patients with MM with 2%-20% CTCs had significantly shorter progression-free survival (3.1 v 15.6 months; P = 2% CTCs is a biomarker of hidden primary PCL and supports the assessment of CTCs by flow cytometry during the diagnostic workup of MM
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