Diagnostic deep‐targeted next‐generation sequencing assessment of <i>TP53</i> gene mutations in multiple myeloma from the whole bone marrow

Petráčková, Anna; Minařík, Jiří; Sedlaříková, Lenka; Libigerova, Tereza; Hamplova, Alzbeta; Krhovská, Petra; Balcárková, Jana; Pika, Tomáš; Papajík, Tomáš; Kriegová, Eva

doi:10.1111/bjh.16547

Cited by 6 publications

(5 citation statements)

References 15 publications

(17 reference statements)

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“…The infiltration of myeloma cells in BM aspirates based on immunophenotyping was highly variable in enrolled patients (3–36%); more than 10% infiltration of plasma cells was found in the BM smears of all enrolled patients. The inter-individual variability in the myeloma cell infiltration may be linked to patchy or site-varied myeloma cell distribution, haemodilution, aspirate pull order, the aggregation of myeloma cells in aspirated BM, myeloma cell immunophenotypes and time-dependent losses of surface markers 23 , as well as disease heterogeneity itself 27 . The infiltration of myeloma cells in all samples after enrichment was > 80% (81–96%).…”

Section: Resultsmentioning

confidence: 99%

“…The full coding sequence of the TP53 gene (exons 2–11, plus 5′ and 3′UTR; NM_000546) and the hotspot regions in NRAS (exons 2–4; NM_002524), KRAS (exons 2–4; NM_004985) and BRAF (exons 11 and 15; NM_004333) were analysed by targeted, ultra-deep NGS, as reported previously 23 , 24 . Amplicon-based libraries were sequenced as paired ends on MiSeq (2 × 151 bp, Illumina, CA, USA), with a minimum target read depth of 5000×.…”

Section: Methodsmentioning

confidence: 99%

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Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

Kriegová

Fillerová

Minařík

et al. 2021

Sci Rep

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Extramedullary disease (EMM) represents a rare, aggressive and mostly resistant phenotype of multiple myeloma (MM). EMM is frequently associated with high-risk cytogenetics, but their complex genomic architecture is largely unexplored. We used whole-genome optical mapping (Saphyr, Bionano Genomics) to analyse the genomic architecture of CD138+ cells isolated from bone-marrow aspirates from an unselected cohort of newly diagnosed patients with EMM (n = 4) and intramedullary MM (n = 7). Large intrachromosomal rearrangements (> 5 Mbp) within chromosome 1 were detected in all EMM samples. These rearrangements, predominantly deletions with/without inversions, encompassed hundreds of genes and led to changes in the gene copy number on large regions of chromosome 1. Compared with intramedullary MM, EMM was characterised by more deletions (size range of 500 bp–50 kbp) and fewer interchromosomal translocations, and two EMM samples had copy number loss in the 17p13 region. Widespread genomic heterogeneity and novel aberrations in the high-risk IGH/IGK/IGL, 8q24 and 13q14 regions were detected in individual patients but were not specific to EMM/MM. Our pilot study revealed an association of chromosome 1 abnormalities in bone marrow myeloma cells with extramedullary progression. Optical mapping showed the potential for refining the complex genomic architecture in MM and its phenotypes.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

Kriegová

Fillerová

Minařík

et al. 2021

Sci Rep

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“…When combined with HIF it leads to mitochondrial impairment. P53 is a tumor suppressor and the deletion or mutation of the TP53 gene is considered as one of the most important negative prognostic factors in MM [ 77 ]. P53 is among the key regulators of cancer metabolism [ 78 , 79 , 80 ].…”

Section: The Transcription Factors Hif-1α C-myc and P53mentioning

confidence: 99%

Metabolic Disorders in Multiple Myeloma

Gavriatopoulou

Paschou

Ntanasis‐Stathopoulos

et al. 2021

IJMS

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Multiple myeloma (MM) is the second most common hematological malignancy and is attributed to monoclonal proliferation of plasma cells in the bone marrow. Cancer cells including myeloma cells deregulate metabolic pathways to ensure proliferation, growth, survival and avoid immune surveillance, with glycolysis and glutaminolysis being the most identified procedures involved. These disorders are considered a hallmark of cancer and the alterations performed ensure that enough energy is available for rapid cell proliferation. An association between metabolic syndrome, inflammatory cytokinesand incidence of MM has been also described, while the use of metformin and statins has been identified as a positive prognostic factor for the disease course. In this review, we aim to present the metabolic disorders that occur in multiple myeloma, the potential defects on the immune system and the potential advantage of targeting the dysregulated pathways in order to enhance antitumor therapeutics.

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“…At the same time, c-Myc regulates cancer cell glutamine metabolism by inducing the expression of ASCT2 and GLS1 ( 223 ). The tumor suppressor P53 is mutated in most cancer types, including MM, and its mutational status serves as a robust negative prognostic marker in myeloma ( 234 ). P53 suppresses glycolysis and thus favors OXPHOS via downregulation of GLUT1/4, and at the same time upregulates phosphatase and tensin homolog (PTEN), a tumor suppressor gene, which inhibits the PI3K-Akt pathway.…”

Section: Metabolomic Reprogramming Of MM Within the Tmementioning

confidence: 99%

Contribution of the Tumor Microenvironment to Metabolic Changes Triggering Resistance of Multiple Myeloma to Proteasome Inhibitors

Schwestermann

Bešše

2022

Front. Oncol.

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Virtually all patients with multiple myeloma become unresponsive to treatment with proteasome inhibitors over time. Relapsed/refractory multiple myeloma is accompanied by the clonal evolution of myeloma cells with heterogeneous genomic aberrations, diverse proteomic and metabolic alterations, and profound changes of the bone marrow microenvironment. However, the molecular mechanisms that drive resistance to proteasome inhibitors within the context of the bone marrow microenvironment remain elusive. In this review article, we summarize the latest knowledge about the complex interaction of malignant plasma cells with its surrounding microenvironment. We discuss the pivotal role of metabolic reprograming of malignant plasma cells within the tumor microenvironment with a subsequent focus on metabolic rewiring in plasma cells upon treatment with proteasome inhibitors, driving multiple ways of adaptation to the treatment. At the same time, mutual interaction of plasma cells with the surrounding tumor microenvironment drives multiple metabolic alterations in the bone marrow. This provides a tumor-promoting environment, but at the same time may offer novel therapeutic options for the treatment of relapsed/refractory myeloma patients.

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Diagnostic deep‐targeted next‐generation sequencing assessment of TP53 gene mutations in multiple myeloma from the whole bone marrow

Cited by 6 publications

References 15 publications

Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

Metabolic Disorders in Multiple Myeloma

Contribution of the Tumor Microenvironment to Metabolic Changes Triggering Resistance of Multiple Myeloma to Proteasome Inhibitors

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