Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
Dis Model Mech ; 14(7)2021 07 01.
Article in English | MEDLINE | ID: mdl-33988237

ABSTRACT

Extramedullary multiple myeloma (EMM) has an overall survival of 6 months and occurs in 20% of multiple myeloma (MM) patients. Genetic and epigenetic mechanisms involved in EMM and the therapeutic role of new agents for MM are not well established. Besides, well-characterized preclinical models for EMM are not available. Herein, a patient-derived orthotopic xenograft (PDOX) was generated from a patient with an aggressive EMM to study in-depth genetic and epigenetic events, and drug responses related to extramedullary disease. A fresh punch of an extramedullary cutaneous lesion was orthotopically implanted in NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ(NSG) mouse. The PDOX mimicked histologic and phenotypic features of the tumor of the patient. Cytogenetic studies revealed a hyperploid genome with multiple genetic poor-prognosis alterations. Copy number alterations (CNAs) were detected in all chromosomes. The IGH translocation t(14;16)(q32;q23)IGH/MAF was already observed at the medullary stage and a new one, t(10;14)(p?11-12;q32), was observed only with extramedullary disease and could be eventually related to EMM progression in this case. Exome sequencing showed 24 high impact single nucleotide variants and 180 indels. From the genes involved, only TP53 was previously described as a driver in MM. A rather balanced proportion of hyper/hypomethylated sites different to previously reported widespread hypomethylation in MM was also observed. Treatment with lenalidomide, dexamethasone and carfilzomib showed a tumor weight reduction of 90% versus non-treated tumors, whereas treatment with the anti-CD38 antibody daratumumab showed a reduction of 46%. The generation of PDOX from a small EMM biopsy allowed us to investigate in depth the molecular events associated with extramedullary disease in combination with drug testing.


Subject(s)
Multiple Myeloma , Animals , Disease Models, Animal , Heterografts , Humans , Mice , Mice, Inbred NOD , Multiple Myeloma/drug therapy , Multiple Myeloma/genetics , Multiple Myeloma/pathology
2.
Breast Cancer Res Treat ; 132(3): 979-92, 2012 Apr.
Article in English | MEDLINE | ID: mdl-21735045

ABSTRACT

Comprehensive genetic testing of the breast cancer susceptibility genes BRCA1 and BRCA2 identified approximately 16% of variants of unknown significance (VUS), a significant proportion of which could affect the correct splicing of the genes. Our aim is to establish a workflow for classifying VUS in these complex genes, the first stage of which is splicing analysis. We used a combined approach consisting of five in silico splicing prediction programs and RT-PCR analysis for a set of 26 variants not previously studied at the mRNA level and six variants that had already been studied, four of which were used as positive controls as they were found to affect the splicing of these genes and the other two were used as negative controls. We identified a splicing defect in 8 of the 26 newly studied variants and ruled out splicing alteration in the remaining 18 variants. The results for the four positive and the two negative control variants were consistent with results presented in the literature. Our results strongly suggest that the combination of RNA analysis and in silico programs is an important step towards the classification of VUS. The results revealed a very high correlation between experimental data and in silico programs when using tools for predicting acceptor/donor sites but a lower correlation in the case of tools for identifying ESE elements.


Subject(s)
BRCA1 Protein/genetics , BRCA2 Protein/genetics , Hereditary Breast and Ovarian Cancer Syndrome/genetics , RNA, Messenger/genetics , Alternative Splicing , BRCA1 Protein/metabolism , BRCA2 Protein/metabolism , Base Sequence , Computer Simulation , Female , Genetic Predisposition to Disease , Humans , Models, Genetic , Molecular Sequence Data , Mutation , Protein Isoforms/genetics , Protein Isoforms/metabolism , RNA, Messenger/metabolism , Sequence Analysis, RNA
SELECTION OF CITATIONS
SEARCH DETAIL
...