30 research outputs found

    Low Percentage of Signal Regulatory Protein α/β+ Memory B Cells in Blood Predicts Development of Anti-drug Antibodies (ADA) in Adalimumab-Treated Rheumatoid Arthritis Patients

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    An important goal for personalized treatment is predicting response to a particular therapeutic. A drawback of biological treatment is immunogenicity and the development of antibodies directed against the drug [anti-drug antibodies (ADA)], which are associated with a poorer clinical outcome. Here we set out to identify a predictive biomarker that discriminates rheumatoid arthritis (RA) patients who are more likely to develop ADA in response to adalimumab, a human monoclonal antibody against tumor necrosis factor (TNF)α. By taking advantage of an immune-phenotyping platform, LEGENDScreen™, we measured the expression of 332 cell surface markers on B and T cells in a cross-sectional adalimumab-treated RA patient cohort with a defined ADA response. The analysis revealed seven differentially expressed markers (DEMs) between the ADA+ and ADA− patients. Validation of the DEMs in an independent prospective European cohort of adalimumab treated RA patients, revealed a significant and consistent reduced frequency of signal regulatory protein (SIRP)α/β-expressing memory B cells in ADA+ vs. ADA− RA patients. We also assessed the predictive value of SIRPα/β expression in a longitudinal RA cohort prior to the initiation of adalimumab treatment. We show that a frequency of < 9.4% of SIRPα/β-expressing memory B cells predicts patients that will develop ADA, and consequentially fail to respond to treatment, with a receiver operating characteristic (ROC) area under the curve (AUC) score of 0.92. Thus, measuring the frequency of SIRPα/β-expressing memory B cells in patients prior to adalimumab treatment may be clinically useful to identify a subgroup of active RA subjects who are going to develop an ADA response and not gain substantial clinical benefit from this treatment

    Exome sequencing identifies germline variants in DIS3 in familial multiple myeloma

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    [Excerpt] Multiple myeloma (MM) is the third most common hematological malignancy, after Non-Hodgkin Lymphoma and Leukemia. MM is generally preceded by Monoclonal Gammopathy of Undetermined Significance (MGUS) [1], and epidemiological studies have identified older age, male gender, family history, and MGUS as risk factors for developing MM [2]. The somatic mutational landscape of sporadic MM has been increasingly investigated, aiming to identify recurrent genetic events involved in myelomagenesis. Whole exome and whole genome sequencing studies have shown that MM is a genetically heterogeneous disease that evolves through accumulation of both clonal and subclonal driver mutations [3] and identified recurrently somatically mutated genes, including KRAS, NRAS, FAM46C, TP53, DIS3, BRAF, TRAF3, CYLD, RB1 and PRDM1 [3,4,5]. Despite the fact that family-based studies have provided data consistent with an inherited genetic susceptibility to MM compatible with Mendelian transmission [6], the molecular basis of inherited MM predisposition is only partly understood. Genome-Wide Association (GWAS) studies have identified and validated 23 loci significantly associated with an increased risk of developing MM that explain ~16% of heritability [7] and only a subset of familial cases are thought to have a polygenic background [8]. Recent studies have identified rare germline variants predisposing to MM in KDM1A [9], ARID1A and USP45 [10], and the implementation of next-generation sequencing technology will allow the characterization of more such rare variants. [...]French National Cancer Institute (INCA) and the Fondation Française pour la Recherche contre le Myélome et les Gammapathies (FFMRG), the Intergroupe Francophone du Myélome (IFM), NCI R01 NCI CA167824 and a generous donation from Matthew Bell. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors thank the Association des Malades du Myélome Multiple (AF3M) for their continued support and participation. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organizatio
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