Dataset Information

N-glycosylation of serum proteins for the assessment of patients with IgD multiple myeloma.

ABSTRACT: Because glycosylation is one of the most common post-translational modifications of proteins and because changes in glycosylation have been shown to have a significant correlation with the development of many cancer types, we investigated the serum N-glycome used to diagnose, stage and evaluate the pathological outcomes in IgD multiple myeloma.Serum samples were available for 20 patients with IgD multiple myeloma, 41 patients with light chain multiple myeloma and 42 healthy control subjects. Serum N-glycans were released and analysed using DNA sequencer-assisted fluorophore-assisted capillary electrophoresis.Characteristic changes were revealed in the serum N-glycome of IgD myeloma. In particular, three N-glycans (NG1(6)A2F, Peak3; NG1(3)A2F, Peak4; NA2FB, Peak7) showed increased clinical value. The best area under the ROC curve of NG1(6)A2F to diagnose IgD myeloma was 0.981, with a 95.0% sensitivity and 95.2% specificity, and that of NG1(3)A2F was 0.936, with a 95.0% sensitivity and 78.6% specificity. The best area under the ROC curve of NA2FB/NG1(3)A2F to differentially diagnose IgD myeloma versus light chain myeloma was 0.744, with a 95.3% sensitivity and 50.0% specificity. The level of NG1(3)A2F was correlated with the international staging system, while the higher abundance of NA2FB presented in IgD myeloma was predictive of a shorter progression-free survival.The advent of serum N-glycan signatures may play a role in the diagnosis, staging and prognosis of IgD myeloma and will serve as the foundation for a precision medicine approach to this rare subtype of multiple myeloma.

SUBMITTER: Chen J

PROVIDER: S-EPMC5740902 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

N-glycosylation of serum proteins for the assessment of patients with IgD multiple myeloma.

Chen Jie J Fang Meng M Chen Xiaoling X Yi Changhong C Ji Jun J Cheng Cheng C Wang Mengmeng M Gu Xing X Sun Quansheng Q Gao Chunfang C

BMC cancer 20171221 1

<h4>Background</h4>Because glycosylation is one of the most common post-translational modifications of proteins and because changes in glycosylation have been shown to have a significant correlation with the development of many cancer types, we investigated the serum N-glycome used to diagnose, stage and evaluate the pathological outcomes in IgD multiple myeloma.<h4>Methods</h4>Serum samples were available for 20 patients with IgD multiple myeloma, 41 patients with light chain multiple myeloma a ...[more]

PMID: 29268706

Similar Datasets

Project description:AimsTo evaluate abnormal metabolites related to treatment response and prognosis of multiple myeloma (MM) patients through ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS).MethodsForty-six symptomatic MM patients were included in this study who had a prior high level of positive monoclonal proteins before receiving targeted therapy with bortezomib-based regimens. UPLC-MS along with traditional immunofixation was performed on MM diagnostic samples and effective serum samples, and UPLC-MS was used to target valuable metabolic markers related to M protein.MM patients were segregated into pre-therapy (pre-T) and post-therapy (post-T) groups according to the response after chemotherapy. A monoclonal protein could be detected at baseline in 33 newly diagnosed MM (NDMM), 13 refractory and relapsed MM (RRMM) patients and 20 healthy controls (HC) by immunofixation.ResultsBetween pre-T and post-T patients, the data showed that 32, 28 and 3 different metabolites were significantly correlated with M protein in IgG, IgA and light chain-type MM, respectively. These identified metabolites were significantly enriched in arginine and proline metabolism as well as glycerophospholipid metabolism pathways. Among them, PC (19:0/22:2) was displayed to increase significantly and consistently with M protein in each subtype of MM after treatment, which obviously indicated that it was related to the treatment response of MM. Further survival analysis of metabolic markers found that aspartic acid, LysoPE (16:0), SM (d18:1/17:0), PC (18:0/24:1), PC (16:0/16:0), TG (18:1/18:1/22:5) and LysoPE (18:2) reaching a certain cutoff value may be associated with shorter progression free survival (PFS). Finally, Cox multivariate regression analysis identified three factors were independent prognostic factors of MM. Moreover, there were significantly different in PC (19:0/22:2) and in aspartic acid between MM patients and healthy people.ConclusionThis work identified significant metabolic disorders in 46 pairs off pre- and post-therapy MM patients, specifically in arginine, proline and glycerophospholipid pathways. The abnormal metabolites have the potential to serve as new biomarkers for evaluating treatment response and prognosis, as well as early monitoring of disease activity. Therefore, these systematic studies on abnormal metabolites as biomarkers for diagnosis and treatment will provide the evidence for future precise treatment of MM.

Dataset Information

N-glycosylation of serum proteins for the assessment of patients with IgD multiple myeloma.

Publications

N-glycosylation of serum proteins for the assessment of patients with IgD multiple myeloma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets