Dataset Information

Raman Spectroscopic Stratification of Multiple Myeloma Patients Based on Exosome Profiling.

ABSTRACT: Multiple myeloma (MM) is a hematological malignancy characterized by abnormal plasma cell proliferation within the bone marrow which leads to progressive bone marrow failure, skeletal osteolytic lesions, and renal insufficiency, thus severely affecting the quality of life. MM is always preceded by monoclonal gammopathy of uncertain significance (MGUS), which progresses to asymptomatic-MM (aMM) or symptomatic-MM (sMM) at a rate of 1% per year. Despite impressive progress in the therapy of the disease, MM remains incurable. Based on these premises, the identification of biomarkers of MGUS progression to MM is a crucial issue in disease management. In this regard, exosomes (EXs) and their precious biomolecular cargo could play a pivotal role in MM detection, stratification, and follow-up. Raman spectroscopy, a label- and manipulation-free technique, and its enhanced version, surface-enhanced Raman spectroscopy (SERS), have been used for characterizing MGUS, aMM, and sMM patient-derived EXs. Here, we have demonstrated the capability of Raman spectroscopy for discriminating EXs along the progression from MGUS to aMM and sMM, thus providing useful clinical indications for patient care. The used SERS devices, based on random nanostructures, have shown good potential in terms of sensitivity, but further developments are needed for achieving reproducible and quantitative SERS results.

SUBMITTER: Russo M

PROVIDER: S-EPMC7711702 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Raman Spectroscopic Stratification of Multiple Myeloma Patients Based on Exosome Profiling.

Russo Mario M Tirinato Luca L Scionti Francesca F Coluccio Maria Laura ML Perozziello Gerardo G Riillo Caterina C Mollace Vincenzo V Gratteri Santo S Malara Natalia N Di Martino Maria Teresa MT Viglietto Giuseppe G Tagliaferri Pierosandro P Tassone Pierfrancesco P Rossi Marco M Candeloro Patrizio P

ACS omega 20201118 47

Multiple myeloma (MM) is a hematological malignancy characterized by abnormal plasma cell proliferation within the bone marrow which leads to progressive bone marrow failure, skeletal osteolytic lesions, and renal insufficiency, thus severely affecting the quality of life. MM is always preceded by monoclonal gammopathy of uncertain significance (MGUS), which progresses to asymptomatic-MM (aMM) or symptomatic-MM (sMM) at a rate of 1% per year. Despite impressive progress in the therapy of the dis ...[more]

PMID: 33283091

Similar Datasets

Project description:Background: Multiple myeloma (MM) is characterized by abnormal proliferation of bone marrow clonal plasma cells. Tumor immunotherapy, a new therapy that has emerged in recent years, offers hope to patients, and studying the expression characteristics of immune-related genes (IRGs) based on whole bone marrow gene expression profiling (GEP) in MM patients can help guide personalized immunotherapy. Methods: In this study, we explored the potential prognostic value of IRGs in MM by combining GEP and clinical data from the GEO database. We identified hub IRGs and transcription factors (TFs) associated with disease progression by Weighted Gene Co-expression Network Analysis (WGCNA), and modeled immune-related prognostic signature by univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the prognostic ability of signature was verified by multiple statistical methods. Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. We mapped the hub IRGs by protein-protein interaction network (PPI) and extracted the top 10 ranked genes. Finally, we conducted vitro assays on two alternative IRGs. Results: Our study identified a total of 14 TFs and 88 IRGs associated with International Staging System (ISS). Ten IRGs were identified by Cox -LASSO regression analysis, and used to develop optimal prognostic signature for overall survival (OS) in MM patients. The 10-IRGs were BDNF, CETP, CD70, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B and SEMA4. In different groups, risk signatures showed excellent survival prediction ability, and MM patients also could be stratified at survival risk. In addition, IRF7 and SHC1 were hub IRGs in PPI network, and the vitro assays proved that they could promote tumor progression. Notably, ssGSEA and GSEA results confirmed that different risk groups could accurately indicate the status of tumor microenvironment (TME) and activation of biological pathways. Conclusion: Our study suggested that immune-related signature could be used as prognostic markers in MM patients.

Dataset Information

Raman Spectroscopic Stratification of Multiple Myeloma Patients Based on Exosome Profiling.

Publications

Raman Spectroscopic Stratification of Multiple Myeloma Patients Based on Exosome Profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets