Medical College of Wisconsin
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Novel biomarkers in multiple myeloma. Transl Res 2018 11;201:49-59 PMID: 30301522

Pubmed ID

30301522

DOI

10.1016/j.trsl.2018.05.003

Abstract

Significant advancements have been made in the molecular mechanisms of myelomagenesis, diagnostic methods, prognostication, and the treatment options in multiple myeloma (MM) over the last decade. Despite these, MM remains a heterogeneous disease with differing outcomes. As myeloma treatment landscape continues to expand, personalized treatment that provides maximum benefit to a specific patient becomes more important. In the last few years, serum monoclonal proteins including the serum-free light chain assays, imaging, and cytogenetics have been used to predict the outcomes of MM patients receiving different types of therapies. With the development of novel technologies, more sensitive detection of residual disease using flow cytometry and next-generation sequencing has been possible. In addition, liquid biopsies using circulating tumor cells, tumor DNA, and novel immune biomarkers are potentially being investigated. These novel potential biomarkers not only accurately detect the mutational landscape of different cancers compared to standard methods but also serve as prognostic and predictive biomarkers for disease relapse and response to therapy. It is likely that we will be able to offer more targeted and risk-adapted therapeutic approach to patients with MM at different stages of their disease guided by these potential biomarkers.

Author List

Levin A, Hari P, Dhakal B

Authors

Binod Dhakal MD Assistant Professor in the Medicine department at Medical College of Wisconsin
Parameswaran Hari MD Chief, Professor in the Medicine department at Medical College of Wisconsin




Scopus

2-s2.0-85050195259

MESH terms used to index this publication - Major topics in bold

Biomarkers
Circulating Tumor DNA
Flow Cytometry
Genetic Markers
High-Throughput Nucleotide Sequencing
Humans
Multiple Myeloma
Neoplasm Staging
Neoplastic Cells, Circulating
jenkins-FCD Prod-332 f92a19b0ec5e8e1eff783fac390ec127e367c2b5