title: Multiple myeloma: is it time for biomarker-driven therapy?
abstract: Remarkable strides have been made in understanding the molecular mechanisms by which multiple myeloma develops, leading to more sophisticated classification that incorporates not only the traditional diagnostic criteria, but also immunophenotype, genetic, and molecular features. However, even with this added information, considerable heterogeneity in clinical outcomes exists within the identified subtypes. The present paradigm for myeloma treatment is built on the basic step of defining transplant eligibility versus noneligibility, as determined by age, performance status, and cumulative burden of comorbidities. An incredibly complex heterogeneous disease is, therefore, treated in a generalized way with the result that large interpatient variability exists in the outcome. As antimyeloma therapeutics continue to expand it is becoming even more crucial to personalize treatment approaches that provide the most value to a specific patient. Development of biomarkers, either individually or as larger sets or patterns and ranging from analysis of blood or bone marrow to biomedical imaging, is a major focus in the field. Biomarkers such as involved serum free light chain ratio and MRI focal lesions have been implemented in the new definition of multiple myeloma and guide clinicians to initiate treatment in otherwise asymptomatic individuals. Currently, however, there is not enough evidence to support intensifying the treatment for high-risk disease or reducing the treatment for low-risk disease. Minimal residual disease-negative status is an important biomarker that holds promise for monitoring the effectiveness of response-adapted strategies. This article sheds light on the forward landscape and rear-mirror view of biomarkers in myeloma.
authors.affiliation: From the Department of Hematologic Oncology & Blood Disorders, Levine Cancer Institute/Carolinas Healthcare System, Charlotte, NC; Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
authors.forename: Manisha
authors.initials: M
authors.lastname: Bhutani
authors.affiliation: From the Department of Hematologic Oncology & Blood Disorders, Levine Cancer Institute/Carolinas Healthcare System, Charlotte, NC; Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
authors.forename: Ola
authors.initials: O
authors.lastname: Landgren
authors.affiliation: From the Department of Hematologic Oncology & Blood Disorders, Levine Cancer Institute/Carolinas Healthcare System, Charlotte, NC; Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
authors.forename: Saad Z
authors.initials: SZ
authors.lastname: Usmani
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D016723:Bone Remodeling / Q000502:physiology; D002986:Clinical Trials as Topic; D003582:Cytogenetics / Q000379:methods; D018450:Disease Progression; D044127:Epigenesis, Genetic / Q000235:genetics; D005434:Flow Cytometry / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods; D005819:Genetic Markers; D006801:Humans; D017404:In Situ Hybridization, Fluorescence / Q000379:methods; D009101:Multiple Myeloma / Q000175:diagnosis / Q000628:therapy*; D009194:Myeloma Proteins / Q000378:metabolism; D009367:Neoplasm Staging; D018365:Neoplasm, Residual / Q000175:diagnosis; D049268:Positron-Emission Tomography / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers; D009194:Myeloma Proteins