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Myeloma cell dynamics in response to Treatment supports a model of hierarchical differentiation and clonal evolution

AutorTang, Min; Zhao, Rui; Velde, Helgi van de; Tross, Jennifer G.; Mitsiades, C. S.; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M.; San Miguel, Jesús F. ; Richardson, Paul G.; Tomasson, Michael H.; Michor, Franziska
Fecha de publicación2016
EditorAmerican Association for Cancer Research
CitaciónClinical Cancer Research 22(16): 4206-4214 (2016)
Resumen[Purpose]: Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. [Experimental Design]: We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. [Results]: Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, >progenitor cells> and >differentiated cells.> Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporatingboth a differentiation hierarchy and clonal evolution best explains the response patterns. [Conclusions]: The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens.
Versión del editorhttps://doi.org/10.1158/1078-0432.CCR-15-2793
Identificadoresdoi: 10.1158/1078-0432.CCR-15-2793
e-issn: 1557-3265
issn: 1078-0432
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