Methods for personalizing medical treatment are the focal point of contemporary biomedical research. In cancer care, we can analyze the effects of therapies at the level of individual cells. Quantitative characterization of treatment efficacy and evaluation of why some individuals respond to specific regimens, whereas others do not, requires additional approaches to genetic sequencing at single time points. Methods for the continuous analysis of changes in phenotype, such as in vivo and ex vivo morphology and motion tracking of cellular proteins and organelles, over time-frames spanning the minute-hour scales, can provide important insights into patient treatment options. Despite improvements in the diagnosis and therapy of many types of breast cancer (BC), many aggressive forms, such as receptor triple-negative cancers, are associated with the worst patient outcomes; though initially effective in reducing tumor burden for some patients, acquired resistance to cytotoxic chemotherapy is almost universal, and there is no rationale for identifying intrinsically drug-resistant and drug-sensitive patient populations before initiating therapy. During cell division, the receptor triple-negative MDA-MB-231 mitotic spindles are the largest in comparison to other BC cell lines. Many of the MDA-MB-231 spindles exhibit rapid lateral twisting during metaphase, which remains unaffected by knockdown of the oncogene Myc and treatment with inhibitors of the serine/threonine-protein kinase B-Raf and the epidermal growth factor receptor (EGFR), alone or in any combination. In this manuscript, we outline a strategy for the selection of the most optimal tubulin inhibitor based on the ability to affect MT dynamics.
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Alexandre Matov (2024) studied this question.
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