Expression of NK cell surface receptors in breast cancer tissue as predictors of resistance to antineoplastic treatment

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Abstract

Background: Currently, one of the most used strategies for the treatment of newly diagnosed patients with breast cancer is neoadjuvant chemotherapy based on the application of taxanes and anthracyclines. However, despite the high number of patients who develop a complete pathological clinical response, resistance and relapse following this therapy continue to be a clinical challenge. As a component of the innate immune system, the cytotoxic function of Natural Killer (NK) cells plays an important role in the elimination of tumor cells. However, the role of NK cells in resistance to systemic therapy in breast cancer remains unclear. The present project aims to evaluate the gene expression profile of human NK cells in breast cancer tissue resistant to treatment with taxanes–anthracyclines. Methods: Biopsies from tumor tissues were obtained from patients with breast cancer without prior treatment. Histopathological analysis and ex vivo exposure to antineoplastic chemotherapeutics were carried out. Alamar blue and lactate dehydrogenase release assays were performed for quantitative analysis of tumor viability. Gene expression profiles from tumor tissues without prior exposure to therapeutic drugs were analyzed by gene expression microarrays and verified by polymerase chain reaction. Results: A significant decrease in gene expression of cell-surface receptors related to NK cells was observed in tumor samples resistant to antineoplastic treatment compared with those that were sensitive to treatment. Conclusion: A decrease in NK cell infiltration into tumor tissue might be a predictive marker for failure of chemotherapeutic treatment in breast cancer.

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Mariel, G. C., Edith, C. T. I., Pilar, C. R., Elena, G. D. N., Humberto, R. M., Guadalupe, M. S. M., … Felipe, J. S. L. (2018). Expression of NK cell surface receptors in breast cancer tissue as predictors of resistance to antineoplastic treatment. Technology in Cancer Research and Treatment, 17. https://doi.org/10.1177/1533033818764499

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