ArticleInternational journal of molecular sciences2023
Unravelling the Therapeutic Potential of Antibiotics in Hypoxia in a Breast Cancer MCF-7 Cell Line Model.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed, 5 citations in OpenAlex.
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6 authors at 2 institutions in 2 countries.
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Abstract
Antibiotics inhibit breast cancer stem cells (CSCs) by suppressing mitochondrial biogenesis. However, the effectiveness of antibiotics in clinical settings is inconsistent. This inconsistency raises the question of whether the tumor microenvironment, particularly hypoxia, plays a role in the response to antibiotics. Therefore, the goal of this study was to evaluate the effectiveness of five commonly used antibiotics for inhibiting CSCs under hypoxia using an MCF-7 cell line model. We assessed the number of CSCs through the mammosphere formation assay and aldehyde dehydrogenase (ALDH)-bright cell count. Additionally, we examined the impact of antibiotics on the mitochondrial stress response and membrane potential. Furthermore, we analyzed the levels of proteins associated with therapeutic resistance. There was no significant difference in the number of CSCs between cells cultured under normoxic and hypoxic conditions. However, hypoxia did affect the rate of CSC inhibition by antibiotics. Specifically, azithromycin was unable to inhibit sphere formation in hypoxia. Erythromycin and doxycycline did not reduce the ratio of ALDH-bright cells, despite decreasing the number of mammospheres. Furthermore, treatment with chloramphenicol, doxycycline, and tetracycline led to the overexpression of the breast cancer resistance protein. Our findings suggest that hypoxia may weaken the inhibitory effects of antibiotics on the breast cancer model.
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