Effect of Exogenous pH on Cell Growth of Breast Cancer Cells.
Sung Mun LeeAya ShantiPublished in: International journal of molecular sciences (2021)
Breast cancer is the most common type of cancer in women and the most life-threatening cancer in females worldwide. One key feature of cancer cells, including breast cancer cells, is a reversed pH gradient which causes the extracellular pH of cancer cells to be more acidic than that of normal cells. Growing literature suggests that alkaline therapy could reverse the pH gradient back to normal and treat the cancer; however, evidence remains inconclusive. In this study, we investigated how different exogenous pH levels affected the growth, survival, intracellular reactive oxygen species (ROS) levels and cell cycle of triple-negative breast cancer cells from MDA-MB-231 cancer cell lines. Our results demonstrated that extreme acidic conditions (pH 6.0) and moderate to extreme basic conditions (pH 8.4 and pH 9.2) retarded cellular growth, induced cell death via necrosis and apoptosis, increased ROS levels, and shifted the cell cycle away from the G0/G1 phase. However, slightly acidic conditions (pH 6.7) increased cellular growth, decreased ROS levels, did not cause significant cell death and shifted the cell cycle from the G0/G1 phase to the G2/M phase, thereby explaining why cancer cells favored acidic conditions over neutral ones. Interestingly, our results also showed that cellular pH history did not significantly affect the subsequent growth of cells when the pH of the medium was changed. Based on these results, we suggest that controlling or maintaining an unfavorable pH (such as a slightly alkaline pH) for cancer cells in vivo could retard the growth of cancer cells or potentially treat the cancer.
Keyphrases
- cell cycle
- cell death
- cell cycle arrest
- papillary thyroid
- breast cancer cells
- cell proliferation
- squamous cell
- dna damage
- systematic review
- stem cells
- ionic liquid
- squamous cell carcinoma
- bone marrow
- metabolic syndrome
- mesenchymal stem cells
- adipose tissue
- climate change
- deep learning
- endothelial cells
- mass spectrometry
- insulin resistance
- single molecule
- anaerobic digestion
- drug induced